Strategically increasing testing capacity, either by making diagnostic tests faster or more available, can reduce reliance on costly preventative interventions, such as distancing and shutdowns, according to researchers.

«The global spread of SARS-CoV-2 and the strategies used to manage it have come at significant societal costs; for example, shutdowns of non-essential businesses and stay-at-home orders are powerful tools to control the pandemic spread of the virus, but are unsustainable over time,» said Katriona Shea, Alumni Professor in the Biological Sciences, Penn State. «Understanding the efficacy of combined public health interventions is a key first step in identifying cost-effective ways to manage the pandemic, especially in areas where there is low vaccine uptake and as we continue to see new, and potentially more dangerous, variants of the virus emerge.»

The team used a mathematical model of SARS-CoV-2 transmission to measure public health outcomes under a variety of intervention scenarios, including testing and isolation and non-pharmaceutical interventions (NPIs) like masking, distancing and lockdown. Their results appeared today (Oct. 28) in the journal PLOS Computational Biology.

«Our work specifically addresses the impact of combining multiple public health interventions,» said Emily Howerton, graduate student in biology, Penn State. «Though these interventions have been well studied in isolation, understanding the combined effectiveness of these interventions is important for planning and pandemic response.»

In their model, the team’s testing system comprised three components — test administration, test delays and test sensitivity. The researchers modeled the number of tests that are administered each day. They defined testing delays as the average time, after test administration, it takes to receive test results and subsequently isolate those with a positive diagnosis. They defined test sensitivity as the percent of actively infectious individuals correctly identified by the diagnostic test. Because NPIs reduce the chance of new infections by preventing transmission, they are modeled to decrease transmission by a certain amount that the team calls the ‘NPI intensity.’

The team’s results suggest that high test administration, short testing delays and more intense non-pharmaceutical interventions all decreased SARS-CoV-2 infection burdens.

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Materials provided by Penn State. Original written by Sara LaJeunesse. Note: Content may be edited for style and length.