BACKGROUND.The effective reproduction number Re(t)is a critical measure of epidemic potential.Re(t)can be calculated in near real time using an incidence time series and the generation time distribution:the time betwe...BACKGROUND.The effective reproduction number Re(t)is a critical measure of epidemic potential.Re(t)can be calculated in near real time using an incidence time series and the generation time distribution:the time between infection events in an infector-infectee pair.In calculating Re(t),the generation time distribution is often approximated by the serial interval distribution:the time between symptom onset in an infector-infectee pair.However,while generation time must be positive by definition,serial interval can be negative if transmission can occur before symptoms,such as in COVID-19,rendering such an approximation improper in some contexts.METHODS.We developed a method to infer the generation time distribution from parametric definitions of the serial interval and incubation period distributions.We then compared estimates of Re(t)for COVID-19 in the Greater Toronto Area of Canada using:negative-permitting versus non-negative serial interval distributions,versus the inferred generation time distribution.RESULTS.We estimated the generation time of COVID-19 to be Gamma-distributed with mean 3.99 and standard deviation 2.96 days.Relative to the generation time distribution,non-negative serial interval distribution caused overestimation of Re(t)due to larger mean,while negative-permitting serial interval distribution caused underestimation of Re(t)due to larger variance.IMPLICATIONS.Approximation of the generation time distribution of COVID-19 with non-negative or negative-permitting serial interval distributions when calculating Re(t)may result in over or underestimation of transmission potential,respectively.展开更多
In this study,we determine and compare the incubation duration,serial interval,pre-symptomatic transmission,and case fatality rate of MERS-CoV and COVID-19 in Saudi Arabia based on contact tracing data we acquired in ...In this study,we determine and compare the incubation duration,serial interval,pre-symptomatic transmission,and case fatality rate of MERS-CoV and COVID-19 in Saudi Arabia based on contact tracing data we acquired in Saudi Arabia.The date of infection and infector-infectee pairings are deduced from travel history to Saudi Arabia or exposure to confirmed cases.The incubation times and serial intervals are estimated using parametric models accounting for exposure interval censoring.Our estimations show that MERS-CoV has a mean incubation time of 7.21(95%CI:6.59–7.85)days,whereas COVID-19(for the circulating strain in the study period)has a mean incubation period of 5.43(95%CI:4.81–6.11)days.MERS-CoV has an estimated serial interval of 14.13(95%CI:13.9–14.7)days,while COVID-19 has an estimated serial interval of 5.1(95%CI:5.0–5.5)days.The COVID-19 serial interval is found to be shorter than the incubation time,indicating that pre-symptomatic transmission may occur in a significant fraction of transmission events.We conclude that during the COVID-19 wave studied,at least 75%of transmission happened prior to the onset of symptoms.The CFR for MERS-CoV is estimated to be 38.1%(95%CI:36.8–39.5),while the CFR for COVID-191.67%(95%CI:1.63–1.71).This work is expected to help design future surveillance and intervention program targeted at specific respiratory virus outbreaks,and have implications for contingency planning for future coronavirus outbreaks.展开更多
The estimation methods of reproduction numbers and serial intervals are important in the early stages of infectious diseases.During the COVID pandemic,China implemented a dynamic zero-COVID policy on the Chinese mainl...The estimation methods of reproduction numbers and serial intervals are important in the early stages of infectious diseases.During the COVID pandemic,China implemented a dynamic zero-COVID policy on the Chinese mainland until the end of 2022.This study compares three estimation methods of basic repro-duction numbers on small-scale,short-duration COVID-19 epidemics in Fujian Province.Basic reproduc-tion numbers were investigated using a varying-strain model via a next-generation matrix method.Serial intervals were derived using the infector-infectee pairs of two epidemics from the Fujian Provincial Center for Disease Control and Prevention.Basic reproduction numbers were estimated using the maxi-mum likelihood estimation method and the exponential growth method.The curves of the effective reproduction numbers of the three epidemics were plotted by utilizing daily cases and the EpiEstim R package.The spatial heterogeneity of infection cases was described using the Gini coefficient.This study provides significant insights on the estimation methods of reproduction numbers for policymakers in the local government.The results reveal that social contacts between infectors and susceptible individuals should be reduced to avoid an increase in deaths and to fight against the spread of infectious diseases.展开更多
基金The study was supported by:the Natural Sciences and Engineering Research Council of Canada(NSERC CGS-D)Ontario Early Researcher Award No.ER17-13-043(Canada)the 2020 COVID-19 Centred Research Award from the St Michael’s Hospital Foundation Research Innovation Council(Canada).
文摘BACKGROUND.The effective reproduction number Re(t)is a critical measure of epidemic potential.Re(t)can be calculated in near real time using an incidence time series and the generation time distribution:the time between infection events in an infector-infectee pair.In calculating Re(t),the generation time distribution is often approximated by the serial interval distribution:the time between symptom onset in an infector-infectee pair.However,while generation time must be positive by definition,serial interval can be negative if transmission can occur before symptoms,such as in COVID-19,rendering such an approximation improper in some contexts.METHODS.We developed a method to infer the generation time distribution from parametric definitions of the serial interval and incubation period distributions.We then compared estimates of Re(t)for COVID-19 in the Greater Toronto Area of Canada using:negative-permitting versus non-negative serial interval distributions,versus the inferred generation time distribution.RESULTS.We estimated the generation time of COVID-19 to be Gamma-distributed with mean 3.99 and standard deviation 2.96 days.Relative to the generation time distribution,non-negative serial interval distribution caused overestimation of Re(t)due to larger mean,while negative-permitting serial interval distribution caused underestimation of Re(t)due to larger variance.IMPLICATIONS.Approximation of the generation time distribution of COVID-19 with non-negative or negative-permitting serial interval distributions when calculating Re(t)may result in over or underestimation of transmission potential,respectively.
基金This study was funded by the Medical Research Council through the COVID-19 Rapid Response Rolling Call[grant number MR/V009761/1]and by Taif University[grant number 4360060].
文摘In this study,we determine and compare the incubation duration,serial interval,pre-symptomatic transmission,and case fatality rate of MERS-CoV and COVID-19 in Saudi Arabia based on contact tracing data we acquired in Saudi Arabia.The date of infection and infector-infectee pairings are deduced from travel history to Saudi Arabia or exposure to confirmed cases.The incubation times and serial intervals are estimated using parametric models accounting for exposure interval censoring.Our estimations show that MERS-CoV has a mean incubation time of 7.21(95%CI:6.59–7.85)days,whereas COVID-19(for the circulating strain in the study period)has a mean incubation period of 5.43(95%CI:4.81–6.11)days.MERS-CoV has an estimated serial interval of 14.13(95%CI:13.9–14.7)days,while COVID-19 has an estimated serial interval of 5.1(95%CI:5.0–5.5)days.The COVID-19 serial interval is found to be shorter than the incubation time,indicating that pre-symptomatic transmission may occur in a significant fraction of transmission events.We conclude that during the COVID-19 wave studied,at least 75%of transmission happened prior to the onset of symptoms.The CFR for MERS-CoV is estimated to be 38.1%(95%CI:36.8–39.5),while the CFR for COVID-191.67%(95%CI:1.63–1.71).This work is expected to help design future surveillance and intervention program targeted at specific respiratory virus outbreaks,and have implications for contingency planning for future coronavirus outbreaks.
基金supported by the Special Projects of the Central(2021L3018)the Natural Science Foundation of Fujian Province ported by the Major Health Research Project of Fujian Province KCZ and GMC were supported by the Fujian Science and Technol-the Government Guiding Local Science and Technology Development of China(2021J01621)+2 种基金the Consultancy Project by the Chinese Academy of Engineering(2022-JB-06,2023-JB-12)JFX was sup-(2021ZD01001).We would like to thank Fujian Research and Training Grants for Young and Middle-aged Leaders in Healthcare.ogy Innovation Platform Construction Project(2019Y2001)Health Science and Technology Project of Fujian Province(2020GGB019).
文摘The estimation methods of reproduction numbers and serial intervals are important in the early stages of infectious diseases.During the COVID pandemic,China implemented a dynamic zero-COVID policy on the Chinese mainland until the end of 2022.This study compares three estimation methods of basic repro-duction numbers on small-scale,short-duration COVID-19 epidemics in Fujian Province.Basic reproduc-tion numbers were investigated using a varying-strain model via a next-generation matrix method.Serial intervals were derived using the infector-infectee pairs of two epidemics from the Fujian Provincial Center for Disease Control and Prevention.Basic reproduction numbers were estimated using the maxi-mum likelihood estimation method and the exponential growth method.The curves of the effective reproduction numbers of the three epidemics were plotted by utilizing daily cases and the EpiEstim R package.The spatial heterogeneity of infection cases was described using the Gini coefficient.This study provides significant insights on the estimation methods of reproduction numbers for policymakers in the local government.The results reveal that social contacts between infectors and susceptible individuals should be reduced to avoid an increase in deaths and to fight against the spread of infectious diseases.
