Weekly Malaria Monitoring Helps Mali Track Potential Outbreaks on a Web-based Database
Mali suffered a coup and war in 2012 and 2013 that triggered large displacements from the north toward the south of people who are not immune to malaria. This migration could heighten the risk of malaria epidemics in regions such as Mopti, which sits along the Niger River in the center of the country. The USAID mission in Mali requested MEASURE Evaluation to support the National Malaria Control Program (NMCP) to expand its malaria data reporting system to some of the health facilities in the region and to ensure timely and accurate malaria case reporting as a way to identify and head off any outbreak.
MEASURE Evaluation responded by setting up a Malaria Epidemic Surveillance System (MESS) for early detection of malaria outbreaks. To identify anomalies, MEASURE Evaluation and the NMCP first conducted a baseline assessment in three community health centers (Centre de Santé Communautaire, or CSCom) in the Mopti region: Asacotamb, Sévaré II (district of Mopti) and Bandiagara Central (district of Bandiagara). We extracted data on malaria morbidity, including simple and severe cases, for the past five years from the health management information system (HMIS) form (Rapport Trimestriel d’Activités, RTA). These data calculated epidemic thresholds for each facility, using methods recommended by the World Health Organization (WHO).
- Output of the system: Monthly/weekly malaria surveillance data, Sevare II, Sept 2014 – July 2015
MEASURE Evaluation then contracted with Yeleman, a data company in West Africa, to set up a web-based database for malaria surveillance, with an embedded data analysis program. The next step was to train health workers from the target CSCom, as well as workers of the private health facilities in their catchment area, to collect and send weekly data to the database.
The incorporated analysis program shows weekly and monthly data on malaria cases, which are compared through linear graphs to the anticipated thresholds set by the baseline. Health workers, health district and regional managers, and central level coordinators now have the tool to detect possible malaria outbreaks through real-time data visualization and monitoring.
The success of this system and its added value to malaria surveillance has led to MEASURE Evaluation and the NMCP expanding the system to the entire region of Mopti. The value of this system, especially in areas with high risk for malaria outbreak, has led WHO Mali to consider building upon this experience to set up a similar system for malaria and other epidemic-prone diseases in the northern regions of Gao, Tombouctou, and Kidal.
