Matveeva Olga, Ogurtsov Aleksey Y, Shabalina Svetlana A
Sendai Viralytics LLC, Acton, MA 01720, USA.
National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894-6075, USA.
medRxiv. 2024 Aug 12:2024.01.21.24301582. doi: 10.1101/2024.01.21.24301582.
This study investigates factors influencing pandemic mortality rates across U.S. states during different waves of SARS-CoV-2 infection from February 2020 to April 2023, given that over one million people died from COVID-19 in the country.
We performed statistical analyses and used linear regression models to estimate age-adjusted and unadjusted excess mortality as functions of life expectancy, vaccination rates, and GDP per capita in U.S. states.
States with lower life expectancy and lower GDP per capita experienced significantly higher mortality rates during the pandemic, underscoring the critical role of underlying health conditions and healthcare infrastructure, as reflected in these factors. When categorizing states by vaccination rates, significant differences in GDP per capita and pre-pandemic life expectancy emerged between states with lower and higher vaccination rates, likely explaining mortality disparities before mass vaccination. During the Delta and Omicron BA.1 waves, when vaccines were widely available, the mortality gap widened, and states with lower vaccination rates experienced nearly double the mortality compared to states with higher vaccination rates (Odds Ratio 1.8, 95% CI 1.7-1.9, p < 0.01). This disparity disappeared during the later Omicron variants, likely because the levels of combined immunity from vaccination and widespread infection across state populations became comparable. We showed that vaccination rates were the only significant factor influencing age-adjusted mortality, highlighting the substantial impact of age-specific demographics on both life expectancy and GDP across states.
The study underscores the critical role of high vaccination rates in reducing excess deaths across all states, regardless of economic status. Vaccination rates proved more decisive than GDP per capita in reducing excess deaths. Additionally, states with lower pre-pandemic life expectancy faced greater challenges, reflecting the combined effects of healthcare quality, demographic variations, and social determinants of health. These findings call for comprehensive public health strategies that address both immediate interventions, like vaccination, and long-term improvements in healthcare infrastructure and social conditions.
鉴于美国有超过100万人死于新冠疫情，本研究调查了2020年2月至2023年4月期间不同波次严重急性呼吸综合征冠状病毒2（SARS-CoV-2）感染期间影响美国各州大流行死亡率的因素。
我们进行了统计分析，并使用线性回归模型来估计年龄调整和未调整的超额死亡率，将其作为美国各州预期寿命、疫苗接种率和人均国内生产总值（GDP）的函数。
预期寿命较低和人均GDP较低的州在疫情期间死亡率显著更高，这凸显了潜在健康状况和医疗基础设施的关键作用，这些因素反映了这一点。按疫苗接种率对各州进行分类时，疫苗接种率较低和较高的州之间在人均GDP和疫情前预期寿命方面出现了显著差异，这可能解释了大规模疫苗接种前的死亡率差异。在德尔塔和奥密克戎BA.1波期间，当疫苗广泛可用时，死亡率差距扩大，疫苗接种率较低的州的死亡率几乎是疫苗接种率较高的州的两倍（优势比1.8，95%置信区间1.7 - 1.9，p < 0.01）。这种差异在后来的奥密克戎变种期间消失了，可能是因为各州人群中疫苗接种和广泛感染产生的综合免疫水平变得相当。我们表明，疫苗接种率是影响年龄调整死亡率的唯一重要因素，突出了特定年龄人口结构对各州预期寿命和GDP的重大影响。
该研究强调了高疫苗接种率在降低所有州超额死亡方面的关键作用，无论经济状况如何。在降低超额死亡方面，疫苗接种率比人均GDP更具决定性。此外，疫情前预期寿命较低的州面临更大挑战，这反映了医疗质量、人口差异和健康的社会决定因素的综合影响。这些发现呼吁采取全面的公共卫生策略，既要应对像疫苗接种这样的即时干预措施，也要实现医疗基础设施和社会条件的长期改善。
