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10.1186/s12916-020-01884-4 http://scihub22266oqcxt.onion/10.1186/s12916-020-01884-4 33504336!7840427!33504336     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=33504336&cmd=llinks): Failed to open stream: HTTP request failed! 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Development of the reproduction number from coronavirus SARS-CoV-2 case data in Germany and implications for political measures |pdf=|usr=}}{{33504336}} gab.com Text Development of the reproduction number from coronavirus SARS-CoV-2 case data in Germany and implications for political measures JO: BMC Med http://www.kidney.de/pget.php?&tw=1&pmid=33504336 #FOAvip BACKGROUND: SARS-CoV-2 has induced a worldwide pandemic and subsequent non-pharmaceutical interventions (NPIs) to control the spread of the virus. As in many countries, the SARS-CoV-2 pandemic in Germany has led to a consecutive roll-out of different NPIs. As these NPIs have (largely unknown) adverse effects, targeting them precisely and monitoring their effectiveness are essential. We developed a compartmental infection dynamics model with specific features of SARS-CoV-2 that allows daily estimation of a time-varying reproduction number and published this information openly since the beginning of April 2020. Here, we present the transmission dynamics in Germany over time to understand the effect of NPIs and allow adaptive forecasts of the epidemic progression. METHODS: We used a data-driven estimation of the evolution of the reproduction number for viral spreading in Germany as well as in all its federal states using our model. Using parameter estimates from literature and, alternatively, with parameters derived from a fit to the initial phase of COVID-19 spread in different regions of Italy, the model was optimized to fit data from the Robert Koch Institute. RESULTS: The time-varying reproduction number (R(t)) in Germany decreased to <1 in early April 2020, 2-3 weeks after the implementation of NPIs. Partial release of NPIs both nationally and on federal state level correlated with moderate increases in R(t) until August 2020. Implications of state-specific R(t) on other states and on national level are characterized. Retrospective evaluation of the model shows excellent agreement with the data and usage of inpatient facilities well within the healthcare limit. While short-term predictions may work for a few weeks, long-term projections are complicated by unpredictable structural changes. CONCLUSIONS: The estimated fraction of immunized population by August 2020 warns of a renewed outbreak upon release of measures. A low detection rate prolongs the delay reaching a low case incidence number upon release, showing the importance of an effective testing-quarantine strategy. We show that real-time monitoring of transmission dynamics is important to evaluate the extent of the outbreak, short-term projections for the burden on the healthcare system, and their response to policy changes. Twit Text FOAVip Development of the reproduction number from coronavirus SARS-CoV-2 case data in Germany and implications for political measures ????BMC Med http://www.kidney.de/pget.php?&tw=1&pmid=33504336 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33504336 #FOAvip English Wikipedia <ref>{{Cite pmid|33504336}}</ref> Development of the reproduction number from coronavirus SARS-CoV-2 case data in Germany and implications for political measures #MMPMID33504336 Khailaie S; Mitra T; Bandyopadhyay A; Schips M; Mascheroni P; Vanella P; Lange B; Binder SC; Meyer-Hermann M BMC Med 2021[Jan]; 19 (1): 32 PMID33504336show ga BACKGROUND: SARS-CoV-2 has induced a worldwide pandemic and subsequent non-pharmaceutical interventions (NPIs) to control the spread of the virus. As in many countries, the SARS-CoV-2 pandemic in Germany has led to a consecutive roll-out of different NPIs. As these NPIs have (largely unknown) adverse effects, targeting them precisely and monitoring their effectiveness are essential. We developed a compartmental infection dynamics model with specific features of SARS-CoV-2 that allows daily estimation of a time-varying reproduction number and published this information openly since the beginning of April 2020. Here, we present the transmission dynamics in Germany over time to understand the effect of NPIs and allow adaptive forecasts of the epidemic progression. METHODS: We used a data-driven estimation of the evolution of the reproduction number for viral spreading in Germany as well as in all its federal states using our model. Using parameter estimates from literature and, alternatively, with parameters derived from a fit to the initial phase of COVID-19 spread in different regions of Italy, the model was optimized to fit data from the Robert Koch Institute. RESULTS: The time-varying reproduction number (R(t)) in Germany decreased to <1 in early April 2020, 2-3 weeks after the implementation of NPIs. Partial release of NPIs both nationally and on federal state level correlated with moderate increases in R(t) until August 2020. Implications of state-specific R(t) on other states and on national level are characterized. Retrospective evaluation of the model shows excellent agreement with the data and usage of inpatient facilities well within the healthcare limit. While short-term predictions may work for a few weeks, long-term projections are complicated by unpredictable structural changes. CONCLUSIONS: The estimated fraction of immunized population by August 2020 warns of a renewed outbreak upon release of measures. A low detection rate prolongs the delay reaching a low case incidence number upon release, showing the importance of an effective testing-quarantine strategy. We show that real-time monitoring of transmission dynamics is important to evaluate the extent of the outbreak, short-term projections for the burden on the healthcare system, and their response to policy changes. |*Basic Reproduction Number[MESH] |*Pandemics[MESH] |COVID-19/*epidemiology/transmission[MESH] |Germany/epidemiology[MESH] |Humans[MESH] |Italy/epidemiology[MESH] |Models, Statistical[MESH]Development of the reproduction number from coronavirus SARS-CoV-2 cas(epmc).pdf DeepDyve Pubget Overpricing