Digital Tool Use in Malaria Surveillance Programs

[Zoe KaldorKeymaster]

We hosted a very engaging webinar on Wednesday, July 11th with Jessica Long, a representative from Dimagi, who discussed how digital tools can help strengthen and support malaria surveillance programs. Below is a summary of the discussion and some key takeaways. If you missed the webinar, you can find the recorded session here and a downloadable version of Jessica’s presentation here.

Background

For the past six months, the National Malaria Control Programs of Senegal and The Gambia, in close partnership with Catholic Relief Services (CRS), have been establishing best practices for coordinating malaria interventions and clinical care in border regions. Jessica gave a brief overview of Dimagi’s work to help prototype a shared cross-border malaria data visualization tool to improve the surveillance of malaria prevelance in Senegal and the Gambia. Malaria surveillance tends to be weakest in countries with the highest burden, making it difficult to accurately assess disease trends and plan interventions. Digital tools like Dimagi’s ATLAS and CommCare platforms help National Malaria Control Programs determine which areas of their countries have the highest rates of malaria. This data then helps countries design strategic malaria control interventions to address region specific.

Some Key Takeaways:

As a digital intervention, CommCare serves as a mobile data collection platform that supports remote workers’ data management in low resource areas. DHIS2 serves as a national health data collection and analytics platorm, and together they make up the most common health information system platforms in West Africa.

ATLAS data visualizations and predictive analytics platform allows it to read any data source – DHIS2, CommCare, or others – and layer analytics on top of very detailed satellite images that allows malaria surveillance programs to dynamically predict population density, for example.

With the detailed imagery afforded by the ATLAS platform, NMCPs can plan household-level interventions and can more accurately assess level of coverage acheived. It allows users to count number of households in a remote area with detialed satellite images to make targets assess the effectiveness of indoor residual spray (IRS) or long lasting insectiside-treated net (LLIN) distribution interventions.

The vision for cross-border data sharing in Senegal and The Gambia looks something like this:

1. Strengthen data collection at a district, facility, and community level
2. Ensure all mobile data collection tools integrate with a national DHSI2 platform
3. Define a shared set of indicators to establish a data exchange protocol
4. Design a data visualization interface that can be used to evaluate the effectiveness of malaria interventions and identify potenial new areas for intervention
5. Establish a set of criterea for how a shared data visualisation will guide action

Be sure to check out the recorded version of Jessica’s session with us, avaialbe here. We look forward to your thoughts and comments below.

• This topic was modified 4 years, 11 months ago by  Zoe Kaldor.
• This topic was modified 4 years, 11 months ago by  Zoe Kaldor.
• This topic was modified 4 years, 11 months ago by  Zoe Kaldor.
• This topic was modified 4 years, 11 months ago by  Zoe Kaldor.
• This topic was modified 4 years, 11 months ago by  Zoe Kaldor.

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