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Estimating effective reproduction number using generation time versus serial interval,with application to COVID-19 in the Greater Toronto Area,Canada 被引量:3

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摘要 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.
出处 《Infectious Disease Modelling》 2020年第1期889-896,共8页 传染病建模(英文)
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).
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