TY - JOUR
T1 - Mapping imported malaria in Bangladesh using parasite genetic and human mobility data
AU - Chang, Hsiao Han
AU - Wesolowski, Amy
AU - Sinha, Ipsita
AU - Jacob, Christopher G.
AU - Mahmud, Ayesha
AU - Uddin, Didar
AU - Zaman, Sazid Ibna
AU - Hossain, Md Amir
AU - Faiz, M. Abul
AU - Ghose, Aniruddha
AU - Sayeed, Abdullah Abu
AU - Rahman, M. Ridwanur
AU - Islam, Akramul
AU - Karim, Mohammad Jahirul
AU - Rezwan, M. Kamar
AU - Shamsuzzaman, Abul Khair Mohammad
AU - Jhora, Sanya Tahmina
AU - Aktaruzzaman, M. M.
AU - Drury, Eleanor
AU - Gonçalves, Sonia
AU - Kekre, Mihir
AU - Dhorda, Mehul
AU - Vongpromek, Ranitha
AU - Miotto, Olivo
AU - Engø-Monsen, Kenth
AU - Kwiatkowski, Dominic
AU - Maude, Richard J.
AU - Buckee, Caroline
N1 - Funding Information:
We thank Joseph Lewnard for helpful discussion on statistical analysis, and the staff of Wellcome Sanger Institute Sample Management, Genotyping, Sequencing and Informatics teams for their contribution. National Institute of General Medical Sciences U54GM088558 Burroughs Wellcome Fund Amy Wesolowski Bill and Melinda Gates Foundation CPT000390 Bill and Melinda Gates Foundation OPP1129596 Medical Research Council G0600718 Bill and Melinda Gates Foundation OPP1118166 Christopher National Institute of General Medical Sciences R35GM124715-02
Publisher Copyright:
© Iordanov et al.
PY - 2019/4
Y1 - 2019/4
N2 - 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.
AB - 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.
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U2 - 10.7554/eLife.43481
DO - 10.7554/eLife.43481
M3 - Article
C2 - 30938289
AN - SCOPUS:85065111606
SN - 2050-084X
VL - 8
JO - eLife
JF - eLife
M1 - e43481
ER -