Estimating the time-varying effectiveness of COVID-19 preparedness in WHO European Region: A biorisk-focused wavelength (BFW) model approach

IF 3.5 Q1 Social Sciences
Journal of Biosafety and Biosecurity Pub Date : 2026-03-01 Epub Date: 2026-03-09 DOI:10.1016/j.jobb.2026.02.001
Tevfik Bulut
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Abstract

This study analyses how the time-varying predictive power of national preparedness capacities over the impact of the coronavirus disease 2019 (COVID-19) pandemic has changed over time. Building on the ‘preparedness paradox’ in the literature, the hypothesis that preparedness is a dynamic process whose effectiveness varies across different stages of the pandemic, rather than remaining a static state, was tested. To this end, a repeated cross-sectional analysis covering the period from 2020 to 2024 was conducted on a fixed cohort of 34 countries in the World Health Organization (WHO) European Region. The study utilised a comprehensive dataset integrating COVID-19 incidence from Our World in Data, annual preparedness scores from the WHO e-State Parties’ Self-Assessment Annual Reporting portal, socio-economic resilience indicators from the United Nations Development Programme Human Development Reports and population density metrics from the United Nations Population Division. The impact of the pandemic was quantified using the epidemiological wavelength model and its associated derivative frameworks. The annual explanatory power (adjusted R2) of three frameworks was compared: a Baseline Model representing general socio-economic resilience (indexed by the Human Development Index) and two specialised Biorisk-Focused Wavelength (BFW) Models (Core and Extended), which isolate specific biosecurity capacities. The results demonstrated that the predictive power of preparedness varied significantly across pandemic stages. During the initial phase in 2020, the Core BFW model, which focuses on basic strategic biorisk capacities, was the most effective predictor (adjusted R2 = 11.2%, p = 0.030). In contrast, as the pandemic reached a mature phase in 2022, the biorisk models lost all explanatory power, while the Baseline Model of systemic resilience emerged as a robust predictor (adjusted R2 = 24.4%, p = 0.002). This trend persisted into the endemic phase of 2024, where systemic resilience maintained a significant, albeit weaker, association (p = 0.032). Out-of-sample validation confirmed these findings: the Core BFW Model showed the highest forecast accuracy in 2020, whereas the Baseline Model demonstrated superior performance during the chronic phase of 2022. These results suggest that while technical biosecurity is critical during an initial shock, its influence is eventually superseded by overall systemic resilience. Consequently, future pandemic preparedness strategies must focus not only on static technical checklists but also on holistic approaches that enhance a nation’s ability to adapt to prolonged crises.
估计世卫组织欧洲区域COVID-19防范的时变有效性:以生物风险为重点的波长(BFW)模型方法
本研究分析了国家防范能力对2019冠状病毒病(COVID-19)大流行影响的时变预测能力如何随时间变化。基于文献中的“防备悖论”,对防备是一个动态过程的假设进行了检验,该过程的有效性在大流行的不同阶段有所不同,而不是保持静止状态。为此,对世界卫生组织(世卫组织)欧洲区域34个国家的固定队列进行了2020年至2024年期间的反复横断面分析。该研究利用了一个综合数据集,整合了来自“我们的世界”数据中的COVID-19发病率、来自世卫组织电子缔约国自我评估年度报告门户网站的年度防范得分、来自联合国开发计划署人类发展报告的社会经济复原力指标和来自联合国人口司的人口密度指标。使用流行病学波长模型及其相关衍生框架对大流行的影响进行了量化。对三个框架的年度解释力(调整后的R2)进行了比较:代表一般社会经济恢复力的基线模型(以人类发展指数为索引)和两个专门的以生物风险为重点的波长(BFW)模型(核心和扩展),它们隔离了特定的生物安全能力。结果表明,在不同的大流行阶段,防范的预测能力差异很大。在2020年初始阶段,关注基本战略生物风险能力的Core BFW模型是最有效的预测因子(调整R2 = 11.2%, p = 0.030)。相比之下,随着大流行在2022年达到成熟阶段,生物风险模型失去了所有解释能力,而系统恢复力基线模型成为一个强大的预测因子(调整R2 = 24.4%, p = 0.002)。这一趋势一直持续到2024年的流行阶段,此时系统恢复力保持了显著的相关性,尽管关联性较弱(p = 0.032)。样本外验证证实了这些发现:核心BFW模型在2020年的预测准确性最高,而基线模型在2022年的慢性期表现优异。这些结果表明,虽然技术生物安全在最初的冲击中至关重要,但其影响最终将被整体系统弹性所取代。因此,未来的大流行防范战略不仅必须注重静态的技术清单,而且必须注重提高国家适应长期危机能力的整体办法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Biosafety and Biosecurity
Journal of Biosafety and Biosecurity Social Sciences-Linguistics and Language
CiteScore
6.00
自引率
0.00%
发文量
20
审稿时长
41 days
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