Statistical analysis of the impact of environmental temperature on the exponential growth rate of cases infected by COVID-19

Livadiotis, G.

doi:10.1371/journal.pone.0233875

Cited by 60 publications

(60 citation statements)

References 24 publications

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“…Most studies (33 out of 61) suggest a negative correlation between COVID-19 and temperature. A negative correlation was found in worldwide studies (Arumugam et al, 2020;Caspi et al, 2020;Chiyomaru and Takemoto, 2020;Notari, 2020;Pirouz et al, 2020;Sajadi et al, 2020;X Wu et al, 2020;Yu, 2020), in California (Gupta and Gupta, 2020), Japan (Ujiie et al, 2020), Ghana (Abdul et al, 2020), Spain (Abdollahi and Rahbaralam, 2020;Tobías and Molina, 2020), Italy (Livadiotis, 2020) and in China (Oliveiros et al, 2020;Qi et al, 2020;Shi et al, 2020;Sil and Kumar, 2020). However, other studies came to the opposite conclusion (6 out of 61): a positive correlation between COVID-19 and temperature in Jakarta (Tosepu et al, 2020) and New York (Bashir et al, 2020), or no association (9 out of 61) in countries such as Spain (Briz-Redón and Serrano-Aroca, 2020), Iran (Ahmadi et al, 2020;Jahangiri et al, 2020), Nigeria (Taiwo and Fashola, 2020) and in a worldwide study (Jamil et al, 2020).…”

Section: Findings 31 Meteorological Variablesmentioning

confidence: 89%

The effect of climate on the spread of the COVID-19 pandemic: A review of findings, and statistical and modelling techniques

Briz‐Redón¹,

Serrano‐Aroca

2020

Progress in Physical Geography: Earth and Environment

136

147

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The new SARS-CoV-2 coronavirus has spread rapidly around the world since it was first reported in humans in Wuhan, China, in December 2019 after being contracted from a zoonotic source. This new virus produces the so-called coronavirus 2019 or COVID-19. Although several studies have supported the epidemiological hypothesis that weather patterns may affect the survival and spread of droplet-mediated viral diseases, the most recent have concluded that summer weather may offer partial or no relief of the COVID-19 pandemic to some regions of the world. Some of these studies have considered only meteorological variables, while others have included non-meteorological factors. The statistical and modelling techniques considered in this research line have included correlation analyses, generalized linear models, generalized additive models, differential equations, or spatio-temporal models, among others. In this paper we provide a systematic review of the recent literature on the effects of climate on COVID-19’s global expansion. The review focuses on both the findings and the statistical and modelling techniques used. The disparate findings reported seem to indicate that the estimated impact of hot weather on the transmission risk is not large enough to control the pandemic, although the wide range of statistical and modelling approaches considered may have partly contributed to the inconsistency of the findings. In this regard, we highlight the importance of being aware of the limitations of the different mathematical approaches, the influence of choosing geographical units and the need to analyse COVID-19 data with great caution. The review seems to indicate that governments should remain vigilant and maintain the restrictions in force against the pandemic rather than assume that warm weather and ultraviolet exposure will naturally reduce COVID-19 transmission.

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Section: Findings 31 Meteorological Variablesmentioning

confidence: 89%

The effect of climate on the spread of the COVID-19 pandemic: A review of findings, and statistical and modelling techniques

Briz‐Redón¹,

Serrano‐Aroca

2020

Progress in Physical Geography: Earth and Environment

136

147

View full text Add to dashboard Cite

show abstract

“…35 )). Applying an exponential growth rate is illuminating from an epidemiological perspective, because COVID-19 would initially spread exponentially in the scenario of a disease spreading within a closed, homogeneous population without interventions 29,35,44,45 . Importantly, when doing so, we observed the same mediation results as above: P < 0.001 (Supplementary Table 39).…”

Section: Linking Partisanship and Physical Distancing To Covid-19mentioning

confidence: 99%

Partisan differences in physical distancing are linked to health outcomes during the COVID-19 pandemic

et al. 2020

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Numerous polls suggest that COVID-19 is a profoundly partisan issue in the United States. Using the geotracking data of 15 million smartphones per day, we found that US counties that voted for Donald Trump (Republican) over Hillary Clinton (Democrat) in the 2016 presidential election exhibited 14% less physical distancing between March and May 2020. Partisanship was more strongly associated with physical distancing than numerous other factors, including counties' COVID-19 cases, population density, median income, and racial and age demographics. Contrary to our predictions, the observed partisan gap strengthened over time and remained when stay-at-home orders were active. Additionally, county-level consumption of conservative media (Fox News) was related to reduced physical distancing. Finally, the observed partisan differences in distancing were associated with subsequently higher COVID-19 infection and fatality growth rates in pro-Trump counties. Taken together, these data suggest that US citizens' responses to COVID-19 are subject to a deep-and consequential-partisan divide.

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“…Applying an exponential growth rate is illuminating from an epidemiological perspective, as COVID-19 would initially spread exponentially in the scenario of a disease spreading within a closed, homogeneous population without interventions 29,35,44,45 . Importantly, when doing so, we observed the same mediation results as above, ps < .001 (Supplementary Table 39).…”

Section: Linking Partisanship and Physical Distancing To Covid-19 Infmentioning

confidence: 99%

Partisan differences in physical distancing are linked to health outcomes during the COVID-19 pandemic.

Gollwitzer¹,

Martel²,

Brady³

et al. 2020

Preprint

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Few things bind disparate groups together like a common challenge. Yet, numerous polls suggest that the current COVID-19 pandemic in the U.S. is subject to a partisan divide. Using the geotracking data of 15 million smartphones per day, we show that counties that voted for Donald Trump over Hillary Clinton in 2016 exhibited 14% less physical distancing between March and May, 2020. Partisanship was a stronger predictor of physical distancing than numerous other factors, including counties’ median income, COVID-19 cases, and racial and age make-up. Contrary to our predictions, this finding strengthened over time and remained when stay-at-home orders were active. Additionally, counties’ consumption of conservative media (Fox News) predicted reduced physical distancing. Finally, reduced physical distancing in pro-Trump counties was associated with subsequently higher COVID-19 infection and fatality growth rates. Taken together, these data suggest that U.S. responses towards COVID-19 are subject to a deep partisan divide.

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Statistical analysis of the impact of environmental temperature on the exponential growth rate of cases infected by COVID-19

Cited by 60 publications

References 24 publications

The effect of climate on the spread of the COVID-19 pandemic: A review of findings, and statistical and modelling techniques

The effect of climate on the spread of the COVID-19 pandemic: A review of findings, and statistical and modelling techniques

Partisan differences in physical distancing are linked to health outcomes during the COVID-19 pandemic

Partisan differences in physical distancing are linked to health outcomes during the COVID-19 pandemic.

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