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新冠病毒传播率的不可预测、违反直觉的地理气候和人口统计学关联

Unpredictable, Counter-Intuitive Geoclimatic and Demographic Correlations of COVID-19 Spread Rates.

作者信息

Seligmann Hervé, Vuillerme Nicolas, Demongeot Jacques

机构信息

Laboratory AGEIS EA 7407, Team Tools for e-Gnosis Medical & Labcom CNRS/UGA/OrangeLabs Telecom4Health, Faculty of Medicine, University Grenoble Alpes (UGA), 38700 La Tronche, France.

The National Natural History Collections, The Hebrew University of Jerusalem, Jerusalem 91404, Israel.

出版信息

Biology (Basel). 2021 Jul 5;10(7):623. doi: 10.3390/biology10070623.

DOI:10.3390/biology10070623
PMID:34356478
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8301123/
Abstract

We present spread parameters for first and second waves of the COVID-19 pandemic for USA states, and for consecutive nonoverlapping periods of 20 days for the USA and 51 countries across the globe. We studied spread rates in the USA states and 51 countries, and analyzed associations between spread rates at different periods, and with temperature, elevation, population density and age. USA first/second wave spread rates increase/decrease with population density, and are uncorrelated with temperature and median population age. Spread rates are systematically inversely proportional to those estimated 80-100 days later. Ascending/descending phases of the same wave only partially explain this. Directions of correlations with factors such as temperature and median age flip. Changes in environmental trends of the COVID-19 pandemic remain unpredictable; predictions based on classical epidemiological knowledge are highly uncertain. Negative associations between population density and spread rates, observed in independent samples and at different periods, are most surprising. We suggest that systematic negative associations between spread rates 80-100 days apart could result from confinements selecting for greater contagiousness, a potential double-edged sword effect of confinements.

摘要

我们给出了美国各州以及美国和全球51个国家在新冠疫情第一波和第二波期间的传播参数,以及美国连续20天不重叠的时间段和全球51个国家连续20天不重叠的时间段的传播参数。我们研究了美国各州和51个国家的传播率,并分析了不同时期传播率之间的关联,以及传播率与温度、海拔、人口密度和年龄之间的关联。美国第一波/第二波传播率随人口密度增加/降低,且与温度和人口年龄中位数无关。传播率与80 - 100天后估计的传播率呈系统的反比关系。同一波的上升/下降阶段只能部分解释这一现象。与温度和年龄中位数等因素的相关方向发生了翻转。新冠疫情环境趋势的变化仍然不可预测;基于经典流行病学知识的预测具有高度不确定性。在独立样本和不同时期观察到的人口密度与传播率之间的负相关最为惊人。我们认为,相隔80 - 100天的传播率之间的系统性负相关可能是由于隔离措施选择了更强的传染性,这是隔离措施潜在的双刃剑效应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b4d/8301123/29fdd851f9af/biology-10-00623-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b4d/8301123/84214264defa/biology-10-00623-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b4d/8301123/18c0a98a2e2e/biology-10-00623-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b4d/8301123/70defded0124/biology-10-00623-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b4d/8301123/29fdd851f9af/biology-10-00623-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b4d/8301123/84214264defa/biology-10-00623-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b4d/8301123/18c0a98a2e2e/biology-10-00623-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b4d/8301123/70defded0124/biology-10-00623-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b4d/8301123/29fdd851f9af/biology-10-00623-g004.jpg

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