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10.1093/ije/dyaa198 http://scihub22266oqcxt.onion/10.1093/ije/dyaa198 33349859!7799106!33349859     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 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Int+J+Epidemiol 2021 ; 49 (6): 1963-1971 Nephropedia Template TP {{tp|p=33349859|t=2021. A demographic scaling model for estimating the total number of COVID-19 infections |pdf=|usr=}}{{33349859}} gab.com Text A demographic scaling model for estimating the total number of COVID-19 infections JO: Int J Epidemiol http://www.kidney.de/pget.php?&tw=1&pmid=33349859 #FOAvip BACKGROUND: Understanding how widely COVID-19 has spread is critical information for monitoring the pandemic. The actual number of infections potentially exceeds the number of confirmed cases. DEVELOPMENT: We develop a demographic scaling model to estimate COVID-19 infections, based on minimal data requirements: COVID-19-related deaths, infection fatality rates (IFRs), and life tables. As many countries lack IFR estimates, we scale them from a reference country based on remaining lifetime to better match the context in a target population with respect to age structure, health conditions and medical services. We introduce formulas to account for bias in input data and provide a heuristic to assess whether local seroprevalence estimates are representative for the total population. APPLICATION: Across 10 countries with most reported COVID-19 deaths as of 23 July 2020, the number of infections is estimated to be three [95% prediction interval: 2-8] times the number of confirmed cases. Cross-country variation is high. The estimated number of infections is 5.3 million for the USA, 1.8 million for the UK, 1.4 million for France, and 0.4 million for Peru, or more than one, six, seven and more than one times the number of confirmed cases, respectively. Our central prevalence estimates for entire countries are markedly lower than most others based on local seroprevalence studies. CONCLUSIONS: The national infection estimates indicate that the pandemic is far more widespread than the numbers of confirmed cases suggest. Some local seroprevalence estimates largely deviate from their corresponding national mean and are unlikely to be representative for the total population. Twit Text FOAVip A demographic scaling model for estimating the total number of COVID-19 infections ????Int J Epidemiol http://www.kidney.de/pget.php?&tw=1&pmid=33349859 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33349859 #FOAvip English Wikipedia <ref>{{Cite pmid|33349859}}</ref> A demographic scaling model for estimating the total number of COVID-19 infections #MMPMID33349859 Bohk-Ewald C; Dudel C; Myrskyla M Int J Epidemiol 2021[Jan]; 49 (6): 1963-1971 PMID33349859show ga BACKGROUND: Understanding how widely COVID-19 has spread is critical information for monitoring the pandemic. The actual number of infections potentially exceeds the number of confirmed cases. DEVELOPMENT: We develop a demographic scaling model to estimate COVID-19 infections, based on minimal data requirements: COVID-19-related deaths, infection fatality rates (IFRs), and life tables. As many countries lack IFR estimates, we scale them from a reference country based on remaining lifetime to better match the context in a target population with respect to age structure, health conditions and medical services. We introduce formulas to account for bias in input data and provide a heuristic to assess whether local seroprevalence estimates are representative for the total population. APPLICATION: Across 10 countries with most reported COVID-19 deaths as of 23 July 2020, the number of infections is estimated to be three [95% prediction interval: 2-8] times the number of confirmed cases. Cross-country variation is high. The estimated number of infections is 5.3 million for the USA, 1.8 million for the UK, 1.4 million for France, and 0.4 million for Peru, or more than one, six, seven and more than one times the number of confirmed cases, respectively. Our central prevalence estimates for entire countries are markedly lower than most others based on local seroprevalence studies. CONCLUSIONS: The national infection estimates indicate that the pandemic is far more widespread than the numbers of confirmed cases suggest. Some local seroprevalence estimates largely deviate from their corresponding national mean and are unlikely to be representative for the total population. |*SARS-CoV-2[MESH] |Adolescent[MESH] |Adult[MESH] |COVID-19/*epidemiology[MESH] |Humans[MESH] |Models, Theoretical[MESH] |Pandemics[MESH] |Prevalence[MESH] |Seroepidemiologic Studies[MESH]A demographic scaling model for estimating the total number of COVID-1(epmc).pdf DeepDyve Pubget Overpricing