Forecasting the spread of COVID-19 based on policy, vaccination, and Omicron data.

The COVID-19 pandemic caused by the novel SARS-COV-2 virus poses a great risk to the world. During the COVID-19 pandemic, observing and forecasting several important indicators of the epidemic (like new confirmed cases, new cases in intensive care unit, and new deaths for each day) helped prepare the appropriate response (e.g.

An analysis of the waning effect of COVID-19 vaccinations.

Vaccine development is one of the key efforts to control the spread of coronavirus disease 2019 (COVID-19). However, it has become apparent that the immunity acquired through vaccination is not permanent, known as the waning effect. Therefore, monitoring the proportion of the population with immunity is essential to improve the forecasting of future waves of the pandemic.

Development of New Stringency Indices for Nonpharmacological Social Distancing Policies Implemented in Korea During the COVID-19 Pandemic: Random Forest Approach.

Background: In the absence of an effective treatment method or vaccine, the outbreak of the COVID-19 pandemic elicited a wide range of unprecedented restriction policies aimed at mitigating and suppressing the spread of the SARS-CoV-2 virus. These policies and their Stringency Index (SI) of more than 160 countries were systematically recorded in the Oxford COVID-19 Government Response Tracker (OxCGRT) data set. The SI is a summary measure of the overall strictness of these policies.