Total: 126
Geographic coverage of demographic surveillance systems for characterising the drivers of childhood mortality in sub-Saharan Africa
BMJ Global Health - 2018.
Author(s): Utazi C Edson, Sahu Sujit K, Atkinson Peter M, Tejedor-Garavito Natalia, Lloyd Christopher T, Tatem, Andrew J.
Type: application. Year: 2018
DOI: 10.1136/bmjgh-2017-000611.

Abstract: A major focus of international health and development goals is the reduction of mortality rates in children under 5 years of age. Achieving this requires understanding the drivers of mortality and how they vary geographically to facilitate the targeting and prioritisation of appropriate interventions. Much of our knowledge on the causes of, and trends in, childhood mortality come from longitudinal demographic surveillance sites, with a renewed focus recently on the establishment and growth of networks of sites from which standardised outputs can facilitate broader understanding of processes. To ensure that the collective outputs from surveillance sites can be used to derive a comprehensive understanding and monitoring system for driving policy on tackling childhood mortality, confidence is needed that existing and planned networks of sites are providing a reliable and representative picture of the geographical variation in factors associated with mortality. Here, we assembled subnational data on childhood mortality as well as key factors known to be associated with it from household surveys in 27 sub-Saharan African countries. We then mapped the locations of existing longitudinal demographic surveillance sites to assess the extent of current coverage of the range of factors, identifying where gaps exist. The results highlight regions with unique combinations of factors associated with childhood mortality that are poorly represented by the current distribution of sites, such as southern Mali, central Nigeria and southern Zambia. Finally, we determined where the establishment of new surveillance systems could improve coverage.
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Spatiotemporal incidence of Zika and associated environmental drivers for the 2015-2016 epidemic in Colombia.
Scientific Data volume 5, Article number: 180073 (2018).
Author(s): Amir S. Siraj, Isabel Rodriguez-Barraquer, Christopher M. Barker, Natalia Tejedor-Garavito, Dennis Harding, Christopher Lorton, Dejan Lukacevic, Gene Oates, Guido Espana, Moritz U.G. Kraemer, Carrie Manore, Michael A. Johansson, Andrew J. Tatem, Robert C. Reiner & T. Alex Perkins
Type: application. Year: 2018
DOI: 10.1038/sdata.2018.73.

Abstract: Despite a long history of mosquito-borne virus epidemics in the Americas, the impact of the Zika virus (ZIKV) epidemic of 2015–2016 was unexpected. The need for scientifically informed decision-making is driving research to understand the emergence and spread of ZIKV. To support that research, we assembled a data set of key covariates for modeling ZIKV transmission dynamics in Colombia, where ZIKV transmission was widespread and the government made incidence data publically available. On a weekly basis between January 1, 2014 and October 1, 2016 at three administrative levels, we collated spatiotemporal Zika incidence data, nine environmental variables, and demographic data into a single downloadable database. These new datasets and those we identified, processed, and assembled at comparable spatial and temporal resolutions will save future researchers considerable time and effort in performing these data processing steps, enabling them to focus instead on extracting epidemiological insights from this important data set. Similar approaches could prove useful for filling data gaps to enable epidemiological analyses of future disease emergence events.
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Geospatial mapping of access to timely essential surgery in sub-Saharan Africa
BMJ Global Health 2018.
Author(s): Juran, Sabrina. Broer, P. Niclas. Klug, Stefanie J. Snow, Rachel C. Okiro, Emelda A. Ouma, Paul O. Snow, Robert W. Tatem, Andrew J. Meara, John G. Alegana, Victor A
Type: application. Year: 2018
DOI: 10.1136/bmjgh-2018-000875.

Abstract: Despite an estimated one-third of the global burden of disease being surgical, only limited estimates of accessibility to surgical treatment in sub-Saharan Africa exist and these remain spatially undefined. Geographical metrics of access to major hospitals were estimated based on travel time. Estimates were then used to assess need for surgery at country level.Methods Major district and regional hospitals were assumed to have capability to perform bellwether procedures. Geographical locations of hospitals in relation to the population in the 47 sub-Saharan countries were combined with spatial ancillary data on roads, elevation, land use or land cover to estimate travel-time metrics of 30 min, 1 hour and 2 hours. Hospital catchment was defined as population residing in areas less than 2 hours of travel time to the next major hospital. Travel-time metrics were combined with fine-scale population maps to define burden of surgery at hospital catchment level.Results Overall, the majority of the population (92.5%) in sub-Saharan Africa reside in areas within 2 hours of a major hospital catchment defined based on spatially defined travel times. The burden of surgery in all-age population was 257.8 million to 294.7 million people and was highest in high-population density countries and lowest in sparsely populated or smaller countries. The estimated burden in children <15 years was 115.3 million to 131.8 million and had similar spatial distribution to the all-age pattern.Conclusion The study provides an assessment of accessibility and burden of surgical disease in sub-Saharan Africa. Yet given the optimistic assumption of adequare surgical capability of major hospitals, the true burden of surgical disease is expected to be much greater. In-depth health facility assessments are needed to define infrastructure, personnel and medicine supply for delivering timely and safe affordable surgery to further inform the analysis.
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Modelling changing population distributions: an example of the Kenyan Coast, 1979–2009
Published online: 11 Jan 2017..
Author(s): Catherine Linard, Caroline W. Kabaria, Marius Gilbert, Andrew J. Tatem, Andrea E. Gaughan, Forrest R. Stevens, Alessandro Sorichetta, Abdisalan M. Noor & Robert W.
Type: method. Year: 2017
DOI: 10.1080/17538947.2016.1275829.

Abstract: Large-scale gridded population datasets are usually produced for the year of input census data using a top-down approach and projected backward and forward in time using national growth rates. Such temporal projections do not include any subnational variation in population distribution trends and ignore changes in geographical covariates such as urban land cover changes. Improved predictions of population distribution changes over time require the use of a limited number of covariates that are time-invariant or temporally explicit. Here we make use of recently released multi-temporal high-resolution global settlement layers, historical census data and latest developments in population distribution modelling methods to reconstruct population distribution changes over 30 years across the Kenyan Coast. We explore the methodological challenges associated with the production of gridded population distribution time-series in data-scarce countries and show that trade-offs have to be found between spatial and temporal resolutions when selecting the best modelling approach. Strategies used to fill data gaps may vary according to the local context and the objective of the study. This work will hopefully serve as a benchmark for future developments of population distribution time-series that are increasingly required for population-at-risk estimations and spatial modelling in various fields.
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