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10.1016/S1473-3099(20)30361-3 http://scihub22266oqcxt.onion/10.1016/S1473-3099(20)30361-3 32445710!7239635!32445710     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 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 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Lancet+Infect+Dis 2020 ; 20 (9): 1025-1033 Nephropedia Template TP {{tp|p=32445710|t=2020. Individual quarantine versus active monitoring of contacts for the mitigation of COVID-19: a modelling study |pdf=|usr=}}{{32445710}} gab.com Text Individual quarantine versus active monitoring of contacts for the mitigation of COVID-19: a modelling study JO: Lancet Infect Dis http://www.kidney.de/pget.php?&tw=1&pmid=32445710 #FOAvip BACKGROUND: Voluntary individual quarantine and voluntary active monitoring of contacts are core disease control strategies for emerging infectious diseases such as COVID-19. Given the impact of quarantine on resources and individual liberty, it is vital to assess under what conditions individual quarantine can more effectively control COVID-19 than active monitoring. As an epidemic grows, it is also important to consider when these interventions are no longer feasible and broader mitigation measures must be implemented. METHODS: To estimate the comparative efficacy of individual quarantine and active monitoring of contacts to control severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we fit a stochastic branching model to reported parameters for the dynamics of the disease. Specifically, we fit a model to the incubation period distribution (mean 5.2 days) and to two estimates of the serial interval distribution: a shorter one with a mean serial interval of 4.8 days and a longer one with a mean of 7.5 days. To assess variable resource settings, we considered two feasibility settings: a high-feasibility setting with 90% of contacts traced, a half-day average delay in tracing and symptom recognition, and 90% effective isolation; and a low-feasibility setting with 50% of contacts traced, a 2-day average delay, and 50% effective isolation. FINDINGS: Model fitting by sequential Monte Carlo resulted in a mean time of infectiousness onset before symptom onset of 0.77 days (95% CI -1.98 to 0.29) for the shorter serial interval, and for the longer serial interval it resulted in a mean time of infectiousness onset after symptom onset of 0.51 days (95% CI -0.77 to 1.50). Individual quarantine in high-feasibility settings, where at least 75% of infected contacts are individually quarantined, contains an outbreak of SARS-CoV-2 with a short serial interval (4.8 days) 84% of the time. However, in settings where the outbreak continues to grow (eg, low-feasibility settings), so too will the burden of the number of contacts traced for active monitoring or quarantine, particularly uninfected contacts (who never develop symptoms). When resources are prioritised for scalable interventions such as physical distancing, we show active monitoring or individual quarantine of high-risk contacts can contribute synergistically to mitigation efforts. Even under the shorter serial interval, if physical distancing reduces the reproductive number to 1.25, active monitoring of 50% of contacts can result in overall outbreak control (ie, effective reproductive number <1). INTERPRETATION: Our model highlights the urgent need for more data on the serial interval and the extent of presymptomatic transmission to make data-driven policy decisions regarding the cost-benefit comparisons of individual quarantine versus active monitoring of contacts. To the extent that these interventions can be implemented, they can help mitigate the spread of SARS-CoV-2. FUNDING: National Institute of General Medical Sciences, National Institutes of Health. Twit Text FOAVip Individual quarantine versus active monitoring of contacts for the mitigation of COVID-19: a modelling study ????Lancet Infect Dis http://www.kidney.de/pget.php?&tw=1&pmid=32445710 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32445710 #FOAvip English Wikipedia <ref>{{Cite pmid|32445710}}</ref> Individual quarantine versus active monitoring of contacts for the mitigation of COVID-19: a modelling study #MMPMID32445710 Peak CM; Kahn R; Grad YH; Childs LM; Li R; Lipsitch M; Buckee CO Lancet Infect Dis 2020[Sep]; 20 (9): 1025-1033 PMID32445710show ga BACKGROUND: Voluntary individual quarantine and voluntary active monitoring of contacts are core disease control strategies for emerging infectious diseases such as COVID-19. Given the impact of quarantine on resources and individual liberty, it is vital to assess under what conditions individual quarantine can more effectively control COVID-19 than active monitoring. As an epidemic grows, it is also important to consider when these interventions are no longer feasible and broader mitigation measures must be implemented. METHODS: To estimate the comparative efficacy of individual quarantine and active monitoring of contacts to control severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we fit a stochastic branching model to reported parameters for the dynamics of the disease. Specifically, we fit a model to the incubation period distribution (mean 5.2 days) and to two estimates of the serial interval distribution: a shorter one with a mean serial interval of 4.8 days and a longer one with a mean of 7.5 days. To assess variable resource settings, we considered two feasibility settings: a high-feasibility setting with 90% of contacts traced, a half-day average delay in tracing and symptom recognition, and 90% effective isolation; and a low-feasibility setting with 50% of contacts traced, a 2-day average delay, and 50% effective isolation. FINDINGS: Model fitting by sequential Monte Carlo resulted in a mean time of infectiousness onset before symptom onset of 0.77 days (95% CI -1.98 to 0.29) for the shorter serial interval, and for the longer serial interval it resulted in a mean time of infectiousness onset after symptom onset of 0.51 days (95% CI -0.77 to 1.50). Individual quarantine in high-feasibility settings, where at least 75% of infected contacts are individually quarantined, contains an outbreak of SARS-CoV-2 with a short serial interval (4.8 days) 84% of the time. However, in settings where the outbreak continues to grow (eg, low-feasibility settings), so too will the burden of the number of contacts traced for active monitoring or quarantine, particularly uninfected contacts (who never develop symptoms). When resources are prioritised for scalable interventions such as physical distancing, we show active monitoring or individual quarantine of high-risk contacts can contribute synergistically to mitigation efforts. Even under the shorter serial interval, if physical distancing reduces the reproductive number to 1.25, active monitoring of 50% of contacts can result in overall outbreak control (ie, effective reproductive number <1). INTERPRETATION: Our model highlights the urgent need for more data on the serial interval and the extent of presymptomatic transmission to make data-driven policy decisions regarding the cost-benefit comparisons of individual quarantine versus active monitoring of contacts. To the extent that these interventions can be implemented, they can help mitigate the spread of SARS-CoV-2. FUNDING: National Institute of General Medical Sciences, National Institutes of Health. |*Contact Tracing[MESH] |*Models, Theoretical[MESH] |*Quarantine[MESH] |Betacoronavirus/*isolation & purification[MESH] |COVID-19[MESH] |Coronavirus Infections/epidemiology/*prevention & control/transmission/virology[MESH] |Disease Outbreaks/*prevention & control[MESH] |Epidemiological Monitoring[MESH] |Humans[MESH] |Monte Carlo Method[MESH] |Pandemics/*prevention & control[MESH] |Pneumonia, Viral/epidemiology/*prevention & control/transmission/virology[MESH] |SARS-CoV-2[MESH]Individual quarantine versus active monitoring of contacts for the mit(epmc).pdf DeepDyve Pubget Overpricing