A bubble-type setting is a social network-based distancing strategy in which personnel work in a bubble where they are only allowed to interact with people within the same group, and a study has shown that it is the most effective approach to flatten the curve of COVID-19 cases (Block et al., 2020). This study focuses on the utilization of bubble-type settings, particularly in the context of different variants of the virus and screeners (e.g., masks and ventilation), to control the transmissibility of the COVID-19 virus in microscale production of emulsified sausage products. A microscale production process for emulsified sausage products was simulated in a bubble-type setting using AnyLogic Version 8.7.6 Personal Learning Edition (2022), and the Wells–Riley model was adapted to determine the effect of different variants of the virus, namely Wuhan, Delta, and Omicron, and the effect of screeners (e.g., masks and ventilation) on the probability of infection (POI) with the COVID-19 virus. A two-way ANOVA was used at a 0.05 level of significance using IBM SPSS Statistics 22 to determine if different factors had a significant effect on the POI and if there was an interaction between the factors. The results showed that different variants of the COVID-19 virus, screeners (e.g., masks and ventilation), and their interaction had a significant effect on the probability of infection with the COVID-19 virus in a bubble-type setting in microscale production of emulsified sausage products, indicating that the utilization of a bubble-type setting with control measures such as wearing efficient masks and an increased ventilation rate could be used to significantly reduce the probability of infection with the COVID-19 virus in microscale production of emulsified sausage products.