Addressing operational challenges of combatting malaria in a remote forest area of Vietnam using spatial decision support system approaches

  • Thang Duc Ngo Department of Epidemiology, National Institute of Malariology, Parasitology and Entomology (NIMPE), Hanoi, Viet Nam.
  • Sara E. Canavati Vysnova Partners Inc., Hanoi, Viet Nam.
  • Ha Son Dinh Department of Epidemiology, National Institute of Malariology, Parasitology and Entomology (NIMPE), Hanoi, Viet Nam.
  • Thinh Duc Ngo Department of Epidemiology, National Institute of Malariology, Parasitology and Entomology (NIMPE), Hanoi, Viet Nam.
  • Duong T. Tran Department of Epidemiology, National Institute of Malariology, Parasitology and Entomology (NIMPE), Hanoi, Viet Nam.
  • Nicholas J. Martin United States Naval Medical Research Unit Two, Phnom Penh, Cambodia.
  • Gerard C. Kelly | gerardckelly@gmail.com Vysnova Partners Inc., Hanoi, Vietnam; Center for Biomedical Research, Burnet Institute, Melbourne, Australia.

Abstract

This study examines the development of a spatial decision support system (SDSS) to address operational challenges for combatting malaria in a priority remote forest area of Vietnam including locating active malaria transmission, guiding targeted response, and identifying mobile and high-risk populations. A customized SDSS was developed for three communes in Phu Yen Province, Vietnam. Geographical reconnaissance (GR) was conducted to map and enumerate all households in the study site. During 2015 and 2016, detected malaria cases were reported to the SDSS and georeferenced to household residence. Individual case data were analysed in the SDSS to guide targeted response. Case investigation data, including suspected forest and remote area transmission locations, were also integrated into the SDSS. Surveys and in-depth interviews were conducted to assess utility and user acceptability. In 2015 and 2016, 4,667 households and a population of 17,563 were captured during GR. During the study period, 128 malaria cases were reported and automatically mapped in the SDSS. Targeted response interventions were conducted in 12 villages, testing 1,872 individuals. Intervention and remote-area sleeping site data were mapped and analysed using the SDSS. During follow-up interviews in 2017 the SDSS was found to be highly acceptable to malaria surveillance personnel. Results suggest that an SDSS can provide an effective tool in Vietnam to support the implementation of specialized surveillance, and calls for further research, application and roll-out in the Greater Mekong Subregion.

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Published
2019-11-06
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Original Articles
Keywords:
Malaria, Surveillance, Spatial decision support systems, Greater Mekong Subregion, Vietnam
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How to Cite
Ngo, T. D., Canavati, S. E., Dinh, H. S., Ngo, T. D., Tran, D. T., Martin, N. J., & Kelly, G. C. (2019). Addressing operational challenges of combatting malaria in a remote forest area of Vietnam using spatial decision support system approaches. Geospatial Health, 14(2). https://doi.org/10.4081/gh.2019.770