Abstract
BACKGROUND: The health emergency declaration owing to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has drawn attention toward nosocomial transmission. The transmission of the disease varies depending on the environmental conditions. Saliva is a recognized SARS-CoV-2 reservoir in infected individuals. Therefore, exposure to fluids during dental procedures leads to a high risk of contagion. OBJECTIVE: This study aimed to develop an infection risk prediction model for COVID-19 based on an analysis of the settlement of the aerosolized particles generated during dental procedures. MATERIALS AND METHODS: The settlement of aerosolized particles during dental aerosol-generating procedures (AGPs) performed on phantoms was evaluated using colored saliva. The gravity-deposited particles were registered using a filter paper within the perimeter of the phantom head, and the settled particles were recorded in standardized photographs. Digital images were processed to analyze the stained area. A logistic regression model was built with the variables ventilation, distance from the mouth, instrument used, area of the mouth treated, and location within the perimeter area. RESULTS: The largest percentage of the areas stained by settled particles ranged from 1 to 5 µm. The maximum settlement range from the mouth of the phantom head was 320 cm, with a high-risk cutoff distance of 78 cm. Ventilation, distance, instrument used, area of the mouth being treated, and location within the perimeter showed association with the amount of settled particles. These variables were used for constructing a scale to determine the risk of exposure to settled particles in dentistry within an infection risk prediction model. CONCLUSION: The greatest risk of particle settlement occurs at a distance up to 78 cm from the phantom mouth, with inadequate ventilation, and when working with a high-speed handpiece. The majority of the settled particles generated during the AGPs presented stained areas ranging from 1 to 5 µm. This model was useful for predicting the risk of exposure to COVID-19 in dental practice.