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气象和人口因素对日本流感流行的影响:一项大型观测数据库研究。

Impact of meteorological and demographic factors on the influenza epidemic in Japan: a large observational database study.

机构信息

Data Science Department, Shionogi & Co., Ltd, Osaka, Japan.

Department of Respiratory Medicine, Nagasaki University Hospital, Nagasaki, Japan.

出版信息

Sci Rep. 2023 Aug 10;13(1):13000. doi: 10.1038/s41598-023-39617-1.

DOI:10.1038/s41598-023-39617-1
PMID:37563139
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10415347/
Abstract

Factors affecting the start date of the influenza epidemic season and total number of infected persons per 1,000,000 population in 47 prefectures of Japan were evaluated. This retrospective observational study (September 2014-August 2019; N = 472,740-883,804) evaluated data from a Japanese health insurance claims database. Single and multiple regression analyses evaluated the time to start of the epidemic or total infected persons per 1,000,000 population with time to absolute humidity (AH) or number of days with AH (≤ 5.5, ≤ 6.0, ≤ 6.5, and ≤ 7.0), total visitors (first epidemic month or per day), and total population. For the 2014/15, 2015/16, and 2016/17 seasons, a weak-to-moderate positive correlation (R: 0.042-0.417) was observed between time to start of the epidemic and time to first day with AH below the cutoff values. Except in the 2016/17 season (R: 0.089), a moderate correlation was reported between time to start of the epidemic and the total population (R: 0.212-0.401). For all seasons, multiple regression analysis showed negative R for time to start of the epidemic and total visitors and population density (positive for time to AH ≤ 7.0). The earlier the climate becomes suitable for virus transmission and the higher the human mobility (more visitors and higher population density), the earlier the epidemic season tends to begin.

摘要

评估了影响日本 47 个都道府县流感流行季起始日期和每 100 万人口感染人数的因素。本回顾性观察研究(2014 年 9 月至 2019 年 8 月;N=472740-883804)评估了来自日本健康保险索赔数据库的数据。单因素和多因素回归分析评估了流行季起始时间或每 100 万人口感染人数与绝对湿度(AH)时间(≤5.5、≤6.0、≤6.5 和≤7.0)、总访客(首个流行月或每日)和总人口的关系。对于 2014/15、2015/16 和 2016/17 三个流行季,流行季起始时间与 AH 首次低于临界值的时间之间呈弱至中度正相关(R:0.042-0.417)。除了 2016/17 流行季(R:0.089)外,流行季起始时间与总人口之间呈中度相关(R:0.212-0.401)。对于所有流行季,多因素回归分析显示流行季起始时间与总访客和人口密度呈负相关(与 AH≤7.0 时间呈正相关)。病毒传播的气候条件越早适宜,人类的流动性(访客越多、人口密度越高)越高,流行季越容易提前开始。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5a0/10415347/a7d2f86a4a1c/41598_2023_39617_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5a0/10415347/5814f6e5aa3c/41598_2023_39617_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5a0/10415347/6e6715b1b214/41598_2023_39617_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5a0/10415347/a7d2f86a4a1c/41598_2023_39617_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5a0/10415347/5814f6e5aa3c/41598_2023_39617_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5a0/10415347/6e6715b1b214/41598_2023_39617_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5a0/10415347/a7d2f86a4a1c/41598_2023_39617_Fig3_HTML.jpg

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