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10.1002/jmv.25885 http://scihub22266oqcxt.onion/10.1002/jmv.25885 32329522!7264574!32329522     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Med+Virol 2020 ; 92 (7): 868-882 Nephropedia Template TP {{tp|p=32329522|t=2020. Understanding epidemic data and statistics: A case study of COVID-19 |pdf=|usr=}}{{32329522}} gab.com Text Understanding epidemic data and statistics: A case study of COVID-19 JO: J Med Virol http://www.kidney.de/pget.php?&tw=1&pmid=32329522 #FOAvip The 2019 novel-coronavirus (COVID-19) has affected 181 countries with approximately 1197405 confirmed cases (by 5th April). Understanding the transmission dynamics of the infection in each country which got affected on a daily basis and evaluating the effectiveness of control policies are critical for our further actions. To date, the statistics of COVID-19 reported cases show that more than 80% of infected are mild cases of disease, around 14% of infected have severe complications, and about 5% are categorized as critical disease victims. Today's report (5th April 2020; daily updates in the prepared website) shows that the confirmed cases of COVID-19 in the United States, Spain, Italy, and Germany are 308850, 126168, 124632, and 96092, respectively. Calculating the total case fatality rate (CFR) of Italy (4th April 2020), about 13.3% of confirmed cases have passed away. Compared with South Korea's rate of 1.8% (seven times lower than Italy) and China's 4% (69% lower than Italy), the CFR of Italy is too high. Some effective policies that yielded significant changes in the trend of cases were the lockdown policy in China, Italy, and Spain (the effect observed after some days), the shutdown of all nonessential companies in Hubei (the effect observed after 5 days), combined policy in South Korea, and reducing working hours in Iran. Twit Text FOAVip Understanding epidemic data and statistics: A case study of COVID-19 ????J Med Virol http://www.kidney.de/pget.php?&tw=1&pmid=32329522 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32329522 #FOAvip English Wikipedia <ref>{{Cite pmid|32329522}}</ref> Understanding epidemic data and statistics: A case study of COVID-19 #MMPMID32329522 Hoseinpour Dehkordi A; Alizadeh M; Derakhshan P; Babazadeh P; Jahandideh A J Med Virol 2020[Jul]; 92 (7): 868-882 PMID32329522show ga The 2019 novel-coronavirus (COVID-19) has affected 181 countries with approximately 1197405 confirmed cases (by 5th April). Understanding the transmission dynamics of the infection in each country which got affected on a daily basis and evaluating the effectiveness of control policies are critical for our further actions. To date, the statistics of COVID-19 reported cases show that more than 80% of infected are mild cases of disease, around 14% of infected have severe complications, and about 5% are categorized as critical disease victims. Today's report (5th April 2020; daily updates in the prepared website) shows that the confirmed cases of COVID-19 in the United States, Spain, Italy, and Germany are 308850, 126168, 124632, and 96092, respectively. Calculating the total case fatality rate (CFR) of Italy (4th April 2020), about 13.3% of confirmed cases have passed away. Compared with South Korea's rate of 1.8% (seven times lower than Italy) and China's 4% (69% lower than Italy), the CFR of Italy is too high. Some effective policies that yielded significant changes in the trend of cases were the lockdown policy in China, Italy, and Spain (the effect observed after some days), the shutdown of all nonessential companies in Hubei (the effect observed after 5 days), combined policy in South Korea, and reducing working hours in Iran. |*Algorithms[MESH] |*Pandemics/prevention & control[MESH] |Asia/epidemiology[MESH] |Betacoronavirus/*pathogenicity[MESH] |COVID-19[MESH] |Communicable Disease Control[MESH] |Coronavirus Infections/diagnosis/*epidemiology/prevention & control/*transmission[MESH] |Europe/epidemiology[MESH] |Health Policy/legislation & jurisprudence[MESH] |Humans[MESH] |Pneumonia, Viral/diagnosis/*epidemiology/prevention & control/*transmission[MESH] |Public Health/legislation & jurisprudence[MESH] |Quarantine/organization & administration[MESH] |SARS-CoV-2[MESH] |Statistics as Topic[MESH]Understanding epidemic data and statistics: A case study of COVID-19 (epmc).pdf DeepDyve Pubget Overpricing