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...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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eLife Sciences Publications Ltd
2019-04-01
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| Series: | eLife |
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| Online Access: | https://elifesciences.org/articles/43481 |
| _version_ | 1811181032792129536 |
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| author | 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 |
| author_facet | 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 |
| author_sort | Hsiao-Han Chang |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T09:12:33Z |
| format | Article |
| id | doaj.art-574796120a8d46b392cc18d0184a9d94 |
| institution | Directory Open Access Journal |
| issn | 2050-084X |
| language | English |
| last_indexed | 2024-04-11T09:12:33Z |
| publishDate | 2019-04-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj.art-574796120a8d46b392cc18d0184a9d942022-12-22T04:32:27ZengeLife Sciences Publications LtdeLife2050-084X2019-04-01810.7554/eLife.43481Mapping imported malaria in Bangladesh using parasite genetic and human mobility dataHsiao-Han Chang0https://orcid.org/0000-0001-8016-1530Amy Wesolowski1https://orcid.org/0000-0001-6320-3575Ipsita Sinha2https://orcid.org/0000-0002-6574-310XChristopher G Jacob3Ayesha Mahmud4Didar Uddin5Sazid Ibna Zaman6Md Amir Hossain7M Abul Faiz8Aniruddha Ghose9Abdullah Abu Sayeed10M Ridwanur Rahman11Akramul Islam12Mohammad Jahirul Karim13M Kamar Rezwan14Abul Khair Mohammad Shamsuzzaman15Sanya Tahmina Jhora16M M Aktaruzzaman17Eleanor Drury18Sonia Gonçalves19Mihir Kekre20Mehul Dhorda21Ranitha Vongpromek22Olivo Miotto23Kenth Engø-Monsen24https://orcid.org/0000-0003-1618-7597Dominic Kwiatkowski25Richard J Maude26Caroline Buckee27https://orcid.org/0000-0002-8386-5899Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, United States; The Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, United StatesDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, United StatesMahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United KingdomWellcome Sanger Institute, Cambridge, United KingdomDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, United States; The Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, United StatesMahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, ThailandMahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, ThailandDepartment of Medicine, Chittagong Medical College, Chittagong, BangladeshMahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand; Dev Care Foundation, Dhaka, BangladeshChittagong Medical College Hospital, Chittagong, BangladeshChittagong Medical College Hospital, Chittagong, BangladeshShaheed Suhrawardy Medical College, Dhaka, BangladeshBRAC Centre, Dhaka, BangladeshNational Malaria Elimination Programme, Dhaka, BangladeshVector-Borne Disease Control, World Health Organization, Dhaka, BangladeshCommunicable Disease Control, Directorate General of Health Services, Dhaka, BangladeshCommunicable Disease Control, Directorate General of Health Services, Dhaka, BangladeshNational Malaria Elimination Programme, Dhaka, BangladeshWellcome Sanger Institute, Cambridge, United KingdomWellcome Sanger Institute, Cambridge, United KingdomWellcome Sanger Institute, Cambridge, United KingdomMahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom; Worldwide Antimalarial Resistance Network, Asia Regional Centre, Bangkok, ThailandWorldwide Antimalarial Resistance Network, Asia Regional Centre, Bangkok, ThailandMahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand; Wellcome Sanger Institute, Cambridge, United Kingdom; Big Data Institute, Oxford University, Oxford, United KingdomTelenor Research, Telenor Group, Fornebu, NorwayWellcome Sanger Institute, Cambridge, United Kingdom; Big Data Institute, Oxford University, Oxford, United KingdomDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, United States; The Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, United States; Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United KingdomDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, United States; The Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, United StatesFor 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.https://elifesciences.org/articles/43481travel surveyparasite flowgenetic barcodesmobilityimportation |
| spellingShingle | 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 Mapping imported malaria in Bangladesh using parasite genetic and human mobility data eLife travel survey parasite flow genetic barcodes mobility importation |
| title | Mapping imported malaria in Bangladesh using parasite genetic and human mobility data |
| title_full | Mapping imported malaria in Bangladesh using parasite genetic and human mobility data |
| title_fullStr | Mapping imported malaria in Bangladesh using parasite genetic and human mobility data |
| title_full_unstemmed | Mapping imported malaria in Bangladesh using parasite genetic and human mobility data |
| title_short | Mapping imported malaria in Bangladesh using parasite genetic and human mobility data |
| title_sort | mapping imported malaria in bangladesh using parasite genetic and human mobility data |
| topic | travel survey parasite flow genetic barcodes mobility importation |
| url | https://elifesciences.org/articles/43481 |
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