Landscape Analysis Workshops in Nepal - The Compass€¦ · Landscape Analysis Workshop at the central level. Shreejana Kc conducted the workshops at the provincial and local levels

Landscape Analysis Workshops in Nepal: Brief report of findings | 1

Landscape Analysis

Workshops in Nepal

Summary of findings

Submitted to: USAID Nepal

Submitted by: Johns Hopkins Center for Communication Programs

3 December 2018

Cooperative Agreement #AID-OAA-A-17-00017

Landscape Analysis Workshops in Nepal: Summary of findings | 1

Table of Contents Table of Contents .......................................................................................................................................... 1

Figures and Tables ........................................................................................................................................ 3

Acronym List ................................................................................................................................................. 6

Acknowledgements ....................................................................................................................................... 8

Executive summary ....................................................................................................................................... 9

Introduction .............................................................................................................................................. 9

Mapping process ................................................................................................................................... 9

Results ..................................................................................................................................................... 10

Who influences local-level SBC for health in Nepal? .......................................................................... 10

Who influences how data on health is used in SBC programs? .......................................................... 11

Conclusion ............................................................................................................................................... 12

Introduction ................................................................................................................................................ 14

Mapping Process ..................................................................................................................................... 15

Overview of report .................................................................................................................................. 16

Who influences local-level SBC for health in Nepal? .................................................................................. 18

Central level: Group #1 ........................................................................................................................... 18

Actors .................................................................................................................................................. 18

Linkages ............................................................................................................................................... 19

Influence and connections .................................................................................................................. 19

Social network analysis metrics: Closeness and Betweenness ........................................................... 20

Central level: Group #2 ........................................................................................................................... 20

Actors .................................................................................................................................................. 21

Linkages ............................................................................................................................................... 21


Social network analysis metrics: Closenss and Betweenness ............................................................. 23

Provincial level ........................................................................................................................................ 23

Actors .................................................................................................................................................. 23

Linkages ............................................................................................................................................... 24




Local level ................................................................................................................................................ 25

Jumla: ChandanNath Urban Municipality ........................................................................................... 25

Jumla: GuthiChaur Rural Municipality ................................................................................................ 28

Surkhet: Panchapuri Urban Municipality ............................................................................................ 31

Surkhet: Barahtal Rural Municipality .................................................................................................. 33

Summary of actors and types of linkages across maps .......................................................................... 36

Cross-cutting themes across maps ......................................................................................................... 37

Who influences how data on health is used in SBC programs? .................................................................. 39

Central level ............................................................................................................................................ 39

Actors .................................................................................................................................................. 39

Linkages ............................................................................................................................................... 40



Provincial level ........................................................................................................................................ 41

Actors .................................................................................................................................................. 42

Linkages ............................................................................................................................................... 42



Local level ................................................................................................................................................ 44

Jumla: ChandanNath Urban Municipality ........................................................................................... 44

Jumla: GuthiChaur Rural Municipality ................................................................................................ 47

Surkhet: Panchapuri Urban Municipality ............................................................................................ 50

Surkhet: Barahtal Rural Municipality .................................................................................................. 53

Summary of actors and types of linkages across maps .......................................................................... 56

Cross-cutting themes across maps ......................................................................................................... 58

Conclusion ................................................................................................................................................... 60

Identified gaps and next steps ................................................................................................................ 61


Figures and Tables Example map depicting who influences how data on health are used in SBC programs in Nepal

(according to provincial-level participants) ..................................................................................... 9

Figure 1. Example map depicting who influences local-level SBC for health in Nepal (according to local-

level stakeholders in Surkhet). ....................................................................................................... 14

Table 1. Information summarized in each Net-Map developed using DataMuse and the graphical

representation of that information for the purposes of interpretation ........................................ 15

Figure 2. Photo taken during the Landscape Analysis Workshop held at the central level during the

presentation of findings from the DataMuse digitized maps. ....................................................... 16

Figure 3. Digitized map, created using DataMuse, depicting who influences local-level SBC for health in

Nepal from the perspective of stakeholders at the central level (group #1). ............................... 18

Figure 4. Influence-Connections matrix for local-level SBC for health from the perspective of

stakeholders at the central level (group #1). ................................................................................. 20

Figure 5. Map, created using DataMuse, depicting who influences local-level SBC for health from the

perspective of stakeholders at the central level (group #2). ......................................................... 21


stakeholders at the central level (group #2). ................................................................................. 22

Figure 7. Digitized map, created using DataMuse, depicting who influences local-level SBC for health

from the perspective of stakeholders at the provincial level. ....................................................... 23


stakeholders at the provincial level. .............................................................................................. 25


from the perspective of stakeholders at the local level (Jumla: ChandanNath Urban

Municipality). ................................................................................................................................. 26


stakeholders at the local level (Jumla: ChandanNath Urban Municipality). ................................. 28


from the perspective of stakeholders at the local level (Jumla: GuthiChaur Rural Municipality). 29


stakeholders at the local level (Jumla: GuthiChaur Rural Municipality). ....................................... 30


from the perspective of stakeholders at the local level (Surkhet: Panchapuri Urban Municipality).

....................................................................................................................................................... 31



stakeholders at the local level (Surkhet: Panchapuri Urban Municipality). .................................. 33


from the perspective of stakeholders at the local level (Surkhet: Barahtal Rural Municipality). . 34


stakeholders at the local level (Surkhet: Barahtal Rural Municipality). ........................................ 35

Table 2. Number of actors, by type, and their distribution across central, Provincial, and local levels ..... 36

Table 3. Number of links, by link type ........................................................................................................ 37

Figure 17. Map, created using DataMuse, depicting who influences how data on health is used in SBC

programs from the perspective of stakeholders at the central level. ........................................... 39

Figure 18. Influence-Connections matrix for how data on health is used in SBC programs from the

perspective of stakeholders at the central level............................................................................ 41


programs from the perspective of stakeholders at the provincial level........................................ 42


perspective of stakeholders at the provincial level. ...................................................................... 44


programs from the perspective of stakeholders at the local level (Jumla: ChandanNath Urban

Municipality). ................................................................................................................................. 45


perspective of stakeholders at the local level (Jumla: ChandanNath Urban Municipality)........... 47


programs from the perspective of stakeholders at the local level (Jumla: GuthiChaur Rural

Municipality). ................................................................................................................................. 48


perspective of stakeholders at the local level (Jumla: GuthiChaur Rural Municipality). ............... 50


programs from the perspective of stakeholders at the local level (Surkhet: Panchapuri Urban

Municipality). ................................................................................................................................. 51


perspective of stakeholders at the local level (Surkhet: Panchapuri Urban Municipality). .......... 53


programs from the perspective of stakeholders at the local level (Surkhet: Barahtal Rural

Municipality). ................................................................................................................................. 54



perspective of stakeholders at the local level (Surkhet: Barahtal Rural Municipality).................. 56

Table 4. Number of actors, by type, and their distribution across central, Provincial, and local levels ..... 57

Table 5. Number of links, by link type ........................................................................................................ 58


Acronym List AWAJ CAD Collaborative Action for Dignity CAED Centre for Agro-Ecology and Development CBO Community-based organization CBS Central Bureau of Statistics CHU Community Health Unit CIAD Center for Alpine Integrated Development CREHPA Center for Research on Environment Health and Population Activities DDA Department of Drug Administration DHO District Health Office DoHS Department of Health Services DPHO District Public Health Office EDF Environmental Development Forum FCHV Female community health volunteer FPAN Family Planning Association of Nepal FWD Family Welfare Division HERD HERD International GIZ Deutsche Gesellschaft für Internationale Zusammenarbeit HKI Helen Keller International HMG Health mothers group HP Health post INF International Fellowship (INGO) INGO International non-governmental organization IOM Institute of Medicine IP Implementing Partner JHU Johns Hopkins University KAHS Karnali Academy of Health Sciences KASDA Karnali Sustainable Development Academy KIRDARC Karnali Integrated Rural Development Research Center MDI Manohari Development Institute MoHP Ministry of Health and Population MoSD Ministry of Social Development MSI Marie Stopes International MSMP/NSMP NGO Non-governmental organization NHEICC National Health Information Education and Communication Center NHRC Nepal Health Research Council ORC Outreach Clinic PHC Primary Health Care PHD Provincial Health Directorate PSI Population Services International R/M palikas Rural/municipal palikas SAC Nepal Social Awareness Center Nepal SBC Social and behavior change SDM SIFPO II Support for International Family Planning Organizations II


SSBH Strengthening Systems for Better Health UN United Nations UNFPA United Nations Population Fund USAID United States Agency for International Development VaRG Valley Research Group Private Limited WAM Women Association for Marginalized Women WFP World Food Programme WHO World Health Organization


Acknowledgements This report was written by Zoé Hendrickson, PhD, Shreejana KC, TrishAnn Davis, Caroline Jacoby,

Sanjanthi Velu, and Pranab Rajbhandari who led workshops, collected data, drafted portions, reviewed

content, and edited the report. TrishAnn Davis, Shreejana Kc, and Zoé Hendrickson conducted the

Landscape Analysis Workshop at the central level. Shreejana Kc conducted the workshops at the

provincial and local levels.

The Breakthrough ACTION Nepal team graciously thanks the many stakeholders who contributed their

time and energy to participate in the Landscape Analysis Workshops at the central, provincial, and local

levels. This activity was supported by the United States Agency for International Development(USAID)

through Cooperative Agreement #AID-OAA-A-17-00017.

Suggested citation: Hendrickson, Z.M., Kc, S., Davis, T.A., Jacoby, C., Velu, S., and Rajbhandari, P.

Breakthrough ACTION Nepal. 2018. Landscape Analysis Workshops in Nepal: Summary of Findings.

Center for Communication Programs: Baltimore, MD.


Executive summary

Introduction

The National Health Information Education and Communication Center (NHEICC), with support from

Breakthrough ACTION, conducted Landscape Analysis Workshops with government and non-

government stakeholders at the central, provincial, and local levels in order to understand the changing

social and behavior change (SBC) system for health and how data on health are used in SBC programs.

These workshops were conducted to identify and take advantage of opportunities to strengthen the

system. The purpose of the Landscape Analysis Workshops was to identify and clarify who influences

local-level SBC for health, and who influences how data on health is used in SBC programs at the various

levels.

Mapping process

During workshops at the central, provincial, and local levels,

participants participated in a Net-Map exercise, where they

were asked to work together develop maps that outlined the

influential actors and how they were linked with other actors

to influence 1) local-level SBC for health or 2) how data on

health are used. Participants described, from their

perspectives, who they considered to be influential actors and

the most important ways these actors were linked within the

system.

Breakthrough ACTION used DataMuse to digitize the maps

drawn by participants. Maps were then analyzed both

qualitatively and quantitatively. This report includes an in-

depth analysis of findings from each Net-Map produced by

participants during the landscape analysis workshops at the

central, provincial, and local levels. This includes:

1) An outline of the types of actors: We summarize the

major actor groups highlighted in maps at each level.

2) A discussion of the relative influence of different

actors: We highlight those actors with the greatest,

and the least, influence according to participants.

3) A summary of each type of linkage: We provide a

detailed description of the trends within each map for each type of linkage.

4) An analysis of influence and connections: We discuss the actors that have high influence and a

large number of connections and compare them to actors in other quadrants:

Example map depicting who influences how data on health are used in SBC

programs in Nepal (according to provincial level participants)


o High influence, few connections

o Low influence, many connections

o Low influence, few connections

5) A summary of two key social network analysis metrics for each map: closeness and

betweenness.

Similarities are then summarized by level (central, provincial, or local), with comparisons drawn across

levels. The report concludes with a discussion of cross-cutting themes and an identification of gaps.

Results

Who influences local-level SBC for health in Nepal?

A comparison of maps from the central, provincial, and local levels suggested that government agencies,

donors, NGOs, and INGOs were most often considered important actors in SBC for health at the local

level. Across all levels, government actors were identified as key influencers of local-level SBC. However,

there were differences in the types of actors identified between central, provincial, and local levels:

• At the central level, NGOs or social groups were not identified as significant group types, while

all groups at the provincial and local levels identified NGOs as important actors in local-level

SBC.

• Community-based organizations (CBOs) were identified in nearly all local-level maps, but not

frequently at the provincial or central levels.

• Private sector actors were only identified by two groups across all maps, suggesting that either

1) there remains minimal private sector involvement in who influences local-level SBC for health

or 2) they are not considered primary players in the local-level SBC system.

Across all levels, linkages between actors based on funding and provision of technical support,

assistance, or capacity building were identified as important ways that actors influencing local-level SBC

for health were linked. Less commonly identified were connections between actors based on program

implementation, advocacy, collaboration, and having a common goal. The most common links varied in

maps developed at the central, provincial, and local levels:

• Central level: Collaboration and having a common goal were the most common links that

stakeholders identified when thinking about how key SBC influencers are related to other actors

in the SBC system.

• Provincial level: Stakeholders identified technical support, assistance, or capacity building most

commonly.

• Local level: Data or information sharing, funding, and authority or supervision were highlighted

as key ways in which actors influencing local-level SBC for health were linked.

At the central level, a comparison of maps depicting who influences local-level SBC for health in Nepal

suggested that:


1) Government actors at the central level (e.g. the Ministry of Health and Population (MoHP), the Department of Health Services (DoHS), and NHEICC) were assigned more relationships than were government actors at the local level (e.g. female community health volunteers (FCHVs), local health institutions, or locally elected representatives) according to maps developed at the central level.

2) There were minimal linkages between local-level and central-level actors.

At the provincial level:

1) The most influential actors were local-level government actors including FCHVs, District Health Offices (DHOs), and HMG. In contrast, INGOs had fewer connections with one another or to other actors.

At the local level:

1) The local-level government (Nagarpalika, RMCP, etc.) typically had the greatest influence. DHOs or central-level government actors were not identified.

2) There were minimal linkages between community-based organizations or between local level organizations (e.g. between HMGs and youth clubs).

Who influences how data on health is used in SBC programs?

Across all levels, government actors were identified as key influencers of how data is used. There were

significant differences, however, in the types of actors identified between central and provincial and

local levels.

• At the central level, academic institutions (e.g. The Johns Hopkins University (JHU)) and research

organizations (e.g. HERD International) were highlighted as important actor types, while only

one group at the provincial and local levels identified any academic institutions or research

organizations as key actors in how data on health is used in SBC programs. This was in Jumla

(ChandanNath Urban Municipality), where the Karnali Academy of Health Sciences (KAHS) was

included as a key actor.

• Similarly, NGOs, private organizations, and INGOs were identified in nearly all local-level maps,

but were not considered important actors in use of data on health at the central level.

• Community-based organizations or local social networks were only identified by two groups

(one in Jumla and one in Surkhet), which indicates the minimal involvement and influence of

local organizations in data use for SBC programs.

Across all levels, linkages between actors based on data or information sharing, funding, and provision

of technical support, assistance, or capacity building were highlighted, suggesting that these avenues

were consistently considered important ways that actors influencing how data are used were linked.

Collaboration or coordination was only recognized as an important type of link for participants from the

central and provincial levels, which may suggest the importance placed by participants at these levels on

collaboration for data use for SBC programs.


• At the central and provincial levels, 1) collaboration and 2) data or information sharing were the

most common links that stakeholders identified when thinking about how actors related to

other actors to influence how data are used in SBC programs.

• Across all four maps drawn at the local level, 1) data or information sharing and 2) technical

support, technical assistance, or capacity building were highlighted as the most common ways

through which actors influencing how data are used were linked together.

At the central level, a comparison of maps depicting who influences how data on health are used in SBC

programs in Nepal suggested that:

1) There were a number of research organizations and academic institutions involved in how data are used in SBC programs from the perspective of stakeholders at the central level. However, there were few linkages between these actors, suggesting that coordination and collaboration are minimal as these organizations typically work on specific funder-driver agendas. These actors had minimal influence over how data are used and were typically simply considered to be providers of information.


1) In comparison with the central-level map, more NGOs and fewer INGOs were included as key actors. In addition, the number of government actors grew and diversified, with government actors from multiple levels (e.g. from FCHVs to R/M palikas to hospitals or health posts (HPs) to DHOs) outlined as playing important roles in how data are used.

2) While private actors like CRS were considered as actors in this map, there were minimal linkages between these actors and governmental or non-governmental actors in terms of how data are used in SBC programs.

At the local level:

1) In comparison to the prominent role of academic institutions and research firms at the central level, academic institutions were only included in one local-level map: Jumla (ChandanNath Urban Municipality).

2) Groups often highlighted a number of government actors, with minimal participation in non-governmental (be it private, NGO, or INGO) actors in how data are used in SBC programs.

3) There were minimal linkages between organizations within the same type of actor (i.e. between INGOs or between NGOs), which may suggest minimal coordination at the local level regarding how data are used.

Conclusion

Clear throughout these maps were gaps that could be addressed through capacity strengthening

activities designed to foster collaboration across actors within the SBC for health system.

Some actors were considered to have significant influence and, simultaneously, limited connections,

such as FCHVs or other local-level actors (e.g. locally-elected representatives, CBOs, local health

institutions, etc.) in local-level SBC for health. Simultaneously, FCHVs were considered, across all four

maps at the local level, to have significant influence and to have linkages to both government and non-


government actors regarding how data are used in SBC programs. FCHVs were shown to play important

mediating roles between certain government actors and health mothers groups (HMGs) related to data

use. This can be a priority group for fostering connections and support.

There was a lack of perceived collaboration, common goal, or information sharing, related to how local-

level SBC for health takes place, among:

• Government actors and local-level community organizations or community leaders

• NHEICC and other governmental actors at the central, provincial, or local levels

• INGOs and NGOs

At the same time, participants in multiple workshops indicated minimal linkages between actors of the

same type (e.g. between INGOs or between NGOs), which may suggest minimal coordination at the local

level regarding how data are used.

Technical assistance was received primarily by government actors, with only a few actors working at the

local level providing technical assistance to CBOs or social actors on local-level SBC for health. Technical

assistance related to use of data on health for SBC programs was also typically focused on government

actors such as the DHO or the HPs, with less attention to partner organizations or to other more local

government actors (e.g. at the ward level).

Overwhelming differences in maps depicting how local-level SBC programs take place or how data are

used for SBC programs across central, provincial, and local levels demonstrated different understandings

of how SBC activities are planned for, designed, and implemented in Nepal. Coordination of actors,

including identification of agreed upon roles and responsibilities, could start to identify similarities

across maps to strengthen the system, fill gaps, and reduce inefficiencies.


Introduction Nepal is undergoing an extensive reorganization of its government structures as part of the country’s

transition to federalism. Under this new system, provinces and local governments have new roles and

responsibilities over health planning and decision-making. The National Health Information Education

and Communication Center (NHEICC) retains a significant role within the new structure to provide

policy, structural and technical support and oversite as the system is forming. As such, NHEICC is

working closely with Breakthrough ACTION to actively collaborate and work in close coordination with

all social and behavior change (SBC), service delivery, multi-sectoral partners and other stakeholders to

understand the changing SBC system for health,

take advantage of opportunities to strengthen the

system, and resolve potential challenges.

A s part of the process to fully understand the new

federal landscape, NHEICC and Breakthrough

ACTION facilitated Net-Map exercises with key SBC

stakeholders for health at the central, provincial,

and local levels. The purpose of this exercise was to

identify and clarify:

1) Who influences local-level SBC for health, and

2) Who influences how data on health is used in SBC programs.

After an orientation, key stakeholders from donors,

government, academic institutions, and research

organizations 1 mapped the “SBC for health”

landscape in Nepal to answer these two guiding

questions.2

A participatory tool known as Net-Map was used

during the Landscape Analysis Workshops. The Net-

Map approach and tool, developed by Eva Schiffer with support from Amitaksha Nag, is used to help

individuals and groups clarify their own view of a situation (including networks and power structures),

1 See Annex 1 for numbers of participants and a list of participating organizations at the central, provincial, and local levels. 2 This process mapped a “social network” of SBC stakeholders. A social network is a group of actors that are linked together by a set of social relations. These relations describe the ties of a specific kind among the actors of the network. Actors of a social network can be individuals, organizations, or companies. Regardless of what they are, they are always the smallest single unit inside a network.

Figure 1. Example map depicting who influences local-level SBC for health in Nepal (according to local-level

stakeholders in Surkhet).


foster discussion, and develop a strategic approach to their networking activities1. It helps to facilitate

this type of analysis by determining the following:

▪ Actors involved in a given network (i.e. NHEICC, Family Welfare Division (FWD), Implementing Partners (IPs), donors, health coordinators, mayors and various committees at local level)

▪ Formal/informal link between actors (e.g. formal directive or supervision, funding, technical support, trust, pressure, communication flow)

▪ Goals of actors (positive, negative or neutral alignment to goals) ▪ Influence of actors (low or high) ▪ Network of stakeholders (analysis of how well are actors linked or not linked to each other)

Net-Maps created using DataMuse include detailed information on actors and the linkages between

them. In the table below, the graphical representation of each type of information included in a Net-

Map is summarized. These details will enable an in-depth interpretation of each Net-Map presented in

this report.

TABLE 1. INFORMATION SUMMARIZED IN EACH NET-MAP DEVELOPED USING DATAMUSE AND THE GRAPHICAL REPRESENTATION OF THAT INFORMATION FOR THE PURPOSES OF INTERPRETATION INFORMATION SUMMARIZED GRAPHICAL REPRESENTATION

Actors Depicted by circles

Types of actors Indicated by the color of each circle

Influence of actor Suggested by the size of the circle (larger = more influence)

Linkages Depicted by arrows

Types of linkages Indicated by the color of each arrow

Strength of the relationship Suggested by the thickness of the arrow (thicker = stronger relationship)

Mapping Process

Participants were split into groups, with some groups answering, “Who influences local-level SBC for

health?” and others answering, “Who influences how data on health is used in SBC programs?” The

landscape analysis workshops were participatory. With the active engagement of the groups during the

mapping process, participants were able to develop multiple different, complete maps by the end of the

one-day workshop.

In real time (where possible), data generated through this participatory mapping exercise were inputted

into a computer analysis software program, called DataMuse, that allowed the maps to be digitized and

analyzed quantitatively and qualitatively. DataMuse includes multiple tools that facilitate analysis,

including quantitative metrics summarizing actors’ influence and number of links with other actors.


DataMuse also enables users to isolate, visually,

specific portions of maps (e.g. looking at all links of a

certain type, or all links to a certain actor), which

allows more in-depth analysis. DataMuse also enables

users to compare multiple versions of maps over time

in a simple way to identify changes in a given network

identified by workshop participants over time.

At the end of each workshop, each group reported

their observations in plenary and highlighted lessons

learned. Following the completion of all landscape

workshops, Breakthrough ACTION led a comparative

analysis of all Net-Maps produced, which included a

description and summary of each map, followed by a

discussion of key social network analysis metrics such

as closeness and betweenness and a comparison of maps across the central, provincial, and local levels.

Overview of report

In the following sections of the report, we summarize findings from Landscape Analysis Workshops

conducted at the central, provincial, and local levels. The maps presented reflect the perspectives of

stakeholders attending each Landscape Analysis Workshop.

The report is organized by the question guiding each Net-Map exercise:

1) Who influences local-level SBC for health, and 2) Who influences how data on health is used in SBC programs.

For each guiding question, we examine each map developed in depth, from the central to provincial to

local levels, to provide specific details about how workshop participants at each level perceived 1) who

influences local-level SBC for health or 2) who influences how data on health is used in SBC programs.

For each map, we:

6) Outline the types of actors: Participants identified influential actors and then grouped them

into types of actors (e.g. government, non-governmental organization (NGO), international non-

governmental organization (INGO), etc.). These actors are grouped by color in the Net-Maps

created using DataMuse. We summarize the major actor groups highlighted in maps at each

level.

7) Discuss the relative influence of different actors: Participants identified the relative influence of

each actor in the map. Influence is signified by the size of the actor’s circle in the Net-Maps

created using DataMuse. We highlight those actors with the greatest, and the least, influence

according to participants.

Figure 2. Photo taken during the Landscape Analysis Workshop held at the central level during

the presentation of findings from the DataMuse digitized maps.


8) Summarize each type of linkage: Participants chose approximately four types of relationships

that they thought linked together the different actors that either 1) influence local-level SBC for

health or 2) influence how data on health are used in SBC programs. Linkages are shown with

arrows, and types of linkages are distinguished based on color, in the Net-Maps created using

DataMuse. We provide a detailed description of the trends within each map for each type of

linkage. For example, if we were to consider funding as a linkage, we would ask: what actors

typically provide funding? Who do they provide funding to? Who does not receive funding? Who

is excluded from these funding relationships?

9) Organize actors based on their influence and number of connections: In this section, a matrix

comparing influence (Y-axis) and connections (X-axis) is presented. We discuss the actors that

have high influence and a large number of connections (top right quadrant) and compare them

to actors in other quadrants:

o High influence, few connections: top left quadrant

o Low influence, many connections: bottom right quadrant

o Low influence, few connections: bottom left quadrant.

We use this as a starting point for potential audience segmentation for future activities.

10) Summarize two key social network analysis metrics for each map: closeness and betweenness.

Closeness refers to how close any individual actor is to every other actor in their network. A

higher score reflects that they are more closely linked to all actors in the network as compared

to others. Betweenness is a measure of how well a specific actor links or bridges to other actors

that are not otherwise linked to each other. A higher score reflects that an actor serves as an in-

between between other actors that are not connected directly to each other.

Following a detailed analysis of each map from each level, we then provide an overarching summary of

the types of actors, types of linkages between actors, and cross-cutting themes emerging across maps

developed by participants in Landscape Analysis Workshops.


Who influences local-level SBC for health in Nepal?

Central level: Group #1

At the central level, two groups developed Net-Maps that reflected their views of the actors and

linkages that play an important role in local-level SBC for health in Nepal. While there were similarities

between the two maps, there were also differences in how the two groups understood the way that the

local-level SBC system functions in Nepal.

In Figure 3 below, a complete Net-Map depicting relevant actors and linkages is shown for the first

group at the central level. This map illustrates, according to one group in this workshop, who influences

local-level SBC for health in Nepal.

Figure 3. Digitized map, created using DataMuse, depicting who influences local-level SBC for health in Nepal from the perspective of stakeholders at the central level (group #1).

Actors

A total of 15 actors or groups of actors were identified by participants in this group, including

governments (6) and donors (5). Actors like community-based organizations (CBOs), leaders, and media

were also included in this group. According to this group’s map, female community health volunteers

(FCHVs) had the highest influence among all the actors as compared to other actors. Interestingly,

locally-elected representatives and the Ministry of Health and Population (MoHP) were given the same

level of influence over local-level SBC for health in Nepal. MoHP, NHEICC, and INGOs/United Nations

(UN)/Donors had more connections than did actors at the local level (e.g. traditional healers, locally-

elected representatives, FCHVs, CBOs, etc.).


Linkages

Below is a description, based on Figure 3, the types of linkages that participants in group #1 at the

central level identified between actors influential in local-level SBC for health.

• Data Sharing: Nearly all actors were shown to share data with at least one other actor. Data sharing was nearly always considered by this group to be bidirectional. The World Health Organization (WHO) and United Nations Population Fund (UNFPA) had a strong relationship for sharing data (signified by a thicker arrow in Figure 3). Data sharing between NHEICC and the WHO, INGOs, UNICEF, and UNFPA were not considered strong (signified by a thinner or dotted arrow in Figure 3). MoHP, FWD, FCHVs, and health workers shared data bidrectionally with one another, suggesting a strongly interconnected sub-group within the larger network among government actors. From participants at the central level, data sharing between the Ministry of Social Welfare and health workers was considered to be weak. This weak linkage may be the result of the fact that stakeholders at the central level were unaware of the linkage between the Ministry of Social Welfare and health workers at the provincial level.

• Funding: With regards to funding, the media was thought to receive funding from governmental and INGO/UN/other donors. Donors were depicted as providing funding to multiple actors, including the WHO, MoHP, FWD, UNFPA, UNICEF, and INGOs. NHEICC, FWD, and the MoHP only provided funding to media.

• Collaboration: Strong collaboration was identified across a range of actors, particularly between INGOs, UN agencies, and donors as well as with central-level government actors (e.g. MoHP). The Ministry of Social Welfare was thought not to collaborate with many actors, and their collaboration with MoHP was not considered strong. Again, this may be due to the fact that stakeholders at the central level were unaware of their collaboration with other actors that may take place at the provincial level. FCHVs and health workers were thought to collaborate with one another but not with other actors in this map. Media and CBOs were thought to collaborate with MoHP, INGOs, UNICEF, and NHEICC.

• Technical Support: Very strong technical support was considered to come from INGOs, UN agencies, and donors most frequently and was thought to be provided to government actors such as the Ministry of Social Welfare, MoHP, NHEICC, and FWD. However, these central government agencies were not depicted as providing technical assistance often to local-level actors in Figure 3 (except in the instance between the Ministry of Social Welfare and locally-elected representatives). Otherwise, technical assistance to the local level was, according to participants in group #1, received by CBOs from UNFPA and INGOs. These CBOs, in addition to health workers, provided technical assistance to FCHVs. There were no instances, in this map, of technical assistance being provided to health workers.

• Authority: In terms of authority, most of the links drawn by participants were from MoHP to other actors such as FWD, INGOs, or NHEICC. Locally-elected representatives were also considered to have authority over local-level actors such as traditional healers, FCHVs, CBOs, and health workers.

Influence and connections

In Figure 4 below, a matrix compares the number of connections of each actor (X-axis) with their

influence (Y-axis). Actors in the top right quadrant have, according to participants in the Landscape

Analysis Workshop at the central level (group #1), high influence and many connections. This figure

shows that government actors (NHEICC and MoHP) had higher influence and higher connections (top


right quadrant), while local leaders such as traditional healers as well as government actors such as the

Ministry of Social Welfare and the FWD had fewer connections and less influence over local-level SBC for

health (bottom left quadrant). Of note, FCHVs and locally-elected representatives were considered to

have significant influence despite their limited number of connections (top left quadrant).

Figure 4. Influence-Connections matrix for local-level SBC for health from the perspective of stakeholders at the central level (group #1).3

Social network analysis metrics: Closeness and Betweenness

• Closeness: INGOs, UNICEF, and NHEICC were most closely linked to all actors in the network.

This network was close-knit with many close connections across actors.

• Betweenness: Locally-elected representatives and CBOs played the most important connecting

roles by linking other actors that may not necessarily have relationships with one another. Other

actors also playing important intermediary roles included NHEICC and INGOs.

Central level: Group #2

In figure 5 below, a complete Net-Map depicting relevant actors and linkages is shown for the second

group at the central level. This map illustrates, according to group #2 in the workshop at the central

level, who influences local-level SBC for health in Nepal.

3 Note: For points reflecting more than one actor (i.e., if the number next to the point is greater than 1), the color of the point may not reflect the type of all actors at that point. It will reflect the type of actor of one of the actors.


Figure 5. Map, created using DataMuse, depicting who influences local-level SBC for health from the perspective of stakeholders at the central level (group #2).

Actors

A total of 16 actors or groups of actors were identified by participants of this group, of them most were

governments (3), INGOs (7) and donors (2). Actors like media and private sector were also identified.

The map showed that NHEICC and local health institutions had the highest influence among all the

actors, followed by United States Agency for International Development (USAID) and health workers.

NHEICC, UN agencies, and USAID had, across all actors, the highest number of connections with other

actors. These connections were primarily having a shared common goal and funding (most often with

INGOs such as Population Services International (PSI), Marie Stopes International (MSI), Helen Keller

International (HKI), Plan International, Care International, FHI360, and Equal Access).

Linkages

Below is a summary, based on Figure 5, of the types of linkages that participants in group #2 at the

central level identified between actors influential in local-level SBC for health.

• Funding: USAID had the primary funding role in this map, and participants linked them with all INGOs as well as NHEICC, UN agencies, and Nepal CRS Company (CRS). NHEICC was depicted as having strong funding links with the national and local media. PSI also was considered an important funder of media and health workers. UN Agencies were funders of Equal Access as well as PSI, but the funding link with PSI was not strong. CRS was a funder of Social Marketing Company.

• Authority: NHEICC and Department of Drug Administration (DDA) were thought to have authority over local health institutions. This authority was represented as a strong link between these government actors. DDA also had authority over CRS (strong link), health workers, and Social Marketing Company, despite its low influence within this map overall.


• Common Goal: Having a common goal was, overall, considered a bidirectional relationship. NHEICC was seen as strongly connected with most INGO actors in terms of their common goal. With the exception of MSI and PSI, INGOs were not linked to one another in terms of common goal in this map. UN agencies had a common goal with Equal Access, local health institutions, and with NHEICC. However, NHEICC and local health institutions were not linked.

• Technical Support: NHEICC is the primary recipient of technical support, with UN agencies and USAID providing it to them. In contrast to group #1 at the central level, who did not identify NHEICC as a source of technical support or assistance to other actors, group #2 at the central level thought that NHEICC provided technical assistance to other groups, including PSI and HKI. NHEICC was not thought to provide technical support to local-level actors. PSI was depicted as providing technical support to national and local media.


In Figure 6 below, a matrix compares the number of connections of each actor with their influence. As

this figure suggests, government actors (NHEICC and local health institutions) had a higher level of

influence (top quadrants). However, NHEICC had higher connections than local health institutions

despite their influence (top right quadrant). DDA and CRS were considered to have low influence and

few connections with others in this network according to this group of participants (bottom left

quadrant).

Figure 6. Influence-Connections matrix for local-level SBC for health from the perspective of stakeholders at the central level (group #2).4



Social network analysis metrics: Closenss and Betweenness

• Closeness: Among all actors shown by participants in Figure 5, USAID was most closely linked to

all other actors.

• Betweenness: USAID and NHEICC played the most important connecting roles by linking or

bridging to other actors that may not necessarily have relationships with one another. Other

actors with similar intermediary roles included PSI and CRS.

Provincial level

In figure 7 below, a complete Net-Map depicting relevant actors and linkages is shown based on

perspectives from key stakeholders at the provincial level. This map illustrates, according to their

perspectives, who influences local-level SBC for health in Nepal.

Figure 7. Digitized map, created using DataMuse, depicting who influences local-level SBC for health from the perspective of stakeholders at the provincial level.

Actors


governments (7) and INGOs (5). Actors like local NGOs, UN agencies (e.g. UNICEF), and community

leaders (e.g. traditional healers) were also included in this group. According to this group’s map, the

most influential actors were local level government actors including FCHVs, the District Health Office

(DHO), and HMGs. In contrast, INGOs had fewer connections to other actors and were considered to

have less influence. Of note, UNICEF was considered to have only one direct link: to the DHO. Traditional

healers and the Provincial Health Directorate (PHD) were thought to have the lowest level of influence

over local-level SBC for health.


Linkages

Below is a summary, based on Figure 7, of the types of linkages that participants at the provincial level

identified between actors influential in local-level SBC for health.

• Funding: INGOs were considered to be the primary sources of funding, which was provided to the DHO as well as the health post (HP). Other NGOs provided funding to HMGs, including Suaahara and the Centre for Agro-Ecology and Development (CAED). At the same time, the Ministry of Social Development (MoSD) provided funding to the DHO and hospital as well as the PHD. Interestingly, the DHO and HP were shown to be mediators between the MOSD as well as the INGOs and downstream actors such as FCHVs or the health mothers group (HMG).

• Supervision: Supervision suggested three separate maps: one for government actors specifically, with supervision coming from MoSD. The HMG was supervised by NGOs and INGOs like Suaahara and Sundar Nepal. Finally, traditional healers received some supervision, although this relationship was not considered strong, from CAED (an NGO).

• Capacity building: INGOs (e.g. WHO and SAVE) and NGOs (e.g. Suaahara and CAED) were identified by participants at the provincial level as sources of capacity building for various government actors working in health including the DHO, the HP, hospitals, HMG, PHD, and FCHVs. The HP acted as a mediator to FCHVs for capacity building received from both NGOs and INGOs.

• Program implementation: Save the children was identified as a major program implementer in this map, with direct linkages to the DHO and HP. The HP served as an important mediator between SAVE or the DHO and FCHVs as well as traditional healers. Similarly, the MoSD was linked to hospitals for program implementation. FCHVs as well as traditional healers were implementers of programs from the HP according to workshop participants at the provincial level.


In the influence-connections matrix below, the DHO and HP were considered to have high influence and

high connections (top right quadrant). Interestingly, FCHVs, HMG, hospitals, and MoSD had high

influence but few connections (top left quadrant).


Figure 8. Influence-Connections matrix for local-level SBC for health from the perspective of stakeholders at the provincial level.5


• Closeness: The DHO was most closely linked to all actors within the map developed by

participants at the provincial level.

• Betweenness: As outlined above, the DHO and the HP played the most important connecting

roles by linking or bridging to other actors that may not necessarily have relationships with one

another (e.g. funders or providers of capacity building or technical assistance with local level

groups like HMGs or FCHVs).

Local level

Four Net-Maps were developed in four municipalities to examine who influences local-level SBC for

health in Nepal. These maps are summarized in depth below.

Jumla: ChandanNath Urban Municipality


perspectives from key stakeholders in Jumla (ChandanNath Urban Municipality). This map illustrates,

according to their perspectives, who influences local-level SBC for health in Nepal.



Figure 9. Digitized map, created using DataMuse, depicting who influences local-level SBC for health from the perspective of stakeholders at the local level (Jumla: ChandanNath Urban Municipality).

Actors


governments (4), CBOs (4) INGOs (3), and NGOs (3). Actors like media (1) and local leaders (1) were also

included in this group. According to this group’s map, the most influential actor was the local municipal

government (Nagarpalika). The HP and media were also influential actors. FCHVs and schools were also

identified as having significant influence in local-level SBC, and they played important mediating roles

between the local government, the HP, and HMGs. However, overlaps between the HP and schools were

minimal. While some local NGOs worked with schools, these NGOs did not have links with the HP

directly.

In contrast, CBOs were all thought to have the lowest level of influence, similar to Breakthrough ACTION

as well as select NGOs such as Manohari Development Institute (MDI).

The local government did not link directly with NGOs like Collaborative Action for Dignity (CAD), MDI, or

Karnali Integrated Rural Development Research Center (KIRDARC). Furthermore, while HPs were directly

linked with INGOs, they did not necessarily always link with the Nagarpalika. Interestingly, while the

media was said to have a major role, it was only linked with local leaders and the Nagarpalika directly.

Interestingly, there were no linkages between local level CBOs (e.g. between youth clubs and HMGs).

Similarly, linkages between INGOs and NGOs were not common – except for Path, who had direct

funding relationships with CAD and KIRDARC.


Linkages

Below is a summary, based on Figure 9, of the types of linkages that participants at the local level in

Jumla (ChandanNath Urban Municipality) identified between actors influential in local-level SBC for

health.

• Funding: The Nagarpalika as well as Plan were the predominant providers of funds related to SBC for health at the local level according to participants in Jumla (ChandanNath). Schools appear to receive funds form not only Nagarpalikas, but also Plan and NGOs like CAD and KIRDARC.

• Technical: While the Nagarpalika provided technical support to the HP, the map depicted minimal technical capacity being provided to the Nagarpalika or other NGOs or other INGOs. Breakthrough ACTION appears to be filling a major gap in this area. MSI was also identified as linked to the HPs through the provision of technical assistance.

• Information: The Nagarpalika received information from the HP as well as local leaders and media, but there was no information sharing shown with local NGOs and little information that goes the “last mile” to child or youth clubs or to HMGs.

• Programmatic: HPs had relationships with Plan as well as the Nagarpalika, local leaders, and MDI for programmatic implementation. The Nagarpalika had a direct link to the child club, and the FCHVs with the HMGs, for programmatic implementation.


Below is a graph of the number of connections of different actors by their influence in the system

(Figure 10). All yellow dots are government, with the HP and the Nagarpalika having high influence and

connections (top right quadrant). The media, in comparison, had high influence, according to

participants at this workshop, but fewer connections (top left quadrant).


Figure 10. Influence-Connections matrix for local-level SBC for health from the perspective of stakeholders at the local level (Jumla: ChandanNath Urban Municipality).6


• Closeness: The Nagarpalika, the local municipality government, had the closest links with all

other actors included in the map in Figure 9.

• Betweenness: As outlined above, the Nagarpalika, schools, and HPs played the most important

connecting roles by linking other actors that may not necessarily have relationships with one

another.

Jumla: GuthiChaur Rural Municipality


perspectives from key stakeholders in Jumla (GuthiChaur Rural Municipality). This map illustrates,




Figure 11. Digitized map, created using DataMuse, depicting who influences local-level SBC for health from the perspective of stakeholders at the local level (Jumla: GuthiChaur Rural Municipality).

Actors


governments (4), INGOs (5), NGOs (4), and CBOs (3). According to this group’s map, the most influential

actor was the local government (Rural Municipality RMCP). Other actors with somewhat greater

influence included the HP, INGOs or projects such as Plan, Breakthrough, Strengthening Systems for

Better Health (SSBH), UNICEF, and World Food Programme (WFP), and some NGOs such as MDI or

Shangri-La Association. Except for HMGs, the local municipality government RMCP was considered to

have direct links with all actors. Interestingly, and in contrast to other maps, the HP and HMGs were not

mediated by FCHVs. In fact, FCHVs were not highlighted as a key actor in this map. Linkages between

local level actors (between social work, youth group, or HMGs, for example) were not reported. Linkages

between INGOs and NGOs were not common. Of note, schools and police were linked with RMCP, but

not with any other actors.

Linkages


Jumla (GuthiChaur Rural Municipality) identified between actors influential in local-level SBC for health.

• Funding: RMCP was a primary source of funding for other government actors – including the HP, school, and police – as well as youth clubs according to participants from Jumla (GuthiChaur). In contrast, INGOs like Plan, Breakthrough ACTION, or UNICEF (considered an INGO by participants) provided direct funding to the HP, RMCP, as well as Shangri-La Association (an NGO). There were no direct connections between RMCP and NGOs shown in the map.

• Technical: Technical assistance was thought to be provided primarily from NGOs and INGOs to government actors and CBOs. RMCP and the HP received technical support from multiple


sources, including INGOs (Breakthrough ACTION and SSBH) as well as Karnali Sustainable Development Academy (KASDA) and MDI (NGOs) according to participants.

• Advocacy: The number of links between actors based on advocacy were minimal in this map. Advocacy was initiated by Breakthrough ACTION or DWO exclusively. DWO also described as advocating with RMCP as well as at the local level with HMGs and youth groups. In contrast, Breakthrough ACTION was thought to advocate with RMCP and the HP.

• Data: Substantial data sharing was reported across actors, with bidirectional arrows suggesting that data flow went between actors in multiple directs. RMCP shared data with all INGOs and NGOs, while there was no reported data sharing between HMGs or youth clubs and other actors.


Below is a graph of the number of connections of different actors by their influence in the system

(Figure 12). All blue dots are government, with RMCP having high influence and connections (top right

quadrant). The HP had more connections but had less influence as compared with RMCP (bottom right

quadrant).

Figure 12. Influence-Connections matrix for local-level SBC for health from the perspective of stakeholders at the local level (Jumla: GuthiChaur Rural Municipality).7


• Closeness: The local government (Rural Municipality RMCP) and the HP were most closely linked

to all actors within the map shown in Figure 11.

• Betweenness: RMCP had the most important connecting roles by linking or bridging to other

actors that may not necessarily have relationships with one another.



Surkhet: Panchapuri Urban Municipality


perspectives from key stakeholders in Surkhet (Panchapuri Urban Municipality). This map illustrates,


Figure 13. Digitized map, created using DataMuse, depicting who influences local-level SBC for health from the perspective of

stakeholders at the local level (Surkhet: Panchapuri Urban Municipality).

Actors


governments (9), INGOs (2), NGOs (2), and social organizations (3). Private actors (e.g. media/radio or

medical facilities) were also identified as key actors in the local-level SBC for health system. According to

this group’s map, the most influential actors were the Nagarpalika and the HP. Other actors with higher

influence included the community school, FCHVs, and the PHC. There were no connections between the

community school and FCHVs, but there were connections between the HP and the community school

(related to information sharing). In fact, FCHVs were connected not only to other government actors,

but also NGOs (Suaahara) as well as private organizations (media/radio) and social actors (Dhami jhakri –

traditional healers – and the HMGs). The INGOs and NGOs were linked directly with government actors,

but not with private or social organizations.

Linkages


Surkhet (Panchapuri Urban Municipality) identified between actors influential in local-level SBC for

health.

• Technical support: Substantial technical support was shown to be provided to government actors, with Breakthrough ACTION as well as Suaahara providing it directly to the Nagarpalika.


HPs were, according to participants, both the recipients of technical assistance and provided technical assistance to other government actors. Technical assistance provided to private medical actors was considered to be a weaker link than that between government actors (shown as a thinner or dotted arrow in Figure 13).

• Authority: The Nagarpalika was considered to have authority over all actors and was directly linked to all actors. There was some evidence of additional authority from Ekta foundation over certain government actors (e.g. AG/Live stock or the HP). In addition, the community school was considered to have some authority over private medical facilities.

• Information: Despite the important role of the Nagarpalika in technical support and authority, they were not, according to participants, highly involved in information sharing. Most information sharing occurred from the media/radio actor to other private actors (e.g. private medical actors) as well as community schools, FCHVs, HMG, or the HP in this map. Ekta foundation was the only actor who shared information with the Nagarpalika. The community school received information from the media/radio as well as EGRP, and there was a bidirectional arrow suggestion mutual information sharing between the community school and the HP. The dhami jhakri (i.e. traditional healers) shared information not only with FCHVs but also with the HMGs, but this information sharing was considered unidirectional; FCHVs were not shown as sharing information with the dhami jhakri. No information sharing was reported with Suaahara.

• Funding: Social actors were not shown to have funding linkages with the government. The Nagarpalika was the primary source of funding for other government actors, while it also received funding from Breakthrough ACTION as well as Suaahara.


In the influence-connections matrix below (Figure 14), the Nagarpalika had high influence and high

connections (top right quadrant). Interestingly, FCHVs, the HP, community schools, PHC, and HMGs had

high influence but few connections (top left quadrant).


Figure 14. Influence-Connections matrix for local-level SBC for health from the perspective of stakeholders at the local level (Surkhet: Panchapuri Urban Municipality).8


• Closeness: As shown in other maps from the local level, the Nagarpalika was most closely linked

with all other actors in the map in Figure 13).

• Betweenness: The Nagarpalika had the most important connecting roles by linking or bridging

other actors that may not necessarily have relationships with one another.

Surkhet: Barahtal Rural Municipality


perspectives from key stakeholders in Surkhet (Barahtal Rural Municipality). This map illustrates,




Figure 15. Digitized map, created using DataMuse, depicting who influences local-level SBC for health from the perspective of stakeholders at the local level (Surkhet: Barahtal Rural Municipality).

Actors


governments (9), NGOs (5), and community organizations (2). According to this group’s map, FCHVs, the

school, the local municipal government (Gaonpalika), and the HP were the actors with the most

influence. There were few connections between the HP and school. Local community actors (e.g. youth

clubs and HMGs) were connected to HP and some local government actors, but not to NGOs. The HP

was connected to nearly all actors (except the Red Cross). Similarly, the Gaonpalika government actor

had links with nearly all actors, but was not linked, according to this group, to Immunization or to

Support for International Family Planning Organizations II (SIFPO II). FCHVs were primarily connected to

the HP and SIFPO II. FCHVs were only connected to the Gaonpalika by receipt of funding. There were no

connections identified between FCHVs and the HMGs. Youth clubs were connected to more government

actors than the HMGs.

Linkages


Surkhet (Barahtal Rural Municipality) identified between actors influential in local-level SBC for health.

• Authority: The local rural municipal government (Gaonpalika) had, according to workshop participants, authority over the gaon health section, which then had authority over multiple actors including other government (e.g. ward office), community organizations (e.g. youth clubs), and NGOs (e.g. SIFPO II, Environmental Development Forum (EDF), Suaahara, and Breakthrough ACTION). The ward office also had authority over the gaon health section, the HP, and schools. The HP had authority, then, over multiple government actors (e.g. Immunization, Community Health Unit (CHU), Primary Health Care (PHC)/Outreach Clinic (ORC)) as well as HMGs. These relationships may reflect the fact that immunization, the gaon health section, and PHC/ORC were all responsibilities of the HPs in their regular work.


• Funding: The Gaonpalika, SIFPO II, Suaahara, and Breakthrough ACTION were primary sources of funding, with the Gaonpalika a larger source of funding than the others, in the map developed by workshop participants shown in Figure 15. NGOs were key sources of funding for the HP and government actors. The Gaonpalika was the strongest source of funding for the ward office, which then provided funding to schools, youth clubs, and other government actors (e.g. PHC/ORC).

• Information: Information was thought to be shared with the Gaonpalika and the HP, but less so with other government actors. There was minimal horizontal information sharing across or between government actors, between NGOs, or between youth clubs and HMGs in this map.

• Technical support: The HP was the major provider of technical support to other government actors and community actors (e.g. HMGs, CHU, FCHVs, Immunization, or gaon health section). The HP was also a major recipient of technical support from NGOs. NGOs provided technical support to the Gaonpalika as well as the gaon health section, with the Gaonpalika considered stronger than the link with the gaon health section. There was no technical support provided, according to participants, to the ward office, PHC/ORC, or youth clubs.


In the influence-connections matrix below (Figure 16), we see that the HP and Gaonpalika had high

influence and high connections (top right quadrant). Interestingly, FCHVs, schools, and immunization

had high influence but few connections (top left quadrant).

Figure 16. Influence-Connections matrix for local-level SBC for health from the perspective of stakeholders at the local level (Surkhet: Barahtal Rural Municipality).9




• Closeness: The Gaonpalika and the HP had, based on the map in Figure 15, the closest links with

all actors.

• Betweenness: The Gaonpalika and the HP also had the most important intermediary roles by

linking other actors that may not necessarily have relationships with one another.

Summary of actors and types of linkages across maps

Table 2 provides an overall picture of the types of actors identified by participants at the central,

provincial, and local levels. A comparison of maps from the central, provincial, and local levels suggested

that government agencies, donors, NGOs, and INGOs were most often considered important actors in

SBC for health at the local level. Across all levels, government actors were identified as key influencers

of local-level SBC. However, there were differences in the types of actors identified between central,

provincial, and local levels:

• At the central level, NGOs or social groups were not identified as significant group types, while

all groups at the provincial and local levels identified NGOs as important actors in local-level

SBC.

• Community-based organizations (CBOs) were identified in nearly all local-level maps, but not

frequently at the provincial or central levels.

• Private sector actors were only identified by two groups across all maps, suggesting that either

1) there remains minimal private sector involvement in who influences local-level SBC for health

or 2) they are not considered primary players in the local-level SBC system.

TABLE 2. NUMBER OF ACTORS, BY TYPE, AND THEIR DISTRIBUTION ACROSS CENTRAL, PROVINCIAL, AND LOCAL LEVELS NUMBER OF ACTORS OF EACH TYPE IDENTIFIED*

CENTRAL PROVINCIAL LOCAL

TYPES OF ACTORS IDENTIFIED

CENTRAL (2 GROUPS)

KARNALI PROVINCE

JUMLA (CHANDANNATH)

JUMLA (GUTHICHAUR)

SURKHET (PANCHAPURI)

SURKHET (BARAHTAL)

Government 6 3 7 4 4 9 8

Donors 2

INGOs 7 5 3 5 2

INGOs/UN/Donors 5

Leaders/community leaders

2 1 1

Media 1 1 1

CBOs 1 4 3 2

Private sector 3 2

NGOs 2 3 4 2 6

Social 3

*Note: if there are no numbers in a particular cell, that indicates that there were no actors identified as that type of actor.


Table 3 shows the types of links that different stakeholders identified between relevant actors

influencing local-level SBC for health. Across all levels, linkages between actors based on funding and

provision of technical support, assistance, or capacity building were identified as important ways that

actors influencing local-level SBC for health were linked. Less commonly identified were connections

between actors based on program implementation, advocacy, collaboration, and having a common goal.

The most common links varied in maps developed at the central, provincial, and local levels:

• Central level: Collaboration and having a common goal were the most common links that

stakeholders identified when thinking about how key SBC influencers are related to other actors

in the SBC system.

• Provincial level: Stakeholders identified technical support, assistance, or capacity building most

commonly.

• Local level: Data or information sharing, funding, and authority or supervision were highlighted

as key ways in which actors influencing local-level SBC for health were linked.

TABLE 3. NUMBER OF LINKS, BY LINK TYPE NUMBER OF LINKS OF EACH TYPE IDENTIFIED*


TYPES OF LINKS IDENTIFIED

CENTRAL (2 GROUPS)

KARNALI PROVINCE

JUMLA (CHANDANNATH)

JUMLA (GUTHICHAUR)


SURKHET (BARAHTAL)

Data or information sharing

26 14 28 15 44

Funding 13 16 14 14 10 11 21

Authority or supervision

10 5 11 30 17

Collaboration 32

Common goal 22

Technical support, technical assistance, or capacity building

23 5 18 5 11 19 14

Program implementation

7 7

Advocacy 5


Cross-cutting themes across maps

We outline below a set of overarching themes that emerged during the landscape analysis workshops at

the central, provincial, and local levels.

At the central level, a comparison of maps depicting who influences local-level SBC for health in Nepal

suggested that:

3) Government actors at the central level (e.g. MoHP, Department of Health Services (DoHS), and NHEICC) were assigned more relationships than were government actors at the local level (e.g.


female community health volunteers or FCHVs, local health institutions, or locally elected representatives) according to maps developed at the central level.

4) NHEICC was considered to have relationships with a variety of INGOs. 5) There were minimal linkages between local-level and central-level actors.


2) The most influential actors were local-level government actors including FCHVs, DHOs, and HMG. In contrast, INGOs had fewer connections with one another or to other actors.

3) UNICEF had only one direct link: to the DHO.

At the local level:

3) The local-level government (Nagarpalika, RMCP, etc.) typically had the greatest influence. DHOs or central-level government actors were not identified.

4) There were variations in key players across gaon and Nagarpalikas. 5) FCHVs and schools had influential roles in some maps, but not all. For those who saw FCHVs as

influential, they were shown to play important mediating roles between the Nagarpalika, HP, and HMGs. However, there were minimal linkages between education-related actors (e.g. schools) and health-related actors (e.g. HPs, FCHVs, etc.)

6) Minimal linkages between community-based organizations or between local level organizations (e.g. between HMGs and youth clubs).


Who influences how data on health is used in SBC programs?

Central level

In figure 17 below, a complete Net-Map depicting relevant actors and linkages is shown. This map

illustrates, according to participants at the central level, who influences how data on health is used in

SBC programs.

Figure 17. Map, created using DataMuse, depicting who influences how data on health is used in SBC programs from the perspective of stakeholders at the central level.

Actors

There were total of 16 actors identified by participants exploring how data on health is used in SBC

programs. Of those actors, most were donors (6) and government (4). The Department of Health

Services (DoHS), within the Ministry of Health and Population (MoHP) was considered to have the most

influence, with other donors such as USAID, DFID, and UNICEF also influential. NHEICC was the second-

most influential government actor. Actors with the least influence were those that were responsible for

or more closely involved in data collection, including Central Bureau of Statistics (CBS) or Institute of

Medicine (IOM) or research organizations such as HERD International, Valley Research Group Private

Limited (VaRG), Center for Research on Environment Health and Population Activities (CREHPA), and

New Era. DoHS and NHEICC had the most linkages with other actors, showing their important


connecting role in this network either collaborating or holding authority over other actors (particularly

those collecting data). In contrast, research organizations and academic institutions had fewer linkages.

Most often, they shared information with funders, received funding from key donors, and were under

the authority of either the DoHS or NHEICC. There were some collaborations specified with these

government actors or donors as well.

Linkages

Below is a summary, based on Figure 17, of the types of linkages that participants at the central level identified between actors influential in how data on health is used in SBC programs.

• Funding: Donors were shown as funding academic institutions and research institutions like JHU, IOM, New Era, CREHPA, VaRG, and HERD International. No funding links were shown from NHEICC, IOM or Nepal Health Research Council (NHRC) to these research organizations. Donors also provided, according to participants at the central level, funding to government actors (e.g. UNICEF to NHEICC or to DoHS).

• Collaboration: According to workshop participants, DoHS collaborated with most actors, and these collaborations were most often considered strong connections. There was bidirectional collaboration between Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) and some of the research organizations (i.e. from GIZ to a research organization and from a research organization to GIZ) like HERD International or VaRG, but these were not considered strong links.

• Technical assistance: DoHS and NHEICC were thought to be the two recipients of technical assistance. Donors like USAID as well as JHU provided technical assistance to these two government actors, with strong links primarily between donors and DoHS or NHEICC. Technical assistance was not specified for other actors (e.g. research organizations or other government actors).

• Authority: DoHS and NHEICC were depicted as having authority over all other actors, including other government actors as well as academic institutions, research organizations, or donors. There was no differentiation based on strength of authority, suggesting that their authority was similar across the network.

• Information sharing: Information sharing was understood by participants to be primarily a unidirectional relationship (i.e. from one actor to another, but not reciprocal), with information thought to flow from research organizations back to donors or to NHEICC. Academic institutions and other governmental actors (e.g. CBS or NHRC) were thought to share information with NHEICC. There was minimal information sharing between academic institutions and research organizations (except from VaRG to JHU) or between donors (except between GIZ and UNFPA and UNFPA and WHO). In contrast, WHO and DoHS had a strong bidirectional flow of information as compared to other information sharing depicted in the map.


In Figure 18 below, a matrix compares the number of connections of each actor with their influence. As

this figure suggests, government actors (NHEICC and DoHS) had higher influence and higher connections

(top right quadrant), while research agencies and academic institutions had fewer links and less

influence (bottom left quadrant). USAID and DFID were considered to have high influence over how data


on health are used, but they were considered to have few connections as compared to government

actors like NHEICC and DoHS (top left quadrant).

Figure 18. Influence-Connections matrix for how data on health is used in SBC programs from the perspective of stakeholders at the central level.


• Closeness: NHEICC and DoHS had the highest closeness centrality scores, suggesting they are

the most direct links to other actors in the map shown in Figure 17.

• Betweenness: DoHS and NHEICC played the most important connecting roles by linking other

actors that may not necessarily have relationships with one another. One example of this

intermediary or bridging role is DoHS’s intermediary connection between NHEICC and GIZ in

terms of collaboration. While DoHS collaborated with both NHEICC and GIZ, NHEICC and GIZ did

not have a direct relationship based on collaboration.

Provincial level

Figure 19 below shows a complete Net-Map of relevant actors and linkages from the perspectives of key

stakeholders at the provincial level. This map illustrates, from their perspectives, who influences how

data is used in SBC programs in Nepal.


Figure 19. Map, created using DataMuse, depicting who influences how data on health is used in SBC programs from the perspective of stakeholders at the provincial level.

Actors

A total of 15 actors or groups of actors were identified, including government actors (7), NGOs (4), and

private actors (4). One INGO was also highlighted as being a key actor in how data on health is used: INF.

According to stakeholders at the provincial level, the DHO was the most influential actor, with PHD also

considered to have high influence as compared to other actors. Private actors like nursing homes and

medical facilities had few links to NGOs or government actors and were considered to have less

influence over how data on health are used in SBC programs in Nepal.

Linkages

Below is a summary, based on Figure 19, of the types of linkages that participants at the provincial level

identified between actors influential in how data on health is used in SBC programs.

• Information: According to participants at the provincial level, information flowed in both one

direction (e.g. from Suaahara, Women Association for Marginalized Women (WAM), or

International Fellowship (INF) to DHO) and bidirectionally (e.g. between DHO and CRS or

between the DHO and PHD). CRS, rural or municipal palikas, and CRS had the greatest number of

linkages related to information sharing. CRS shared with the Family Planning Association of

Nepal (FPAN), the DHO, as well as other private actors such as the media, nursing homes, and

medical facilities. Rural and municipal palikas received information, according to participants,

from both NGOs like Suaahara, WAM, or AWAJ and other government actors like FCHVs and

hospitals or HPs. Finally, the DHO received information primarily from NGOs (Suaahara or

WAM), CRS, and PHD. There was no evidence of information sharing between private actors and

rural or municipal palikas in this map.

• Financial support: Financial support related to using data on health for SBC programs was

segregated between private actors (from CRS to the media, nursing homes, and medical


facilities) and government actors in the map shown in Figure 19. SDM was considered a primary

funding source for rural or municipal palikas and PHD, while the DHO was considered a funding

source for hospitals or HPs, who then provided financial support to FCHVs. There were no

funding linkages between private and government actors and NGOs or INGOs.

• Capacity building: The majority of capacity building linkages shown in Figure 19 were between

NGOs and INGOs and local government actors such as FCHVs (6) and hospital or HPs (5). NGOs

and INGOs were the primary providers of capacity building. The DHO and WAM were considered

to provide capacity building to R/M palikas, but this linkage was considered to be less strong

than other capacity building linkages with other actors. There were no capacity building linkages

between private actors and non-private actors. CRS provided capacity building exclusively to

nursing homes and medical facilities.

• Coordination: Coordination was primarily thought to be a bidirectional linkage, suggesting that

two actors coordinated efforts towards using data on health for SBC programs. According to

participants, NGOs such as WAM and AWAJ coordinated with multiple government actors (e.g.

R/M palikas, hospitals or HPs, or the DHO) and INF. Among government actors, the DHO and

PHD coordinated with multiple governmental and non-governmental actors. Similar to

information sharing, SDM coordinated solely with PHD. Private actors had minimal coordination

with other actors; while CRS coordinated with DHO, this linkage was considered less strong than

others. Non-governmental actors did not have as much coordination with one another as they

did with government actors or as did government actors with one another. While WAM

coordinated with Suaahara, and AWAJ with FPAN, these linkages were unidirectional.


In the influence-connections matrix below (Figure 20), the DHO was considered to have the highest

influence and most connections (top right quadrant). Other government actors such as PHD and

hospitals or HPs also had high influence and a high number of connections related to how data on health

are used in SBC programs. CRS and AWAJ and fell in this top right quadrant, suggesting that these actors

are important stakeholders with whom to consult on data use for SBC programs according to

participants at the provincial level.

Interestingly, FCHVs and R/M palikas as well as WAM were considered to have a high number of

connections, but less influence over how data on health are used (bottom right quadrant). Activities to

increase their influence over data use could be used to strengthen their roles in and ownership over SBC

for health at the local level.


Figure 20. Influence-Connections matrix for how data on health is used in SBC programs from the perspective of stakeholders at the provincial level.10


• Closeness: The DHO and the R/M palikas had the highest closeness centrality scores, suggesting

they had the most direct links to other actors in the map in Figure 19.

• Betweenness: CRS and the DHO played the most important connecting role by linking other

actors that may not necessarily have relationships with one another (e.g. between the media

and the DHO). This illustrates the importance of coordinating activities with these actors.

Local level

Jumla: ChandanNath Urban Municipality


stakeholders in one palika in Jumla (ChandanNath Urban Municipality). This map illustrates, from their

perspectives, who influences how data is used in SBC programs in Nepal.



Figure 21. Map, created using DataMuse, depicting who influences how data on health is used in SBC programs from the perspective of stakeholders at the local level (Jumla: ChandanNath Urban Municipality).

Actors

A total of 16 actors or groups of actors were identified, including government actors (6) and INGOs (4).

NGOs (3), private actors (2), and academic institutions (1) were also highlighted. According to

stakeholders in Jumla (ChandanNath Urban Municipality), the municipality and the HP had the greatest

influence over how data on health are used in SBC programs in Nepal. While there was only one

academic institution highlighted as an important actor, it – as well as the DHO – was also considered to

have a large influence over how data on health are used. In comparison, private actors, INGOs, and

NGOs had significantly less influence and fewer connections to influential actors.

Linkages

Below is a summary, based on Figure 21, of the types of linkages that participants at the local level

(Jumla: ChandanNath Urban Municipality) identified between actors influential in how data on health is

used in SBC programs.

• Funding: Funding came primarily from government actors according to participants. The

municipality provided funding to other government actors such as HPs, ward palikas, and FCHVs

directly. The municipality was also thought to provide funding to Women Dev and Karnali

Academy of Health Sciences (KAHS). The HP received funding from both the municipality and

the ward palika and funded FCHVs independently as well. FCHVs received funding from three

sources: the HP, municipality, and ward palika. The DHO and municipality provided funding to


KAHS as well. There was a weak funding link also identified between WFP and MDI, but this was

considered less strong than those linkages with government actors.

• Technical support: KAHS was a primary source of technical support for actors on use of data on

health for SBC programs. KAHS was thought to provide technical support to government actors

(e.g. HP, municipality, ward palikas, and FCHVs) as well as NGOs (e.g. Women Dev and MDI),

private actors (e.g. medical facilities), and INGOs (e.g. MSI and INF). Other sources of technical

support were SSBH, who provided support exclusively to government actors at multiple levels

(the DHO, municipality, ward palika, and HP). However, the technical support provided to the

ward palika was considered less than that provided to other government actors. Government

actors were typically recipients of technical support rather than providers of such support

(except in the case of the DHO providing technical support to the HP). Most NGOs and INGOs

provided inconsistent technical support. For example, WFP was thought to provide technical

support to MDI only. MSMP provided support exclusively to the municipality. Women Dev and

N-CRS provided some support to FCHVs.

• Advocacy: The map in Figure 19 showed that the municipality was the sole recipient of advocacy

on use of data on health for SBC programs. KAHS, MSMP, SSBH, and the DHO were considered

to be sources of advocacy for the municipality. Ward palikas or HPs, however, had no

relationships based on advocacy with other actors.

• Data sharing: Data sharing was both a unidirectional relationship (e.g. from INF to the HP) and a

bidirectional relationship (e.g. between KAHS and the HP) in the map developed by participants

(Figure 19). The municipality had the largest number of data sharing connections with other

actors (7). The municipality shared data with the academic institution (KAHS) as well as NGOs,

INGOs, and other government actors. The HP also had a large number (6) of bidirectional data

sharing relationships with government and non-governmental actors. The ward palika had only

one data sharing relationship: with MSMP. N-CRS was considered to have only one data sharing

relationship with other actors: with the HP. FCHVs shared data with the municipality and the HP,

but not with other actors. The DHO was the only actor to have a data sharing relationship with

the Statistics office according to participants.


In the influence-connections matrix below (Figure 22), the municipality was considered to have the

highest influence and most connections (top right quadrant). The HP and KAHS also had high

influence and a high number of connections related to how data on health are used in SBC

programs. Importantly, other government actors such as the DHO, ward palika, and FCHVs were

thought to have a large influence over use of data on health for SBC programs, but they had few

connections with other actors in the system (top left quadrant). Activities to facilitate connections

with other actors (governmental and non-governmental) that encourage data sharing, for example,

could strengthen how data are used in SBC programs at the local level.


Figure 22. Influence-Connections matrix for how data on health is used in SBC programs from the perspective of stakeholders at the local level (Jumla: ChandanNath Urban Municipality).11


• Closeness: The HP, municipality, and KAHS were most directly linked to all actors in the map in Figure 21.

• Betweenness: The academic institution, KAHS, played the most important connecting role by linking other actors that may not necessarily have relationships with one another (e.g. between the HP and MSI). This illustrates the importance of coordinating activities with this academic institution.

Jumla: GuthiChaur Rural Municipality


stakeholders in Jumla (GuthiChaur Rural Municipality). This map illustrates, from their perspectives, who

influences how data is used in SBC programs in Nepal.



Figure 23. Map, created using DataMuse, depicting who influences how data on health is used in SBC programs from the perspective of stakeholders at the local level (Jumla: GuthiChaur Rural Municipality).

Actors

A total of 16 actors or groups of actors were identified, including government actors (7) and NGOs (3)

and INGOs (3). CBOs (2) and private actors (1) were also highlighted. According to stakeholders in Jumla

(GuthiChaur Rural Municipality), the Gaonpalika had the greatest influence over how data on health are

used in SBC programs in Nepal. The DHO had the second greatest influence over how data on health are

used. The most influence was held, according to participants, by government actors. In comparison,

private actors, INGOs, CBOs, and NGOs had significantly less influence and fewer connections to

influential actors.

Linkages


(Jumla: GuthiChaur Rural Municipality) identified between actors influential in how data on health is


• Funding: According to participants, funding came primarily from government actors including

NSMP and the Gaonpalika. NSMP provided funding for the Gaonpalika, while the Gaonpalika

provided funding to both other government actors (e.g. HPs, schools, or the ward) and CBOs

(e.g. HMGs). The HMGs also received funding from Shangri-La Association according to

participants. Other sources of funding were INGOs including Plan International (funding Shangri-

La Association, an NGO), SSBH (funding HPs directly), and Breakthrough ACTION (funding the

Gaonpalika). The ward was an intermediate, receiving funding from the Gaonpalika and in turn

funding child clubs.

• Technical support: Technical support was thought to be both provided to influential

government actors (e.g. the Gaonpalika or the HP) and provided by them (e.g. Gaonpalika


providing technical support to schools or HPs providing support to FCHVs). Primary sources of

technical support were SSBH (providing technical support to medical facilities as well as

government actors like the Gaonpalika, HPs, or ward) and the DHO (providing support to HPs

and FCHVs directly as well as HMGs). NSMP also provided technical support to HPs and ward.

There were no connections between the ward and the FCHVs or schools in terms of technical

support according to participants.

• Advocacy: The Gaonpalika was the sole recipient of advocacy, with NSMP considered to have a

strong advocacy relationship with the Gaonpalika. Breakthrough ACTION and SSBH were also

considered to advocate with the Gaonpalika (Breakthrough ACTION more strongly than SSBH).

• Data sharing: The Gaonpalika had the greatest number of actors that had shared data with

them in the map shown in Figure 23. The Gaonpalika received data from NSMP, the DHO, and

SSBH and shared data with them (bidirectional relationships). In addition, the Gaonpalika

received data from the HP and provided data to Breakthrough ACTION. In contrast, the HP was

thought to provide data to the largest number of actors, including other government actors

(NSMP, the Gaonpalika, DHO, ward, and school), NGOs (MDI and CASDA), and INGOs

(Breakthrough ACTION). FCHVs shared data with both the HMGs and the ward (although this

relationship was considered less strong than other data sharing linkages in the system). The

NGOs and INGOs did not share data with one another according to participants.


In the influence-connections matrix below (Figure 24), the Gaonpalika was considered to have the

highest influence and most connections (top right quadrant). The DHO also had high influence, but a

smaller number of connections related to how data on health are used in SBC programs (top left

quadrant). In contrast, the HP had a large number of connections but less influence (bottom right

quadrant). In contrast, other actors were considered to have limited influence and few connections

related to how data on health are used in SBC programs. Activities to facilitate connections between

influential government actors and other actors in the system could strengthen how data are used in

SBC programs at the local level.


Figure 24. Influence-Connections matrix for how data on health is used in SBC programs from the perspective of stakeholders at the local level (Jumla: GuthiChaur Rural Municipality).12


• Closeness: The Gaonpalika had the most direct links to all actors in the map in Figure 23.

• Betweenness: The HPs, Gaonpalika, and most interestingly HMGs played the most important connecting roles by linking other actors that may not necessarily have relationships with one another (e.g. Shangri-La Association and FCHVs or the Gaonpalika). This illustrates the importance of coordinating activities with not only HPs and the Gaonpalika, but also at the local level with HMGs.

Surkhet: Panchapuri Urban Municipality


stakeholders in Surkhet (Panchapuri Urban Municipality). This map illustrates, from their perspectives,

who influences how data is used in SBC programs in Nepal.



Figure 25. Map, created using DataMuse, depicting who influences how data on health is used in SBC programs from the perspective of stakeholders at the local level (Surkhet: Panchapuri Urban Municipality).

Actors

A total of 11 actors or groups of actors were identified, with government actors (8) the most common

type of actor. NGOs (2) and private actors (1) were also highlighted. According to stakeholders in

Surkhet (Panchapuri Urban Municipality), the health unit had the greatest influence over how data on

health are used in SBC programs in Nepal. The FCHVs had the second greatest influence over how data

on health are used. While government actors had the most influence, NGOs and the private actor had

significantly less influence and fewer connections to influential actors.

Linkages


(Surkhet: Panchapuri Urban Municipality) identified between actors influential in how data on health is


• Funding: According to participants, the health unit provided funding to government actors such

as the CHU, HP, PHC, and FCHVs. The health unit was also a key recipient of funding from both

governmental actors (e.g. the District Public Health Office (DPHO)) and NGOs (Breakthrough

ACTION and Suaahara).

• Rights and responsibilities: According to participants in Surkhet (Panchapuri Urban

Municipality), the health unit was the source of rights and responsibilities over how data on

health are used, with linkages with nearly all actors (except FCHVs). The HP also had important

linkages with Suaahara and FCHVs regarding rights and responsibilities.

• Technical support: The DPHO and FPAN were key sources of technical support to government

actors (e.g. CHU, PHC, HPs, or the health unit) in the map shown in Figure 25. In addition, the HP


provided technical support to the DPHO, and the DPHO provided technical support to FPAN. The

health unit was an important intermediary regarding provision and receipt of technical support.

The health unit received technical support from higher-level government actors (e.g. DPHO or

FPAN) or NGOs (e.g. Breakthrough ACTION). Then, the health unit was thought to provide

technical support to lower-level government actors (e.g. HPs, PHC, CHUs, or FCHVs). NGOs were

considered to also provide technical support to other government actors as well; Suaahara was

a source of direct support to FCHVs, while Breakthrough ACTION offered technical support to

the CHU as well as HPs. Schools received technical support from both the health unit and the

DPHO directly.

• Information sharing: Information sharing was understood as a bidirectional relationship

between actors, with information flowing to and from both actors. The health unit had the

greatest number of actors to whom they were linked through information sharing relationships

according to participants. However, other actors had few data sharing relationships with one

another. While FPAN shared information bidirectionally with the HP, PHC, and the health unit,

other government actors were thought to share information bidirectionally with the health unit

only. However, the health unit did not have direct information sharing relationships with the

DPHO, CRS, or FCHVs. According to participants, schools only shared information with the health

unit, and FCHVs only shared information with Suaahara directly. While Breakthrough ACTION

had a strong relationship with the health unit, it did not have data sharing relationships with

other actors.


In the influence-connections matrix below (Figure 26), the health unit was considered to have the

highest influence and most connections (top right quadrant). The FCHV, HP, and PHC also had high

influence, but a smaller number of connections related to how data on health are used in SBC programs

(top left quadrant). In contrast, other actors were considered to have limited influence and few

connections related to how data on health are used in SBC programs. Activities to facilitate connections

between influential government actors and other actors in the system could strengthen how data are

used in SBC programs at the local level.


Figure 26. Influence-Connections matrix for how data on health is used in SBC programs from the perspective of stakeholders at the local level (Surkhet: Panchapuri Urban Municipality).13


• Closeness: The health unit and DPHO had the most direct links to all actors in the map shown in Figure 25.

• Betweenness: The health unit and DPHO played the most important connecting roles by linking other actors that may not necessarily have relationships with one another (e.g. CHU and FCHVs or Breakthrough ACTION and FCHVs).

Surkhet: Barahtal Rural Municipality


stakeholders in Surkhet (Barahtal Rural Municipality). This map illustrates, from their perspectives, who

influences how data is used in SBC programs in Nepal.



Figure 27. Map, created using DataMuse, depicting who influences how data on health is used in SBC programs from the perspective of stakeholders at the local level (Surkhet: Barahtal Rural Municipality).

Actors

A total of 17 actors or groups of actors were identified, with government actors (12) the most common

type of actor. NGOs (2), local social networks (1), private actors (1), and INGOs (1) were also highlighted.

According to stakeholders in Surkhet (Barahtal Rural Municipality), and similar to what stakeholders in

Surkhet (Panchapuri Urban Municipality) described, the HP had the greatest influence over how data on

health are used in SBC programs in Nepal. The FCHVs had the second greatest influence over how data

on health are used according to both Surkhet-based groups. While government actors had the most

influence, other types of actors were considered to have less influence.

Linkages


(Surkhet: Barahtal Rural Municipality) identified between actors influential in how data on health is used

in SBC programs.

• Funding: According to participants, funding overwhelmingly was limited to government actors

and came primarily from the Gaonpalika. The Gaonpalika was considered a strong source of

funding for schools, the ward office, CHU, HP, and child and youth clubs. It also provided

funding, although considered to be weaker, to the gaon health section, FCHVs, and PHC/ORC.

Receiving funding from the Gaonpalika, the ward office was also a source of funding for other

government actors such as the HP or schools as well as the child and youth clubs. In addition,

Social Awareness Center Nepal (SAC Nepal) was thought to provide additional funding to the

gaon health section.

• Technical support: Non-governmental actors were considered to be primary sources of

technical support (e.g. SAC Nepal, SIFPO II, or the Peace Corps). SAC Nepal provided technical


support to schools, PHC/ORC, the ward office, the gaon health section, and the HP. SIFPO II

offered technical support to the HP, HMGs, and gaon health section. The Gaonpalika also

provided such support to other government actors such as the HP or gaon health section.

Importantly, the HMGs and the FCHVs were shown to have a bidirectional relationship regarding

provision of technical support. The gaon health section received technical support from multiple

sources, including SAC Nepal, the Gaonpalika, SIFPO II, and Peace Corps. According to

participants in Surkhet (Barahtal Rural Municipality), several government actors were often both

the recipients and providers of technical support. For example, the HP received technical

support from both government and non-governmental actors: CHU, the Gaonpalika, SIFPO II,

SAC Nepal, and Peace Corps. The HP also provided technical support to CHU, FCHVs, and Peace

Corps.

• Information sharing: Information sharing was considered to be both unidirectional and

bidirectional. Multiple actors shared information with the HP (12), while the HP shared

information with 10 other actors. Other actors with multiple relationships based on information

sharing included SAC Nepal, the gaon health section, and FCHVs. In addition, some government

actors were important sources of information but did not have information shared with them

(e.g. Gaonpalika, regional hospitals, or immunization clinics). Some actors were only connected

with one other actor to share information. For example, schools only shared information with

CHUs, and medical clinics, immunization clinics, regional hospitals, and child and youth clubs

were only linked with the HP.

• Authority: According to participants, authority over use of data on health for SBC programs was

held by multiple government actors including the Gaonpalika, who were thought to have

authority over NGOs such as SAC Nepal and SIFPO II as well as medical clinics and other

government actors such as the gaon health section, and health insurance. In turn, the gaon

health section was considered to have authority over the HPm health insurance, and medical

clinics. The ward office was considered to have authority over CHU, the HP, and the health

insurance as well. Finally, the HP then had the authority over local-level actors such as PHC/ORC,

HMGs, and FCHVs. According to participants, several government actors were under multiple

levels of authority. Health insurance was under the purview of three other government actors,

and the HP and CHU under the authority of two government actors.


In the influence-connections matrix below (Figure 28), the HP was considered to have the highest

influence and most connections (top right quadrant). The gaon health section also had a large number of

connections, but less influence (bottom right quadrant) related to how data on health are used in SBC

programs. In contrast, FCHVs had few connections, but were considered to have greater influence over

how data are used (top left quadrant).


Figure 28. Influence-Connections matrix for how data on health is used in SBC programs from the perspective of stakeholders at the local level (Surkhet: Barahtal Rural Municipality).14


• Closeness: The HP had the closest links to all actors in the map shown in Figure 27. The gaon health section and Gaonpalika also were closely linked to other actors.

• Betweenness: The HP played the most important connecting role by linking other actors that may not necessarily have relationships with one another (e.g. Gaonpalika and HMGs).

Summary of actors and types of linkages across maps

Table X provides an overall picture of the types of actors identified by each group across central,

provincial, and local levels. Evident across all groups was the number of government agencies, NGOs,

and INGOs that considered important actors in who influences how data on health is used in SBC

programs. Across all levels, government actors were identified as key influencers of how data is used.

There were significant differences, however, in the types of actors identified between central and

provincial and local levels.

• At the central level, academic institutions (e.g. JHU) and research organizations (e.g. HERD

International) were highlighted as important actor types, while only one group at the provincial

and local levels identified any academic institutions or research organizations as key actors in

how data on health is used in SBC programs. This was in Jumla (ChandanNath Urban

Municipality), where the KAHS was included as a key actor.

• Similarly, NGOs, private organizations, and INGOs (were identified in nearly all local-level maps,

but were not considered important actors in use of data on health at the central level.



• Community-based organizations or local social networks were only identified by two groups

(one in Jumla and one in Surkhet), which indicates the minimal involvement and influence of

local organizations in data use for SBC programs.

TABLE 4. NUMBER OF ACTORS, BY TYPE, AND THEIR DISTRIBUTION ACROSS CENTRAL, PROVINCIAL, AND LOCAL LEVELS NUMBER OF ACTORS OF EACH TYPE IDENTIFIED*


TYPES OF ACTORS IDENTIFIED

CENTRAL

KARNALI PROVINCE

JUMLA (CHANDANNATH)

JUMLA (GUTHICHAUR)


SURKHET (BARAHTAL)

Government 4 6 6 7 8 12

Donors 6

Academic institutions

2 1

Research organizations

4

NGOs 4 3 3 2 2

Private 4 2 1 1 1

INGO 1 4 3 1

CBOs/social networks

2 1


Table 4 shows the types of links that different stakeholders identified between relevant actors

influencing how data on health are used for SBC programs. Across all levels, linkages between actors

based on data or information sharing, funding, and provision of technical support, assistance, or

capacity building were depicted on maps created, suggesting that these avenues were consistently

considered important ways that actors influencing how data are used were linked. Less commonly

identified were connections between actors based on authority or supervision, primarily a concern from

the group at the central level and one group in Surkhet (Barahtal Rural Municipality). Similarly,

collaboration or coordination was only recognized as an important type of link for participants from the

central and provincial levels, which may suggest the importance placed by participants at these levels in

how to foster collaboration in data use for SBC programs. Advocacy was an important way that

participants from Jumla (both palikas) identified that actors were linked together to influence how data

are used.

At the central and provincial levels, 1) collaboration and 2) data or information sharing were the most

common links that stakeholders identified when thinking about how actors related to other actors to

influence how data are used in SBC programs. Across all four maps drawn at the local level, 1) data or

information sharing and 2) technical support, technical assistance, or capacity building were highlighted

as the most common ways through which actors influencing how data are used were linked together.

These differences suggest that priorities between actors at the central and provincial levels as compared

to the local levels in terms of how data are used in SBC programs may differ. More specifically,


collaboration and coordination may be a pivotal way for actors to interact at higher government levels,

while at the local level these actors interact in more hands-on ways to influence how data are used.

TABLE 5. NUMBER OF LINKS, BY LINK TYPE NUMBER OF LINKS OF EACH TYPE IDENTIFIED*


TYPES OF LINKS IDENTIFIED

CENTRAL KARNALI PROVINCE

JUMLA (CHANDANNATH)

JUMLA (GUTHICHAUR)


SURKHET (BARAHTAL)

Data or information sharing

37 22 29 21 22 57

Funding 25 7 10 10 7 13

Authority or supervision

30 15

Collaboration or coordination

40 33

Technical support, technical assistance, or capacity building

12 15 20 14 20 22

Advocacy 4 3

Rights and responsibilities

10


Cross-cutting themes across maps

We outline below a set of overarching themes that emerged during the landscape analysis workshops at

the central, provincial, and local levels.

At the central level, a comparison of maps depicting who influences how data on health are used in SBC

programs in Nepal suggested that:

2) There were a number of research organizations and academic institutions involved in how data are used in SBC programs from the perspective of stakeholders at the central level. However, there were few linkages between these actors, suggesting that coordination and collaboration are minimal as these organizations typically work on specific funder-driver agendas. These actors had minimal influence over how data are used and were typically simply considered to be providers of information.

3) INGOs were considered to play key roles in data use at the central level, with actors such as GIZ, UNFPA, WHO, UNICEF, DFID, and USAID highlighted by participants as major sources of funding.

4) Certain government actors (e.g. NHEICC or DoHS) with large influence and authority were major recipients of technical assistance. These actors also tended to collaborate with more actors in the system than did others who benefitted less often from technical assistance.



3) Actors and types of linkages specified were more similar to those described at the local level rather than at the central level.

4) The DHO and PHD were key influential actors in how data are used in SBC programs. 5) In comparison with the central-level map, more NGOs and fewer INGOs were included as key

actors. In addition, the number of government actors grew and diversified, with government actors from multiple levels (e.g. from FCHVs to R/M palikas to hospitals or HPs to DHOs) outlined as playing important roles in how data are used.

6) While private actors like CRS were considered as actors in this map, there were minimal linkages between these actors and governmental or non-governmental actors in terms of how data are used in SBC programs.

At the local level:

4) While the DHO remained an important actor in most local-level maps, maps drawn in Jumla and Surkhet more often highlighted municipalities, Gaonpalikas, and health units/posts as influential actors in how data are used in SBC programs.

5) FCHVs were considered, across all four maps, to have significant influence and to have linkages to both government and non-government actors. FCHVs were shown to play important mediating roles between certain government actors and HMGs.

6) While schools were included in some maps, there were minimal linkages between education-related actors (e.g. schools) and health-related actors (e.g. HPs, FCHVs, etc.)

7) There were variations in key players across gaon and Nagarpalikas. 8) In comparison to the prominent role of academic institutions and research firms at the central

level, academic institutions were only included in one local-level map: Jumla (ChandanNath Urban Municipality).

9) Groups often highlighted a number of government actors, with minimal participation in non-governmental (be it private, NGO, or INGO) actors in how data are used in SBC programs.

10) There were minimal linkages between organizations within the same type of actor (i.e. between INGOs or between NGOs), which may suggest minimal coordination at the local level regarding how data are used.


Conclusion A comparison of Net-Maps developed during landscape analysis workshops at the central, provincial,

and local levels illustrated variation in 1) the types of actors considered influential to local-level SBC for

health and how data are used in SBC programs and 2) how those actors are linked to one another within

the SBC system. Some provincial actors were not present at the local level, and some local-level actors

were not present at the provincial level. Similarly, provincial and local-level stakeholders failed to

highlight central-level government actors as influential in local-level SBC. The absence of provincial-level

actors across maps for both guiding questions suggested that actors at the provincial level were not

perceived, at least among participants, to have significant influence over SBC for health or use of data

on health in SBC programs. While the system continues to change and roles and responsibilities are

clarified, the provincial level has the opportunity to expand its coordinating role by establishing

networks with other influential actors in the SBC system.

Some actors were considered to have great influence over local-level SBC or how data are used and

many connections, while others had 1) limited influence with many connections or 2) great influence but

fewer connections. Using the matrices presented throughout this report, we see the opportunity to

segment audiences and to develop and lead tailored activities to address the needs of particular actors

within the SBC for health system at the local level. For example, actors with high influence and more

connections would be important guiding members of SBC committees involved in local-, provincial, or

central-level decision-making for health programs. Actors with many connections but minimal influence

could be important audiences to serve a coordinating role within the SBC system. Activities to

strengthen capacity in coordination would be useful for such actors. Finally, actors with high influence

but few connections could be important to incorporate into existing SBC networks to foster

collaboration across governmental and non-governmental actors. Opportunities for inter- or intra-

agency dialogue through activities such as technical working groups or learning exchanges could be

beneficial for such actors.

While some local-level actors were highlighted at the central level as key to local-level SBC, these actors

were most often FCHVs or the HP and not local-level governments. This may be a function of the recent

changes to the government system, with the local-level government’s roles and responsibilities

continuing to shift and expand. In the seven-step process for health decision-making for the annual

health program at the local level, 1) ward-level stakeholders (e.g. ward chairman) and 2) local-level

stakeholders (e.g. the health coordinator) are considered to be key players. However, findings from the

landscape analysis workshops did not consistently include these actors as key influencers in SBC for

health at the local level. Further efforts to identify those actors that interface with the ward chairman or

the health coordinator could inform activities designed to facilitate coordination and collaboration

across government levels for SBC for health programs. Activities should establish networks that link the

ward-level chairman or health coordinator with those actors considered to be influential. Committees


that support the health coordinator, for example, could be context-specific and composed of key actors

identified at the local level through maps like those developed here.

In maps developed to understand who influences how data on health are used in SBC programs,

provincial and local-level stakeholders routinely identified the DHO and/or DPHO as influential actors

with connections to both other government actors and non-governmental actors. As changes to the

federal system continue, the roles and responsibiltiies of this actor will shift, and we envision the results

of this Landscape Analysis Report to be invaluable to help identify those actors that will need to ensure

that the role currently played by district-level actors continues to be filled as the system changes

Across maps at the provincial and local levels, NGOs and INGOs were present, but central-level

government actors were typically not. At the central level, INGOs were present, but NGOs or local-level

government actors were often not present. While academic institutions and research firms were present

at the central level when identifying who influences how data are used in SBC programs, only one map

developed at the local level highlighted an academic institution as playing an influential role. These

variations illustrate visually the extent to which connections between the central, provincial, and local

levels are lacking and how the establishment and fostering of these connections within the new federal

health system could 1) improve opportunities for collaboration, technical support, and information

sharing to improve SBC at the local level.

Identified gaps and next steps

Clear throughout these maps were gaps that could be addressed through capacity strengthening

activities designed to foster collaboration across actors within the SBC for health system.

Some actors were considered to have significant influence and, simultaneously, limited connections,

such as FCHVs or other local-level actors (e.g. locally-elected representatives, CBOs, local health

institutions, etc.) in local-level SBC for health. Simultaneously, FCHVs were considered, across all four

maps at the local level, to have significant influence and to have linkages to both government and non-

government actors regarding how data are used in SBC programs. FCHVs were shown to play important

mediating roles between certain government actors and HMGs related to data use. This can be a priority

group for fostering connections and support.

There was a lack of perceived collaboration, common goal, or information sharing, related to how local-

level SBC for health takes place, among:

• Government actors and local-level community organizations or community leaders

• NHEICC and other governmental actors at the central, provincial, or local levels

• INGOs and NGOs


At the same time, participants in multiple workshops indicated minimal linkages between actors of the

same type (e.g. between INGOs or between NGOs), which may suggest minimal coordination at the local

level regarding how data are used.

Technical assistance was received primarily by government actors, with only a few actors working at the

local level providing technical assistance to CBOs or social actors on local-level SBC for health. Technical

assistance related to use of data on health for SBC programs was also typically focused on government

actors such as the DHO or the HPs, with less attention to partner organizations or to other more local

government actors (e.g. at the ward level).

Overwhelming differences in maps depicting how local-level SBC programs take place or how data are

used for SBC programs across central, provincial, and local levels demonstrated different understandings

of how SBC activities are planned for, designed, and implemented in Nepal. Coordination of actors,

including identification of agreed upon roles and responsibilities, could start to identify similarities

across maps to strengthen the system, fill gaps, and reduce inefficiencies.

Documents

Landscape Analysis Workshops in Nepal - The Compass€¦ · Landscape Analysis Workshop at the central level. Shreejana Kc conducted the workshops at the provincial and local levels