Moran Kelly R, Lopez Tammie, Del Valle Sara Y
Statistical Sciences Group, Los Alamos National Laboratory, Los Alamos, NM, USA.
Genomics and Bioanalytics Group, Los Alamos National Laboratory, Los Alamos, NM, USA.
BMC Glob Public Health. 2025 Mar 25;3(1):24. doi: 10.1186/s44263-025-00143-z.
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.
新冠疫情在全球造成的毁灭性影响强烈提醒人们，积极有效的疫情应对至关重要。疾病建模与预测是这一应对措施的关键，因为它们能实现前瞻性评估和战略规划。在新冠疫情应对期间，我们对来自14个国家的疾病建模人员及其所支持的对象进行了85次访谈，从而对面临的挑战、吸取的经验教训以及对未来疫情的准备情况进行了定性概述。受访者强调了预测中的几个关键挑战和考量因素，特别指出了人类行为和各种与数据相关的问题（包括数据可用性、质量和标准化）所带来的复杂性。他们强调了模型创建者、基于这些模型做出决策的人员以及普通公众之间有效沟通的重要性。此外，他们指出了应对全球公平性的必要性，讨论了集中式与分散式危机应对方式的优缺点，并强调了建立可持续准备措施的必要性。他们对未来疫情准备情况的看法不一，只有43%的受访者表示我们对未来疫情的准备更充分。根据访谈过程中获得的见解，我们最后提出了在成功应对疫情的背景下，建模可以而且应该呈现的样子。这些访谈及其综合分析为塑造未来对全球健康危机的应对和准备工作提供了关键视角。
