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Rigorous surveillance is necessary for high confidence in end-of-outbreak declarations for Ebola and other infectious diseases
Author(s) -
Robin N. Thompson,
Oliver Morgan,
Katri Jalava
Publication year - 2019
Publication title -
philosophical transactions of the royal society b biological sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.753
H-Index - 272
eISSN - 1471-2970
pISSN - 0962-8436
DOI - 10.1098/rstb.2018.0431
Subject(s) - outbreak , infectious disease (medical specialty) , certainty , declaration , transmission (telecommunications) , ebola hemorrhagic fever , disease , disease surveillance , medicine , public health , biosecurity , environmental health , ebola virus , virology , computer science , pathology , telecommunications , philosophy , epistemology , programming language
The World Health Organization considers an Ebola outbreak to have ended once 42 days have passed since the last possible exposure to a confirmed case. Benefits of a quick end-of-outbreak declaration, such as reductions in trade/travel restrictions, must be balanced against the chance of flare-ups from undetected residual cases. We show how epidemiological modelling can be used to estimate the surveillance level required for decision-makers to be confident that an outbreak is over. Results from a simple model characterizing an Ebola outbreak suggest that a surveillance sensitivity (i.e. case reporting percentage) of 79% is necessary for 95% confidence that an outbreak is over after 42 days without symptomatic cases. With weaker surveillance, unrecognized transmission may still occur: if the surveillance sensitivity is only 40%, then 62 days must be waited for 95% certainty. By quantifying the certainty in end-of-outbreak declarations, public health decision-makers can plan and communicate more effectively. This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’. This issue is linked with the earlier theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’.

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