Using Mobile Technology to Facilitate Reactive Case Detection of Malaria

How to Cite

Cressman, G., McKay, M., Al-Mafazy, A.- wahid, Ramsan, M. M., Ali, A. S., Garimo, I. A., Mkali, H., & Ngondi, J. J. (2017). Using Mobile Technology to Facilitate Reactive Case Detection of Malaria. Online Journal of Public Health Informatics, 9(1).


ObjectiveThis presentation will share findings from more than three years ofusing mobile technology for reactive case detection (RACD) to helpeliminate malaria in a well-defined geographic area. It will reviewthe concepts of RACD, the application of mobile technology, lessonslearned from more than three years of application, and considerationsin applying this technology in other malaria elimination contexts.IntroductionZanzibar is comprised primarily of two large islands with apopulation of 1.3 million. Indoor Residual Spraying (IRS) campaigns,distribution of long-lasting insecticide treated bed nets (LLINs),and use of Rapid Diagnostic Tests (RDTs) have reduced Malariaprevalence from 39% in 2005 to less than 1% in 2011-2012. Asmalaria burden decreases, there is an increasing need to track andfollow up individual cases to contain transmission that could lead toresurgence. One method being used to achieve these aims is reactivecase detection (RACD).RACD is generally understood to be triggered whenever a case isidentified by passive case detection. The response involves visiting thehousehold of the newly reported case and screening family members.Depending on program protocol, it may also involve screeningneighbors within a defined radius. RACD has been used or testedin Cambodia, China, India, Peru, Senegal, Swaziland, Tanzania,and Zambia. RACD can be resource intensive. Several studies raisequestions concerning whether and how RACD can be prioritized andtargeted effectively as case numbers continue to decline.MethodsSince September 2012 Zanzibar Malaria Elimination Programme(ZAMEP) has used RACD to limit onward transmission, reduce thelocal parasite reservoir, and gather data needed improve programeffectiveness. Zanzibar is one of very few malaria eliminationcontexts using a mobile technology system to support RACD.1Thissystem, called the Malaria Case Notification system (MCN) usesmobile software called Coconut Surveillance.Coconut Surveillance is free and open source software designed formalaria elimination. It includes an interactive SMS system for casenotification, a mobile software application designed to guide mobilecase workers through RACD, and an analytics software applicationdesigned for surveillance and response program managers.Data were collected in the Coconut Surveillance database formore than three years, beginning in September 2012. Reports weremonitored in real time and periodically to assess RACD responsetimes against protocol targets, case trends, case locations, and otherdata. Geographical Information System (GIS) software was usedto produce detailed maps of case households. Three independentassessments were conducted of various aspects of the malariasurveillance system.ResultsFrom September 2012 to December 2015, Coconut Surveillancehas helped malaria surveillance officers in Zanzibar respond tomore than 8,617 (84%) reported cases of malaria, complete nearly10,245 household visits, test more than 36,185 household members,and identify and treat 2,032 previously unknown cases. The averagenumber of RACD activities occurring within 48 hours increased from72% in 2013 to 89% in 2015. The number of household membersscreened during RACD also increased from 7,589 in 2013 to 14,987in 2015. Challenges included incomplete registers at health carefacilities, lack of transport, inadequate training for clinicians andsurveillance officers, and insufficient communication to the affectedcommunities.ConclusionsIn Zanzibar twenty malaria surveillance officers equipped withinexpensive Android tablets and motorbikes are keeping malariaprevalence at less than 1%. The effectiveness of the system mightbe enhanced by improving training for clinicians and surveillanceofficers, ensuring the availability of transportation for surveillanceofficers, and improving communications to the affected communities.These results suggest key considerations for applying this and similarsystems in other malaria elimination contexts.
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