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Telford CT, Amman BR, Towner JS, Montgomery JM, Lessler J, Shoemaker T. Predictive Model for Estimating Annual Ebolavirus Spillover Potential. Emerg Infect Dis 2025; 31:689-698. [PMID: 40133032 PMCID: PMC11950271 DOI: 10.3201/eid3104.241193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/27/2025] Open
Abstract
Forest changes, human population dynamics, and meteorologic conditions have been associated with zoonotic Ebolavirus spillover into humans. High-resolution spatial data for those variables can be used to produce estimates of spillover potential and assess possible annual changes. We developed a model of Ebolavirus spillover during 2001-2021, accounting for variables measured across multiple spatial and temporal scales. We estimated the annual relative odds of Ebolavirus spillover during 2021 and 2022. The highest relative spillover odds estimates occurred in patches that closely followed the spatial distribution of forest loss and fragmentation. Regions throughout equatorial Africa had increased spillover estimates related to changes in forests and human populations. Spillover events in 2022 occurred in locations in the top 0.1% of overall spillover odds estimates or where estimates increased from 2021 to 2022. This model can be used to preemptively target surveillance to identify outbreaks, mitigate disease spread, and educate the public on risk factors for infection.
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Badker R, Kipperman N, Ash B, Madhav NK, Oppenheim B, Savage P, Stephenson N, Pardee C. Constructing a global human epidemic database using open-source digital biosurveillance. Sci Data 2025; 12:344. [PMID: 40011511 PMCID: PMC11865598 DOI: 10.1038/s41597-025-04663-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2024] [Accepted: 02/18/2025] [Indexed: 02/28/2025] Open
Abstract
We developed a dataset consisting of outbreak data collected from official, open-source surveillance reports representing more than 170 pathogens, 237 countries and territories, and more than 3300 events that occurred primarily between 1963 and 2023. Here we present and analyze a subset of these data, comprising a dataset of human epidemic events with onset between 2015 and 2020. Structuring of epidemiological data in the dataset follows a specific methodology to ensure consistency across all events. This methodology has been designed to produce the most reliable spatiotemporal view of an outbreak as possible. To ensure data are true-to-source, the structured data undergoes multiple rounds of both manual and automated review and validation. The extensive and standardized nature of the dataset makes it well-suited for both descriptive epidemiology and exploring outbreak dynamics and disease emergence.
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3
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Sundaram M, Dorado M, Akaribo B, Filion A, Han BA, Gottdenker NL, Schmidt JP, Drake JM, Stephens PR. Fruit-frugivore dependencies are important in Ebolavirus outbreaks in Sub-Saharan Africa. ECOGRAPHY 2024; 2024:e06950. [PMID: 40018392 PMCID: PMC11867621 DOI: 10.1111/ecog.06950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 02/27/2024] [Indexed: 03/01/2025]
Abstract
Ebolaviruses have the ability to infect a wide variety of species, with many African mammals potentially serving either as primary reservoirs or secondary amplifying hosts. Previous work has shown that frugivorous bats and primates are often associated with spillover and outbreaks. Yet the role that patterns of biodiversity, either of mammalian hosts or of common fruiting species such as Ficus (figs, fruit resources used by a wide variety of species), play in driving outbreak risk remains unclear. We investigated what factors most directly influence Ebolavirus outbreak risk in Sub-Saharan Africa by using a phylogenetically informed path analysis to compare a wide array of potential models (path diagrams) of spatial dynamics. We considered mammalian frugivore richness, cercopithecid and hominid primate richness, richness of pteropodid (fruit) bats, the spatial distribution of species that have tested positive for Ebolavirus antibodies in the wild, Ficus habitat suitability, and environmental conditions (mean annual and variability in temperature and rainfall). The proximate factors that most influenced whether a given host species range contained a site of a previous outbreak event were 1) habitat suitability for Ficus and 2) the diversity of cercopithecid primates. Frugivore richness overall (including bats, primates, and a few other mammals) and the richness of bats in the family Pteropodidae had a strong effect on which species tested positive for Ebolavirus antibodies, but did not influence outbreak risk directly in pathways explored. We interpret this as evidence that foraging around Ficus and frugivorous mammals (such as cercopithecid primates which are commonly hunted for food) play a prominent role in driving outbreaks into human communities, relative to other factors we considered which influence outbreak risk more indirectly.
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Affiliation(s)
- Mekala Sundaram
- Department of Integrative Biology, Oklahoma State University, Stillwater, OK, USA
- Department of Infectious Diseases and Savannah River Ecology Laboratory, University of Georgia, Aiken, SC, USA
| | | | - Benedicta Akaribo
- Department of Integrative Biology, Oklahoma State University, Stillwater, OK, USA
| | - Antoine Filion
- Department of Integrative Biology, Oklahoma State University, Stillwater, OK, USA
| | | | | | - John P. Schmidt
- Odum School of Ecology, University of Georgia, Athens, GA, USA
| | - John M. Drake
- Odum School of Ecology, University of Georgia, Athens, GA, USA
- Center for the Ecology of Infectious Diseases, University of Georgia, Athens, GA, USA
| | - Patrick R. Stephens
- Department of Integrative Biology, Oklahoma State University, Stillwater, OK, USA
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4
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Gonzalez A, Nikparvar B, Matson MJ, Seifert SN, Ross HD, Munster V, Bharti N. Human movement and transmission dynamics early in Ebola outbreaks. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.18.23300175. [PMID: 38196653 PMCID: PMC10775320 DOI: 10.1101/2023.12.18.23300175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
Human movement drives the transmission and spread of communicable pathogens. It is especially influential for emerging pathogens when population immunity is low and spillover events are rare. We digitized serial printed maps to measure transportation networks (roads and rivers) in Central and West Africa as proxies for population mobility to assess relationships between movement and Ebola transmission. We find that the lengths of roads and rivers in close proximity to spillover sites at or near the time of spillover events are significantly correlated with the number of EVD cases, particularly in the first 100 days of each outbreak. Early management and containment efforts along transportation networks may be beneficial in mitigation during the early days of transmission and spatial spread for Ebola outbreaks.
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Affiliation(s)
- Alexandria Gonzalez
- Biology Department and Center for Infectious Disease Dynamics, Penn State University, University Park, PA, 16802, USA
| | - Behnam Nikparvar
- Biology Department and Center for Infectious Disease Dynamics, Penn State University, University Park, PA, 16802, USA
| | - M. Jeremiah Matson
- University of Utah Health, Department of Internal Medicine, Salt Lake City, UT 84132, USA
| | - Stephanie N. Seifert
- Paul G. Allen School for Global Health, Washington State University, Pullman, WA, 99164 USA
| | - Heather D. Ross
- Donald W. Hamer Center for Maps and Geospatial Information, Penn State University Libraries, Penn State University, University Park, PA, 16802, USA
| | - Vincent Munster
- Division of Intramural Research, Laboratory of Virology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rocky Mountain Laboratories, Hamilton, Montana, 59840 USA
| | - Nita Bharti
- Biology Department and Center for Infectious Disease Dynamics, Penn State University, University Park, PA, 16802, USA
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5
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Mishra B, Rath S, Mohanty M, Mohapatra PR. The Threat of Impending Pandemics: A Proactive Approach. Cureus 2023; 15:e36723. [PMID: 37123718 PMCID: PMC10130798 DOI: 10.7759/cureus.36723] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/22/2023] [Indexed: 03/29/2023] Open
Abstract
The incessant occurrence of devastating health-related events, either on a large scale, such as pandemics, or in a local community in the form of sporadic outbreaks due to infectious agents, warrants a rapid, target-oriented, well-organized response team to combat the demonic consequences. While the world has been recovering from the clutches of the recent disastrous COVID-19 pandemic, the struggles against novel emerging and re-emerging pathogens such as monkeypox (mpox), newer evolving strains of influenza, Ebola, Zika, and the yellow fever virus continue to date. Therefore, a multisectoral, intercontinental, collaborative, interdisciplinary, and highly dedicated approach should always be implemented to achieve optimal health and avert future threats.
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Affiliation(s)
| | - Sutapa Rath
- Microbiology, All India Institute of Medical Sciences, Bhubaneswar, IND
| | - Monalisa Mohanty
- Microbiology, All India Institute of Medical Sciences, Bhubaneswar, IND
| | - Prasanta R Mohapatra
- Pulmonary Medicine and Critical Care, All India Institute of Medical Sciences, Bhubaneswar, IND
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Torres Munguía JA, Badarau FC, Díaz Pavez LR, Martínez-Zarzoso I, Wacker KM. A global dataset of pandemic- and epidemic-prone disease outbreaks. Sci Data 2022; 9:683. [PMID: 36357405 PMCID: PMC9648436 DOI: 10.1038/s41597-022-01797-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 10/20/2022] [Indexed: 11/12/2022] Open
Abstract
This paper presents a new dataset of infectious disease outbreaks collected from the Disease Outbreak News and the Coronavirus Dashboard produced by the World Health Organization. The dataset contains information on 70 infectious diseases and 2227 public health events that occurred over the period from January 1996 to March 2022 in 233 countries and territories around the world. We illustrate the potential use of this dataset to the research community by analysing the spatial distribution of disease outbreaks. We find evidence of spatial clusters of high incidences ("hot spots") in Africa, America, and Asia. This spatial analysis enables policymakers to identify the regions with the greatest likelihood of suffering from disease outbreaks and, taking into account their degree of preparedness and vulnerability, to develop policies that may help contain the spreading of future outbreaks. Further applications could focus on combining our data with other information sources to study, for instance, the link between environmental, globalization, and/or socioeconomic factors with disease outbreaks.
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Affiliation(s)
| | | | | | - Inmaculada Martínez-Zarzoso
- Faculty of Economic Sciences, Georg-August-Universität Göttingen, Göttingen, Germany
- Department of Economics, University Jaume I, Castelló de la Plana, Spain
| | - Konstantin M Wacker
- Faculty of Economics and Business, University of Groningen, Groningen, The Netherlands
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Yamaoka S, Ebihara H. Pathogenicity and Virulence of Ebolaviruses with Species- and Variant-specificity. Virulence 2021; 12:885-901. [PMID: 33734027 PMCID: PMC7993122 DOI: 10.1080/21505594.2021.1898169] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 02/10/2021] [Accepted: 02/19/2021] [Indexed: 01/05/2023] Open
Abstract
Ebola virus (EBOV), belonging to the species Zaire ebolavirus in the genus Ebolavirus, causes a severe febrile illness in humans with case fatality rates (CFRs) up to 90%. While there have been six virus species classified, which each have a single type virus in the genus Ebolavirus, CFRs of ebolavirus infections vary among viruses belonging to each distinct species. In this review, we aim to define the ebolavirus species-specific virulence on the basis of currently available laboratory and experimental findings. In addition, this review will also cover the variant-specific virulence of EBOV by referring to the unique biological and pathogenic characteristics of EBOV variant Makona, a new EBOV variant isolated from the 2013-2016 EBOV disease outbreak in West Africa. A better definition of species-specific and variant-specific virulence of ebolaviruses will facilitate our comprehensive knowledge on genus Ebolavirus biology, leading to the development of therapeutics against well-focused pathogenic mechanisms of each Ebola disease.
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Affiliation(s)
- Satoko Yamaoka
- Department of Molecular Medicine, Mayo Clinic, Rochester, USA
| | - Hideki Ebihara
- Department of Molecular Medicine, Mayo Clinic, Rochester, USA
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8
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Lee-Cruz L, Lenormand M, Cappelle J, Caron A, De Nys H, Peeters M, Bourgarel M, Roger F, Tran A. Mapping of Ebola virus spillover: Suitability and seasonal variability at the landscape scale. PLoS Negl Trop Dis 2021; 15:e0009683. [PMID: 34424896 PMCID: PMC8425568 DOI: 10.1371/journal.pntd.0009683] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Revised: 09/08/2021] [Accepted: 07/26/2021] [Indexed: 01/06/2023] Open
Abstract
The unexpected Ebola virus outbreak in West Africa in 2014 involving the Zaire ebolavirus made clear that other regions outside Central Africa, its previously documented niche, were at risk of future epidemics. The complex transmission cycle and a lack of epidemiological data make mapping areas at risk of the disease challenging. We used a Geographic Information System-based multicriteria evaluation (GIS-MCE), a knowledge-based approach, to identify areas suitable for Ebola virus spillover to humans in regions of Guinea, Congo and Gabon where Ebola viruses already emerged. We identified environmental, climatic and anthropogenic risk factors and potential hosts from a literature review. Geographical data layers, representing risk factors, were combined to produce suitability maps of Ebola virus spillover at the landscape scale. Our maps show high spatial and temporal variability in the suitability for Ebola virus spillover at a fine regional scale. Reported spillover events fell in areas of intermediate to high suitability in our maps, and a sensitivity analysis showed that the maps produced were robust. There are still important gaps in our knowledge about what factors are associated with the risk of Ebola virus spillover. As more information becomes available, maps produced using the GIS-MCE approach can be easily updated to improve surveillance and the prevention of future outbreaks. Ebola virus disease is a highly pathogenic disease transmitted from wildlife to humans. It was first described in 1976 and its distribution remained restricted to Central Africa until 2014, when an outbreak in West Africa, causing more than 28,000 cases and more than 11,000 deaths, took place. Anthropogenic factors, such as bushmeat hunting, trade and consumption, and environmental and climatic factors, may promote the contact between humans and infected animals, such as bats, primates and duikers, increasing the risk of virus transmission to the human population. In this study, we used the spatial multicriteria evaluation framework to gather all available information on risk factors and animal species susceptible to infection, and produce maps of areas suitable for Ebola virus spillover in regions in Guinea, Congo and Gabon. The resulting maps highlighted high spatial and temporal variability in the suitability for Ebola virus spillover. Data from reported cases of Ebola virus transmission from wild animals to humans were used to validate the maps. The approach developed is capable of integrating a wide diversity of risk factors, and provides a flexible and simple tool for surveillance, which can be updated as more data and knowledge on risk factors become available.
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Affiliation(s)
- Larisa Lee-Cruz
- CIRAD, UMR ASTRE, Montpellier, France
- ASTRE, Univ Montpellier, CIRAD, INRAE, Montpellier, France
- CIRAD, UMR TETIS, Montpellier, France
- TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE, Montpellier, France
| | - Maxime Lenormand
- TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE, Montpellier, France
| | - Julien Cappelle
- CIRAD, UMR ASTRE, Montpellier, France
- ASTRE, Univ Montpellier, CIRAD, INRAE, Montpellier, France
| | - Alexandre Caron
- CIRAD, UMR ASTRE, Montpellier, France
- ASTRE, Univ Montpellier, CIRAD, INRAE, Montpellier, France
- Faculdade Veterinaria, Universidade Eduardo Mondlane, Maputo, Mozambique
| | - Hélène De Nys
- ASTRE, Univ Montpellier, CIRAD, INRAE, Montpellier, France
- CIRAD, UMR ASTRE, Harare, Zimbabwe
| | - Martine Peeters
- TransVIHMI, IRD, INSERM, Univ Montpellier, Montpellier, France
| | - Mathieu Bourgarel
- ASTRE, Univ Montpellier, CIRAD, INRAE, Montpellier, France
- CIRAD, UMR ASTRE, Harare, Zimbabwe
| | - François Roger
- CIRAD, UMR ASTRE, Montpellier, France
- ASTRE, Univ Montpellier, CIRAD, INRAE, Montpellier, France
| | - Annelise Tran
- CIRAD, UMR ASTRE, Montpellier, France
- ASTRE, Univ Montpellier, CIRAD, INRAE, Montpellier, France
- CIRAD, UMR TETIS, Montpellier, France
- TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE, Montpellier, France
- * E-mail:
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9
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Zeng Z, Fan Y, Quan X, Yu H, Chen S, Zhang S. Energy-transfer-mediated oxygen activation in carbonyl functionalized carbon nitride nanosheets for high-efficient photocatalytic water disinfection and organic pollutants degradation. WATER RESEARCH 2020; 177:115798. [PMID: 32305702 DOI: 10.1016/j.watres.2020.115798] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 03/14/2020] [Accepted: 04/03/2020] [Indexed: 06/11/2023]
Abstract
Polymeric photocatalysts are promising candidates for water purification, however their catalytic performance are still unsatisfactory due to the fast charge recombination that leads to low reactive oxygen radicals production. In this study, a conceptual energy-transfer-mediated photocatalytic oxygen activation system over polymeric carbon nitride without the need of electron-hole separation is proposed, exhibiting remarkable singlet oxygen triggered bacteria inactivation performance as well as organic pollutants degradation. By structure and excitonic effect modulation, the oxygen activation process changes from the traditional electron-transfer mechanism to the final energy-transfer pathway, leading to the selective generation of singlet oxygen with high efficiency. The generated singlet oxygen is found to fervently attack the bacteria membrane, creating irreparable pores or holes on the cell membrane for cytoplasmic contents leaking out to accelerate bacteria destruction. The work demonstrated here offers a new photocatalytic oxygen activation pathway for achieving high-efficient reactive oxygen species generation performance without the need of charge separation.
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Affiliation(s)
- Zhenxing Zeng
- Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education), School of Environmental Science and Technology, Dalian University of Technology, Dalian, 116024, China
| | - Yaofang Fan
- Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education), School of Environmental Science and Technology, Dalian University of Technology, Dalian, 116024, China
| | - Xie Quan
- Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education), School of Environmental Science and Technology, Dalian University of Technology, Dalian, 116024, China.
| | - Hongtao Yu
- Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education), School of Environmental Science and Technology, Dalian University of Technology, Dalian, 116024, China
| | - Shuo Chen
- Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education), School of Environmental Science and Technology, Dalian University of Technology, Dalian, 116024, China
| | - Shushen Zhang
- Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education), School of Environmental Science and Technology, Dalian University of Technology, Dalian, 116024, China
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10
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Madelain V, Duthey A, Mentré F, Jacquot F, Solas C, Lacarelle B, Vallvé A, Barron S, Barrot L, Mundweiler S, Thomas D, Carbonnelle C, Raoul H, de Lamballerie X, Guedj J. Ribavirin does not potentiate favipiravir antiviral activity against Ebola virus in non-human primates. Antiviral Res 2020; 177:104758. [PMID: 32135218 DOI: 10.1016/j.antiviral.2020.104758] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Revised: 02/24/2020] [Accepted: 02/26/2020] [Indexed: 01/26/2023]
Abstract
BACKGROUND In spite of recurrent and dramatic outbreaks, there are no therapeutics approved against Ebola virus disease. Favipiravir, a RNA polymerase inhibitor active against several RNA viruses, recently demonstrated significant but not complete protection in a non-human primate model of Ebola virus disease. In this study, we assessed the benefit of the combination of favipiravir and ribavirin, another broad spectrum antiviral agent, in the same model. METHODS 15 female cynomolgus macaques were challenged intramuscularly with 1,000 FFU of Ebola virus Gabon 2001 strain and followed for 21 days. All animals received favipiravir 180 mg/kg twice a day (BID), either as monotherapy (n = 5) or in combination with ribavirin (n = 10). Ribavirin was given either at the dose 10 mg/kg BID (n = 5) or 5 mg/kg BID (n = 5). Favipiravir and ribavirin were initiated two and one days before viral challenge respectively and treatment were continued for 14 days. Treatment effects on viral and hematological markers were assessed using a mathematical model. Survival rate of 0% and 20% were obtained in macaques receiving favipiravir plus ribavirin 10 and 5 mg/kg BID, respectively, compared to 40% in the favipiravir monotherapy group (P = 0.061 when comparing monotherapy and bitherapy, log rank). Viral dynamic modeling analysis did not identify an association between plasma concentrations of ribavirin and viral load levels. Using a model of erythropoiesis, plasma concentrations of ribavirin were strongly associated with a hemoglobin drop (p = 0.0015). CONCLUSION Ribavirin plus favipiravir did not extend survival rates and did not lower viral replication rate compared to favipiravir monotherapy in this animal model. Patients receiving this combination in other indications, such as Lassa fever, should be closely monitored to prevent potential toxicity associated with anemia.
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Affiliation(s)
| | - Aurélie Duthey
- Laboratoire P4 Inserm-Jean Mérieux, US003 Inserm, 69365, Lyon, France
| | - France Mentré
- Université de Paris, IAME, INSERM, F-75018, Paris, France
| | - Frédéric Jacquot
- Laboratoire P4 Inserm-Jean Mérieux, US003 Inserm, 69365, Lyon, France
| | - Caroline Solas
- Aix-Marseille Univ, APHM, UMR "Emergence des Pathologies Virales" IRD190-Inserm1207-EHESP, Laboratoire Pharmacocinétique-Toxicologie, Hôpital La Timone, 13005, Marseille, France
| | - Bruno Lacarelle
- Aix-Marseille Univ, APHM, UMR "Emergence des Pathologies Virales" IRD190-Inserm1207-EHESP, Laboratoire Pharmacocinétique-Toxicologie, Hôpital La Timone, 13005, Marseille, France
| | - Audrey Vallvé
- Laboratoire P4 Inserm-Jean Mérieux, US003 Inserm, 69365, Lyon, France
| | - Stéphane Barron
- Laboratoire P4 Inserm-Jean Mérieux, US003 Inserm, 69365, Lyon, France
| | - Laura Barrot
- Laboratoire P4 Inserm-Jean Mérieux, US003 Inserm, 69365, Lyon, France
| | | | - Damien Thomas
- Laboratoire P4 Inserm-Jean Mérieux, US003 Inserm, 69365, Lyon, France
| | | | - Hervé Raoul
- Laboratoire P4 Inserm-Jean Mérieux, US003 Inserm, 69365, Lyon, France
| | - Xavier de Lamballerie
- UMR "Emergence des Pathologies Virales" (EPV: Aix-Marseille University - IRD 190 - Inserm 1207 - EHESP), Institut Hospitalo-Universitaire Méditerranée Infection, F-13385, Marseille, France
| | - Jérémie Guedj
- Université de Paris, IAME, INSERM, F-75018, Paris, France.
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11
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Shapiro JT, Sovie AR, Faller CR, Monadjem A, Fletcher RJ, McCleery RA. Ebola spillover correlates with bat diversity. EUR J WILDLIFE RES 2020. [DOI: 10.1007/s10344-019-1346-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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12
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Ramshaw RE, Letourneau ID, Hong AY, Hon J, Morgan JD, Osborne JCP, Shirude S, Van Kerkhove MD, Hay SI, Pigott DM. A database of geopositioned Middle East Respiratory Syndrome Coronavirus occurrences. Sci Data 2019; 6:318. [PMID: 31836720 PMCID: PMC6911100 DOI: 10.1038/s41597-019-0330-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Accepted: 11/15/2019] [Indexed: 12/21/2022] Open
Abstract
As a World Health Organization Research and Development Blueprint priority pathogen, there is a need to better understand the geographic distribution of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and its potential to infect mammals and humans. This database documents cases of MERS-CoV globally, with specific attention paid to zoonotic transmission. An initial literature search was conducted in PubMed, Web of Science, and Scopus; after screening articles according to the inclusion/exclusion criteria, a total of 208 sources were selected for extraction and geo-positioning. Each MERS-CoV occurrence was assigned one of the following classifications based upon published contextual information: index, unspecified, secondary, mammal, environmental, or imported. In total, this database is comprised of 861 unique geo-positioned MERS-CoV occurrences. The purpose of this article is to share a collated MERS-CoV database and extraction protocol that can be utilized in future mapping efforts for both MERS-CoV and other infectious diseases. More broadly, it may also provide useful data for the development of targeted MERS-CoV surveillance, which would prove invaluable in preventing future zoonotic spillover. Measurement(s) | Middle East Respiratory Syndrome • geographic location | Technology Type(s) | digital curation | Factor Type(s) | geographic distribution of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) • year | Sample Characteristic - Organism | Middle East respiratory syndrome-related coronavirus | Sample Characteristic - Location | Earth (planet) |
Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11108801
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Affiliation(s)
- Rebecca E Ramshaw
- Institute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave., Suite 600, Seattle, WA, United States
| | - Ian D Letourneau
- Institute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave., Suite 600, Seattle, WA, United States
| | - Amy Y Hong
- Bloomberg School of Public Health, Johns Hopkins University, 615N Wolfe St, Baltimore, MD, 21205, United States
| | - Julia Hon
- Institute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave., Suite 600, Seattle, WA, United States
| | - Julia D Morgan
- Institute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave., Suite 600, Seattle, WA, United States
| | - Joshua C P Osborne
- Institute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave., Suite 600, Seattle, WA, United States
| | - Shreya Shirude
- Institute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave., Suite 600, Seattle, WA, United States
| | - Maria D Van Kerkhove
- Department of Infectious Hazards Management, Health Emergencies Programme, World Health Organization, Avenue Appia 20, 1211, Geneva, Switzerland
| | - Simon I Hay
- Institute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave., Suite 600, Seattle, WA, United States.,Department of Health Metrics Sciences, School of Medicine, University of Washington, 2301 5th Ave., Suite 600, Seattle, WA, United States
| | - David M Pigott
- Institute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave., Suite 600, Seattle, WA, United States. .,Department of Health Metrics Sciences, School of Medicine, University of Washington, 2301 5th Ave., Suite 600, Seattle, WA, United States.
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13
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Timothy JWS, Hall Y, Akoi-Boré J, Diallo B, Tipton TRW, Bower H, Strecker T, Glynn JR, Carroll MW. Early transmission and case fatality of Ebola virus at the index site of the 2013-16 west African Ebola outbreak: a cross-sectional seroprevalence survey. THE LANCET. INFECTIOUS DISEASES 2019; 19:429-438. [PMID: 30799252 PMCID: PMC6437313 DOI: 10.1016/s1473-3099(18)30791-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Revised: 11/15/2018] [Accepted: 12/06/2018] [Indexed: 12/12/2022]
Abstract
BACKGROUND To date, epidemiological studies at the index site of the 2013-16 west African Ebola outbreak in Meliandou, Guinea, have been restricted in their scope. We aimed to determine the occurrence of previously undocumented Ebola virus disease (EVD) cases and infections, and to reconstruct transmission events. METHODS This cross-sectional seroprevalence survey of the adult population of Meliandou used a highly specific oral fluid test and detailed interviews of all households in the village and key informants. Each household was interviewed, with all members prompted to describe the events of the outbreak, any illness within the household, and possible contact with suspected cases. Information for deceased individuals was provided by relatives living in the same household. Symptoms were based on Ebola virus Makona variant EVD case definitions (focusing on fever, vomiting, and diarrhoea). For antibody testing, we used an Ebola virus glycoprotein IgG capture enzyme immunoassay developed from a previously validated assay. A maximum exposure level was assigned to every participant using a predetermined scale. We used a generalised linear model (logit function) to estimate odds ratios for the association of sociodemographic variables and exposure level with Ebola virus infection. We adjusted estimates for age and maximum exposure, as appropriate. FINDINGS Between June 22, and July 9, 2017, we enrolled 237 participants from 27 households in Meliandou. Two households refused to participate and one was absent. All adults in participating households who were present for the interview provided an oral fluid swab for testing, of which 224 were suitable for analysis. In addition to the 11 EVD deaths described previously, on the basis of clinical description and oral fluid testing, we found two probable EVD deaths and eight previously unrecognised anti-Ebola virus IgG-positive survivors, including one who had mild symptoms and one who was asymptomatic, resulting in a case fatality of 55·6% (95% CI 30·8-78·5) for adults. Health-care work (adjusted odds ratio 6·64, 1·54-28·56; p=0·001) and level of exposure (odds ratio adjusted for linear trend across five levels 2·79, 1·59-4·883; p<0·0001) were independent risk factors for infection. INTERPRETATION Ebola virus infection was more widespread in this spillover population than previously recognised (21 vs 11 cases). We show the first serological evidence of survivors in this population (eight anti-Ebola virus IgG seropositive) and report a case fatality lower than previously reported (55·6% vs 100% in adults). These data show the high community coverage achievable by using a non-invasive test and, by accurately documenting the beginnings of the west African Ebola virus outbreak, reveal important insight into transmission dynamics and risk factors that underpin Ebola virus spillover events. FUNDING US Food and Drug Administration, Wellcome Trust, and German Research Council.
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Affiliation(s)
| | - Yper Hall
- Research and Development Institute, National Infection Service, Public Health England, Porton Down, Salisbury, UK
| | - Joseph Akoi-Boré
- Public Health England/Tropical Medicine Institute Berlin Reference Laboratory, Guéckédou, Guinea
| | - Boubacar Diallo
- World Health Organization, Regional Office for Africa, Brazzaville, Republic of Congo
| | - Thomas R W Tipton
- Research and Development Institute, National Infection Service, Public Health England, Porton Down, Salisbury, UK
| | - Hilary Bower
- London School of Hygiene & Tropical Medicine, London, UK
| | - Thomas Strecker
- Institute of Virology, Philipps University, Marburg, Germany
| | - Judith R Glynn
- London School of Hygiene & Tropical Medicine, London, UK
| | - Miles W Carroll
- Research and Development Institute, National Infection Service, Public Health England, Porton Down, Salisbury, UK
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Kraemer MUG, Golding N, Bisanzio D, Bhatt S, Pigott DM, Ray SE, Brady OJ, Brownstein JS, Faria NR, Cummings DAT, Pybus OG, Smith DL, Tatem AJ, Hay SI, Reiner RC. Utilizing general human movement models to predict the spread of emerging infectious diseases in resource poor settings. Sci Rep 2019; 9:5151. [PMID: 30914669 PMCID: PMC6435716 DOI: 10.1038/s41598-019-41192-3] [Citation(s) in RCA: 63] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Accepted: 03/03/2019] [Indexed: 12/03/2022] Open
Abstract
Human mobility is an important driver of geographic spread of infectious pathogens. Detailed information about human movements during outbreaks are, however, difficult to obtain and may not be available during future epidemics. The Ebola virus disease (EVD) outbreak in West Africa between 2014-16 demonstrated how quickly pathogens can spread to large urban centers following one cross-species transmission event. Here we describe a flexible transmission model to test the utility of generalised human movement models in estimating EVD cases and spatial spread over the course of the outbreak. A transmission model that includes a general model of human mobility significantly improves prediction of EVD's incidence compared to models without this component. Human movement plays an important role not only to ignite the epidemic in locations previously disease free, but over the course of the entire epidemic. We also demonstrate important differences between countries in population mixing and the improved prediction attributable to movement metrics. Given their relative rareness, locally derived mobility data are unlikely to exist in advance of future epidemics or pandemics. Our findings show that transmission patterns derived from general human movement models can improve forecasts of spatio-temporal transmission patterns in places where local mobility data is unavailable.
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Affiliation(s)
- M U G Kraemer
- Department of Zoology, University of Oxford, Oxford, UK.
- Harvard Medical School, Boston, MA, USA.
- Computational Epidemiology Lab, Boston Children's Hospital, Boston, MA, USA.
| | - N Golding
- Department of BioSciences, University of Melbourne, Parkville, VIC, Australia
| | - D Bisanzio
- RTI International, Washington, D.C., USA
- Epidemiology and Public Health Division, School of Medicine, University of Nottingham, Nottingham, UK
| | - S Bhatt
- Imperial College London, London, United Kingdom
| | - D M Pigott
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - S E Ray
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - O J Brady
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - J S Brownstein
- Harvard Medical School, Boston, MA, USA
- Computational Epidemiology Lab, Boston Children's Hospital, Boston, MA, USA
| | - N R Faria
- Department of Zoology, University of Oxford, Oxford, UK
| | - D A T Cummings
- Department of Biology, University of Florida, Gainesville, FL, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA
| | - O G Pybus
- Department of Zoology, University of Oxford, Oxford, UK
| | - D L Smith
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Sanaria Institute for Global Health and Tropical Medicine, Rockville, USA
| | - A J Tatem
- WorldPop, Department of Geography and Environmental Sciences, University of Southampton, Southampton, UK
- Flowminder Foundation, Stockholm, Sweden
| | - S I Hay
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
| | - R C Reiner
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
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15
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De Nys HM, Kingebeni PM, Keita AK, Butel C, Thaurignac G, Villabona-Arenas CJ, Lemarcis T, Geraerts M, Vidal N, Esteban A, Bourgarel M, Roger F, Leendertz F, Diallo R, Ndimbo-Kumugo SP, Nsio-Mbeta J, Tagg N, Koivogui L, Toure A, Delaporte E, Ahuka-Mundeke S, Tamfum JJM, Mpoudi-Ngole E, Ayouba A, Peeters M. Survey of Ebola Viruses in Frugivorous and Insectivorous Bats in Guinea, Cameroon, and the Democratic Republic of the Congo, 2015-2017. Emerg Infect Dis 2018; 24:2228-2240. [PMID: 30307845 PMCID: PMC6256401 DOI: 10.3201/eid2412.180740] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
To clarify the role of bats in the ecology of Ebola viruses, we assessed the prevalence of Ebola virus antibodies in a large-scale sample of bats collected during 2015–2017 from countries in Africa that have had previous Ebola outbreaks (Guinea, the Democratic Republic of the Congo) or are at high risk for outbreaks (Cameroon). We analyzed 4,022 blood samples of bats from >12 frugivorous and 27 insectivorous species; 2–37 (0.05%–0.92%) bats were seropositive for Zaire and 0–30 (0%–0.75%) bats for Sudan Ebola viruses. We observed Ebola virus antibodies in 1 insectivorous bat genus and 6 frugivorous bat species. Certain bat species widespread across Africa had serologic evidence of Zaire and Sudan Ebola viruses. No viral RNA was detected in the subset of samples tested (n = 665). Ongoing surveillance of bats and other potential animal reservoirs are required to predict and prepare for future outbreaks.
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16
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Schmidt JP, Park AW, Kramer AM, Han BA, Alexander LW, Drake JM. Spatiotemporal Fluctuations and Triggers of Ebola Virus Spillover. Emerg Infect Dis 2018; 23:415-422. [PMID: 28221131 PMCID: PMC5382727 DOI: 10.3201/eid2303.160101] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Because the natural reservoir of Ebola virus remains unclear and disease
outbreaks in humans have occurred only sporadically over a large region,
forecasting when and where Ebola spillovers are most likely to occur constitutes
a continuing and urgent public health challenge. We developed a statistical
modeling approach that associates 37 human or great ape Ebola spillovers since
1982 with spatiotemporally dynamic covariates including vegetative cover, human
population size, and absolute and relative rainfall over 3 decades across
sub-Saharan Africa. Our model (area under the curve 0.80 on test data) shows
that spillover intensity is highest during transitions between wet and dry
seasons; overall, high seasonal intensity occurs over much of tropical Africa;
and spillover intensity is greatest at high (>1,000/km2) and very
low (<100/km2) human population densities compared with
intermediate levels. These results suggest strong seasonality in Ebola spillover
from wild reservoirs and indicate particular times and regions for targeted
surveillance.
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17
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Pigott DM, Deshpande A, Letourneau I, Morozoff C, Reiner RC, Kraemer MUG, Brent SE, Bogoch II, Khan K, Biehl MH, Burstein R, Earl L, Fullman N, Messina JP, Mylne AQN, Moyes CL, Shearer FM, Bhatt S, Brady OJ, Gething PW, Weiss DJ, Tatem AJ, Caley L, De Groeve T, Vernaccini L, Golding N, Horby P, Kuhn JH, Laney SJ, Ng E, Piot P, Sankoh O, Murray CJL, Hay SI. Local, national, and regional viral haemorrhagic fever pandemic potential in Africa: a multistage analysis. Lancet 2017; 390:2662-2672. [PMID: 29031848 PMCID: PMC5735217 DOI: 10.1016/s0140-6736(17)32092-5] [Citation(s) in RCA: 68] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2017] [Revised: 07/18/2017] [Accepted: 07/20/2017] [Indexed: 01/03/2023]
Abstract
BACKGROUND Predicting when and where pathogens will emerge is difficult, yet, as shown by the recent Ebola and Zika epidemics, effective and timely responses are key. It is therefore crucial to transition from reactive to proactive responses for these pathogens. To better identify priorities for outbreak mitigation and prevention, we developed a cohesive framework combining disparate methods and data sources, and assessed subnational pandemic potential for four viral haemorrhagic fevers in Africa, Crimean-Congo haemorrhagic fever, Ebola virus disease, Lassa fever, and Marburg virus disease. METHODS In this multistage analysis, we quantified three stages underlying the potential of widespread viral haemorrhagic fever epidemics. Environmental suitability maps were used to define stage 1, index-case potential, which assesses populations at risk of infection due to spillover from zoonotic hosts or vectors, identifying where index cases could present. Stage 2, outbreak potential, iterates upon an existing framework, the Index for Risk Management, to measure potential for secondary spread in people within specific communities. For stage 3, epidemic potential, we combined local and international scale connectivity assessments with stage 2 to evaluate possible spread of local outbreaks nationally, regionally, and internationally. FINDINGS We found epidemic potential to vary within Africa, with regions where viral haemorrhagic fever outbreaks have previously occurred (eg, western Africa) and areas currently considered non-endemic (eg, Cameroon and Ethiopia) both ranking highly. Tracking transitions between stages showed how an index case can escalate into a widespread epidemic in the absence of intervention (eg, Nigeria and Guinea). Our analysis showed Chad, Somalia, and South Sudan to be highly susceptible to any outbreak at subnational levels. INTERPRETATION Our analysis provides a unified assessment of potential epidemic trajectories, with the aim of allowing national and international agencies to pre-emptively evaluate needs and target resources. Within each country, our framework identifies at-risk subnational locations in which to improve surveillance, diagnostic capabilities, and health systems in parallel with the design of policies for optimal responses at each stage. In conjunction with pandemic preparedness activities, assessments such as ours can identify regions where needs and provisions do not align, and thus should be targeted for future strengthening and support. FUNDING Paul G Allen Family Foundation, Bill & Melinda Gates Foundation, Wellcome Trust, UK Department for International Development.
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Affiliation(s)
- David M Pigott
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Aniruddha Deshpande
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Ian Letourneau
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Chloe Morozoff
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Robert C Reiner
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Moritz U G Kraemer
- Department of Zoology, University of Oxford, Oxford, UK; Harvard Medical School, Harvard University, Boston, MA, USA; Boston Children's Hospital, Boston, MA, USA
| | - Shannon E Brent
- Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, ON, Canada
| | - Isaac I Bogoch
- Divisions of General Internal Medicine and Infectious Diseases, Toronto General Hospital, Toronto, ON, Canada; Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Kamran Khan
- Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, ON, Canada
| | - Molly H Biehl
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Roy Burstein
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Lucas Earl
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Nancy Fullman
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Jane P Messina
- School of Geography and the Environment, University of Oxford, Oxford, UK; School of Interdisciplinary Area Studies, University of Oxford, Oxford, UK
| | | | - Catherine L Moyes
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Freya M Shearer
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Samir Bhatt
- Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Oliver J Brady
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Peter W Gething
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Daniel J Weiss
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Andrew J Tatem
- WorldPop, Department of Geography and Environment, University of Southampton, Southampton, UK; Flowminder Foundation, Stockholm Sweden
| | | | - Tom De Groeve
- European Commission, Joint Research Centre, Ispra, Italy
| | | | - Nick Golding
- Quantitative and Applied Ecology Group, School of BioSciences, University of Melbourne, Parkville, VIC, Australia
| | - Peter Horby
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Jens H Kuhn
- Integrated Research Facility at Fort Detrick, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Frederick, MD, USA
| | | | - Edmond Ng
- Director's Office, London School of Hygiene & Tropical Medicine, London, UK
| | - Peter Piot
- Director's Office, London School of Hygiene & Tropical Medicine, London, UK
| | | | | | - Simon I Hay
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
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18
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Nyakarahuka L, Ayebare S, Mosomtai G, Kankya C, Lutwama J, Mwiine FN, Skjerve E. Ecological Niche Modeling for Filoviruses: A Risk Map for Ebola and Marburg Virus Disease Outbreaks in Uganda. PLOS CURRENTS 2017; 9:ecurrents.outbreaks.07992a87522e1f229c7cb023270a2af1. [PMID: 29034123 PMCID: PMC5614672 DOI: 10.1371/currents.outbreaks.07992a87522e1f229c7cb023270a2af1] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
INTRODUCTION Uganda has reported eight outbreaks caused by filoviruses between 2000 to 2016, more than any other country in the world. We used species distribution modeling to predict where filovirus outbreaks are likely to occur in Uganda to help in epidemic preparedness and surveillance. METHODS The MaxEnt software, a machine learning modeling approach that uses presence-only data was used to establish filovirus - environmental relationships. Presence-only data for filovirus outbreaks were collected from the field and online sources. Environmental covariates from Africlim that have been downscaled to a nominal resolution of 1km x 1km were used. The final model gave the relative probability of the presence of filoviruses in the study area obtained from an average of 100 bootstrap runs. Model evaluation was carried out using Receiver Operating Characteristic (ROC) plots. Maps were created using ArcGIS 10.3 mapping software. RESULTS We showed that bats as potential reservoirs of filoviruses are distributed all over Uganda. Potential outbreak areas for Ebola and Marburg virus disease were predicted in West, Southwest and Central parts of Uganda, which corresponds to bat distribution and previous filovirus outbreaks areas. Additionally, the models predicted the Eastern Uganda region and other areas that have not reported outbreaks before to be potential outbreak hotspots. Rainfall variables were the most important in influencing model prediction compared to temperature variables. CONCLUSIONS Despite the limitations in the prediction model due to lack of adequate sample records for outbreaks, especially for the Marburg cases, the models provided risk maps to the Uganda surveillance system on filovirus outbreaks. The risk maps will aid in identifying areas to focus the filovirus surveillance for early detection and responses hence curtailing a pandemic. The results from this study also confirm previous findings that suggest that filoviruses are mainly limited by the amount of rainfall received in an area.
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Affiliation(s)
- Luke Nyakarahuka
- 1) Department of Food Safety and Infection Biology, Norwegian University of Life Sciences, Oslo, Norway; 2) Department of Biosecurity, Ecosystems and Veterinary Public Health, Makerere University, Kampala Uganda; 3) Department of Arbovirology, Emerging and Re-Emerging disease, Uganda Virus Research Institute, Entebbe, Uganda
| | - Samuel Ayebare
- Climate Change and Biodiversity Unit, Wildlife Conservation Society, Bronx, New York, United States of America
| | - Gladys Mosomtai
- Earth Observation Unit, International Centre for Insect Physiology and Ecology, Nairobi, Kenya
| | - Clovice Kankya
- Department of Biosecurity, Ecosystems and Veterinary Public Health, Makerere University, Kampala, Uganda
| | - Julius Lutwama
- Department of Arbovirology, Emerging and Re-Emerging diseases, Uganda Virus Research Institute, Entebbe, Uganda
| | - Frank Norbert Mwiine
- Department of Biomolecular Resources and Biolab Sciences, Makerere University, Kampala, Uganda
| | - Eystein Skjerve
- Department of Food Safety and Infection Biology, Norwegian University of Life Sciences, Oslo, Norway
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19
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Longbottom J, Browne AJ, Pigott DM, Sinka ME, Golding N, Hay SI, Moyes CL, Shearer FM. Mapping the spatial distribution of the Japanese encephalitis vector, Culex tritaeniorhynchus Giles, 1901 (Diptera: Culicidae) within areas of Japanese encephalitis risk. Parasit Vectors 2017; 10:148. [PMID: 28302156 PMCID: PMC5356256 DOI: 10.1186/s13071-017-2086-8] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2016] [Accepted: 03/10/2017] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Japanese encephalitis (JE) is one of the most significant aetiological agents of viral encephalitis in Asia. This medically important arbovirus is primarily spread from vertebrate hosts to humans by the mosquito vector Culex tritaeniorhynchus. Knowledge of the contemporary distribution of this vector species is lacking, and efforts to define areas of disease risk greatly depend on a thorough understanding of the variation in this mosquito's geographical distribution. RESULTS We assembled a contemporary database of Cx. tritaeniorhynchus presence records within Japanese encephalitis risk areas from formal literature and other relevant resources, resulting in 1,045 geo-referenced, spatially and temporally unique presence records spanning from 1928 to 2014 (71.9% of records obtained between 2001 and 2014). These presence data were combined with a background dataset capturing sample bias in our presence dataset, along with environmental and socio-economic covariates, to inform a boosted regression tree model predicting environmental suitability for Cx. tritaeniorhynchus at each 5 × 5 km gridded cell within areas of JE risk. The resulting fine-scale map highlights areas of high environmental suitability for this species across India, Nepal and China that coincide with areas of high JE incidence, emphasising the role of this vector in disease transmission and the utility of the map generated. CONCLUSIONS Our map contributes towards efforts determining the spatial heterogeneity in Cx. tritaeniorhynchus distribution within the limits of JE transmission. Specifically, this map can be used to inform vector control programs and can be used to identify key areas where the prevention of Cx. tritaeniorhynchus establishment should be a priority.
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Affiliation(s)
- Joshua Longbottom
- Spatial Ecology & Epidemiology Group, Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Annie J. Browne
- Spatial Ecology & Epidemiology Group, Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - David M. Pigott
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA USA
| | - Marianne E. Sinka
- Oxford Long Term Ecology Laboratory, Department of Zoology, University of Oxford, Oxford, UK
| | - Nick Golding
- Quantitative & Applied Ecology Group, School of BioSciences, University of Melbourne, Parkville, VIC Australia
| | - Simon I. Hay
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA USA
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Catherine L. Moyes
- Spatial Ecology & Epidemiology Group, Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Freya M. Shearer
- Spatial Ecology & Epidemiology Group, Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
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20
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Schmidt JP, Park AW, Kramer AM, Han BA, Alexander LW, Drake JM. Spatiotemporal Fluctuations and Triggers of Ebola Virus Spillover. Emerg Infect Dis 2017. [DOI: 10.3201/eid2302.160101] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
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22
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Peterson AT, Samy AM. Geographic potential of disease caused by Ebola and Marburg viruses in Africa. Acta Trop 2016; 162:114-124. [PMID: 27311387 DOI: 10.1016/j.actatropica.2016.06.012] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2016] [Revised: 06/04/2016] [Accepted: 06/10/2016] [Indexed: 01/17/2023]
Abstract
Filoviruses represent a significant public health threat worldwide. West Africa recently experienced the largest-scale and most complex filovirus outbreak yet known, which underlines the need for a predictive understanding of the geographic distribution and potential for transmission to humans of these viruses. Here, we used ecological niche modeling techniques to understand the relationship between known filovirus occurrences and environmental characteristics. Our study derived a picture of the potential transmission geography of Ebola virus species and Marburg, paired with views of the spatial uncertainty associated with model-to-model variation in our predictions. We found that filovirus species have diverged ecologically, but only three species are sufficiently well known that models could be developed with significant predictive power. We quantified uncertainty in predictions, assessed potential for outbreaks outside of known transmission areas, and highlighted the Ethiopian Highlands and scattered areas across East Africa as additional potentially unrecognized transmission areas.
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Affiliation(s)
| | - Abdallah M Samy
- Biodiversity Institute, The University of Kansas, Lawrence, KS, 66045, USA; Faculty of Science, Ain Shams University, Abbassia, Cairo, 11566, Egypt.
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23
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Wolf M. Rethinking Urban Epidemiology: Natures, Networks and Materialities. INTERNATIONAL JOURNAL OF URBAN AND REGIONAL RESEARCH 2016; 40:958-982. [PMID: 32336869 PMCID: PMC7165666 DOI: 10.1111/1468-2427.12381] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
How should we understand the relationship between urban environments and infectious diseases? This article addresses this question from three particular perspectives: that of the materialities of health, that of nature and that of networks. The first perspective analytically blends biological dynamics, environmental influence and social practice. The second perspective, mainly influenced by multispecies ethnographies, foregrounds the liveliness and unboundedness of cities. Finally, the third perspective analyses how health is drawn into the domain of security. The article argues that while globalization and urbanization are often discussed as having triggered the emergence and spread of pathogens, urban epidemics are not self-evident and 'natural' consequences of these pro-cesses. They do not fall neatly into universal categories of space, modernity or risk; rather, they are produced and shaped by a range of social, political, biological and economic sites and scales. Accordingly, the emergence of pathogens depends on its articulation through specific analytical frameworks. This article suggests that a critical focus on how infectious diseases manifest themselves differently in different local contexts may not only provide insights into the manifold forms of urban life, but also into the multiple, complex and highly political constitution of health.
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Judson SD, Fischer R, Judson A, Munster VJ. Ecological Contexts of Index Cases and Spillover Events of Different Ebolaviruses. PLoS Pathog 2016; 12:e1005780. [PMID: 27494600 PMCID: PMC4975397 DOI: 10.1371/journal.ppat.1005780] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2016] [Accepted: 06/30/2016] [Indexed: 01/01/2023] Open
Abstract
Ebola virus disease afflicts both human and animal populations and is caused by four ebolaviruses. These different ebolaviruses may have distinct reservoir hosts and ecological contexts that determine how, where, and when different ebolavirus spillover events occur. Understanding these virus-specific relationships is important for preventing transmission of ebolaviruses from wildlife to humans. We examine the ecological contexts surrounding 34 human index case infections of ebolaviruses from 1976-2014. Determining possible sources of spillover from wildlife, characterizing the environment of each event, and creating ecological niche models to estimate habitats suitable for spillover, we find that index case infections of two ebolaviruses, Ebola virus and Sudan virus, have occurred under different ecological contexts. The index cases of Ebola virus infection are more associated with tropical evergreen broadleaf forests and consuming bushmeat than the cases of Sudan virus. Given these differences, we emphasize caution when generalizing across different ebolaviruses and that location and virus-specific ecological knowledge will be essential to unravelling how human and animal behavior lead to the emergence of Ebola virus disease.
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Affiliation(s)
- Seth D. Judson
- Virus Ecology Unit, Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rocky Mountain Laboratories, Hamilton, Montana, United States of America
- David Geffen School of Medicine at UCLA, Los Angeles, California, United States of America
| | - Robert Fischer
- Virus Ecology Unit, Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rocky Mountain Laboratories, Hamilton, Montana, United States of America
| | - Andrew Judson
- Square Inc, San Francisco, California, United States of America
| | - Vincent J. Munster
- Virus Ecology Unit, Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rocky Mountain Laboratories, Hamilton, Montana, United States of America
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Pigott DM, Millear AI, Earl L, Morozoff C, Han BA, Shearer FM, Weiss DJ, Brady OJ, Kraemer MU, Moyes CL, Bhatt S, Gething PW, Golding N, Hay SI. Updates to the zoonotic niche map of Ebola virus disease in Africa. eLife 2016; 5. [PMID: 27414263 PMCID: PMC4945152 DOI: 10.7554/elife.16412] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2016] [Accepted: 06/20/2016] [Indexed: 12/28/2022] Open
Abstract
As the outbreak of Ebola virus disease (EVD) in West Africa is now contained, attention is turning from control to future outbreak prediction and prevention. Building on a previously published zoonotic niche map (Pigott et al., 2014), this study incorporates new human and animal occurrence data and expands upon the way in which potential bat EVD reservoir species are incorporated. This update demonstrates the potential for incorporating and updating data used to generate the predicted suitability map. A new data portal for sharing such maps is discussed. This output represents the most up-to-date estimate of the extent of EVD zoonotic risk in Africa. These maps can assist in strengthening surveillance and response capacity to contain viral haemorrhagic fevers. DOI:http://dx.doi.org/10.7554/eLife.16412.001
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Affiliation(s)
- David M Pigott
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, United States.,Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom
| | - Anoushka I Millear
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, United States
| | - Lucas Earl
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, United States
| | - Chloe Morozoff
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, United States
| | - Barbara A Han
- Cary Institute of Ecosystem Studies, New York, United States
| | - Freya M Shearer
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom
| | - Daniel J Weiss
- Spatial Ecology and Epidemiology Group, University of Oxford, Oxford, United Kingdom.,Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Oliver J Brady
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom
| | - Moritz Ug Kraemer
- Spatial Ecology and Epidemiology Group, University of Oxford, Oxford, United Kingdom.,Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Catherine L Moyes
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom
| | - Samir Bhatt
- Spatial Ecology and Epidemiology Group, University of Oxford, Oxford, United Kingdom.,Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Peter W Gething
- Spatial Ecology and Epidemiology Group, University of Oxford, Oxford, United Kingdom.,Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Nick Golding
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom.,Department of BioSciences, University of Melbourne, Parkville, Australia
| | - Simon I Hay
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, United States.,Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom
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26
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Host-Primed Ebola Virus GP Exposes a Hydrophobic NPC1 Receptor-Binding Pocket, Revealing a Target for Broadly Neutralizing Antibodies. mBio 2016; 7:e02154-15. [PMID: 26908579 PMCID: PMC4791852 DOI: 10.1128/mbio.02154-15] [Citation(s) in RCA: 78] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
UNLABELLED The filovirus surface glycoprotein (GP) mediates viral entry into host cells. Following viral internalization into endosomes, GP is cleaved by host cysteine proteases to expose a receptor-binding site (RBS) that is otherwise hidden from immune surveillance. Here, we present the crystal structure of proteolytically cleaved Ebola virus GP to a resolution of 3.3 Å. We use this structure in conjunction with functional analysis of a large panel of pseudotyped viruses bearing mutant GP proteins to map the Ebola virus GP endosomal RBS at molecular resolution. Our studies indicate that binding of GP to its endosomal receptor Niemann-Pick C1 occurs in two distinct stages: the initial electrostatic interactions are followed by specific interactions with a hydrophobic trough that is exposed on the endosomally cleaved GP1 subunit. Finally, we demonstrate that monoclonal antibodies targeting the filovirus RBS neutralize all known filovirus GPs, making this conserved pocket a promising target for the development of panfilovirus therapeutics. IMPORTANCE Ebola virus uses its glycoprotein (GP) to enter new host cells. During entry, GP must be cleaved by human enzymes in order for receptor binding to occur. Here, we provide the crystal structure of the cleaved form of Ebola virus GP. We demonstrate that cleavage exposes a site at the top of GP and that this site binds the critical domain C of the receptor, termed Niemann-Pick C1 (NPC1). We perform mutagenesis to find parts of the site essential for binding NPC1 and map distinct roles for an upper, charged crest and lower, hydrophobic trough in cleaved GP. We find that this 3-dimensional site is conserved across the filovirus family and that antibody directed against this site is able to bind cleaved GP from every filovirus tested and neutralize viruses bearing those GPs.
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27
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Jun SR, Leuze MR, Nookaew I, Uberbacher EC, Land M, Zhang Q, Wanchai V, Chai J, Nielsen M, Trolle T, Lund O, Buzard GS, Pedersen TD, Wassenaar TM, Ussery DW. Ebolavirus comparative genomics. FEMS Microbiol Rev 2015; 39:764-78. [PMID: 26175035 PMCID: PMC4551310 DOI: 10.1093/femsre/fuv031] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/08/2015] [Indexed: 12/17/2022] Open
Abstract
The 2014 Ebola outbreak in West Africa is the largest documented for this virus. To examine the dynamics of this genome, we compare more than 100 currently available ebolavirus genomes to each other and to other viral genomes. Based on oligomer frequency analysis, the family Filoviridae forms a distinct group from all other sequenced viral genomes. All filovirus genomes sequenced to date encode proteins with similar functions and gene order, although there is considerable divergence in sequences between the three genera Ebolavirus, Cuevavirus and Marburgvirus within the family Filoviridae. Whereas all ebolavirus genomes are quite similar (multiple sequences of the same strain are often identical), variation is most common in the intergenic regions and within specific areas of the genes encoding the glycoprotein (GP), nucleoprotein (NP) and polymerase (L). We predict regions that could contain epitope-binding sites, which might be good vaccine targets. This information, combined with glycosylation sites and experimentally determined epitopes, can identify the most promising regions for the development of therapeutic strategies.This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).
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Affiliation(s)
- Se-Ran Jun
- Comparative Genomics Group, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA Joint Institute for Computational Sciences, University of Tennessee, Knoxville, TN 37996, USA
| | - Michael R Leuze
- Computer Science and Mathematics Division, Computer Science Research Group, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Intawat Nookaew
- Comparative Genomics Group, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Edward C Uberbacher
- Comparative Genomics Group, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Miriam Land
- Comparative Genomics Group, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Qian Zhang
- Comparative Genomics Group, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA UT-ORNL Graduate School of Genome Science and Technology, University of Tennessee, Knoxville, TN 37996, USA
| | - Visanu Wanchai
- Comparative Genomics Group, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Juanjuan Chai
- Computer Science and Mathematics Division, Computer Science Research Group, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Morten Nielsen
- Center for Biological Sequence Analysis, Department of Systems Biology, The Technical University of Denmark, Building 208, DK-2800 Lyngby, Denmark Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín, San Martín, B 1650 HMP, Buenos Aires, Argentina
| | - Thomas Trolle
- Center for Biological Sequence Analysis, Department of Systems Biology, The Technical University of Denmark, Building 208, DK-2800 Lyngby, Denmark
| | - Ole Lund
- Center for Biological Sequence Analysis, Department of Systems Biology, The Technical University of Denmark, Building 208, DK-2800 Lyngby, Denmark
| | | | - Thomas D Pedersen
- Center for Biological Sequence Analysis, Department of Systems Biology, The Technical University of Denmark, Building 208, DK-2800 Lyngby, Denmark Assays, Cultures and Enzymes Division, Chr. Hansen A/S, Hørsholm, Denmark
| | - Trudy M Wassenaar
- Molecular Microbiology and Genomics Consultants, Tannenstr 7, D-55576 Zotzenheim, Germany
| | - David W Ussery
- Comparative Genomics Group, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA UT-ORNL Graduate School of Genome Science and Technology, University of Tennessee, Knoxville, TN 37996, USA Center for Biological Sequence Analysis, Department of Systems Biology, The Technical University of Denmark, Building 208, DK-2800 Lyngby, Denmark
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28
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Mylne AQN, Pigott DM, Longbottom J, Shearer F, Duda KA, Messina JP, Weiss DJ, Moyes CL, Golding N, Hay SI. Mapping the zoonotic niche of Lassa fever in Africa. Trans R Soc Trop Med Hyg 2015; 109:483-92. [PMID: 26085474 PMCID: PMC4501400 DOI: 10.1093/trstmh/trv047] [Citation(s) in RCA: 93] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2015] [Accepted: 05/29/2015] [Indexed: 02/05/2023] Open
Abstract
Background Lassa fever is a viral haemorrhagic illness responsible for disease outbreaks across West Africa. It is a zoonosis, with the primary reservoir species identified as the Natal multimammate mouse, Mastomys natalensis. The host is distributed across sub-Saharan Africa while the virus' range appears to be restricted to West Africa. The majority of infections result from interactions between the animal reservoir and human populations, although secondary transmission between humans can occur, particularly in hospital settings. Methods Using a species distribution model, the locations of confirmed human and animal infections with Lassa virus (LASV) were used to generate a probabilistic surface of zoonotic transmission potential across sub-Saharan Africa. Results Our results predict that 37.7 million people in 14 countries, across much of West Africa, live in areas where conditions are suitable for zoonotic transmission of LASV. Four of these countries, where at-risk populations are predicted, have yet to report any cases of Lassa fever. Conclusions These maps act as a spatial guide for future surveillance activities to better characterise the geographical distribution of the disease and understand the anthropological, virological and zoological interactions necessary for viral transmission. Combining this zoonotic niche map with detailed patient travel histories can aid differential diagnoses of febrile illnesses, enabling a more rapid response in providing care and reducing the risk of onward transmission.
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Affiliation(s)
- Adrian Q N Mylne
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | | | - Joshua Longbottom
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Freya Shearer
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | | | | | | | - Catherine L Moyes
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Nick Golding
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Simon I Hay
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK Institute for Health Metrics and Evaluation, University of Washington, Seattle, USA Fogarty International Center, National Institutes of Health, Bethesda, Maryland, USA
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Van Kerkhove MD, Bento AI, Mills HL, Ferguson NM, Donnelly CA. A review of epidemiological parameters from Ebola outbreaks to inform early public health decision-making. Sci Data 2015; 2:150019. [PMID: 26029377 PMCID: PMC4443880 DOI: 10.1038/sdata.2015.19] [Citation(s) in RCA: 95] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2014] [Accepted: 04/13/2015] [Indexed: 11/09/2022] Open
Abstract
The unprecedented scale of the Ebola outbreak in West Africa has, as of 29 April 2015, resulted in more than 10,884 deaths among 26,277 cases. Prior to the ongoing outbreak, Ebola virus disease (EVD) caused relatively small outbreaks (maximum outbreak size 425 in Gulu, Uganda) in isolated populations in central Africa. Here, we have compiled a comprehensive database of estimates of epidemiological parameters based on data from past outbreaks, including the incubation period distribution, case fatality rate, basic reproduction number (R 0 ), effective reproduction number (R t ) and delay distributions. We have compared these to parameter estimates from the ongoing outbreak in West Africa. The ongoing outbreak, because of its size, provides a unique opportunity to better understand transmission patterns of EVD. We have not performed a meta-analysis of the data, but rather summarize the estimates by virus from comprehensive investigations of EVD and Marburg outbreaks over the past 40 years. These estimates can be used to parameterize transmission models to improve understanding of initial spread of EVD outbreaks and to inform surveillance and control guidelines.
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Affiliation(s)
- Maria D. Van Kerkhove
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London W2 1PG, UK
- Center for Global Health, Institut Pasteur, Paris 75015, France
| | - Ana I. Bento
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London W2 1PG, UK
| | - Harriet L. Mills
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London W2 1PG, UK
| | - Neil M. Ferguson
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London W2 1PG, UK
| | - Christl A. Donnelly
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London W2 1PG, UK
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30
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A global compendium of human Crimean-Congo haemorrhagic fever virus occurrence. Sci Data 2015; 2:150016. [PMID: 25977820 PMCID: PMC4409013 DOI: 10.1038/sdata.2015.16] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2014] [Accepted: 02/13/2015] [Indexed: 11/08/2022] Open
Abstract
In order to map global disease risk, a geographic database of human Crimean-Congo haemorrhagic fever virus (CCHFV) occurrence was produced by surveying peer-reviewed literature and case reports, as well as informal online sources. Here we present this database, comprising occurrence data linked to geographic point or polygon locations dating from 1953 to 2013. We fully describe all data collection, geo-positioning, database management and quality-control procedures. This is the most comprehensive database of confirmed CCHF occurrence in humans to-date, containing 1,721 geo-positioned occurrences in total.
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31
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Pigott DM, Golding N, Mylne A, Huang Z, Weiss DJ, Brady OJ, Kraemer MUG, Hay SI. Mapping the zoonotic niche of Marburg virus disease in Africa. Trans R Soc Trop Med Hyg 2015; 109:366-78. [PMID: 25820266 PMCID: PMC4447827 DOI: 10.1093/trstmh/trv024] [Citation(s) in RCA: 83] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2014] [Accepted: 02/23/2015] [Indexed: 11/12/2022] Open
Abstract
Background Marburg virus disease (MVD) describes a viral haemorrhagic fever responsible for a number of outbreaks across eastern and southern Africa. It is a zoonotic disease, with the Egyptian rousette (Rousettus aegyptiacus) identified as a reservoir host. Infection is suspected to result from contact between this reservoir and human populations, with occasional secondary human-to-human transmission. Methods Index cases of previous human outbreaks were identified and reports of infection in animals recorded. These data were modelled within a species distribution modelling framework in order to generate a probabilistic surface of zoonotic transmission potential of MVD across sub-Saharan Africa. Results Areas suitable for zoonotic transmission of MVD are predicted in 27 countries inhabited by 105 million people. Regions are suggested for exploratory surveys to better characterise the geographical distribution of the disease, as well as for directing efforts to communicate the risk of practices enhancing zoonotic contact. Conclusions These maps can inform future contingency and preparedness strategies for MVD control, especially where secondary transmission is a risk. Coupling this risk map with patient travel histories could be used to guide the differential diagnosis of highly transmissible pathogens, enabling more rapid response to outbreaks of haemorrhagic fever.
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Affiliation(s)
- David M Pigott
- Spatial Ecology & Epidemiology Group, Department of Zoology, University of Oxford, Oxford, UK
| | - Nick Golding
- Spatial Ecology & Epidemiology Group, Department of Zoology, University of Oxford, Oxford, UK
| | - Adrian Mylne
- Spatial Ecology & Epidemiology Group, Department of Zoology, University of Oxford, Oxford, UK
| | - Zhi Huang
- Spatial Ecology & Epidemiology Group, Department of Zoology, University of Oxford, Oxford, UK
| | - Daniel J Weiss
- Spatial Ecology & Epidemiology Group, Department of Zoology, University of Oxford, Oxford, UK
| | - Oliver J Brady
- Spatial Ecology & Epidemiology Group, Department of Zoology, University of Oxford, Oxford, UK
| | - Moritz U G Kraemer
- Spatial Ecology & Epidemiology Group, Department of Zoology, University of Oxford, Oxford, UK
| | - Simon I Hay
- Spatial Ecology & Epidemiology Group, Department of Zoology, University of Oxford, Oxford, UK Fogarty International Center, National Institutes of Health, Bethesda, Maryland, USA
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32
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Affiliation(s)
- A Townsend Peterson
- Biodiversity Institute, University of Kansas, Lawrence, Kansas, United States of America
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33
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