Will an outbreak exceed available resources for control? Estimating the risk from invading pathogens using practical definitions of a severe epidemic

Abstract

14Forecasting whether or not initial reports of disease will be followed by a major epidemic 15 is an important component of disease management. Most estimates of the probability of 16 a major epidemic involve assuming that infections occur according to a branching 17 process. Surprisingly, however, these calculations can be carried out without the factors 18 that differentiate a major epidemic from a minor outbreak ever being defined precisely. 19We assess potential implications of this lack of explicitness by considering the differences 20 between three practically relevant possible definitions of a major epidemic. Specifically, 21we consider a major epidemic as an outbreak in which: i) a large number of hosts are 22 infected simultaneously; ii) a large number of infections occur in total; and iii) disease 23 persists in the population for a long time. We calculate the probability of a major epidemic 24 under each of these definitions, initially considering the commonly used stochastic 25Susceptible-Infected-Susceptible model as a tractable case study allowing analytical 26 progress. We show how the probability of a major epidemic can either be similar to, or 27 very different from, the branching process estimate, depending on which definition of a 28 major epidemic is used. We also show, using other models, that this ambiguity continues 29 to hold in different epidemiological settings. In particular, we consider two additional 30 models: the stochastic Susceptible-Infected-Removed model, and a more complex host-31 vector model parameterised for Zika virus. Our work highlights how the precise definition 32 of a major epidemic must be considered carefully when estimating the risk posed by a 33 new outbreak. It also demonstrates that the precise definition of a major epidemic must 34 be tailored to the epidemiology of the host-pathogen system under consideration. 35 36 KEYWORDS 37 mathematical modelling; infectious disease epidemiology; major epidemic; forecasting 38 39 SHORT TITLE 40 Assessing the practically relevant risk of a major epidemic 41 42 AUTHOR SUMMARY 43When cases of disease are first reported in a new region or country, policy-makers must 44 decide if a disease control programme should be rolled out, as well as how to deploy 45 limited resources. Central to this assessment is understanding the risk of initial cases 46 generating a major epidemic as opposed to fading out as a minor outbreak in which only 47

Big Data Analytics in the Fight against Major Public Health Incidents (Including COVID-19): A Conceptual Framework

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Real-Time Estimation of the Risk of Death from Novel Coronavirus (COVID-19) Infection: Inference Using Exported Cases

“…The basic reproduction number ( 0 ), the average number of secondary cases generated by a single primary case in a fully susceptible population, represents an epidemiological measurement of the transmissibility, helping us to quantify the pandemic potential of COVID-19. Here, we define a pandemic as the worldwide spread of a newly emerged disease, in which the number of simultaneously infected individuals exceeds the capacity for treatment [12]. Using the growth rate of the estimated cumulative incidence from exportation cases and accounting for the time delay from illness onset to death, the present study aims to estimate the cCFR of COVID-19 in real-time.…”

Real-Time Estimation of the Risk of Death from Novel Coronavirus (COVID-19) Infection: Inference Using Exported Cases

“…The basic reproduction number (R 0 ), the average number of secondary cases generated by a single primary case in a fully susceptible population, represents an epidemiological measurement of the transmissibility, helping us to quantify the pandemic potential of COVID-19. Here, we define a pandemic as the worldwide spread of a newly emerged disease, in which the number of simultaneously infected individuals exceeds the capacity for treatment [12]. Using the growth rate of the estimated cumulative incidence from exportation cases and accounting for the time delay from illness onset to death, the present study aims to estimate the cCFR of COVID-19 in real-time.…”