The influence of urbanisation on measures of Plasmodium falciparum infection prevalence in East Africa.

There is a growing interest in the effects of urbanisation in Africa on Plasmodium falciparum risks and disease outcomes. We undertook a review of published and unpublished literature to identify parasite survey data from communities in East Africa. Data were selected to represent the most reliable and contemporary estimates of infection prevalence and were categorised by urban or rural status using a number of approaches. We identified 329 spatially distinct surveys undertaken since 1980 in the sub-region of which 37 were undertaken in urban settlements and 292 in rural settlements. Overall rural settlements reported significantly higher parasite prevalence among children aged 0-14 than urban settlements (on average 10% higher infection rates; p<0.05). No urban settlements recorded parasite prevalence in excess of 75%. In areas of East Africa where climatic conditions are likely to support higher parasite transmission, the rural-urban difference was most marked. There was a significant trend towards documenting higher classes of parasite prevalence in rural compared to urban settlements (p<0.05) and the mean difference between rural and urban samples was 18% (p<0.001). These results further highlight the need to better define urban extents in Africa in order to capture the non-climatic determinants of infection and disease risk and provide a more informed approach to describing the burden of disease across the continent.

Earth observation, geographic information systems and Plasmodium falciparum malaria in sub-Saharan Africa.

This review highlights the progress and current status of remote sensing (RS) and geographical information systems (GIS) as currently applied to the problem of Plasmodium falciparum malaria in sub-Saharan Africa (SSA). The burden of P. falciparum malaria in SSA is first summarized and then contrasted with the paucity of accurate and recent information on the nature and extent of the disease. This provides perspective on both the global importance of the pathogen and the potential for contribution of RS and GIS techniques. The ecology of P. falciparum malaria and its major anopheline vectors in SSA in then outlined, to provide the epidemiological background for considering disease transmission processes and their environmental correlates. Because RS and GIS are recent techniques in epidemiology, all mosquito-borne diseases are considered in this review in order to convey the range of ideas, insights and innovation provided. To conclude, the impact of these initial studies is assessed and suggestions provided on how these advances could be best used for malaria control in an appropriate and sustainable manner, with key areas for future research highlighted.

Updating Historical Maps of Malaria Transmission Intensity in East Africa Using Remote Sensing.

Remotely sensed imagery has been used to update and improve the spatial resolution of malaria transmission intensity maps in Tanzania, Uganda, and Kenya. Discriminant analysis achieved statistically robust agreements between historical maps of the intensity of malaria transmission and predictions based on multitemporal meteorological satellite sensor data processed using temporal Fourier analysis. The study identified land surface temperature as the best predictor of transmission intensity. Rainfall and moisture availability as inferred by cold cloud duration (ccd) and the normalized difference vegetation index (ndvi), respectively, were identified as secondary predictors of transmission intensity. Information on altitude derived from a digital elevation model significantly improved the predictions. "Malaria-free" areas were predicted with an accuracy of 96 percent while areas where transmission occurs only near water, moderate malaria areas, and intense malaria transmission areas were predicted with accuracies of 90 percent, 72 percent, and 87 percent, respectively. The importance of such maps for rationalizing malaria control is discussed, as is the potential contribution of the next generation of satellite sensors to these mapping efforts.

Plasmodium falciparum parasite prevalence in East Africa: a review.

OBJECTIVES: Empirical data on malaria endemicity are rarely available for public domain use to guide effective malaria control. This paper describes the work carried in East Africa since 1997 as part of a pan-African collaboration to map the risk of malaria, Mapping Malaria Risk in Africa (MARA) aimed at redressing deficiency. DATA EXTRACTION: Studies of cross-sectional community estimates of Plasmodium falciparum prevalence among children aged 0-15 years were identified from a variety of sources including electronic searches of published material, manual review of pre-electronic peer reviewed journals and searches of libraries and archives in Kenya, Tanzania and Uganda. Each survey source, infection prevalence, date, longitude and latitude and survey characteristics were recorded. DATA SYNTHESIS: All data were subjected to a number of selection criteria including minimum sample sizes, samples randomly selected, community-based surveys, age ranges of sampled communities within 0-15 years, and surveys that were spatially unique. Of the 2,003 survey data points identified since 1907 in East Africa, only 503 were eligible for inclusion in the analysis dating from 1927 to 2003. The spatial plots of the data demonstrate the paucity of information on malaria prevalence from a number of densely populated areas and highlight the concentration of empirical data in concert with research centres in the sub-region. CONCLUSIONS: Models are required to define malaria risk in areas of East Africa where no empirical data are available so that limited resources can be better targeted to those in greatest need.

Modelling malaria risk in East Africa at high-spatial resolution.

OBJECTIVES: Malaria risk maps have re-emerged as an important tool for appropriately targeting the limited resources available for malaria control. In Sub-Saharan Africa empirically derived maps using standardized criteria are few and this paper considers the development of a model of malaria risk for East Africa. METHODS: Statistical techniques were applied to high spatial resolution remotely sensed, human settlement and land-use data to predict the intensity of malaria transmission as defined according to the childhood parasite ratio (PR) in East Africa. Discriminant analysis was used to train environmental and human settlement predictor variables to distinguish between four classes of PR risk shown to relate to disease outcomes in the region. RESULTS: Independent empirical estimates of the PR were identified from Kenya, Tanzania and Uganda (n = 330). Surrogate markers of climate recorded on-board earth orbiting satellites, population settlement, elevation and water bodies all contributed significantly to the predictive models of malaria transmission intensity in the sub-region. The accuracy of the model was increased by stratifying East Africa into two ecological zones. In addition, the inclusion of urbanization as a predictor of malaria prevalence, whilst reducing formal accuracy statistics, nevertheless improved the consistency of the predictive map with expert opinion malaria maps. The overall accuracy achieved with ecological zone and urban stratification was 62% with surrogates of precipitation and temperature being among the most discriminating predictors of the PR. CONCLUSIONS: It is possible to achieve a high degree of predictive accuracy for Plasmodium falciparum parasite prevalence in East Africa using high-spatial resolution environmental data. However, discrepancies were evident from mapped outputs from the models which were largely due to poor coverage of malaria training data and the comparable spatial resolution of predictor data. These deficiencies will only be addressed by more random, intensive small areas studies of empirical estimates of PR.

Relation between severe malaria morbidity in children and level of Plasmodium falciparum transmission in Africa.

BACKGROUND: Malaria remains a major cause of mortality and morbidity in Africa. Many approaches to malaria control involve reducing the chances of infection but little is known of the relations between parasite exposure and the development of effective clinical immunity so the long-term effect of such approaches to control on the pattern and frequency of malaria cannot be predicted. METHODS: We have prospectively recorded paediatric admissions with severe malaria over three to five years from five discrete communities in The Gambia and Kenya. Demographic analysis of the communities exposed to disease risk allowed the estimation of age-specific rates for severe malaria. Within each community the exposure to Plasmodium falciparum infection was determined through repeated parasitological and serological surveys among children and infants. We used acute respiratory-tract infections (ARI) as a comparison. FINDINGS: 3556 malaria admissions were recorded for the five sites. Marked differences were observed in age, clinical spectrum and rates of severe malaria between the five sites. Paradoxically, the risks of severe disease in childhood were lowest among populations with the highest transmission intensities, and the highest disease risks were observed among populations exposed to low-to-moderate intensities of transmission. For severe malaria, for example, admission rates (per 1000 per year) for children up to their 10th birthday were estimated as 3.9, 25.8, 25.9, 16.7, and 18.0 in the five communities; the forces of infection estimated for those communities (new infections per infant per month) were 0.001, 0.034, 0.050, 0.093, and 0.176, respectively. Similar trends were noted for cerebral malaria and for severe malaria anaemia but not for ARI. Mean age of disease decreased with increasing transmission intensity. INTERPRETATION: We propose that a critical determinant of life-time disease risk is the ability to develop clinical immunity early in life during a period when other protective mechanisms may operate. In highly endemic areas measures which reduce parasite transmission, and thus immunity, may lead to a change in both the clinical spectrum of severe disease and the overall burden of severe malaria morbidity.

PIP: 3556 pediatric admissions with severe malaria over 3-5 years from five discrete communities in the Gambia and Kenya were recorded prospectively in a study of the relationship between parasite exposure and the development of effective clinical immunity against malaria. The exposure to Plasmodium falciparum infection in each community was determined through repeated parasitological and serological surveys among children and infants, while acute respiratory tract infections (ARI) were used as a comparison. Clear differences were observed in age, clinical spectrum, and rates of severe malaria between the five sites. The risks of severe disease in childhood were lowest in populations with the highest transmission intensities, while the highest disease risks were observed among populations exposed to low-to-moderate intensities of transmission. Similar trends were observed for cerebral malaria and severe malaria anemia, but not for ARI. The mean age of disease decreased with increasing transmission intensity.