A COVID-19 infection risk model for frontline health care workers

In this study, we formulate a theoretical model to calculate the risk of being infected in health care facilities considering the following factors: the average number of encounters with a suspected COVID-19 patient per hour; interaction time for each encounter; work shift duration or exposure time; crowd density, which may depend on the amount of space available in a given location; and availability and effectiveness of protective gears and facilities provided for the frontline health care workers. Based on the simulation results, a set of risk assessment criteria is proposed to classify risks as ‘low’, ‘moderate’, or ‘high’. We recommend the following: (1) decrease the rate of patient encounter per frontline health care worker, e.g., maximum of three encounters per hour in a 12-h work shift duration; (2) decrease the interaction time between the frontline health care worker and the patients, e.g., less than 40 min for the whole day; (3) increase the clean and safe space for social distancing, e.g., maximum of 10% crowd density, and if possible, implement compartmentalization of patients; and/or (4) provide effective protective gears and facilities, e.g., 95% effective, th at the frontline health care workers can use during their shift. Moreover, the formulated model can be used for other similar scenarios, such as identifying infection risk in public transportation, school classroom settings, offices, and mass gatherings.
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - Category: Bioinformatics Source Type: research