“We’re working closely with the Ministry of Health to use the model in analyzing how the COVID trends are moving,” Muwanguzi said. “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. We had fewer cases than projected because we were able to mitigate a predicted source that was captured well in the model.”
Muwanguzi also noted that the tool not only helps provide data for mitigation policies, but it also helps the country plan how to use its resources.
“For example, 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.”
Yet, on June 18, Uganda entered a 42-day lockdown after the daily number of new cases increased from fewer than a hundred at the end of May to nearly 2,000. The week after the lockdown started, the model projected 11,222 new cases would be reported if no mitigation efforts were put in place.
“Unlike the previous wave where factors influencing the spread were mostly from outside the country, the current wave is influenced by internal factors,” said Joseph Muvawala, executive director of NPA, in a column published by New Vision, a national newspaper in Uganda. “With these statistics, a total lockdown was inevitable, irrespective of the known economic consequences; human life is far too precious to lose.”
According to Muvawala’s column, the projected increases have helped Uganda better prepare their hospital centers by procuring enough supplies and planning to avoid overwhelming hospitals and health care workers.
However, Ssentongo warned, the model is only as good as the data provided to it.
“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.”
Global benefit of global collaboration
According to Schiff, their findings clearly demonstrate the advantages of inter-country cooperation in pandemic control.
“This is a crisis that no single country can fully manage on its own,” Schiff said.
The researchers plan to continue updating the tool with more information as it becomes available, as well as implement data regarding vaccinations as they become more available in Africa. It is available freely online.
“One of the limitations of doing science is that you can do clever work, publish in a good journal that is reviewed by your peers, but it is still difficult to translate the work into effective policy,” Schiff said. “We wanted to implement this tool to do good and help save lives. We could never have accomplished this without the close collaboration with our African colleagues in Uganda. It was critical to make sure this was a framework that people who make policy can use and apply in their work — that’s what makes this valuable.”
Schiff is also affiliated with the Huck Institutes for Life Sciences’ Center for Infectious Disease Dynamics and the Department of Physics at Penn State. Other contributors include co-first authors Claudio Fronterre, Centre for Health Informatics, Computing and Statistics, Lancaster University, United Kingdom, and Andrew Geronimo, Department of Neurosurgery, Penn State College of Medicine; Helen Greatrex, Steven J. Greybush and Yan Wang, Penn State Department of Meteorology and Atmospheric Science; Pamela K. Mbabazi, Joseph Muvawala, Sarah B. Nahalamba and Philip O. Omadi, National Planning Authority, Uganda; Bernard T. Opar, Ministry of Health, Uganda; Shamim A. Sinnar, Penn State Department of Medicine, Penn State College of Medicine; and Michael M. Norton, Penn State Center for Neural Engineering, Penn State Department of Engineering Science and Mechanics; Andrew J. Whalen, Massachusetts General Hospital Department of Neurosurgery and Harvard Medical School; Leonhard Held, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Switzerland; and Christopher Jewell and Peter Diggle, Centre for Health Informatics, Computing and Statistics, Lancaster University, United Kingdom.
The U.S. NIH Director’s Transformative Award and the Coronavirus Research Seed Fund from Penn State’s Institute for Computational and Data Sciences and the Huck Institute for Life Sciences supported this work.
Note: A perspectives article on this study was published on Aug. 3 in PNAS. The authors, Belinda Archibong, assistant professor of economics at Barnard College, Columbia University, and C. Jessica E. Metcalf, associate professor of ecology, evolutionary biology and public affairs, Princeton University, were not involved in the research led by Schiff. The perspectives article lauds the modeling tool, specifically its ability to both reveal and incorporate significant heterogeneity of infectious diseases transmission and response across Africa, and calls for more data collection and sharing to continue improving such tools.