Public health policy impact evaluation: A potential use case for longitudinal monitoring of viruses in wastewater at small geographic scales

Abstract

Public health policy impact evaluation is challenging to study because randomized controlled experiments are infeasible to conduct, and policy changes often coincide with non-policy events. Quasi-experiments do not use randomization and can provide useful knowledge for causal inference. Here we demonstrate how longitudinal wastewater monitoring of viruses at a small geographic scale may be used in a quasi-experimental design to evaluate the impact of COVID-19 public health policies on the spread of COVID-19 among a university population. We first evaluated the correlation between incident, reported COVID-19 cases and wastewater SARS-CoV-2 RNA concentrations and observed changes to the correlation over time, likely due to changes in testing requirements and testing options. Using a difference-in-differences approach, we then evaluated the association between university COVID-19 public health policy changes and levels of SARS-CoV-2 RNA concentrations in wastewater. We did not observe changes in SARS-CoV-2 RNA concentrations associated with most policy changes. Policy changes associated with a significant change in campus wastewater SARS-CoV-2 RNA concentrations included changes to face covering recommendations, indoor gathering bans, and routine surveillance testing requirements and availability.