Re-evaluating March/April 2020 COVID-19 infections in dental staff – a novel application of a predictive computational model

Introduction A computational model developed by others was applied retrospectively to our survey data on dental staff to determine whether the pre-existing infection control practices left dental staff at greater risk of infection with Covid-19. Method Survey data was used and passed through a computational model. Methods were devised to check for impact of the missing variables in the survey data, compared to the dataset used for the development of the computational algorithm. Results The model predicted 82/2888 (2.84%) of dental staff were infected. The model correctly predicted the results of all seven respondents who also reported PCR test results. The lack of included data on sex in the original survey had no impact on the output of the model by itself. Adding in the effect of skipped meals gave an upper bound of infected dental staff as 5.78% Discussion The model estimated between March 24 ^th - April 21 ^st 5.36% of mobile app users were infected with Covid-19. The estimated range of Covid-19 infections with dental staff compared favourably with this. Conclusion UK dental staff did not appear to be at increased risk of infection with Covid-19 compared with the background population during the beginning of the pandemic using the pre-existing infection control measures.