Do Humidity and Temperature Impact the Spread of the Novel Coronavirus?

Yuan, Shu; Jiang, Si‐Cong; Li, Zi-Lin

doi:10.3389/fpubh.2020.00240

Cited by 60 publications

(56 citation statements)

References 24 publications

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“…Bu et al ( 2020 ) have concluded that a temperature range of 13–19 °C and humidity of 50–80% are suitable for the survival and transmission of COVID-19. Yuan et al ( 2020 ) have presented a comprehensive review on the impact of temperature and humidity on the transmission of COVID-19. Ujiie et al ( 2020 ) have observed higher infectivity of COVID-19 pandemic patients during the winter season in Japan.…”

Section: Resultsmentioning

confidence: 99%

Association between climatic variables and COVID-19 pandemic in National Capital Territory of Delhi, India

Singh

Bhardwaj²,

Kumar³

2020

Environ Dev Sustain

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Globally, since the end of December 2019, coronavirus disease (COVID-19) has been recognized as a severe infectious disease. Therefore, this study has been attempted to examine the linkage between climatic variables and COVID-19 particularly in National Capital Territory of Delhi (NCT of Delhi), India. For this, daily data of COVID-19 has been used for the period March 14 to June 11, 2020, (90 days). Eight climatic variables such as maximum, minimum and mean temperature (°C), relative humidity (%), bright sunshine hours, wind speed (km/h), evaporation (mm), and rainfall (mm) have been analyzed in relation to COVID-19. To study the relationship among different climatic variables and COVID-19 spread, Karl Pearson's correlation analysis has been performed. The Mann-Kendall method and Sen's slope estimator have been used to detect the direction and magnitude of COVID-19 trends, respectively. The results have shown that out of eight selected climatic variables, six variables, viz. maximum temperature, minimum temperature, mean temperature, relative humidity, evaporation, and wind speed are positively associated with coronavirus disease cases (statistically significant at 95 and 99% confidence levels). No association of coronavirus disease has been found with bright sunshine hours and rainfall. Besides, COVID-19 cases and deaths have shown increasing trends, significant at 99% confidence level. The results of this study suggest that climatic conditions in NCT of Delhi are favorable for COVID-19 and the disease may spread further with the increasing temperature, relative humidity, evaporation and wind speed. This is the only study which has presented the analysis of COVID-19 spread in relation to several climatic variables for the most densely populated and rapidly growing city of India. Thus, considering the results obtained, effective policies and actions are necessary especially by identifying the areas where the spread rate is increasing rapidly in this megacity. The prevention and protection measures should be adopted aiming at to reduce the further transmission of disease in the city.

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Section: Resultsmentioning

confidence: 99%

Association between climatic variables and COVID-19 pandemic in National Capital Territory of Delhi, India

Singh

Bhardwaj²,

Kumar³

2020

Environ Dev Sustain

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“…Other aspects influencing droplet or airborne transmission are temperature and humidity because they correlate with the spread of and deaths associated with COVID-19 [98][99][100]. In China, the number of confirmed cases increased with higher temperature and higher humidity in most of the provinces [101,102].…”

Section: J O U R N a L P R E -P R O O Fmentioning

confidence: 99%

Potential sources, modes of transmission and effectiveness of prevention measures against SARS-CoV-2

Kampf

Brüggemann

Kaba

et al. 2020

Journal of Hospital Infection

127

121

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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“…Since the beginning of the outbreak, a number of studies have investigated the relationship between climate and COVID-19 transmission by examining epidemiological data from different regions worldwide. As highlighted by Yuan et al (2020), these studies found contradictory results, even when analysing similar data for similar regions. In the case of Italy, a preliminary analysis using moving averages from five provinces showed a negative association between relative humidity and daily incidence, but a positive association between daily temperature and daily incidence in three of five provinces (Passerini et al, 2020).…”

Section: Introductionmentioning

confidence: 91%

Delayed positive association between air temperature and covid-19 incidence in Italy

Fong¹,

Goodson²,

Smith³

2020

Preprint

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The association between air temperature and covid-19 incidence is unclear, particularly regarding lag effects. Here we address this research gap using high resolution data from Italy. We obtained daily covid-19 cases, populations at risk, and mean daily air temperature from 97 Italian cities for the period 24 February through 21 September 2020. We fitted a mixed-effects distributed lag non-linear model, presenting the effects as relative risks (RR) and cumulative relative risks (RRcum).Negative increments in mean daily temperature produced approximately inverted U- shaped lag-responses, though for large positive increments in temperature, the peak RR occurred at the maximal lag of 14 days. The temperature exposure response curves generally showed an increased RR with increasing temperature, though the shape varied according to the lag period. Positive and negative increments in temperature caused increases and decreases in the RRcum respectively, though the plateau effect for negative increments was not observed above small positive increments in temperature.We postulate that latent variables correlated with temperature, such as frequency and duration of social activities, are the underlying cause of our observed trends. Nonetheless, our statistical model can be utilised to forecast cumulative covid-19 incidence rates assuming specified air temperature increments at the city level.

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Do Humidity and Temperature Impact the Spread of the Novel Coronavirus?

Cited by 60 publications

References 24 publications

Association between climatic variables and COVID-19 pandemic in National Capital Territory of Delhi, India

Association between climatic variables and COVID-19 pandemic in National Capital Territory of Delhi, India

Potential sources, modes of transmission and effectiveness of prevention measures against SARS-CoV-2

Delayed positive association between air temperature and covid-19 incidence in Italy

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