1 International Water Management Institute (IWMI), PO Box 2075, Colombo, Sri Lanka.
2 Department of International Health, University of Copenhagen, Denmark.
3 Department of Molecular Biology and Biotechnology, Faculty of Science, University of Peradeniya, Sri Lanka.
4 Anti-Malaria Campaign, Anuradhapura, Sri Lanka.
Correspondence: Wim van der Hoek, International Water Management Institute, PO Box 2075, Colombo, Sri Lanka. E-mail: w.van-der-hoek{at}cgiar.org
![]() |
Abstract |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
Methods In a group of seven villages in north central Sri Lanka, malaria cases were compared with community controls for distance from house to breeding sites and a number of other variables, including type of housing construction and use of anti-mosquito measures. The presence of An. culicifacies in bedrooms was determined by indoor insecticide spray collections.
Results People living within 750 m of the local stream, which was the established vector-breeding site, were at much higher risk for malaria than people living further away (odds ratio adjusted for confounding by other variables 5.93, 95% CI: 3.508.91). Houses close to the stream also had more adult An. culicifacies in the bedrooms. Poor housing construction was an independent risk factor for malaria.
Conclusions Risk maps of malaria in Sri Lanka can be based on the location of houses relative to streams and rivers that are potential breeding sites for the malaria vector An. culicifacies. A distance of 750 m is suggested as the cut-off point in defining low- and high-risk villages.
Accepted 21 October 2002
Recently there has been keen interest in mapping malaria distribution and risk. Such maps would make it possible to target control measures at high-risk areas and greatly increase the cost efficiency of malaria control programmes.1,2 Most risk maps that have been developed so far have used as key inputs climatic models and information on weather data such as rainfall, temperature, and relative humidity, which, to a large extent, determine the survival and reproduction of the vector mosquito and the development of the parasite in the vector.3,4 Other studies have used different indicators of vector presence, reproduction, and survival, such as vegetation patterns, land use, and soil moisture.57 The environmental and climatic variables are then linked with entomological and epidemiological information to identify geographical areas at high risk for malaria. These have covered either vast areas, such as the efforts to map the malaria risk in Africa8 or a relatively limited number of villages.9
In Sri Lanka, the major vector of malaria, Anopheles culicifacies, breeds mainly in pools formed in streams and riverbeds.1013 In a series of mark-release recapture experiments on An. culicifacies it was shown that this species could travel at least 500 m in one night14 and that 27% of An. culicifacies mosquitoes had flown a distance of 2 km to a recapture village within 47 days of marking and release.15 Although the estimation of flight ranges has a number of methodological difficulties and depends on the local ecology, it is expected that people living close to the breeding sites would be at higher risk for the disease. A risk map of malaria for Sri Lanka could therefore, in principle, be based on the availability of surface water that has a potential for pool formation during critical periods of the year. However, it is crucial that the demarcation of high-risk areas based on entomological findings is supported by epidemiological evidence. It has been shown that the build-up of An. culicifacies in stream-bed pools in the dry season is the essential mechanism that eventually leads to the seasonal peak of human malaria.16 Two studies in Sri Lanka have tried to estimate the risk of living close to breeding sites. In southern Sri Lanka, residents of houses located close to potential breeding sites had a higher risk for malaria, but only if the house was poorly constructed and provided easy access to mosquitoes.17 In a study in one village in north central Sri Lanka, living close to the local stream was a risk factor for malaria, although of borderline significance when controlled for a range of other risk factors.18 In both studies, most houses were located less than 500 m from the breeding site and there was, therefore, a limited contrast between exposed and non-exposed houses. To further investigate the importance of house location relative to established and potential breeding sites we expanded our previous study in one village18 to seven villages with a larger contrast in distance from houses to breeding sites. The study was done to find out how important distance from house to breeding site is for the occurrence of malaria relative to other potential risk factors. This would then make it possible to decide whether, in Sri Lanka and in countries with similar conditions, risk maps of malaria could be based on this distance parameter.
![]() |
Methods |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
Cases were inhabitants of the seven villages who attended the village treatment centre, the district hospital in Kekirawa, or a mobile clinic of the Anti-Malaria Campaign, and who were found to have a blood film positive for malaria parasites between March 1997 and May 1999. Controls were defined as people from the seven villages who did not report an episode of malaria during the previous 2 weeks. The control series was obtained by randomly sampling four people from the census list of the seven villages for each case. Initially four clinic controls were selected from the registries of the health facilities in addition to the community controls. However, this was discontinued in October 1998 when an outbreak of malaria made it logistically impossible to collect the required information within the set time limits and when not enough clinic controls were available for each malaria case. Individuals selected as controls, who later developed malaria were counted as both a control and a case and individuals could be selected more than once as a control.21 A positive blood film less than 28 days after a previous positive blood film was considered a recrudescence and was not included in the analysis as a new case. Trained field assistants visited the cases and controls at their houses to collect information on a range of exposure variables. A structured questionnaire in the local language was used to obtain information on use of preventive measures and use of anti-malaria drugs in the past 2 weeks for controls and in the 2 weeks before diagnosis for the cases. Parameters pertaining to the type of housing construction and presence of vegetation and cattle sheds near the house were based on direct observations by the interviewer. If a household reported bed net use, the enumerator asked permission to inspect the bed net. Houses were classified as good if they had complete brick walls and a roof of permanent material (tiles, asbestos, or corrugated iron) and as poor if they had incomplete walls, walls made of mud, or a thatched roof. Households were visited up to three times. If the selected person or caretaker was not present at the third visit, any adult household member was questioned about the malaria episode. The maximum time between diagnosis and collection of data was 2 weeks. Regular supervision in the field took place by the authors themselves.
At the treatment centre, as well as at the Kekirawa hospital, all malaria patients received standard treatment with chloroquine and primaquine according to the national guidelines of the Anti-Malaria Campaign of Sri Lanka. According to the same guidelines, patients with a Plasmodium falciparum infection were asked to come back after 7 days for a second blood slide reading and if still found positive were given sulphadoxine-pyrimethamine.
The study protocols and ethical aspects of the study were reviewed by the Provincial Director of Health Services. Community meetings were organized in the study area to inform the population and solicit their opinion on the establishment of the treatment centre and the research project associated with it. During the study period the regular malaria control measures of the Anti-Malaria Campaign, including residual house spraying with insecticides, continued.
Mosquito collections
Methods and results of the entomological component of the study will be reported in more detail elsewhere. Briefly, from May 1996 to December 1998 indoor-resting mosquito densities were estimated based on fortnightly collections. For each collection 10% of the houses were randomly sampled in each of the villages. To collect mosquitoes a team of two assistants and one entomologist sampled the room of the selected houses where individuals had been sleeping the night before. After covering all exits, a white cotton sheet was placed on the floor and a pyrethrum-based insecticide was sprayed in the room. Fifteen minutes following the spraying the mosquitoes were collected from the sheet and kept in separate vials for each house. All mosquitoes collected were identified on the same day in the field and recorded by species, gender, and blood meal status for female mosquitoes. In total 2652 spray sheet collections were done in the 473 houses of the seven villages.
Data analysis
For each house the shortest distance to the Yan Oya stream was calculated using ArcInfo geographical information system software (Environmental Systems Research Institute, Redlands, CA, USA). All other analyses were done with SPSS version 8.0. Control for confounding was done with multiple logistic regression.
![]() |
Results |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
|
|
![]() |
Discussion |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
The association between malaria risk and distance from house to breeding sites has been documented in other parts of the world where different vectors play a role, but it was never as strong as in Sri Lanka.6,2224 While in large parts of Africa breeding places of the vector An. gambiae are diffuse and various, the breeding places of An. culicifacies in Sri Lanka are very much confined to streams. In the Sri Lankan situation one would like to map rivers and streams that have the potential for pooling and superimpose a population distribution map to identify the population at risk. While this would have been a difficult task some years ago, new technologies such as satellite remote sensing and geographical information systems have made it possible to map large areas at low cost. These modern technologies would have to be combined with expert knowledge of malaria control personnel and water resources managers in the field. In general, it is well known by malaria control personnel in Sri Lanka that malaria risk and outbreaks depend heavily upon the dynamics of a relatively small number of rivers and streams.
In addition to rivers and streams there are an estimated 18 000 irrigation reservoirs (tanks) in Sri Lanka. These reservoirs seem less important for the generation of epidemiologically relevant vector mosquitoes than the rivers and streams, but their role has only recently been investigated in more detail.25
An alternative explanation for the low number of malaria cases in villages far from the stream could be that people from these villages went for treatment elsewhere. However, based on an intensive study of health-seeking behaviour in the same villages we are confident that this was not the case.20 Two other hospitals in the area were visited on a regular basis by the researchers to check the records, but no malaria cases were recorded from the study area. Furthermore, the epidemiological results had a clear biological explanation, with an increased risk of having the vector mosquito in the house when the house was located close to the stream. The dispersal range of vector mosquitoes emanating from breeding sites depends on several factors, including wind speed and direction, vegetation pattern, and the fauna, consisting of domestic animals and wildlife to feed on. However, based on the epidemiological data presented, the effective flight range of the vector mosquito can be considered to be less than 1 km.
The study could not describe the protective effects of personal and household malaria control measures very well. The exposure contrast was often small, with few people using bed nets and most houses covered by the insecticide-spraying programme. However, this reflects the actual situation in most of the malaria endemic zones of Sri Lanka. The study found that people living close to the stream used more preventive measures, especially traditional fumigants. We only sampled anopheline mosquitoes but it is likely that more nuisance biting mosquitoes were found close to the stream and that this explained the high usage of preventive measures. Cattle are important blood-meal hosts of anopheline mosquitoes and could either divert mosquitoes away or attract them in larger numbers to human dwellings. This study found no clear effect of distance from house to cattle shed. Our risk estimate for type of housing construction was similar to the one found in another part of Sri Lanka.17 However, the results of the present study suggest that location of house relative to breeding sites is a more important independent risk factor for malaria.
As expected, malaria was clustered in a relatively small number of households. Twenty-nine individuals had more than one malaria episode recorded during the year and five individuals had three episodes. If there was one month in between two malaria episodes, the second episode was registered as a new case. This time period is rather arbitrary, but we feel that with the clear follow-up procedures it was unlikely that after more than one month it was still the same infection. Prior primaquine treatment also made relapse of P. vivax infections less likely.
We have previously described the succession of peaks of An. culicifacies larvae, adult mosquitoes, and human malaria cases that occurred in one of the study villages in 1994.19 After that time, malaria incidence in the study area remained low until the sharp increase during September and October 1998. This illustrates the unstable nature of malaria transmission in Sri Lanka with highly fluctuating incidence from year to year.13
Insecticides for malaria control take up a large part of the health budget of Sri Lanka. While the residual spraying programme has already evolved from blanket coverage to a stratified approach, spatial targeting with the help of risk maps would further reduce costs. The risk map approach would also be useful for planning of other malaria control measures such as distribution of (impregnated) bed nets, larviciding, and environmental management measures. We have proposed the use of water management for the control of breeding of the vector as a low cost measure.26 Risk maps would make it possible to combine water management with very focused spraying activities and bed net impregnation programmes. This would be a strong combination of control measures that would have to be applied only part of the year.
In Sri Lanka it seems appropriate to base risk maps for malaria on the location of houses relative to streams and rivers that are potential breeding sites for the vector An. culicifacies. The present study suggests the use of a distance of 750 m as cut-off point for a risk map. Once such a risk map is constructed, this measure has to be validated with additional field-level studies. It could then lead to more cost-efficient targeting of control measures, location of treatment facilities, and also find use for decision making in development projects, especially settlement policies.
![]() |
Acknowledgments |
---|
![]() |
Notes |
---|
![]() |
References |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
2 Carter R, Mendis KN, Roberts D. Spatial targeting of interventions against malaria. Bull World Health Organ 2000;78:140111.[ISI][Medline]
3 Thomson MC, Connor SJ, Milligan P, Flasse SP. Mapping malaria risk in Africa: what can satellite data contribute. Parasitol Today 1997;13: 31318.[CrossRef][ISI][Medline]
4 Craig MH, Snow RW, Le Sueur D. A climate-based distribution model of malaria transmission in sub-Saharan Africa. Parasitol Today 1999; 15:10511.[CrossRef][ISI][Medline]
5 Beck LR, Rodriguez MH, Dister SW et al. Remote sensing as a landscape epidemiologic tool to identify villages at high risk for malaria transmission. Am J Trop Med Hyg 1994;51:27180.[ISI][Medline]
6 Rejmankova E, Roberts DR, Pawley A, Manguin S, Polanco J. Predictions of adult Anopheles albimanus densities in villages based on distances to remotely sensed larval habitats. Am J Trop Med Hyg 1995; 53:48288.[ISI][Medline]
7 Patz JA, Strzepek K, Lele S et al. Predicting key malaria transmission factors, biting and entomological inoculation rates, using modelled soil moisture in Kenya. Trop Med Int Health 1998;3:81827.[CrossRef][ISI][Medline]
8 Snow RW, Craig MH, Deichmann U, Le Sueur D. A preliminary continental risk map for malaria mortality among African children. Parasitol Today 1999;15:99104.[CrossRef][ISI][Medline]
9 Thomas CJ, Lindsay SW. Local-scale variation in malaria infection amongst rural Gambian children estimated by satellite remote sensing. Trans R Soc Trop Med Hyg 2000;94:15963.[CrossRef][ISI][Medline]
10 Carter HF. The anopheline mosquitoes of Ceylon. The differential characters of the adults and larvae. Ceylon Journal of Science (D) 1925;1:5798.
11 Carter HF, Jacocks WP. Observations on the transmission of malaria by anopheline mosquitoes in Ceylon. Ceylon Journal of Science (D) 1929;2:6786.
12 Amerasinghe FP, Ariyasena TG. Larval survey of surface water-breeding mosquitoes during irrigation development in the Mahaweli project, Sri Lanka. J Med Entomol 1990;27:789802.[ISI][Medline]
13 Konradsen F, Amerasinghe FP, van der Hoek W, Amerasinghe PH. Malaria in Sri Lanka: Current Knowledge on Transmission and Control. Colombo: International Water Management Institute, 2000, pp. 177.
14 Curtis CF, Rawlings P. A preliminary study of dispersal and survival of Anopheles culicifacies in relation to the possibility of inhibiting the spread of insecticide resistance. Ecol Entomol 1980;5:1117.[ISI]
15 Rawlings P, Curtis CF, Wickremasinghe MB, Lines J. The influence of age and season on dispersal and recapture of Anopheles culicifacies in Sri Lanka. Ecol Entomol 1981;6:30719.[ISI]
16 Amerasinghe FP, Konradsen F, Fonseka KT, Amerasinghe PH. Anopheline (Diptera: culicidae) breeding in a traditional tank-based village ecosystem in north central Sri Lanka. J Med Entomol 1997;34: 29097.[ISI][Medline]
17 Gunawardena DM, Wickremasinghe AR, Muthuwatta L et al. Malaria risk factors in an endemic region of Sri Lanka, and the impact and cost implications of risk factor-based interventions. Am J Trop Med Hyg 1998;58:53342.
18 van der Hoek W, Konradsen F, Dijkstra DS, Amerasinghe PH, Amerasinghe FP. Risk factors for malaria: a microepidemiological study in a village in Sri Lanka. Trans R Soc Trop Med Hyg 1998;92:26569.[CrossRef][ISI][Medline]
19 Amerasinghe PH, Amerasinghe FP, Konradsen F, Fonseka KT, Wirtz RA. Malaria vectors in a traditional dry zone village in Sri Lanka. Am J Trop Med Hyg 1999;60:42129.
20 Konradsen F, Amerasinghe PH, Perera D, van der Hoek W, Amerasinghe FP. A village treatment center for malaria: community response in Sri Lanka. Soc Sci Med 2000;50:87989.[CrossRef][ISI][Medline]
21 Rothman KJ, Greenland S. Case-control studies. In: Rothman KJ, Greenland S (eds). Modern Epidemiology. 2nd Edn. Philadelphia: Lippincott-Raven Publishers, 1998, pp. 93114.
22 Thompson R, Begtrup K, Cuamba N et al. The Matola malaria project: a temporal and spatial study of malaria transmission and disease in a suburban area of Maputo, Mozambique. Am J Trop Med Hyg 1997;57: 55059.[ISI][Medline]
23 Kleinschmidt I, Bagayoko M, Clarke GPY, Craig MH, Le Sueur D. A spatial statistical approach to malaria mapping. Int J Epidemiol 2000; 29:35561.
24 Guthmann JP, Hall AJ, Jaffar S, Palacios A, Lines J, Llanos-Cuentas A. Environmental risk factors for clinical malaria: a case-control study in the Grau region of Peru. Trans R Soc Trop Med Hyg 2001;95:57783.[CrossRef][ISI][Medline]
25 Amerasinghe FP, Konradsen F, van der Hoek W et al. Small Irrigation Tanks as a Source of Malaria Mosquito Vectors: A Study in North-Central Sri Lanka. Research Report no. 57. Colombo: International Water Management Institute, 2001, pp. 128.
26 Konradsen F, Steele P, Perera D, van der Hoek W, Amerasinghe PH, Amerasinghe FP. Cost of malaria control in Sri Lanka. Bull World Health Organ 1999;77:30109.[ISI][Medline]