Census-derived migration data as a tool for informing malaria elimination policy

Malaria Journal

Research

Arnaud Le Menach¹  Darlene Bhavnani¹  Roberto C. Córdoba²  Linus Bengtsson³  Xin Lu³  Erik Wetter⁴  Keith H. Carter⁵  Alessandro Sorichetta⁶  Nick W. Ruktanonchai⁶  Elisabeth zu Erbach-Schoenberg⁶  Andrew J. Tatem⁷ 

[1] Clinton Health Access Initiative, Boston, MA, USA;Department of Health Surveillance, Costa Rica Ministry of Health, San Jose, Costa Rica;Flowminder Foundation, Stockholm, Sweden;Karolinska Institute, Stockholm, Sweden;Flowminder Foundation, Stockholm, Sweden;Stockholm School of Economics, Stockholm, Sweden;Pan American Health Organization/World Health Organization, Washington, DC, USA;WorldPop, Geography and Environment, University of Southampton, SO17 1BJ, Southampton, UK;Flowminder Foundation, Stockholm, Sweden;WorldPop, Geography and Environment, University of Southampton, SO17 1BJ, Southampton, UK;Flowminder Foundation, Stockholm, Sweden;Fogarty International Center, National Institutes of Health, Bethesda, MD, USA;

关键词: Malaria elimination;    Human mobility;    Census data;    Migration;    Mobile phone data;   

DOI  :  10.1186/s12936-016-1315-5

 received in 2016-01-13, accepted in 2016-04-27,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundNumerous countries around the world are approaching malaria elimination. Until global eradication is achieved, countries that successfully eliminate the disease will contend with parasite reintroduction through international movement of infected people. Human-mediated parasite mobility is also important within countries near elimination, as it drives parasite flows that affect disease transmission on a subnational scale.MethodsMovement patterns exhibited in census-based migration data are compared with patterns exhibited in a mobile phone data set from Haiti to quantify how well migration data predict short-term movement patterns. Because short-term movement data were unavailable for Mesoamerica, a logistic regression model fit to migration data from three countries in Mesoamerica is used to predict flows of infected people between subnational administrative units throughout the region.ResultsPopulation flows predicted using census-based migration data correlated strongly with mobile phone-derived movements when used as a measure of relative connectivity. Relative population flows are therefore predicted using census data across Mesoamerica, informing the areas that are likely exporters and importers of infected people. Relative population flows are used to identify community structure, useful for coordinating interventions and elimination efforts to minimize importation risk. Finally, the ability of census microdata inform future intervention planning is discussed in a country-specific setting using Costa Rica as an example.ConclusionsThese results show long-term migration data can effectively predict the relative flows of infected people to direct malaria elimination policy, a particularly relevant result because migration data are generally easier to obtain than short-term movement data such as mobile phone records. Further, predicted relative flows highlight policy-relevant population dynamics, such as major exporters across the region, and Nicaragua and Costa Rica’s strong connection by movement of infected people, suggesting close coordination of their elimination efforts. Country-specific applications are discussed as well, such as predicting areas at relatively high risk of importation, which could inform surveillance and treatment strategies.

【 授权许可】

CC BY   
© Ruktanonchai et al. 2016

【 图 表 】

Fig. 5

Fig. 4

12888_2023_5299_Article_IEq1.gif

Fig. 3

12944_2017_533_Article_IEq2.gif

Fig. 2

Fig. 2

Fig. 5

Fig. 2

Fig. 6

Fig. 1

12936_2016_1315_Article_IEq9.gif

12936_2016_1315_Article_IEq8.gif

Fig. 5

Fig. 1

Fig. 5

12951_2016_171_Article_IEq6.gif

Fig. 3