Mapping imported malaria in Bangladesh using parasite genetic and human mobility data

For countries aiming for malaria elimination, travel of infected individuals between endemic areas undermines local interventions. Quantifying parasite importation has therefore become a priority for national control programs. We analyzed epidemiological surveillance data, travel surveys, parasite g...

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Bibliographic Details
Main Authors: Hsiao-Han Chang, Amy Wesolowski, Ipsita Sinha, Christopher G Jacob, Ayesha Mahmud, Didar Uddin, Sazid Ibna Zaman, Md Amir Hossain, M Abul Faiz, Aniruddha Ghose, Abdullah Abu Sayeed, M Ridwanur Rahman, Akramul Islam, Mohammad Jahirul Karim, M Kamar Rezwan, Abul Khair Mohammad Shamsuzzaman, Sanya Tahmina Jhora, M M Aktaruzzaman, Eleanor Drury, Sonia Gonçalves, Mihir Kekre, Mehul Dhorda, Ranitha Vongpromek, Olivo Miotto, Kenth Engø-Monsen, Dominic Kwiatkowski, Richard J Maude, Caroline Buckee
Format: Article
Language:English
Published: eLife Sciences Publications Ltd 2019-04-01
Series:eLife
Subjects:
Online Access:https://elifesciences.org/articles/43481
Description
Summary:For countries aiming for malaria elimination, travel of infected individuals between endemic areas undermines local interventions. Quantifying parasite importation has therefore become a priority for national control programs. We analyzed epidemiological surveillance data, travel surveys, parasite genetic data, and anonymized mobile phone data to measure the spatial spread of malaria parasites in southeast Bangladesh. We developed a genetic mixing index to estimate the likelihood of samples being local or imported from parasite genetic data and inferred the direction and intensity of parasite flow between locations using an epidemiological model integrating the travel survey and mobile phone calling data. Our approach indicates that, contrary to dogma, frequent mixing occurs in low transmission regions in the southwest, and elimination will require interventions in addition to reducing imported infections from forested regions. Unlike risk maps generated from clinical case counts alone, therefore, our approach distinguishes areas of frequent importation as well as high transmission.
ISSN:2050-084X