ADF STAFF
Dr. Joseph Muvawala stood before Ugandan journalists on July 7 with pages full of COVID-19 case numbers and a stern message.
“The lockdown,” he said, “is working.”
The executive director of Uganda’s National Planning Authority (NPA) based his conviction on data from a forecasting tool that makes biweekly predictions of new infections and helps health authorities decide whether to implement or modify countermeasures.
The authority collaborated with an international team of scientists led by a group at Pennsylvania State University in the United States to develop the tool for African countries.
It uses available case data, population, economic status, current mitigation efforts and meteorological data from satellites to project how COVID-19 could spread.
The scientists created a set of easy-to-interpret visualization tools, put them online with open-source coding, and worked closely with Ugandan planners and economists on implementation.
Project lead Professor Steven Schiff, who founded the Penn State Center for Neural Engineering, worked for 15 years with Ugandan hospitals, planners, economists, and policymakers on predictive mapping of infant infections and birth defects.
“When the COVID-19 pandemic began, we had this unusual team of scientists hard at work on implementing P3H (predictive, personalized public health) in Africa,” he said in an article on Penn State’s website.
“We thought that we had much we could contribute toward the fight against this new virus. It was critical to make sure this was a framework that people who make policy can use and apply in their work.”
Schiff’s team includes Paddy Ssentongo, assistant research professor of engineering science and mechanics, who is originally from Uganda.
Ssentongo said the diverse dynamics of COVID-19 in Africa necessitated a tool that could capture and interpret complex data.
“If we just wait for patients to become sick with COVID-19, we’re already losing,” he said. “The best thing to do is prevention.”
Working with the scientists, Abraham Muwanguzi, NPA manager of science and technology, gave the modeling tool to Uganda’s Ministry of Health to analyze COVID-19 trends.
It has had major real-world implications.
“In September and October of 2020, at the peak of COVID cases, the model projected an increase in cross-border cases, prompting the government to close our border,” he said. “We had fewer cases than projected because we were able to mitigate a predicted source that was captured well in the model.”
The tool also helps the country plan how to allocate resources.
“In March and April of this year, the model projected a tremendous drop in cases,” Muwanguzi said. “Our hospital centers started emptying out — there really were fewer cases. We could then scale down operations and reappropriate resources to other areas of need.”
On June 18, however, Uganda began a 42-day lockdown after new cases spiked from fewer than 100 at the end of May to nearly 2,000. The week after the lockdown started, the model projected 11,222 new cases if no countermeasures were adopted.
The NPA says the predictive tool has proven to be 97% accurate.
But the forecasts are only as good as the data provided.
“We hope other countries in Africa will not only use this tool, but also collaborate to make sure they are integrating data in terms of testing and reporting cases,” Ssentongo said. “The tool is a roadmap to tell a country how the pandemic is evolving and where the country is going.
“It’s successful if the country sees the projections, implements mitigation efforts and sees a lower number of actual cases.”