TY - JOUR
T1 - Temperature and Latitude Correlate with SARS-CoV-2 Epidemiological Variables but not with Genomic Change Worldwide
AU - Burra, Prakruthi
AU - Soto-Díaz, Katiria
AU - Chalen, Izan
AU - Gonzalez-Ricon, Rafael Jaime
AU - Istanto, Dave
AU - Caetano-Anollés, Gustavo
N1 - Funding Information:
This study began as a class research project in CPSC 567, a course in bioinformatics and systems biology taught by G.C.-A. at the University of Illinois in the spring of 2020. We thank Tre Tomaszewski for his input on the choice of genomic data and other members of the class who provided extensive feedback on the project. We also thank Herve Seligmann for sharing results prior to publication. Finally, we acknowledge with gratitude, the work of all researchers who obtained specimens, and generated and shared genetic sequence data on GISAID. COVID-19 research in the laboratory of G.C.-A is supported by the Office of Research and Office of International Programs in the College of Agricultural, Consumer and Environmental Sciences at the University of Illinois at Urbana-Champaign.
Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Office of Research and Office of International Programs, College of Agricultural, Consumer and Environmental Sciences at the University of Illinois at Urbana-Champaign.
PY - 2021/1/26
Y1 - 2021/1/26
N2 - The SARS-CoV-2 virus that causes the COVID-19 disease has spread quickly and massively around the entire globe, causing millions of confirmed cases and deaths worldwide. The disease poses a serious ongoing threat to public health. This study aims to understand the disease potential of the virus in different regions by studying how average spring temperature and its strong predictor, latitude, affect epidemiological variables such as disease incidence, mortality, recovery cases, active cases, testing rate, and hospitalization. We also seek to understand the association of temperature and geographic coordinates with viral genomics. Epidemiological data along with temperature, latitude, longitude, and preparedness index were collected for different countries and US states during the early stages of the pandemic. Our worldwide epidemiological analysis showed a significant correlation between temperature and incidence, mortality, recovery cases and active cases. The same tendency was found with latitude, but not with longitude. In the US, we observed no correlation between temperature or latitude and epidemiological variables. Interestingly, longitude was correlated with incidence, mortality, active cases, and hospitalization. An analysis of mutational change and mutational change per time in 55 453 aligned SARS-CoV-2 genome sequences revealed these parameters were uncorrelated with temperature and geographic coordinates. The epidemiological trends we observed worldwide suggest a seasonal effect for the disease that is not directly controlled by the genomic makeup of the virus. Future studies will need to determine if correlations are more likely the result of effects associated with the environment or the innate immunity of the host.
AB - The SARS-CoV-2 virus that causes the COVID-19 disease has spread quickly and massively around the entire globe, causing millions of confirmed cases and deaths worldwide. The disease poses a serious ongoing threat to public health. This study aims to understand the disease potential of the virus in different regions by studying how average spring temperature and its strong predictor, latitude, affect epidemiological variables such as disease incidence, mortality, recovery cases, active cases, testing rate, and hospitalization. We also seek to understand the association of temperature and geographic coordinates with viral genomics. Epidemiological data along with temperature, latitude, longitude, and preparedness index were collected for different countries and US states during the early stages of the pandemic. Our worldwide epidemiological analysis showed a significant correlation between temperature and incidence, mortality, recovery cases and active cases. The same tendency was found with latitude, but not with longitude. In the US, we observed no correlation between temperature or latitude and epidemiological variables. Interestingly, longitude was correlated with incidence, mortality, active cases, and hospitalization. An analysis of mutational change and mutational change per time in 55 453 aligned SARS-CoV-2 genome sequences revealed these parameters were uncorrelated with temperature and geographic coordinates. The epidemiological trends we observed worldwide suggest a seasonal effect for the disease that is not directly controlled by the genomic makeup of the virus. Future studies will need to determine if correlations are more likely the result of effects associated with the environment or the innate immunity of the host.
KW - SARS-CoV-2
KW - active cases
KW - testing rate
KW - hospitalization
KW - genome analysis
KW - mutation
KW - recovery patients
KW - mortality
KW - incidence
KW - COVID-19
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U2 - 10.1177/1176934321989695
DO - 10.1177/1176934321989695
M3 - Article
C2 - 33551640
SN - 1176-9343
VL - 17
JO - Evolutionary Bioinformatics
JF - Evolutionary Bioinformatics
M1 - 1176934321989695
ER -