i

Pattern of Host Seeking and Oviposition Preferences of Malaria

Vectors in Kilifi County, Coastal Kenya

Abdullah Said Hemed

ADEHS (Vector Control)

A thesis submitted to the School of Biological Sciences of the University of Nairobi in partial

fulfillment of the requirements for the award of the degree of Master of Science in Applied

Parasitology

June 2013

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DECLARATION

I, Abdullah Said Hemed, declare that this thesis is my original work and has not been

presented for examination in any other University

Candidate

Signed …………………………………….. Date ……………..

Abdullah Said Hemed

Supervisors

This thesis has been submitted with our approval as supervisors

Signed........................................................... Date .......................

Wolfgang Richard Mukabana

(Associate Professor, School of Biological Sciences, University of Nairobi, Nairobi Kenya)

Signed............................................................. Date .......................

Prof. Charles M. Mbogo

(Chief Research Scientist, Vector Biology Department, KEMRI Centre for Geographic

Medicine Research - Coast, Kenya)

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ACKNOWLEDGEMENTS

This work was only feasible with support and contributions of various people and institutions

in different ways. I would like to express my appreciation to the management and staff of the

University of Nairobi for giving me admission and academic support. Further, I am deeply

grateful to my supervisors, Prof. Wolfgang Mukabana of the University of Nairobi, I am also

thankful to Prof. Charles Mbogo, Dr. Simon Muriu and Dr. Joseph Mwangangi all of the

Kenya Medical Research Institute (KEMRI), for their tireless guidance in shaping this work.

I am greatly indebted to Mr. Joseph Nzovu and Mr. Festus Yaah for their support and

instructions in laboratory work. I can’t forget the residents of Jaribuni village for their

priceless contribution in making this work possible in those homes, houses and farms. I am

indebted to field workers Mr. Arnold Mramba and Japhet Mwafondo who worked hard with

me in the field to fulfill my goals. I would like to express my thanks to Mrs. Rosemary

Wamae for helping in data compilation, Miss. Benyl Ondeto for technical advice on

computer applications and Mr. Christopher Nyundo who helped me to develop a map of

habitats in the study area. Special thanks to Ifakara Health Institute (IHI) for fully funding my

MSc studies. In particular I thank Dr. Gerry Francis Killeen for his efforts to nominate my

name for the scholarship. My family deserves the very special appreciations for their patience

during the whole period of my stay away from them during this work. I acknowledge the

Academy of Sciences for the Developing World, for supply of CDC backpack motorized

aspirator, used successfully in this study to collect indoor resting mosquitoes. Sincerely, I

express my heartfelt gratitude to the KEMRI/WellcomeTrust, Research Programme, Kilifi

and staff for hosting me and funding this study.

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TABLE OF CONTENTS

ITEM PAGE

TITLE ..................................................................................................................................... i

DECLARATION ................................................................................................................... ii

ACKNOWLEDGEMENTS .................................................................................................. iii

TABLE OF CONTENTS ...................................................................................................... iv

LIST OF FIGURES ............................................................................................................. vii

LIST OF TABLES .............................................................................................................. viii

ACCRONYMS AND ABREVIATIONS .............................................................................. ix

ABSTRACT ......................................................................................................................... xi

1 CHAPTER ONE: INTRODUCTION AND LITERATURE REVIEW ............................ 1

1.1 Introduction ............................................................................................................ 1

1.2 Literature Review ................................................................................................... 3

1.2.1 Biology and Epidemiology of Malaria ............................................................... 3

1.2.2 Malaria vectors (Afro-tropical species) ............................................................. 5

1.2.3 Life cycle of mosquitoes ................................................................................... 6

1.2.4 Medical importance of mosquito ....................................................................... 7

1.2.5 Oviposition and spatial distribution of habitats .................................................. 7

1.2.6 Mosquito habitat productivity ........................................................................... 7

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1.2.7 Mosquito host seeking ...................................................................................... 8

1.2.8 Anopheline mosquito foraging behavior ............................................................ 9

1.2.9 Malaria vector control ..................................................................................... 11

1.3 Problem statement ................................................................................................. 12

1.4 Justification and significance of the research ......................................................... 13

1.5 Hypothesis ............................................................................................................ 14

1.6 Objectives ............................................................................................................. 14

1.6.1 General objective ............................................................................................ 14

1.6.2 Specific objectives .......................................................................................... 14

2 CHAPTER TWO: MATERIAL AND METHODS ....................................................... 15

2.1 Study area ............................................................................................................. 15

2.2 Experimental design .............................................................................................. 17

2.2.1 Anopheles habitat productivity and diversity ................................................... 17

2.3 Ecological factors influencing Anopheles productivity, and emerging mosquito

fitness. ..................................................................................................................... 18

2.3.1 Artificial habitats ............................................................................................ 18

2.3.2 Emergence cages ............................................................................................ 19

2.3.3 Spatial connectivity of Anopheles mosquitoes to pre-adult aquatic habitats ..... 20

2.4 Data analysis ......................................................................................................... 25

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2.5 Ethical consideration ............................................................................................. 25

3 CHAPTER THREE: RESULTS .................................................................................... 26

3.1 Habitat productivity and diversity ......................................................................... 26

3.2 Larval productivity................................................................................................ 26

3.3 Seasonal variation in larval habitat productivity .................................................... 28

3.4 Adult productivity ................................................................................................. 30

3.5 Influence of physicochemical factors on habitat productivity ................................ 32

3.5.1 Conductivity ................................................................................................... 32

3.5.2 Dissolved Oxygen ........................................................................................... 32

3.5.3 Salinity ........................................................................................................... 32

3.6 Body size variation in wild Anopheles mosquito population .................................. 34

3.7 Correlation of habitat productivity and distance from human habitation ................ 36

3.8 Effects of mosquito larval habitat distribution on indoor resting densities ............. 38

3.9 ELISA for sporozoite rate and blood meal analysis ............................................... 42

4 CHAPTER FOUR: DISCUSSION, CONCLUSION AND RECOMMENDATIONS .... 45

4.1 Discussion ............................................................................................................ 45

4.2 Conclusion ............................................................................................................ 52

4.3 Recommendations ................................................................................................. 52

REFERENCES .................................................................................................................... 53

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LIST OF FIGURES

ITEM………………… …………………………………………………………….….. PAGE

Figure 1: Malaria control cycle between the human host, parasite and vector mosquito ......... 4

Figure 2: Distribution of Mosquito breeding habitat and houses in Jaribuni village Kilifi .... 16

Figure 3: Artificial habitat for monitoring mosquito oviposition preferences ....................... 19

Figure 4: Emergent cage placed over natural habitat to monitor productivity ....................... 20

Figure 5: A characteristic house in Jaribuni village .............................................................. 24

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LIST OF TABLES

ITEM…….………………………………………………………………… ………….. PAGE

Table 1: Mosquito larval densities per dip per habitat sampled ............................................ 27

Table 2: Temporal variation of Anopheles larval density per dip per habitat ........................ 29

Table 3: Temporal variation of habitat productivity per M2 of adult mosquito counts .......... 31

Table 4: Regression of adult mosquito productivity against physicochemical variables ....... 33

Table 5: The mean wing length variations amongst the wild Anopheles mosquitoes ............ 35

Table 6 Temporal mosquito larval density recorded from artificial breeding habitats ........... 37

Table 7: Temporal variation of indoor resting mosquitoes collected .................................... 40

Table 8: Correlation of indoor resting Anopheles mosquito densities ................................... 41

Table 9: Plasmodium falciparum infection rate for indoor collected female Anopheles ........ 43

Table 10: Blood meal sources for Anopheles species collected indoors ................................ 44

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ACCRONYMS AND ABREVIATIONS

ASDW Academy of sciences for the developing world

ACT Artemisinin-based combination therapy

ANOVA Analysis of variancea

CDC Centres for disease control and Prevention

Co2 Carbon dioxide

CS Circumsporozoites

DDT Dichlorodiphenyltrichloroethene

DEET Diethyl ether

DO Dissolved oxygen

GMP Gates Malaria Partnership

GPS Geographical Positioning System

GBI Goat Blood Index

HBI ` Human Blood Index

ID Identification number

IGR Insect Growth Regulator

IHI Ifakara Health Institute

IPTp Intermitent Preventive Treatment for pregnants

IRS Indoor residual spray

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ITN Insecticide-treated mosquito net

IVM Intergrated vector management

KEMRI Kenya Medical Research Institute

LLIN Long Lasting Insecticide Net

M2 Meter square

MAbs Monoclonal antibodies

MoPHS Ministry of Public Health and Sanitation

PBS Phosphate buffered saline

pH Hydrogen-ion exponent

RBM Roll Back Malaria partnership

s.l. sensu lato

s.s. sensu stricto

UoN University of Nairobi

USAID United States Agency for International development

WHO World Health Organisation

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ABSTRACT

Most malaria vectors alternate between their vertebrate hosts and stagnant water bodies for

blood meal and oviposition sites respectively. These two resources are obligatory

requirements for completion of the mosquito gonotrophic cycle. Knowledge of spatial

distribution and factors influencing habitat productivity of Anopheles mosquitoes is

mandatory in planning their control. The current study was carried out with the aim of

estimating the host seeking and oviposition patterns of malaria vector mosquitoes.

Mechanized aspiration for indoor resting mosquito collection and larval habitat

characterization was done to evaluate the productivity and fitness of emerging adult

mosquitoes at Jaribuni village in Kilifi at the coast of Kenya, from December 2010 to May

2011. Emergence cages measuring 0.5x0.5x0.5 meters were placed on natural habitats to

monitor emerging adults. Similarly, 5 replicates of artificial aquatic habitats were placed

between 0-100m at interval of 25m from selected houses to monitor Anopheles oviposition

preferences in distance. All larval habitats were monitored longitudinally for mosquito

immature stages and physicochemical characteristics. ELISA technique was used to analyze

parasite rate and blood meal source from malaria vectors. A total of 454 sampling visits were

made in five types of aquatic habitats, in which 71.79% the habitats found with Anopheles

larvae. The highest larval productivity was recorded in pools, river and ditches although the

river was the most stable habitat throughout the year. During the 6-month (December 2010-

May 2011) sampling period, the highest proportion of mosquitoes collected indoors were

anophelines 57% (296/519). An. funestus was the predominant species comprising of 97.1%

of all Anopheles collected indoors. Compared to the other Anopheles species, An. funestus

had higher indoor densities, a higher human blood index (0.90) and a higher sporozoite rate

(5.03%). In conclusion, Anopheline breeding sites were diverse ranging from the river

system, stream pools, ditches, trenches and abandoned water storage tanks. Nevertheless, the

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river was the most preferred breeding site with abandoned water storage tanks being the least

preferred. Generally, salinity, dissolved oxygen, conductivity and temperature were found to

have significant influence on habitat productivity. Furthermore, adult anophelines preferred

to feed close to their breeding sites.

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1 CHAPTER ONE: INTRODUCTION AND LITERATURE REVIEW

1.1 Introduction

Malaria is increasingly becoming a complex public health problem, especially in developing

countries. Several efforts have been made by the World Health Organization (WHO) and its

partners to combat the disease in particular through the Roll Back Malaria (RBM) initiative

(WHO, 2008). One of the main issues of concern with malaria is lack of clear understanding

of patterns of malaria vectors in host seeking and oviposition which is the basis for vector

management.

Malaria is estimated to cause 350-500 million clinical cases annually with 90% of all cases

reported from Africa (RBM, 2003). The risk of death from malaria is considerably higher in

Africa than other parts of the world. It is estimated around one million (over 90%) deaths due

to malaria occur in Africa South of the Sahara. Majority of deaths occur among children aged

five years and below (WHO, 2006) while each year approximately 25% of pregnant women

get infected with malaria during pregnancy (WHO, 2004). Malaria constitutes 30-50% of

outpatient consultations and 20-30% inpatients in Africa (Uneke, 2009). It has been estimated

to cause economic burden of 12 billion US dollars per year and slows economic growth by

approximately 1.3% (Rugemalila, et al 2006).

In Kenya, it is estimated that about 70% of the population lives in areas where malaria is the

leading cause of morbidity and mortality, (USAID, 2010). In Kenya, recent evidence indicates

that malaria accounts for 30% of all outpatients and 19% of inpatients, with 20% deaths of

children aged five years and below (Kenya Ministry of Public Health & Sanitation, 2007).

Every year, about six thousand pregnant women suffer from malaria-associated anemia and as

a result four thousand babies are born with low birth weight (MoPHS, 2007). The highest

malaria transmission intensity in the country occurs in the western and coastal regions.

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Mbogo et al., (2003) reported malaria prevalence of about 60% among the school children

along the Kenya coast suggesting high transmission intensity in late 1990’s.

Malaria is an acute infectious disease caused by parasitic protozoa of the genus Plasmodium

and is spread by the arthropod vector the female Anopheles mosquito. This association

between malaria and mosquitoes was suspected several years ago, during early civilization. It

is said in history that the Queen of Egypt, Cleopatra, slept under a mosquito net and in 11th

century the drainage of swamps was practiced by ancient Romans as among efforts to prevent

malaria. In 1897 Ronald Ross proved the role of mosquitoes in malaria transmission when he

demonstrated oocysts in the mosquito gut (Kakkilaya, 2008).

Takken and Knols, (2007) observed that malaria vectors preference of humans as major

source of blood meal, increases the chances of malaria transmission. Development of the

human malaria parasite Plasmodium spp form a cycle occurring both in the female Anopheles

mosquito (sporogony) and human host (schizogony) (Paaijmans, 2008). It is during these

recurrent cycles involving vector blood feeding, digestion and oviposition that malaria

transmission occurs. Therefore, the risk of malaria infection can be explained by studying

adult mosquito foraging behavior and ecology (Le Menach et al., 2005, Chaves et al., 2010).

Malaria control strategies require the consideration of both disease management and

transmission reduction through vector control. Moreover, like many other developing

countries, Kenya has for long been depending on insecticide treated bed nets (ITN) and indoor

residual spraying (IRS) to protect people from mosquito bites. The Kenya National Malaria

Strategy 2009-2017 expanded its policy on ITNs to include universal coverage, defined as

“one net per two people” in prioritized regions of the country by 2010, from the previous one

that focused on vulnerable populations (Kenya Ministry of Public Health & Sanitation, 2009).

The work in this thesis was undertaken to improve the understanding of patterns of host

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seeking and oviposition of malaria vectors in an effort towards successful integrated vector

management (IVM) in malaria control campaigns.

1.2 Literature Review

1.2.1 Biology and Epidemiology of Malaria

Malaria transmission involves the interaction between susceptible human host, protozoan

parasite, arthropod vector, physical environments and socio-economic situations of the

society. As regards physical environments, malaria prevalence and entomological factors are

interdependent. Sub-Sahara Africa is the most malaria affected area in the world (Killeen, et

al., 2001), due to several factors that favor disease transmission. These include; (a)

predominance of Plasmodium falciparum Welch which causes severe forms of malaria

disease (Shillcutt, 2008), (b) the efficient malaria vectors, Anopheles gambiae Giles complex

(Anopheles gambiae sensu stricto and Anopheles arabiensis) and Anopheles funestus Giles,

(Beier, 1999), (c) suitable hot humid tropical climate and local weather conditions including

high temperatures, rainfall and humidity optimal for both parasite and vector mosquitoes

(Kiszewski & Teklehaimanot, 2004), and (d) the instability of socio-economic conditions

worsening situations for societies living in high malaria risk localities coupled with poor

health infrastructures and lack of suitable interventions and protective measures (Carter, et al.,

2000).

Plasmodium parasites known to cause malaria to humans belong to four species, P.

falciparum, P. malariae, P. vivax and P. ovale, with Plasmodium falciparum, being the most

virulent and common cause of febrile illness and associated mortalities. There is however an

increasingly infectious P. knowlesi simian species making up to the fifth human malaria

parasite (Chandler and Read, 1961). The disease is transmitted from person to person through

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the infective bites of female Anopheline mosquitoes. Only the adult female Anopheles

mosquito, needs a blood meal protein for egg development and maturation. The control

strategy of the disease is based on the three epidemiological components i.e. the human host,

the parasite and the vectors as illustrated in figure 1 below.

Man

(host)

Plasmodium

(agent)Mosquito

(vector)

•Transmission

•Vector infection

•Vector biting nuisance

•Sporogony

•Infection and disease

•Schizogony

CONTROL METHODS

•Bednets

•Mosquito repellents

•Indoor residual spraying

•Screening mosquito house-entry points

•Larviciding

•Biological control of adults

•Environmental management

CONTROL METHODS

•Prompt diagnosis and treatment of human infections

•Mosquito-human barriers

•Gametocides & vaccines?

CONTROL METHODS

•Mosquito-human barriers

•Prophylaxis

•Intermittent preventive treatment

• Anti-sporozoite vaccines?

•Blood screening before transfusion

Figure 1: Malaria control cycle between the human host, parasite and vector mosquito

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1.2.2 Malaria vectors (Afro-tropical species)

Anopheles mosquitoes can be distinguished from other mosquitoes by the palps, which are as

long as proboscis, and by presence of distinct marks on the wings. Adult Anopheles can also

be identified by their typical resting position, adults rest with their bodies in an acute or near

right angle to the surface upon which they rest (Gillies and DeMeilon, 1968).

Anopheles mosquitoes responsible for malaria transmission are widely distributed around the

world (except in Antarctica) from endemic areas to where the disease has been eliminated

(CDC, 2010). It is estimated that there are over 400 Anopheles species worldwide but only 30-

40 species are involved in malaria transmission, and about 1-2 species are major drivers of

disease transmission in a given area (White, 1974). Anopheles gambiae Giles complex is the

most efficient vector species of the fatal malaria parasite Plasmodium falciparum Welch

(Coetzee et al., 2000).

Anopheles gambiae complex comprises of seven sibling species; An. gambiae sensu stricto

Giles, An. arabiensis Patton, An. merus Donitz, An. melas Theobald, An. quadriannulatus

Theobald, An. bwambae White and An. quadriannulatus B, (Coetzee, 2004; Brooke et al.,

2002). In Sub-Sahara Africa, the major malaria vectors are Anopheles gambiae sensu stricto,

Anopheles arabiensis and Anopheles funestus Giles (Devine and Killeen, 2010) which are

widely distributed in Africa. In addition to the above 3 major malaria vectors, (Mbogo et al,

2003), reported An.merus as a secondary vector along the coast of Kenya. Other malaria

vectors along the coast of Kenya include Anopheles coustani, Anopheles squamosus,

Anopheles pharoensis and Anopheles nili (Mbogo et al., 1995). Anopheles gambiae complex

and Anopheles funestus tend to show seasonality trends in abundance and breeding. Anopheles

funestus breeds in swamps and the population density peaks at the end of rainy seasons and

onset of dry season (Gillies and DeMeilon, 1968).

6

1.2.3 Life cycle of mosquitoes

Mosquitoes have a holometabolous lifecycle (complete metamorphosis). They undergo four

different stages in their lifecycle; egg, larva, pupa and adult, the first three are aquatic and the

adult is terrestrial.

Some species such as Anopheles and Aedes mosquitoes lay their eggs singly on water surface,

but others such as Culex the eggs are glued together and laid in rafts. The Anopheles egg is

boat shaped, with bilateral floats, and cannot resist desiccation. A female adult mosquito can

lay between 50-200 eggs per single oviposition. In tropics the eggs hatch within 2-3 days due

to high temperatures, while in cold climates they last up to 3weeks.

Mosquito larva has got a well-developed head with a mouth brush for feeding, a thorax and

nine segments abdomen and has no legs. The Anopheles larvae unlike other mosquito, lack

respiratory siphon for respiration, instead they use spiracle placed on the eighth segment of

the abdomen and often lie parallel below the water surface. The Anopheles larvae feed on

bacteria, yeast, viruses, algae and other organic matter. Since they are surface feeders, they

spend most of the time on the water surface unless disturbed. The mosquito larval

development involves four larval instars, 1st, 2nd, 3rd, and 4th instars. In each instar molting

takes place after casting the exoskeleton for growth. Larval development to pupa takes about

4-7days under optimal conditions.

The pupa is comma shaped with fused head and thorax forming a cephalothorax, it doesn’t

feed and it is very active when disturbed. It frequently comes to water surface to breath by

using a pair of respiratory trumpets. The pupa molts to an adult mosquito after 1-3days

depending on ambient temperature.

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The complete process from egg to adult varies from one species to another, under favorable

temperatures takes a minimum of 7 days, but usually takes 10-14 days in tropical countries.

1.2.4 Medical importance of mosquito

Mosquitoes apart from their biting annoyance are important vectors of diseases such as

malaria, lymphatic filariasis, dengue, yellow fever and many other arboviral diseases.

1.2.5 Oviposition and spatial distribution of habitats

Malaria vectors lay eggs in relatively clean slow moving and standing water such as irrigation

water, rice fields, shallow ditches, flooded depressions, river banks, marshes and burrow pits

(Oyewole et al., 2009). In addition, An. gambiae mosquitoes prefer small sunlit pools and

man-made habitats (Service, 1977, Shililu et al, 2003) in the vicinity of human habitations

(Carter, et al., 2000). In all mosquito species, location and selection of an oviposition site is

essential in life history because potential breeding sites vary with respect to both biotic and

abiotic characteristics (Sumba et al., 2004). The gravid Anopheles mosquito selects a suitable

breeding site to lay its eggs, (Tsila, et al, 2010) hence it determines the larval distribution in a

locality (Pates and Curtis, 2005). This selection influences reproductive potential and

determines survival rate of larvae (Bond et al, 2005). In selecting a suitable oviposition site,

gravid Anopheles mosquito use biological and chemical cues as attractants (Mokay & Shine,

2003). One female mosquito reproduces up to several hundred eggs over several broods of life

time. Soon after emerging, an adult female mosquito is normally ready to mate (Takken and

Lindsay, 2006) after which she begins to seek a blood meal.

1.2.6 Mosquito habitat productivity

Habitat productivity refers to the rate of adult mosquito emergence from individual aquatic

habitats. Proper knowledge of gravid mosquito foraging behaviour for oviposition is key in

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understanding the habitat productivity (Gu et al, 2008). For instance, most gravid An.

gambiae mosquitoes tend to oviposit in habitats closer to the human habitations; hence these

habitats are relatively more productive than those located far away. The productivity of

available aquatic habitats within the vicinity of human habitations, determines adult vectors

population and the risk of malaria transmission in a locality (Munga et al, 2009). (Gu and

Novak, 2009) observed that aquatic habitats differ in mosquito productivity in heterogeneous

environments and this may facilitate targeted intervention. Empirical studies have suggested

that the major determinants of oviposition and larval abundances in a habitat are type and

location of aquatic habitats (Diabate et al., 2005; Munga et al., 2006; Mwangangi et al.,

2007). For instance, one of such studies reported that brick pits alone accounted for 60-80

percent of the total pupal samples in western Kenya (Mutuku et al., 2006).

1.2.7 Mosquito host seeking

Le Menach et al., (2005) reported that a set of cues such as host movement, body temperature,

odours, and carbon dioxide (Co2) are used to locate sources of blood-meal by newly emerged

mosquitoes from aquatic habitats. The availability of preferred hosts for blood meal within the

flight-range of malaria vectors influence the emergency rate, feeding cycle length, malaria

transmission dynamics and even survival of the vectors (Burkot, 1988, Killeen et al., 2001).

Success of host finding and oviposition varies from species to species and is dependent on the

flight ability of the mosquito, (Gu et al., 2006). Anopheles mosquitoes particularly differ in

host seeking behavior. Some species prefer to feed on humans, these are categorized and

referred to as anthropophagic, and others prefer to feed on animals and are referred to as

zoophagic. Mosquitoes with preference to feed indoors are referred to as endophagic whereas

outdoor feeding mosquitoes are referred to as exophagic; however these names are mere

references of the particular behavioral categories and not distinct nomenclature units.

9

Mosquito feeding behaviour as respects timing is a primary requisite for the understanding of

malaria transmission (Chandler and Read, 1961).

1.2.8 Anopheline mosquito foraging behavior

Foraging is a term used to refer to a definite set of behaviours exhibited when a female

mosquito searches for a host as a source of blood meal and oviposition site. These two

requirements consist central obligations and requirements for completion of the mosquito

gonotrophic cycle (Gu and Novak, 2009). Generally, endophily in Anopheles mosquitoes is

characterized by resting on the walls, ceiling, dark objects and under furniture. This often

occur prior to or after a blood meal; in the last case of which is crucial for digestion and egg

development. Engorged females fly to the nearby suitable water bodies for egg laying

(Mboera, 2005; Mboera et al 2006; Takken and Lindsay, 2006). A sexually mature female

mosquito usually needs two to three blood meals for initial oviposition. However, subsequent

feeding and oviposition patterns may vary slightly, in addition, the duration of the

gonotrophic cycle varies with ambient temperature ( Lyimo and Takken, 1993).

Generally, the distribution of humans and suitable habitats for mosquito larval development

vary across the landscape and the density of disease vectors fluctuates seasonally due to

dynamics of the habitat availability. These fluctuations are driven by environmental factors

mainly rainfall, temperature and topography which dictate the level of human-vector contact

and consequently disease transmission. Malaria vectors have a typical flight range of 1-2km

(Carter, et al., 2000) an essential component influencing distribution. The productivity of

breeding habitats and the effective dispersal range of the malaria vectors determine the

dimensions of malaria transmission in a region. A limited energy reserve restricts An.

gambiae from long-range flights to lay eggs in aquatic habitats far from human habitations.

10

(Le Menach et al., 2005) observed that vector dispersal can be influenced by the patterns of

host locality as well as the ecological situations of oviposition sites.

Survival and development of mosquitoes depends largely on appropriate physicochemical

parameters in the habitat, such as pH, temperature, salinity, oxygen content and nutrient

composition (Oyewole et al., 2009). ( and Takken 1993) observed that malaria parasite

transmission is dependent on the number of blood meals required to complete a gonotrophic

cycle which is influenced by body size of the female Anopheles.

Studies to assess the association of physicochemical factors and larval development have been

conducted before in Dakar, Senegal, (Robert et al., 1998) and western Kenya, (Gimnig et al.,

2001). In both studies, it has been shown that presence or development of Anopheles larvae in

pools correlate with water temperature, salinity, concentration of carbonates and nitrates. In a

separate study, (Mwangangi et al., 2007), along the coast of Kenya, using emergent cages

placed over natural habitats, found no association between physicochemical parameters with

body size of emerging mosquitoes, except for chlorophyll a. However, in a similar study of

habitat productivity, (Midega et al., 2007) concluded that there was variation in habitat

productivity along the coast of Kenya. The current study used both natural and artificial larval

habitats to evaluate this association.

(Kigadye et al., 2010) reported that due to variation in host preferences and abundance of

malaria vectors, there is need to identify and map species distribution in heterogeneous

environments. (Chaves et al, 2010) observed that Anopheles gambiae s.s prefer to feed mostly

on humans even when introduced to other hosts under controlled field trials while (Mahande

et al, 2007) reported that Anopheles arabiensis prefer feeding on animals. The availability of

humans as the sole source of blood meal alongside vector mosquito blood meal preference is

the primary reasons for anthropophagic behaviour (Burkot, 1988).

11

1.2.9 Malaria vector control

Vector control is an important aspect in the management of malaria transmission, being one of

the key components of the Roll Back Malaria (RBM), and can be directed either against the

immature stages or adult mosquitoes. The main goal of malaria vector control is to minimize

the vector population so as to reduce considerably the incidence and prevalence of both

parasite infection and clinical malaria. Several regions of the world use vector control as a

tool for malaria eradication and it has considerably reduced the incidence in some countries

(Killeen, et al 2004). From the late nineteenth century to early twentieth century, before the

invention of Dichlorodiphenyltrichloroethane (DDT), environmental management was the

main approach for malaria vector control, targeting aquatic stages; this included

environmental modification with permanent outcome and environmental manipulation with

temporary outcome (Castro, et al., 2010). The discovery of DDT which was extremely

effective made the control and eradication of malaria vectors feasible in some regions of the

world, and was used as an IRS in malaria control campaigns (Gu et al., 2008).

Among the current available chemical methods of mosquito control is the use of pesticides

such as Pyrethrin from plant flower extracts and synthetic pyrethroids which are used in ITNs

and IRS targeting adult mosquitoes as contact poisons. Mosquito population reduction can

also be achieved by hindering the dispersal through interrupting the life cycle using chemical

larvicides like organophosphates e.g. temephos, and insect growth regulators (IGRs) e.g.

methoprene (Hardin and Jackson, 2009). Others include use of biological methods like

bacteria. The bacterial larvicide applications consist of two bacterial strains of Bacillus

thuringiensis israeliensis (Bti) and Bacillus sphaericus (Bs). (Becker, 1998) reported the

introduction of large-scale routine operations of Bti for the first time in Europe in the first five

years of its invention. Tropical countries consider integrating biolarvicides into their control

12

programmes (Fillinger, et al., 2003). Tanzania has been successfully used Bti for killing

mosquito larval stages in a malaria control programme in Dar es salaam, (Fillinger et al.,

2008).

WHO defined Integrated vector management (IVM) as a “rational decision making process

for the optimal use of resources for vector control”. Several strategies are employed in control

of vector borne diseases, yet they remain a chief global public health challenge. Recent

evidence indicates the inclusion of IVM in national malaria control programmes in tropical

African countries has high potential for success of control, (Beier et al., 2008, Geissbuhler et

al., 2007). WHO has approved as first line control, IVM programme combining ITN, IRS and

source reduction in the fight against malaria vectors, (Muturi et al., 2008).

1.3 Problem statement

Tropical African countries rely on case management and insecticide-based control i.e.

insecticide treated nets (ITN) and indoor residual spraying (IRS) of the major vector species

in their malaria campaigns, despite resistance challenge. In these campaigns, insecticide

treated nets/long lasting insecticide nets (ITN/LLIN) have mostly been ranked as the top most

reliable tool for malaria vector control (GMP Report, 2001-2006). However, environmental

management for larval control has been neglected in Africa (Gu et al., 2006; Fillinger et al.,

2004). Increased coverage of ITNs and IRS in many parts of Africa has led to achievement of

vast benefits but the level of control is limited. Both ITNs and IRS target indoor mosquitoes

but the focus towards elimination in most settings should also target outdoor exposure to

mosquitoes (Ferguson, et al., 2010). Anthropophagic Anopheles mosquitoes are regarded to

be key vectors of malaria and lymphatic filariasis, (Snow, 1983), especially along the coast of

East Africa where the diseases are widely spread. Considering the importance of

environmental management, control of multiple vector borne diseases can be achieved when

13

integrated with other available tools. The success story of malaria eradication in Europe,

United States and the Middle East was based on integrating rigorous larval control measures

and other tools (Fillinger et al., 2003).

This study intended to develop a new perspective of environmental management by source

reduction, targeting mosquito foraging behavior. A study conducted by (Mbogo et al., 2003)

in the coastal area of Kenya demonstrated a spatial heterogeneity in the species composition

of Anopheles mosquitoes, however, factors associated with the spatial occurrence of larval

habitats were still not clear. In a different study of the same area (Mwangangi et al., 2007)

observed that targeting aquatic habitats surrounding house compounds could drastically

reduce mosquito abundance and malaria incidence, suggesting interference with foraging

movements as a promising target. The current study aimed at estimation of indices of spatial

connectivity to measure the availability of human hosts and aquatic habitats to host seeking

and gravid mosquitoes respectively by mapping and analyzing distribution patterns of host

seeking mosquitoes and larval populations.

1.4 Justification and significance of the research

The majority of female Anopheles mosquitoes alternate between human host for blood meal

and suitable aquatic habitats for oviposition (Sumba et al., 2004). Aquatic habitats vary in

physicochemical variables which affect oviposition preference, productivity and fitness of

larval populations. (Gu et al., 2008), noted that oviposition foraging is normally overlooked as

a factor governing distributional patterns of mosquito productivity. In planning malaria vector

control programs targeting mosquito aquatic stages, prior understanding and knowledge of the

local ecological situation and spatial distribution of breeding habitats are very important

aspects for success. However, the oviposition pattern and habitat distribution of most

ecosystems are not clearly understood thus the need to evaluate and understand them. In the

14

current study, spatio-temporal analysis of habitat productivity was conducted in Jaribuni

village along the Kenyan coast with an aim of elucidating crucial information on Anopheles

mosquito habitat suitability and productivity. Findings of this study will be useful to regional

authorities in planning strategies for mosquito larval control using environmental

management.

1.5 Hypothesis

Human host seeking patterns of Anopheles mosquitoes are influenced by oviposition patterns

1.6 Objectives

1.6.1 General objective

To estimate the host seeking and oviposition patterns of Anopheline mosquitoes

1.6.2 Specific objectives

1. To determine Anopheline habitat productivity and diversity.

2. To evaluate ecological factors which influence Anopheline productivity and emerging

mosquito fitness.

3. To assess spatial connectivity of Anopheline mosquitoes to their pre-adult aquatic

habitats.

15

2 CHAPTER TWO: MATERIAL AND METHODS

2.1 Study area

This study was carried out in Jaribuni village (03o37.3’S; 039o44.6’E) which lies

approximately 30km west of Kilifi town in the Kilifi County, along the Kenyan coast (Fig

2.1). Jaribuni lies at an altitude range of 40-400 meters above sea level and experiences two

wet seasons annually, with the long rains in April/June and short rainy period occurring in

October/December with mean annual precipitation range of 400mm-1,200mm. The mean

annual temperature ranges between 22oC and 30oC and the average relative humidity is

approximately 70% (Mtwapa Meteorological Station, 2010). Jaribuni River cuts across the

study site with abundant small pools of water and vegetation along both sides. The vegetation

cover in the area consists of bushes and shrubs. Jaribuni area is characterized by subsistence

farming such as cassava and maize, with some plantations of coconuts, and cashew nuts, and

scattered village houses. Small scale rearing of domestic animals such as cattle, goats and

poultry are also carried out in the area. The rural population mainly lives in mud-walled

houses with coconut-leaf-thatch (Makuti) roofs. Mosquitoes have free access to these houses

through eaves because they have no ceilings, moreover, unscreened windows/ventilation

openings and others are structurally defective. Homesteads are scattered and separated from

one another by agricultural land. The Kenya Medical Research Institute (KEMRI) has

established a semi-field station set up for mosquito experiments in Jaribuni village. The

present study area covered an area of (2x2) km2 grid in the village.

16

Mwapula

Marere

Jaribuni

Dispensary

Vinagoni

Magogoni-K

Mdangarani

JARIBUNI AREA

Figure 2: Distribution of Mosquito breeding habitat and houses in Jaribuni village Kilifi-County Coastal Region

17

2.2 Experimental design

2.2.1 Anopheles habitat productivity and diversity

2.2.1.1 Breeding site identification and mapping

A longitudinal survey of potential mosquito breeding habitats was conducted within 4km2

grid of the Jaribuni village on fortnight basis for a period of five months between December

2010 and April 2011. The grid was selected to cover part of the river Jaribuni which was the

main breeding site during the dry season and adjacent human habitations. The grid was set by

measuring 1km each direction towards North, South, West and East, using hand held

geographical positioning system (GPS) machine (eTrex© Vista HCx, Garmin), the centre

point was a bridge crossing the river Jaribuni. All temporary habitats such as ditches, trenches

and abandoned water storage tanks and permanent open water bodies such as river and

adjacent pools were considered as potential mosquito breeding habitats and recorded.

Immature aquatic mosquito stages were sampled by a standard dipper (350mls) depending on

the size of the habitat. During sampling, 10-20 dips were made in each habitat depending on

its size, pooled together and sieved into enamel trays to constitute a single sample for the

particular habitat. Field collected samples were placed into whirl packs and then transferred to

field laboratory for further processing. Larval habitats and human habitations were allocated

different codes and geo-referenced by taking coordinates using (GPS).

2.2.1.2 Mosquito larval identification

All mosquito larvae and pupae were placed in enamel trays in the laboratory and sorted out

into anopheline and culicines from other accidentally collected aquatic organisms and debris.

Anopheles and culicine larvae were further categorized as early (1st and 2nd) or late (3rd & 4th)

instars larvae. Pupae were generalized for both anophelines and culicines and placed in

18

emergent cages for adults to emerge. The emerged adults were then morphologically

identified into species using the keys of Gillies and Coetzee, 1987.

2.3 Ecological factors influencing Anopheles productivity, and emerging mosquito fitness.

2.3.1 Artificial habitats

Plastic basins (Figure 2) were placed at selected sites along transects identified in the study

village (Jaribuni) with the reference point being five inhabited houses that were also sampled

for adult mosquitoes on fortnight basis (Section 3.7). Each transect was 100m long and five

artificial habitats were placed at intervals of 25 meters along its length (0m, 25m, 50m, 75m

and 100m). Each habitat was filled with approximately 1.5kg of fresh mud and three liters of

sieved river water. The habitats were coded for easy reference and left open to allow

colonization by wild mosquitoes. The habitats were then monitored on daily basis for

oviposition by wild mosquitoes. Mosquito larvae in the artificial habitats as well as

physicochemical characteristics such as temperature, conductivity, Dissolved oxygen (DO)

and salinity were recorded daily with the aid of YSI EC 300 machine, Brannum Lane, Yellow

Spring, OH, USA and DO by CORNING 312 machine, Corning Incorporated, NY USA.

Turbidity was monitored by expert visual assessment and recorded as clear, low or high.

Water was added daily into artificial habitats to replenish amount lost through evaporation.

The number of early instar larvae were daily collected, their numbers estimated, and

transferred to the laboratory for further processing. Pupae were placed in holding cages in the

laboratory and allowed to emerge as adults to facilitate morphological identification using

keys by Gillies and Coetzee (1987). For the emergent adults, only Anopheles mosquitoes were

identified to species level.

19

Figure 3: Artificial habitat for monitoring mosquito oviposition preferences and distances from houses

2.3.2 Emergence cages

In naturally occurring mosquito habitats, cages of 0.5mx0.5mx0.5m and 0.3mx0.3mx0.3m

were used to estimate habitat productivity. The cages were made of iron rod frames and

welded with 6-inches wide iron plates on the lower sides to prevent in and out movement of

water and mosquito larvae. The cages were then covered with a netting material for the

control of emerging adults (Figure 3). The cages were placed on selected representative

natural habitats identified in the study area that had aquatic stages of Anopheles mosquitoes.

The emerged adult mosquitoes from the cages were collected daily by simple mouth aspirator

and placed in paper cups. The specimens were transferred to KEMRI, Kilifi Vector biology

laboratory for further processing. In the laboratory, the identified Anopheles mosquitoes were

killed by freezing and one wing removed and mounted on the microscope slide by using DPX

mounting solution for measurement of wing length. The wing length measurement was done

20

with the help of ocular micrometer mounted on a microscope eye piece for the estimation of

average adult body size. Wing length measurements were taken from the distal end of the

alula to the tip, excluding the fringe of scales.

Figure 4: Emergent cage placed over natural habitat to monitor productivity

2.3.3 Spatial connectivity of Anopheles mosquitoes to pre-adult aquatic habitats

2.3.3.1 Sampling procedure

Probability sampling design was used to select ten houses for aspiration in the village block.

The area was divided in 4 sub-blocks or grids (A=25 houses, B=23 houses, C=18 houses and

D=16 houses) for even distribution of the sampled houses. Number of houses in each of the 4

sub-blocks of 1km2 was pre-determined. The stratified sampling method was applied to get

the number of houses for indoor sampling in each grid, then, simple random method was

21

employed in selecting the required number of houses. The following formula was used:

Sample in a sub-block = number of houses in a sub-block x sample size n (10)

Total number of houses in a block

A= (25x10)/82=3houses, B= (23x10)/82=3houses, C= (18x10)/82=2houses and

D= (16x10)/82=2houses

2.3.3.2 Indoor resting mosquito collection method

Sampling of human host seeking mosquitoes (indoor resting) was done using aspiration

collection method as described by Service (1993) in ten selected houses between 06.00am and

11.00am on a fortnight basis for six months (December 2010-May 2011). The method used a

motorized improved “CDC backpack Aspirator” Model 1412 (John W. Hock Company,

Florida, USA), originally developed by U.S. Public Health Services to collect the indoor-

resting adult mosquitoes such as Aedes aegypti. The collection cup was inserted into the wand

with slight twist until it fitted. The blower was then turned on with the switch located in the

wand. The aspirator was powered by 12v rechargeable battery. Collections were then made by

systematically moving the flexible wand on wall surfaces, roofs, hanging clothes and under

furniture to collect resting mosquitoes. After each collection, the collection cup was closed

before turning off the blower to prevent escape of caught mosquitoes. The adult mosquitoes in

collection cups were then stored in cold boxes to prevent drying up during transfer to the

laboratory where they were then killed in a freezer under -20oC temperatures. Caught

mosquitoes were identified by the use of morphological appearance with the aid of

entomological Microscope and identification key by (Gillies and Coetzee, 1987); (Gillies and

22

DeMeillon, 1968). Anophelines were identified to species level whereas the rest were

generally regarded as culicines. The physiological status of mosquitoes was determined

through abdominal examination of freshly collected samples as unfed, fed, half gravid or

gravid.

2.3.3.3 Sporozoite rate

Enzyme linked immunosorbent assay (ELISA) technique was performed to establish infection

of female Anopheles mosquitoes collected indoors. This was based upon presence of specific

anti-Plasmodium falciparum sporozoite monoclonal antibodies (MAbs) from mosquito

salivary glands. Female Anopheles mosquitoes were cut between thorax and abdomen; heads

and thoraces were left to soak in the Nonidet P-40 for 20 minutes before being used to test for

the presence of Plasmodium falciparum circumsporozoite proteins. The “sandwich” ELISA

began by adsorption of the capture MAbs to the wells of the microtitre plate. After 30 minutes

incubation at room temperature, the well contents were aspirated and the remaining active

binding sites on the plate were blocked with blocking buffer. Mosquito samples were ground

individually in a 1.5 ml vial by plastic rod in blocking buffer containing Nonidet P-40, diluted

with blocking buffer. Resultant preparations were then aliquoted into microtitre plate wells.

Positive and negative controls were also added to specific wells. After 2 hour incubation, the

mosquito triturate was aspirated and the wells were washed two times with PBS-Tween 20

and banged to dry. The respective peroxidase-linked MAbs were then added to the wells,

completing the formation of the “sandwich”. After one hour incubation at room temperature

the well contents were aspirated, the plate was washed three times with PBS-Tween 20

solution and banged to dry and the clear peroxidase substrate was added. A dark green

product was formed as the peroxidase enzyme reacted with the substrate, the intensity of the

23

color being relative to the amount of circumsporozoite (CS) antigen present in the test sample.

The results were read visually after 30 minutes of incubation.

The sporozoite rate was estimated as a proportion (n/N), calculated as the number of infected

mosquitoes (n) divided by the total number tested (N).

2.3.3.4 Blood meal ELISA analysis

Blood fed and half gravid abdomens of individual mosquitoes were triturated manually with

plastic pestle in1.5ml microfuge tube containing 100µl phosphate buffer saline (PBS). Nine

hundred microlitres of the blocking buffer was then added to each sample to make a final

volume of 1ml. Samples were then transferred to polyvinyl microtitre plate wells in aliquots

of 50µl and incubated overnight at room temperature. The plate was then washed twice with

PBS-Tween 20 followed by addition of 50µl host specific conjugate in 5ml boiled casein-

Tween 20 enzyme diluents then incubated for one hour at room temperature. The wells

washed 3 times with PBS-Tween 20 then 100µl of ABTS peroxidase substrate was added to

each well. After 30 minutes of incubation, the dark green positive reactions for peroxidase or

dark yellow reactions for phosphotases were visually assessed. A second host source was

determined in the same microtitre plate where mosquitoes were screened for human blood.

The phosphotase-labeled anti-bovine IgG was added to the peroxidase-labeled antihuman IgG

solution. Blood meal were screened first for human IgG by addition of peroxidase substrate,

reading made after 30 minutes and wells washed 3 times with PBS-Tween 20 then to each

well 100µl of phosphatase substrate was added. Plate was read after 1 hour to determine

positive bovine reactions. Non-reacting samples were then tested for goat blood. Test serum

from each host was added except that for which enzyme conjugate was added. Microtitre plate

contained control serum from each host and blank controls containing 50µl of PBS alone.

24

Figure 5: A characteristic house within Jaribuni village where indoor resting mosquitoes were sampled

25

2.4 Data analysis

Field data collection was done and entered in pre-designed field data forms then transferred

into Excel spreadsheets. The data was first cleaned for errors and analysis done using R-

statistical package. One way analysis of variance (ANOVA) was used to compare the

productivity of different larval habitats while the student t-test was used to compare early and

late instars abundance in habitats, the same test was used to compare the mean larval density

of each habitat against the overall mean. Regression analysis was used to test for correlation

between the various physicochemical factors and habitat productivity of mosquitoes and

distance from aquatic habitats to indoor resting Anopheles population. To generate a map

showing selected houses and locations of breeding sites, a computerized program, ESRI

ArcMap version 10 was employed (Figure 1). The productivity in artificial habitats was

determined by the number of larvae per habitat per day. The productivity of malaria vectors in

natural habitats was determined by the number of emerging adult mosquitoes per m2 per day.

The sporozoite rate was calculated as a proportion of number infected over total number

tested. Human blood index (HBI) and Goat blood index (GBI) was calculated as proportion of

number positive for a particular host over number of tested mosquito samples.

2.5 Ethical consideration

Permission to conduct this study was granted by KEMRI National ethical review committee

(permit number KEMRI SSC 1719). The informed verbal consent was sought from heads of

households for the study to be carried out in their farms and household surroundings for larval

habitat searching and artificial habitat and aspiration to be performed in their houses after

26

3 CHAPTER THREE: RESULTS

3.1 Habitat productivity and diversity

A total of five different habitat types were identified and sampled for mosquito productivity in

Jaribuni village during the study. The five habitat types included temporary pools, abandoned

water tanks, ditches, river and trenches. A total of 454 sampling visits were made to the

habitats with a proportion of 77.3% of the habitats having water (Table 1). Of this, the river

was the most stable habitat in terms of its capacity to retain water most of the time (100%)

followed by temporary pools (74.7%) and ditches (70.3%). Abandoned water tanks and

trenches were less stable habitats, they were only found with water when it rained.

Abandoned water tanks in 76.9% of the sampling visits were found dry and trenches were dry

in 76.7% of the sampling visits. The highest proportion of presence of anopheline mosquitoes

was recorded in pools with the least recorded in water tanks.

3.2 Larval productivity

The mean early and late stage larva, and pupal densities per dip per habitat for anophelines

and culicines were monitored during the entire six month study period (Table 1). The data

showed gradual decrease in larval densities per dip per habitat from early to late instars larvae

and from late instars to pupae in all five types of aquatic habitats. Early instar densities were

significantly higher than late instar densities for both anophelines and culicines at p<0.05

(Table 1). One way ANOVA test showed a statistically significant difference in Anopheles

larval productivity among the five habitat types. When comparing the means of Anopheles

larval density of each habitat type (ditches, pools, river and abandoned water tanks), against

overall mean larval density, the river had significantly higher mean density.

27

Table 1: Mosquito larval densities per dip per habitat sampled fortnightly between December 2010 and April 2011 in Jaribuni village,

Kilifi County

Table

Habitat type

Frequency

of habitats

sampled

%Habitats

with water

%Habitats

positive for

Anopheles

Mean

Anopheles

early

instars

Mean

Anopheles

late instars

Mean

Culicines

early

instars

Mean

Culicines

late

instars

Mean

Pupa

(An+Cx)

Ditch 148 70.30 70.19 1.12 0.26 1.96 0.70 0.04

Pool 79 74.70 77.97 0.69 0.40 2.31 1.10 0.08

River 176 100 73.86 1.21� � 0.44� � 0.75 0.55 0.11

Water Tank 13 23.10 33.33 0.00 0.00 0.08 0.03 0.00

Trench 38 23.70 0.00 0.08 0.00 0.00 0.11 0.00

Total 454 77.30 71.79 0.96� � 0.33 1.34�

�

0.64 0.07

� � indicate significant difference in mean larval densities at p<0.05

28

28

3.3 Seasonal variation in larval habitat productivity

On temporal basis, all the habitats showed differential productivity with the month of March

recording significantly higher overall productivity of anopheline larvae (p<0.05). Temporal

productivity varied significantly among different habitats (Table 2). Normally, the river

became more productive during the dry season when water volume and velocity was low. The

month of April was the wettest month compared to the rest of the four months. The number of

small pools along the river and ditches increased and the ability to retain water longer for

mosquito larval development and consequently the productivity also increased. Overall larval

density was 1.28 larvae per dip, with observed early instar density recorded as 0.97 and late

instar density as 0.33 larvae per dip per habitat (Table 2). Higher larval densities were

recorded in the river habitats in the first three months of larval sampling, i.e., December to

February (range 1.49-2.65) while the highest larval density of 2.75 was recorded in March

compared to April (1.49 larvae per dip) in pools (Table 2).

29

Table 2: Temporal variation of Anopheles larval density per dip per habitat in Jaribuni village

from Dec 2010-Apr 2011

Month

Habitat type *L1L2 *L 3L4 Total Anopheles larvae

December Ditch 0.77 0.18 0.95 Pool 0.56 0.18 0.74 River 1.39 0.48 1.87 Trench 0.00 0.00 0.00 Water tank - - - January Ditch 0.74 0.18 0.93 Pool 0.13 0.07 0.20 River 0.92 0.50 1.42 Trench 0.00 0.00 0.00 Water tank *- - - February Ditch 1.97 0.19 2.16 Pool 0.85 0.21 1.06 River 2.17 0.48 2.65 Trench 0.00 0.00 0.00 Water tank 0.00 0.00 0,00 March Ditch 1.66 0.60 2.26� � � Pool 1.32 1.43 2.75� � � River 1.50 0.82 2.32� � � Trench 0.00 0.00 0.00 Water tank - - - April Ditch 0.80 0.27 1.07 Pool 0.91 0.59 1.49 River 0.06 0.08 0.15 Trench 0.00 0.00 0.00 Water tank 0.50 0.00 0.50 Total 0.97 0.33 1.28

(-) = no data (habitat was dry at the time of data collection)

(*L1L2) = larval stages 1&2

(*L3L4) = larval stages 3&4

� �� � Indicate significant difference in seasonal larval habitat productivity at p<0.05

30

3.4 Adult productivity

Three wild type Anopheles species and culicines of various species were collected from

naturally occurring habitats using emergent cages placed over the habitats and monitored for

adult productivity (Table 3). A total 247 adult Anopheles mosquitoes were collected in three

months from March-May 2011 and were dominated by An. gambiae, 225(91.1%) followed by

An. pretoriensis 21(8.5%) and An. funestus 1(0.4%). The proportion of An. gambiae

mosquitoes was significantly higher (91.1%) with ditches being the most productive habitats

throughout the experiment. An ANOVA and Turkey’s HDS test of significance for An.

gambiae adult productivity showed that the productivity within the cages differed

significantly over time (F=53.13, df=2, 8, p<0.05) with the month of April being more

productive compared to other months. Similarly, ditches were found to be the most productive

habitats for An. gambiae adults per m2, (F=12.75, df=2, 6, p=0.02). Only one An. funestus

emerged and a low density of An. pretoriensis (1.1mosquito per m2) was recorded in April

from ditches (Table 3). In May the river was not monitored for adult productivity, because

water level was high and the cages could not be placed. High water volume during the month

of May lowered the adult density per square metre from pools.

31

Table 3: Temporal variation of habitat productivity per M2 of adult mosquito counts in relation to physicochemical factors

Month Habitat

type

An.

gambiae

An.

Funestus

An.

pretoriensis

Culicines Salinity (ppt)

Mean±SD

Temp (oC)

Mean±SD

Dissolved

O2 (mg/l)

Mean±SD

Conductivity

(µS/cm)

Mean±SD

March Ditch

1.04�

� � 0.00 0.00 1.75 5.60±1.71 29.22±1.70 2.24±1.00 10.54±3.18

Pool 0.00 0.00 0.00 2.10 3.98±1.57 36.39±2.11 2.68±1.55 8.71±3.49

River 0.00 0.00 0.00 2.28 2.10±0.00 32.97±0.63 1.88±0.64 4.63±0.15

April Ditch

6.04�

� � 0.10 1.10 5.35 5.24±1.91 29.21±1.24 2.28±0.59 7.07±3.70

Pool 4.55 0.00 0.00 7.18 3.76±1.46 33.46±3.90 2.31±0.37 7.47±3.47

River 3.20 0.00 0.00 2.40 2.10±0.00 32.80±0.95 1.82±0.38 4.67±0.22

May Ditch

2.62�

� � 0.00 0.00 2.16 5.03±1.95 29.28±0.78 2.36±0.43 4.80±1.52

Pool 0.44 0.00 0.00 0.00 2.84±0.76 29.06±0.51 2.10±0.00 4.67±1.80

River *- - - - - - - -

(-) = there were no data because cages were not placed over river

�� � � indicate significant difference in seasonal adult habitat productivity at p<0.05

32

3.5 Influence of physicochemical factors on habitat productivity

A summary of the mean range of physicochemical factors and corresponding adult

productivity in different habitat types is shown in table 5. Pearson’s χ2 gave slight association

between habitat type and temperature (p<0.001) with mosquito productivity. Table 4 shows

regression analysis to test association of adult Anopheles species productivity against

conductivity, dissolved oxygen (DO) and salinity.

3.5.1 Conductivity

For each unit increase in An. gambiae, there was a decrease in conductivity by 0.059 units.

This indicates that there was negative correlation between conductivity and An. gambiae

productivity (r<0).

3.5.2 Dissolved Oxygen

An. gambiae and An. pretoriensis showed negative correlation to DO (r<0). Increasing

dissolved oxygen was associated with a decrease in the two species. Anopheles funestus and

culicines showed positive correlation; an increase in dissolved oxygen resulted in the increase

of the two (r>0).

3.5.3 Salinity

An. gambiae and An. pretoriensis showed positive correlation to salinity (r>0), a slight

increase of salinity resulted to increase in the two species (Table 4). Anopheles funestus and

culicines showed a negative correlation to salinity (r<0), increasing salinity led to a reduction

in the density of the two.

33

Table 4: Regression of adult mosquito productivity against physicochemical variables

r-coeficient SE T P>t 95% CI

Conductivity

An. Gambiae -0.0593 0.0567 -1.05 0.296 -0.1706 0.0520

An. pretoriensis -0.2164 0.1976 -1.09 0.274 -0.6045 0.1717

An. Funestus -3.4894 3.7648 -0.93 0.354 -10.8821 3.9033

Culicines -0.0659 0.0682 -0.97 0.334 -0.1998 0.068

Dissolved

Oxygen

An. Gambiae -0.0025 0.0126 -0.20 0.842 -0.0273 0.2223

An. pretoriensis -0.0230 0.044 -0.52 0.601 -0.1094 0.0634

An. Funestus 0.0883 0.8385 0.11 0.916 -1.5581 1.7348

Culicines 0.0063 0.0152 0.42 0.676 -0.0235 0.0362

Salinity

An. Gambiae 0.0376 0.0296 1.27 0.204 -0.0205 0.0957

An. pretoriensis 0.1632 0.1031 1.58 0.114 -0.0393 0.3656

An. Funestus -0.7933 1.9639 -0.40 0.686 -4.6499 3.0632

Culicines -0.0304 0.0357 -0.85 0.395 -0.1004 0.0397

34

3.6 Body size variation in wild Anopheles mosquito population

Table 5 shows the mean body size (mm) variations amongst wild mosquitoes from natural

occurring habitats. A total of 247 samples of wild Anopheles mosquitoes collected from

emergent cages were analyzed for body size variation through wing length measurements

amongst different caged habitats in the study area. Of this, 225 (123females & 102males)

were An. gambiae, 21 (5females & 16males) were An. pretoriensis and only 1(female) was

An. funestus (Table 5). There were slight differences with respect to mosquito body sizes by

habitats. Anopheles gambiae females which emerged from ditches had mean body size of

3.08mm (range 2.5mm-3.8mm), those from pools had mean body size of 3.17mm (range

3mm-3.4mm) and those from the river had 2.96mm (range 2.6mm-3.5mm) mean body size.

Anopheles pretoriensis females emerged from ditches had mean body size of 2.8mm (range

2.5mm-3mm) while those from the river had 2.9mm mean size. One An. funestus female

emerged from ditch and had a body size of 2.5mm.

35

Table 5: The mean wing length (mm) variations amongst wild Anopheles mosquitoes from

natural occurring habitats

Habitat type

Anopheles species # Mosquitoes Ditch Pool River Grand Total

Mean wing length (mm)

An. funestus *(F) 1 2.50 *- - 2.50

An. gambiae (F) 123 3.08 3.17 2.96 3.08

An. gambiae *(M) 102 2.93 - 3.07 2.93

An. pretoriensis (F) 5 2.80 - 2.90 2.82

An. pretoriensis (M) 16 2.81 - - 2.81

Grand Total 247 2.99 3.17 2.98 2.99

*(-) = Means there was no Anopheles mosquito for body size measurement in the habitat

*(F) = Females

*(M) = Males

36

3.7 Correlation of habitat productivity and distance from human habitation

The experiment done using artificial breeding habitat to monitor Anopheline breeding

preference in distance from human habitation, Anopheles gambiae was the only malaria

vector species that was identified as having oviposited in the artificial habitats placed at 0, 25,

50, 75 and 100 meter distances (Table 6). The highest density of 3.46 Anopheles larvae per

habitat per month was recorded in February from habitats placed at 50 meter positions and the

lowest density of 0.05 larvae per habitat per month at location 0 meters in January. The

highest culicine larval density of 5.73 larvae per habitat was recorded in February in habitats

located 50 meters from human house. Both anopheline and culicine larvae were recorded in

habitats located at position 50 meters in all four months of the experiment (Table 6). Culicines

were not specific in distance and time preferences. There was no seasonal variation in

productivity of mosquitoes with distance from houses.

37

Table 6 Temporal mosquito larval density in distances recorded from artificial breeding habitats

Anophelines Culicines

Distances (m) Jan Feb Mar Apr Jan Feb Mar Apr

0 0.05 0.00 0.00 0.00 0.00 0.00 4.55 0.10

25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.35

50** 3.00** 3.46** 0.40** 0.70** 0.02 5.73 1.78 1.93

75 0.10 0.00 0.00 0.00 0.08 0.00 0.00 0.43

100 0.08 0.00 0.00 0.00 0.00 0.00 0.37 3.10

**Indicates association of distance against Anophelines oviposition in time

38

3.8 Effects of mosquito larval habitat distribution on indoor resting densities

A total of 519 adult mosquitoes were collected from ten randomly selected houses in Jaribuni

village. A summary of the different species and their distribution is shown on table 7 where

anopheline mosquitoes constituted 57% (296) of the total collection while various species of

culicines constituted 43% (223). Among the anophelines, 85(28.7%) males were collected

resting indoors. Female anophelines comprised of three species namely, An. funestus

205(97.1%), An. gambiae 5(2.4%), and An. pretoriensis 1(0.5%). Generally, the female An.

funestus were the most predominant vector species collected indoors. The temporal variation

of indoor female Anopheles populations, (Table 7) shows that December and January had

very low proportions of indoor resting Anopheles populations 8(5.5%) and 10(40%)

respectively. There was a significant association between months and number of each

Anopheles species (Pearson χ2=287.57, df=25, P=0.000)

Table 8 shows correlation of indoor resting Anopheles mosquito densities to distance from

nearest breeding site in Jaribuni village. Houses located between 60-250meters from the

nearest breeding habitats had higher mosquito densities compared to those houses that were

less than 50 and more than 250 meters from the breeding site. Generally, more than 98% of all

adult indoor collected malaria vectors were collected within this range but the peak densities

were in houses located at 60meters and 220meter distances. The nearest breeding habitats in

these two distances were the river and pools. However, lower An. gambiae and An. funestus

densities, (0.18 and 0.27 respectively) per house per collection were realized in houses near

pools. The correlation analysis of indoor resting Anopheles densities against habitat type

indicated the number of An. gambiae and An. pretoriensis reduced from ditch to river by

8.25% and 30.15% respectively, while An. funestus increased by 38.76%, the reason is the

species habitat preferences (Table 8) and was highest in the river. There was negative

correlation between the mean densities of all three Anopheles species and distances, the

39

correlation analysis showed an increase in one meter led to 40.51% An. gambiae, 32.89% An.

pretoriensis and 16.23% An. funestus reduction.

40

Table 7: Temporal variation of indoor resting mosquitoes collected (by aspiration) from Jaribuni village from December 2010 to May 2011

Month

An.gambiae

*(F)No.(%)

An.funestus

(F)No.(%)

An.pretoriensis

(F) No.(%)

Anopheles

*(M) No.(%)

Culicines(F))N

o.(%)

Culicines (M)

No.(%)

Total

December 0(0.0) 6(4.1) 0(0.0) 2(1.4) 54(37.0) 84(57.5) 146

January 1(4.0) 3(12.0) 1(4.0) 5(20.0) 7(28.0) 8(32.0) 25

February 1(1.0) 61(61.6) 0(0.0) 21(21.2) 3(3.0) 13(13.1) 99

March 1(0.8) 70(58.3) 0(0.0) 32(26.7) 10(8.3) 7(5.8) 120

April 1(1.7) 17(28.3) 0(0.0) 16(26.7) 7(11.7) 19(31.7) 60

May 1(1.4) 48(69.6) 0(0.0) 9(13.0) 3(4.4) 8(11.6) 69

Total 5(0.9)*** 205(39.5)*** 1(0.2)*** 85(16.4) 84(16.2) 139(26.8) 519

*(F)=Females, *(M)=Males

***Indicate significant diference in indoor adult Anopheles populations at p<0.05

41

Table 8: Correlation of indoor resting Anopheles mosquito densities to distance from nearest

breeding site in Jaribuni village

Habitat type Distance(m) An. gambiae An. funestus An.pretoriensis Total

Ditch 50 0.00 0.20 0.00 0.20

River 60 0.09 6.55 0.00 6.64

Pool 60 0.18 0.27 0.09 0.54

River 150 0.00 0.73 0.00 0.73

River 180 0.09 2.36 0.00 2.45

Pool 180 0.00 0.55 0.00 0.55

River 180 0.00 0.00 0.00 0.00

River 220 0.09 6.55 0.00 6.64

River 250 0.00 1.18 0.00 1.18

River 500 0.00 0.27 0.00 0.27

42

3.9 ELISA for sporozoite rate and blood meal analysis

A total of 203 samples of indoor collected female Anopheles mosquitoes from Jaribuni village

were analyzed for sporozoites by ELISA technique (Table 9). The samples comprized of An.

funestus 199(98%), An. gambiae 3(1.5%) and An. pretoriensis 1(0.5%). The

circumsporozoites (CS) protein of Plasmodium falciparum was only detected in 10 specimens

of An. funestus (5.03%) mosquitoes, while an overall sporozoite rate was 4.93%.

A total of 80 specimens were analyzed for blood meal sources among indoor collected

anopheline mosquitoes from Jaribuni village by ELISA (Table 10). The samples comprized of

77(96.2%) An. funestus, 2(2.5%) An. gambiae and only 1(1.3%) An. pretoriensis. The results

showed that, the overall preference of blood meal source for malaria vectors in the area was

humans (HBI) 0.89, followed by mixed blood sources human and goat (HGBI) 0.03, human,

goat and bovine (HGBBI) 0.01 then goat (GBI) 0.01 and 0.06 unknown. Table 10 shows the

human blood index (HBI) for An. funestus was high 0.91 (n=77) of the tested samples, while

mixed blood sources were 0.03 human and goat, and 0.01human, goat and bovine blood. The

human blood index (HBI) for An.gambiae was 0.5 (n=2) and Goat blood index (GBI) was 0.5.

A single sample of An. pretoriensis tested, the source of blood could not be detected.

43

Table 9: Plasmodium falciparum infection rate for indoor collected female Anopheles

mosquitoes from Jaribuni village Kilifi county (December 2010 to May 2011)

Species No. Tested No. Positive Sporozoite rate(%)

An. Funestus 199 10 5.03**

An. Gambiae 3 0 0.00

An. Pretoriensis 1 0 0.00

Total 203 10 4.93

** Proportion of infected Anopheles funestus species by sporozoites

44

Table 10: Blood meal sources for Anopheles species collected indoor in Jaribuni village-Kilifi

county, Kenya

% of samples

Mosquito

species

No.

Tested

Goat Human Human &

goat

Human, goat &

bovine

Unknown

An. Funestus 77 0.0 90.9* 2.6** 1.3** 5.2***

An. Gambiae 2 50.0 50.0* 0.0 0.0 0.0

An. pretoriensis 1 0.0 0.0 0.0 0.0 100.0***

Total 80 1.3 88.8* 2.5** 1.3** 6.3

*proportions of Anopheles species tested positive for human blood only

**proportion of Anophelesspecies found with mixed blood meal

***proportion of Anopheles where the blood meal could not be identified

45

4 CHAPTER FOUR: DISCUSSION, CONCLUSION AND

RECOMMENDATIONS

4.1 Discussion

Five major potential mosquito breeding habitats were identified in Jaribuni during the dry

period including river (stream), small stream pools along the river margins, manmade ditches

resulting from sand digging close to the river, abandoned water storage tanks and small

temporary trenches. Most of these man-made ditches and stream pools dried out during the

dry season while abandoned water tanks and trenches contained water in few occasions when

it rained. The river was the main source of water for stream pools and adjacent man-made

ditches. There was significant difference in Anopheles larval productivity between these

habitats, on temporal bases with the month of March showing higher larval productivity due

to rain showers during the month. It was evident that the highest Anopheles larval density was

taken from the river an observation attributed to its stability. The availability of optimal

mosquito vector species breeding habitat primarily influenced the species fecundity in a given

area (Imbahale et al., 2011).

This study found that anopheline and culicine larvae in naturally occurring habitats to co-

exist, similar to results of Mwangangi et al., (2007) indicating they are still important

breeding sites. Early instar densities for both anophelines and culicines were significantly

high in most of the sampling occasions in all types of breeding habitats compared to late

instars and pupae. This implied that, the gravid mosquitoes were attracted to oviposit on these

habitats but there was high larval mortality as suggested by the decline in populations of late

instars and pupae. The ability of the habitat to support larval survival and development to

complete life cycle was low in ditches and water tanks compared to the river and stream

pools. A combination of factors contribute to low survival rate of mosquitoes in a particular

46

habitat (Gimnig et al., 2002), which include high temperatures and low humidity. These

climatic factors may contribute to the drying up of small habitats, and thus making them less

suitable for mosquito breeding. Other factors that may limit the increase in larval populations

include overcrowding of larvae in a habitat leading to resources competition, physicochemical

factors imbalances and intra/inter-specific predation among mosquitoes (Carlson et al, 2004).

However, Minakawa et al (2005) observed that larval habitat stability was the most important

factor affecting survivorship of mosquito larvae. The hot dry season had resulted into several

small temporary ditches and pools drying out before the larva reached the adult stage.

Nevertheless, dry weather accelerated larval development in aquatic habitats; reduced river

water volume and velocity made the margins and stream pools with submerged vegetation

favorite breeding habitats for An. funestus in the area resulting into increased adult population.

Emerging adult mosquitoes monitored by emergent traps over natural occurring habitats

showed the river, stream pools and ditches were the most productive. An. gambiae s.l was the

predominant collected adult mosquito species among malaria vectors in the area but these

results were not comparable to those of indoor resting mosquito collection where An. funestus

was the predominant species. This difference might be caused by more than a few reasons,

including breeding preferences of these two anopheles species, number of cages placed over

the permanent breeding habitats against small temporary ones, and their feeding and resting

behaviours. Findings similar to this have been reported from the Gambia, West Africa by

Bogh et al., (2003), between two Anopheles species, An. melas and An. gambiae ss, and also

in Western Kenya between An. gambiae ss and An. arabiensis (Minakawa et al., 1999).

If this difference is attributable to the feeding and resting behaviour of the Anopheles species,

then most probably, majority of the collected An. gambiae s.l were An. arabiensis. In the

current study, further analysis of anophelines to sibling species could not be done but one

47

sample of An. gambie s.l. collected indoor was analyzed for blood meal by ELIZA and was

found with goat’s blood. This result indicated the existence of zoophagic An. gambiae

complex species in the area. An. arabiensis are zoophagic and exophilic mosquito (Mahande

et al., 2007) and they are normally predominant in dry, hot season (Githeko et al., 1996).

Moreover, it’s probable that cages were useful in reducing the sunlight intensity to the habitat.

This could have reduced water evaporation rate and prolonged wet time for An. gambiae s.l to

complete their development to adults in temporary pools and ditches compared to bare

habitats. There was continuous emergence of adult mosquitoes from caged habitats although

in low numbers throughout the experiment. This implied that there were mixed aquatic

mosquito stages confined in habitats by cages showing the difference in oviposition time

among the species.

Prior sampling was done for the presence and absence of aquatic stages before placing an

emergence cage for adult mosquito emergence. In three months of this experiment, ditches

were found to be the most productive habitats for adults over time. Due to the fact that they

were higher in number and more cages were placed on them. For instance, in March only

ditches were productive for anophelines and the higher numbers were recorded in the

following months of April and May. This experiment revealed that An. gambiae s.l.

mosquitoes were the most emerged malaria vector species in natural occurring habitats. The

emergent cages placed on river margins were less productive for adult mosquitoes. Probably,

this was due to predation but also in several occasions during this experiment, the river

flooded when it rained. When the river was flooded, the cages were pushed away and pre-

mature mosquitoes were drowned. Setting up emergent cages in flooded river was not

feasible. Consequently, less number of cages placed over the river resulted into less emerged

adult mosquitoes collected. Some few An. pretoriensis and one An. funestus were among

48

collected malaria vectors from ditches in the month of April. In comparison, the month of

April was the most productive for emerging adult mosquitoes from natural habitats to other

two months of experiment i.e. March and May. The few rains in April averaged 2.13mm and

atmospheric temperature 32.5oC improved the habitat stability and suitability for the aquatic

stage mosquito developments to adults. Other physicochemical factors such as salinity,

dissolved oxygen and conductivity were in the range favoring Anopheles production in the

habitats.

Body size variation of the Anopheles results showed that, An. gambiae s.l that emerged from

ditches and pools had mean body sizes of 3.08mm and 3.17mm respectively. This implied that

they were efficient malaria vectors since body size of 3mm or above has been shown to

enhance the vectorial capacity of mosquitoes (Lyimo and Takken, 1993). Anopheles gambie

from the river were smaller with mean body size of 2.96mm these have less chances of

survival and are thus less efficient vectors. Body size is an important feature in mosquito

fitness because it is associated with longevity, survival, blood meal capacity (Kelly and

Edman, 1992), and number of eggs per single oviposition (Woke, et al.,, 1956), all of which

influence the vectorial capacity. Well grown mosquitoes of 3mm or above have higher chance

of living longer than smaller mosquitoes. Vector longevity provides enough time for a

parasite they harbour to develop up to its infective stage (Howley, 1985). A fully grown

female Anopheles mosquito needs a single blood meal for each gonotrophic cycle (Lyimo and

Takken, 1993). This has an advantage of reducing the risk of being killed by the vertebrate

host out of repeated feeding visits. Schwartz and Koella, (2001) noted that “biting is risky, the

mosquito mortality increases with its biting rate”. A mosquito is capable of producing many

eggs in a single batch, this reproductive success enables a single mosquito to easily maintain

its colony in the locality and sustain disease transmission. The same fitness applies to males in

49

terms of mating success and mating frequencies (Takken et al., 2006). The vectorial capacity

of the mosquito is greatly influenced by combination of these factors. In all the samples,

sexual dimorphism was evident as exemplified by the differences in size for both female and

male in all the species

Artificial habitats placed at 0, 25, 50, 75 and 100m distances from human habitations to

monitor anopheline breeding preferences, showed that, An. gambiae was the only malaria

vector that oviposited although the area has higher population of An. funestus. This was due to

the fact that An. gambiae prefer breeding in small temporary water bodies subjected to direct

sunlight (Gillies and Coetzee, 1987), as was the artificial habitats, although they tend to adapt

in different new environments (Filliger et al., 2004). An. funestus did not oviposit in artificial

habitats because their preference is large permanent shaded water bodies with vegetation

(Gillies and DeMeilon, 1968) like the Jaribuni River. Higher densities of Anopheles larvae

were observed in habitats located at 50m distances from human houses in different occasions,

compared to only once in 0, 75, and 100m distances. Culicine larvae were widely distributed

in all habitat locations for the whole period of experiment because they are non-selective

breeders. There were no seasonal variations in productivity observed during four months of

experiment, although mosquito populations were low because the area was hot and dry.

The closeness of An. gambiae to human habitations had also been observed in indoor resting

mosquito collections, relatively high proportions were collected in houses located between

60m and 120m from the nearest breeding habitats. This implied that spatial distribution of An.

gambiae breeding habitats is associated with distribution of human habitations. Habitat

specificity was also observed in indoor resting collections, peak densities of An. funestus were

collected from houses located near to the river while An. gambiae from houses near to the

ditches and pools. Generally, the results showed that there was a decrease in indoor Anopheles

50

mosquito population with an increase in distance from the nearest breeding habitat, suggesting

that malaria vectors in the study area bred proximal to human habitations. The mark-release-

capture studies conducted in the same area by Midega et al., (2007), showed that house

location and distance did not correlate with aquatic habitats of Anopheles mosquitoes. The

results in the current study show that during the extensive dry season in Jaribuni village, the

river and adjacent stream pools and ditches were the main reliable breeding habitats

throughout the year and An. funestus was the predominant species. These results comply with

the study by Mbogo et al., (2003); Braginets et al., (2003) along the coast of Kenya. It is said

that An. funestus is the “bridging species” between the dry and wet season (Mbogo et al.,

2003), especially in the settings like Jaribuni village having a permanent river which is a

stable habitat all year round. Such vector population dynamical outcomes sustain malaria

transmission.

The ELISA analysis for malaria vectors gave a 4.93% infection rate of mosquitoes infected

with circumsporozoites (CS) protein of P. falciparum, which probably correlate with high

infectiousness of human population in the area. From all malaria vector species collected

resting indoors; only An. funestus mosquitoes were found infected with parasite by 5.03%.

This has higher implication in malaria transmission dynamics in the locality, since the main

reliable breeding source in the dry season is the river crossing the village and adjacent pools

and ditches which have shown to be very productive for An. funestus. Although this study

found high population of An. gambiae s.l and few An. pretoriensis from the aquatic habitats,

low populations of these two species were found indoors and none of them were found

infected with circumsporozoite protein of P. falciparum. This however, does not propose that

An. gambiae and An. pretoriensis are not playing significant role in malaria transmission in

the study area. The social and cultural behaviour of the hosts and host preferences of the

51

mosquito species can drive into host selection and eventually influence the prevalence of the

disease in a locality (Burkot, 1988). The study conducted in southern Ethiopia on An.

arabiensis feeding behaviour (Tirados, et al., 2006) found that, in the areas where humans

were more readily available, the mosquitoes fed on humans, in the situation where animals

were accessed easier, they fed upon them.

The results of the blood meal analyses confirmed high anthropophagic, endophilic behaviour

of An. funestus. Their specific human blood index (HBI) was high 0.90, concomitant with

their established disposition as main malaria vectors in tropical Africa. Results similar to

these on sporozoite rate and blood meal tests for An. funestus in the area have been reported

by Mbogo et al (2003). On the other hand, these results suggest that residents in the village

are facing a high malaria risk although most of the houses (80%) sampled indoor resting

mosquitoes had bed nets. These results suggest more research on biting behaviour of

mosquitoes as well as sleeping behavior of the people in the area. The mixed blood meals

identified in 3 samples of An. funestus, possibly was due to the failure of the mosquitoes to

complete their gonotrophic circle by only one blood meal. The observed mixed blood meals

from two and three hosts can also be considered to these mosquito species, as adaptable to

feeding from any available host. This multiple hosts feeding behavior of mosquitoes may

facilitate the transmission of zoonotic diseases, such as West Nile fever and Rift Valley fever

as was alerted by Muriu et al., (2008) in a study conducted in Mwea rice scheme, where the

multiple hosts feeding was very high among collected mosquito species. A sample of An.

gambiae s.l collected resting indoor and tested positive for goat’s blood only, evidenced that

there were some mosquitoes in the area feeding outside but enter the house to rest or they

were still seeking more blood meal from human for eggs development.

52

4.2 Conclusion

This study revealed that mosquito breeding habitats are diverse in Jaribuni village but river

and its adjoining pools provided a stable source of mosquitoes. Mosquitoes from more

permanent habitats were generally small in size. Temperature, salinity, conductivity,

dissolved oxygen and distance from human habitations were found to correlate with malaria

vector production in the habitats. The spatial distribution of aquatic habitats correlates with

human host seeking mosquito indoor densities. Malaria vectors colonized habitats proximal to

the residential houses (250m). An. funestus is the predominant malaria vector during hot dry

season in Jaribuni village given its high density indoors and in permanent breeding habitats,

higher proportion of anthropophagic behaviour and high proportion of sporozoite rate.

4.3 Recommendations

Vector populations emerging from our experimental habitats did not match the vector

populations from house catches. Therefore, further research needs to be done with the

objective of ascertaining outdoor-resting malaria vector populations and their feeding

behaviours as regards the potential of malaria transmission. Further work should be done to

establish An. gambiae s.l sibling species dispersion patterns from source, host seeking and

resting behaviours. Environmental management for malaria vector control should be adopted

as a key interventional method alongside existing ones for reduction of local vector

populations in the area of Jaribuni, in Kilifi County at the coast of Kenya.

53

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