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10.1016/j.ijid.2020.05.043 http://scihub22266oqcxt.onion/10.1016/j.ijid.2020.05.043 32425631!7229979!32425631     free     free     free 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 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 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 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 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Int+J+Infect+Dis 2020 ; 96 (ä): 376-383 Nephropedia Template TP {{tp|p=32425631|t=2020. A dynamic modeling tool for estimating healthcare demand from the COVID19 epidemic and evaluating population-wide interventions |pdf=|usr=}}{{32425631}} gab.com Text A dynamic modeling tool for estimating healthcare demand from the COVID19 epidemic and evaluating population-wide interventions JO: Int J Infect Dis http://www.kidney.de/pget.php?&tw=1&pmid=32425631 #FOAvip OBJECTIVES: Public health officials need tools to assist in anticipating the healthcare resources required to confront the SARS-COV-2 pandemic. We constructed a modeling tool to aid active public health officials to estimate healthcare demand from the pandemic in their jurisdictions and to evaluate the potential impact of population-wide social-distancing interventions. METHODS: The tool uses an SEIR compartmental model to project the pandemic's local spread. Users input case counts, healthcare resources, and select intervention strategies to evaluate. Outputs include the number of infections and deaths with and without intervention, and the demand for hospital and critical care beds and ventilators relative to existing capacity. We illustrate the tool using data from three regions of Chile. RESULTS: Our scenarios indicate a surge in COVID-19 patients could overwhelm Chilean hospitals by June, peaking in July or August at six to 50 times the current supply of beds and ventilators. A lockdown strategy or combination of case isolation, home quarantine, social distancing of individuals >70 years, and telework interventions may keep treatment demand below capacity. CONCLUSIONS: Aggressive interventions can avert substantial morbidity and mortality from COVID-19. Our tool permits rapid evaluation of locally-applicable policy scenarios and updating of results as new data become available. Twit Text FOAVip A dynamic modeling tool for estimating healthcare demand from the COVID19 epidemic and evaluating population-wide interventions ????Int J Infect Dis http://www.kidney.de/pget.php?&tw=1&pmid=32425631 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32425631 #FOAvip English Wikipedia <ref>{{Cite pmid|32425631}}</ref> A dynamic modeling tool for estimating healthcare demand from the COVID19 epidemic and evaluating population-wide interventions #MMPMID32425631 Rainisch G; Undurraga EA; Chowell G Int J Infect Dis 2020[Jul]; 96 (ä): 376-383 PMID32425631show ga OBJECTIVES: Public health officials need tools to assist in anticipating the healthcare resources required to confront the SARS-COV-2 pandemic. We constructed a modeling tool to aid active public health officials to estimate healthcare demand from the pandemic in their jurisdictions and to evaluate the potential impact of population-wide social-distancing interventions. METHODS: The tool uses an SEIR compartmental model to project the pandemic's local spread. Users input case counts, healthcare resources, and select intervention strategies to evaluate. Outputs include the number of infections and deaths with and without intervention, and the demand for hospital and critical care beds and ventilators relative to existing capacity. We illustrate the tool using data from three regions of Chile. RESULTS: Our scenarios indicate a surge in COVID-19 patients could overwhelm Chilean hospitals by June, peaking in July or August at six to 50 times the current supply of beds and ventilators. A lockdown strategy or combination of case isolation, home quarantine, social distancing of individuals >70 years, and telework interventions may keep treatment demand below capacity. CONCLUSIONS: Aggressive interventions can avert substantial morbidity and mortality from COVID-19. Our tool permits rapid evaluation of locally-applicable policy scenarios and updating of results as new data become available. |*Betacoronavirus[MESH] |COVID-19[MESH] |Coronavirus Infections/prevention & control/*therapy[MESH] |Delivery of Health Care[MESH] |Health Resources[MESH] |Humans[MESH] |Pandemics/prevention & control[MESH] |Pneumonia, Viral/prevention & control/*therapy[MESH] |SARS-CoV-2[MESH]A dynamic modeling tool for estimating healthcare demand from the COVI(epmc).pdf DeepDyve Pubget Overpricing