Dynamic denominators: the impact of seasonally varying population numbers on disease incidence estimates

Population Health Metrics

Research

Amy Wesolowski¹  Bonita Graupe²  Catherine Linard³  Christoper Lourenço⁴  Elisabeth zu Erbach-Schoenberg⁵  Carla Pezzulo⁵  Alessandro Sorichetta⁵  Tomas J. Bird⁵  Victor A. Alegana⁵  Nick W. Ruktanonchai⁵  Andrew J. Tatem⁶ 

[1] Flowminder Foundation, Roslagsgatan 17, 113 55, Stockholm, Sweden;Center for Communicable Disease Dynamics and Department of Epidemiology, Harvard, Boston, MA, USA;Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA;Mobile Telecommunications Limited, Windhoek, Namibia;Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Av. FD Roosevelt 50, 1050, Brussels, Belgium;Department of Geography, Université de Namur, Rue de Bruxelles 61, 5000, Namur, Belgium;WorldPop, Geography and Environment, University of Southampton, University Road, SO17 1BJ, Southampton, UK;Clinton Health Access Initiative, Boston, MA, USA;WorldPop, Geography and Environment, University of Southampton, University Road, SO17 1BJ, Southampton, UK;Flowminder Foundation, Roslagsgatan 17, 113 55, Stockholm, Sweden;WorldPop, Geography and Environment, University of Southampton, University Road, SO17 1BJ, Southampton, UK;Flowminder Foundation, Roslagsgatan 17, 113 55, Stockholm, Sweden;Fogarty International Center, National Institutes of Health, 20892, Bethesda, MD, USA;

关键词: Health metrics;    Mobile phones;    Malaria;    Surveillance;    Disease incidence;    Seasonality;   

DOI  :  10.1186/s12963-016-0106-0

 received in 2016-03-31, accepted in 2016-10-05,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundReliable health metrics are crucial for accurately assessing disease burden and planning interventions. Many health indicators are measured through passive surveillance systems and are reliant on accurate estimates of denominators to transform case counts into incidence measures. These denominator estimates generally come from national censuses and use large area growth rates to estimate annual changes. Typically, they do not account for any seasonal fluctuations and thus assume a static denominator population. Many recent studies have highlighted the dynamic nature of human populations through quantitative analyses of mobile phone call data records and a range of other sources, emphasizing seasonal changes. In this study, we use mobile phone data to capture patterns of short-term human population movement and to map dynamism in population densities.MethodsWe show how mobile phone data can be used to measure seasonal changes in health district population numbers, which are used as denominators for calculating district-level disease incidence. Using the example of malaria case reporting in Namibia we use 3.5 years of phone data to investigate the spatial and temporal effects of fluctuations in denominators caused by seasonal mobility on malaria incidence estimates.ResultsWe show that even in a sparsely populated country with large distances between population centers, such as Namibia, populations are highly dynamic throughout the year. We highlight how seasonal mobility affects malaria incidence estimates, leading to differences of up to 30 % compared to estimates created using static population maps. These differences exhibit clear spatial patterns, with likely overestimation of incidence in the high-prevalence zones in the north of Namibia and underestimation in lower-risk areas when compared to using static populations.ConclusionThe results here highlight how health metrics that rely on static estimates of denominators from censuses may differ substantially once mobility and seasonal variations are taken into account. With respect to the setting of malaria in Namibia, the results indicate that Namibia may actually be closer to malaria elimination than previously thought. More broadly, the results highlight how dynamic populations are. In addition to affecting incidence estimates, these changes in population density will also have an impact on allocation of medical resources. Awareness of seasonal movements has the potential to improve the impact of interventions, such as vaccination campaigns or distributions of commodities like bed nets.

【 授权许可】

CC BY   
© The Author(s). 2016