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Singapore Computer Model to Reduce COVID-19 Infections

A team of scientists from Nanyang Technological University, Singapore (NTU Singapore) has developed a predictive computer model. When tested on real pandemic data would have reduced the rate of both COVID19 infections and deaths by an average of 72% 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.

The main goal of our study is to aid health authorities to make data-driven decisions in fighting the global COVID-19 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.

– Assistant Professor NTU’s School of Civil and Environmental Engineering and lead researcher

Through the testing of the model in four Asian countries using data available, the team demonstrated that it could have helped reduce the number of COVID-19 infections and deaths by up to 76% in Japan, 65% in South Korea, 59% per cent in Pakistan and 89 per cent in Nepal.

The computer model achieved the result by recommending timely and country-specific advice on the optimal application and duration of COVID-19 interventions, such as home quarantines, social distancing measures, and personal protective measures that would help to thwart the negative impact of the pandemic.

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%, compared to the actual cases that took place in the four countries over the past year.

Harnessing the power of machine learning, the research team developed the model by inputting large amounts of data on COVID-19 mortalities and infections worldwide that is available for the whole of 2020, helping it learn the dynamics of the pandemic.

As the pandemic progresses and the COVID-19 virus undergoes many mutations, it threatens the resilience of global society across every aspect of daily life, the environment, and the economy, and it requires the prompt and prioritised attention of policymakers worldwide.

The developed computer programme could serve as a useful tool to help governments formulate strategies and interventions at an early stage to limit or even counter a predicted surge in cases, reducing infections and mortality rates.

The team plans to introduce more variables, such as economic status and cultural differences, into the model to further improve its accuracy. They are seeking to validate its efficacy by including data from additional countries in Europe and North America, providing insights into COVID-19 evolution across different geographies.

As reported by OpenGov Asia, Singapore’s healthcare community have learned various things from the Covid-19 experience that can guide the way they deliver care in the future. Accurate information is essential as the basis for informed decisions. Moreover, people can take more control of their healthcare destinies when they are empowered by information and technology.

As Singapore and much of the world is turning the corner on the pandemic, it is driving the adoption of transformative technologies in healthcare. In the last year, it was the intense and unrelenting pressures of the pandemic that ultimately proved to be the most potent agent of change for digital transformation in healthcare.

The necessary elements of this transformation—the required infrastructure—are rapidly coming to maturity. It starts with the increasing availability of health data from connected devices. It is unleashed by the increasing sophistication of technologies like Artificial Intelligence (AI), hybrid cloud and automation.

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