BACKGROUND: This study aimed to compare the cost-effectiveness of coronavirus disease 2019 (COVID-19) mass testing, carried out in November 2020 in the Italian Bolzano/Südtirol province, to scenarios without mass testing in terms of hospitalizations averted and quality-adjusted life-year (QALYs) saved.
METHODS: We applied branching processes to estimate the effective reproduction number (Rt) and model scenarios with and without mass testing, assuming Rt = 0.9 and Rt = 0.95. We applied a bottom-up approach to estimate the costs of mass testing, with a mixture of bottom-up and top-down methodologies to estimate hospitalizations averted and incremental costs in case of non-intervention. Lastly, we estimated the incremental cost-effectiveness ratio (ICER), denoted by screening and related social costs, and hospitalization costs averted per outcome derived, hospitalizations averted and QALYs saved.
RESULTS: The ICERs per QALY were €24 249 under Rt = 0.9 and €4604 under Rt = 0.95, considering the official and estimated data on disease spread. The cost-effectiveness acceptability curves show that for the Rt = 0.9 scenario, at the maximum threshold willingness to pay the value of €40 000, mass testing has an 80% probability of being cost-effective compared to no mass testing. Under the worst scenario (Rt = 0.95), at the willingness to pay threshold, mass testing has an almost 100% probability of being cost-effective.
CONCLUSIONS: We provide evidence on the cost-effectiveness and potential impact of mass COVID-19 testing on a local healthcare system and community. Although the intervention is shown to be cost-effective, we believe the initiative should be carried out when there is initial rapid local disease transmission with a high Rt, as shown in our model.
