This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research Article
Aldo Ummarino
Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini, 4 – 20090 - Pieve Emanuele (MI) - Italy
Corresponding Author
ORCiD: https://orcid.org/0000-0001-6247-5392
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Declarations:
Declarations
- The author has confirmed that a statement listing potential conflicts of interest or lack thereof is included in the text.
Climate seems to influence the spread of SARS-CoV-2, but the findings of the studies performed so far are conflicting. To overcome these issues, we performed a global scale study considering 134,871 virologic-climatic-demographic data (209 countries, first 16 weeks of the pandemic). To analyze the relation between Covid-19, population density, and climate, a theoretical path diagram was hypothesized and tested using Structural Equation Modeling (SEM), a powerful statistical technique for the evaluation of causal assumptions. The results of the analysis showed that both climate and population density significantly influence the spread of Covid-19 (p<0.001 and p<0.01, respectively). Overall, climate outweighs population density (b-incidence=0.18, b-prevalence=0.11 versus b-incidence=0.04, b-prevalence=0.05). Among the climatic factors, irradiation plays the most relevant role, with a factor-loading of -0.77, followed by temperature (-0.56), humidity (0.52), precipitation (0.44), and pressure (0.073); for all p<0.001. An interesting outcome was the value of residual variance (ε-incidence=0.97, ε-prevalence=0.98) suggesting that other factors influence the transmission of the infection. In conclusion, this study demonstrates that climatic factors significantly influence the spread of SARS-CoV-2. However, demographic factors, together with other determinants, can affect transmission, and their influence may overcome the protective effect of climate, where favourable.
Keywords
Covid-19, SARS-CoV-2, structural equation modeling, climate, solar irradiation, temperature, humidity
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- SupplementaryTableS1.xlsx
Original data analyzed
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This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research Article
Aldo Ummarino
Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini, 4 – 20090 - Pieve Emanuele (MI) - Italy
Corresponding Author
ORCiD: https://orcid.org/0000-0001-6247-5392
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 29 Sep, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Declarations:
Declarations
- The author has confirmed that a statement listing potential conflicts of interest or lack thereof is included in the text.
Climate seems to influence the spread of SARS-CoV-2, but the findings of the studies performed so far are conflicting. To overcome these issues, we performed a global scale study considering 134,871 virologic-climatic-demographic data (209 countries, first 16 weeks of the pandemic). To analyze the relation between Covid-19, population density, and climate, a theoretical path diagram was hypothesized and tested using Structural Equation Modeling (SEM), a powerful statistical technique for the evaluation of causal assumptions. The results of the analysis showed that both climate and population density significantly influence the spread of Covid-19 (p<0.001 and p<0.01, respectively). Overall, climate outweighs population density (b-incidence=0.18, b-prevalence=0.11 versus b-incidence=0.04, b-prevalence=0.05). Among the climatic factors, irradiation plays the most relevant role, with a factor-loading of -0.77, followed by temperature (-0.56), humidity (0.52), precipitation (0.44), and pressure (0.073); for all p<0.001. An interesting outcome was the value of residual variance (ε-incidence=0.97, ε-prevalence=0.98) suggesting that other factors influence the transmission of the infection. In conclusion, this study demonstrates that climatic factors significantly influence the spread of SARS-CoV-2. However, demographic factors, together with other determinants, can affect transmission, and their influence may overcome the protective effect of climate, where favourable.
Figure 1
Figure 2
This is a list of supplementary files associated with this preprint. Click to download.
- SupplementaryTableS1.xlsx
Original data analyzed
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