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10.3390/ijerph18084052 http://scihub22266oqcxt.onion/10.3390/ijerph18084052 33921381!8068915!33921381     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=33921381&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Int+J+Environ+Res+Public+Health 2021 ; 18 (8): ä Nephropedia Template TP {{tp|p=33921381|t=2021. The Impact of Temperature on the Risk of COVID-19: A Multinational Study |pdf=|usr=}}{{33921381}} gab.com Text The Impact of Temperature on the Risk of COVID-19: A Multinational Study JO: Int J Environ Res Public Health http://www.kidney.de/pget.php?&tw=1&pmid=33921381 #FOAvip The current understanding of ambient temperature and its link to the outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is unclear. The objective of this study was to explore the environmental and climatic risk factors for SARS-CoV-2. For this study, we analyzed the data at the beginning of the outbreak (from 20 January to 31 March 2020) to avoid the influence of preventive or control measures. We obtained the number of cases and deaths due to SARS-CoV-2, international tourism, population age, universal health coverage, regional factors, the SARS-CoV-2 testing rate, and population density of a country. A total of 154 countries were included in this study. There were high incidence rates and mortality risks in the countries that had an average ambient temperature between 0 and 10 degrees C. The adjusted incidence rate for temperatures between 0 and 10 degrees C was 2.91 (95% CI 2.87-2.95). We randomly divided the data into a training set (80% of data) for model derivation and a test set (20% of data) for validation. Using a random forest statistical model, the model had high accuracy for predicting the high epidemic status of a country (ROC = 95.5%, 95% CI 87.9-100.0%) in the test set. Population age, temperature, and international tourism were the most important factors affecting the risk of SARS-CoV-2 in a country. An understanding the determinants of the SARS-CoV-2 outbreak can help to design better strategies for disease control. This study highlights the need to consider thermal effect in the prevention of emerging infectious diseases. Twit Text FOAVip The Impact of Temperature on the Risk of COVID-19: A Multinational Study ????Int J Environ Res Public Health http://www.kidney.de/pget.php?&tw=1&pmid=33921381 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33921381 #FOAvip English Wikipedia <ref>{{Cite pmid|33921381}}</ref> The Impact of Temperature on the Risk of COVID-19: A Multinational Study #MMPMID33921381 Yang HY; Lee JKW Int J Environ Res Public Health 2021[Apr]; 18 (8): ä PMID33921381show ga The current understanding of ambient temperature and its link to the outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is unclear. The objective of this study was to explore the environmental and climatic risk factors for SARS-CoV-2. For this study, we analyzed the data at the beginning of the outbreak (from 20 January to 31 March 2020) to avoid the influence of preventive or control measures. We obtained the number of cases and deaths due to SARS-CoV-2, international tourism, population age, universal health coverage, regional factors, the SARS-CoV-2 testing rate, and population density of a country. A total of 154 countries were included in this study. There were high incidence rates and mortality risks in the countries that had an average ambient temperature between 0 and 10 degrees C. The adjusted incidence rate for temperatures between 0 and 10 degrees C was 2.91 (95% CI 2.87-2.95). We randomly divided the data into a training set (80% of data) for model derivation and a test set (20% of data) for validation. Using a random forest statistical model, the model had high accuracy for predicting the high epidemic status of a country (ROC = 95.5%, 95% CI 87.9-100.0%) in the test set. Population age, temperature, and international tourism were the most important factors affecting the risk of SARS-CoV-2 in a country. An understanding the determinants of the SARS-CoV-2 outbreak can help to design better strategies for disease control. This study highlights the need to consider thermal effect in the prevention of emerging infectious diseases. |*COVID-19[MESH] |COVID-19 Testing[MESH] |Humans[MESH] |Population Density[MESH] |SARS-CoV-2[MESH]The Impact of Temperature on the Risk of COVID-19: A Multinational Stu(epmc).pdf DeepDyve Pubget Overpricing