Predictions For Europe For The COVID-19 Pandemicafter Lockdown Was Lifted Using An Sir Model

AO_SCPLOWBSTRACTC_SCPLOWI analyze a simplified SIR model developed from a paper written by Gyan Bhanot and Charles de Lisi in May of 2020 to find the successes and limitations of their predictions. In particular, I study the predicted cases and deaths fitted to data from March and its potential application to data in September. The data is observed to fit the model as predicted until around 150 days after December 31, 2019, after which many countries lift their lockdowns and begin to reopen. A plateau in cases followed by an increase approximately 1.5 months after is also observed. In terms of deaths, the data fits the shape of the model, but the model mostly underestimates the death toll after around 160 days. An analysis of the residuals is provided to locate the precise date of the departure of each country from its accepted data estimates and test each data point to its predicted value using a Z-test to determine whether each observation can fit the given model. The observed behavior is matched to policy measures taken in each country to attach an explanation to these observations. I notice that an international reopening results in a sharp increase in cases, and aim to plot this new growth in cases and predict when the pandemic will end for each country.