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Counting Cases, or Protecting the Workforce? Establishing Freedom-from-Disease in Occupational Settings (304134)

Keywords: Applied statistics, COVID-19, sampling, survey, freedom-from-disease

Standard screening programs estimate the number of cases of disease in a population. An alternative approach is to estimate the likelihood that a population is free from disease. This is attractive in the context of workplaces aiming to reduce risk of COVID-19 for employees. COVID-19 has a contagious pre-symptomatic phase and might also be spread by asymptomatic cases. We developed a highly flexible sampling approach that maximizes the probability that a workplace is free from pre-/asymptomatic COVID-19 while minimizing the number of sampling events required over time and/or the sample size for each event. The approach accounts for imperfect lab tests, COVID-19 incidence and transmission rates in surrounding communities, population size (total and/or by shift) and transmission rates at the workplace. It can be used for long-term surveillance and to evaluate effectiveness of control measures. Input values can easily be changed to account for disease dynamics. The approach is implemented in Excel combined with the publicly available utility FreeCalc and is geared toward a broad audience; no prior experience with specific statistical methods is required.