1
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Gajewski Z, McElmurray P, Wojdak J, McGregor C, Zeller L, Cooper H, Belden LK, Hopkins S. Nonrandom foraging and resource distributions affect the relationships between host density, contact rates and parasite transmission. Ecol Lett 2024; 27:e14385. [PMID: 38480959 DOI: 10.1111/ele.14385] [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: 08/28/2023] [Revised: 01/31/2024] [Accepted: 02/01/2024] [Indexed: 03/17/2024]
Abstract
Nonrandom foraging can cause animals to aggregate in resource dense areas, increasing host density, contact rates and pathogen transmission, but when should nonrandom foraging and resource distributions also have density-independent effects? Here, we used a factorial experiment with constant resource and host densities to quantify host contact rates across seven resource distributions. We also used an agent-based model to compare pathogen transmission when host movement was based on random foraging, optimal foraging or something between those states. Nonrandom foraging strongly depressed contact rates and transmission relative to the classic random movement assumptions used in most epidemiological models. Given nonrandom foraging in the agent-based model and experiment, contact rates and transmission increased with resource aggregation and average distance to resource patches due to increased host movement in search of resources. Overall, we describe three density-independent mechanisms by which host behaviour and resource distributions alter contact rate functions and pathogen transmission.
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Affiliation(s)
- Zachary Gajewski
- Department of Applied Ecology, North Carolina State University, Raleigh, North Carolina, USA
| | - Philip McElmurray
- Department of Biological Sciences, Virginia Tech, Blacksburg, Virginia, USA
- Department of Anthropology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Jeremy Wojdak
- Department of Biology, Radford University, Radford, Virginia, USA
| | - Cari McGregor
- Department of Biology, Radford University, Radford, Virginia, USA
| | - Lily Zeller
- Department of Applied Ecology, North Carolina State University, Raleigh, North Carolina, USA
| | - Hannah Cooper
- Department of Applied Ecology, North Carolina State University, Raleigh, North Carolina, USA
| | - Lisa K Belden
- Department of Biological Sciences, Virginia Tech, Blacksburg, Virginia, USA
| | - Skylar Hopkins
- Department of Applied Ecology, North Carolina State University, Raleigh, North Carolina, USA
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2
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Titcomb G, Hulke J, Mantas JN, Gituku B, Young H. Cattle aggregations at shared resources create potential parasite exposure hotspots for wildlife. Proc Biol Sci 2023; 290:20232239. [PMID: 38052242 DOI: 10.1098/rspb.2023.2239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Accepted: 11/08/2023] [Indexed: 12/07/2023] Open
Abstract
Globally rising livestock populations and declining wildlife numbers are likely to dramatically change disease risk for wildlife and livestock, especially at resources where they congregate. However, limited understanding of interspecific transmission dynamics at these hotspots hinders disease prediction or mitigation. In this study, we combined gastrointestinal nematode density and host foraging activity measurements from our prior work in an East African tropical savannah system with three estimates of parasite sharing capacity to investigate how interspecific exposures alter the relative riskiness of an important resource - water - among cattle and five dominant herbivore species. We found that due to their high parasite output, water dependence and parasite sharing capacity, cattle greatly increased potential parasite exposures at water sources for wild ruminants. When untreated for parasites, cattle accounted for over two-thirds of total potential exposures around water for wild ruminants, driving 2-23-fold increases in relative exposure levels at water sources. Simulated changes in wildlife and cattle ratios showed that water sources become increasingly important hotspots of interspecific transmission for wild ruminants when relative abundance of cattle parasites increases. These results emphasize that livestock have significant potential to alter the level and distribution of parasite exposures across the landscape for wild ruminants.
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Affiliation(s)
- Georgia Titcomb
- Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins 80523-1019, CO, USA
- Department of Ecology, Evolution, and Marine Biology, University of California, Santa Barbara, CA, USA
| | - Jenna Hulke
- Department of Biology, Texas A&M University, College Station, TX 77843, USA
| | | | - Benard Gituku
- Ecological Monitoring Unit, Ol Pejeta Conservancy, Nanyuki, Kenya
| | - Hillary Young
- Department of Ecology, Evolution, and Marine Biology, University of California, Santa Barbara, CA, USA
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3
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Gilbertson MLJ, Hart SN, VanderWaal K, Onorato D, Cunningham M, VandeWoude S, Craft ME. Seasonal changes in network connectivity and consequences for pathogen transmission in a solitary carnivore. Sci Rep 2023; 13:17802. [PMID: 37853051 PMCID: PMC10584909 DOI: 10.1038/s41598-023-44815-y] [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: 04/22/2023] [Accepted: 10/12/2023] [Indexed: 10/20/2023] Open
Abstract
Seasonal variation in habitat use and animal behavior can alter host contact patterns with potential consequences for pathogen transmission dynamics. The endangered Florida panther (Puma concolor coryi) has experienced significant pathogen-induced mortality and continues to be at risk of future epidemics. Prior research has found increased panther movement in Florida's dry versus wet seasons, which may affect panther population connectivity and seasonally increase potential pathogen transmission. Our objective was to determine if Florida panthers are more spatially connected in dry seasons relative to wet seasons, and test if identified connectivity differences resulted in divergent predicted epidemic dynamics. We leveraged extensive panther telemetry data to construct seasonal panther home range overlap networks over an 11 year period. We tested for differences in network connectivity, and used observed network characteristics to simulate transmission of a broad range of pathogens through dry and wet season networks. We found that panthers were more spatially connected in dry seasons than wet seasons. Further, these differences resulted in a trend toward larger and longer pathogen outbreaks when epidemics were initiated in the dry season. Our results demonstrate that seasonal variation in behavioral patterns-even among largely solitary species-can have substantial impacts on epidemic dynamics.
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Affiliation(s)
- Marie L J Gilbertson
- Department of Veterinary Population Medicine, University of Minnesota, St Paul, MN, 55108, USA.
- Wisconsin Cooperative Wildlife Research Unit, Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, WI, 53706, USA.
| | - S Niamh Hart
- Department of Veterinary Population Medicine, University of Minnesota, St Paul, MN, 55108, USA
| | - Kimberly VanderWaal
- Department of Veterinary Population Medicine, University of Minnesota, St Paul, MN, 55108, USA
| | - Dave Onorato
- Fish and Wildlife Research Institute, Florida Fish and Wildlife Conservation Commission, Naples, FL, 34114, USA
| | - Mark Cunningham
- Fish and Wildlife Research Institute, Florida Fish and Wildlife Conservation Commission, Gainesville, FL, 32601, USA
| | - Sue VandeWoude
- Department of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO, 80523, USA
| | - Meggan E Craft
- Department of Veterinary Population Medicine, University of Minnesota, St Paul, MN, 55108, USA
- Department of Ecology, Evolution and Behavior, University of Minnesota, St Paul, MN, 55108, USA
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4
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de Castro P, Urbina F, Norambuena A, Guzmán-Lastra F. Sequential epidemic-like spread between agglomerates of self-propelled agents in one dimension. Phys Rev E 2023; 108:044104. [PMID: 37978653 DOI: 10.1103/physreve.108.044104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 09/13/2023] [Indexed: 11/19/2023]
Abstract
Motile organisms can form stable agglomerates such as cities or colonies. In the outbreak of a highly contagious disease, the control of large-scale epidemic spread depends on factors like the number and size of agglomerates, travel rate between them, and disease recovery rate. While the emergence of agglomerates permits early interventions, it also explains longer real epidemics. In this work, we study the spread of susceptible-infected-recovered (SIR) epidemics (or any sort of information exchange by contact) in one-dimensional spatially structured systems. By working in one dimension, we establish a necessary foundation for future investigation in higher dimensions and mimic micro-organisms in narrow channels. We employ a model of self-propelled particles which spontaneously form multiple clusters. For a lower rate of stochastic reorientation, particles have a higher tendency to agglomerate and therefore the clusters become larger and less numerous. We examine the time evolution averaged over many epidemics and how it is affected by the existence of clusters through the eventual recovery of infected particles before reaching new clusters. New terms appear in the SIR differential equations in the last epidemic stages. We show how the final number of ever-infected individuals depends nontrivially on single-individual parameters. In particular, the number of ever-infected individuals first increases with the reorientation rate since particles escape sooner from clusters and spread the disease. For higher reorientation rate, travel between clusters becomes too diffusive and the clusters too small, decreasing the number of ever-infected individuals.
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Affiliation(s)
- Pablo de Castro
- ICTP-South American Institute for Fundamental Research - Instituto de Física Teórica da UNESP, Rua Dr. Bento Teobaldo Ferraz 271, 01140-070 São Paulo, Brazil
| | - Felipe Urbina
- Centro Multidisciplinario de Física, Universidad Mayor, Huechuraba, 8580745 Santiago, Chile
| | - Ariel Norambuena
- Centro Multidisciplinario de Física, Universidad Mayor, Huechuraba, 8580745 Santiago, Chile
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5
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Marmor Y, Abbey A, Shahar Y, Mokryn O. Assessing individual risk and the latent transmission of COVID-19 in a population with an interaction-driven temporal model. Sci Rep 2023; 13:12955. [PMID: 37563358 PMCID: PMC10415258 DOI: 10.1038/s41598-023-39817-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 07/31/2023] [Indexed: 08/12/2023] Open
Abstract
Interaction-driven modeling of diseases over real-world contact data has been shown to promote the understanding of the spread of diseases in communities. This temporal modeling follows the path-preserving order and timing of the contacts, which are essential for accurate modeling. Yet, other important aspects were overlooked. Various airborne pathogens differ in the duration of exposure needed for infection. Also, from the individual perspective, Covid-19 progression differs between individuals, and its severity is statistically correlated with age. Here, we enrich an interaction-driven model of Covid-19 and similar airborne viral diseases with (a) meetings duration and (b) personal disease progression. The enriched model enables predicting outcomes at both the population and the individual levels. It further allows predicting individual risk of engaging in social interactions as a function of the virus characteristics and its prevalence in the population. We further showed that the enigmatic nature of asymptomatic transmission stems from the latent effect of the network density on this transmission and that asymptomatic transmission has a substantial impact only in sparse communities.
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Affiliation(s)
- Yanir Marmor
- Information Systems, University of Haifa, Haifa, Israel
| | - Alex Abbey
- Information Systems, University of Haifa, Haifa, Israel
| | - Yuval Shahar
- Software and Information Systems Engineering, Ben Gurion University, Beer Sheva, Israel
| | - Osnat Mokryn
- Information Systems, University of Haifa, Haifa, Israel.
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6
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Gupte PR, Albery GF, Gismann J, Sweeny A, Weissing FJ. Novel pathogen introduction triggers rapid evolution in animal social movement strategies. eLife 2023; 12:e81805. [PMID: 37548365 PMCID: PMC10449382 DOI: 10.7554/elife.81805] [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: 07/12/2022] [Accepted: 08/04/2023] [Indexed: 08/08/2023] Open
Abstract
Animal sociality emerges from individual decisions on how to balance the costs and benefits of being sociable. Novel pathogens introduced into wildlife populations should increase the costs of sociality, selecting against gregariousness. Using an individual-based model that captures essential features of pathogen transmission among social hosts, we show how novel pathogen introduction provokes the rapid evolutionary emergence and coexistence of distinct social movement strategies. These strategies differ in how they trade the benefits of social information against the risk of infection. Overall, pathogen-risk-adapted populations move more and have fewer associations with other individuals than their pathogen-risk-naive ancestors, reducing disease spread. Host evolution to be less social can be sufficient to cause a pathogen to be eliminated from a population, which is followed by a rapid recovery in social tendency. Our conceptual model is broadly applicable to a wide range of potential host-pathogen introductions and offers initial predictions for the eco-evolutionary consequences of wildlife pathogen spillover scenarios and a template for the development of theory in the ecology and evolution of animals' movement decisions.
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Affiliation(s)
- Pratik Rajan Gupte
- Groningen Institute for Evolutionary Life Sciences, University of GroningenGroningenNetherlands
| | - Gregory F Albery
- Georgetown UniversityWashingtonUnited States
- Wissenschaftskolleg zu BerlinBerlinGermany
| | - Jakob Gismann
- Groningen Institute for Evolutionary Life Sciences, University of GroningenGroningenNetherlands
| | - Amy Sweeny
- Institute of Evolutionary Biology, University of EdinburghEdinburghUnited Kingdom
| | - Franz J Weissing
- Groningen Institute for Evolutionary Life Sciences, University of GroningenGroningenNetherlands
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7
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Huang YH, Owen-Smith N, Henley MD, Kilian JW, Kamath PL, Ochai SO, van Heerden H, Mfune JKE, Getz WM, Turner WC. Variation in herbivore space use: comparing two savanna ecosystems with different anthrax outbreak patterns in southern Africa. MOVEMENT ECOLOGY 2023; 11:46. [PMID: 37525286 PMCID: PMC10392021 DOI: 10.1186/s40462-023-00385-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Accepted: 04/16/2023] [Indexed: 08/02/2023]
Abstract
BACKGROUND The distribution of resources can affect animal range sizes, which in turn may alter infectious disease dynamics in heterogenous environments. The risk of pathogen exposure or the spatial extent of outbreaks may vary with host range size. This study examined the range sizes of herbivorous anthrax host species in two ecosystems and relationships between spatial movement behavior and patterns of disease outbreaks for a multi-host environmentally transmitted pathogen. METHODS We examined range sizes for seven host species and the spatial extent of anthrax outbreaks in Etosha National Park, Namibia and Kruger National Park, South Africa, where the main host species and outbreak sizes differ. We evaluated host range sizes using the local convex hull method at different temporal scales, within-individual temporal range overlap, and relationships between ranging behavior and species contributions to anthrax cases in each park. We estimated the spatial extent of annual anthrax mortalities and evaluated whether the extent was correlated with case numbers of a given host species. RESULTS Range size differences among species were not linearly related to anthrax case numbers. In Kruger the main host species had small range sizes and high range overlap, which may heighten exposure when outbreaks occur within their ranges. However, different patterns were observed in Etosha, where the main host species had large range sizes and relatively little overlap. The spatial extent of anthrax mortalities was similar between parks but less variable in Etosha than Kruger. In Kruger outbreaks varied from small local clusters to large areas and the spatial extent correlated with case numbers and species affected. Secondary host species contributed relatively few cases to outbreaks; however, for these species with large range sizes, case numbers positively correlated with outbreak extent. CONCLUSIONS Our results provide new information on the spatiotemporal structuring of ranging movements of anthrax host species in two ecosystems. The results linking anthrax dynamics to host space use are correlative, yet suggest that, though partial and proximate, host range size and overlap may be contributing factors in outbreak characteristics for environmentally transmitted pathogens.
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Affiliation(s)
- Yen-Hua Huang
- Wisconsin Cooperative Wildlife Research Unit, Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, WI, 53706, USA.
| | - Norman Owen-Smith
- Centre for African Ecology, School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Wits, 2050, South Africa
| | - Michelle D Henley
- Applied Behavioural Ecology and Ecosystem Research Unit, School of Environmental Sciences, University of South Africa, Florida, Johannesburg, 1710, South Africa
- Elephants Alive, Ekuthuleni Shareblock Ltd, Hoedspruit, 1380, South Africa
- Department of Philosophy, Faculty of Humanities, University of Johannesburg, Auckland Park, 2006, South Africa
| | - J Werner Kilian
- Etosha Ecological Institute (retired), Etosha National Park, Ministry of Environment, Forestry and Tourism, Okaukuejo, Namibia
| | - Pauline L Kamath
- School of Food and Agriculture, University of Maine, Orono, ME, 04469, USA
| | - Sunday O Ochai
- Department of Veterinary Tropical Diseases, University of Pretoria, Onderstepoort, South Africa
| | - Henriette van Heerden
- Department of Veterinary Tropical Diseases, University of Pretoria, Onderstepoort, South Africa
| | - John K E Mfune
- Department of Environmental Science, University of Namibia, Windhoek, Namibia
| | - Wayne M Getz
- Department of Environmental Science, Policy & Management, University of California, Berkeley, CA, 94704, USA
- School of Mathematical Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Wendy C Turner
- Wisconsin Cooperative Wildlife Research Unit, U.S. Geological Survey, Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, WI, 53706, USA
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8
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Yang A, Wilber MQ, Manlove KR, Miller RS, Boughton R, Beasley J, Northrup J, VerCauteren KC, Wittemyer G, Pepin K. Deriving spatially explicit direct and indirect interaction networks from animal movement data. Ecol Evol 2023; 13:e9774. [PMID: 36993145 PMCID: PMC10040956 DOI: 10.1002/ece3.9774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 01/11/2023] [Indexed: 03/29/2023] Open
Abstract
Quantifying spatiotemporally explicit interactions within animal populations facilitates the understanding of social structure and its relationship with ecological processes. Data from animal tracking technologies (Global Positioning Systems [“GPS”]) can circumvent longstanding challenges in the estimation of spatiotemporally explicit interactions, but the discrete nature and coarse temporal resolution of data mean that ephemeral interactions that occur between consecutive GPS locations go undetected. Here, we developed a method to quantify individual and spatial patterns of interaction using continuous‐time movement models (CTMMs) fit to GPS tracking data. We first applied CTMMs to infer the full movement trajectories at an arbitrarily fine temporal scale before estimating interactions, thus allowing inference of interactions occurring between observed GPS locations. Our framework then infers indirect interactions—individuals occurring at the same location, but at different times—while allowing the identification of indirect interactions to vary with ecological context based on CTMM outputs. We assessed the performance of our new method using simulations and illustrated its implementation by deriving disease‐relevant interaction networks for two behaviorally differentiated species, wild pigs (Sus scrofa) that can host African Swine Fever and mule deer (Odocoileus hemionus) that can host chronic wasting disease. Simulations showed that interactions derived from observed GPS data can be substantially underestimated when temporal resolution of movement data exceeds 30‐min intervals. Empirical application suggested that underestimation occurred in both interaction rates and their spatial distributions. CTMM‐Interaction method, which can introduce uncertainties, recovered majority of true interactions. Our method leverages advances in movement ecology to quantify fine‐scale spatiotemporal interactions between individuals from lower temporal resolution GPS data. It can be leveraged to infer dynamic social networks, transmission potential in disease systems, consumer–resource interactions, information sharing, and beyond. The method also sets the stage for future predictive models linking observed spatiotemporal interaction patterns to environmental drivers.
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Affiliation(s)
- Anni Yang
- Department of Geography and Environmental SustainabilityUniversity of OklahomaOklahomaNormanUSA
- Department of Fish, Wildlife and Conservation BiologyColorado State UniversityColoradoFort CollinsUSA
- United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife ServicesNational Wildlife Research CenterColoradoFort CollinsUSA
| | - Mark Q. Wilber
- Forestry, Wildlife, and Fisheries, Institute of AgricultureUniversity of TennesseeTennesseeKnoxvilleUSA
| | - Kezia R. Manlove
- Department of Wildland Resources and Ecology CenterUtah State UniversityUtahLoganUSA
| | - Ryan S. Miller
- Center for Epidemiology and Animal HealthUnited States Department of Agriculture, Animal and Plant Health Inspection Service, Veterinary ServiceColoradoFort CollinsUSA
| | - Raoul Boughton
- Archbold Biological StationBuck Island RanchFloridaLake PlacidUSA
| | - James Beasley
- Savannah River Ecology LaboratoryWarnell School of Forestry and Natural ResourcesUniversity of GeorgiaSouth CarolinaAikenUSA
| | - Joseph Northrup
- Wildlife Research and Monitoring SectionOntario Ministry of Natural Resources and ForestryOntarioPeterboroughCanada
| | - Kurt C. VerCauteren
- United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife ServicesNational Wildlife Research CenterColoradoFort CollinsUSA
| | - George Wittemyer
- Department of Fish, Wildlife and Conservation BiologyColorado State UniversityColoradoFort CollinsUSA
| | - Kim Pepin
- United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife ServicesNational Wildlife Research CenterColoradoFort CollinsUSA
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9
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Egan ME, Pepin KM, Fischer JW, Hygnstrom SE, VerCauteren KC, Bastille‐Rousseau G. Social network analysis of white‐tailed deer scraping behavior: Implications for disease transmission. Ecosphere 2023. [DOI: 10.1002/ecs2.4434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/22/2023] Open
Affiliation(s)
- Michael E. Egan
- Cooperative Wildlife Research Laboratory Southern Illinois University Carbondale Illinois USA
- School of Biological Sciences Southern Illinois University Carbondale Illinois USA
| | - Kim M. Pepin
- National Wildlife Research Center United States Department of Agriculture, Animal and Plant Health Inspection Services, Wildlife Service Fort Collins Colorado USA
| | - Justin W. Fischer
- National Wildlife Research Center United States Department of Agriculture, Animal and Plant Health Inspection Services, Wildlife Service Fort Collins Colorado USA
| | - Scott E. Hygnstrom
- Wisconsin Center for Wildlife College of Natural Resources, University of Wisconsin‐Stevens Point Stevens Point Wisconsin USA
| | - Kurt C. VerCauteren
- National Wildlife Research Center United States Department of Agriculture, Animal and Plant Health Inspection Services, Wildlife Service Fort Collins Colorado USA
| | - Guillaume Bastille‐Rousseau
- Cooperative Wildlife Research Laboratory Southern Illinois University Carbondale Illinois USA
- School of Biological Sciences Southern Illinois University Carbondale Illinois USA
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10
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Silk MJ, Wilber MQ, Fefferman NH. Capturing complex interactions in disease ecology with simplicial sets. Ecol Lett 2022; 25:2217-2231. [PMID: 36001469 DOI: 10.1111/ele.14079] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 04/21/2022] [Accepted: 06/29/2022] [Indexed: 11/28/2022]
Abstract
Network approaches have revolutionized the study of ecological interactions. Social, movement and ecological networks have all been integral to studying infectious disease ecology. However, conventional (dyadic) network approaches are limited in their ability to capture higher-order interactions. We present simplicial sets as a tool that addresses this limitation. First, we explain what simplicial sets are. Second, we explain why their use would be beneficial in different subject areas. Third, we detail where these areas are: social, transmission, movement/spatial and ecological networks and when using them would help most in each context. To demonstrate their application, we develop a novel approach to identify how pathogens persist within a host population. Fourth, we provide an overview of how to use simplicial sets, highlighting specific metrics, generative models and software. Finally, we synthesize key research questions simplicial sets will help us answer and draw attention to methodological developments that will facilitate this.
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Affiliation(s)
- Matthew J Silk
- NIMBioS, University of Tennessee, Knoxville, Tennessee, USA.,CEFE, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France
| | - Mark Q Wilber
- Department of Forestry, Wildlife and Fisheries, University of Tennessee, Knoxville, Tennessee, USA
| | - Nina H Fefferman
- NIMBioS, University of Tennessee, Knoxville, Tennessee, USA.,Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, Tennessee, USA.,Department of Mathematics, University of Tennessee, Knoxville, Tennessee, USA
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11
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Pepin KM, Brown VR, Yang A, Beasley JC, Boughton R, VerCauteren KC, Miller RS, Bevins SN. Optimizing response to an introduction of African swine fever in wild pigs. Transbound Emerg Dis 2022; 69:e3111-e3127. [PMID: 35881004 DOI: 10.1111/tbed.14668] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 07/22/2022] [Accepted: 07/24/2022] [Indexed: 11/28/2022]
Abstract
African swine fever virus (ASFv) is a virulent pathogen that threatens domestic swine industries globally and persists in wild boar populations in some countries. Persistence in wild boar can challenge elimination and prevent disease-free status, making it necessary to address wild swine in proactive response plans. In the U.S., invasive wild pigs are abundant and found across a wide range of ecological conditions that could drive different epidemiological dynamics among populations. Information on size of control areas required to rapidly eliminate ASFv in wild pigs and how this area should change with management constraints and local ecology are needed to optimize response planning. We developed a spatially-explicit disease transmission model contrasting wild pig movement and contact ecology in two ecosystems in southeastern U.S. We simulated ASFv spread and determined optimal response area (reported as radius of a circle) for eliminating ASFv rapidly over a range of detection times (when ASFv is detected relative to true date of introduction), culling capacities (proportion of wild pigs in the culling zone removed weekly), and wild pig densities. Large radii for response areas (14 km) were needed under most conditions but could be shortened with early detection (≤ 8 weeks) and high culling capacities (≥ 15% weekly). Under most conditions ASFv was eliminated in less than 22 weeks using optimal control radii, although ecological conditions with high rates of wild pig movement required higher culling capacities (≥ 10% weekly) for elimination within one year. Results highlight the importance of adjusting response plans based on local ecology and show wild pig movement is a better predictor of optimal response area than numbers of ASFv cases early in the outbreak trajectory. Our framework provides a tool for determining optimal control plans in different areas, guiding expectations of response impacts, and planning resources needed for rapid elimination. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Kim M Pepin
- National Wildlife Research Center, Wildlife Services, Animal and Plant Health Inspection Service, United States Department of Agriculture, 4101 Laporte Ave., Fort Collins, CO, 80526
| | - Vienna R Brown
- United States Department of Agriculture, Animal and Plant Health Inspection Services, Wildlife Services, National Feral Swine Damage Management Program, Fort Collins, CO
| | - Anni Yang
- National Wildlife Research Center, Wildlife Services, Animal and Plant Health Inspection Service, United States Department of Agriculture, 4101 Laporte Ave., Fort Collins, CO, 80526.,Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, Colorado, 80523, US
| | - James C Beasley
- Savannah River Ecology Laboratory, Warnell School of Forestry and Natural Resources, University of Georgia, PO Drawer E, Aiken, South Carolina, 29802, US
| | - Raoul Boughton
- Archbold Biological Station's Buck Island Ranch, 300 Buck Island Ranch Road, Lake Placid, FL, 33852, US
| | - Kurt C VerCauteren
- National Wildlife Research Center, Wildlife Services, Animal and Plant Health Inspection Service, United States Department of Agriculture, 4101 Laporte Ave., Fort Collins, CO, 80526
| | - Ryan S Miller
- Centers for Epidemiology and Animal Health, Veterinary Services, Animal and Plant Health Inspection Service, United States Department of Agriculture, 2150 Center Ave., Fort Collins, CO, 80526
| | - Sarah N Bevins
- National Wildlife Research Center, Wildlife Services, Animal and Plant Health Inspection Service, United States Department of Agriculture, 4101 Laporte Ave., Fort Collins, CO, 80526
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