Morgenstern Christian, Laydon Daniel J, Whittaker Charles, Mishra Swapnil, Haw David, Bhatt Samir, Ferguson Neil M
MRC Centre for Global Infectious Disease Analysis & WHO Collaborating Centre for Infectious Disease Modelling, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom.
University of Copenhagen, Copenhagen, Denmark.
PLoS One. 2024 Jun 13;19(6):e0301785. doi: 10.1371/journal.pone.0301785. eCollection 2024.
The COVID-19 pandemic has caused over 7.02 million deaths as of January 2024 and profoundly affected most countries' Gross Domestic Product (GDP). Here, we study the interaction of SARS-CoV-2 transmission, mortality, and economic output between January 2020 and December 2022 across 25 European countries.
We use a Bayesian mixed effects model with auto-regressive terms to estimate the temporal relationships between disease transmission, excess deaths, changes in economic output, transit mobility and non-pharmaceutical interventions (NPIs) across countries.
Disease transmission intensity (logRt) decreases GDP and increases excess deaths, where the latter association is longer-lasting. Changes in GDP as well as prior week transmission intensity are both negatively associated with each other (-0.241, 95% CrI: -0.295 - -0.189). We find evidence of risk-averse behaviour, as changes in transit and prior week transmission intensity are negatively associated (-0.055, 95% CrI: -0.074 to -0.036). Our results highlight a complex cost-benefit trade-off from individual NPIs. For example, banning international travel is associated with both increases in GDP (0.014, 0.002-0.025) and decreases in excess deaths (-0.014, 95% CrI: -0.028 - -0.001). Country-specific random effects, such as the poverty rate, are positively associated with excess deaths while the UN government effectiveness index is negatively associated with excess deaths.
The interplay between transmission intensity, excess deaths, population mobility and economic output is highly complex, and none of these factors can be considered in isolation. Our results reinforce the intuitive idea that significant economic activity arises from diverse person-to-person interactions. Our analysis quantifies and highlights that the impact of disease on a given country is complex and multifaceted. Long-term economic impairments are not fully captured by our model, as well as long-term disease effects (Long COVID).
截至2024年1月，新冠疫情已导致超过702万人死亡，并对大多数国家的国内生产总值（GDP）产生了深远影响。在此，我们研究了2020年1月至2022年12月期间25个欧洲国家新冠病毒传播、死亡率和经济产出之间的相互作用。
我们使用带有自回归项的贝叶斯混合效应模型来估计各国疾病传播、超额死亡、经济产出变化、交通流动性和非药物干预（NPIs）之间的时间关系。
疾病传播强度（logRt）会降低GDP并增加超额死亡，且后一种关联持续时间更长。GDP变化与前一周的传播强度呈负相关（-0.241，95%可信区间：-0.295至-0.189）。我们发现了风险规避行为的证据，因为交通变化与前一周的传播强度呈负相关（-0.055，95%可信区间：-0.074至-0.036）。我们的结果凸显了个体非药物干预措施复杂的成本效益权衡。例如，禁止国际旅行与GDP增长（0.014，0.002 - 0.025）和超额死亡减少（-0.014，95%可信区间：-0.028至-0.001）都有关联。特定国家的随机效应，如贫困率，与超额死亡呈正相关，而联合国政府效能指数与超额死亡呈负相关。
传播强度、超额死亡、人口流动性和经济产出之间的相互作用非常复杂，这些因素都不能孤立地考虑。我们的结果强化了一个直观的观点，即重大经济活动源于多样化的人际互动。我们的分析量化并突出表明，疾病对特定国家的影响是复杂多面的。我们的模型没有完全捕捉到长期经济损害以及长期疾病影响（长期新冠）。
