Publications

Total: 139
The effects of urbanization on global Plasmodium vivax malaria transmission
Malaria Journal, 11, 403..
Author(s): Qi, Qiuyin, Guerra, Carlos A., Moyes, Catherine L., Elyazar, Iqbal R. F., Gething, Peter W., Hay, Simon I. and Tatem, Andrew J.
Type: application. Year: 2012
DOI: .

Abstract: Many recent studies have examined the impact of urbanization on Plasmodium falciparum malaria endemicity and found a general trend of reduced transmission in urban areas. However, none has examined the effect of urbanization on Plasmodium vivax malaria, which is the most widely distributed malaria species and can also cause severe clinical syndromes in humans. In this study, a set of 10,003 community-based P. vivax parasite rate (PvPR) surveys are used to explore the relationships between PvPR in urban and rural settings. Methods: The PvPR surveys were overlaid onto a map of global urban extents to derive an urban/rural assignment. The differences in PvPR values between urban and rural areas were then examined. Groups of PvPR surveys inside individual city extents (urban) and surrounding areas (rural) were identified to examine the local variations in PvPR values. Finally, the relationships of PvPR between urban and rural areas within the ranges of 41 dominant Anopheles vectors were examined. Results: Significantly higher PvPR values in rural areas were found globally. The relationship was consistent at continental scales when focusing on Africa and Asia only, but in the Americas, significantly lower values of PvPR in rural areas were found, though the numbers of surveys were small. Moreover, except for the countries in the Americas, the same trends were found at national scales in African and Asian countries, with significantly lower values of PvPR in urban areas. However, the patterns at city scales among 20 specific cities where sufficient data were available were less clear, with seven cities having significantly lower PvPR values in urban areas and two cities showing significantly lower PvPR in rural areas. The urban–rural PvPR differences within the ranges of the dominant Anopheles vectors were generally, in agreement with the regional patterns found. Conclusions: Except for the Americas, the patterns of significantly lower P. vivax transmission in urban areas have been found globally, regionally, nationally and by dominant vector species here, following trends observed previously for P. falciparum. To further understand these patterns, more epidemiological, entomological and parasitological analyses of the disease at smaller spatial scales are needed.
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The effects of spatial population dataset choice on population at risk of disease estimates
Population Health Metrics, 9: 4..
Author(s): Tatem, A.J., Campiz, N., Gething, P.W., Snow, R.W. and Linard, C
Type: method. Year: 2011
DOI: .

Abstract: The spatial modeling of infectious disease distributions and dynamics is increasingly being undertaken for health services planning and disease control monitoring, implementation, and evaluation. Where risks are heterogeneous in space or dependent on person-to-person transmission, spatial data on human population distributions are required to estimate infectious disease risks, burdens, and dynamics. Several different modeled human population distribution datasets are available and widely used, but the disparities among them and the implications for enumerating disease burdens and populations at risk have not been considered systematically. Here, we quantify some of these effects using global estimates of populations at risk (PAR) of P. falciparum malaria as an example. Methods: The recent construction of a global map of P. falciparum malaria endemicity enabled the testing of different gridded population datasets for providing estimates of PAR by endemicity class. The estimated population numbers within each class were calculated for each country using four different global gridded human population datasets: GRUMP (~1km spatial resolution), LandScan (~1km), UNEP Global Population Databases (~5km), and GPW3 (~5km). More detailed assessments of PAR variation and accuracy were conducted for three African countries where census data were available at a higher administrative-unit level than used by any of the four gridded population datasets. Results: The estimates of PAR based on the datasets varied by more than 10 million people for some countries, even accounting for the fact that estimates of population totals made by different agencies are used to correct national totals in these datasets and can vary by more than 5% for many low-income countries. In many cases, these variations in PAR estimates comprised more than 10% of the total national population. The detailed country-level assessments suggested that none of the datasets was consistently more accurate than the others in estimating PAR. The sizes of such differences among modeled human populations were related to variations in the methods, input resolution, and date of the census data underlying each dataset. Data quality varied from country to country within the spatial population datasets. Conclusions: Detailed, highly spatially resolved human population data are an essential resource for planning health service delivery for disease control, for the spatial modeling of epidemics, and for decision-making processes related to public health. However, our results highlight that for the low-income regions of the world where disease burden is greatest, existing datasets display substantial variations in estimated population distributions, resulting in uncertainty in disease assessments that utilize them. Increased efforts are required to gather contemporary and spatially detailed demographic data to reduce this uncertainty, particularly in Africa, and to develop population distribution modeling methods that match the rigor, sophistication, and ability to handle uncertainty of contemporary disease mapping and spread modeling. In the meantime, studies that utilize a particular spatial population dataset need to acknowledge the uncertainties inherent within them and consider how the methods and data that comprise each will affect conclusions
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Population mapping of poor countries
Nature, 474, 36..
Author(s): Tatem, A.J. and Linard, C
Type: method. Year: 2011
DOI: .

Abstract: Global population maps can be valuable for quantifying populations at risk, such as those near nuclear power plants (Nature 472, 400-401; 2011). But the uncertainties inherent in such data sets must be acknowledged. The census data used in map construction for rich countries are recent and detailed. The same is often not true for poorer countries. For example, Angola's last census was in 1970, broken down into just 18 districts. Estimates of its current total resident population vary from 13.3 million to 19 million, according to the US Census Bureau and the United Nations, respectively. When such outdated and coarse-resolution data are subject to different modelling assumptions by different groups, it can lead to substantially divergent estimates of population distributions and, consequently, populations at risk. Uncertainties in and between global population maps should be more widely discussed, and a greater effort made to quantify them. Furthermore, spatially referenced demographic data used in map construction are often scattered across national statistical offices and websites. A centralized, open-access, up-to-date database would benefit many fields that rely on population maps, and would require minimal investment
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Population distribution, settlement patterns and accessibility across Africa in 2010
PLoS ONE, 7(2): e31743..
Author(s): Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J
Type: method. Year: 2011
DOI: .

Abstract: The spatial distribution of populations and settlements across a country and their interconnectivity and accessibility from urban areas are important for delivering healthcare, distributing resources and economic development. However, existing spatially explicit population data across Africa are generally based on outdated, low resolution input demographic data, and provide insufficient detail to quantify rural settlement patterns and, thus, accurately measure population concentration and accessibility. Here we outline approaches to developing a new high resolution population distribution dataset for Africa and analyse rural accessibility to population centers. Contemporary population count data were combined with detailed satellite-derived settlement extents to map population distributions across Africa at a finer spatial resolution than ever before. Substantial heterogeneity in settlement patterns, population concentration and spatial accessibility to major population centres is exhibited across the continent. In Africa, 90% of the population is concentrated in less than 21% of the land surface and the average per-person travel time to settlements of more than 50,000 inhabitants is around 3.5 hours, with Central and East Africa displaying the longest average travel times. The analyses highlight large inequities in access, the isolation of many rural populations and the challenges that exist between countries and regions in providing access to services. The datasets presented are freely available as part of the AfriPop project, providing an evidence base for guiding strategic decisions.
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