Evidence map›Paper›PMID 34306336›Full record

ArticleAmerican journal of translational research2021

Association of temperature and relative humidity with the growth rate of the coronavirus disease 2019 epidemic.

Lei Qin, Qiang Sun, Jiani Shao, Yang Chen, Xiaomei Zhang, Jian Li, Mingchih Chen, Ben-Chang Shia, Szu-Yuan Wu

Abstract read
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Article in American journal of translational research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Lei QinSchool of Statistics, University of International Business and Economics Beijing, China.
Qiang SunSchool of Statistics, University of International Business and Economics Beijing, China.
Jiani ShaoSchool of International Education, University of International Business and Economics Beijing, China.
Yang ChenSchool of Statistics, University of International Business and Economics Beijing, China.
Xiaomei ZhangSchool of Statistics, University of International Business and Economics Beijing, China.
Jian LiGraduate Institute of Business Administration, College of Management, Fu Jen Catholic University New Taipei, Taiwan.
Mingchih ChenGraduate Institute of Business Administration, College of Management, Fu Jen Catholic University New Taipei, Taiwan.
Ben-Chang ShiaGraduate Institute of Business Administration, College of Management, Fu Jen Catholic University New Taipei, Taiwan.
Szu-Yuan WuGraduate Institute of Business Administration, College of Management, Fu Jen Catholic University New Taipei, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The effects of temperature and relative humidity on the growth of coronavirus disease 2019 (COVID-19) remain unclear. Data on the COVID-19 epidemic that were analyzed in this study were obtained from the official websites of the National Health Commission of China and the Health Commissions of 31 provinces in China. From January 26 to February 25, 2020, the cumulative number of confirmed COVID-19 cases in each region was counted daily using data from our database. Curve fitting of daily scatter plots of the relationship between epidemic growth rate (GR) with average temperature (AT) and average relative humidity (ARH) was conducted using the loess method. The heterogeneity across days and provinces was calculated to assess the necessity of using a longitudinal model. Fixed-effect models with polynomial terms were developed to quantify the relationship between variations in the GR and AT or ARH. An increased AT markedly reduced the GR when the AT was lower than -5°C, the GR was moderately reduced when the AT ranged from -5°C to 15°C, and the GR increased when the AT exceeded 15°C. ARH increased the GR when it was less than 72% and reduced the GR when it exceeded 72%. The temperature and relative humidity curves were not linearly associated with the GR of COVID-19. The GR was moderately reduced when the AT ranged from -5°C to 15°C. When the AT was lower or higher than -5°C to 15°C, the GR of COVID-19 increased. An increased ARH increased the GR when the ARH was lower than 72% and reduced the GR when the ARH exceeded 72%.

Indexed as

COVID-19relative humiditytemperature

Identifiers

PMID34306336
PMCPMC8290681

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.