Total: 149
Estimating the Plasmodium falciparum morbidity and mortality burden 2005 and 2009 in Somalia: Combining models of population distribution, time-space changes in malaria infection risk and the epidemiology of malaria disease burden
Report prepared for UNICEF-Somalia, March 2010.
Author(s): Snow RW, Alegana VA, Okiro EA, Gething PW, Patil P, Tatem A.J., Linard C, Moloney G, Borle M, Yusuf FE, Amran J, Noor AM
Type: application. Year: 2010
DOI: .

Abstract: To effectively guide malaria control and understand how interventions impact on transmission of the parasite it is important to map where people live in relation to the intensity of malaria transmission. We developed a model of human population settlement interpolated across space to define the distributions of people at risk of malaria. We used parasite prevalence data assembled from 1657 community surveys to spatially model the distribution of malaria risk at 1x1 km resolutions. This model showed a good correlation between predicted and observed estimates of infection in a withheld test data set (2005-07: R2 = 0.76; Mean error = -2.7%; 2008-09: R2 = 0.71; Mean error = -3.1%). We the created three strata of malaria risk that related to disease epidemiology. Following a search for malaria-specific incidence data on clinical attacks and direct causes of death due to Plasmodium falciparum we estimated the median estimates (and ranges) of disease outcome under the three transmission strata. Using the combined models of population, infection and disease outcome we have estimated that in 2005 there may have been approximately 1.73 million clinical attacks of P. falciparum malaria according to the modeled malaria endemicity and population projections during this period. At the end of the period 2008-2009 populations exposed to high transmission had decreased dramatically; consequently the modeled predictions of the number of clinical attacks in 2009 was 57% lower than 2005 with approximately 740,000 clinical cases and a 67% reduction in malaria-specific mortality to approximately 7,460 deaths. The majority of transmission intensity change between 2005 and 2009 occurred in South Central Somalia. Whether the small incremental increase in insecticide treated net coverage (2005: 7% -2009: 22%) and increased investment in disease management were responsible for this change or changes in rainfall were responsible remains uncertain. The models however provide an opportunity to explore these plausibility arguments in more detail. Interestingly we compared other possible models of morbidity estimation using incomplete health information systems and assuming a fixed rate of non-presentation to the formal health facilities in Somalia and predicted a morbidity burden of 630,000 cases in 2009. While lower than the epidemiological model approach both approaches are within a presumed margin of uncertainty and these comparative approaches deserve further attention
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International population movements and regional Plasmodium falciparum malaria elimination strategies
Proceedings of the National Academy of Sciences, 107: 24..
Author(s): Tatem, A.J. and Smith, D.L.
Type: application. Year: 2010
DOI: .

Abstract: Calls for the eradication of malaria require the development of global and regional strategies based on a strong and consistent evidence base. Evidence from the previous global malaria eradication program and more recent transborder control campaigns have shown the importance of accounting for human movement in introducing infections to areas targeted for elimination. Here, census-based migration data were analysed with network analysis tools, P. falciparum malaria transmission maps and global population databases to map globally communities of countries linked by relatively high levels of infection movements. The likely principal sources and destinations of imported cases in each region were also mapped. Results indicate that certain groups of countries, such as those in West Africa and central Asia are much more strongly connected by relatively high levels of population and infection movement than others. In contrast, countries such as Ethiopia and Myanmar display significantly greater isolation in terms of likely infection movements in and out. The mapping here of both communities of countries linked by likely higher levels of infection movement, and 'natural' migration boundaries that display reduced movement of people and infections between regions has practical utility. These can inform the design of malaria elimination strategies by identifying regional communities of countries afforded protection from re-colonisation by surrounding regions of reduced migration. For more isolated countries, a nationally-focussed control or elimination program is likely to stand a better chance of success than those receiving high levels of visitors and migrants from high transmission regions.
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Human population, urban settlement patterns and their impact on Plasmodium falciparum malaria endemicity
Malaria Journal, 2008. 7:218..
Author(s): Tatem, A.J., Guerra, C.A., Kabaria, C.W., Noor, A.M., Hay, S.I.
Type: application. Year: 2008
DOI: 10.1186/1475-2875-7-218.

Abstract: The efficient allocation of financial resources for malaria control and the optimal distribution of appropriate interventions require accurate information on the geographic distribution of malaria risk and of the human populations it affects. Low population densities in rural areas and high population densities in urban areas can influence malaria transmission substantially. Here, the Malaria Atlas Project (MAP) global database of Plasmodium falciparum parasite rate (PfPR) surveys, medical intelligence and contemporary population surfaces are utilized to explore these relationships and other issues involved in combining malaria risk maps with those of human population distribution in order to define populations at risk more accurately. METHODS: First, an existing population surface was examined to determine if it was sufficiently detailed to be used reliably as a mask to identify areas of very low and very high population density as malaria free regions. Second, the potential of international travel and health guidelines (ITHGs) for identifying malaria free cities was examined. Third, the differences in PfPR values between surveys conducted in author defined rural and urban areas were examined. Fourth, the ability of various global urban extent maps to reliably discriminate these author-based classifications of urban and rural in the PfPR database was investigated. Finally, the urban map that most accurately replicated the author-based classifications was analysed to examine the effects of urban classifications on PfPR values across the entire MAP database. RESULTS: Masks of zero population density excluded many non-zero PfPR surveys, indicating that the population surface was not detailed enough to define areas of zero transmission resulting from low population densities. In contrast, the ITHGs enabled the identification and mapping of 53 malaria free urban areas within endemic countries. Comparison of PfPR survey results showed significant differences between author-defined urban and rural designations in Africa, but not for the remainder of the malaria endemic world. The Global Rural Urban Mapping Project (GRUMP) urban extent mask proved most accurate for mapping these author-defined rural and urban locations, and further sub-divisions of urban extents into urban and peri-urban classes enabled the effects of high population densities on malaria transmission to be mapped and quantified. CONCLUSION: The availability of detailed, contemporary census and urban extent data for the construction of coherent and accurate global spatial population databases is often poor. These known sources of uncertainty in population surfaces and urban maps have the potential to be incorporated into future malaria burden estimates. Currently, insufficient spatial information exists globally to identify areas accurately where population density is low enough to impact upon transmission. Medical intelligence does however exist to reliably identify malaria free cities. Moreover, in Africa, urban areas that have a significant effect on malaria transmission can be mapped.
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High resolution settlement and population maps for low income nations: combining land cover and national census in East Africa.
PLoS One, 2007. 2: p. e1298..
Author(s): Tatem, A.J., Noor, A.M., von Hagen, C., Di Gregorio, A., and S.I. Hay
Type: method. Year: 2007
DOI: .

Abstract: Between 2005 and 2050, the human population is forecast to grow by 2.7 billion, with the vast majority of this growth occurring in low income countries. This growth is likely to have significant social, economic and environmental impacts, and make the achievement of international development goals more difficult. The measurement, monitoring and potential mitigation of these impacts require high resolution, contemporary data on human population distributions. In low income countries, however, where the changes will be concentrated, the least information on the distribution of population exists. In this paper we investigate whether satellite imagery in combination with land cover information and census data can be used to create inexpensive, high resolution and easily-updatable settlement and population distribution maps over large areas. METHODOLOGY/PRINCIPAL FINDINGS: We examine various approaches for the production of maps of the East African region (Kenya, Uganda, Burundi, Rwanda and Tanzania) and where fine resolution census data exists, test the accuracies of map production approaches and existing population distribution products. The results show that combining high resolution census, settlement and land cover information is important in producing accurate population distribution maps. CONCLUSIONS: We find that this semi-automated population distribution mapping at unprecedented spatial resolution produces more accurate results than existing products and can be undertaken for as little as $0.01 per km2. The resulting population maps are a product of the Malaria Atlas Project (MAP: and are freely available.
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