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      Heterogeneity of Rift Valley fever virus transmission potential across livestock hosts, quantified through a model-based analysis of host viral load and vector infection

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          Abstract

          Quantifying the variation of pathogens’ life history traits in multiple host systems is crucial to understand their transmission dynamics. It is particularly important for arthropod-borne viruses (arboviruses), which are prone to infecting several species of vertebrate hosts. Here, we focus on how host-pathogen interactions determine the ability of host species to transmit a virus to susceptible vectors upon a potentially infectious contact. Rift Valley fever (RVF) is a viral, vector-borne, zoonotic disease, chosen as a case study. The relative contributions of livestock species to RVFV transmission has not been previously quantified. To estimate their potential to transmit the virus over the course of their infection, we 1) fitted a within-host model to viral RNA and infectious virus measures, obtained daily from infected lambs, calves, and young goats, 2) estimated the relationship between vertebrate host infectious titers and probability to infect mosquitoes, and 3) estimated the net infectiousness of each host species over the duration of their infectious periods, taking into account different survival outcomes for lambs. Our results indicate that the efficiency of viral replication, along with the lifespan of infectious particles, could be sources of heterogeneity between hosts. Given available data on RVFV competent vectors, we found that, for similar infectious titers, infection rates in the Aedes genus were on average higher than in the Culex genus. Consequently, for Aedes-mediated infections, we estimated the net infectiousness of lambs to be 2.93 (median) and 3.65 times higher than that of calves and goats, respectively. In lambs, we estimated the overall infectiousness to be 1.93 times higher in individuals which eventually died from the infection than in those recovering. Beyond infectiousness, the relative contributions of host species to transmission depend on local ecological factors, including relative abundances and vector host-feeding preferences. Quantifying these contributions will ultimately help design efficient, targeted, surveillance and vaccination strategies.

          Author summary

          Viruses spread by mosquitoes present a major threat to animal and public health worldwide. When these pathogenic viruses can infect multiple species, controlling their spread becomes difficult. Rift Valley fever virus (RVFV) is such a virus. It spreads predominantly among ruminant livestock but can also spill over and cause severe disease in humans. Understanding which of these ruminant species are most important for the transmission of RVFV can help for effective control. One piece of this puzzle is to assess how effective infected animals are at transmitting RVFV to mosquitoes. To answer this question, we combine mathematical models with observations from experimental infections in cattle, sheep, and goats, and model changes in viremia over time within individuals. We then quantify the relationship between hosts’ viremia and the probability to infect mosquitoes. In combining these two analyses, we estimate the overall transmission potential of sheep, when in contact with mosquitoes, to be 3 to 5 times higher than that of goats and cattle. Further, sheep that experience a lethal infection have an even larger overall transmission potential. Once applied at the level of populations, with setting-specific herd composition and exposure to mosquitoes, these results will help unravel species’ role in RVF outbreaks.

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          Weak convergence and optimal scaling of random walk Metropolis algorithms

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            Risk factors for human disease emergence.

            A comprehensive literature review identifies 1415 species of infectious organism known to be pathogenic to humans, including 217 viruses and prions, 538 bacteria and rickettsia, 307 fungi, 66 protozoa and 287 helminths. Out of these, 868 (61%) are zoonotic, that is, they can be transmitted between humans and animals, and 175 pathogenic species are associated with diseases considered to be 'emerging'. We test the hypothesis that zoonotic pathogens are more likely to be associated with emerging diseases than non-emerging ones. Out of the emerging pathogens, 132 (75%) are zoonotic, and overall, zoonotic pathogens are twice as likely to be associated with emerging diseases than non-zoonotic pathogens. However, the result varies among taxa, with protozoa and viruses particularly likely to emerge, and helminths particularly unlikely to do so, irrespective of their zoonotic status. No association between transmission route and emergence was found. This study represents the first quantitative analysis identifying risk factors for human disease emergence.
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              How generation intervals shape the relationship between growth rates and reproductive numbers

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: ResourcesRole: ValidationRole: Writing – review & editing
                Role: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput Biol
                plos
                PLoS Computational Biology
                Public Library of Science (San Francisco, CA USA )
                1553-734X
                1553-7358
                July 2022
                22 July 2022
                : 18
                : 7
                : e1010314
                Affiliations
                [1 ] INRAE, Oniris, BIOEPAR, Nantes, France
                [2 ] Quantitative Veterinary Epidemiology, Wageningen University and Research, Wageningen, The Netherlands
                [3 ] Wageningen Bioveterinary Research, Lelystad, The Netherlands
                [4 ] Sorbonne Université, INSERM, Institut Pierre Louis d’Epidémiologie et de Santé Publique (IPLESP), Paris, France
                University of Warwick, UNITED KINGDOM
                Author notes

                The authors have declared that no competing interests exist.

                ¤ Current Address: Department of Biology, New Mexico State University, Las Cruces, NM 88003, United States of America

                Author information
                https://orcid.org/0000-0001-5687-3570
                https://orcid.org/0000-0002-1981-427X
                https://orcid.org/0000-0001-9790-2438
                https://orcid.org/0000-0002-5758-636X
                https://orcid.org/0000-0002-2646-196X
                https://orcid.org/0000-0002-0034-8950
                https://orcid.org/0000-0002-5227-1406
                Article
                PCOMPBIOL-D-21-02043
                10.1371/journal.pcbi.1010314
                9348665
                35867712
                358c4ef2-b852-4577-857a-70168cb56072
                © 2022 Cecilia et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 15 November 2021
                : 16 June 2022
                Page count
                Figures: 5, Tables: 2, Pages: 19
                Funding
                Funded by: INRAE metaprogram GISA
                Award ID: FORESEE project
                Funded by: INRAE
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100013414, Conseil Régional des Pays de la Loire;
                Award Recipient :
                Funded by: CIRAD
                Award Recipient :
                Funded by: Dutch research council
                Award ID: One Health PACT 109986
                This work was supported by INRAE metaprogram GISA (Integrated Management of Animal Health, project FORESEE), INRAE (HC), Conseil Régional des Pays de la Loire (HC), CIRAD (HC), and the Dutch research council (NWO, One Health PACT project 109986, MdW). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Disease Vectors
                Insect Vectors
                Mosquitoes
                Biology and Life Sciences
                Species Interactions
                Disease Vectors
                Insect Vectors
                Mosquitoes
                Biology and Life Sciences
                Zoology
                Entomology
                Insects
                Mosquitoes
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Invertebrates
                Arthropoda
                Insects
                Mosquitoes
                Biology and Life Sciences
                Zoology
                Animals
                Invertebrates
                Arthropoda
                Insects
                Mosquitoes
                Biology and life sciences
                Organisms
                Viruses
                RNA viruses
                Bunyaviruses
                Rift Valley fever virus
                Biology and life sciences
                Microbiology
                Medical microbiology
                Microbial pathogens
                Viral pathogens
                Bunyaviruses
                Rift Valley fever virus
                Medicine and health sciences
                Pathology and laboratory medicine
                Pathogens
                Microbial pathogens
                Viral pathogens
                Bunyaviruses
                Rift Valley fever virus
                Biology and life sciences
                Organisms
                Viruses
                Viral pathogens
                Bunyaviruses
                Rift Valley fever virus
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Vector-Borne Diseases
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Viral Diseases
                Arboviral Infections
                Biology and Life Sciences
                Agriculture
                Animal Management
                Livestock
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Vertebrates
                Amniotes
                Mammals
                Ruminants
                Goats
                Biology and Life Sciences
                Zoology
                Animals
                Vertebrates
                Amniotes
                Mammals
                Ruminants
                Goats
                Biology and Life Sciences
                Microbiology
                Virology
                Viral Structure
                Virions
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogenesis
                Host-Pathogen Interactions
                Custom metadata
                vor-update-to-uncorrected-proof
                2022-08-03
                Input data and scripts can be accessed at https://git.wur.nl/bosch123/riftvalley_withinhost.

                Quantitative & Systems biology
                Quantitative & Systems biology

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