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Integrating #macroeconomic and public #health impacts in #social planning #policies for #pandemic response

Abstract

Infectious disease outbreaks with pandemic potential present challenges for mitigation and control. Policymakers make decisions to reduce disease-associated morbidity and mortality while also minimizing socioeconomic costs of control. Despite ongoing efforts and widespread recognition of the challenge, there remains a paucity of decision tool frameworks that integrate epidemic and macroeconomic dynamics. Here, we propose and analyze an econo-epidemic model to identify robust planning policies to limit epidemic impacts while maintaining economic activity. The model couples epidemic dynamics, behavioral change, economic activity, and feasible policy plans informed by respiratory disease threats of pandemic concern. We compare alternative fixed, dynamic open-loop optimal control, and feedback control policies via a welfare loss framework. We find that open loop policies that adjust employment dynamically while maintaining a flat epidemic curve in advance of the uncertain arrival of population-scale vaccination outperform fixed employment reduction policies. However, open loop policies are highly sensitive to misestimation of parameters associated with intrinsic disease strength and feedback between economic activity and transmission, leading to potentially significant increases in welfare loss. In contrast, feedback control policies guided by open loop dynamical targets of the time-varying reproduction number perform near-optimally when parameters are well-estimated, while significantly outperforming open loop policies whenever disease features and population-scale behavioral response are misestimated -- as they inevitably are. These findings present a template for integrating principled economic models with epidemic scenarios to identify vulnerabilities in policy responses and expand policy options in preparation for future pandemics.

Source: MedRxIV, https://www.medrxiv.org/content/10.1101/2025.01.21.25320900v1

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