The future of pandemic modeling in support of decision making: lessons learned from COVID-19

疫情建模在决策支持中的未来:从新冠肺炎疫情中汲取的经验教训

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Abstract

The devastating global impacts of the COVID-19 pandemic are a stark reminder of the need for proactive and effective pandemic response. Disease modeling and forecasting are key in this response, as they enable forward-looking assessment and strategic planning. Via 85 interviews spanning 14 countries with disease modelers and those they support, conducted amid the COVID-19 pandemic response, we offer a qualitative overview of challenges faced, lessons learned, and readiness for future pandemics. The interviewees highlighted several key challenges and considerations in forecasting, particularly emphasizing the complications introduced by human behavior and various data-related issues (including data availability, quality, and standardization). They underscored the importance of effective communication among those who create models, those who make decisions based on these models, and the general public. Additionally, they pointed out the necessity for addressing global equity, debated the merits of centralized versus decentralized responses to crises, and stressed the need for establishing measures for sustainable preparedness. Their verdicts on future pandemic readiness were mixed, with only 43% of respondents saying we are better prepared for a future pandemic. We conclude by providing our vision for how modeling can and should look in the context of a successful pandemic response, in light of the insights gleaned via the interview process. These interviews and their synthesis offer crucial perspectives to shape future responses and preparedness for global health crises.

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