Abstract
Non-pharmaceutical interventions (NPIs) have been crucial in mitigating the COVID-19 pandemic, yet they've also heterogeneously disrupted production across sectors, highlighting socio-economic vulnerabilities. This study develops an ensemble model combining a Bayesian hierarchical model with supply chain dynamics to assess the direct and indirect impacts of three NPI themes—Gathering Restrictions, Mobility Restrictions, and Health Measures—on industrial output and carbon emissions in Beijing. The findings show that Health Measures enhanced local economic output by 1.12 %, yet also boosted regional carbon emissions by 6.15 %, primarily from the increased production in the Electric and Heat Power Production (EHP) sector, with a carbon intensity 1.96 times above the regional average. This emphasizes the urgent need for decarbonizing EHP to align health and environmental objectives in future pandemics. Furthermore, Mobility Restrictions had the most severe economic impact, 2.01 times greater than Gathering Restrictions, with Stationery Manufacturing being the most affected. Textile Manufacturing showed particular sensitivity to both Gathering Restrictions and Health Measures. These insights contribute to a more nuanced understanding of NPIs' impacts, supporting the development of balanced pandemic response strategies that consider economic, environmental, and health outcomes.
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