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10.1371/journal.pone.0238340 http://scihub22266oqcxt.onion/10.1371/journal.pone.0238340 32853295!7451571!32853295     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       PLoS+One 2020 ; 15 (8): e0238340 Nephropedia Template TP {{tp|p=32853295|t=2020. An epidemiological model to aid decision-making for COVID-19 control in Sri Lanka |pdf=|usr=}}{{32853295}} gab.com Text An epidemiological model to aid decision-making for COVID-19 control in Sri Lanka JO: PLoS One http://www.kidney.de/pget.php?&tw=1&pmid=32853295 #FOAvip BACKGROUND: Sri Lanka diagnosed its first local case of COVID-19 on 11 March 2020. The government acted swiftly to contain transmission, with extensive public health measures. At the end of 30 days, Sri Lanka had 197 cases, 54 recovered and 7 deaths; a staged relaxing of the lockdown is now underway. This paper proposes a theoretical basis for estimating the limits within which transmission should be constrained in order to ensure that the case load remains within the capacity of Sri Lanka's health system. METHODS: We used the Susceptible, Infected, Recovered (SIR) model to explore the number of new infections and estimate ICU bed requirement at different levels of R0 values after lifting lockdown restrictions. We developed a web-based application that enables visualization of cases and ICU bed requirements with time, with adjustable parameters that include: population at risk; number of identified and recovered cases; percentage identified; infectious period; R0 or doubling time; percentage critically ill; available ICU beds; duration of ICU stay; and uncertainty of projection. RESULTS: The three-day moving average of the caseload suggested two waves of transmission from Day 0 to 17 (R0 = 3.32, 95% CI 1.85-5.41) and from Day 18-30 (R = 1.25, 95%CI: 0.93-1.63). We estimate that if there are 156 active cases with 91 recovered at the time of lifting lockdown restrictions, and R increases to 1.5 (doubling time 19 days), under the standard parameters for Sri Lanka, the ICU bed capacity of 300 is likely to be saturated by about 100 days, signaled by 18 new infections (95% CI 15-22) on Day 14 after lifting lockdown restrictions. CONCLUSION: Our model suggests that to ensure that the case load remains within the available capacity of the health system after lifting lockdown restrictions, transmission should not exceed R = 1.5. This model and the web-based application may be useful in other low and middle income countries which have similar constraints on health resources. Twit Text FOAVip An epidemiological model to aid decision-making for COVID-19 control in Sri Lanka ????PLoS One http://www.kidney.de/pget.php?&tw=1&pmid=32853295 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32853295 #FOAvip English Wikipedia <ref>{{Cite pmid|32853295}}</ref> An epidemiological model to aid decision-making for COVID-19 control in Sri Lanka #MMPMID32853295 Ediriweera DS; de Silva NR; Malavige GN; de Silva HJ PLoS One 2020[]; 15 (8): e0238340 PMID32853295show ga BACKGROUND: Sri Lanka diagnosed its first local case of COVID-19 on 11 March 2020. The government acted swiftly to contain transmission, with extensive public health measures. At the end of 30 days, Sri Lanka had 197 cases, 54 recovered and 7 deaths; a staged relaxing of the lockdown is now underway. This paper proposes a theoretical basis for estimating the limits within which transmission should be constrained in order to ensure that the case load remains within the capacity of Sri Lanka's health system. METHODS: We used the Susceptible, Infected, Recovered (SIR) model to explore the number of new infections and estimate ICU bed requirement at different levels of R0 values after lifting lockdown restrictions. We developed a web-based application that enables visualization of cases and ICU bed requirements with time, with adjustable parameters that include: population at risk; number of identified and recovered cases; percentage identified; infectious period; R0 or doubling time; percentage critically ill; available ICU beds; duration of ICU stay; and uncertainty of projection. RESULTS: The three-day moving average of the caseload suggested two waves of transmission from Day 0 to 17 (R0 = 3.32, 95% CI 1.85-5.41) and from Day 18-30 (R = 1.25, 95%CI: 0.93-1.63). We estimate that if there are 156 active cases with 91 recovered at the time of lifting lockdown restrictions, and R increases to 1.5 (doubling time 19 days), under the standard parameters for Sri Lanka, the ICU bed capacity of 300 is likely to be saturated by about 100 days, signaled by 18 new infections (95% CI 15-22) on Day 14 after lifting lockdown restrictions. CONCLUSION: Our model suggests that to ensure that the case load remains within the available capacity of the health system after lifting lockdown restrictions, transmission should not exceed R = 1.5. This model and the web-based application may be useful in other low and middle income countries which have similar constraints on health resources. |*Decision Making[MESH] |Betacoronavirus[MESH] |COVID-19[MESH] |Communicable Disease Control/methods[MESH] |Coronavirus Infections/*epidemiology/*prevention & control[MESH] |Humans[MESH] |Internet[MESH] |Models, Theoretical[MESH] |Pandemics/*prevention & control[MESH] |Pneumonia, Viral/*epidemiology/*prevention & control[MESH] |Public Health[MESH] |SARS-CoV-2[MESH] |Software[MESH]An epidemiological model to aid decision-making for COVID-19 control i(epmc).pdf DeepDyve Pubget Overpricing