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Decision making of lockdown during COVID-19 pandemic

The Covid-19 pandemic has led to an unprecedented challenge to the lifestyle of people, public health.

The Covid-19 pandemic has led to an unprecedented challenge to the lifestyle of people, public health. The impact is felt in finance, business, travel, tourism, education, and other sectors of the company. People have been cautious, and that is why they introduced the lockdowns. However, there is a need to make predictions on different factors such as when the pandemic would and end and the duration of the lockdown so that necessary action is taken.

The authors talk about a predictive mathematical model of both the first, second, and third worlds on the future predictions of the pandemic. The authors insist that the prediction may be useful to government authorities, planning commissions, and healthcare organizations in coming up with suitable plans during the pandemic. There are proposed methodologies such as the SIR model for Covid-19, which detects any disease, time-dependent discrete SIR, and steady-state solutions. The authors further analyze the lockdown effect, a plan of action the government can take, including having a partial lockdown. He concludes that data can be trained and studied to ensure future pandemics are regulated.

The author shares an analysis that is hard to believe, given that the data gathered over the Covid-19 situation is still small. The duration of the pandemic is less than two years, which means that there is a possibility of inadequate data to make conclusions. I support the authors’ assertions that if mathematical models are crafted out of the Covid-19 data, it can help with managing future pandemics. There is also a need to consider other models to try and find out which are the best models. Markedly, the article articulates accurate models to fit the Covid-19 data, and the relevance of results from the models showcases a possibility of managing different situations when pandemics strike. However, there is a need to have more data and data spread over more than two years to come up with an accurate prediction and conclusion.

Read more:
Ghosh, A., Roy, S., Mondal, H., Biswas, S., & Bose, R. (2021). Mathematical modelling for decision making of lockdown during COVID-19. Applied Intelligence, 1-17.

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