Estimating the probability of a major outbreak from the timing of early cases: an indeterminate problem?

Conservation biologists, as well as veterinary and public health officials, would benefit greatly from being able to forecast whether outbreaks of infectious disease will be major. For values of the basic reproductive number (R0) between one and two, infectious disease outbreaks have a reasonable ch...

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Autores principales:	Meggan E Craft, Hawthorne L Beyer, Daniel T Haydon
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/ef4309ff7d33482cb894b737adbb93e9
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spelling	oai:doaj.org-article:ef4309ff7d33482cb894b737adbb93e92021-11-18T07:54:40ZEstimating the probability of a major outbreak from the timing of early cases: an indeterminate problem?1932-620310.1371/journal.pone.0057878https://doaj.org/article/ef4309ff7d33482cb894b737adbb93e92013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23483934/?tool=EBIhttps://doaj.org/toc/1932-6203Conservation biologists, as well as veterinary and public health officials, would benefit greatly from being able to forecast whether outbreaks of infectious disease will be major. For values of the basic reproductive number (R0) between one and two, infectious disease outbreaks have a reasonable chance of either fading out at an early stage or, in the absence of intervention, spreading widely within the population. If it were possible to predict when fadeout was likely to occur, the need for costly precautionary control strategies could be minimized. However, the predictability of even simple epidemic processes remains largely unexplored. Here we conduct an examination of simulated data from the early stages of a fatal disease outbreak and explore how observable information might be useful for predicting major outbreaks. Specifically, would knowing the time of deaths for the first few cases allow us to predict whether an outbreak will be major? Using two approaches, trajectory matching and discriminant function analysis, we find that even in our best-case scenario (with accurate knowledge of epidemiological parameters, and precise times of death), it was not possible to reliably predict the outcome of a stochastic Susceptible-Exposed-Infectious-Recovered (SEIR) process.Meggan E CraftHawthorne L BeyerDaniel T HaydonPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 3, p e57878 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Meggan E Craft Hawthorne L Beyer Daniel T Haydon Estimating the probability of a major outbreak from the timing of early cases: an indeterminate problem?
description	Conservation biologists, as well as veterinary and public health officials, would benefit greatly from being able to forecast whether outbreaks of infectious disease will be major. For values of the basic reproductive number (R0) between one and two, infectious disease outbreaks have a reasonable chance of either fading out at an early stage or, in the absence of intervention, spreading widely within the population. If it were possible to predict when fadeout was likely to occur, the need for costly precautionary control strategies could be minimized. However, the predictability of even simple epidemic processes remains largely unexplored. Here we conduct an examination of simulated data from the early stages of a fatal disease outbreak and explore how observable information might be useful for predicting major outbreaks. Specifically, would knowing the time of deaths for the first few cases allow us to predict whether an outbreak will be major? Using two approaches, trajectory matching and discriminant function analysis, we find that even in our best-case scenario (with accurate knowledge of epidemiological parameters, and precise times of death), it was not possible to reliably predict the outcome of a stochastic Susceptible-Exposed-Infectious-Recovered (SEIR) process.
format	article
author	Meggan E Craft Hawthorne L Beyer Daniel T Haydon
author_facet	Meggan E Craft Hawthorne L Beyer Daniel T Haydon
author_sort	Meggan E Craft
title	Estimating the probability of a major outbreak from the timing of early cases: an indeterminate problem?
title_short	Estimating the probability of a major outbreak from the timing of early cases: an indeterminate problem?
title_full	Estimating the probability of a major outbreak from the timing of early cases: an indeterminate problem?
title_fullStr	Estimating the probability of a major outbreak from the timing of early cases: an indeterminate problem?
title_full_unstemmed	Estimating the probability of a major outbreak from the timing of early cases: an indeterminate problem?
title_sort	estimating the probability of a major outbreak from the timing of early cases: an indeterminate problem?
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/ef4309ff7d33482cb894b737adbb93e9
work_keys_str_mv	AT megganecraft estimatingtheprobabilityofamajoroutbreakfromthetimingofearlycasesanindeterminateproblem AT hawthornelbeyer estimatingtheprobabilityofamajoroutbreakfromthetimingofearlycasesanindeterminateproblem AT danielthaydon estimatingtheprobabilityofamajoroutbreakfromthetimingofearlycasesanindeterminateproblem
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Estimating the probability of a major outbreak from the timing of early cases: an indeterminate problem?

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