ArticlePLoS computational biology2018
Control fast or control smart: When should invading pathogens be controlled?
Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Key questions for modelling COVID-19 exit strategies.Proceedings. Biological sciences · 2020Pooled it
- When should lockdown be implemented? Devising cost-effective strategies for managing epidemics amid vaccine uncertainty.PLoS computational biology · 2024Article
- Climate change impacts on plant pathogens, food security and paths forward.Nature reviews. Microbiology · 2023Review
- Non-pharmaceutical interventions and the emergence of pathogen variants.Evolution, medicine, and public health · 2023Article
- How growers make decisions impacts plant disease control.PLoS computational biology · 2022Article
- Optimal health and economic impact of non-pharmaceutical intervention measures prior and post vaccination in England: a mathematical modelling study.Royal Society open science · 2022Article
- Dynamic resource allocation for controlling pathogen spread on a large metapopulation network.Journal of the Royal Society, Interface · 2022Article
- Optimal strategies to protect a sub-population at risk due to an established epidemic.Journal of the Royal Society, Interface · 2022Article
- Evaluating online and tangible interfaces for engaging stakeholders in forecasting and control of biological invasions.Ecological applications : a publication of the Ecological Society of America · 2021Article
- The persistent threat of emerging plant disease pandemics to global food security.Proceedings of the National Academy of Sciences of the United States of America · 2021Review
- Optimal timing of one-shot interventions for epidemic control.PLoS computational biology · 2021Article
- The effect of the definition of 'pandemic' on quantitative assessments of infectious disease outbreak risk.Scientific reports · 2021Article
- Will an outbreak exceed available resources for control? Estimating the risk from invading pathogens using practical definitions of a severe epidemic.Journal of the Royal Society, Interface · 2020Article
- Optimising risk-based surveillance for early detection of invasive plant pathogens.PLoS biology · 2020Article
- A theoretical framework for transitioning from patient-level to population-scale epidemiological dynamics: influenza A as a case study.Journal of the Royal Society, Interface · 2020Article
- Applying optimal control theory to a spatial simulation model of sudden oak death: ongoing surveillance protects tanoak while conserving biodiversity.Journal of the Royal Society, Interface · 2020Article
- Small world in the real world: Long distance dispersal governs epidemic dynamics in agricultural landscapes.Epidemics · 2020Article
- Improved inference of time-varying reproduction numbers during infectious disease outbreaks.Epidemics · 2019Article
- Preface to theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019Article
- How decision makers can use quantitative approaches to guide outbreak responses.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The intuitive response to an invading pathogen is to start disease management as rapidly as possible, since this would be expected to minimise the future impacts of disease. However, since more spread data become available as an outbreak unfolds, processes underpinning pathogen transmission can almost always be characterised more precisely later in epidemics. This allows the future progression of any outbreak to be forecast more accurately, and so enables control interventions to be targeted more precisely. There is also the chance that the outbreak might die out without any intervention whatsoever, making prophylactic control unnecessary. Optimal decision-making involves continuously balancing these potential benefits of waiting against the possible costs of further spread. We introduce a generic, extensible data-driven algorithm based on parameter estimation and outbreak simulation for making decisions in real-time concerning when and how to control an invading pathogen. The Control Smart Algorithm (CSA) resolves the trade-off between the competing advantages of controlling as soon as possible and controlling later when more information has become available. We show-using a generic mathematical model representing the transmission of a pathogen of agricultural animals or plants through a population of farms or fields-how the CSA allows the timing and level of deployment of vaccination or chemical control to be optimised. In particular, the algorithm outperforms simpler strategies such as intervening when the outbreak size reaches a pre-specified threshold, or controlling when the outbreak has persisted for a threshold length of time. This remains the case even if the simpler methods are fully optimised in advance. Our work highlights the potential benefits of giving careful consideration to the question of when to start disease management during emerging outbreaks, and provides a concrete framework to allow policy-makers to make this decision.
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