Weather Parameters and COVID-19

Pahuja, Sourabh; Madan, Manu; Mittal, Saurabh; Pandey, Ravindra Mohan; Nilima, Nilima; Madan, Karan; Hadda, Vijay; Tiwari, Pawan; Guleria, Randeep

doi:10.1097/jom.0000000000002082

Cited by 18 publications

(14 citation statements)

References 8 publications

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“…Pan et al (2021) collect cases from 202 locations in 8 countries and conclude that weather conditions such as temperature, relative humidity, wind speed, and ultraviolet rays significantly did not correlate with the COVID-19 cases. Pahuja et al (2021) study the number of cases in New Delhi, India, and did not observe a correlation between the number of cases and humidity or wind speed neither.…”

Section: Literature Reviewmentioning

confidence: 78%

Do Weather Conditions Affect COVID-19 Epidemic? Evidence Based on Panel Data of Prefecture-level Administrative Regions in China

Lin

Wang

Huang

2021

Preprint

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Background: Similar to other infectious diseases, weather conditions may affect the COVID-19 epidemic through changes to transmission dynamics, host susceptibility, and virus survival in the environment. It’s critical to explore the relationship between weather variables and the spread of the COVID-19 for understanding seasonality and the possibility of future outbreaks, developing early warning systems, infection control methods, and public health measures. However, the influence of weather change on COVID-19 edidemic is still an emerging research field, and there is still relatively limited literature available.Objectives: Our study aims to explore the causal relationship between weather conditions and COVID-19 epidemic, the regional heterogeneity of the influence of weathner conditions in east-middle-west and coastal-inland, the moderating effect of diurnal temperature difference, public health measures, and public opinion on the influence of weather conditions on the epidemic to investigate the effects of these factors on the intensity of weather conditions.Methods: First, we theoretically explain the influence mechanism of weather conditions on the epidemic based on the epidemiological triangle model. Then, we collect COVID-19-related prefecture-daily panel data in mainland China from January 1, 2020, to February 19, apply two-way fixed effect model of multiple linear regression, and also take into account other influencing factors such as population movement, public health interventions of the local government, economic and social conditions, to explore the causal relationship between weather conditions and the COVID-19 epidemic.Results: It is found that first, there is a conditional negative linear relationship between the weather conditions and the epidemic. When the average temperature is greater than -7℃, there is a significant negative causal relationship between the average temperature and the growth rate of the confirmed cases. Similarly, when the relative humidity is greater than 46%, the increase in the relative humidity significantly contain the epidemic. However, when the average temperature is less than -7℃ or the relative humidity is less than 46%, the effect of weather conditions is not significant. Further, from the perspective of weather conditions, prefecture-level administrative regions such as Chifeng, Zhangjiakou, and Ulanqab are more conducive to the outbreak of the epidemic in winter. Then, weather conditions have a greater influence in the east than in the middle and western regions, and it is better in coastal region than in the inland. Finally, increasing diurnal temperature differences will improve the impact of weather conditions on the confirmed cases. In dry and cold regions, higher diurnal temperature differences will increase the risk of spread of the disease; Strict public health measures and good public opinion can mitigate the adverse effects of cold and dry weather on the spread of the epidemic.Discussion: In future research, it can adopt more detailed investigation methods. Under the legal framework of privacy protection, questionnaire surveys can be carried out with patients' consent to draw more accurate conclusions. At the same time, in terms of the mechanism of the role of weather variables, more in-depth interdisciplinary cooperation with epidemiologists is needed to study the specific impact of weather conditions on the survivability of the COVID-19 virus and the immunity of susceptible populations to obtain a clearer picture and compelling conclusions.

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Section: Literature Reviewmentioning

confidence: 78%

Do Weather Conditions Affect COVID-19 Epidemic? Evidence Based on Panel Data of Prefecture-level Administrative Regions in China

Lin

Wang

Huang

2021

Preprint

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“…In Beijing, Shanghai, and Guangzhou, the correlation between temperature and the number of positive cases was negative, while in Japan, it was positive. The study conducted by Pahuja et al [19] demonstrated a positive correlation between the wind speed and the COVID-19 case counts. In contrast, Coccia [20] showed that the high wind speed could reduce the number of COVID-19 cases.…”

Section: Introductionmentioning

confidence: 94%

Analyzing the Factors Affecting the COVID-19 Risk Level in the US Counties

Ziyadidegan¹,

Razavi²,

Pesarakli³

et al. 2021

Preprint

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The COVID-19 disease spreads swiftly, and nearly three months after the first positive case was confirmed in China, Coronavirus started to spread all over the United States. Some states and counties reported an extremely high number of positive cases and deaths, while some reported too few COVID-19 related cases and mortality. In this paper, the factors that could affect the transmission of COVID-19 and its risk level in different counties have been determined and analyzed. Using Pearson Correlation, K-means clustering, and several classification models, the most critical ones were determined. Results showed that mean temperature, percent of people below poverty, percent of adults with obesity, air pressure, percentage of rural areas, and percent of uninsured people in each county were the most significant and effective attributes.

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“…In Beijing, Shanghai, and Guangzhou, the correlation between temperature and the number of positive cases was negative, while in Japan, it was positive. The study conducted by Pahuja et al [24] demonstrated a positive correlation between the wind speed and the COVID-19 case counts. In contrast, Coccia [25] showed that the high wind speed could reduce the number of COVID-19 cases.…”

Section: Introductionmentioning

confidence: 94%

Factors affecting the COVID-19 risk in the US counties: an innovative approach by combining unsupervised and supervised learning

Ziyadidegan

Razavi

Pesarakli

et al. 2021

Preprint

View full text Add to dashboard Cite

The COVID-19 disease spreads swiftly, and nearly three months after the first positive case was confirmed in China, Coronavirus started to spread all over the United States. Some states and counties reported high number of positive cases and deaths, while some reported lower COVID-19 related cases and mortality. In this paper, the factors that could affect the risk of COVID-19 infection and mortality were analyzed in county level. An innovative method by using K-means clustering and several classification models is utilized to determine the most critical factors. Results showed that mean temperature, percent of people below poverty, percent of adults with obesity, air pressure, population density, wind speed, longitude, and percent of uninsured people were the most significant attributes.

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Weather Parameters and COVID-19

Cited by 18 publications

References 8 publications

Do Weather Conditions Affect COVID-19 Epidemic? Evidence Based on Panel Data of Prefecture-level Administrative Regions in China

Do Weather Conditions Affect COVID-19 Epidemic? Evidence Based on Panel Data of Prefecture-level Administrative Regions in China

Analyzing the Factors Affecting the COVID-19 Risk Level in the US Counties

Factors affecting the COVID-19 risk in the US counties: an innovative approach by combining unsupervised and supervised learning

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