Using information technology for

resistance containment: Malaria

surveillance in the future moving toward elimination strategy • By

Wichai Satimai MD.,MA.,DTM&H

Bureau of Vector Borne diseases

Department of Disease Control

Ministry of Public Health Thailand

2.181.110.24 0

2

4

6

8

10

12

14

16

0

2

4

6

8

10

12

14

16

ABER SPR API

ABER & SPR / 100 pop. API / 1,000 pop.

Annual Blood Examination Rate (ABER), Slide PositivityRate (SPR) and

Annual Parasite Incidence (API/1,000), Thailand FY 1965 - 2011

Fiscal Year

38.2

60.8

0

20

40

60

80

100

1965 1968 1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010

P.falciparum P.vivax

Percentage

Fiscal Year

Proportion of malaria parasite species, Thailand, FY 1965-2011

P. falciparum

P. vivax

5

0

20

40

60

80

100

1965 1968 1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010

P.falciparum P.vivax

Percentage

Fiscal Year

CHL SP2 SP3 QT MSP M

2005 M+ATS whole country in 2005 (2days)

M

Proportion of malaria parasite species

in relation to the National drug policy, Thailand, FY 1965-2010

1973 SP 1985

MSP

1982

QT

1990 M

1995 M+ATS ; only in Trat, Chantaburi, Tak

1965

CHL

2008 M+ATS 3 days

7

1.Mae Hong Son

2.Tak

3.Kanchanaburi

4.Ratchaburi

5.Ranong

6.Ubon Ratchathania

7.Chanthaburi

8.Trat

9.Yala

9

5

4

1

2

3 6

8

7

Nine Provinces as Sentinel sites for monitoring of

drug resistance

Tak

2004 1997

Mef 25 mg/kg + Art 12 mg/kg for 2 days N ACPR% LTF% ETF% 1997: 38 89.5 10.5 0 2002: 39 92.3 5.4 2.6 2003: 71 96.6 3.4 0 2004: 47 86.5 13.5 0 2006: 46 89 11 0

2002 2003 2006

2003

2003 2002 1997 2004

2005 2004 1997 2002 2003 2006

TAK

2003 2002 1997 2004 2002

KB

2003 2002 2004 2005 2006

RB

2003 2002 1997 2004 1998 2000

RN

MHS CHM

2002

2005

2004

2003

1998

1997

TR

2004

2002

2003

CHB

2003

2002

1997

2004

1998

1999

UB

M3 M5A12 M3A12 2006

Result 3: Efficacy of CQ, 2009-2010

MH CB YL KN

No. recruited 56 55 53 48

Lost 6 5 0 0

Withdrawn) 2 0 0 0

No. analyzed 48 50 53 48

% Parasitaemia

Day 3 8.3 30 0 31.3

% ACPR 100 96 100 93.8

% ETF 0 0 0 0

% LCF 0 0 0 0

% LPF 0 4 0 6.2

11

Implementation Areas

Only Zone 1 areas use

Atovaquone/Proguanil

The rest follows the

national drug policy

Zone 1

Sakaeo

Srisaket

Chanthaburi

Trat

Burirum

Ubonratchathani

Surin

Table 2 Primer pairs and specific restriction enzymes for detecting 3 polymorphisms at codon 268

Primer pairs and specific restriction enzymes for detecting 3 polymorphisms

Codon 268 Type Primer pair Restriction Enzyme

Product size

(base pair)

Outer primer

CYTB1+CYTB2 939

TAT Wild type CYTB3+CYTB5 NsiI 359+25

TCT Y268S CYTB2+CYTB6 AlwNI 147+24

AAT Y268N CYTB2+CYTB7 SspI 150+24

NsiI cuts TAT; AlwNI cuts TCT; SspI cuts TAT and TCT, but not AAT

DNA Sequencing

Web-based malaria surveillance: Malaria surveillance in the future moving toward

malaria elimination in Thailand

Original System: Forms are recorded, and summarized on paper

Detected cases are plotted on household walking map

To provide effective management information

system capable of coordination at operational

staff to enable rapid and high quality

implementation of malaria elimination strategy

Objective

3 out of 6 Core Modules in Vector-Borne Disease Control

have been implemented

Epidemiology Module

Vector

Control Module

BCC

Module

Key Features • Case Management (Real time – Village V.S. household level

traceable) • Case detection

• Case Investigation

• Case Follow up

• Vector Control (Effectively distributed/controlled) • The most up-to-date population survey cover any risk areas

• LLIN /LLIHN distribution

• IRS action

• Impregnated Bed Net Distribution

• Behavioral Change Communication (Individual Home Visit

information can be sent to the center for evaluating the awareness of

residences within the target areas)

• Different type of reports displayed in different presentation format

(table, graph,GIS,etc.)

• Integrate into public heath routine tasks

• Simple and easy to interpret, and user friendly

Technologies

• Web-based synchronization technology

• capable of switching between offline / online mode of data entry. This

terminology is benefit for the low resources area. Users can still operate

in case of internet link has difficulties. Then data can be later

transferred when internet is back to normal.

• Mobile Computing

• simply disseminated or received information to/from different devices in

other platforms i.e. Mobile/ Tablet

• Geographical Information System (GIS) ready

• ability to toggle GIS in key element of indicators for better understanding of the situation in short term

Work & Data Flow

EP 1

EP 3 EP 1

Not Infected

Infected

• Case

investigation • Treatment

Day 0

• Drug compliance • Case follow-up

Day 1,2,3

Pf : Day 7,14,21,28,35,42 Pv: Day 7,14,21,28,60,90

• Case follow-up

• Case Detection

MIS

VIVO

EP 1 FU

Data Capturing for Case Management

Active Case/Passive Case Detection

Location Information

Diagnosis

Treatment

Infected Cases Follow Up Schedule generated automatically

Cases Follow Up can be done through Tablet 7 inches Device

Epidemiology Summary Report

Epidemiology Reports can be displayed in different format (Table, Bar Chart, Pie, or Line), and different time frame (monthly, Weekly)

Day 0 alert will be sent using SMS

on a daily basis and

Summary on a weekly basis

Maps in Malaria GIS (http://gis.biophics.org) 1. Number of Malaria Cases

2. Malaria Incidence

3. Proportion of PF Malaria Receiving ACT

4. Proportion of PV Malaria Receiving chloroquine and

primaquine

5. Percent of PF Malaria Receiving ACT and have DOT

6. Percent of PF Malaria Receiving ACT, DOT but Day 3

Positive

7. PF Cases Receiving ACT, DOT but Day 3 Positive (by

Patient)

8. Percent of malaria cases who got investigate

9. Indigenous Case

10. Malaria Stratification Area

GIS can display number of Malaria Cases classified by administrative level up to village level

March 18, 2010

Cases Investigation captured cases which

have possible same source of infection

2009 = 54 cases

Day 3 Positive Cases (ACT) 2009-2012

2010 = 33 Cases 2011 = 14 cases 2012=81 cases

Conclusions

• New technology can become one of a major strategy to fight

against Vector-Borne Disease

• Knowledge sharing/transferring should be strengthened among

regional countries in order to exchange information across

different territories

• Regional and Global Collaborations or networking across public

health units should be initialized for the purpose of

joining/sharing disease control tasks, and lead to practical integration between working units across barriers

Thank you