The COVID-19 Testing Impact Calculator is a free resource that shows how different approaches to testing and other mitigation measures, such as mask use, can curb the spread of the virus in any organization. It provides schools and businesses with clear guidance on risk-reducing behaviors and testing to help them stay open safely, according to the National Institutes of Health.
The tool was funded by the National Institute of Biomedical Imaging and Bioengineering (NIBIB), part of the National Institutes of Health. A team led by the Consortia for Improving Medicine with Innovation and Technology (CIMIT) at Massachusetts General Hospital, Boston, and researchers at the Massachusetts Institute of Technology (MIT), Cambridge, developed the tool to model the costs and benefits of COVID-19 testing strategies for individual organizations.
The team developed their mathematical model and calculator as part of NIH's Rapid Acceleration of Diagnostics (RADx) Tech program. The calculator is simple: a user enters a few specifics about their site and the tool produces customized scenarios for surveillance testing. The tool models four different COVID-19 testing methods, including onsite and lab-based, and calculates the number of people to test each day. It shows the estimated cost of each testing option and outlines the tradeoffs in the speed and accuracy of each kind of test.
The COVID-19 Testing Impact Calculator also shows how other Centers for Disease Control and Prevention-recommended countermeasures, such as masks, contact tracing and social distancing, can work in concert with testing to keep people safe. Users enter which of these measures are in place in their organization and the tool integrates this information to produce testing recommendations. By adjusting these entries, users get a demonstration of how implementing simple countermeasures can drastically reduce their testing costs. For example, for a site that allows mask-less activities, such as meetings or dining, reducing the group size on the calculator from 12 to six cuts the cost of the recommended testing strategy by more than half.
