The international team is developing a predictive tool to help mitigate COVID-19 in Africa


The modeling tool incorporates data from current cases, population, economic status, current mitigation efforts and meteorological detection of satellites to project how COVID-19 could be extended to and between African countries. Credit: Andrew Geronimo, Penn State

The virus that gives rise to COVID-19 is the third coronavirus that has threatened humanity in the last two decades. It also happens to move more efficiently from person to person than SARS or MERS. The first African case of COVID-19 was diagnosed in Egypt in mid-February 2020. Four weeks later, the first closures across Africa began. Steven Schiff, President Brush’s engineering professor at Penn State, who had already established research partnerships in Uganda, saw his team’s opportunity to apply what they learned from their ongoing efforts to track and control disease infectious countries and provide countries like Uganda with more information to help guide policy to mitigate the viral pandemic.

The result was a collaboration between several countries to develop a surveillance modeling tool that would provide a weekly projection of predicted COVID-19 cases in all African countries, based on current case data, population, , current efforts to mitigate and detect meteorological satellites. Developed in collaboration with Uganda’s National Planning Agency (NPA), the country’s senior organization for economic development and planning, the tool’s COVID-19 projections use openly available data to provide a projection of cases, as well as lower and upper ranks to help the country decide whether to implement or modify mitigation policies.

The researchers published their approach on June 29 at Proceedings of the National Academy of Sciences of the United States of America. The project was funded in part by the Director of National Institutes of Health’s Transformative Research Award, a grant awarded to Schiff in 2018 for its “high risk and high reward” approach to predictive and personalized public health (P3H).

Prediction that guides the prevention of a pandemic

“When the COVID-19 pandemic started, we had this unusual team of scientists working hard on the implementation of P3H in Africa, and we thought we could contribute a lot to the fight against this new virus,” said Schiff, who founded Penn State Center for Neural Engineering and serves as a professor of scientific and mechanical engineering at the College of Engineering and neurosurgery at the College of Medicine.

The team includes Paddy Ssentongo, assistant professor of research in scientific and mechanical engineering. Ssentongo is originally from Uganda, where he earned a bachelor’s degree in medicine before moving to Penn State to complete a master’s degree in public health and a doctorate in epidemiology. He graduated this year.

“This pandemic has shown us that we need to put more emphasis on global public health, especially in places with fragile health systems, including many African countries,” Ssentongo said. “If we wait for people to get sick, we’re already losing. The best we can do is prevent.”

Researchers reached out to various disciplines to attract experts — from epidemiologists to meteorologists and economists — on all the factors that influence viral spread.

“We put together a great team to deal with what was needed,” said Schiff, who is also a researcher at the Penn State Neuroscience Institute. “The team is made up of 19 people spread across four countries, in addition to many more people who contributed through discussions and support.”

The complexity of mitigation

Equally important as understanding the number and location of people with active cases, according to Schiff, is understanding the importance of climate, geography, and other factors, especially in developing countries where many people live and work in more exposed conditions than people. of industrialized countries. .

“If a coastal country closes its borders, it is likely that landlocked Uganda will see an increase in cases because they depend on coastal countries to import them, without imports, people will move and interact more to find work and food,” he said. dir Schiff. noting that these changes in movement may create changes in the projections of new cases from neighboring countries versus domestic cases. “You need real-time information gathered about the virus, such as tests and blockages, as well as other influencing factors such as the varied economic security of different countries and their health systems. Our strategy synthesizes all this data across Africa to make surprisingly good projections of the expected number of cases depending on how these factors interact and influence the transmission of COVID to the population “.

Abraham JB Muwanguzi, co-author of the paper and manager of the NPA’s science and technology department, is also the principal investigator in Uganda with the Schiff NIH Fellowship.

“We are working closely with the Ministry of Health to use the model in analyzing how COVID trends are moving,” Muwanguzi said. “In September and October 2020, at the peak of COVID cases, the model projected an increase in cross-border cases, which caused the government to close our border. We had fewer cases than expected because we were able to mitigate a predicted source that has been captured well in the model “.

Muwanguzi also noted that the tool not only helps provide data for mitigation policies, but also helps the country plan how to use its resources.

“For example, in March and April of this year, the model projected a huge drop in cases,” Muwanguzi said. “Our hospitals began to empty; there were really fewer cases. Then we could reduce operations and appropriate resources to other areas of need.”

However, on June 18, Uganda entered a 42-day shutdown after the daily number of new cases rose from less than a hundred in late May to nearly 2,000. The week after the closure began, the model anticipated 11,222 new cases if no mitigation efforts were made.

“Unlike the previous wave where the factors influencing the spread were mostly from outside the country, the current wave is influenced by internal factors,” NPA executive director Joseph Muvawala said in a column published by New Vision, a national newspaper in Uganda. “With these statistics, a total blockade was inevitable, regardless of the known economic consequences; human life is too valuable to lose.”

According to the Muvawala column, the planned increases have helped Uganda better prepare its hospitals by procuring sufficient supplies and planning to avoid overwhelming hospitals and health workers.

However, Ssentongo warned, the model is only as good as the data provided to it.

“We hope that other African countries will not only use this tool, but also collaborate to ensure that they integrate data in terms of evidence and case reports,” Ssentongo said. “The tool is a roadmap to tell a country how the pandemic is evolving and where the country is going. It is successful if the country sees the projections, implements mitigation efforts, and sees a smaller number of real cases.”

Global advantage of global collaboration

According to Schiff, his findings clearly demonstrate the benefits of cross-border cooperation in pandemic control.

“This is a crisis that no country can handle on its own,” Schiff said.

Researchers plan to continue updating the tool with more information as it becomes available, as well as implement vaccination data as they become more available in Africa. It is available free of charge online.

“One of the limitations of doing science is that you can do smart work, publish it in a good journal reviewed by your peers, but it’s still hard 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 achieved this without the close collaboration of our African colleagues in Uganda. It was crucial to make sure that this was a framework that people that they make policies they can use and apply to their work; that’s what makes this valuable. ”

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More information:
Paddy Ssentongo et al, Pan-African evolution of COVID-19 dynamics within and between countries, Proceedings of the National Academy of Sciences (2021). DOI: 10.1073 / pnas.2026664118

Citation: International Team Develops Prediction Tool to Help Mitigate COVID-19 in Africa (2021, June 30) Retrieved June 30, 2021 at -international-team-tool-mitigate-covid-. html

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