Expanding to the Elimination 8 Countries
By: Allan Walker, Anya A’Hearn, Marena Brinkhurst
Using open data and location analytics, the #VisualizeNoMalaria initiative, the Republic of Zambia Ministry of Health, PATH, and MACEPA are working towards a malaria-free country. Collaborating with eight technology partners, including Mapbox, the initiative is applying business intelligence tools and training to transform how Province and District Health Care Professionals report, visualize, and act on their data.
For the past two years, we’ve helped rally thousands of volunteers working together to map hundred of thousands of square kilometers of the malaria affected world. This year, we’re working alongside PATH and other technical partners to develop analysis-ready data layers to help answer critical operational questions. The #VisualizeNoMalaria partners are also committed to collaborating with the wider malaria elimination community to share the tools and datasets that we are building with the other Elimination 8 countries in southern Africa.
Access to better data has helped drive a 92 percent reduction in malaria-related deaths in Southern Province, Zambia, between 2014 and 2017. But malaria has no regard for borders. Collaboration between provinces and countries is key to making progress against this deadly disease.” (Courtesy PATH)
Scaling the data
To support an expansion of efforts in Zambia and beyond, we need to scale the data behind the operational dashboards that the #VisualizeNoMalaria initiative has built with PATH and public health officials.
So far, Mapbox volunteers have processed over 50 gigabytes of open data on population density, hydrology, cell tower coverage, elevation data, and more for all of the Elimination 8 countries. We are now working with the #VisualizeNoMalaria partners to turn these data layers into user-friendly data layers in the operational dashboards. Users can also use custom Mapbox background maps integrated with Tableau to show features like roads, waterways, and structures when working with their malaria case data.
The data layers will also serve as inputs to a prototype predictive model that the #VisualizeNoMalaria partners are developing to enable forecasting of malaria cases, which will support health and aid workers to better prepare and deploy resources to get ahead of the disease.
Answering questions from the front lines
With this package of data layers, PATH will now be better equipped to answer questions like, “Where are Community Health Workers in Southern Zambia in view (or not) of cell towers?” This information can increase the fidelity of data on malaria cases because Community Health Workers use SMS to report cases of malaria, so it’s crucial to know where they can and cannot get cell reception to submit reports on time.
Combining the new data layers for cell tower coverage and elevation with data on the positions of Community Health Workers, in an Alteryx workflow, we’re able to get a picture of which Community Health Workers are inside and outside of cell tower range. This information is then linked with data on Malaria Case Reporting in PATH’s operational dashboards in Tableau to make the results of the analysis easier to explore and interact with.
These new data layers and the operational and predictive tools they support are still a work in progress. We’ll share more about how we built these data layers later this week. Watch for updates on the work of the #VisualizeNoMalaria partners and the Government of Zambia as we continue to build the operational dashboards and predictive model into robust tools for making data driven public health decisions.
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Helping PATH scale out data for #VisualizeNoMalaria was originally published in Points of interest on Medium, where people are continuing the conversation by highlighting and responding to this story.