Viet Nam is among the Asia-Pacific countries focusing on eliminating malaria. Mapping helps target malaria interventions. Nguyen Xuan Thang and colleagues (James O’Donnell, Vashti Irani, Leanna Surrao, Ricardo Ataide, Josh Tram, An Le, Sara Canavati, Tran Thanh Duong, Tran Quoc Tuy, Gary Dahl, Gerard Kelly, Jack Richards, Ngo Duc Thang) presented their pilot mapping efforts at the Malaria World Congress in Melbourne recently and below share their experiences with us.
Viet Nam is focused on eliminating malaria by 2030. Viet Nam saw a 73% reduction in cases between 2013 and 2017 (NIMPE data), yet border provinces still have a high burden of malaria. However, some provinces still have a high burden of malaria. To achieve malaria elimination, it is essential to deploy targeted interventions in these locations.
Spatial Decision Support Systems (SDSS) can be used by National Malaria programs to integrate geographic elements in the management of malaria cases and facilitate targeted malaria interventions in these high-risk settings.
The objective of this work was to pilot a SDSS system for Binh Phuoc and Dak Nong Provinces in Viet Nam to facilitate ongoing surveillance and targeted malaria, as part of the Regional Artemisinin-resistance Initiative (RAI). This objective was achieved by:
Collecting baseline GIS data at household level and environmental characteristics associated with the area;
- Establishing a routine data collection system that will be reported by mobile medical staff by mobile phone;
- Integrating this data to form a spatial decision support system (SDSS);
- Using the SDSS system for direct reporting to malaria control programs that provided strategic solutions for the prevention of disease spread and the elimination of malaria
In Phase 1, a household and mapping survey was conducted in collaboration with commune, district and village health workers. Epicollect5 software was used on smartphones with GPS functionality to record mapping information (latitude and longitude) and general information on household members. During Phase 1, 10,506 households were surveyed and data was aggregated in a custom Geographic Information System (GIS) database.
The majority of the surveyed individuals were of the Kinh ethnicity (19,282; 35.4%), followed by M’Nong (4,669; 8.6%) and Mong (3,359; 6.2%). Data related to malaria among mobile populations were included in the GIS as a means to identify and describe groups at high risk for malaria e.g. forest-goers. The survey data were reviewed, cleaned and matched using the ID numbers, then aggregated with relevant administrative boundary data and linked on ArcGIS 10.2 software. This database is located in a custom GIS system and can be visualized as a spatial transmission model to support appropriate decision-making
Phase 2 focused on ongoing surveillance with rapid case reporting and responses. Malaria cases diagnosed at public and local health facilities were entered into the system by Commune Health Officials. Village Health Workers were immediately notified and went to the patient’s home to undertake case investigation including further household mapping and active case detection activities. The Viet Nam National Institute of Malariology was also notified, and organized local officials to carry out an investigation into the sources of transmission (i.e. ‘hotspots’) and to implement timely interventions.
When the cases were identified, Village Health Workers went to the patient’s home to undertake operational procedures including geographic exploration, household mapping to identify the location and to identify the list of affected households. They also collected this data on EpiCollect5. Collated information on cases, transmission point, zoning of the target villages allowed for early detection of malaria outbreaks. The National Institute of Malariology can also issue guidelines when the hotspots are identified and when disease outbreaks occur
These activities are ongoing. In conclusion, a custom GIS database was developed using a household survey in Binh Phuoc and Dak Nong province of Viet Nam. Malaria cases were mapped to identify hotspots of malaria transmission and enable further active case detection and targeted interventions. This established GIS database aims to support routine case notification and to enhance the role of surveillance for active case detection and responses to achieve malaria elimination.
The authors are affiliated with the National Institute of Malariology, Parasitology, Entomology (NIMPE), Viet Nam; Burnet Institute, Australia; and Health Poverty Action, UK. Contact: firstname.lastname@example.org