Census-derived migration data as a tool for informing malaria elimination policy
Census-derived migration data as a tool for informing malaria elimination policy
Background: Numerous 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.
Methods: Movement 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.
Results: Population 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.
Conclusions: These 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.
Ruktanonchai, Nick W.
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Bhavnani, Darlene
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Sorichetta, Alessandro
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Bengtsson, Linus
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Carter, Keith H.
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Córdoba, Roberto C.
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Le Menach, Arnaud
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Lu, Xin
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Wetter, Erik
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Zu Erbach-Schoenberg, Elisabeth
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Tatem, Andrew J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e
11 May 2016
Ruktanonchai, Nick W.
fe68cb8d-3760-4955-99fa-47d43f86580a
Bhavnani, Darlene
72545b8a-b1b9-4c9f-ada8-d8587b678f39
Sorichetta, Alessandro
c80d941b-a3f5-4a6d-9a19-e3eeba84443c
Bengtsson, Linus
f7585eb4-9e78-422d-8178-4310985aa24e
Carter, Keith H.
ae06a10f-fc11-4f0d-8ed4-bcb3b44254cf
Córdoba, Roberto C.
c8ccd69c-a456-48fe-918f-101ce2442a32
Le Menach, Arnaud
31494ace-95c8-488f-bf84-42747d9d72a7
Lu, Xin
a681bac0-d6d1-4e8e-a642-4ce42ae2cc9d
Wetter, Erik
dd9554f1-7107-4d5b-b19f-7198af551091
Zu Erbach-Schoenberg, Elisabeth
9a1f59b2-c661-42c9-ad94-96772c292add
Tatem, Andrew J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Ruktanonchai, Nick W., Bhavnani, Darlene, Sorichetta, Alessandro, Bengtsson, Linus, Carter, Keith H., Córdoba, Roberto C., Le Menach, Arnaud, Lu, Xin, Wetter, Erik, Zu Erbach-Schoenberg, Elisabeth and Tatem, Andrew J.
(2016)
Census-derived migration data as a tool for informing malaria elimination policy.
Malaria Journal, 15, [273].
(doi:10.1186/s12936-016-1315-5).
Abstract
Background: Numerous 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.
Methods: Movement 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.
Results: Population 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.
Conclusions: These 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.
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Accepted/In Press date: 27 April 2016
e-pub ahead of print date: 11 May 2016
Published date: 11 May 2016
Organisations:
Global Env Change & Earth Observation, WorldPop, Population, Health & Wellbeing (PHeW)
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Local EPrints ID: 394265
URI: http://eprints.soton.ac.uk/id/eprint/394265
ISSN: 1475-2875
PURE UUID: b9f50f07-42bd-4df1-af2f-459cb7721812
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Date deposited: 13 May 2016 09:01
Last modified: 15 Mar 2024 03:43
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Contributors
Author:
Nick W. Ruktanonchai
Author:
Darlene Bhavnani
Author:
Linus Bengtsson
Author:
Keith H. Carter
Author:
Roberto C. Córdoba
Author:
Arnaud Le Menach
Author:
Xin Lu
Author:
Erik Wetter
Author:
Elisabeth Zu Erbach-Schoenberg
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