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Bastide P, Rocu P, Wirtz J, Hassler GW, Chevenet F, Fargette D, Suchard MA, Dellicour S, Lemey P, Guindon S. Modeling the velocity of evolving lineages and predicting dispersal patterns. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.06.597755. [PMID: 38895258 PMCID: PMC11185746 DOI: 10.1101/2024.06.06.597755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Accurate estimation of the dispersal velocity or speed of evolving organisms is no mean feat. In fact, existing probabilistic models in phylogeography or spatial population genetics generally do not provide an adequate framework to define velocity in a relevant manner. For instance, the very concept of instantaneous speed simply does not exist under one of the most popular approaches that models the evolution of spatial coordinates as Brownian trajectories running along a phylogeny [30]. Here, we introduce a new family of models - the so-called "Phylogenetic Integrated Velocity" (PIV) models - that use Gaussian processes to explicitly model the velocity of evolving lineages instead of focusing on the fluctuation of spatial coordinates over time. We describe the properties of these models and show an increased accuracy of velocity estimates compared to previous approaches. Analyses of West Nile virus data in the U.S.A. indicate that PIV models provide sensible predictions of the dispersal of evolving pathogens at a one-year time horizon. These results demonstrate the feasibility and relevance of predictive phylogeography in monitoring epidemics in time and space.
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Affiliation(s)
- Paul Bastide
- IMAG, Université de Montpellier, CNRS, Montpellier, France
| | - Pauline Rocu
- Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier. CNRS - UMR 5506. Montpellier, France
| | - Johannes Wirtz
- CEFE, Université de Montpellier, CNRS, EPHE, IRD, Montpellier, France
| | - Gabriel W Hassler
- Department of Economics, Sociology, and Statistics, RAND, Santa Monica, CA, USA
| | | | - Denis Fargette
- PHIM, IRD, INRAE, CIRAD, Université de Montpellier, Montpellier, France
| | - Marc A Suchard
- Department of Biostatistics, Jonathan and Karin Fielding School of Public Health, University of California, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA, USA
| | - Simon Dellicour
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Brussels, Belgium
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium
| | - Stéphane Guindon
- Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier. CNRS - UMR 5506. Montpellier, France
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Dellicour S, Bastide P, Rocu P, Fargette D, Hardy OJ, Suchard MA, Guindon S, Lemey P. How fast are viruses spreading in the wild? BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.10.588821. [PMID: 38645268 PMCID: PMC11030353 DOI: 10.1101/2024.04.10.588821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Genomic data collected from viral outbreaks can be exploited to reconstruct the dispersal history of viral lineages in a two-dimensional space using continuous phylogeographic inference. These spatially explicit reconstructions can subsequently be used to estimate dispersal metrics allowing to unveil the dispersal dynamics and evaluate the capacity to spread among hosts. Heterogeneous sampling intensity of genomic sequences can however impact the accuracy of dispersal insights gained through phylogeographic inference. In our study, we implement a simulation framework to evaluate the robustness of three dispersal metrics - a lineage dispersal velocity, a diffusion coefficient, and an isolation-by-distance signal metric - to the sampling effort. Our results reveal that both the diffusion coefficient and isolation-by-distance signal metrics appear to be robust to the number of samples considered for the phylogeographic reconstruction. We then use these two dispersal metrics to compare the dispersal pattern and capacity of various viruses spreading in animal populations. Our comparative analysis reveals a broad range of isolation-by-distance patterns and diffusion coefficients mostly reflecting the dispersal capacity of the main infected host species but also, in some cases, the likely signature of rapid and/or long-distance dispersal events driven by human-mediated movements through animal trade. Overall, our study provides key recommendations for the lineage dispersal metrics to consider in future studies and illustrates their application to compare the spread of viruses in various settings.
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Morris R, Wang S. Building a pathway to One Health surveillance and response in Asian countries. SCIENCE IN ONE HEALTH 2024; 3:100067. [PMID: 39077383 PMCID: PMC11262298 DOI: 10.1016/j.soh.2024.100067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 03/27/2024] [Indexed: 07/31/2024]
Abstract
To detect and respond to emerging diseases more effectively, an integrated surveillance strategy needs to be applied to both human and animal health. Current programs in Asian countries operate separately for the two sectors and are principally concerned with detection of events that represent a short-term disease threat. It is not realistic to either invest only in efforts to detect emerging diseases, or to rely solely on event-based surveillance. A comprehensive strategy is needed, concurrently investigating and managing endemic zoonoses, studying evolving diseases which change their character and importance due to influences such as demographic and climatic change, and enhancing understanding of factors which are likely to influence the emergence of new pathogens. This requires utilisation of additional investigation tools that have become available in recent years but are not yet being used to full effect. As yet there is no fully formed blueprint that can be applied in Asian countries. Hence a three-step pathway is proposed to move towards the goal of comprehensive One Health disease surveillance and response.
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Affiliation(s)
- Roger Morris
- Massey University EpiCentre and EpiSoft International Ltd, 76/100 Titoki Street, Masterton 5810, New Zealand
| | - Shiyong Wang
- Health, Nutrition and Population, World Bank Group, Washington, DC, USA
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4
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Sanogo IN, Guinat C, Dellicour S, Diakité MA, Niang M, Koita OA, Camus C, Ducatez M. Genetic insights of H9N2 avian influenza viruses circulating in Mali and phylogeographic patterns in Northern and Western Africa. Virus Evol 2024; 10:veae011. [PMID: 38435712 PMCID: PMC10908551 DOI: 10.1093/ve/veae011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 01/18/2024] [Accepted: 02/13/2024] [Indexed: 03/05/2024] Open
Abstract
Avian influenza viruses (AIVs) of the H9N2 subtype have become widespread in Western Africa since their first detection in 2017 in Burkina Faso. However, the genetic characteristics and diffusion patterns of the H9N2 virus remain poorly understood in Western Africa, mainly due to limited surveillance activities. In addition, Mali, a country considered to play an important role in the epidemiology of AIVs in the region, lacks more comprehensive data on the genetic characteristics of these viruses, especially the H9N2 subtype. To better understand the genetic characteristics and spatio-temporal dynamics of H9N2 virus within this region, we carried out a comprehensive genetic characterization of H9N2 viruses collected through active surveillance in live bird markets in Mali between 2021 and 2022. We also performed a continuous phylogeographic analysis to unravel the dispersal history of H9N2 lineages between Northern and Western Africa. The identified Malian H9N2 virus belonged to the G1 lineage, similar to viruses circulating in both Western and Northern Africa, and possessed multiple molecular markers associated with an increased potential for zoonotic transmission and virulence. Notably, some Malian strains carried the R-S-N-R motif at their cleavage site, mainly observed in H9N2 strains in Asia. Our continuous phylogeographic analysis revealed a single and significant long-distance lineage dispersal event of the H9N2 virus to Western Africa, likely to have originated from Morocco in 2015, shaping the westward diffusion of the H9N2 virus. Our study highlights the need for long-term surveillance of H9N2 viruses in poultry populations in Western Africa, which is crucial for a better understanding of virus evolution and effective management against potential zoonotic AIV strain emergence.
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Affiliation(s)
- Idrissa Nonmon Sanogo
- Interactions Hôtes-Agents Pathogènes (IHAP), UMR 1225, Université de Toulouse, INRAE, ENVT, Toulouse 31076, France
- Faculté d’Agronomie et de Médecine Animale (FAMA), Université de Ségou, Ségou BP 24, Mali
| | - Claire Guinat
- Interactions Hôtes-Agents Pathogènes (IHAP), UMR 1225, Université de Toulouse, INRAE, ENVT, Toulouse 31076, France
| | - Simon Dellicour
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Brussels B-1050, Belgium
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven, Leuven BE-3000, Belgium
| | - Mohamed Adama Diakité
- Service diagnostic et recherche Laboratoire Central Vétérinaire, Bamako BP 2295, Mali
| | - Mamadou Niang
- Food and Agriculture Organization of the United Nations (FAO-UN), Emergency Centre for Transboundary Animal Diseases (ECTAD), Regional Office for Africa (RAF), Accra BP 1628, Ghana
| | - Ousmane A Koita
- Laboratoire de Biologie Moléculaire Appliquée, Faculté des Sciences et Techniques (FAST), University of Sciences, Techniques and Technologies of Bamako (USTTB), Mali Université de Bamako, Bamako E 3206, Mali
| | - Christelle Camus
- Interactions Hôtes-Agents Pathogènes (IHAP), UMR 1225, Université de Toulouse, INRAE, ENVT, Toulouse 31076, France
| | - Mariette Ducatez
- Interactions Hôtes-Agents Pathogènes (IHAP), UMR 1225, Université de Toulouse, INRAE, ENVT, Toulouse 31076, France
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5
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Lu L, Zhang F, Oude Munnink BB, Munger E, Sikkema RS, Pappa S, Tsioka K, Sinigaglia A, Dal Molin E, Shih BB, Günther A, Pohlmann A, Ziegler U, Beer M, Taylor RA, Bartumeus F, Woolhouse M, Aarestrup FM, Barzon L, Papa A, Lycett S, Koopmans MPG. West Nile virus spread in Europe: Phylogeographic pattern analysis and key drivers. PLoS Pathog 2024; 20:e1011880. [PMID: 38271294 PMCID: PMC10810478 DOI: 10.1371/journal.ppat.1011880] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 12/04/2023] [Indexed: 01/27/2024] Open
Abstract
BACKGROUND West Nile virus (WNV) outbreaks in birds, humans, and livestock have occurred in multiple areas in Europe and have had a significant impact on animal and human health. The patterns of emergence and spread of WNV in Europe are very different from those in the US and understanding these are important for guiding preparedness activities. METHODS We mapped the evolution and spread history of WNV in Europe by incorporating viral genome sequences and epidemiological data into phylodynamic models. Spatially explicit phylogeographic models were developed to explore the possible contribution of different drivers to viral dispersal direction and velocity. A "skygrid-GLM" approach was used to identify how changes in environments would predict viral genetic diversity variations over time. FINDINGS Among the six lineages found in Europe, WNV-2a (a sub-lineage of WNV-2) has been predominant (accounting for 73% of all sequences obtained in Europe that have been shared in the public domain) and has spread to at least 14 countries. In the past two decades, WNV-2a has evolved into two major co-circulating clusters, both originating from Central Europe, but with distinct dynamic history and transmission patterns. WNV-2a spreads at a high dispersal velocity (88km/yr-215 km/yr) which is correlated to bird movements. Notably, amongst multiple drivers that could affect the spread of WNV, factors related to land use were found to strongly influence the spread of WNV. Specifically, the intensity of agricultural activities (defined by factors related to crops and livestock production, such as coverage of cropland, pasture, cultivated and managed vegetation, livestock density) were positively associated with both spread direction and velocity. In addition, WNV spread direction was associated with high coverage of wetlands and migratory bird flyways. CONCLUSION Our results suggest that-in addition to ecological conditions favouring bird- and mosquito- presence-agricultural land use may be a significant driver of WNV emergence and spread. Our study also identified significant gaps in data and the need to strengthen virological surveillance in countries of Central Europe from where WNV outbreaks are likely seeded. Enhanced monitoring for early detection of further dispersal could be targeted to areas with high agricultural activities and habitats of migratory birds.
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Affiliation(s)
- Lu Lu
- Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom
- Usher Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Feifei Zhang
- Usher Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Bas B. Oude Munnink
- Erasmus MC, Viroscience and Pandemic and Disaster Preparedness Centre, Rotterdam, the Netherlands
| | - Emmanuelle Munger
- Erasmus MC, Viroscience and Pandemic and Disaster Preparedness Centre, Rotterdam, the Netherlands
| | - Reina S. Sikkema
- Erasmus MC, Viroscience and Pandemic and Disaster Preparedness Centre, Rotterdam, the Netherlands
| | - Styliani Pappa
- Department of Microbiology, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Katerina Tsioka
- Department of Microbiology, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | | | | | - Barbara B. Shih
- Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Anne Günther
- Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Greifswald-Riems, Germany
| | - Anne Pohlmann
- Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Greifswald-Riems, Germany
| | - Ute Ziegler
- Institute of Novel and Emerging Infectious Diseases, Friedrich-Loeffler-Institut, Greifswald-Riems, Germany
| | - Martin Beer
- Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Greifswald-Riems, Germany
| | - Rachel A. Taylor
- Department of Epidemiological Sciences, Animal and Plant Health Agency, United Kingdom
| | - Frederic Bartumeus
- Centre for Advanced Studies of Blanes (CEAB-CSIC), Girona, Spain
- Centre for Research on Ecology and Forestry Applications (CREAF), Barcelona, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
| | - Mark Woolhouse
- Usher Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Frank M. Aarestrup
- Research Group for Genomic Epidemiology, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Luisa Barzon
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Anna Papa
- Department of Microbiology, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Samantha Lycett
- Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Marion P. G. Koopmans
- Erasmus MC, Viroscience and Pandemic and Disaster Preparedness Centre, Rotterdam, the Netherlands
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6
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Layan M, Dacheux L, Lemey P, Brunker K, Ma L, Troupin C, Dussart P, Chevalier V, Wood JLN, Ly S, Duong V, Bourhy H, Dellicour S. Uncovering the endemic circulation of rabies in Cambodia. Mol Ecol 2023; 32:5140-5155. [PMID: 37540190 DOI: 10.1111/mec.17087] [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: 11/22/2022] [Accepted: 07/18/2023] [Indexed: 08/05/2023]
Abstract
In epidemiology, endemicity characterizes sustained pathogen circulation in a geographical area, which involves a circulation that is not being maintained by external introductions. Because it could potentially shape the design of public health interventions, there is an interest in fully uncovering the endemic pattern of a disease. Here, we use a phylogeographic approach to investigate the endemic signature of rabies virus (RABV) circulation in Cambodia. Cambodia is located in one of the most affected regions by rabies in the world, but RABV circulation between and within Southeast Asian countries remains understudied. Our analyses are based on a new comprehensive data set of 199 RABV genomes collected between 2014 and 2017 as well as previously published Southeast Asian RABV sequences. We show that most Cambodian sequences belong to a distinct clade that has been circulating almost exclusively in Cambodia. Our results thus point towards rabies circulation in Cambodia that does not rely on external introductions. We further characterize within-Cambodia RABV circulation by estimating lineage dispersal metrics that appear to be similar to other settings, and by performing landscape phylogeographic analyses to investigate environmental factors impacting the dispersal dynamic of viral lineages. The latter analyses do not lead to the identification of environmental variables that would be associated with the heterogeneity of viral lineage dispersal velocities, which calls for a better understanding of local dog ecology and further investigations of the potential drivers of RABV spread in the region. Overall, our study illustrates how phylogeographic investigations can be performed to assess and characterize viral endemicity in a context of relatively limited data.
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Affiliation(s)
- Maylis Layan
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université Paris Cité, UMR2000, CNRS, Paris, France
- Collège Doctoral, Sorbonne Université, Paris, France
| | - Laurent Dacheux
- Lyssavirus Epidemiology and Neuropathology Unit, Institut Pasteur, Université Paris Cité, Paris, France
- WHO Collaborating Centre for Reference and Research on Rabies, Institut Pasteur, Université Paris Cité, Paris, France
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven, University of Leuven, Leuven, Belgium
| | - Kirstyn Brunker
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, UK
| | - Laurence Ma
- Biomics, Center for Technological Resources and Research (C2RT), Institut Pasteur, Université Paris Cité, Paris, France
| | - Cécile Troupin
- Virology Unit, Institut Pasteur du Cambodge, Phnom Penh, Cambodia
| | - Philippe Dussart
- Virology Unit, Institut Pasteur du Cambodge, Phnom Penh, Cambodia
| | - Véronique Chevalier
- CIRAD, UMR ASTRE, Montpellier, France
- ASTRE, Univ. Montpellier CIRAD, INRAE, Montpellier, France
- Epidemiology and Clinical Research, Institut Pasteur de Madagascar, Antananarivo, Madagascar
| | - James L N Wood
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Sowath Ly
- Epidemiology and Public Health, Institut Pasteur du Cambodge, Phnom Penh, Cambodia
| | - Veasna Duong
- Virology Unit, Institut Pasteur du Cambodge, Phnom Penh, Cambodia
| | - Hervé Bourhy
- Lyssavirus Epidemiology and Neuropathology Unit, Institut Pasteur, Université Paris Cité, Paris, France
- WHO Collaborating Centre for Reference and Research on Rabies, Institut Pasteur, Université Paris Cité, Paris, France
| | - Simon Dellicour
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven, University of Leuven, Leuven, Belgium
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium
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7
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Hollingsworth BD, Grubaugh ND, Lazzaro BP, Murdock CC. Leveraging insect-specific viruses to elucidate mosquito population structure and dynamics. PLoS Pathog 2023; 19:e1011588. [PMID: 37651317 PMCID: PMC10470969 DOI: 10.1371/journal.ppat.1011588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/02/2023] Open
Abstract
Several aspects of mosquito ecology that are important for vectored disease transmission and control have been difficult to measure at epidemiologically important scales in the field. In particular, the ability to describe mosquito population structure and movement rates has been hindered by difficulty in quantifying fine-scale genetic variation among populations. The mosquito virome represents a possible avenue for quantifying population structure and movement rates across multiple spatial scales. Mosquito viromes contain a diversity of viruses, including several insect-specific viruses (ISVs) and "core" viruses that have high prevalence across populations. To date, virome studies have focused on viral discovery and have only recently begun examining viral ecology. While nonpathogenic ISVs may be of little public health relevance themselves, they provide a possible route for quantifying mosquito population structure and dynamics. For example, vertically transmitted viruses could behave as a rapidly evolving extension of the host's genome. It should be possible to apply established analytical methods to appropriate viral phylogenies and incidence data to generate novel approaches for estimating mosquito population structure and dispersal over epidemiologically relevant timescales. By studying the virome through the lens of spatial and genomic epidemiology, it may be possible to investigate otherwise cryptic aspects of mosquito ecology. A better understanding of mosquito population structure and dynamics are key for understanding mosquito-borne disease ecology and methods based on ISVs could provide a powerful tool for informing mosquito control programs.
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Affiliation(s)
- Brandon D Hollingsworth
- Department of Entomology, Cornell University, Ithaca, New York, United States of America
- Cornell Institute for Host Microbe Interaction and Disease, Cornell University, Ithaca, New York, United States of America
| | - Nathan D Grubaugh
- Yale School of Public Health, New Haven, Connecticut, United States of America
- Yale University, New Haven, Connecticut, United States of America
| | - Brian P Lazzaro
- Department of Entomology, Cornell University, Ithaca, New York, United States of America
- Cornell Institute for Host Microbe Interaction and Disease, Cornell University, Ithaca, New York, United States of America
| | - Courtney C Murdock
- Department of Entomology, Cornell University, Ithaca, New York, United States of America
- Cornell Institute for Host Microbe Interaction and Disease, Cornell University, Ithaca, New York, United States of America
- Northeast Regional Center for Excellence in Vector-borne Diseases, Cornell University, Ithaca, New York, United States of America
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8
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Vogels C, Brackney D, Dupuis A, Robich R, Fauver J, Brito A, Williams S, Anderson J, Lubelczyk C, Lange R, Prusinski M, Kramer L, Gangloff-Kaufmann J, Goodman L, Baele G, Smith R, Armstrong P, Ciota A, Dellicour S, Grubaugh N. Phylogeographic reconstruction of the emergence and spread of Powassan virus in the northeastern United States. Proc Natl Acad Sci U S A 2023; 120:e2218012120. [PMID: 37040418 PMCID: PMC10120011 DOI: 10.1073/pnas.2218012120] [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: 10/21/2022] [Accepted: 02/23/2023] [Indexed: 04/12/2023] Open
Abstract
Powassan virus is an emerging tick-borne virus of concern for public health, but very little is known about its transmission patterns and ecology. Here, we expanded the genomic dataset by sequencing 279 Powassan viruses isolated from Ixodes scapularis ticks from the northeastern United States. Our phylogeographic reconstructions revealed that Powassan virus lineage II was likely introduced or emerged from a relict population in the Northeast between 1940 and 1975. Sequences strongly clustered by sampling location, suggesting a highly focal geographical distribution. Our analyses further indicated that Powassan virus lineage II emerged in the northeastern United States mostly following a south-to-north pattern, with a weighted lineage dispersal velocity of ~3 km/y. Since the emergence in the Northeast, we found an overall increase in the effective population size of Powassan virus lineage II, but with growth stagnating during recent years. The cascading effect of population expansion of white-tailed deer and I. scapularis populations likely facilitated the emergence of Powassan virus in the northeastern United States.
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Affiliation(s)
- Chantal B. F. Vogels
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510
| | - Doug E. Brackney
- Center for Vector Biology and Zoonotic Diseases, Department of Entomology, The Connecticut Agricultural Experiment Station, New Haven, CT 06511
| | - Alan P. Dupuis
- The Arbovirus Laboratory, New York State Department of Health, Wadsworth Center, Slingerlands, NY 12159
- Department of Biomedical Sciences, State University of New York at Albany School of Public Health, Albany, NY 12222
| | - Rebecca M. Robich
- Vector-borne Disease Laboratory, MaineHealth Institute for Research, Scarborough, ME 04074
| | - Joseph R. Fauver
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510
- Department of Epidemiology, University of Nebraska Medical Center, Omaha, NE 68198
| | - Anderson F. Brito
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510
- Instituto Todos pela Saúde, São Paulo SP01310-942, Brazil
| | - Scott C. Williams
- Department of Environmental Science and Forestry, The Connecticut Agricultural Experiment Station, New Haven, CT 06511
| | - John F. Anderson
- Center for Vector Biology and Zoonotic Diseases, Department of Entomology, The Connecticut Agricultural Experiment Station, New Haven, CT 06511
| | - Charles B. Lubelczyk
- Vector-borne Disease Laboratory, MaineHealth Institute for Research, Scarborough, ME 04074
| | - Rachel E. Lange
- The Arbovirus Laboratory, New York State Department of Health, Wadsworth Center, Slingerlands, NY 12159
- Department of Biomedical Sciences, State University of New York at Albany School of Public Health, Albany, NY 12222
| | - Melissa A. Prusinski
- New York State Department of Health, Bureau of Communicable Disease Control, Albany, NY 12237
| | - Laura D. Kramer
- The Arbovirus Laboratory, New York State Department of Health, Wadsworth Center, Slingerlands, NY 12159
- Department of Biomedical Sciences, State University of New York at Albany School of Public Health, Albany, NY 12222
| | | | - Laura B. Goodman
- Department of Public and Ecosystem Health, Cornell University, Ithaca, NY 14853
| | - Guy Baele
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven3000, Belgium
| | - Robert P. Smith
- Vector-borne Disease Laboratory, MaineHealth Institute for Research, Scarborough, ME 04074
| | - Philip M. Armstrong
- Center for Vector Biology and Zoonotic Diseases, Department of Entomology, The Connecticut Agricultural Experiment Station, New Haven, CT 06511
| | - Alexander T. Ciota
- The Arbovirus Laboratory, New York State Department of Health, Wadsworth Center, Slingerlands, NY 12159
- Department of Biomedical Sciences, State University of New York at Albany School of Public Health, Albany, NY 12222
| | - Simon Dellicour
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven3000, Belgium
- Spatial Epidemiology Lab, Université Libre de Bruxelles, Brussels1050, Belgium
| | - Nathan D. Grubaugh
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06511
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9
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Van Borm S, Boseret G, Dellicour S, Steensels M, Roupie V, Vandenbussche F, Mathijs E, Vilain A, Driesen M, Dispas M, Delcloo AW, Lemey P, Mertens I, Gilbert M, Lambrecht B, van den Berg T. Combined Phylogeographic Analyses and Epidemiologic Contact Tracing to Characterize Atypically Pathogenic Avian Influenza (H3N1) Epidemic, Belgium, 2019. Emerg Infect Dis 2023; 29:351-359. [PMID: 36692362 PMCID: PMC9881769 DOI: 10.3201/eid2902.220765] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
The high economic impact and zoonotic potential of avian influenza call for detailed investigations of dispersal dynamics of epidemics. We integrated phylogeographic and epidemiologic analyses to investigate the dynamics of a low pathogenicity avian influenza (H3N1) epidemic that occurred in Belgium during 2019. Virus genomes from 104 clinical samples originating from 85% of affected farms were sequenced. A spatially explicit phylogeographic analysis confirmed a dominating northeast to southwest dispersal direction and a long-distance dispersal event linked to direct live animal transportation between farms. Spatiotemporal clustering, transport, and social contacts strongly correlated with the phylogeographic pattern of the epidemic. We detected only a limited association between wind direction and direction of viral lineage dispersal. Our results highlight the multifactorial nature of avian influenza epidemics and illustrate the use of genomic analyses of virus dispersal to complement epidemiologic and environmental data, improve knowledge of avian influenza epidemiologic dynamics, and enhance control strategies.
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10
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Zhao J, Dellicour S, Yan Z, Veit M, Gill MS, He WT, Zhai X, Ji X, Suchard MA, Lemey P, Su S. Early Genomic Surveillance and Phylogeographic Analysis of Getah Virus, a Reemerging Arbovirus, in Livestock in China. J Virol 2023; 97:e0109122. [PMID: 36475767 PMCID: PMC9888209 DOI: 10.1128/jvi.01091-22] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 10/14/2022] [Indexed: 12/13/2022] Open
Abstract
Getah virus (GETV) mainly causes disease in livestock and may pose an epidemic risk due to its expanding host range and the potential of long-distance dispersal through animal trade. Here, we used metagenomic next-generation sequencing (mNGS) to identify GETV as the pathogen responsible for reemerging swine disease in China and subsequently estimated key epidemiological parameters using phylodynamic and spatially-explicit phylogeographic approaches. The GETV isolates were able to replicate in a variety of cell lines, including human cells, and showed high pathogenicity in a mouse model, suggesting the potential for more mammal hosts. We obtained 16 complete genomes and 79 E2 gene sequences from viral strains collected in China from 2016 to 2021 through large-scale surveillance among livestock, pets, and mosquitoes. Our phylogenetic analysis revealed that three major GETV lineages are responsible for the current epidemic in livestock in China. We identified three potential positively selected sites and mutations of interest in E2, which may impact the transmissibility and pathogenicity of the virus. Phylodynamic inference of the GETV demographic dynamics identified an association between livestock meat consumption and the evolution of viral genetic diversity. Finally, phylogeographic reconstruction of GETV dispersal indicated that the sampled lineages have preferentially circulated within areas associated with relatively higher mean annual temperature and pig population density. Our results highlight the importance of continuous surveillance of GETV among livestock in southern Chinese regions associated with relatively high temperatures. IMPORTANCE Although livestock is known to be the primary reservoir of Getah virus (GETV) in Asian countries, where identification is largely based on serology, the evolutionary history and spatial epidemiology of GETV in these regions remain largely unknown. Through our sequencing efforts, we provided robust support for lineage delineation of GETV and identified three major lineages that are responsible for the current epidemic in livestock in China. We further analyzed genomic and epidemiological data to reconstruct the recent demographic and dispersal history of GETV in domestic animals in China and to explore the impact of environmental factors on its genetic diversity and its diffusion. Notably, except for livestock meat consumption, other pig-related factors such as the evolution of live pig transport and pork production do not show a significant association with the evolution of viral genetic diversity, pointing out that further studies should investigate the potential contribution of other host species to the GETV outbreak. Our analysis of GETV demonstrates the need for wider animal species surveillance and provides a baseline for future studies of the molecular epidemiology and early warning of emerging arboviruses in China.
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Affiliation(s)
- Jin Zhao
- Jiangsu Engineering Laboratory of Animal Immunology, Institute of Immunology, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
- Sanya Institute of Nanjing Agricultural University, Sanya, China
| | - Simon Dellicour
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Brussels, Belgium
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium
| | - Ziqing Yan
- Jiangsu Engineering Laboratory of Animal Immunology, Institute of Immunology, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
| | - Michael Veit
- Institute for Virology, Center for Infection Medicine, Veterinary Faculty, Free University Berlin, Berlin, Germany
| | - Mandev S. Gill
- Department of Statistics, University of Georgia, Athens, Georgia, USA
- Institute of Bioinformatics, University of Georgia, Athens, Georgia, USA
| | - Wan-Ting He
- Jiangsu Engineering Laboratory of Animal Immunology, Institute of Immunology, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
- Sanya Institute of Nanjing Agricultural University, Sanya, China
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium
| | - Xiaofeng Zhai
- Jiangsu Engineering Laboratory of Animal Immunology, Institute of Immunology, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
- Sanya Institute of Nanjing Agricultural University, Sanya, China
| | - Xiang Ji
- Department of Mathematics, School of Science & Engineering, Tulane University, New Orleans, Louisiana, USA
| | - Marc A. Suchard
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, California, USA
- Department of Biomathematics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium
| | - Shuo Su
- Jiangsu Engineering Laboratory of Animal Immunology, Institute of Immunology, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
- Sanya Institute of Nanjing Agricultural University, Sanya, China
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11
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Gunasekara U, Bertram MR, Van Long N, Minh PQ, Chuong VD, Perez A, Arzt J, VanderWaal K. Phylogeography as a Proxy for Population Connectivity for Spatial Modeling of Foot-and-Mouth Disease Outbreaks in Vietnam. Viruses 2023; 15:v15020388. [PMID: 36851602 PMCID: PMC9958845 DOI: 10.3390/v15020388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 01/17/2023] [Accepted: 01/18/2023] [Indexed: 01/31/2023] Open
Abstract
Bayesian space-time regression models are helpful tools to describe and predict the distribution of infectious disease outbreaks and to delineate high-risk areas for disease control. In these models, structured and unstructured spatial and temporal effects account for various forms of non-independence amongst case counts across spatial units. Structured spatial effects capture correlations in case counts amongst neighboring provinces arising from shared risk factors or population connectivity. For highly mobile populations, spatial adjacency is an imperfect measure of connectivity due to long-distance movement, but we often lack data on host movements. Phylogeographic models inferring routes of viral dissemination across a region could serve as a proxy for patterns of population connectivity. The objective of this study was to investigate whether the effects of population connectivity in space-time regressions of case counts were better captured by spatial adjacency or by inferences from phylogeographic analyses. To compare these two approaches, we used foot-and-mouth disease virus (FMDV) outbreak data from across Vietnam as an example. We identified that accounting for virus movement through phylogeographic analysis serves as a better proxy for population connectivity than spatial adjacency in spatial-temporal risk models. This approach may contribute to design surveillance activities in countries lacking movement data.
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Affiliation(s)
- Umanga Gunasekara
- Veterinary Population Medicine, University of Minnesota, St. Paul, MN 55108, USA
| | - Miranda R. Bertram
- Foreign Animal Disease Research Unit, USDA-ARS, Plum Island Animal Disease Center, Southold, NY 11957, USA
| | - Nguyen Van Long
- Department of Animal Health, Ministry of Agriculture and Rural Development, Hanoi, Vietnam
| | - Phan Quang Minh
- Department of Animal Health, Ministry of Agriculture and Rural Development, Hanoi, Vietnam
| | - Vo Dinh Chuong
- Department of Animal Health, Ministry of Agriculture and Rural Development, Hanoi, Vietnam
| | - Andres Perez
- Veterinary Population Medicine, University of Minnesota, St. Paul, MN 55108, USA
| | - Jonathan Arzt
- Foreign Animal Disease Research Unit, USDA-ARS, Plum Island Animal Disease Center, Southold, NY 11957, USA
- Correspondence: (J.A.); (K.V.)
| | - Kimberly VanderWaal
- Veterinary Population Medicine, University of Minnesota, St. Paul, MN 55108, USA
- Correspondence: (J.A.); (K.V.)
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12
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Kozakiewicz CP, Burridge CP, Lee JS, Kraberger SJ, Fountain-Jones NM, Fisher RN, Lyren LM, Jennings MK, Riley SPD, Serieys LEK, Craft ME, Funk WC, Crooks KR, VandeWoude S, Carver S. Habitat connectivity and host relatedness influence virus spread across an urbanising landscape in a fragmentation-sensitive carnivore. Virus Evol 2022; 9:veac122. [PMID: 36694819 PMCID: PMC9865512 DOI: 10.1093/ve/veac122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 10/22/2022] [Accepted: 12/20/2022] [Indexed: 12/24/2022] Open
Abstract
Spatially heterogeneous landscape factors such as urbanisation can have substantial effects on the severity and spread of wildlife diseases. However, research linking patterns of pathogen transmission to landscape features remains rare. Using a combination of phylogeographic and machine learning approaches, we tested the influence of landscape and host factors on feline immunodeficiency virus (FIVLru) genetic variation and spread among bobcats (Lynx rufus) sampled from coastal southern California. We found evidence for increased rates of FIVLru lineage spread through areas of higher vegetation density. Furthermore, single-nucleotide polymorphism (SNP) variation among FIVLru sequences was associated with host genetic distances and geographic location, with FIVLru genetic discontinuities precisely correlating with known urban barriers to host dispersal. An effect of forest land cover on FIVLru SNP variation was likely attributable to host population structure and differences in forest land cover between different populations. Taken together, these results suggest that the spread of FIVLru is constrained by large-scale urban barriers to host movement. Although urbanisation at fine spatial scales did not appear to directly influence virus transmission or spread, we found evidence that viruses transmit and spread more quickly through areas containing higher proportions of natural habitat. These multiple lines of evidence demonstrate how urbanisation can change patterns of contact-dependent pathogen transmission and provide insights into how continued urban development may influence the incidence and management of wildlife disease.
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Affiliation(s)
| | | | - Justin S Lee
- Genomic Sequencing Laboratory, Centers for Disease Control and Prevention, Atlanta, GA 30329, USA
| | | | | | - Robert N Fisher
- Western Ecological Research Center, U.S. Geological Survey, San Diego, CA 92101, USA
| | - Lisa M Lyren
- Western Ecological Research Center, U.S. Geological Survey, San Diego, CA 92101, USA
| | - Megan K Jennings
- Biology Department, San Diego State University, San Diego, CA 92182, USA
| | - Seth P D Riley
- National Park Service, Santa Monica Mountains National Recreation Area, Thousand Oaks, CA 91360, USA
| | | | - Meggan E Craft
- Department of Ecology, Evolution and Behavior, University of Minnesota, St Paul, MN 55108, USA
| | - W Chris Funk
- Department of Biology, Colorado State University, Fort Collins, CO 80523, USA,Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO 80523, USA
| | - Kevin R Crooks
- Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO 80523, USA,Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO 80523, USA
| | - Sue VandeWoude
- Department of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO 80523, USA
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13
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Klitting R, Kafetzopoulou LE, Thiery W, Dudas G, Gryseels S, Kotamarthi A, Vrancken B, Gangavarapu K, Momoh M, Sandi JD, Goba A, Alhasan F, Grant DS, Okogbenin S, Ogbaini-Emovo E, Garry RF, Smither AR, Zeller M, Pauthner MG, McGraw M, Hughes LD, Duraffour S, Günther S, Suchard MA, Lemey P, Andersen KG, Dellicour S. Predicting the evolution of the Lassa virus endemic area and population at risk over the next decades. Nat Commun 2022; 13:5596. [PMID: 36167835 PMCID: PMC9515147 DOI: 10.1038/s41467-022-33112-3] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 09/02/2022] [Indexed: 01/27/2023] Open
Abstract
Lassa fever is a severe viral hemorrhagic fever caused by a zoonotic virus that repeatedly spills over to humans from its rodent reservoirs. It is currently not known how climate and land use changes could affect the endemic area of this virus, currently limited to parts of West Africa. By exploring the environmental data associated with virus occurrence using ecological niche modelling, we show how temperature, precipitation and the presence of pastures determine ecological suitability for virus circulation. Based on projections of climate, land use, and population changes, we find that regions in Central and East Africa will likely become suitable for Lassa virus over the next decades and estimate that the total population living in ecological conditions that are suitable for Lassa virus circulation may drastically increase by 2070. By analysing geotagged viral genomes using spatially-explicit phylogeography and simulating virus dispersal, we find that in the event of Lassa virus being introduced into a new suitable region, its spread might remain spatially limited over the first decades.
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Affiliation(s)
- Raphaëlle Klitting
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, 92037, USA.
| | - Liana E. Kafetzopoulou
- grid.5596.f0000 0001 0668 7884Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven - University of Leuven, Leuven, Belgium ,grid.424065.10000 0001 0701 3136Bernhard Nocht Institute for Tropical Medicine, Hamburg, Germany
| | - Wim Thiery
- grid.8767.e0000 0001 2290 8069Department of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel, Brussels, Belgium
| | - Gytis Dudas
- grid.6441.70000 0001 2243 2806Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
| | - Sophie Gryseels
- grid.5284.b0000 0001 0790 3681Evolutionary Ecology group, Department of Biology, University of Antwerp, 2610 Antwerp, Belgium ,grid.20478.390000 0001 2171 9581Vertebrate group, Directorate Taxonomy and Phylogeny, Royal Belgian Institute of Natural Sciences, 1000 Brussels, Belgium
| | - Anjali Kotamarthi
- grid.214007.00000000122199231Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037 USA
| | - Bram Vrancken
- grid.5596.f0000 0001 0668 7884Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven - University of Leuven, Leuven, Belgium
| | - Karthik Gangavarapu
- grid.214007.00000000122199231Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037 USA
| | - Mambu Momoh
- grid.442296.f0000 0001 2290 9707Eastern Technical University of Sierra Leone, Kenema, Sierra Leone ,grid.463455.50000 0004 1799 2069Viral Hemorrhagic Fever Program, Kenema Government Hospital, Ministry of Health and Sanitation, Kenema, Sierra Leone
| | - John Demby Sandi
- grid.463455.50000 0004 1799 2069Viral Hemorrhagic Fever Program, Kenema Government Hospital, Ministry of Health and Sanitation, Kenema, Sierra Leone
| | - Augustine Goba
- grid.463455.50000 0004 1799 2069Viral Hemorrhagic Fever Program, Kenema Government Hospital, Ministry of Health and Sanitation, Kenema, Sierra Leone
| | - Foday Alhasan
- grid.463455.50000 0004 1799 2069Viral Hemorrhagic Fever Program, Kenema Government Hospital, Ministry of Health and Sanitation, Kenema, Sierra Leone
| | - Donald S. Grant
- grid.463455.50000 0004 1799 2069Viral Hemorrhagic Fever Program, Kenema Government Hospital, Ministry of Health and Sanitation, Kenema, Sierra Leone ,grid.442296.f0000 0001 2290 9707College of Medicine and Allied Health Sciences, University of Sierra Leone, Kenema, Sierra Leone
| | - Sylvanus Okogbenin
- grid.508091.5Irrua Specialist Teaching Hospital, Irrua, Nigeria ,grid.411357.50000 0000 9018 355XFaculty of Clinical Sciences, College of Medicine, Ambrose Alli University, Ekpoma, Nigeria
| | | | - Robert F. Garry
- grid.265219.b0000 0001 2217 8588Department of Microbiology and Immunology, Tulane University, School of Medicine, New Orleans, LA 70112 USA ,grid.505518.c0000 0004 5901 1919Zalgen Labs, LCC, Frederick, MD 21703 USA ,grid.475149.aGlobal Virus Network (GVN), Baltimore, MD 21201 USA
| | - Allison R. Smither
- grid.265219.b0000 0001 2217 8588Department of Microbiology and Immunology, Tulane University, School of Medicine, New Orleans, LA 70112 USA
| | - Mark Zeller
- grid.214007.00000000122199231Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037 USA
| | - Matthias G. Pauthner
- grid.214007.00000000122199231Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037 USA
| | - Michelle McGraw
- grid.214007.00000000122199231Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037 USA
| | - Laura D. Hughes
- grid.214007.00000000122199231Department of Integrative, Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037 USA
| | - Sophie Duraffour
- grid.424065.10000 0001 0701 3136Bernhard Nocht Institute for Tropical Medicine, Hamburg, Germany ,grid.452463.2German Center for Infection Research (DZIF), Partner site Hamburg–Lübeck–Borstel–Riems, Hamburg, Germany
| | - Stephan Günther
- grid.424065.10000 0001 0701 3136Bernhard Nocht Institute for Tropical Medicine, Hamburg, Germany ,grid.452463.2German Center for Infection Research (DZIF), Partner site Hamburg–Lübeck–Borstel–Riems, Hamburg, Germany
| | - Marc A. Suchard
- grid.19006.3e0000 0000 9632 6718Department of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA USA
| | - Philippe Lemey
- grid.5596.f0000 0001 0668 7884Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven - University of Leuven, Leuven, Belgium
| | - Kristian G. Andersen
- grid.214007.00000000122199231Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037 USA ,grid.214007.00000000122199231Scripps Research Translational Institute, La Jolla, CA 92037 USA
| | - Simon Dellicour
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven - University of Leuven, Leuven, Belgium. .,Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, CP160/12 50, av. FD Roosevelt, 1050, Bruxelles, Belgium.
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14
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Kawakubo S, Tomitaka Y, Tomimura K, Koga R, Matsuoka H, Uematsu S, Yamashita K, Ho SYW, Ohshima K. The Recombinogenic History of Turnip Mosaic Potyvirus Reveals its Introduction to Japan in the 19th Century. Virus Evol 2022; 8:veac060. [PMID: 35903148 PMCID: PMC9320297 DOI: 10.1093/ve/veac060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 06/09/2022] [Accepted: 06/24/2022] [Indexed: 11/15/2022] Open
Abstract
Characterizing the detailed spatial and temporal dynamics of plant pathogens can provide
valuable information for crop protection strategies. However, the epidemiological
characteristics and evolutionary trajectories of pathogens can differ markedly from one
country to another. The most widespread and important virus of brassica vegetables, turnip
mosaic virus (TuMV), causes serious plant diseases in Japan. We collected 317 isolates of
TuMV from Raphanus and Brassica plants throughout Japan
over nearly five decades. Genomic sequences from these isolates were combined with
published sequences. We identified a total of eighty-eight independent recombination
events in Japanese TuMV genomes and found eighty-two recombination-type patterns in Japan.
We assessed the evolution of TuMV through space and time using whole and partial genome
sequences of both nonrecombinants and recombinants. Our results suggest that TuMV was
introduced into Japan after the country emerged from its isolationist policy (1639–1854)
in the Edo period and then dispersed to other parts of Japan in the 20th century. The
results of our analyses reveal the complex structure of the TuMV population in Japan and
emphasize the importance of identifying recombination events in the genome. Our study also
provides an example of surveying the epidemiology of a virus that is highly
recombinogenic.
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Affiliation(s)
- Shusuke Kawakubo
- Laboratory of Plant Virology, Department of Biological Resource Science, Faculty of Agriculture, Saga University , 1-banchi, Honjo-machi, Saga, Saga 840-8502, Japan
| | - Yasuhiro Tomitaka
- Laboratory of Plant Virology, Department of Biological Resource Science, Faculty of Agriculture, Saga University , 1-banchi, Honjo-machi, Saga, Saga 840-8502, Japan
- Institute for Plant Protection, National Agriculture and Food Research Organization , 2-1-18 Kannondai, Tsukuba, Ibaraki 305-8666, Japan
| | - Kenta Tomimura
- Laboratory of Plant Virology, Department of Biological Resource Science, Faculty of Agriculture, Saga University , 1-banchi, Honjo-machi, Saga, Saga 840-8502, Japan
- Institute of Fruit Tree and Tea Science, National Agriculture and Food Research Organization , 485-6 Okitsu Nakacho, Shimizu, Shizuoka 424-0292, Japan
| | - Ryoko Koga
- Laboratory of Plant Virology, Department of Biological Resource Science, Faculty of Agriculture, Saga University , 1-banchi, Honjo-machi, Saga, Saga 840-8502, Japan
| | - Hiroki Matsuoka
- Laboratory of Plant Virology, Department of Biological Resource Science, Faculty of Agriculture, Saga University , 1-banchi, Honjo-machi, Saga, Saga 840-8502, Japan
| | - Seiji Uematsu
- Laboratory of Agro-Environmental Science, Warm Region Horticulture Institute, Chiba Prefectural Agriculture and Forestry Research Center , 1762 Yamamoto, Tateyama, Chiba 294-0014, Japan
- Laboratory of Molecular and Cellular Biology, Department of Bioregulation and Bio- interaction, Tokyo University of Agriculture and Technology , 3-5-8 Saiwai-cho, Fuchu, Tokyo 183-8509, Japan
| | - Kazuo Yamashita
- Vegetable Research Institute, Aomori Prefectural Industrial Technology Research Center , 91 Yanagisawa, Inuotose, Rokunohe, Aomori 033-0071, Japan
- Fukuchi Garlic R&S, 4-92 Akane , Fukuda, Nanbu-machi, Aomori 039-0815, Japan
| | - Simon Y W Ho
- School of Life and Environmental Sciences, University of Sydney , Sydney, NSW 2006, Australia
| | - Kazusato Ohshima
- Laboratory of Plant Virology, Department of Biological Resource Science, Faculty of Agriculture, Saga University , 1-banchi, Honjo-machi, Saga, Saga 840-8502, Japan
- The United Graduate School of Agricultural Sciences, Kagoshima University , 1-21-24 Korimoto, Kagoshima, Kagoshima 890-0065, Japan
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15
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Deviatkin AA, Vakulenko YA, Dashian MA, Lukashev AN. Evaluating the Impact of Anthropogenic Factors on the Dissemination of Contemporary Cosmopolitan, Arctic, and Arctic-like Rabies Viruses. Viruses 2021; 14:66. [PMID: 35062270 PMCID: PMC8777955 DOI: 10.3390/v14010066] [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: 12/07/2021] [Accepted: 12/29/2021] [Indexed: 11/16/2022] Open
Abstract
Rabies is a globally prevalent viral zoonosis that causes 59,000 deaths per year and has important economic consequences. Most virus spread is associated with the migration of its primary hosts. Anthropogenic dissemination, mainly via the transportation of rabid dogs, shaped virus ecology a few hundred years ago and is responsible for several current outbreaks. A systematic analysis of aberrant long-distance events in the steppe and Arctic-like groups of rabies virus was performed using statistical (Bayesian) phylogeography and plots of genetic vs. geographic distances. The two approaches produced similar results but had some significant differences and complemented each other. No phylogeographic analysis could be performed for the Arctic group because polar foxes transfer the virus across the whole circumpolar region at high velocity, and there was no correlation between genetic and geographic distances in this virus group. In the Arctic-like group and the steppe subgroup of the cosmopolitan group, a significant number of known sequences (15-20%) was associated with rapid long-distance transfers, which mainly occurred within Eurasia. Some of these events have been described previously, while others have not been documented. Most of the recent long-distance transfers apparently did not result in establishing the introduced virus, but a few had important implications for the phylogeographic history of rabies. Thus, human-mediated long-distance transmission of the rabies virus remains a significant threat that needs to be addressed.
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Affiliation(s)
- Andrei A. Deviatkin
- Laboratory of Molecular Biology and Biochemistry, Institute of Molecular Medicine, Sechenov First Moscow State Medical University, 119435 Moscow, Russia
- The National Medical Research Center for Endocrinology, 117036 Moscow, Russia
| | - Yulia A. Vakulenko
- Martsinovsky Institute of Medical Parasitology, Tropical and Vector Borne Diseases, Sechenov First Moscow State Medical University, 119435 Moscow, Russia; (Y.A.V.); (A.N.L.)
- Department of Virology, Faculty of Biology, Lomonosov Moscow State University, 119234 Moscow, Russia
| | - Mariia A. Dashian
- Faculty of Biomedicine, Pirogov Medical University, 117997 Moscow, Russia;
| | - Alexander N. Lukashev
- Martsinovsky Institute of Medical Parasitology, Tropical and Vector Borne Diseases, Sechenov First Moscow State Medical University, 119435 Moscow, Russia; (Y.A.V.); (A.N.L.)
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16
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Martinet B, Dellicour S, Ghisbain G, Przybyla K, Zambra E, Lecocq T, Boustani M, Baghirov R, Michez D, Rasmont P. Global effects of extreme temperatures on wild bumblebees. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2021; 35:1507-1518. [PMID: 33319368 DOI: 10.1111/cobi.13685] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 12/04/2020] [Accepted: 12/09/2020] [Indexed: 06/12/2023]
Abstract
Climate plays a key role in shaping population trends and determining the geographic distribution of species because of limits in species' thermal tolerance. An evaluation of species tolerance to temperature change can therefore help predict their potential spatial shifts and population trends triggered by ongoing global warming. We assessed inter- and intraspecific variations in heat resistance in relation to body mass, local mean temperatures, and evolutionary relationships in 39 bumblebee species, a major group of pollinators in temperate and cold ecosystems, across 3 continents, 6 biomes, and 20 regions (2386 male specimens). Based on experimental bioassays, we measured the time before heat stupor of bumblebee males at a heatwave temperature of 40 °C. Interspecific variability was significant, in contrast to interpopulational variability, which was consistent with heat resistance being a species-specific trait. Moreover, cold-adapted species are much more sensitive to heat stress than temperate and Mediterranean species. Relative to their sensitivity to extreme temperatures, our results help explain recent population declines and range shifts in bumblebees following climate change.
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Affiliation(s)
- Baptiste Martinet
- Laboratory of Zoology, Research Institute of Biosciences, University of Mons (UMons), Place du Parc 20, Mons, 7000, Belgium
- Evolutionary Biology & Ecology, Université Libre de Bruxelles, Avenue Paul Héger - CP 160/12, Brussels, 1000, Belgium
| | - Simon Dellicour
- Spatial Epidemiology Lab. (SpELL), Université Libre de Bruxelles, CP160/12 50, av. FD Roosevelt, Brussels, 1050, Belgium
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Herestraat 49, Leuven, 3000, Belgium
| | - Guillaume Ghisbain
- Laboratory of Zoology, Research Institute of Biosciences, University of Mons (UMons), Place du Parc 20, Mons, 7000, Belgium
| | - Kimberly Przybyla
- Laboratory of Zoology, Research Institute of Biosciences, University of Mons (UMons), Place du Parc 20, Mons, 7000, Belgium
| | - Ella Zambra
- Laboratory of Zoology, Research Institute of Biosciences, University of Mons (UMons), Place du Parc 20, Mons, 7000, Belgium
| | - Thomas Lecocq
- Laboratory of Zoology, Research Institute of Biosciences, University of Mons (UMons), Place du Parc 20, Mons, 7000, Belgium
- INRAE, URAFPA, University of Lorraine, Nancy, France
| | - Mira Boustani
- Laboratory of Zoology, Research Institute of Biosciences, University of Mons (UMons), Place du Parc 20, Mons, 7000, Belgium
| | - Ruslan Baghirov
- Department of Invertebrate Zoology, Tomsk State University, Leninast 36, Tomsk, 634050, Russia
- Department of Biology and Genetics, Siberian State Medical University, Moskovskiy Trakt, 2, Tomsk, 634050, Russia
| | - Denis Michez
- Laboratory of Zoology, Research Institute of Biosciences, University of Mons (UMons), Place du Parc 20, Mons, 7000, Belgium
| | - Pierre Rasmont
- Laboratory of Zoology, Research Institute of Biosciences, University of Mons (UMons), Place du Parc 20, Mons, 7000, Belgium
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17
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Use of partial N-gene sequences as a tool to monitor progress on rabies control and elimination efforts in Ethiopia. Acta Trop 2021; 221:106022. [PMID: 34161816 PMCID: PMC8652542 DOI: 10.1016/j.actatropica.2021.106022] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Revised: 06/10/2021] [Accepted: 06/15/2021] [Indexed: 11/21/2022]
Abstract
Ethiopia is one of the African countries most affected by rabies. A coarse catalog of rabies viruses (RABV) was created as a benchmark to assess the impact of control and elimination activities. We evaluated a 726 bp amplicon at the end of the N-gene to infer viral lineages in circulation using maximum likelihood and Bayesian methods for phylogenetic reconstruction. We sequenced 228 brain samples from wild and domestic animals collected in five Ethiopian regions during 2010-2017. Results identified co-circulating RABV lineages that are causing recurrent spillover infections into wildlife and domestic animals. We found no evidence of importation of RABVs from other African countries or vaccine-induced cases in the area studied. A divergent RABV lineage might be involved in an independent rabies cycle in jackals. This investigation provides a feasible approach to assess rabies control and elimination efforts in resource-limited countries.
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18
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Nahata KD, Bollen N, Gill MS, Layan M, Bourhy H, Dellicour S, Baele G. On the Use of Phylogeographic Inference to Infer the Dispersal History of Rabies Virus: A Review Study. Viruses 2021; 13:v13081628. [PMID: 34452492 PMCID: PMC8402743 DOI: 10.3390/v13081628] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 08/06/2021] [Accepted: 08/11/2021] [Indexed: 12/28/2022] Open
Abstract
Rabies is a neglected zoonotic disease which is caused by negative strand RNA-viruses belonging to the genus Lyssavirus. Within this genus, rabies viruses circulate in a diverse set of mammalian reservoir hosts, is present worldwide, and is almost always fatal in non-vaccinated humans. Approximately 59,000 people are still estimated to die from rabies each year, leading to a global initiative to work towards the goal of zero human deaths from dog-mediated rabies by 2030, requiring scientific efforts from different research fields. The past decade has seen a much increased use of phylogeographic and phylodynamic analyses to study the evolution and spread of rabies virus. We here review published studies in these research areas, making a distinction between the geographic resolution associated with the available sequence data. We pay special attention to environmental factors that these studies found to be relevant to the spread of rabies virus. Importantly, we highlight a knowledge gap in terms of applying these methods when all required data were available but not fully exploited. We conclude with an overview of recent methodological developments that have yet to be applied in phylogeographic and phylodynamic analyses of rabies virus.
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Affiliation(s)
- Kanika D. Nahata
- Department of Microbiology, Immunology and Transplantation, Rega Institute KU Leuven, 3000 Leuven, Belgium; (N.B.); (M.S.G.); (S.D.); (G.B.)
- Correspondence:
| | - Nena Bollen
- Department of Microbiology, Immunology and Transplantation, Rega Institute KU Leuven, 3000 Leuven, Belgium; (N.B.); (M.S.G.); (S.D.); (G.B.)
| | - Mandev S. Gill
- Department of Microbiology, Immunology and Transplantation, Rega Institute KU Leuven, 3000 Leuven, Belgium; (N.B.); (M.S.G.); (S.D.); (G.B.)
| | - Maylis Layan
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Sorbonne Université, UMR2000, CNRS, 75015 Paris, France;
| | - Hervé Bourhy
- Lyssavirus Epidemiology and Neuropathology Unit, Institut Pasteur, 75015 Paris, France;
- WHO Collaborating Centre for Reference and Research on Rabies, Institut Pasteur, 75015 Paris, France
| | - Simon Dellicour
- Department of Microbiology, Immunology and Transplantation, Rega Institute KU Leuven, 3000 Leuven, Belgium; (N.B.); (M.S.G.); (S.D.); (G.B.)
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, 1050 Bruxelles, Belgium
| | - Guy Baele
- Department of Microbiology, Immunology and Transplantation, Rega Institute KU Leuven, 3000 Leuven, Belgium; (N.B.); (M.S.G.); (S.D.); (G.B.)
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19
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Dellicour S, Gill MS, Faria NR, Rambaut A, Pybus OG, Suchard MA, Lemey P. Relax, Keep Walking - A Practical Guide to Continuous Phylogeographic Inference with BEAST. Mol Biol Evol 2021; 38:3486-3493. [PMID: 33528560 PMCID: PMC8321535 DOI: 10.1093/molbev/msab031] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Spatially explicit phylogeographic analyses can be performed with an inference framework that employs relaxed random walks to reconstruct phylogenetic dispersal histories in continuous space. This core model was first implemented 10 years ago and has opened up new opportunities in the field of phylodynamics, allowing researchers to map and analyze the spatial dissemination of rapidly evolving pathogens. We here provide a detailed and step-by-step guide on how to set up, run, and interpret continuous phylogeographic analyses using the programs BEAUti, BEAST, Tracer, and TreeAnnotator.
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Affiliation(s)
- Simon Dellicour
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Mandev S Gill
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Nuno R Faria
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Imperial College London, London, United Kingdom
- Department of Zoology, University of Oxford, Oxford, United Kingdom
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Andrew Rambaut
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Marc A Suchard
- Department of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
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20
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Munsey A, Mwiine FN, Ochwo S, Velazquez-Salinas L, Ahmed Z, Maree F, Rodriguez LL, Rieder E, Perez A, Dellicour S, VanderWaal K. Phylogeographic analysis of foot-and-mouth disease virus serotype O dispersal and associated drivers in East Africa. Mol Ecol 2021; 30:3815-3825. [PMID: 34008868 DOI: 10.1111/mec.15991] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 05/06/2021] [Accepted: 05/10/2021] [Indexed: 02/06/2023]
Abstract
The continued endemicity of foot and mouth disease virus (FMDV) in East Africa has significant implications for livestock production and poverty reduction, yet its complex epidemiology in endemic settings remains poorly understood. Identifying FMDV dispersal routes and drivers of transmission is key to improved control strategies. Environmental heterogeneity and anthropogenic drivers (e.g., demand for animal products) can impact viral spread by influencing host movements. Here, we utilized FMDV serotype O VP1 genetic sequences and corresponding spatiotemporal data in order to (i) infer the recent dispersal history, and (II) investigate the impact of external factors (cattle density, human population density, proximity to livestock markets, and drought) on dispersal velocity, location, and direction of FMDV serotype O in East Africa. We identified statistical evidence of long-distance transmission events, and we found that FMDV serotype O tends to remain circulating in areas of high cattle density, high human population density, and in close proximity to livestock markets. The latter two findings highlight the influence of anthropogenic factors on FMDV serotype O spread in this region. These findings contribute to the understanding of FMDV epidemiology in East Africa and can help guide improved control measures.
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Affiliation(s)
- Anna Munsey
- Veterinary Population Medicine Department, University of Minnesota College of Veterinary Medicine, St. Paul, MN, USA
| | - Frank Norbert Mwiine
- Makerere University College of Veterinary Medicine, Animal Resources and Biosecurity (COVAB), Kampala, Uganda
| | - Sylvester Ochwo
- Makerere University College of Veterinary Medicine, Animal Resources and Biosecurity (COVAB), Kampala, Uganda
| | - Lauro Velazquez-Salinas
- Veterinary Population Medicine Department, University of Minnesota College of Veterinary Medicine, St. Paul, MN, USA.,Foreign Animal Disease Research Unit, Plum Island Animal Disease Center, Agricultural Research Service (ARS), United States Department of Agriculture, Greenport, NY, USA
| | - Zaheer Ahmed
- Animal and Plant Health Inspection Services (APHIS), National Veterinary Services Laboratories, Foreign Animal Disease Diagnostic Laboratory, Plum Island Animal Disease Center, United States Department of Agriculture, Greenport, NY, USA
| | - Francois Maree
- Onderstepoort Veterinary Institute, Pretoria, South Africa
| | - Luis L Rodriguez
- Foreign Animal Disease Research Unit, Plum Island Animal Disease Center, Agricultural Research Service (ARS), United States Department of Agriculture, Greenport, NY, USA
| | - Elizabeth Rieder
- Foreign Animal Disease Research Unit, Plum Island Animal Disease Center, Agricultural Research Service (ARS), United States Department of Agriculture, Greenport, NY, USA
| | - Andres Perez
- Veterinary Population Medicine Department, University of Minnesota College of Veterinary Medicine, St. Paul, MN, USA
| | - Simon Dellicour
- Spatial Epidemiology Laboratory (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium.,Department of Microbiology, Immunology and Transplantation, Laboratory for Clinical and Epidemiological Virology, Rega Institute, KU Leuven, Leuven, Belgium
| | - Kimberly VanderWaal
- Veterinary Population Medicine Department, University of Minnesota College of Veterinary Medicine, St. Paul, MN, USA
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21
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Mathematical modelling and phylodynamics for the study of dog rabies dynamics and control: A scoping review. PLoS Negl Trop Dis 2021; 15:e0009449. [PMID: 34043640 PMCID: PMC8189497 DOI: 10.1371/journal.pntd.0009449] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 06/09/2021] [Accepted: 05/05/2021] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Rabies is a fatal yet vaccine-preventable disease. In the last two decades, domestic dog populations have been shown to constitute the predominant reservoir of rabies in developing countries, causing 99% of human rabies cases. Despite substantial control efforts, dog rabies is still widely endemic and is spreading across previously rabies-free areas. Developing a detailed understanding of dog rabies dynamics and the impact of vaccination is essential to optimize existing control strategies and developing new ones. In this scoping review, we aimed at disentangling the respective contributions of mathematical models and phylodynamic approaches to advancing the understanding of rabies dynamics and control in domestic dog populations. We also addressed the methodological limitations of both approaches and the remaining issues related to studying rabies spread and how this could be applied to rabies control. METHODOLOGY/PRINCIPAL FINDINGS We reviewed how mathematical modelling of disease dynamics and phylodynamics have been developed and used to characterize dog rabies dynamics and control. Through a detailed search of the PubMed, Web of Science, and Scopus databases, we identified a total of n = 59 relevant studies using mathematical models (n = 30), phylodynamic inference (n = 22) and interdisciplinary approaches (n = 7). We found that despite often relying on scarce rabies epidemiological data, mathematical models investigated multiple aspects of rabies dynamics and control. These models confirmed the overwhelming efficacy of massive dog vaccination campaigns in all settings and unraveled the role of dog population structure and frequent introductions in dog rabies maintenance. Phylodynamic approaches successfully disentangled the evolutionary and environmental determinants of rabies dispersal and consistently reported support for the role of reintroduction events and human-mediated transportation over long distances in the maintenance of rabies in endemic areas. Potential biases in data collection still need to be properly accounted for in most of these analyses. Finally, interdisciplinary studies were determined to provide the most comprehensive assessments through hypothesis generation and testing. They also represent new avenues, especially concerning the reconstruction of local transmission chains or clusters through data integration. CONCLUSIONS/SIGNIFICANCE Despite advances in rabies knowledge, substantial uncertainty remains regarding the mechanisms of local spread, the role of wildlife in dog rabies maintenance, and the impact of community behavior on the efficacy of control strategies including vaccination of dogs. Future integrative approaches that use phylodynamic analyses and mechanistic models within a single framework could take full advantage of not only viral sequences but also additional epidemiological information as well as dog ecology data to refine our understanding of rabies spread and control. This would represent a significant improvement on past studies and a promising opportunity for canine rabies research in the frame of the One Health concept that aims to achieve better public health outcomes through cross-sector collaboration.
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22
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Voupawoe G, Varkpeh R, Kamara V, Sieh S, Traoré A, De Battisti C, Angot A, Loureiro LFLDJ, Soumaré B, Dauphin G, Abebe W, Coetzer A, Scott T, Nel L, Blanton J, Dacheux L, Bonas S, Bourhy H, Gourlaouen M, Leopardi S, De Benedictis P, Léchenne M, Zinsstag J, Mauti S. Rabies control in Liberia: Joint efforts towards zero by 30. Acta Trop 2021; 216:105787. [PMID: 33385361 DOI: 10.1016/j.actatropica.2020.105787] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Revised: 11/24/2020] [Accepted: 11/25/2020] [Indexed: 01/24/2023]
Abstract
Despite declaration as a national priority disease, dog rabies remains endemic in Liberia, with surveillance systems and disease control activities still developing. The objective of these initial efforts was to establish animal rabies diagnostics, foster collaboration between all rabies control stakeholders, and develop a short-term action plan with estimated costs for rabies control and elimination in Liberia. Four rabies diagnostic tests, the direct fluorescent antibody (DFA) test, the direct immunohistochemical test (dRIT), the reverse transcriptase polymerase chain reaction (RT-PCR) assay and the rapid immunochromatographic diagnostic test (RIDT), were implemented at the Central Veterinary Laboratory (CVL) in Monrovia between July 2017 and February 2018. Seven samples (n=7) out of eight suspected animals were confirmed positive for rabies lyssavirus, and molecular analyses revealed that all isolates belonged to the Africa 2 lineage, subgroup H. During a comprehensive in-country One Health rabies stakeholder meeting in 2018, a practical workplan, a short-term action plan and an accurately costed mass dog vaccination strategy were developed. Liberia is currently at stage 1.5/5 of the Stepwise Approach towards Rabies Elimination (SARE) tool, which corresponds with countries that are scaling up local-level interventions (e.g. dog vaccination campaigns) to the national level. Overall an estimated 5.3 - 8 million USD invested over 13 years is needed to eliminate rabies in Liberia by 2030. Liberia still has a long road to become free from dog-rabies. However, the dialogue between all relevant stakeholders took place, and disease surveillance considerably improved through implementing rabies diagnosis at the CVL. The joint efforts of diverse national and international stakeholders laid important foundations to achieve the goal of zero dog-mediated human rabies deaths by 2030.
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23
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Maljkovic Berry I, Melendrez MC, Bishop-Lilly KA, Rutvisuttinunt W, Pollett S, Talundzic E, Morton L, Jarman RG. Next Generation Sequencing and Bioinformatics Methodologies for Infectious Disease Research and Public Health: Approaches, Applications, and Considerations for Development of Laboratory Capacity. J Infect Dis 2021; 221:S292-S307. [PMID: 31612214 DOI: 10.1093/infdis/jiz286] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
Next generation sequencing (NGS) combined with bioinformatics has successfully been used in a vast array of analyses for infectious disease research of public health relevance. For instance, NGS and bioinformatics approaches have been used to identify outbreak origins, track transmissions, investigate epidemic dynamics, determine etiological agents of a disease, and discover novel human pathogens. However, implementation of high-quality NGS and bioinformatics in research and public health laboratories can be challenging. These challenges mainly include the choice of the sequencing platform and the sequencing approach, the choice of bioinformatics methodologies, access to the appropriate computation and information technology infrastructure, and recruiting and retaining personnel with the specialized skills and experience in this field. In this review, we summarize the most common NGS and bioinformatics workflows in the context of infectious disease genomic surveillance and pathogen discovery, and highlight the main challenges and considerations for setting up an NGS and bioinformatics-focused infectious disease research public health laboratory. We describe the most commonly used sequencing platforms and review their strengths and weaknesses. We review sequencing approaches that have been used for various pathogens and study questions, as well as the most common difficulties associated with these approaches that should be considered when implementing in a public health or research setting. In addition, we provide a review of some common bioinformatics tools and procedures used for pathogen discovery and genome assembly, along with the most common challenges and solutions. Finally, we summarize the bioinformatics of advanced viral, bacterial, and parasite pathogen characterization, including types of study questions that can be answered when utilizing NGS and bioinformatics.
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Affiliation(s)
- Irina Maljkovic Berry
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, Maryland
| | | | - Kimberly A Bishop-Lilly
- Genomics and Bioinformatics Department, Biological Defense Research Directorate, Naval Medical Research Center-Frederick, Fort Detrick, Maryland
| | - Wiriya Rutvisuttinunt
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, Maryland
| | - Simon Pollett
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, Maryland.,Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland
| | - Eldin Talundzic
- Division of Parasitic Diseases and Malaria, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Lindsay Morton
- Global Emerging Infections Surveillance, Armed Forces Health Surveillance Branch, Silver Spring, Maryland
| | - Richard G Jarman
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, Maryland
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24
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Kalkauskas A, Perron U, Sun Y, Goldman N, Baele G, Guindon S, De Maio N. Sampling bias and model choice in continuous phylogeography: Getting lost on a random walk. PLoS Comput Biol 2021; 17:e1008561. [PMID: 33406072 PMCID: PMC7815209 DOI: 10.1371/journal.pcbi.1008561] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 01/19/2021] [Accepted: 11/24/2020] [Indexed: 12/11/2022] Open
Abstract
Phylogeographic inference allows reconstruction of past geographical spread of pathogens or living organisms by integrating genetic and geographic data. A popular model in continuous phylogeography—with location data provided in the form of latitude and longitude coordinates—describes spread as a Brownian motion (Brownian Motion Phylogeography, BMP) in continuous space and time, akin to similar models of continuous trait evolution. Here, we show that reconstructions using this model can be strongly affected by sampling biases, such as the lack of sampling from certain areas. As an attempt to reduce the effects of sampling bias on BMP, we consider the addition of sequence-free samples from under-sampled areas. While this approach alleviates the effects of sampling bias, in most scenarios this will not be a viable option due to the need for prior knowledge of an outbreak’s spatial distribution. We therefore consider an alternative model, the spatial Λ-Fleming-Viot process (ΛFV), which has recently gained popularity in population genetics. Despite the ΛFV’s robustness to sampling biases, we find that the different assumptions of the ΛFV and BMP models result in different applicabilities, with the ΛFV being more appropriate for scenarios of endemic spread, and BMP being more appropriate for recent outbreaks or colonizations. Phylogeography studies past location and migration using information from current geographic locations of genetic sequences. For example, phylogeography can be used to reconstruct the history of geographical spread of an outbreak using the genetic sequences of the pathogen collected at different times and locations. Here, we investigate the effects of different model assumptions on phylogeographic inference. In particular, we examine the effects of the strategy used to collect samples. We show that sample collection biases can have a strong impact on the quality of phylogeographic reconstruction: geographically biased sampling scheme can be very detrimental for popular continuous phylogeography models. We consider different ways to counter these effects, from utilising alternative phylogeographic models, to the inclusion of partially informative samples (known cases without genetic sequences). While these strategies do alleviate the effects of sampling biases, they also lead to considerable additional computational burden. We also investigate the intrinsic differences of different phylogeographic models, and their effects on reconstructed patterns in different scenarios.
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Affiliation(s)
- Antanas Kalkauskas
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom
| | - Umberto Perron
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom
| | - Yuxuan Sun
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom
| | - Nick Goldman
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom
| | - Guy Baele
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Stephane Guindon
- Department of Computer Science, LIRMM, CNRS and Université de Montpellier, Montpellier, France
| | - Nicola De Maio
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom
- * E-mail:
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25
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Host relatedness and landscape connectivity shape pathogen spread in the puma, a large secretive carnivore. Commun Biol 2021; 4:12. [PMID: 33398025 PMCID: PMC7782801 DOI: 10.1038/s42003-020-01548-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Accepted: 11/25/2020] [Indexed: 01/29/2023] Open
Abstract
Urban expansion can fundamentally alter wildlife movement and gene flow, but how urbanization alters pathogen spread is poorly understood. Here, we combine high resolution host and viral genomic data with landscape variables to examine the context of viral spread in puma (Puma concolor) from two contrasting regions: one bounded by the wildland urban interface (WUI) and one unbounded with minimal anthropogenic development (UB). We found landscape variables and host gene flow explained significant amounts of variation of feline immunodeficiency virus (FIV) spread in the WUI, but not in the unbounded region. The most important predictors of viral spread also differed; host spatial proximity, host relatedness, and mountain ranges played a role in FIV spread in the WUI, whereas roads might have facilitated viral spread in the unbounded region. Our research demonstrates how anthropogenic landscapes can alter pathogen spread, providing a more nuanced understanding of host-pathogen relationships to inform disease ecology in free-ranging species.
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26
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Whitmer SLM, Lo MK, Sazzad HMS, Zufan S, Gurley ES, Sultana S, Amman B, Ladner JT, Rahman MZ, Doan S, Satter SM, Flora MS, Montgomery JM, Nichol ST, Spiropoulou CF, Klena JD. Inference of Nipah virus evolution, 1999-2015. Virus Evol 2021; 7:veaa062. [PMID: 34422315 PMCID: PMC7947586 DOI: 10.1093/ve/veaa062] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Despite near-annual human outbreaks of Nipah virus (NiV) disease in Bangladesh, typically due to individual spillover events from the local bat population, only twenty whole-genome NiV sequences exist from humans and ten from bats. NiV whole-genome sequences from annual outbreaks have been challenging to generate, primarily due to the low viral load in human throat swab and serum specimens. Here, we used targeted enrichment with custom NiV-specific probes and generated thirty-five additional unique full-length genomic sequences directly from human specimens and viral isolates. We inferred the temporal and geographic evolutionary history of NiV in Bangladesh and expanded a tool to visualize NiV spatio-temporal spread from a Bayesian continuous diffusion analysis. We observed that strains from Bangladesh segregated into two distinct clades that have intermingled geographically in Bangladesh over time and space. As these clades expanded geographically and temporally, we did not observe evidence for significant branch and site-specific selection, except for a single site in the Henipavirus L polymerase. However, the Bangladesh 1 and 2 clades are differentiated by mutations initially occurring in the polymerase, with additional mutations accumulating in the N, G, F, P, and L genes on external branches. Modeling the historic geographical and temporal spread demonstrates that while widespread, NiV does not exhibit significant genetic variation in Bangladesh. Thus, future public health measures should address whether NiV within in the bat population also exhibits comparable genetic variation, if zoonotic transmission results in a genetic bottleneck and if surveillance techniques are detecting only a subset of NiV.
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Affiliation(s)
- Shannon L M Whitmer
- Viral Special Pathogens Branch, Centers for Disease Control and Prevention, 1600 Clifton Rd. NE, Atlanta, GA 30329, USA
| | - Michael K Lo
- Viral Special Pathogens Branch, Centers for Disease Control and Prevention, 1600 Clifton Rd. NE, Atlanta, GA 30329, USA
| | - Hossain M S Sazzad
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr, b), Dhaka, Bangladesh
- Kirby Institute, University of New South Wales, Sydney, NSW, Australia
| | - Sara Zufan
- Viral Special Pathogens Branch, Centers for Disease Control and Prevention, 1600 Clifton Rd. NE, Atlanta, GA 30329, USA
| | - Emily S Gurley
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr, b), Dhaka, Bangladesh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Sharmin Sultana
- Institute of Epidemiology, Disease Control and Research, Bangladesh
| | - Brian Amman
- Viral Special Pathogens Branch, Centers for Disease Control and Prevention, 1600 Clifton Rd. NE, Atlanta, GA 30329, USA
| | - Jason T Ladner
- The Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, AZ 86011, USA
| | - Mohammed Ziaur Rahman
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr, b), Dhaka, Bangladesh
| | - Stephanie Doan
- The Center for Global Health, Centers for Disease Control and Prevention, 1600 Clifton Rd. NE, Atlanta, GA 30329
| | - Syed M Satter
- Institute of Epidemiology, Disease Control and Research, Bangladesh
| | - Meerjady S Flora
- Institute of Epidemiology, Disease Control and Research, Bangladesh
| | - Joel M Montgomery
- Viral Special Pathogens Branch, Centers for Disease Control and Prevention, 1600 Clifton Rd. NE, Atlanta, GA 30329, USA
| | - Stuart T Nichol
- Viral Special Pathogens Branch, Centers for Disease Control and Prevention, 1600 Clifton Rd. NE, Atlanta, GA 30329, USA
| | - Christina F Spiropoulou
- Viral Special Pathogens Branch, Centers for Disease Control and Prevention, 1600 Clifton Rd. NE, Atlanta, GA 30329, USA
| | - John D Klena
- Viral Special Pathogens Branch, Centers for Disease Control and Prevention, 1600 Clifton Rd. NE, Atlanta, GA 30329, USA
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27
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Bourhy H, de Melo GD, Tarantola A. [New aspects of rabies control]. BULLETIN DE L'ACADEMIE NATIONALE DE MEDECINE 2020; 204:1000-1009. [PMID: 32981935 PMCID: PMC7500396 DOI: 10.1016/j.banm.2020.09.036] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Accepted: 09/10/2020] [Indexed: 12/25/2022]
Abstract
Rabies still causes about 60,000 human deaths per year, mainly in poor populations in Africa and Asia. However, since Louis Pasteur developed the first vaccine 130 years ago, prophylactic measures have been considerably improved and simplified. They now consist of the vaccine combined with purified rabies immunoglobulins of equine or human origin. In general, however, post-exposure prophylaxis protocols are long and expensive. Furthermore, the immunoglobulins used for associated serotherapy are costly and not widely available in developing countries. Approaches have been developed to deal with these two issues that offer hope for a paradigm shift for the benefit of exposed populations. Finally, mass rabies vaccination in dogs, which are the most cost-effective measure for preventing rabies in humans, are difficult to implement and sometimes have moderate effectiveness. The identification and analysis of the epidemiological drivers conditioning the circulation of the virus in dog populations allow a better understanding of the key control points that need to be associated with these campaigns for a better efficacy.
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Affiliation(s)
- H Bourhy
- Unité lyssavirus, épidémiologie et neuropathologie, centre collaborateur de l'Organisation mondiale de la santé de référence et de recherche sur la rage, institut Pasteur, 28, rue du Docteur Roux, 75724 Paris cedex 15, France
| | - G D de Melo
- Unité lyssavirus, épidémiologie et neuropathologie, centre collaborateur de l'Organisation mondiale de la santé de référence et de recherche sur la rage, institut Pasteur, 28, rue du Docteur Roux, 75724 Paris cedex 15, France
| | - A Tarantola
- Unité lyssavirus, épidémiologie et neuropathologie, centre collaborateur de l'Organisation mondiale de la santé de référence et de recherche sur la rage, institut Pasteur, 28, rue du Docteur Roux, 75724 Paris cedex 15, France
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28
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Dellicour S, Lequime S, Vrancken B, Gill MS, Bastide P, Gangavarapu K, Matteson NL, Tan Y, du Plessis L, Fisher AA, Nelson MI, Gilbert M, Suchard MA, Andersen KG, Grubaugh ND, Pybus OG, Lemey P. Epidemiological hypothesis testing using a phylogeographic and phylodynamic framework. Nat Commun 2020; 11:5620. [PMID: 33159066 PMCID: PMC7648063 DOI: 10.1038/s41467-020-19122-z] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 09/30/2020] [Indexed: 01/05/2023] Open
Abstract
Computational analyses of pathogen genomes are increasingly used to unravel the dispersal history and transmission dynamics of epidemics. Here, we show how to go beyond historical reconstructions and use spatially-explicit phylogeographic and phylodynamic approaches to formally test epidemiological hypotheses. We illustrate our approach by focusing on the West Nile virus (WNV) spread in North America that has substantially impacted public, veterinary, and wildlife health. We apply an analytical workflow to a comprehensive WNV genome collection to test the impact of environmental factors on the dispersal of viral lineages and on viral population genetic diversity through time. We find that WNV lineages tend to disperse faster in areas with higher temperatures and we identify temporal variation in temperature as a main predictor of viral genetic diversity through time. By contrasting inference with simulation, we find no evidence for viral lineages to preferentially circulate within the same migratory bird flyway, suggesting a substantial role for non-migratory birds or mosquito dispersal along the longitudinal gradient.
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Affiliation(s)
- Simon Dellicour
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, CP160/12, 50 Avenue FD Roosevelt, 1050, Bruxelles, Belgium.
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Herestraat 49, 3000, Leuven, Belgium.
| | - Sebastian Lequime
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Bram Vrancken
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Mandev S Gill
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Paul Bastide
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Karthik Gangavarapu
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, 92037, USA
| | - Nathaniel L Matteson
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, 92037, USA
| | - Yi Tan
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Infectious Diseases Group, J. Craig Venter Institute, Rockville, MD, USA
| | | | - Alexander A Fisher
- Department of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Martha I Nelson
- Fogarty International Center, National Institutes of Health, Bethesda, MD, 20894, USA
| | - Marius Gilbert
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, CP160/12, 50 Avenue FD Roosevelt, 1050, Bruxelles, Belgium
| | - Marc A Suchard
- Department of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Kristian G Andersen
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, 92037, USA
- Scripps Research Translational Institute, La Jolla, CA, 92037, USA
| | - Nathan D Grubaugh
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, 06510, USA
| | | | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
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29
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Dellicour S, Lemey P, Artois J, Lam TT, Fusaro A, Monne I, Cattoli G, Kuznetsov D, Xenarios I, Dauphin G, Kalpravidh W, Von Dobschuetz S, Claes F, Newman SH, Suchard MA, Baele G, Gilbert M. Incorporating heterogeneous sampling probabilities in continuous phylogeographic inference - Application to H5N1 spread in the Mekong region. Bioinformatics 2020; 36:2098-2104. [PMID: 31790143 DOI: 10.1093/bioinformatics/btz882] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Revised: 11/01/2019] [Accepted: 11/22/2019] [Indexed: 12/25/2022] Open
Abstract
MOTIVATION The potentially low precision associated with the geographic origin of sampled sequences represents an important limitation for spatially explicit (i.e. continuous) phylogeographic inference of fast-evolving pathogens such as RNA viruses. A substantial proportion of publicly available sequences is geo-referenced at broad spatial scale such as the administrative unit of origin, rather than more precise locations (e.g. geographic coordinates). Most frequently, such sequences are either discarded prior to continuous phylogeographic inference or arbitrarily assigned to the geographic coordinates of the centroid of their administrative area of origin for lack of a better alternative. RESULTS We here implement and describe a new approach that allows to incorporate heterogeneous prior sampling probabilities over a geographic area. External data, such as outbreak locations, are used to specify these prior sampling probabilities over a collection of sub-polygons. We apply this new method to the analysis of highly pathogenic avian influenza H5N1 clade data in the Mekong region. Our method allows to properly include, in continuous phylogeographic analyses, H5N1 sequences that are only associated with large administrative areas of origin and assign them with more accurate locations. Finally, we use continuous phylogeographic reconstructions to analyse the dispersal dynamics of different H5N1 clades and investigate the impact of environmental factors on lineage dispersal velocities. AVAILABILITY AND IMPLEMENTATION Our new method allowing heterogeneous sampling priors for continuous phylogeographic inference is implemented in the open-source multi-platform software package BEAST 1.10. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Simon Dellicour
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, 3000 Leuven, Belgium.,Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, 1050 Bruxelles, Belgium
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, 3000 Leuven, Belgium
| | - Jean Artois
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, 1050 Bruxelles, Belgium
| | - Tommy T Lam
- State Key Laboratory of Emerging Infectious Diseases, School of Public Health, The University of Hong Kong, Hong Kong SAR, China
| | - Alice Fusaro
- Department of Comparative Biomedical Sciences, Istituto Zooprofilattico Sperimentale delle Venezie (IZSVe), Legnaro, Italy
| | - Isabella Monne
- Department of Comparative Biomedical Sciences, Istituto Zooprofilattico Sperimentale delle Venezie (IZSVe), Legnaro, Italy
| | - Giovanni Cattoli
- Department of Comparative Biomedical Sciences, Istituto Zooprofilattico Sperimentale delle Venezie (IZSVe), Legnaro, Italy.,Animal Production and Health Laboratory, Joint FAO/IAEA Division, 2444 Seibersdorf, Austria
| | | | - Ioannis Xenarios
- Center for Integrative Genomics, University of Lausanne, 1005 Lausanne, Switzerland
| | | | - Wantanee Kalpravidh
- Food and Agriculture Organization of the United Nations, Regional Office for Asia and the Pacific, Emergency Center of the Transboundary Animal Diseases, Bangkok 10200, Thailand
| | | | - Filip Claes
- Food and Agriculture Organization of the United Nations, Regional Office for Asia and the Pacific, Emergency Center of the Transboundary Animal Diseases, Bangkok 10200, Thailand
| | - Scott H Newman
- Food and Agriculture Organization of the United Nations, Regional Office for Africa, Accra, Ghana
| | - Marc A Suchard
- Department of Biomathematics, David Geffen School of Medicine, Los Angeles, CA, USA.,Department of Biostatistics, Fielding School of Public Health, Los Angeles, CA, USA.,Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Guy Baele
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, 3000 Leuven, Belgium
| | - Marius Gilbert
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, 1050 Bruxelles, Belgium
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30
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He WT, Ji X, He W, Dellicour S, Wang S, Li G, Zhang L, Gilbert M, Zhu H, Xing G, Veit M, Huang Z, Han GZ, Huang Y, Suchard MA, Baele G, Lemey P, Su S. Genomic Epidemiology, Evolution, and Transmission Dynamics of Porcine Deltacoronavirus. Mol Biol Evol 2020; 37:2641-2654. [PMID: 32407507 PMCID: PMC7454817 DOI: 10.1093/molbev/msaa117] [Citation(s) in RCA: 72] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has shown once again that coronavirus (CoV) in animals are potential sources for epidemics in humans. Porcine deltacoronavirus (PDCoV) is an emerging enteropathogen of swine with a worldwide distribution. Here, we implemented and described an approach to analyze the epidemiology of PDCoV following its emergence in the pig population. We performed an integrated analysis of full genome sequence data from 21 newly sequenced viruses, along with comprehensive epidemiological surveillance data collected globally over the last 15 years. We found four distinct phylogenetic lineages of PDCoV, which differ in their geographic circulation patterns. Interestingly, we identified more frequent intra- and interlineage recombination and higher virus genetic diversity in the Chinese lineages compared with the USA lineage where pigs are raised in different farming systems and ecological environments. Most recombination breakpoints are located in the ORF1ab gene rather than in genes encoding structural proteins. We also identified five amino acids under positive selection in the spike protein suggesting a role for adaptive evolution. According to structural mapping, three positively selected sites are located in the N-terminal domain of the S1 subunit, which is the most likely involved in binding to a carbohydrate receptor, whereas the other two are located in or near the fusion peptide of the S2 subunit and thus might affect membrane fusion. Finally, our phylogeographic investigations highlighted notable South-North transmission as well as frequent long-distance dispersal events in China that could implicate human-mediated transmission. Our findings provide new insights into the evolution and dispersal of PDCoV that contribute to our understanding of the critical factors involved in CoVs emergence.
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Affiliation(s)
- Wan-Ting He
- MOE International Joint Collaborative Research Laboratory for Animal Health & Food Safety, Jiangsu Engineering Laboratory of Animal Immunology, Institute of Immunology, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
| | - Xiang Ji
- Departments of Biomathematics and Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA.,Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA.,Department of Mathematics, Tulane University, New Orleans, LA
| | - Wei He
- MOE International Joint Collaborative Research Laboratory for Animal Health & Food Safety, Jiangsu Engineering Laboratory of Animal Immunology, Institute of Immunology, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
| | - Simon Dellicour
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium.,Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium
| | - Shilei Wang
- MOE International Joint Collaborative Research Laboratory for Animal Health & Food Safety, Jiangsu Engineering Laboratory of Animal Immunology, Institute of Immunology, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
| | - Gairu Li
- MOE International Joint Collaborative Research Laboratory for Animal Health & Food Safety, Jiangsu Engineering Laboratory of Animal Immunology, Institute of Immunology, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
| | - Letian Zhang
- MOE International Joint Collaborative Research Laboratory for Animal Health & Food Safety, Jiangsu Engineering Laboratory of Animal Immunology, Institute of Immunology, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
| | - Marius Gilbert
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium
| | - Henan Zhu
- Departments of Biomathematics and Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA.,Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA
| | - Gang Xing
- Key Laboratory of Animal Virology of Ministry of Agriculture, Zhejiang University, Hangzhou, China
| | - Michael Veit
- Institute for Virology, Center for Infection Medicine, Veterinary Faculty, Free University Berlin, Berlin, Germany
| | - Zhen Huang
- Zhengzhou New Channel Agricultural Technology Co., Ltd, Zhengzhou, Henan, China
| | - Guan-Zhu Han
- Jiangsu Key Laboratory for Microbes and Functional Genomics, College of Life Sciences, Nanjing Normal University, Nanjing, Jiangsu, China
| | - Yaowei Huang
- Key Laboratory of Animal Virology of Ministry of Agriculture, Zhejiang University, Hangzhou, China
| | - Marc A Suchard
- Departments of Biomathematics and Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA.,Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA
| | - Guy Baele
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium
| | - Shuo Su
- MOE International Joint Collaborative Research Laboratory for Animal Health & Food Safety, Jiangsu Engineering Laboratory of Animal Immunology, Institute of Immunology, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
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31
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Hill SC, de Souza R, Thézé J, Claro I, Aguiar RS, Abade L, Santos FCP, Cunha MS, Nogueira JS, Salles FCS, Rocco IM, Maeda AY, Vasami FGS, du Plessis L, Silveira PP, de Jesus JG, Quick J, Fernandes NCCA, Guerra JM, Réssio RA, Giovanetti M, Alcantara LCJ, Cirqueira CS, Díaz-Delgado J, Macedo FLL, Timenetsky MDCST, de Paula R, Spinola R, Telles de Deus J, Mucci LF, Tubaki RM, de Menezes RMT, Ramos PL, de Abreu AL, Cruz LN, Loman N, Dellicour S, Pybus OG, Sabino EC, Faria NR. Genomic Surveillance of Yellow Fever Virus Epizootic in São Paulo, Brazil, 2016 - 2018. PLoS Pathog 2020; 16:e1008699. [PMID: 32764827 PMCID: PMC7437926 DOI: 10.1371/journal.ppat.1008699] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 08/19/2020] [Accepted: 06/10/2020] [Indexed: 12/17/2022] Open
Abstract
São Paulo, a densely inhabited state in southeast Brazil that contains the fourth most populated city in the world, recently experienced its largest yellow fever virus (YFV) outbreak in decades. YFV does not normally circulate extensively in São Paulo, so most people were unvaccinated when the outbreak began. Surveillance in non-human primates (NHPs) is important for determining the magnitude and geographic extent of an epizootic, thereby helping to evaluate the risk of YFV spillover to humans. Data from infected NHPs can give more accurate insights into YFV spread than when using data from human cases alone. To contextualise human cases, identify epizootic foci and uncover the rate and direction of YFV spread in São Paulo, we generated and analysed virus genomic data and epizootic case data from NHPs in São Paulo. We report the occurrence of three spatiotemporally distinct phases of the outbreak in São Paulo prior to February 2018. We generated 51 new virus genomes from YFV positive cases identified in 23 different municipalities in São Paulo, mostly sampled from NHPs between October 2016 and January 2018. Although we observe substantial heterogeneity in lineage dispersal velocities between phylogenetic branches, continuous phylogeographic analyses of generated YFV genomes suggest that YFV lineages spread in São Paulo at a mean rate of approximately 1km per day during all phases of the outbreak. Viral lineages from the first epizootic phase in northern São Paulo subsequently dispersed towards the south of the state to cause the second and third epizootic phases there. This alters our understanding of how YFV was introduced into the densely populated south of São Paulo state. Our results shed light on the sylvatic transmission of YFV in highly fragmented forested regions in São Paulo state and highlight the importance of continued surveillance of zoonotic pathogens in sentinel species.
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Affiliation(s)
- Sarah C. Hill
- Department of Zoology, University of Oxford, Oxford, United Kingdom
- Department of Pathobiology and Population Sciences, Royal Veterinary College, Hawkshead, United Kingdom
| | | | - Julien Thézé
- Department of Zoology, University of Oxford, Oxford, United Kingdom
- Université Clermont Auvergne, INRAE, VetAgro Sup, UMR EPIA, Saint-Genès-Champanelle, France
| | - Ingra Claro
- Instituto de Medicina Tropical, Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina e, Universidade de São Paulo, São Paulo, Brazil
| | - Renato S. Aguiar
- Laboratório de Virologia Molecular, Departamento de Genética, Instituto de Biologia, Rio de Janeiro, Brazil
| | - Leandro Abade
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | | | | | | | - Flavia C. S. Salles
- Instituto de Medicina Tropical, Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina e, Universidade de São Paulo, São Paulo, Brazil
| | | | | | | | - Louis du Plessis
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Paola P. Silveira
- Laboratório de Virologia Molecular, Departamento de Genética, Instituto de Biologia, Rio de Janeiro, Brazil
| | - Jaqueline G. de Jesus
- Instituto de Medicina Tropical, Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina e, Universidade de São Paulo, São Paulo, Brazil
| | - Joshua Quick
- Institute of Microbiology and Infection, University of Birmingham, Birmingham, United Kingdom
| | | | | | | | - Marta Giovanetti
- Laboratório de Flavivírus, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | - Luiz C. J. Alcantara
- Laboratório de Flavivírus, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | | | | | | | | | - Regiane de Paula
- Centro de Vigilância Epidemiológica "Prof. Alexandre Vranjac", São Paulo, Brazil
| | - Roberta Spinola
- Centro de Vigilância Epidemiológica "Prof. Alexandre Vranjac", São Paulo, Brazil
| | | | - Luís F. Mucci
- Superintendência do Controle de Endemias, São Paulo, Brazil
| | | | | | | | - Andre L. de Abreu
- Secretaria de Vigilância em Saúde, Ministério da Saúde (SVS/MS), Brasília-DF, Brazil
| | | | - Nick Loman
- Institute of Microbiology and Infection, University of Birmingham, Birmingham, United Kingdom
| | - Simon Dellicour
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, CP160/12 50, Bruxelles, Belgium
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Oliver G. Pybus
- Department of Zoology, University of Oxford, Oxford, United Kingdom
- Department of Pathobiology and Population Sciences, Royal Veterinary College, Hawkshead, United Kingdom
| | - Ester C. Sabino
- Instituto de Medicina Tropical, Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina e, Universidade de São Paulo, São Paulo, Brazil
| | - Nuno R. Faria
- Department of Zoology, University of Oxford, Oxford, United Kingdom
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32
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Dellicour S, Desmecht D, Paternostre J, Malengreaux C, Licoppe A, Gilbert M, Linden A. Unravelling the dispersal dynamics and ecological drivers of the African swine fever outbreak in Belgium. J Appl Ecol 2020. [DOI: 10.1111/1365-2664.13649] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Affiliation(s)
- Simon Dellicour
- Spatial Epidemiology Lab (SpELL) Université Libre de Bruxelles Bruxelles Belgium
- Department of Microbiology, Immunology and Transplantation Rega Institute, KU Leuven Leuven Belgium
| | - Daniel Desmecht
- FARAH Research Center Faculty of Veterinary Medicine University of Liège Liège Belgium
| | - Julien Paternostre
- FARAH Research Center Faculty of Veterinary Medicine University of Liège Liège Belgium
| | - Céline Malengreaux
- Department of Environmental and Agricultural Studies Public Service of Wallonia Gembloux Belgium
| | - Alain Licoppe
- Department of Environmental and Agricultural Studies Public Service of Wallonia Gembloux Belgium
| | - Marius Gilbert
- Spatial Epidemiology Lab (SpELL) Université Libre de Bruxelles Bruxelles Belgium
| | - Annick Linden
- FARAH Research Center Faculty of Veterinary Medicine University of Liège Liège Belgium
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33
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Brunker K, Jaswant G, Thumbi S, Lushasi K, Lugelo A, Czupryna AM, Ade F, Wambura G, Chuchu V, Steenson R, Ngeleja C, Bautista C, Manalo DL, Gomez MRR, Chu MYJV, Miranda ME, Kamat M, Rysava K, Espineda J, Silo EAV, Aringo AM, Bernales RP, Adonay FF, Tildesley MJ, Marston DA, Jennings DL, Fooks AR, Zhu W, Meredith LW, Hill SC, Poplawski R, Gifford RJ, Singer JB, Maturi M, Mwatondo A, Biek R, Hampson K. Rapid in-country sequencing of whole virus genomes to inform rabies elimination programmes. Wellcome Open Res 2020; 5:3. [PMID: 32090172 PMCID: PMC7001756 DOI: 10.12688/wellcomeopenres.15518.2] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/12/2020] [Indexed: 12/19/2022] Open
Abstract
Genomic surveillance is an important aspect of contemporary disease management but has yet to be used routinely to monitor endemic disease transmission and control in low- and middle-income countries. Rabies is an almost invariably fatal viral disease that causes a large public health and economic burden in Asia and Africa, despite being entirely vaccine preventable. With policy efforts now directed towards achieving a global goal of zero dog-mediated human rabies deaths by 2030, establishing effective surveillance tools is critical. Genomic data can provide important and unique insights into rabies spread and persistence that can direct control efforts. However, capacity for genomic research in low- and middle-income countries is held back by limited laboratory infrastructure, cost, supply chains and other logistical challenges. Here we present and validate an end-to-end workflow to facilitate affordable whole genome sequencing for rabies surveillance utilising nanopore technology. We used this workflow in Kenya, Tanzania and the Philippines to generate rabies virus genomes in two to three days, reducing costs to approximately £60 per genome. This is over half the cost of metagenomic sequencing previously conducted for Tanzanian samples, which involved exporting samples to the UK and a three- to six-month lag time. Ongoing optimization of workflows are likely to reduce these costs further. We also present tools to support routine whole genome sequencing and interpretation for genomic surveillance. Moreover, combined with training workshops to empower scientists in-country, we show that local sequencing capacity can be readily established and sustainable, negating the common misperception that cutting-edge genomic research can only be conducted in high resource laboratories. More generally, we argue that the capacity to harness genomic data is a game-changer for endemic disease surveillance and should precipitate a new wave of researchers from low- and middle-income countries.
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Affiliation(s)
- Kirstyn Brunker
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
- The Boyd Orr Centre for Population and Ecosystem Health, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Gurdeep Jaswant
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
- University of Nairobi Institute of Tropical and Infectious Diseases (UNITID), Nairobi, Kenya
| | - S.M. Thumbi
- University of Nairobi Institute of Tropical and Infectious Diseases (UNITID), Nairobi, Kenya
- Center for Global Health Research, Kenya Medical Research Institute, Nairobi, Kenya
- Paul G. Allen School for Global Animal Health, Washington State University, Pullman, WA, USA
| | | | - Ahmed Lugelo
- Department of Veterinary Medicine and Public Health, Sokoine University of Agriculture, Morogoro, Tanzania
| | - Anna M. Czupryna
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Fred Ade
- Center for Global Health Research, Kenya Medical Research Institute, Nairobi, Kenya
| | - Gati Wambura
- Center for Global Health Research, Kenya Medical Research Institute, Nairobi, Kenya
| | - Veronicah Chuchu
- Center for Global Health Research, Kenya Medical Research Institute, Nairobi, Kenya
| | - Rachel Steenson
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Chanasa Ngeleja
- Tanzania Veterinary Laboratory Agency, Ministry of Livestock and Fisheries Development, Dar es Salaam, Tanzania
| | - Criselda Bautista
- Research Institute for Tropical Medicine (RITM), Manilla, Philippines
| | - Daria L. Manalo
- Research Institute for Tropical Medicine (RITM), Manilla, Philippines
| | | | | | - Mary Elizabeth Miranda
- Research Institute for Tropical Medicine (RITM), Manilla, Philippines
- Field Epidemiology Training Program Alumni Foundation (FETPAFI), Manilla, Philippines
| | - Maya Kamat
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Kristyna Rysava
- The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematical Institute, University of Warwick, Coventry, UK
| | - Jason Espineda
- Department of Agriculture Regional Field Office 5, Regional Animal Disease, Diagnostic Laboratory, Cabangan, Camalig, Albay, Philippines
| | - Eva Angelica V. Silo
- Department of Agriculture Regional Field Office 5, Regional Animal Disease, Diagnostic Laboratory, Cabangan, Camalig, Albay, Philippines
| | - Ariane Mae Aringo
- Department of Agriculture Regional Field Office 5, Regional Animal Disease, Diagnostic Laboratory, Cabangan, Camalig, Albay, Philippines
| | - Rona P. Bernales
- Department of Agriculture Regional Field Office 5, Regional Animal Disease, Diagnostic Laboratory, Cabangan, Camalig, Albay, Philippines
| | - Florencio F. Adonay
- Albay Veterinary Office, Provincial Government of Albay, Albay Farmers' Bounty Village, Cabangan, Camalig, Albay, Philippines
| | - Michael J. Tildesley
- The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematical Institute, University of Warwick, Coventry, UK
| | - Denise A. Marston
- Wildlife Zoonoses & Vector-Borne Diseases Research Group, Animal and Plant Health Agency (APHA), Weybridge, UK
| | - Daisy L. Jennings
- Wildlife Zoonoses & Vector-Borne Diseases Research Group, Animal and Plant Health Agency (APHA), Weybridge, UK
| | - Anthony R. Fooks
- Wildlife Zoonoses & Vector-Borne Diseases Research Group, Animal and Plant Health Agency (APHA), Weybridge, UK
- Institute of Infection and Global Health,, University of Liverpool, Liverpool, UK
| | - Wenlong Zhu
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
| | | | | | - Radoslaw Poplawski
- Institute of Microbiology and Infection, School of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK
- Advanced Research Computing, University of Birmingham, Birmingham, B15 2TT, UK
| | - Robert J. Gifford
- MRC-University of Glasgow Centre for Virus Research (CVR), University of Glasgow, Glasgow, UK
| | - Joshua B. Singer
- MRC-University of Glasgow Centre for Virus Research (CVR), University of Glasgow, Glasgow, UK
| | - Mathew Maturi
- Zoonotic Disease Unit, Ministry of Health, Ministry of Agriculture, Livestock and Fisheries, Nairobi, Kenya
| | - Athman Mwatondo
- Zoonotic Disease Unit, Ministry of Health, Ministry of Agriculture, Livestock and Fisheries, Nairobi, Kenya
| | - Roman Biek
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
- The Boyd Orr Centre for Population and Ecosystem Health, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Katie Hampson
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
- The Boyd Orr Centre for Population and Ecosystem Health, University of Glasgow, Glasgow, G12 8QQ, UK
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Jara M, Frias-De-Diego A, Machado G. Phylogeography of Equine Infectious Anemia Virus. Front Ecol Evol 2020. [DOI: 10.3389/fevo.2020.00127] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
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Colombi D, Poletto C, Nakouné E, Bourhy H, Colizza V. Long-range movements coupled with heterogeneous incubation period sustain dog rabies at the national scale in Africa. PLoS Negl Trop Dis 2020; 14:e0008317. [PMID: 32453756 PMCID: PMC7274467 DOI: 10.1371/journal.pntd.0008317] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 06/05/2020] [Accepted: 04/22/2020] [Indexed: 12/25/2022] Open
Abstract
Dog-transmitted rabies is responsible for more than 98% of human cases worldwide, remaining a persistent problem in developing countries. Mass vaccination targets predominantly major cities, often compromising disease control due to re-introductions. Previous work suggested that areas neighboring cities may behave as the source of these re-introductions. To evaluate this hypothesis, we introduce a spatially explicit metapopulation model for rabies diffusion in Central African Republic. Calibrated on epidemiological data for the capital city, Bangui, the model predicts that long-range movements are essential for continuous re-introductions of rabies-exposed dogs across settlements, eased by the large fluctuations of the incubation period. Bangui's neighborhood, instead, would not be enough to self-sustain the epidemic, contrary to previous expectations. Our findings suggest that restricting long-range travels may be very efficient in limiting rabies persistence in a large and fragmented dog population. Our framework can be applied to other geographical contexts where dog rabies is endemic.
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Affiliation(s)
- Davide Colombi
- INSERM, Sorbonne Université, Institut Pierre Louis d’Epidémiologie et de Santé Publique IPLESP, Paris, France
- Computational Epidemiology Laboratory, Institute for Scientific Interchange (ISI), Turin, Italy
- Physics Department and INFN, University of Turin, Turin, Italy
| | - Chiara Poletto
- INSERM, Sorbonne Université, Institut Pierre Louis d’Epidémiologie et de Santé Publique IPLESP, Paris, France
| | | | - Hervé Bourhy
- Institut Pasteur, Unit Lyssavirus Epidemiology and Neuropathology, WHO Collaborating Center for Reference and Research on Rabies, Paris, France
| | - Vittoria Colizza
- INSERM, Sorbonne Université, Institut Pierre Louis d’Epidémiologie et de Santé Publique IPLESP, Paris, France
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Brunker K, Jaswant G, Thumbi S, Lushasi K, Lugelo A, Czupryna AM, Ade F, Wambura G, Chuchu V, Steenson R, Ngeleja C, Bautista C, Manalo DL, Gomez MRR, Chu MYJV, Miranda ME, Kamat M, Rysava K, Espineda J, Silo EAV, Aringo AM, Bernales RP, Adonay FF, Tildesley MJ, Marston DA, Jennings DL, Fooks AR, Zhu W, Meredith LW, Hill SC, Poplawski R, Gifford RJ, Singer JB, Maturi M, Mwatondo A, Biek R, Hampson K. Rapid in-country sequencing of whole virus genomes to inform rabies elimination programmes. Wellcome Open Res 2020; 5:3. [PMID: 32090172 PMCID: PMC7001756 DOI: 10.12688/wellcomeopenres.15518.1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/30/2019] [Indexed: 08/27/2023] Open
Abstract
Genomic surveillance is an important aspect of contemporary disease management but has yet to be used routinely to monitor endemic disease transmission and control in low- and middle-income countries. Rabies is an almost invariably fatal viral disease that causes a large public health and economic burden in Asia and Africa, despite being entirely vaccine preventable. With policy efforts now directed towards achieving a global goal of zero dog-mediated human rabies deaths by 2030, establishing effective surveillance tools is critical. Genomic data can provide important and unique insights into rabies spread and persistence that can direct control efforts. However, capacity for genomic research in low- and middle-income countries is held back by limited laboratory infrastructure, cost, supply chains and other logistical challenges. Here we present and validate an end-to-end workflow to facilitate affordable whole genome sequencing for rabies surveillance utilising nanopore technology. We used this workflow in Kenya, Tanzania and the Philippines to generate rabies virus genomes in two to three days, reducing costs to approximately £60 per genome. This is over half the cost of metagenomic sequencing previously conducted for Tanzanian samples, which involved exporting samples to the UK and a three- to six-month lag time. Ongoing optimization of workflows are likely to reduce these costs further. We also present tools to support routine whole genome sequencing and interpretation for genomic surveillance. Moreover, combined with training workshops to empower scientists in-country, we show that local sequencing capacity can be readily established and sustainable, negating the common misperception that cutting-edge genomic research can only be conducted in high resource laboratories. More generally, we argue that the capacity to harness genomic data is a game-changer for endemic disease surveillance and should precipitate a new wave of researchers from low- and middle-income countries.
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Affiliation(s)
- Kirstyn Brunker
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
- The Boyd Orr Centre for Population and Ecosystem Health, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Gurdeep Jaswant
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
- University of Nairobi Institute of Tropical and Infectious Diseases (UNITID), Nairobi, Kenya
| | - S.M. Thumbi
- University of Nairobi Institute of Tropical and Infectious Diseases (UNITID), Nairobi, Kenya
- Center for Global Health Research, Kenya Medical Research Institute, Nairobi, Kenya
- Paul G. Allen School for Global Animal Health, Washington State University, Pullman, WA, USA
| | | | - Ahmed Lugelo
- Department of Veterinary Medicine and Public Health, Sokoine University of Agriculture, Morogoro, Tanzania
| | - Anna M. Czupryna
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Fred Ade
- Center for Global Health Research, Kenya Medical Research Institute, Nairobi, Kenya
| | - Gati Wambura
- Center for Global Health Research, Kenya Medical Research Institute, Nairobi, Kenya
| | - Veronicah Chuchu
- Center for Global Health Research, Kenya Medical Research Institute, Nairobi, Kenya
| | - Rachel Steenson
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Chanasa Ngeleja
- Tanzania Veterinary Laboratory Agency, Ministry of Livestock and Fisheries Development, Dar es Salaam, Tanzania
| | - Criselda Bautista
- Research Institute for Tropical Medicine (RITM), Manilla, Philippines
| | - Daria L. Manalo
- Research Institute for Tropical Medicine (RITM), Manilla, Philippines
| | | | | | - Mary Elizabeth Miranda
- Research Institute for Tropical Medicine (RITM), Manilla, Philippines
- Field Epidemiology Training Program Alumni Foundation (FETPAFI), Manilla, Philippines
| | - Maya Kamat
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Kristyna Rysava
- The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematical Institute, University of Warwick, Coventry, UK
| | - Jason Espineda
- Department of Agriculture Regional Field Office 5, Regional Animal Disease, Diagnostic Laboratory, Cabangan, Camalig, Albay, Philippines
| | - Eva Angelica V. Silo
- Department of Agriculture Regional Field Office 5, Regional Animal Disease, Diagnostic Laboratory, Cabangan, Camalig, Albay, Philippines
| | - Ariane Mae Aringo
- Department of Agriculture Regional Field Office 5, Regional Animal Disease, Diagnostic Laboratory, Cabangan, Camalig, Albay, Philippines
| | - Rona P. Bernales
- Department of Agriculture Regional Field Office 5, Regional Animal Disease, Diagnostic Laboratory, Cabangan, Camalig, Albay, Philippines
| | - Florencio F. Adonay
- Albay Veterinary Office, Provincial Government of Albay, Albay Farmers' Bounty Village, Cabangan, Camalig, Albay, Philippines
| | - Michael J. Tildesley
- The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematical Institute, University of Warwick, Coventry, UK
| | - Denise A. Marston
- Wildlife Zoonoses & Vector-Borne Diseases Research Group, Animal and Plant Health Agency (APHA), Weybridge, UK
| | - Daisy L. Jennings
- Wildlife Zoonoses & Vector-Borne Diseases Research Group, Animal and Plant Health Agency (APHA), Weybridge, UK
| | - Anthony R. Fooks
- Wildlife Zoonoses & Vector-Borne Diseases Research Group, Animal and Plant Health Agency (APHA), Weybridge, UK
- Institute of Infection and Global Health,, University of Liverpool, Liverpool, UK
| | - Wenlong Zhu
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
| | | | | | - Radoslaw Poplawski
- Institute of Microbiology and Infection, School of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK
- Advanced Research Computing, University of Birmingham, Birmingham, B15 2TT, UK
| | - Robert J. Gifford
- MRC-University of Glasgow Centre for Virus Research (CVR), University of Glasgow, Glasgow, UK
| | - Joshua B. Singer
- MRC-University of Glasgow Centre for Virus Research (CVR), University of Glasgow, Glasgow, UK
| | - Mathew Maturi
- Zoonotic Disease Unit, Ministry of Health, Ministry of Agriculture, Livestock and Fisheries, Nairobi, Kenya
| | - Athman Mwatondo
- Zoonotic Disease Unit, Ministry of Health, Ministry of Agriculture, Livestock and Fisheries, Nairobi, Kenya
| | - Roman Biek
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
- The Boyd Orr Centre for Population and Ecosystem Health, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Katie Hampson
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
- The Boyd Orr Centre for Population and Ecosystem Health, University of Glasgow, Glasgow, G12 8QQ, UK
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Abstract
Lassa virus is the causative agent of Lassa fever, a viral hemorrhagic fever with a case fatality rate of approximately 30% in Africa. Previous studies disclosed a geographical pattern in the distribution of Lassa virus strains and a westward movement of the virus across West Africa during evolution. Our study provides a deeper understanding of the geography of genetic lineages and sublineages of the virus in Nigeria. In addition, we modeled how the virus spread in the country. This knowledge allows us to predict into which geographical areas the virus might spread in the future and prioritize areas for Lassa fever surveillance. Our study not only aimed to generate Lassa virus sequences from across Nigeria but also to isolate and conserve the respective viruses for future research. Both isolates and sequences are important for the development and evaluation of medical countermeasures to treat and prevent Lassa fever, such as diagnostics, therapeutics, and vaccines. Lassa virus is genetically diverse with several lineages circulating in West Africa. This study aimed at describing the sequence variability of Lassa virus across Nigeria and inferring its spatiotemporal evolution. We sequenced and isolated 77 Lassa virus strains from 16 Nigerian states. The final data set, including previous works, comprised metadata and sequences of 219 unique strains sampled between 1969 and 2018 in 22 states. Most of this data originated from Lassa fever patients diagnosed at Irrua Specialist Teaching Hospital, Edo State, Nigeria. The majority of sequences clustered with the main Nigerian lineages II and III, while a few sequences formed a new cluster related to Lassa virus strains from Hylomyscus pamfi. Within lineages II and III, seven and five sublineages, respectively, were distinguishable. Phylogeographic analysis suggests an origin of lineage II in the southeastern part of the country around Ebonyi State and a main vector of dispersal toward the west across the Niger River, through Anambra, Kogi, Delta, and Edo into Ondo State. The frontline of virus dispersal appears to be in Ondo. Minor vectors are directed northeast toward Taraba and Adamawa and south toward Imo and Rivers. Lineage III might have spread from northern Plateau State into Kaduna, Nasarawa, Federal Capital Territory, and Bauchi. One sublineage moved south and crossed the Benue River into Benue State. This study provides a geographic mapping of lineages and phylogenetic clusters in Nigeria at a higher resolution. In addition, we estimated the direction and time frame of virus dispersal in the country. IMPORTANCE Lassa virus is the causative agent of Lassa fever, a viral hemorrhagic fever with a case fatality rate of approximately 30% in Africa. Previous studies disclosed a geographical pattern in the distribution of Lassa virus strains and a westward movement of the virus across West Africa during evolution. Our study provides a deeper understanding of the geography of genetic lineages and sublineages of the virus in Nigeria. In addition, we modeled how the virus spread in the country. This knowledge allows us to predict into which geographical areas the virus might spread in the future and prioritize areas for Lassa fever surveillance. Our study not only aimed to generate Lassa virus sequences from across Nigeria but also to isolate and conserve the respective viruses for future research. Both isolates and sequences are important for the development and evaluation of medical countermeasures to treat and prevent Lassa fever, such as diagnostics, therapeutics, and vaccines.
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Dellicour S, Troupin C, Jahanbakhsh F, Salama A, Massoudi S, Moghaddam MK, Baele G, Lemey P, Gholami A, Bourhy H. Using phylogeographic approaches to analyse the dispersal history, velocity and direction of viral lineages - Application to rabies virus spread in Iran. Mol Ecol 2019; 28:4335-4350. [PMID: 31535448 DOI: 10.1111/mec.15222] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Revised: 08/04/2019] [Accepted: 08/05/2019] [Indexed: 12/26/2022]
Abstract
Recent years have seen the extensive use of phylogeographic approaches to unveil the dispersal history of virus epidemics. Spatially explicit reconstructions of viral spread represent valuable sources of lineage movement data that can be exploited to investigate the impact of underlying environmental layers on the dispersal of pathogens. Here, we performed phylogeographic inference and applied different post hoc approaches to analyse a new and comprehensive data set of viral genomes to elucidate the dispersal history and dynamics of rabies virus (RABV) in Iran, which have remained largely unknown. We first analysed the association between environmental factors and variations in dispersal velocity among lineages. Second, we present, test and apply a new approach to study the link between environmental conditions and the dispersal direction of lineages. The statistical performance (power of detection, false-positive rate) of this new method was assessed using simulations. We performed phylogeographic analyses of RABV genomes, allowing us to describe the large diversity of RABV in Iran and to confirm the cocirculation of several clades in the country. Overall, we estimate a relatively high lineage dispersal velocity, similar to previous estimates for dog rabies virus spread in northern Africa. Finally, we highlight a tendency for RABV lineages to spread in accessible areas associated with high human population density. Our analytical workflow illustrates how phylogeographic approaches can be used to investigate the impact of environmental factors on several aspects of viral dispersal dynamics.
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Affiliation(s)
- Simon Dellicour
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium.,Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium
| | - Cécile Troupin
- Unit Lyssavirus Epidemiology and Neuropathology, WHO Collaborating Centre for Reference and Research on Rabies, Institut Pasteur, Paris, France
| | - Fatemeh Jahanbakhsh
- WHO Collaborating Centre for Reference and Research on Rabies, Pasteur Institute of Iran, Tehran, Iran
| | - Akram Salama
- Department of Medicine and Infectious Diseases, Faculty of Veterinary Medicine, University of Sadat City, Sadat City, Egypt
| | - Siamak Massoudi
- Department of Environment, Wildlife Diseases Group, Wildlife Bureau, Tehran, Iran
| | - Madjid K Moghaddam
- Department of Environment, Wildlife Diseases Group, Wildlife Bureau, Tehran, Iran
| | - Guy Baele
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium
| | - Alireza Gholami
- WHO Collaborating Centre for Reference and Research on Rabies, Pasteur Institute of Iran, Tehran, Iran
| | - Hervé Bourhy
- Unit Lyssavirus Epidemiology and Neuropathology, WHO Collaborating Centre for Reference and Research on Rabies, Institut Pasteur, Paris, France
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39
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Rakotomalala M, Vrancken B, Pinel-Galzi A, Ramavovololona P, Hébrard E, Randrianangaly JS, Dellicour S, Lemey P, Fargette D. Comparing patterns and scales of plant virus phylogeography: Rice yellow mottle virus in Madagascar and in continental Africa. Virus Evol 2019; 5:vez023. [PMID: 31384483 PMCID: PMC6671560 DOI: 10.1093/ve/vez023] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Rice yellow mottle virus (RYMV) in Madagascar Island provides an opportunity to study the spread of a plant virus disease after a relatively recent introduction in a large and isolated country with a heterogeneous host landscape ecology. Here, we take advantage of field survey data on the occurrence of RYMV disease throughout Madagascar dating back to the 1970s, and of virus genetic data from ninety-four isolates collected since 1989 in most regions of the country to reconstruct the epidemic history. We find that the Malagasy isolates belong to a unique recombinant strain that most likely entered Madagascar through a long-distance introduction from the most eastern part of mainland Africa. We infer the spread of RYMV as a continuous process using a Bayesian statistical framework. In order to calibrate the time scale in calendar time units in this analysis, we pool the information about the RYMV evolutionary rate from several geographical partitions. Whereas the field surveys and the phylogeographic reconstructions both point to a rapid southward invasion across hundreds of kilometers throughout Madagascar within three to four decades, they differ on the inferred origin location and time of the epidemic. The phylogeographic reconstructions suggest a lineage displacement and unveil a re-invasion of the northern regions that may have remained unnoticed otherwise. Despite ecological differences that could affect the transmission potential of RYMV in Madagascar and in mainland Africa, we estimate similar invasion and dispersal rates. We could not identify environmental factors that have a relevant impact on the lineage dispersal velocity of RYMV in Madagascar. This study highlights the value and complementarity of (historical) nongenetic and (more contemporaneous) genetic surveillance data for reconstructing the history of spread of plant viruses.
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Affiliation(s)
- Mbolarinosy Rakotomalala
- Centre Régional de Recherche du Nord-Ouest du FOFIFA, BP 289, Mahavoky Avaratra, Mahajanga 401, Madagascar
| | - Bram Vrancken
- Department of Microbiology and Immunology, Laboratory for Clinical and Epidemiological Virology, Rega Institute, KU Leuven, Herestraat 49 box 1040, 3000 Leuven, Belgium
| | - Agnès Pinel-Galzi
- IRD, Cirad, Université Montpellier, IPME, 911 avenue Agropolis, BP 64501 34934 Montpellier cedex 5, France
| | - Perle Ramavovololona
- Département de Biologie et d’Ecologie Végétales, Faculté des Sciences, Université d’Antananarivo, BP 906
| | - Eugénie Hébrard
- IRD, Cirad, Université Montpellier, IPME, 911 avenue Agropolis, BP 64501 34934 Montpellier cedex 5, France
| | | | - Simon Dellicour
- Department of Microbiology and Immunology, Laboratory for Clinical and Epidemiological Virology, Rega Institute, KU Leuven, Herestraat 49 box 1040, 3000 Leuven, Belgium
- Spatial Epidemiology Lab, Université Libre de Bruxelles, CP 264 / 3,50 av FD Roosevelt, B-1050 Brussels, Belgium
| | - Philippe Lemey
- Department of Microbiology and Immunology, Laboratory for Clinical and Epidemiological Virology, Rega Institute, KU Leuven, Herestraat 49 box 1040, 3000 Leuven, Belgium
| | - Denis Fargette
- IRD, Cirad, Université Montpellier, IPME, 911 avenue Agropolis, BP 64501 34934 Montpellier cedex 5, France
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Laenen L, Vergote V, Vanmechelen B, Tersago K, Baele G, Lemey P, Leirs H, Dellicour S, Vrancken B, Maes P. Identifying the patterns and drivers of Puumala hantavirus enzootic dynamics using reservoir sampling. Virus Evol 2019; 5:vez009. [PMID: 31024739 PMCID: PMC6476162 DOI: 10.1093/ve/vez009] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Hantaviruses are zoonotic hemorrhagic fever viruses for which prevention of human spillover remains the first priority in disease management. Tailored intervention measures require an understanding of the drivers of enzootic dynamics, commonly inferred from distorted human incidence data. Here, we use longitudinal sampling of approximately three decades of Puumala orthohantavirus (PUUV) evolution in isolated reservoir populations to estimate PUUV evolutionary rates, and apply these to study the impact of environmental factors on viral spread. We find that PUUV accumulates genetic changes at a rate of ∼10−4 substitutions per site per year and that land cover type defines the dispersal dynamics of PUUV, with forests facilitating and croplands impeding virus spread. By providing reliable short-term PUUV evolutionary rate estimates, this work facilitates the evaluation of spatial risk heterogeneity starting from timed phylogeographic reconstructions based on virus sampling in its animal reservoir, thereby side-stepping the need for difficult-to-collect human disease incidence data.
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Affiliation(s)
- Lies Laenen
- KU Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Division of Clinical and Epidemiological Virology, Herestraat 49, 3000 Leuven, Belgium
| | - Valentijn Vergote
- KU Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Division of Clinical and Epidemiological Virology, Herestraat 49, 3000 Leuven, Belgium
| | - Bert Vanmechelen
- KU Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Division of Clinical and Epidemiological Virology, Herestraat 49, 3000 Leuven, Belgium
| | - Katrien Tersago
- Evolutionary Ecology Group, Department of Biology, University of Antwerp, Antwerp, Belgium.,Epidemiology of Infectious Diseases, Belgian Institute of Health, Sciensano, Brussels, Belgium
| | - Guy Baele
- KU Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Division of Clinical and Epidemiological Virology, Herestraat 49, 3000 Leuven, Belgium
| | - Philippe Lemey
- KU Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Division of Clinical and Epidemiological Virology, Herestraat 49, 3000 Leuven, Belgium
| | - Herwig Leirs
- Evolutionary Ecology Group, Department of Biology, University of Antwerp, Antwerp, Belgium
| | - Simon Dellicour
- KU Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Division of Clinical and Epidemiological Virology, Herestraat 49, 3000 Leuven, Belgium.,Spatial Epidemiology Lab (spELL), Université Libre de Bruxelles, Bruxelles, Belgium
| | - Bram Vrancken
- KU Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Division of Clinical and Epidemiological Virology, Herestraat 49, 3000 Leuven, Belgium
| | - Piet Maes
- KU Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Division of Clinical and Epidemiological Virology, Herestraat 49, 3000 Leuven, Belgium
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Tian H, Feng Y, Vrancken B, Cazelles B, Tan H, Gill MS, Yang Q, Li Y, Yang W, Zhang Y, Zhang Y, Lemey P, Pybus OG, Stenseth NC, Zhang H, Dellicour S. Transmission dynamics of re-emerging rabies in domestic dogs of rural China. PLoS Pathog 2018; 14:e1007392. [PMID: 30521641 PMCID: PMC6283347 DOI: 10.1371/journal.ppat.1007392] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Accepted: 10/08/2018] [Indexed: 12/17/2022] Open
Abstract
Despite ongoing efforts to control transmission, rabies prevention remains a challenge in many developing countries, especially in rural areas of China where re-emerging rabies is under-reported due to a lack of sustained animal surveillance. By taking advantage of detailed genomic and epidemiological data for the re-emerging rabies outbreak in Yunnan Province, China, collected between 1999 and 2015, we reconstruct the demographic and dispersal history of domestic dog rabies virus (RABV) as well as the dynamics of dog-to-dog and dog-to-human transmission. Phylogeographic analyses reveal a lower diffusion coefficient than previously estimated for dog RABV dissemination in northern Africa. Furthermore, epidemiological analyses reveal transmission rates between dogs, as well as between dogs and humans, lower than estimates for Africa. Finally, we show that reconstructed epidemic history of RABV among dogs and the dynamics of rabid dogs are consistent with the recorded human rabies cases. This work illustrates the benefits of combining phylogeographic and epidemic modelling approaches for uncovering the spatiotemporal dynamics of zoonotic diseases, with both approaches providing estimates of key epidemiological parameters.
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Affiliation(s)
- Huaiyu Tian
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
- * E-mail: (HT); (HZ); (SD)
| | - Yun Feng
- Yunnan Institute of Endemic Diseases Control and Prevention, Yunnan Provincial Key Laboratory for Zoonosis Control and Prevention, Dali, China
| | - Bram Vrancken
- KU Leuven, Department of Microbiology and Immunology, Rega Institute, Laboratory of Evolutionary and Computational Virology, Leuven, Belgium
| | - Bernard Cazelles
- Institut de Biologie de l’École Normale Supérieure UMR 8197, Eco-Evolutionary Mathematics, École Normale Supérieure, France
- Unité Mixte Internationnale 209, Mathematical and Computational Modeling of Complex Systems, Institut de Recherche pour le Développement et Université Pierre et Marie Curie, Bondy, France
| | - Hua Tan
- School of Biomedical Informatics, the University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Mandev S. Gill
- KU Leuven, Department of Microbiology and Immunology, Rega Institute, Laboratory of Evolutionary and Computational Virology, Leuven, Belgium
| | - Qiqi Yang
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
| | - Yidan Li
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
| | - Weihong Yang
- Yunnan Institute of Endemic Diseases Control and Prevention, Yunnan Provincial Key Laboratory for Zoonosis Control and Prevention, Dali, China
| | - Yuzhen Zhang
- Yunnan Institute of Endemic Diseases Control and Prevention, Yunnan Provincial Key Laboratory for Zoonosis Control and Prevention, Dali, China
| | - Yunzhi Zhang
- Yunnan Institute of Endemic Diseases Control and Prevention, Yunnan Provincial Key Laboratory for Zoonosis Control and Prevention, Dali, China
| | - Philippe Lemey
- KU Leuven, Department of Microbiology and Immunology, Rega Institute, Laboratory of Evolutionary and Computational Virology, Leuven, Belgium
| | - Oliver G. Pybus
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Nils Chr. Stenseth
- Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, Blindern, Oslo, Norway
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, China
| | - Hailin Zhang
- Yunnan Institute of Endemic Diseases Control and Prevention, Yunnan Provincial Key Laboratory for Zoonosis Control and Prevention, Dali, China
- * E-mail: (HT); (HZ); (SD)
| | - Simon Dellicour
- KU Leuven, Department of Microbiology and Immunology, Rega Institute, Laboratory of Evolutionary and Computational Virology, Leuven, Belgium
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium
- * E-mail: (HT); (HZ); (SD)
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Kraemer MUG, Cummings DAT, Funk S, Reiner RC, Faria NR, Pybus OG, Cauchemez S. Reconstruction and prediction of viral disease epidemics. Epidemiol Infect 2018; 147:e34. [PMID: 30394230 PMCID: PMC6398585 DOI: 10.1017/s0950268818002881] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2018] [Revised: 08/24/2018] [Accepted: 09/21/2018] [Indexed: 01/29/2023] Open
Abstract
A growing number of infectious pathogens are spreading among geographic regions. Some pathogens that were previously not considered to pose a general threat to human health have emerged at regional and global scales, such as Zika and Ebola Virus Disease. Other pathogens, such as yellow fever virus, were previously thought to be under control but have recently re-emerged, causing new challenges to public health organisations. A wide array of new modelling techniques, aided by increased computing capabilities, novel diagnostic tools, and the increased speed and availability of genomic sequencing allow researchers to identify new pathogens more rapidly, assess the likelihood of geographic spread, and quantify the speed of human-to-human transmission. Despite some initial successes in predicting the spread of acute viral infections, the practicalities and sustainability of such approaches will need to be evaluated in the context of public health responses.
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Affiliation(s)
- M. U. G. Kraemer
- Harvard Medical School, Harvard University, Boston, MA, USA
- Computational Epidemiology Lab, Boston Children's Hospital, Boston, MA, USA
- Department of Zoology, University of Oxford, Oxford, UK
| | - D. A. T. Cummings
- Department of Biology, University of Florida, Gainesville, Florida, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
| | - S. Funk
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK
| | - R. C. Reiner
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, USA
| | - N. R. Faria
- Department of Zoology, University of Oxford, Oxford, UK
| | - O. G. Pybus
- Department of Zoology, University of Oxford, Oxford, UK
| | - S. Cauchemez
- Mathematical Modelling of Infectious Diseases and Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, Paris, France
- CNRS UMR2000: Génomique évolutive, modélisation et santé, Paris, France
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43
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Adam DC, Scotch M, MacIntyre CR. Bayesian Phylogeography and Pathogenic Characterization of Smallpox Based on HA, ATI, and CrmB Genes. Mol Biol Evol 2018; 35:2607-2617. [PMID: 30099520 PMCID: PMC6231489 DOI: 10.1093/molbev/msy153] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Variola virus is at risk of re-emergence either through accidental release, bioterrorism, or synthetic biology. The use of phylogenetics and phylogeography to support epidemic field response is expected to grow as sequencing technology becomes miniaturized, cheap, and ubiquitous. In this study, we aimed to explore the use of common VARV diagnostic targets hemagglutinin (HA), cytokine response modifier B (CrmB), and A-type inclusion protein (ATI) for phylogenetic characterization as well as the representativeness of modelling strategies in phylogeography to support epidemic response should smallpox re-emerge. We used Bayesian discrete-trait phylogeography using the most complete data set currently available of whole genome (n = 51) and partially sequenced (n = 20) VARV isolates. We show that multilocus models combining HA, ATI, and CrmB genes may represent a useful heuristic to differentiate between VARV Major and subclades of VARV Minor which have been associated with variable case-fatality rates. Where whole genome sequencing is unavailable, phylogeography models of HA, ATI, and CrmB may provide preliminary but uncertain estimates of transmission, while supplementing whole genome models with additional isolates sequenced only for HA can improve sample representativeness, maintaining similar support for transmission relative to whole genome models. We have also provided empirical evidence delineating historic international VARV transmission using phylogeography. Due to the persistent threat of re-emergence, our results provide important research for smallpox epidemic preparedness in the posteradication era as recommended by the World Health Organisation.
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Affiliation(s)
- Dillon C Adam
- Biosecurity Program, Kirby Institute, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Matthew Scotch
- School of Public Health and Community Medicine, University of New South Wales, Sydney, NSW
- Biodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, Tempe, AZ
- Department of Biomedical Informatics, College of Health Solutions, Arizona State University, Tempe, AZ
| | - Chandini Raina MacIntyre
- Biosecurity Program, Kirby Institute, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
- College of Public Service and Community Solutions and College of Health Solutions, Arizona State University, Tempe, AZ
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44
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Baele G, Dellicour S, Suchard MA, Lemey P, Vrancken B. Recent advances in computational phylodynamics. Curr Opin Virol 2018; 31:24-32. [PMID: 30248578 DOI: 10.1016/j.coviro.2018.08.009] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2018] [Revised: 08/16/2018] [Accepted: 08/20/2018] [Indexed: 01/02/2023]
Abstract
Time-stamped, trait-annotated phylogenetic trees built from virus genome data are increasingly used for outbreak investigation and monitoring ongoing epidemics. This routinely involves reconstructing the spatial and demographic processes from large data sets to help unveil the patterns and drivers of virus spread. Such phylodynamic inferences can however become quite time-consuming as the dimensions of the data increase, which has led to a myriad of approaches that aim to tackle this complexity. To elucidate the current state of the art in the field of phylodynamics, we discuss recent developments in Bayesian inference and accompanying software, highlight methods for improving computational efficiency and relevant visualisation tools. As an alternative to fully Bayesian approaches, we touch upon conditional software pipelines that compromise between statistical coherence and turn-around-time, and we highlight the available software packages. Finally, we outline future directions that may facilitate the large-scale tracking of epidemics in near real time.
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Affiliation(s)
- Guy Baele
- KU Leuven Department of Microbiology and Immunology, Rega Institute, Laboratory of Evolutionary and Computational Virology, Leuven, Belgium.
| | - Simon Dellicour
- KU Leuven Department of Microbiology and Immunology, Rega Institute, Laboratory of Evolutionary and Computational Virology, Leuven, Belgium; Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium
| | - Marc A Suchard
- Department of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA; Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Philippe Lemey
- KU Leuven Department of Microbiology and Immunology, Rega Institute, Laboratory of Evolutionary and Computational Virology, Leuven, Belgium
| | - Bram Vrancken
- KU Leuven Department of Microbiology and Immunology, Rega Institute, Laboratory of Evolutionary and Computational Virology, Leuven, Belgium
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45
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Faria NR, Kraemer MUG, Hill SC, Goes de Jesus J, Aguiar RS, Iani FCM, Xavier J, Quick J, du Plessis L, Dellicour S, Thézé J, Carvalho RDO, Baele G, Wu CH, Silveira PP, Arruda MB, Pereira MA, Pereira GC, Lourenço J, Obolski U, Abade L, Vasylyeva TI, Giovanetti M, Yi D, Weiss DJ, Wint GRW, Shearer FM, Funk S, Nikolay B, Fonseca V, Adelino TER, Oliveira MAA, Silva MVF, Sacchetto L, Figueiredo PO, Rezende IM, Mello EM, Said RFC, Santos DA, Ferraz ML, Brito MG, Santana LF, Menezes MT, Brindeiro RM, Tanuri A, Dos Santos FCP, Cunha MS, Nogueira JS, Rocco IM, da Costa AC, Komninakis SCV, Azevedo V, Chieppe AO, Araujo ESM, Mendonça MCL, Dos Santos CC, Dos Santos CD, Mares-Guia AM, Nogueira RMR, Sequeira PC, Abreu RG, Garcia MHO, Abreu AL, Okumoto O, Kroon EG, de Albuquerque CFC, Lewandowski K, Pullan ST, Carroll M, de Oliveira T, Sabino EC, Souza RP, Suchard MA, Lemey P, Trindade GS, Drumond BP, Filippis AMB, Loman NJ, Cauchemez S, Alcantara LCJ, Pybus OG. Genomic and epidemiological monitoring of yellow fever virus transmission potential. Science 2018; 361:894-899. [PMID: 30139911 PMCID: PMC6874500 DOI: 10.1126/science.aat7115] [Citation(s) in RCA: 208] [Impact Index Per Article: 34.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2018] [Accepted: 07/20/2018] [Indexed: 12/21/2022]
Abstract
The yellow fever virus (YFV) epidemic in Brazil is the largest in decades. The recent discovery of YFV in Brazilian Aedes species mosquitos highlights a need to monitor the risk of reestablishment of urban YFV transmission in the Americas. We use a suite of epidemiological, spatial, and genomic approaches to characterize YFV transmission. We show that the age and sex distribution of human cases is characteristic of sylvatic transmission. Analysis of YFV cases combined with genomes generated locally reveals an early phase of sylvatic YFV transmission and spatial expansion toward previously YFV-free areas, followed by a rise in viral spillover to humans in late 2016. Our results establish a framework for monitoring YFV transmission in real time that will contribute to a global strategy to eliminate future YFV epidemics.
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Affiliation(s)
- N R Faria
- Department of Zoology, University of Oxford, Oxford, UK.
| | - M U G Kraemer
- Department of Zoology, University of Oxford, Oxford, UK
- Computational Epidemiology Lab, Boston Children's Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - S C Hill
- Department of Zoology, University of Oxford, Oxford, UK
| | - J Goes de Jesus
- Laboratório de Flavivírus, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | - R S Aguiar
- Laboratório de Virologia Molecular, Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - F C M Iani
- Laboratório Central de Saúde Pública, Instituto Octávio Magalhães, FUNED, Belo Horizonte, Minas Gerais, Brazil
- Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - J Xavier
- Laboratório de Flavivírus, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | - J Quick
- Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK
| | - L du Plessis
- Department of Zoology, University of Oxford, Oxford, UK
| | - S Dellicour
- Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium
| | - J Thézé
- Department of Zoology, University of Oxford, Oxford, UK
| | - R D O Carvalho
- Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - G Baele
- Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium
| | - C-H Wu
- Department of Statistics, University of Oxford, Oxford, UK
| | - P P Silveira
- Laboratório de Virologia Molecular, Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - M B Arruda
- Laboratório de Virologia Molecular, Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - M A Pereira
- Laboratório Central de Saúde Pública, Instituto Octávio Magalhães, FUNED, Belo Horizonte, Minas Gerais, Brazil
| | - G C Pereira
- Laboratório Central de Saúde Pública, Instituto Octávio Magalhães, FUNED, Belo Horizonte, Minas Gerais, Brazil
| | - J Lourenço
- Department of Zoology, University of Oxford, Oxford, UK
| | - U Obolski
- Department of Zoology, University of Oxford, Oxford, UK
| | - L Abade
- Department of Zoology, University of Oxford, Oxford, UK
- The Global Health Network, University of Oxford, Oxford, UK
| | - T I Vasylyeva
- Department of Zoology, University of Oxford, Oxford, UK
| | - M Giovanetti
- Laboratório de Flavivírus, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
- Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - D Yi
- Department of Statistics, Harvard University, Cambridge, MA, USA
| | - D J Weiss
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - G R W Wint
- Department of Zoology, University of Oxford, Oxford, UK
| | - F M Shearer
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - S Funk
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
| | - B Nikolay
- Mathematical Modelling of Infectious Diseases and Center of Bioinformatics, Institut Pasteur, Paris, France
- CNRS UMR2000: Génomique Évolutive, Modélisation et Santé, Institut Pasteur, Paris, France
| | - V Fonseca
- Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
- KwaZulu-Natal Research, Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - T E R Adelino
- Laboratório Central de Saúde Pública, Instituto Octávio Magalhães, FUNED, Belo Horizonte, Minas Gerais, Brazil
| | - M A A Oliveira
- Laboratório Central de Saúde Pública, Instituto Octávio Magalhães, FUNED, Belo Horizonte, Minas Gerais, Brazil
| | - M V F Silva
- Laboratório Central de Saúde Pública, Instituto Octávio Magalhães, FUNED, Belo Horizonte, Minas Gerais, Brazil
| | - L Sacchetto
- Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - P O Figueiredo
- Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - I M Rezende
- Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - E M Mello
- Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - R F C Said
- Secretaria de Estado de Saúde de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - D A Santos
- Secretaria de Estado de Saúde de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - M L Ferraz
- Secretaria de Estado de Saúde de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - M G Brito
- Secretaria de Estado de Saúde de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - L F Santana
- Secretaria de Estado de Saúde de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - M T Menezes
- Laboratório de Virologia Molecular, Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - R M Brindeiro
- Laboratório de Virologia Molecular, Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - A Tanuri
- Laboratório de Virologia Molecular, Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - F C P Dos Santos
- Núcleo de Doenças de Transmissão Vetorial, Instituto Adolfo Lutz, São Paulo, Brazil
| | - M S Cunha
- Núcleo de Doenças de Transmissão Vetorial, Instituto Adolfo Lutz, São Paulo, Brazil
| | - J S Nogueira
- Núcleo de Doenças de Transmissão Vetorial, Instituto Adolfo Lutz, São Paulo, Brazil
| | - I M Rocco
- Núcleo de Doenças de Transmissão Vetorial, Instituto Adolfo Lutz, São Paulo, Brazil
| | - A C da Costa
- Instituto de Medicina Tropical e Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - S C V Komninakis
- Retrovirology Laboratory, Federal University of São Paulo, São Paulo, Brazil
- School of Medicine of ABC (FMABC), Clinical Immunology Laboratory, Santo André, São Paulo, Brazil
| | - V Azevedo
- Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - A O Chieppe
- Coordenação de Vigilância Epidemiológica do Estado do Rio de Janeiro, Rio de Janeiro, Brazil
| | - E S M Araujo
- Laboratório de Flavivírus, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | - M C L Mendonça
- Laboratório de Flavivírus, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | - C C Dos Santos
- Laboratório de Flavivírus, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | - C D Dos Santos
- Laboratório de Flavivírus, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | - A M Mares-Guia
- Laboratório de Flavivírus, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | - R M R Nogueira
- Laboratório de Flavivírus, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | - P C Sequeira
- Laboratório de Flavivírus, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | - R G Abreu
- Departamento de Vigilância das Doenças Transmissíveis da Secretaria de Vigilância em Saúde, Ministério da Saúde, Brasília-DF, Brazil
| | - M H O Garcia
- Departamento de Vigilância das Doenças Transmissíveis da Secretaria de Vigilância em Saúde, Ministério da Saúde, Brasília-DF, Brazil
| | - A L Abreu
- Secretaria de Vigilância em Saúde, Coordenação Geral de Laboratórios de Saúde Pública, Ministério da Saúde, Brasília-DF, Brazil
| | - O Okumoto
- Secretaria de Vigilância em Saúde, Coordenação Geral de Laboratórios de Saúde Pública, Ministério da Saúde, Brasília-DF, Brazil
| | - E G Kroon
- Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - C F C de Albuquerque
- Organização Pan - Americana da Saúde/Organização Mundial da Saúde - (OPAS/OMS), Brasília-DF, Brazil
| | - K Lewandowski
- Public Health England, National Infections Service, Porton Down, Salisbury, UK
| | - S T Pullan
- Public Health England, National Infections Service, Porton Down, Salisbury, UK
| | - M Carroll
- NIHR HPRU in Emerging and Zoonotic Infections, Public Health England, London, UK
| | - T de Oliveira
- Laboratório de Flavivírus, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
- KwaZulu-Natal Research, Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban, South Africa
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban, South Africa
| | - E C Sabino
- Instituto de Medicina Tropical e Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - R P Souza
- Núcleo de Doenças de Transmissão Vetorial, Instituto Adolfo Lutz, São Paulo, Brazil
| | - M A Suchard
- Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, CA, USA
- Department of Biomathematics and Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA, USA
| | - P Lemey
- Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium
| | - G S Trindade
- Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - B P Drumond
- Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - A M B Filippis
- Laboratório de Flavivírus, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | - N J Loman
- Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK
| | - S Cauchemez
- Mathematical Modelling of Infectious Diseases and Center of Bioinformatics, Institut Pasteur, Paris, France
- CNRS UMR2000: Génomique Évolutive, Modélisation et Santé, Institut Pasteur, Paris, France
| | - L C J Alcantara
- Laboratório de Flavivírus, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil.
- Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - O G Pybus
- Department of Zoology, University of Oxford, Oxford, UK.
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46
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Dellicour S, Vrancken B, Trovão NS, Fargette D, Lemey P. On the importance of negative controls in viral landscape phylogeography. Virus Evol 2018; 4:vey023. [PMID: 30151241 PMCID: PMC6101606 DOI: 10.1093/ve/vey023] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Phylogeographic reconstructions are becoming an established procedure to evaluate the factors that could impact virus spread. While a discrete phylogeographic approach can be used to test predictors of transition rates among discrete locations, alternative continuous phylogeographic reconstructions can also be exploited to investigate the impact of underlying environmental layers on the dispersal velocity of a virus. The two approaches are complementary tools for studying pathogens' spread, but in both cases, care must be taken to avoid misinterpretations. Here, we analyse rice yellow mottle virus (RYMV) sequence data from West and East Africa to illustrate how both approaches can be used to study the impact of environmental factors on the virus’ dispersal frequency and velocity. While it was previously reported that host connectivity was a major determinant of RYMV spread, we show that this was a false positive result due to the lack of appropriate negative controls. We also discuss and compare the phylodynamic tools currently available for investigating the impact of environmental factors on virus spread.
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Affiliation(s)
- Simon Dellicour
- Laboratory for Clinical and Epidemiological Virology, Rega Institute, KU Leuven, Leuven, Belgium.,Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, CP160/12 50, av. FD Roosevelt, 1050 Bruxelles, Belgium
| | - Bram Vrancken
- Laboratory for Clinical and Epidemiological Virology, Rega Institute, KU Leuven, Leuven, Belgium
| | - Nídia S Trovão
- Laboratory for Clinical and Epidemiological Virology, Rega Institute, KU Leuven, Leuven, Belgium
| | - Denis Fargette
- Institut de Recherche pour le Développement (IRD), UMR IPME (IRD, CIRAD, Université de Montpellier), BP 64051 34394 Montpellier cedex 5, France
| | - Philippe Lemey
- Laboratory for Clinical and Epidemiological Virology, Rega Institute, KU Leuven, Leuven, Belgium
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47
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Dolan PT, Whitfield ZJ, Andino R. Mechanisms and Concepts in RNA Virus Population Dynamics and Evolution. Annu Rev Virol 2018; 5:69-92. [PMID: 30048219 DOI: 10.1146/annurev-virology-101416-041718] [Citation(s) in RCA: 78] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
RNA viruses are unique in their evolutionary capacity, exhibiting high mutation rates and frequent recombination. They rapidly adapt to environmental changes, such as shifts in immune pressure or pharmacological challenge. The evolution of RNA viruses has been brought into new focus with the recent developments of genetic and experimental tools to explore and manipulate the evolutionary dynamics of viral populations. These studies have uncovered new mechanisms that enable viruses to overcome evolutionary challenges in the environment and have emphasized the intimate relationship of viral populations with evolution. Here, we review some of the emerging viral and host mechanisms that underlie the evolution of RNA viruses. We also discuss new studies that demonstrate that the relationship between evolutionary dynamics and virus biology spans many spatial and temporal scales, affecting transmission dynamics within and between hosts as well as pathogenesis.
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Affiliation(s)
- Patrick T Dolan
- Department of Biology, Stanford University, Stanford, California 94305, USA.,Department of Microbiology and Immunology, University of California, San Francisco, California 94143, USA;
| | - Zachary J Whitfield
- Department of Microbiology and Immunology, University of California, San Francisco, California 94143, USA;
| | - Raul Andino
- Department of Microbiology and Immunology, University of California, San Francisco, California 94143, USA;
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48
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Dellicour S, Baele G, Dudas G, Faria NR, Pybus OG, Suchard MA, Rambaut A, Lemey P. Phylodynamic assessment of intervention strategies for the West African Ebola virus outbreak. Nat Commun 2018; 9:2222. [PMID: 29884821 PMCID: PMC5993714 DOI: 10.1038/s41467-018-03763-2] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Accepted: 03/12/2018] [Indexed: 01/25/2023] Open
Abstract
Genetic analyses have provided important insights into Ebola virus spread during the recent West African outbreak, but their implications for specific intervention scenarios remain unclear. Here, we address this issue using a collection of phylodynamic approaches. We show that long-distance dispersal events were not crucial for epidemic expansion and that preventing viral lineage movement to any given administrative area would, in most cases, have had little impact. However, major urban areas were critical in attracting and disseminating the virus: preventing viral lineage movement to all three capitals simultaneously would have contained epidemic size to one-third. We also show that announcements of border closures were followed by a significant but transient effect on international virus dispersal. By quantifying the hypothetical impact of different intervention strategies, as well as the impact of barriers on dispersal frequency, our study illustrates how phylodynamic analyses can help to address specific epidemiological and outbreak control questions. During the last Ebola virus outbreak in West Africa, a large amount of viral genomic data was obtained. Here, Dellicour et al. use phylodynamic approaches to assess effect of intervention strategies such as border closures.
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Affiliation(s)
- Simon Dellicour
- Department of Microbiology and Immunology, Rega Institute, KU Leuven - University of Leuven, Herestraat 49, 3000, Leuven, Belgium.
| | - Guy Baele
- Department of Microbiology and Immunology, Rega Institute, KU Leuven - University of Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Gytis Dudas
- Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, 98109, Seattle, WA, USA
| | - Nuno R Faria
- Department of Zoology, University of Oxford, Oxford, OX1 3PS, United Kingdom
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, OX1 3PS, United Kingdom
| | - Marc A Suchard
- Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, CA, 90095, USA.,Department of Biomathematics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA, 90095, USA.,Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA, 90095, USA
| | - Andrew Rambaut
- Institute of Evolutionary Biology, University of Edinburgh, King's Buildings, Edinburgh, EH9 3FL, UK.,Fogarty International Center, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Philippe Lemey
- Department of Microbiology and Immunology, Rega Institute, KU Leuven - University of Leuven, Herestraat 49, 3000, Leuven, Belgium
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Brunker K, Lemey P, Marston DA, Fooks AR, Lugelo A, Ngeleja C, Hampson K, Biek R. Landscape attributes governing local transmission of an endemic zoonosis: Rabies virus in domestic dogs. Mol Ecol 2018; 27:773-788. [PMID: 29274171 PMCID: PMC5900915 DOI: 10.1111/mec.14470] [Citation(s) in RCA: 38] [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: 08/17/2017] [Revised: 11/15/2017] [Accepted: 11/20/2017] [Indexed: 12/24/2022]
Abstract
Landscape heterogeneity plays an important role in disease spread and persistence, but quantifying landscape influences and their scale dependence is challenging. Studies have focused on how environmental features or global transport networks influence pathogen invasion and spread, but their influence on local transmission dynamics that underpin the persistence of endemic diseases remains unexplored. Bayesian phylogeographic frameworks that incorporate spatial heterogeneities are promising tools for analysing linked epidemiological, environmental and genetic data. Here, we extend these methodological approaches to decipher the relative contribution and scale-dependent effects of landscape influences on the transmission of endemic rabies virus in Serengeti district, Tanzania (area ~4,900 km2 ). Utilizing detailed epidemiological data and 152 complete viral genomes collected between 2004 and 2013, we show that the localized presence of dogs but not their density is the most important determinant of diffusion, implying that culling will be ineffective for rabies control. Rivers and roads acted as barriers and facilitators to viral spread, respectively, and vaccination impeded diffusion despite variable annual coverage. Notably, we found that landscape effects were scale-dependent: rivers were barriers and roads facilitators on larger scales, whereas the distribution of dogs was important for rabies dispersal across multiple scales. This nuanced understanding of the spatial processes that underpin rabies transmission can be exploited for targeted control at the scale where it will have the greatest impact. Moreover, this research demonstrates how current phylogeographic frameworks can be adapted to improve our understanding of endemic disease dynamics at different spatial scales.
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Affiliation(s)
- Kirstyn Brunker
- Institute of Biodiversity, Animal Health and Comparative MedicineUniversity of GlasgowGlasgowUK
- The Boyd Orr Centre for Population and Ecosystem HealthUniversity of GlasgowGlasgowUK
- Animal and Plant Health AgencyAddlestoneUK
| | - Philippe Lemey
- Department of Microbiology and ImmunologyKU Leuven – University of LeuvenLeuvenBelgium
| | | | | | - Ahmed Lugelo
- Department of Veterinary Medicine and Public HealthSokoine University of AgricultureMorogoroUnited Republic of Tanzania
| | - Chanasa Ngeleja
- Tanzania Veterinary Laboratory AgencyDar es SalaamUnited Republic of Tanzania
| | - Katie Hampson
- Institute of Biodiversity, Animal Health and Comparative MedicineUniversity of GlasgowGlasgowUK
- The Boyd Orr Centre for Population and Ecosystem HealthUniversity of GlasgowGlasgowUK
| | - Roman Biek
- Institute of Biodiversity, Animal Health and Comparative MedicineUniversity of GlasgowGlasgowUK
- The Boyd Orr Centre for Population and Ecosystem HealthUniversity of GlasgowGlasgowUK
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