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With the advent of an infectious disease outbreak, epidemiologists and public health officials quickly try to forecast deaths and infections using complex computer models. But with a brand new virus like the one that causes COVID-19, these estimates are complicated by a dearth of credible information on symptoms, contagion and those who are most at risk.
My team at the Goldenson Center for Actuarial Research has developed a free, user-friendly computer model that has a different goal. It demonstrates how infections and deaths progress on a daily basis over a three-month period depending on how people behave in response to the outbreak. This model allows the public to input data that demonstrate how changes in safety measures in their communities, including wearing face covering and social distancing, can significantly impact the spread of this virus and mortality rates.
Our Goldenson Center COVID-19 model uses a hypothetical 1,000-person population and calculates outcomes using three types of information: the initial number of infections, social distancing, and personal protection measures that include wearing masks, frequent hand-washing and staying quarantined if exhibiting COVID-19 symptoms. Our model then uses this initial information to project on a daily basis the cumulative infections and deaths over a three-month period. It’s not based on actual disease data and is designed to demonstrate the effects of safety measures, rather than make specific predictions.