The Effectiveness of Strategies to Contain SARS-CoV-2: Testing, Vaccinations, and NPIs

TL;DR

This study uses an agent-based model to evaluate the impact of testing, vaccinations, and NPIs on COVID-19 spread, finding rapid testing to be highly effective in reducing infections during vaccination rollouts.

Contribution

It introduces a quantitative agent-based simulation model to assess policy effects on COVID-19 spread, accounting for seasonality and virus variants.

Findings

Rapid testing significantly reduces infection numbers.

Vaccination alone is less effective without testing.

Frequent large-scale testing can replace costly NPIs.

Abstract

In order to slow the spread of the CoViD-19 pandemic, governments around the world have enacted a wide set of policies limiting the transmission of the disease. Initially, these focused on non-pharmaceutical interventions; more recently, vaccinations and large-scale rapid testing have started to play a major role. The objective of this study is to explain the quantitative effects of these policies on determining the course of the pandemic, allowing for factors like seasonality or virus strains with different transmission profiles. To do so, the study develops an agent-based simulation model, which is estimated using data for the second and the third wave of the CoViD-19 pandemic in Germany. The paper finds that during a period where vaccination rates rose from 5% to 40%, large-scale rapid testing had the largest effect on reducing infection numbers. Frequent large-scale rapid testing should remain part of strategies to contain CoViD-19; it can substitute for many non-pharmaceutical interventions that come at a much larger cost to individuals, society, and the economy.