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10.1136/jech-2020-214209 http://scihub22266oqcxt.onion/10.1136/jech-2020-214209 32366584!7577097!32366584     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 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Epidemiol+Community+Health 2020 ; 74 (10): 858-860 Nephropedia Template TP {{tp|p=32366584|t=2020. A first estimation of the impact of public health actions against COVID-19 in Veneto (Italy) |pdf=|usr=}}{{32366584}} gab.com Text A first estimation of the impact of public health actions against COVID-19 in Veneto (Italy) JO: J Epidemiol Community Health http://www.kidney.de/pget.php?&tw=1&pmid=32366584 #FOAvip BACKGROUND: Veneto is one of the first Italian regions where the COVID-19 outbreak started spreading. Containment measures were approved soon thereafter. The present study aims at providing a first look at the impact of the containment measures on the outbreak progression in the Veneto region, Italy. METHODS: A Bayesian changepoint analysis was used to identify the changing speed of the epidemic curve. Then, a piecewise polynomial model was considered to fit the data in the first period before the detected changepoint. In this time interval, that is, the weeks from 27 February to 12 March, a quadratic growth was identified by a generalised additive model (GAM). Finally, the model was used to generate the projection of the expected number of hospitalisations at 2 weeks based on the epidemic speed before the changepoint. Such estimates were then compared with the actual outbreak behaviour. RESULTS: The comparison between the observed and predicted hospitalisation curves highlights a slowdown on the total COVID-19 hospitalisations after the onset of containment measures. The estimated daily slowdown effect of the epidemic growth is estimated as 78 hospitalisations per day as of 27 March (95% CI 75 to 81). CONCLUSIONS: The containment strategies seem to have positively impacted the progression of the COVID-19 epidemic outbreak in Veneto. Twit Text FOAVip A first estimation of the impact of public health actions against COVID-19 in Veneto (Italy) ????J Epidemiol Community Health http://www.kidney.de/pget.php?&tw=1&pmid=32366584 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32366584 #FOAvip English Wikipedia <ref>{{Cite pmid|32366584}}</ref> A first estimation of the impact of public health actions against COVID-19 in Veneto (Italy) #MMPMID32366584 Gregori D; Azzolina D; Lanera C; Prosepe I; Destro N; Lorenzoni G; Berchialla P J Epidemiol Community Health 2020[Oct]; 74 (10): 858-860 PMID32366584show ga BACKGROUND: Veneto is one of the first Italian regions where the COVID-19 outbreak started spreading. Containment measures were approved soon thereafter. The present study aims at providing a first look at the impact of the containment measures on the outbreak progression in the Veneto region, Italy. METHODS: A Bayesian changepoint analysis was used to identify the changing speed of the epidemic curve. Then, a piecewise polynomial model was considered to fit the data in the first period before the detected changepoint. In this time interval, that is, the weeks from 27 February to 12 March, a quadratic growth was identified by a generalised additive model (GAM). Finally, the model was used to generate the projection of the expected number of hospitalisations at 2 weeks based on the epidemic speed before the changepoint. Such estimates were then compared with the actual outbreak behaviour. RESULTS: The comparison between the observed and predicted hospitalisation curves highlights a slowdown on the total COVID-19 hospitalisations after the onset of containment measures. The estimated daily slowdown effect of the epidemic growth is estimated as 78 hospitalisations per day as of 27 March (95% CI 75 to 81). CONCLUSIONS: The containment strategies seem to have positively impacted the progression of the COVID-19 epidemic outbreak in Veneto. |*Forecasting[MESH] |*Public Health[MESH] |Bayes Theorem[MESH] |Betacoronavirus[MESH] |COVID-19[MESH] |Coronavirus Infections/epidemiology[MESH] |Disease Outbreaks[MESH] |Hospitalization/*statistics & numerical data[MESH] |Humans[MESH] |Italy/epidemiology[MESH] |Models, Statistical[MESH] |Pandemics/*prevention & control[MESH] |Pneumonia, Viral/epidemiology[MESH]A first estimation of the impact of public health actions against COVI(epmc).pdf DeepDyve Pubget Overpricing