Meteorological factors, population immunity, and COVID-19 incidence: A global multi-city analysis.

IF 3.3 Q2 ENVIRONMENTAL SCIENCES
Environmental Epidemiology Pub Date : 2024-11-11 eCollection Date: 2024-12-01 DOI:10.1097/EE9.0000000000000338
Denise Feurer, Tim Riffe, Maxi Stella Kniffka, Enrique Acosta, Ben Armstrong, Malcolm Mistry, Rachel Lowe, Dominic Royé, Masahiro Hashizume, Lina Madaniyazi, Chris Fook Sheng Ng, Aurelio Tobias, Carmen Íñiguez, Ana Maria Vicedo-Cabrera, Martina S Ragettli, Eric Lavigne, Patricia Matus Correa, Nicolás Valdés Ortega, Jan Kyselý, Aleš Urban, Hans Orru, Ene Indermitte, Marek Maasikmets, Marco Dallavalle, Alexandra Schneider, Yasushi Honda, Barrak Alahmad, Antonella Zanobetti, Joel Schwartz, Gabriel Carrasco, Iulian Horia Holobâca, Ho Kim, Whanhee Lee, Michelle L Bell, Noah Scovronick, Fiorella Acquaotta, Micheline de Sousa Zanotti Stagliorio Coélho, Magali Hurtado Diaz, Eunice Elizabeth Félix Arellano, Paola Michelozzi, Massimo Stafoggia, Francesca de'Donato, Shilpa Rao, Francesco Di Ruscio, Xerxes Seposo, Yuming Guo, Shilu Tong, Pierre Masselot, Antonio Gasparrini, Francesco Sera
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引用次数: 0

Abstract

Objectives: While COVID-19 continues to challenge the world, meteorological variables are thought to impact COVID-19 transmission. Previous studies showed evidence of negative associations between high temperature and absolute humidity on COVID-19 transmission. Our research aims to fill the knowledge gap on the modifying effect of vaccination rates and strains on the weather-COVID-19 association.

Methods: Our study included COVID-19 data from 439 cities in 22 countries spanning 3 February 2020 - 31 August 2022 and meteorological variables (temperature, relative humidity, absolute humidity, solar radiation, and precipitation). We used a two-stage time-series design to assess the association between meteorological factors and COVID-19 incidence. For the exposure modeling, we used distributed lag nonlinear models with a lag of up to 14 days. Finally, we pooled the estimates using a random effect meta-analytic model and tested vaccination rates and dominant strains as possible effect modifiers.

Results: Our results showed an association between temperature and absolute humidity on COVID-19 transmission. At 5 °C, the relative risk of COVID-19 incidence is 1.22-fold higher compared to a reference level at 17 °C. Correlated with temperature, we observed an inverse association for absolute humidity. We observed a tendency of increased risk on days without precipitation, but no association for relative humidity and solar radiation. No interaction between vaccination rates or strains on the weather-COVID-19 association was observed.

Conclusions: This study strengthens previous evidence of a relationship of temperature and absolute humidity with COVID-19 incidence. Furthermore, no evidence was found that vaccinations and strains significantly modify the relationship between environmental factors and COVID-19 transmission.

气象因素、人口免疫力和 COVID-19 发病率:全球多城市分析。
目标:虽然 COVID-19 仍在挑战世界,但气象变量被认为会影响 COVID-19 的传播。以前的研究表明,高温和绝对湿度与 COVID-19 传播之间存在负相关。我们的研究旨在填补关于疫苗接种率和菌株对天气-COVID-19关联的调节作用的知识空白:我们的研究包括来自 22 个国家 439 个城市的 COVID-19 数据(时间跨度为 2020 年 2 月 3 日至 2022 年 8 月 31 日)和气象变量(温度、相对湿度、绝对湿度、太阳辐射和降水量)。我们采用两阶段时间序列设计来评估气象因素与 COVID-19 发病率之间的关联。在建立暴露模型时,我们使用了滞后期长达 14 天的分布式滞后非线性模型。最后,我们使用随机效应元分析模型对估计值进行了汇总,并将疫苗接种率和优势菌株作为可能的效应调节因子进行了测试:结果表明,温度和绝对湿度与 COVID-19 的传播有关。在 5 °C时,COVID-19发病率的相对风险是17 °C参考水平的1.22倍。与温度相关,我们观察到绝对湿度与温度呈反向关系。我们观察到在无降水的日子里风险有增加的趋势,但相对湿度和太阳辐射没有关联。没有观察到疫苗接种率或菌株与天气-COVID-19相关性之间的相互作用:这项研究加强了之前关于温度和绝对湿度与 COVID-19 发病率之间关系的证据。此外,没有证据表明接种疫苗和菌株会显著改变环境因素与 COVID-19 传播之间的关系。
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
Environmental Epidemiology
Environmental Epidemiology Medicine-Public Health, Environmental and Occupational Health
CiteScore
5.70
自引率
2.80%
发文量
71
审稿时长
25 weeks
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