Process data on the number of infected, deceased and dead over time? To make predictions in conditions of great variability and unexpected upheavals? To conduct a comparative analysis? To realize statistical conclusions? And where are the predictions, projections, simulations, and how valid and useful are they in cases where uncertainty and risk are high?
Statistics, predictions, projections and simulations are all very important in the fight of the Covid-19 pandemic. They guide to a large extent for which many public health measures would not have been taken or gone extremely poor. In fact, public health or health in its generality would not have been here, but for the statistics, predictions, projections, simulations. We need them, all the time.
Edward Wilson Ansah and Maya Lambovska comments are supported by online Synposia. I suggest you log at St Jude Chilren's hospital, AMerican Statistical Association, And UCONN Statistics Dept. for a few online examples. D. Booth
Its a broad area and impacts are direct and indirect.
We a group of mathematicians and statisticians have modeled the impact of different macro economic parameter on the consumption pattern and stock market for different businesses in a country. to predict the growth and recovery path and pace for businesses overall.
Macro economic factors like GDP, unemployment rate, repo rate, etc.. and its impact on economic recovery is critical.
We have built multiple ensemble models to analyze the impact of Pandemic (increase in infection rate, mortality rate, spread, peak) on macroeconomic parameters, which in-turn will impact stocks and commodity sales. Hence used simulations then to predict the impact of different businesses and their recovery pattern at national and market levels.
Used techniques like nowcasting and DSGE
refer the paper, should this give you some idea:
Article 3Ps- Path, Pace and Pattern of Recovery from COVID-19 for Di...