Deterministic epidemic models overestimate the basic reproduction number of observed outbreaks  

作　　者：Wajid Ali Christopher E.Overton Robert R.Wilkinson Kieran J.Sharkey 

机构地区：[1]Department of Mathematical Sciences,University of Liverpool,Peach Street,Liverpool,L697ZX,England,United Kingdom [2]Department of Applied Mathematics,Liverpool John Moores University,Byrom Street,Liverpool,L35UX,England,United Kingdom

出　　处：《Infectious Disease Modelling》2024年第3期680-688,共9页传染病建模（英文）

基　　金：This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 955708.

摘　　要：The basic reproduction number,R_(0),is a well-known quantifier of epidemic spread.However,a class of existing methods for estimating R_(0)from incidence data early in the epidemic can lead to an over-estimation of this quantity.In particular,when fitting deterministic models to estimate the rate of spread,we do not account for the stochastic nature of epidemics and that,given the same system,some outbreaks may lead to epidemics and some may not.Typically,an observed epidemic that we wish to control is a major outbreak.This amounts to implicit selection for major outbreaks which leads to the over-estimation problem.We formally characterised the split between major and minor outbreaks by using Otsu's method which provides us with a working definition.We show that by conditioning a‘deterministic’model on major outbreaks,we can more reliably estimate the basic reproduction number from an observed epidemic trajectory.

关 键 词：Estimating R_(0) Simple birth-death process Major outbreak Conditioned epidemic Stochastic fade-out 

分 类 号：R181.8[医药卫生—流行病学]