Optimal health and disease management using spatial uncertainty: a geographic characterization of emergent artemisinin-resistant Plasmodium falciparum distributions in Southeast Asia

International Journal of Health Geographics

Kyaw M. Tun¹  Tin M. Hlaing¹  Marina McDew-White²  Tim J. C. Anderson²  Shalini Nair²  Mallika Imwong³  Sasithon Pukrittayakamee⁴  Nhien T. Nguyen⁵  Shannon Takala-Harrison⁶  Rick M. Fairhurst⁷  Nicholas P. J. Day⁸  M. Abul Faiz⁸  Didier Menard⁹  Jean-Marie Kindermans^1,10  Richard J. Maude^1,11  Nicholas J. White^1,11  Elizabeth A. Ashley^1,11  Arjen M. Dondorp^1,11  Mayfong Mayxay^1,11  Tran T. Hien^1,11  Francois Nosten^1,11  Frank Smithuis^1,11  Charles J. Woodrow^1,11  Peter W. Gething^1,12  Eric P. M. Grist^1,13  Philippe J. Guerin^1,13  Georgina Humphreys^1,13  Ignacio Suay Mas^1,13  Carol Hopkins Sibley^1,13  Mehul Dhorda^1,13  Benoit Witkowski^1,13  Ric N. Price^1,13  Jennifer A. Flegg^1,13  Paul N. Newton^1,13 

[1] Defence Services Medical Research Centre;Department of Genetics, Texas Biomedical Research Institute;Department of Molecular Tropical Medicine and Genetics, Faculty of Tropical Medicine, Mahidol University;Faculty of Tropical Medicine, Mahidol University;Hospital for Tropical Disease, Oxford University Clinical Research Unit;Institute for Global Health, University of Maryland School of Medicine;Laboratory of Malaria and Vector Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health;Mahidol-Oxford Tropical Medicine Research Unit, Mahidol University;Malaria Molecular Epidemiology Unit, Institute Pasteur in Cambodia;Médecins Sans Frontières;Nuffield Department of Medicine, Centre for Tropical Medicine and Global Health, University of Oxford;Spatial Epidemiology and Ecology Group, Department of Zoology, University of Oxford;WorldWide Antimalarial Resistance Network (WWARN);

关键词: Surveillance;    Drug resistance;    Malaria;    Artemisinin;    Greater Mekong Subregion;   

DOI  :  10.1186/s12942-016-0064-6

来源: DOAJ

【 摘 要 】

Abstract Background Artemisinin-resistant Plasmodium falciparum malaria parasites are now present across much of mainland Southeast Asia, where ongoing surveys are measuring and mapping their spatial distribution. These efforts require substantial resources. Here we propose a generic ‘smart surveillance’ methodology to identify optimal candidate sites for future sampling and thus map the distribution of artemisinin resistance most efficiently. Methods The approach uses the ‘uncertainty’ map generated iteratively by a geostatistical model to determine optimal locations for subsequent sampling. Results The methodology is illustrated using recent data on the prevalence of the K13-propeller polymorphism (a genetic marker of artemisinin resistance) in the Greater Mekong Subregion. Conclusion This methodology, which has broader application to geostatistical mapping in general, could improve the quality and efficiency of drug resistance mapping and thereby guide practical operations to eliminate malaria in affected areas.

【 授权许可】

Unknown