Sexual transmission and the probability of an end of the Ebola virus disease epidemic

Lee, Hyojung; Nishiura, Hiroshi

doi:10.1016/j.jtbi.2019.03.022

Cited by 23 publications

(47 citation statements)

References 30 publications

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“…While these could bias z s and alter declaration times, some of these more realistic dynamics can be included as future extensions. We can adjust for delays by applying nowcasting techniques [24] and include heterogeneity by using a negative binomial renewal model [1]. Future generalisations of our method will consider how data about reporting trends (e.g.…”

Section: Discussionmentioning

confidence: 99%

An exact method for quantifying the reliability of end-of-epidemic declarations in real time

Parag

Donnelly

Jha

et al. 2020

Preprint

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We derive and validate a novel and analytic method for estimating the probability that an epidemic has been eliminated (i.e. that no future local cases will emerge) in real time. When this probability crosses 0.95 an outbreak can be declared over with 95% confidence. Our method is easy to compute, only requires knowledge of the incidence curve and the serial interval distribution, and evaluates the statistical lifetime of the outbreak of interest. Using this approach, we rigorously show how the time-varying under-reporting of infected cases will artificially inflate the inferred probability of elimination and hence lead to early (false- positive) end-of-epidemic declarations. Contrastingly, we prove that incorrectly identifying imported cases as local will deceptively decrease this probability, resulting in late (false-negative) declarations. Failing to sustain intensive surveillance during the later phases of an epidemic can therefore substantially mislead policymakers on when it is safe to remove travel bans or relax quarantine and social distancing advisories. World Health Organisation guidelines recommend fixed (though disease-specific) waiting times for end-of-epidemic declarations that cannot accommodate these variations. Consequently, there is an unequivocal need for more active and specialised metrics for reliably identifying the conclusion of an epidemic.

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Section: Discussionmentioning

confidence: 99%

An exact method for quantifying the reliability of end-of-epidemic declarations in real time

Parag

Donnelly

Jha

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Here, we only considered potential flare-ups due to unreported cases, and did not explicitly model the possibility that Ebola survivors, who were assumed to have fully recovered, might drive additional cases. Recrudescence from survivors could be included in assessments of the risk of flare-ups after outbreaks are declared over, and a model has recently been developed including these rare events [47]. As a result, targeted monitoring of survivors beyond the WHO guideline period of 42 days that we consider here is also important.…”

Section: Discussionmentioning

confidence: 99%

Rigorous surveillance is necessary for high confidence in end-of-outbreak declarations for Ebola and other infectious diseases

Thompson

Morgan

Jalava

2019

Phil. Trans. R. Soc. B

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One contribution of 16 to a theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. Subject Areas: computational biology, ecology, health and disease and epidemiology, systems biologyThe 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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“…The 2001 foot and mouth disease outbreak in the UK and the 2003 SARS pandemic were new epidemics that were driven extinct without vaccination before they became endemic, but both exhibited long tails before eradication was achieved. The 2014–16 Ebola epidemic in West Africa was eliminated (with vaccination at the end of the epidemic [ 72 ]), but eradication took some time with flare ups occurring in different countries [ 73 , 74 ].…”

Section: Key Epidemiological Quantitiesmentioning

confidence: 99%

Key questions for modelling COVID-19 exit strategies

et al. 2020

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Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute ‘Models for an exit strategy’ workshop (11–15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.

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Sexual transmission and the probability of an end of the Ebola virus disease epidemic

Cited by 23 publications

References 30 publications

An exact method for quantifying the reliability of end-of-epidemic declarations in real time

An exact method for quantifying the reliability of end-of-epidemic declarations in real time

Rigorous surveillance is necessary for high confidence in end-of-outbreak declarations for Ebola and other infectious diseases

Key questions for modelling COVID-19 exit strategies

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