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Metcalf CJE, Andriamandimby SF, Baker RE, Glennon EE, Hampson K, Hollingsworth TD, Klepac P, Wesolowski A. Challenges in evaluating risks and policy options around endemic establishment or elimination of novel pathogens. Epidemics 2021; 37:100507. [PMID: 34823222 PMCID: PMC7612525 DOI: 10.1016/j.epidem.2021.100507] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 08/20/2021] [Accepted: 10/06/2021] [Indexed: 11/12/2022] Open
Abstract
When a novel pathogen emerges there may be opportunities to eliminate transmission - locally or globally - whilst case numbers are low. However, the effort required to push a disease to elimination may come at a vast cost at a time when uncertainty is high. Models currently inform policy discussions on this question, but there are a number of open challenges, particularly given unknown aspects of the pathogen biology, the effectiveness and feasibility of interventions, and the intersecting political, economic, sociological and behavioural complexities for a novel pathogen. In this overview, we detail how models might identify directions for better leveraging or expanding the scope of data available on the pathogen trajectory, for bounding the theoretical context of emergence relative to prospects for elimination, and for framing the larger economic, behavioural and social context that will influence policy decisions and the pathogen’s outcome.
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Affiliation(s)
- C Jessica E Metcalf
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA; Princeton School of Public and International Affairs, Princeton University, Princeton, USA.
| | | | - Rachel E Baker
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA; Princeton High Meadows Environmental Institute, Princeton University, Princeton, NJ, USA
| | - Emma E Glennon
- Disease Dynamics Unit, Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, UK
| | - Katie Hampson
- Institute of Biodiversity, Animal Health & Comparative Medicine, University of Glasgow, Glasgow, UK
| | - T Deirdre Hollingsworth
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, UK
| | - Petra Klepac
- London School of Hygiene and Tropical Medicine, London, UK
| | - Amy Wesolowski
- Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
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Glennon EE, Bruijning M, Lessler J, Miller IF, Rice BL, Thompson RN, Wells K, Metcalf CJE. Challenges in modeling the emergence of novel pathogens. Epidemics 2021; 37:100516. [PMID: 34775298 DOI: 10.1016/j.epidem.2021.100516] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 09/29/2021] [Accepted: 10/22/2021] [Indexed: 01/24/2023] Open
Abstract
The emergence of infectious agents with pandemic potential present scientific challenges from detection to data interpretation to understanding determinants of risk and forecasts. Mathematical models could play an essential role in how we prepare for future emergent pathogens. Here, we describe core directions for expansion of the existing tools and knowledge base, including: using mathematical models to identify critical directions and paths for strengthening data collection to detect and respond to outbreaks of novel pathogens; expanding basic theory to identify infectious agents and contexts that present the greatest risks, over both the short and longer term; by strengthening estimation tools that make the most use of the likely range and uncertainties in existing data; and by ensuring modelling applications are carefully communicated and developed within diverse and equitable collaborations for increased public health benefit.
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Affiliation(s)
- Emma E Glennon
- Disease Dynamics Unit, Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, UK.
| | - Marjolein Bruijning
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
| | - Justin Lessler
- Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Ian F Miller
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA; Rocky Mountain Biological Laboratory, Crested Butte, CO 81224, USA
| | - Benjamin L Rice
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA; Madagascar Health and Environmental Research (MAHERY), Maroantsetra, Madagascar
| | - Robin N Thompson
- Mathematics Institute, University of Warwick, Warwick CV4 7AL, UK; The Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Warwick CV4 7AL, UK
| | - Konstans Wells
- Department of Biosciences, Swansea University, Swansea SA28PP, UK
| | - C Jessica E Metcalf
- Disease Dynamics Unit, Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, UK; Princeton School of Public and International Affairs, Princeton University, Princeton, NJ, USA
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Glennon EE, Becker DJ, Peel AJ, Garnier R, Suu-Ire RD, Gibson L, Hayman DTS, Wood JLN, Cunningham AA, Plowright RK, Restif O. What is stirring in the reservoir? Modelling mechanisms of henipavirus circulation in fruit bat hosts. Philos Trans R Soc Lond B Biol Sci 2019; 374:20190021. [PMID: 31401962 PMCID: PMC6711305 DOI: 10.1098/rstb.2019.0021] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
Pathogen circulation among reservoir hosts is a precondition for zoonotic spillover. Unlike the acute, high morbidity infections typical in spillover hosts, infected reservoir hosts often exhibit low morbidity and mortality. Although it has been proposed that reservoir host infections may be persistent with recurrent episodes of shedding, direct evidence is often lacking. We construct a generalized SEIR (susceptible, exposed, infectious, recovered) framework encompassing 46 sub-models representing the full range of possible transitions among those four states of infection and immunity. We then use likelihood-based methods to fit these models to nine years of longitudinal data on henipavirus serology from a captive colony of Eidolon helvum bats in Ghana. We find that reinfection is necessary to explain observed dynamics; that acute infectious periods may be very short (hours to days); that immunity, if present, lasts about 1-2 years; and that recurring latent infection is likely. Although quantitative inference is sensitive to assumptions about serology, qualitative predictions are robust. Our novel approach helps clarify mechanisms of viral persistence and circulation in wild bats, including estimated ranges for key parameters such as the basic reproduction number and the duration of the infectious period. Our results inform how future field-based and experimental work could differentiate the processes of viral recurrence and reinfection in reservoir hosts. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.
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Affiliation(s)
- Emma E Glennon
- Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, UK
| | - Daniel J Becker
- Department of Microbiology and Immunology, Montana State University, Bozeman, MT 59717, USA.,Department of Biology, Indiana University, Bloomington, IN 47405, USA
| | - Alison J Peel
- Environmental Futures Research Institute, Griffith University, Nathan, Queensland, QLD 4111, Australia
| | - Romain Garnier
- Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, UK.,Department of Biology, Georgetown University, Washington, DC 20007, USA
| | - Richard D Suu-Ire
- School of Veterinary Medicine, College of Basic and Applied Sciences, University of Ghana, Legon, Accra, Ghana
| | - Louise Gibson
- Institute of Zoology, Zoological Society of London, London NW1 4RY, UK
| | - David T S Hayman
- Molecular Epidemiology and Public Health Laboratory, Infectious Disease Research Centre, Hopkirk Research Institute, Massey University, Palmerston North, 4442, New Zealand
| | - James L N Wood
- Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, UK
| | | | - Raina K Plowright
- Department of Microbiology and Immunology, Montana State University, Bozeman, MT 59717, USA
| | - Olivier Restif
- Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, UK
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Abstract
The preparedness of health systems to detect, treat, and prevent onward transmission of Ebola virus disease (EVD) is central to mitigating future outbreaks. Early detection of outbreaks is critical to timely response, but estimating detection rates is difficult because unreported spillover events and outbreaks do not generate data. Using three independent datasets available on the distributions of secondary infections during EVD outbreaks across West Africa, in a single district (Western Area) of Sierra Leone, and in the city of Conakry, Guinea, we simulated realistic outbreak size distributions and compared them to reported outbreak sizes. These three empirical distributions lead to estimates for the proportion of detected spillover events and small outbreaks of 26% (range 8-40%, based on the full outbreak data), 48% (range 39-62%, based on the Sierra Leone data), and 17% (range 11-24%, based on the Guinea data). We conclude that at least half of all spillover events have failed to be reported since EVD was first recognized. We also estimate the probability of detecting outbreaks of different sizes, which is likely less than 10% for single-case spillover events. Comparing models of the observation process also suggests the probability of detecting an outbreak is not simply the cumulative probability of independently detecting any one individual. Rather, we find that any individual's probability of detection is highly dependent upon the size of the cluster of cases. These findings highlight the importance of primary health care and local case management to detect and contain undetected early stage outbreaks at source.
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Affiliation(s)
- Emma E. Glennon
- Department of Veterinary Medicine, University of Cambridge, Cambridge United Kingdom
- * E-mail:
| | - Freya L. Jephcott
- Department of Veterinary Medicine, University of Cambridge, Cambridge United Kingdom
| | - Olivier Restif
- Department of Veterinary Medicine, University of Cambridge, Cambridge United Kingdom
| | - James L. N. Wood
- Department of Veterinary Medicine, University of Cambridge, Cambridge United Kingdom
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Glennon EE, Restif O, Sbarbaro SR, Garnier R, Cunningham AA, Suu-Ire RD, Osei-Amponsah R, Wood JLN, Peel AJ. Domesticated animals as hosts of henipaviruses and filoviruses: A systematic review. Vet J 2017; 233:25-34. [PMID: 29486875 DOI: 10.1016/j.tvjl.2017.12.024] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Revised: 08/24/2017] [Accepted: 12/29/2017] [Indexed: 01/10/2023]
Abstract
Bat-borne viruses carry undeniable risks to the health of human beings and animals, and there is growing recognition of the need for a 'One Health' approach to understand their frequently complex spill-over routes. While domesticated animals can play central roles in major spill-over events of zoonotic bat-borne viruses, for example during the pig-amplified Malaysian Nipah virus outbreak of 1998-1999, the extent of their potential to act as bridging or amplifying species for these viruses has not been characterised systematically. This review aims to compile current knowledge on the role of domesticated animals as hosts of two types of bat-borne viruses, henipaviruses and filoviruses. A systematic literature search of these virus-host interactions in domesticated animals identified 72 relevant studies, which were categorised by year, location, design and type of evidence generated. The review then focusses on Africa as a case study, comparing research efforts in domesticated animals and bats with the distributions of documented human cases. Major gaps remain in our knowledge of the potential ability of domesticated animals to contract or spread these zoonoses. Closing these gaps will be necessary to fully evaluate and mitigate spill-over risks of these viruses, especially with global agricultural intensification.
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Affiliation(s)
- Emma E Glennon
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK.
| | - Olivier Restif
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | | | - Romain Garnier
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Andrew A Cunningham
- Institute of Zoology, Zoological Society of London, Regent's Park, London, UK
| | | | | | - James L N Wood
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Alison J Peel
- Environmental Futures Research Institute, Griffith University, Nathan, Australia
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Van Boeckel TP, Glennon EE, Chen D, Gilbert M, Robinson TP, Grenfell BT, Levin SA, Bonhoeffer S, Laxminarayan R. Reducing antimicrobial use in food animals. Science 2017; 357:1350-1352. [PMID: 28963240 PMCID: PMC6510296 DOI: 10.1126/science.aao1495] [Citation(s) in RCA: 328] [Impact Index Per Article: 46.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Affiliation(s)
| | - Emma E Glennon
- Center for Disease Dynamics, Economics and Policy, Washington, DC 20005, USA.,Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, UK
| | - Dora Chen
- Center for Disease Dynamics, Economics and Policy, Washington, DC 20005, USA.,Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
| | - Marius Gilbert
- Université Libre de Bruxelles, Brussels 1050, Belgium.,Fonds National de la Recherche Scientifique, Brussels 1050, Belgium
| | - Timothy P Robinson
- International Livestock Research Institute, Nairobi 00100, Kenya.,Food and Agriculture Organization of the United Nations, Rome 00153, Italy
| | - Bryan T Grenfell
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA.,Fogarty International Center, National Institutes of Health, Bethesda, MD 20892, USA
| | - Simon A Levin
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA.,Princeton Environmental Institute, Princeton University, Princeton, NJ 08544, USA
| | | | - Ramanan Laxminarayan
- Center for Disease Dynamics, Economics and Policy, Washington, DC 20005, USA. .,Princeton Environmental Institute, Princeton University, Princeton, NJ 08544, USA
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