In a recent paper published in the Nature Journal, researchers discussed the development of the coronavirus disease 2019 (COVID-19) Activity Risk Calculator (CovARC), a gamified tool to estimate infection risks associated with day-to-day activities during the COVID-19 pandemic.
This simple tool aims to help the public make informed decisions regarding engaging in various activities and reducing COVID-19 transmission.
Study: COVID-19 activity risk calculator as a gamified public health intervention tool. Image Credit: Drazen Zigic/Shutterstock.com
Background
Varying risk levels have been identified for different activities and gatherings during the COVID-19 pandemic owing to factors such as precautions to prevent viral spread, vaccine efficacy, and COVID transmission rates.
This complexity in risk levels has resulted in confusion among the public regarding personal risk, which has led to the development of various tools to assess the risks.
However, currently available tools are inaccurate and overlook individual characteristics, leading to confusion around infection prevention strategies such as masking and vaccination. Since the determination of infection risk is crucial in the fight against the pandemic, there is an urgent need for accurate risk assessment tools.
Study
The present study describes the methods used in the development of CovARC. The tool uses various datasets from online sources, including variants and confirmed case datasets, COVID-19 Trends and Impact Survey on Facebook, the Johns Hopkins dataset, and the Centers for Disease Control and Prevention (CDC) variants dataset, to determine the number of active COVID-19 cases.
While the confirmed case dataset is updated daily, the variants dataset uses data from 31 days ago, as every variant is prevalent in the population for one month. The number of active cases is calculated by subtracting the confirmed cases on a given day from that of the previous day and calculating the 14-day aggregate.
CovARC also uses custom datasets such as the mask's fitted filtration efficacy (FFE) dataset and the vaccine efficacy against different viral variants dataset to estimate COVID-19 risk.
Additionally, the tool takes into account factors such as age, sex, indoor and outdoor environment, past illness, and viral variants on infection risk, hospital admission, and death in order to accurately assess the risks associated with various activities during the pandemic.
Results
The study results show the impact of vaccination and mask usage on infection risk during high case count periods. The researchers presented the range of risks of hospitalization and death in different scenarios, considering the impact of viral variants and the user’s health and demographic data.
The results show that CovARC uses various data sources and algorithms to assess the risk of infection, hospitalization, and death based on the data input by the user.
The risk assessment process involved extracting confirmed cases data from the Johns Hopkins dataset and cross-validating it with Facebook survey data, and then calculating the COVID-19 case density and adjusting it for the impact of variants, mask usage, and vaccination status.
The effectiveness of CovARC is shown through scenarios involving various age groups, mask types, vaccination statuses, and contact levels. The tool's user-friendly streamlined interface gives a range of risks rather than specific values.
Even as uncertainties persist in current methods used for COVID-19 risk estimation, this study shows CovARC as an accessible tool with the potential for COVID-19 risk reduction and public health education.
In the future, the researchers plan to add more parameters such as immunity, vaccination or infection-related health risks, and waning immunity to fine-tune the tool.
The study findings show the potential of the CovARC tool to empower the public to make informed decisions about safely engaging in various activities and reducing COVID-19 transmission.
Conclusions
To summarize, CovARC is a vital resource that can help the general public and policymakers determine COVID-19-related risks of infection, hospitalization, and mortality.
According to the authors, CovARC is simpler, more comprehensive, and more accurate than current alternatives, thanks to its streamlined interface that allows quick COVID-19 risk estimation.
The tool also takes into account factors such as gender, age, comorbidities, vaccination status, masks use, mask types, and the number of close contacts. Future directions include determining the impact of the CovARC tool on the level of COVID-19 community transmission.
This study contributes to public health by presenting a simple, scalable, yet accurate tool that estimates the COVID-19 transmission risk associated with various day-to-day activities during the pandemic.
Moreover, since CovARC considers factors such as variants of the virus and vaccine coverage, it can be useful in most parts of the world.
By highlighting the impact of mask use and vaccination on infection risk during high case count periods, the paper informs policy decisions on COVID-19 case thresholds for introducing mask mandates and other interventions.