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10.1016/j.dsx.2020.09.002 http://scihub22266oqcxt.onion/10.1016/j.dsx.2020.09.002 32919321!7467899!32919321     free     free     free Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Diabetes+Metab+Syndr 2020 ; 14 (6): 1735-1742 Nephropedia Template TP {{tp|p=32919321|t=2020. A correlation study between meteorological parameters and COVID-19 pandemic in Mumbai, India |pdf=|usr=}}{{32919321}} gab.com Text A correlation study between meteorological parameters and COVID-19 pandemic in Mumbai, India JO: Diabetes Metab Syndr http://www.kidney.de/pget.php?&tw=1&pmid=32919321 #FOAvip BACKGROUND AND AIMS: Meteorological parameters play a major role in the transmission of infectious diseases such as COVID-19. In this study, we aim to analyze the correlation between meteorological parameters and COVID-19 pandemic in the financial capital of India, Mumbai. METHODS: In this research, we collected data from April 27 till July 25, 2020 (90 days). A Spearman rank correlation test along with two-tailed p test and an Artificial Neural Network (ANN) technique have been used to predict the associations of COVID-19 with meteorological parameters. RESULTS: A significant correlation of COVID-19 was found with temperature (T(min)), dew point (DP(max)), relative humidity (RH(max), RH(avg), RH(min)) and surface pressure (P(max), P(avg), P(min)). The parameters which showed significant correlation were then taken for the modeling and prediction of COVID-19 infections using Artificial Neural Network technique. CONCLUSIONS: It was found that the relative humidity and pressure parameters had the most influencing effect out of all other significant parameters (obtained from Spearman's method) on the active number of COVID-19 cases. The finding in this study might be useful for the public, local authorities, and the Ministry of Health, Govt. of India to combat COVID-19. Twit Text FOAVip A correlation study between meteorological parameters and COVID-19 pandemic in Mumbai, India ????Diabetes Metab Syndr http://www.kidney.de/pget.php?&tw=1&pmid=32919321 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32919321 #FOAvip English Wikipedia <ref>{{Cite pmid|32919321}}</ref> A correlation study between meteorological parameters and COVID-19 pandemic in Mumbai, India #MMPMID32919321 Kumar G; Kumar RR Diabetes Metab Syndr 2020[Nov]; 14 (6): 1735-1742 PMID32919321show ga BACKGROUND AND AIMS: Meteorological parameters play a major role in the transmission of infectious diseases such as COVID-19. In this study, we aim to analyze the correlation between meteorological parameters and COVID-19 pandemic in the financial capital of India, Mumbai. METHODS: In this research, we collected data from April 27 till July 25, 2020 (90 days). A Spearman rank correlation test along with two-tailed p test and an Artificial Neural Network (ANN) technique have been used to predict the associations of COVID-19 with meteorological parameters. RESULTS: A significant correlation of COVID-19 was found with temperature (T(min)), dew point (DP(max)), relative humidity (RH(max), RH(avg), RH(min)) and surface pressure (P(max), P(avg), P(min)). The parameters which showed significant correlation were then taken for the modeling and prediction of COVID-19 infections using Artificial Neural Network technique. CONCLUSIONS: It was found that the relative humidity and pressure parameters had the most influencing effect out of all other significant parameters (obtained from Spearman's method) on the active number of COVID-19 cases. The finding in this study might be useful for the public, local authorities, and the Ministry of Health, Govt. of India to combat COVID-19. |*Meteorological Concepts[MESH] |Atmospheric Pressure[MESH] |COVID-19/*epidemiology[MESH] |Humans[MESH] |Humidity[MESH] |India/epidemiology[MESH] |Neural Networks, Computer[MESH] |SARS-CoV-2[MESH] |Temperature[MESH]A correlation study between meteorological parameters and COVID-19 pan(epmc).pdf DeepDyve Pubget Overpricing