2014.ISDS.Abstracts.Final.pdf


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ISDS 2014 Conference Abstracts

Using Mobile Technology to Help Eliminate Malaria in 
Zanzibar

Gordon M. Cressman*1, Michael V. McKay1, Abdul-wahid Al-Mafazy2, Mahdi M. Ramsan1, 
Abdullah S. Ali2, Issa A. Garimo1, Humphrey Mkali2 and Jeremiah J. Ngondi1

1RTI International, Research Triangle Park, NC, USA; 2Zanzibar Malaria Elimination Programme, Zanzibar Town, United Republic of 
Tanzania

Objective
This presentation aims to share the results of a six-year effort to 

use mobile health (mHealth) technology to help eliminate malaria 
from a well-defined geographic area. This presentation will review 
the history, technology, results, lessons-learned, and applicability to 
other contexts.

Introduction
Zanzibar is comprised primarily of two large islands with a 

population of 1.3 million. Indoor Residual Spraying (IRS) campaigns, 
distribution of long-lasting insecticide treated bed nets (LLINs), 
ensuring treatment medication is available, and use of Rapid 
Diagnostic Tests (RDTs) have reduced Malaria prevalence from 
39% in 2005[1] to less than 1% in 2011-2012. This is the third time 
Zanzibar has been close to eliminating malaria, but there are serious 
challenges. These include vector resistance to pyrethroids, the short-
lived efficacy of LLINs, and resistance to behavior change. Constant 
traffic with mainland Tanzania and foreign countries also poses 
the risk of outbreaks. An effective and sustained surveillance and 
rapid response system is essential to control outbreaks and optimize 
interventions.

Methods
In 2008 The Zanzibar Malaria Elimination Program (ZAMEP), 

in collaboration with the U.S. President’s Malaria Initiative (PMI), 
the U.S. Centers for Disease Control and Prevention (CDC), and 
RTI International (RTI), developed and implemented the Malaria 
Epidemic Early Detection System (MEEDS). MEEDS enabled 159 
government primary health care units to use simple forms displayed 
on feature phone handsets to submit weekly aggregate case data via 
Unstructured Supplementary Service Data (USSD). This enabled 
ZAMEP to make data-driven decisions regarding active case detection 
and coverage of malaria interventions.

In 2012 MEEDS was modified to support individual case reporting. 
Each District Malaria Surveillance Officer (DMSO) was equipped 
with a tablet computer running Coconut Surveillance, a mobile 
application developed by RTI in collaboration with ZAMEP. Coconut 
Surveillance receives case alerts from MEEDS automatically. Once a 
DMSO is alerted of a new case, he or she is guided through an active 
case response protocol by Coconut Surveillance. Additional case data 
are entered into the tablet at the facility and the household. Coconut 
Surveillance uses the Geographical Positioning System (GPS) 
capability of the tablet to record the location of the household. Each 
household member is tested, and new cases are treated immediately. 
The data are synchronized at least daily with a shared cloud database. 
A web-based dashboard enables near real-time monitoring of active 
follow-up. An automated notification system helps to alert officials 
to system errors and problems with case follow-up. Officials use 
near real-time maps and reports to quickly identify hot-spots and 
transmission patterns.

Results
Since January 2013 this integrated system has been used to 

respond to more than 4,000 case reports, Rapid Diagnostic Tests 
(RDTs) have been administered to and data collected from more than 
14,400 household members, and 914 new cases have been diagnosed 
and treated. This provides Zanzibar with near real-time case 
identification, geo-located data, and management information about 
field staff progress. Continuous enhancement has added intelligence 
and automation to improve data quality, detect outbreaks, and alert 
decision makers.

Conclusions
The integrated MEEDS and Coconut Surveillance system in 

Zanzibar is recognized as one of the most advanced in the world, but 
it faces several challenges. For example, services for the MEEDS 
facility-based case reporting system are costly and, at times, 
unreliable. The system is not linked to the Health Management 
Information System (HMIS). Finally, cases from the extensive private 
sector, migrants and the military are not captured, and the system does 
not capture information on intervention quality.

Keywords
Malaria; Surveillance system; Surveillance-response systems; Mobile 
technology; Tanzania

References

1. Jaenisch T, Sullivan DJ, Dutta A, Deb S, Ramsan M, Othman MK,
Gaczkowski R, Tielsch J, Sazawal S. Malaria incidence and prevalence 
on Pemba Island before the onset of the successful control intervention 
on the Zanzibar Archipelago. Malar J. 2010;7:32.

*Gordon M. Cressman

E-mail: gmc@rti.org    

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 7(1):e15, 2015