Offline-first data collection app and dashboard for the discovery, treatment and followup of sleeping sickness cases.


The Ministry of Health of the Democratic Republic of Congo does active and passive case finding expeditions to find and treat people sick with Human African Trypanosomiasis, also known as HAT or sleeping sickness. Sleeping sickness is caused by the bite of the tsetse fly, that transmit a trypanosomes that infect the patients blood and cerebrospinal fluids and cause symptoms that slowly develop over years and that end with the patient’s life.

The trypanosomes are first in the blood and case mild symptoms like headaches, fatigue or inflamed glands. People in this first stage of the disease rarely seek treatment, but can transmit the disease to others through the bite of the fly (the vector of the disease) and should be identified and treated. If they are not they will progress into the second stage of the disease and the trypanosomes will get into the liquid in the brain and spine and start causing more severe symptoms and eventually the death. HAT affects mostly poor populations living in remote rural areas of Africa. In order to identify and treat new cases and reduce the transmission with the goal of total elimination in 2020 in mind, mobile teams travel to villages at risk to mass test populations.

HAT is a neglected disease, endemic in the region. The number of cases has continued to decrease over the years, but getting to zero cases is challenging due to the cost of finding and treating patients, the particularities of the disease, the complexity of the treatment, the cultural appreciation of it, and the challenges of delivering health services in DRC.


With the support of the Bill and Melinda Gates Foundation and the University of California – Los Ángeles (UCLA) we built a data collection app and a dashboard to move from paper to digital for data collection and micro-planning.



  • Limited or no connectivity
  • Incomplete maps and multiple names for each location
  • No IDs used for personal identification of patients
  • Need to incorporate historical data
  • Health care workers have low tech literacy
  • Active case finding consists of a series of tests done by different teams in different moments of time


  • Define offline-first workflows and resolve sync
  • Geolocate tests locations and feed maps used by other programs
  • Propose a way to uniquely identify patients maintaining their privacy
  • Define workflows to incorporate historical data to program database
  • Launch an app that can easily be used by healthcare workers


My team at eHealth Africa was part of a consortium of experts from different organizations. We met with representatives of the HAT program at the Ministry of Health of DRC to learn about the context of the program and the data collection efforts to date. These meetings, celebrated at the Institute of Tropical Medicine in Antwerp and with frequent followup calls, helped us understand the problem and propose a more suitable solution.

At the kick-off of the program and when we had a prototype ready for a pilot in the field I travelled to DRC with members of my team to have meetings with the HAT program directors to gather requirements and validate progress. In our trips to the field we spent a week following mobile teams doing active case finding and visited some of the clinics doing treatment for confirmed cases. These trips provided insights about the context of use, the end users, and the challenges and mitigation options, and informed the user experience of our solution, the workflows supported by our app, and the user interface designs.

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