DiSARM

DiSARM is a spatial intelligence tool, built to enable disease control programs to deliver more effective field campaigns. It is currently being used to fight malaria in Botswana, Namibia, Zimbabwe and Swaziland. The project is supported by Bill and Melinda Gates Foundation, Clinton Health Access Initiative and Google.

There are two teams on the project: a data science team and a software development team. The data science team writes models for predicting things like roof types of buildings, sprayable/unsprayable structures and risk of contracting malaria for a given area. The development team builds software that supports these models.

I worked on the development team where we wrote software to support spray campaigns. The main piece of work has been creating DOUMA (DiSARM Offline Universal Mobile Application).

DOUMA allows the malaria programs to plan their campaigns ahead of time and gives them estimates on number of structures in the areas they want to spray. After planning, the spray teams can then collect data as they are spraying houses. Once data has been collected, it is all synced to a dashboard that provides the malaria programs with statistics on their spraying efforts.

DOUMA works offline as the network connection can be quite patchy in the areas that are being sprayed. The front-end was therefore built as a Progressive Web App with Vue, to take advantage of the offline functionality of service workers. The back-end is built with NodeJS and Mongo.

The code is open source and available on the github page.