Oral Presentation First Malaria World Congress 2018

Knowing is good – knowing everything is better (51367)

Edward Thomsen 1 , Kirsten Duda 1 , Busiku Hamainza 2 3 , Michael Coleman 1
  1. Liverpool School of Tropical Medicine, Liverpool, MERSYSIDE, United Kingdom
  2. National Malaria Elimination Programme, Lusaka, Zambia
  3. National Malaria Elimination Programme, Lusaka, Zambia

Effective malaria programmes rely on case management and vector tools to, control, eliminate and respond to outbreaks. To best deploy limited resources and obtain the largest impact requires control programmes access entomological, epidemiological and operational data from many diverse sources.

Most programmes rely predominantly on case data from the health management system, often the district health information system 2 (DHIS2). As no operational decision-support system has been able to interact in a user-friendly way with the DHIS2, integration of key data has been limited across programmes.

In order to fill this gap, we created a tool in the DDMS+ that is interoperable with DHIS2. The tool was built using open source software RunwaySDK, and interacts with the DHIS2 through its web API. The tool went through positive and negative user testing to ensure robustness. To enhance the ability of aggregating data from diverse data sets a novel drag and drop system was created that could create new data modules and associated “ontologies”.

Previously, DDMS+ was the only database and decision-support tool that accepted completely disaggregated entomological and intervention monitoring data. With the new interoperability functionality added during this project, a user can aggregate that data, and send indicator datasets directly into the DHIS2. This allows DHIS2 users to create dashboards that not only have case surveillance data, but entomology and intervention data as well.

There are numerous software systems that have been created for vector control, however, the ability to share data between these systems is lacking and this hinders the success of control and elimination programmes. We have developed the first platform that can integrate diverse data easily and share data with other key country systems such as the DHIS2. Currently this is being evaluated in several disease settings including malaria to improve the vector control and elimination agenda.