NTU computer model can help cut Covid-19 infections, deaths by up to 89%
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Reviewed by Emily Henderson, B.Sc.Sep 16 2021

A team of scientists from Nanyang Technological University, Singapore (NTU Singapore) has developed a predictive computer model that, when tested on real pandemic data, proposed strategies that would have reduced the rate of both COVID-19 infections and deaths by an average of 72 percent, based on a sample from four countries.

The model, called NSGA-II, could be used to alert local governments in advance on possible surges in COVID-19 infections and mortalities, allowing them time to put forward relevant countermeasures more rapidly.

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The team also showed NSGA-II could make predictions on the daily increases of COVID-19 confirmed cases and deaths that were highly accurate, at a confidence level of 95 percent, compared to the actual cases that took place in the four countries over the past year.

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Assistant Professor Zhang Limao from NTU's School of Civil and Environmental Engineering, who led the study, said: "The main goal of our study is to aid health authorities to make data-driven decisions in fighting the global COVID-19 pandemic. As we have observed in global efforts, there is no one-size-fits-all solution, and we hope our comprehensive programme would be able to help governments tailor the solutions at an early stage to best fit their country's needs at different stages of the pandemic. The critical knowledge discovered in historical data enables us to provide early warning, preparation, and prevention for crisis control and enhance the resilience of human societies."


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