A general framework for optimising cost-effectiveness of pandemic response under partial intervention measures

Quang Dang Nguyen and Mikhail Prokopenko

Papers from arXiv.org

Abstract: The COVID-19 pandemic created enormous public health and socioeconomic challenges. The health effects of vaccination and non-pharmaceutical interventions (NPIs) were often contrasted with significant social and economic costs. We describe a general framework aimed to derive adaptive cost-effective interventions, adequate for both recent and emerging pandemic threats. We also quantify the net health benefits and propose a reinforcement learning approach to optimise adaptive NPIs. The approach utilises an agent-based model simulating pandemic responses in Australia, and accounts for a heterogeneous population with variable levels of compliance fluctuating over time and across individuals. Our analysis shows that a significant net health benefit may be attained by adaptive NPIs formed by partial social distancing measures, coupled with moderate levels of the society's willingness to pay for health gains (health losses averted). We demonstrate that a socially acceptable balance between health effects and incurred economic costs is achievable over a long term, despite possible early setbacks.

Date: 2022-05, Revised 2022-11
New Economics Papers: this item is included in nep-hea
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Published in Scientific Reports 12, 19482 (2022)

Downloads: (external link)
http://arxiv.org/pdf/2205.08996 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2205.08996

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().