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A Stratified Model to Quantify the Effects of Containment Policies on the Spread of COVID-19
{In this manuscript, a method is presented that can be used to predict the spread of COVID-19 in any country and under any containment policy imposed separately on different groups in the population. The method tunes the parameters of a known stratified model based on the available data on the spread of COVID-19. The model includes a set of nonlinear ordinary differential equations and is easy to simulate and easy to understand. As it is presented in this manuscript, the population is divided into age-groups. But given the availability of the data, there is no reason to limit the stratification into only age-groups and we can consider any relevant groups. To estimate the parameters of the model such that it reflects the characteristics of the spread of COVID-19 in a population, the method relies on an optimisation scheme. More specifically, the optimisation scheme estimates the contact rates between different age groups in the population. But a very important and useful feature of the model is that the estimated parameters for one population can be translated and used for any other population with a known age-structure, which in this day and age, includes almost any country or city in the world. Also, it is shown that the method is quite insensitive to the underlying assumptions in the optimisation scheme and also to deliberate or non-deliberate errors that might have occurred in collecting the data.}
@misc{item_3239456, title = {{A Stratified Model to Quantify the Effects of Containment Policies on the Spread of COVID-19}}, abstract = {{In this manuscript, a method is presented that can be used to predict the spread of COVID-19 in any country and under any containment policy imposed separately on different groups in the population. The method tunes the parameters of a known stratified model based on the available data on the spread of COVID-19. The model includes a set of nonlinear ordinary differential equations and is easy to simulate and easy to understand. As it is presented in this manuscript, the population is divided into age-groups. But given the availability of the data, there is no reason to limit the stratification into only age-groups and we can consider any relevant groups. To estimate the parameters of the model such that it reflects the characteristics of the spread of COVID-19 in a population, the method relies on an optimisation scheme. More specifically, the optimisation scheme estimates the contact rates between different age groups in the population. But a very important and useful feature of the model is that the estimated parameters for one population can be translated and used for any other population with a known age-structure, which in this day and age, includes almost any country or city in the world. Also, it is shown that the method is quite insensitive to the underlying assumptions in the optimisation scheme and also to deliberate or non-deliberate errors that might have occurred in collecting the data.}}, year = {2020}, slug = {item_3239456}, author = {Bokharaie, V} }