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We use the logistic function to estimate the number of individuals infectedby a virus in a period of time as a function of social isolation level in theprevious period of the infection occurrences. Each period is composed by afixed date range in days which the social isolation is supposed to take effectover the virus spread in the next date range. The sample is the COVID-19 casesand social isolation level data from S\~ao Paulo State, Brazil. The proposedmethod is divided into two stages: 1) The logistic function is fitted againstCOVID-19 empirical data to obtain the function parameters; 2) the functionparameters, except for the overall growth rate, and the mean of socialisolation level for all periods of time are used to calculate a constant called$\lambda$. The logistic growth rate for each period of time is calculated using$\lambda$ and the isolation level for that period. The number of cases in aperiod is estimated using the logistic function and the growth rate fromprevious period of time to obtain the effect of social isolation during theelapsed time. The period of time that produces a better correlation betweenempirical and estimated data was 5 days. We conclude the method performs a dataestimation with high correlation with the empirical data.

Estimating the number of COVID-19 cases from population isolation level