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Title: Mapping imported malaria in Bangladesh using parasite genetic and human mobility data
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
Telenor ASA
Harvard T.H. Chan School of Public Health
Organisation Mondiale de la Santé
University of Oxford
Bangladesh Rural Advancement Committee
Mahidol University
Chittagong Medical College Hospital
Nuffield Department of Clinical Medicine
Chittagong Medical College
Johns Hopkins Bloomberg School of Public Health
Wellcome Sanger Institute
Asia Regional Centre
Dev Care Foundation
Shaheed Suhrawardy Medical College
Directorate General of Health Services
Keywords: Biochemistry, Genetics and Molecular Biology;Immunology and Microbiology
Issue Date: 1-Apr-2019
Citation: eLife. Vol.8, (2019)
Abstract: © Iordanov et al. 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: 2050084X
Appears in Collections:Scopus 2019

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