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

Author:

Chang Hsiao-Han12ORCID,Wesolowski Amy3ORCID,Sinha Ipsita45ORCID,Jacob Christopher G6,Mahmud Ayesha12,Uddin Didar4,Zaman Sazid Ibna4,Hossain Md Amir7,Faiz M Abul48,Ghose Aniruddha9,Sayeed Abdullah Abu9,Rahman M Ridwanur10,Islam Akramul11,Karim Mohammad Jahirul12,Rezwan M Kamar13,Shamsuzzaman Abul Khair Mohammad14,Jhora Sanya Tahmina14,Aktaruzzaman M M12,Drury Eleanor6,Gonçalves Sonia6,Kekre Mihir6,Dhorda Mehul4515,Vongpromek Ranitha15,Miotto Olivo4616,Engø-Monsen Kenth17ORCID,Kwiatkowski Dominic616,Maude Richard J1245,Buckee Caroline12ORCID

Affiliation:

1. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, United States

2. The Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, United States

3. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, United States

4. Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand

5. Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom

6. Wellcome Sanger Institute, Cambridge, United Kingdom

7. Department of Medicine, Chittagong Medical College, Chittagong, Bangladesh

8. Dev Care Foundation, Dhaka, Bangladesh

9. Chittagong Medical College Hospital, Chittagong, Bangladesh

10. Shaheed Suhrawardy Medical College, Dhaka, Bangladesh

11. BRAC Centre, Dhaka, Bangladesh

12. National Malaria Elimination Programme, Dhaka, Bangladesh

13. Vector-Borne Disease Control, World Health Organization, Dhaka, Bangladesh

14. Communicable Disease Control, Directorate General of Health Services, Dhaka, Bangladesh

15. Worldwide Antimalarial Resistance Network, Asia Regional Centre, Bangkok, Thailand

16. Big Data Institute, Oxford University, Oxford, United Kingdom

17. Telenor Research, Telenor Group, Fornebu, Norway

Abstract

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.

Funder

National Institute of General Medical Sciences

Burroughs Wellcome Fund

Bill and Melinda Gates Foundation

Medical Research Council

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

Reference50 articles.

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