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Pathogens
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Spatio-Temporal Analysis of Veterinary Infectious Diseases
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Spatio-Temporal Analysis of Veterinary Infectious Diseases

A special issue of Pathogens (ISSN 2076-0817). This special issue belongs to the section "Epidemiology of Infectious Diseases".

Deadline for manuscript submissions: 1 August 2024 | Viewed by 5954

Special Issue Editors

Dr. Kimberly VanderWaal

E-Mail Website
Guest Editor
Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN 55108, USA
Interests: population connectivity and pathogen spread; molecular epidemiology of viruses, including viral evolution and multi-strain dynamics; spatio-temporal analysis of infectious diseases
Dr. Catalina Picasso-Risso

E-Mail Website
Guest Editor
Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN 55108, USA
Interests: spatio-temporal analysis; diagnostic epidemiology; data-informed decisions; infectious diseases; one health

Special Issue Information

Dear Colleagues,

Infectious diseases are a major determinant of the health and welfare of animal populations, and in many cases, the incidence of pathogens in animals has direct implications for the stability of food systems and pathogen spillover to humans. Quantifying the spatial and temporal dynamics of pathogens is a key component to understanding the transmission, control, and impacts of veterinary infectious diseases. This Special Issue aims to highlight the application of spatial and temporal analytical methods to the study of veterinary infectious diseases, including those impacting wild and domestic populations. These include descriptive and predictive tools that aim to analyze spatiotemporal variation in the occurrence of disease in animal populations, and to elucidate underlying environmental or demographic drivers, and their impact on risk-based surveillance and control strategies. We are also interested in studies that investigate how population connectivity influences the spatiotemporal dynamics of disease, utilizing a variety of tools such as network analysis, modeling, and molecular epidemiology. Ultimately, research on this issue will illustrate how diverse spatial and temporal analytical tools can be applied to elucidate drivers of disease occurrence, facilitate data-informed decision making, enhance disease preparedness, and optimize surveillance and control measures.

Dr. Kimberly VanderWaal
Dr. Catalina Picasso-Risso
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Pathogens is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • population connectivity
  • molecular epidemiology
  • spatial epidemiology
  • pathogen spread
  • veterinary
  • infectious diseases

Published Papers (4 papers)

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Research

16 pages, 924 KiB  
Article
Spatial Distribution of Dermanyssus gallinae Infestations in Greece and Their Association with Ambient Temperature, Humidity, and Altitude
by Georgios Sioutas, Athanasios I. Gelasakis and Elias Papadopoulos
Pathogens 2024, 13(4), 347; https://doi.org/10.3390/pathogens13040347 - 22 Apr 2024
Viewed by 361
Abstract
Dermanyssus gallinae, the poultry red mite (PRM), is the most prevalent and harmful ectoparasite of laying hens globally. Although prevalence and risk factor studies can help veterinarians make decisions regarding farm treatments, relevant data are scarce. The present study investigated the prevalence [...] Read more.
Dermanyssus gallinae, the poultry red mite (PRM), is the most prevalent and harmful ectoparasite of laying hens globally. Although prevalence and risk factor studies can help veterinarians make decisions regarding farm treatments, relevant data are scarce. The present study investigated the prevalence and infestation severity of PRM in poultry farms across Greece and examined potential risk factors. AviVet traps were used to sample 84 farms (51 backyard, 33 industrial) over three years. Farm altitude, temperature, humidity, region, and production systems were assessed as potential risk factors with chi-square tests, initially for all the studied farms and then exclusively for backyard farms. The overall prevalence was 75.0% and was higher in backyard farms (80.4%) compared with industrial ones (66.7%), varying regionally from 66.7 to 90.9%. Altitude and temperature were not significant risk factors, but farms with humidity <60% had a lower infestation risk. Infestation severity did not significantly differ by risk factors. The poultry red mite is highly prevalent across Greek poultry production systems and regions. In the future, global warming, reduced acaricide options, and a ban on cage systems will all threaten a wider spatio-temporal distribution of the PRM, justifying the urgent need for effective monitoring and control methods to protect hen production and welfare and workers’ health. Full article
(This article belongs to the Special Issue Spatio-Temporal Analysis of Veterinary Infectious Diseases)
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10 pages, 895 KiB  
Article
Evaluating Trends in Strangles Outbreaks Using Temperature and Precipitation Data in the United States of America for 2018–2022
by Bryce A. Thomas, Ryan K. Saylor, Zachary P. Taylor and DeLacy V. L. Rhodes
Pathogens 2023, 12(9), 1106; https://doi.org/10.3390/pathogens12091106 - 29 Aug 2023
Viewed by 875
Abstract
Strangles is a highly contagious upper respiratory infection of equids that is globally distributed. The causative agent of strangles, Streptococcus equi subspecies equi, can be spread through indirect contact with infected fomites, and studies have shown this microbe to live well in [...] Read more.
Strangles is a highly contagious upper respiratory infection of equids that is globally distributed. The causative agent of strangles, Streptococcus equi subspecies equi, can be spread through indirect contact with infected fomites, and studies have shown this microbe to live well in varying environmental conditions. The purpose of this study was to analyze strangles case numbers across the United States of America from 2018 to 2022 to investigate potential temporal or weather patterns associated with outbreaks. Diagnosed case records were obtained from the Equine Disease Communication Center, university databases, government agencies, or veterinary diagnostic labs, and geographic information systems (GISs) were used to map cases and to acquire relevant meteorological data from outbreak areas. These data were analyzed using logistic regression to explore trends that occur between outbreaks and changes in temperature and precipitation. Initial review of weather data suggested monthly changes in strangles case numbers corresponded with changing seasons. Logistic regression indicated that changes in monthly average temperature and minimum temperature were significantly associated with increased or decreased odds of strangles outbreaks, respectively. Future analyses should focus on weather data isolated within a smaller region or state to better resolve trends in strangles outbreaks throughout the continental USA. Full article
(This article belongs to the Special Issue Spatio-Temporal Analysis of Veterinary Infectious Diseases)
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10 pages, 5975 KiB  
Article
Space–Time Patterns of Poultry Pathogens in the USA: A Case Study of Ornithobacterium rhinotracheale and Pasteurella multocida in Turkey Populations
by Magnus R. Campler, Amro Hashish, Mostafa Ghanem, Mohamed M. El-Gazzar and Andréia G. Arruda
Pathogens 2023, 12(8), 1004; https://doi.org/10.3390/pathogens12081004 - 31 Jul 2023
Viewed by 1029
Abstract
Respiratory infections caused by Ornithobacterium rhinotrachealis (ORT) and Pasteurella multocida (PM) bacteria are significant threats to the poultry industry by causing economic losses and welfare issues. Due to characterization difficulties and underutilization of epidemiological tools, description of the spatio-temporal spread of these diseases [...] Read more.
Respiratory infections caused by Ornithobacterium rhinotrachealis (ORT) and Pasteurella multocida (PM) bacteria are significant threats to the poultry industry by causing economic losses and welfare issues. Due to characterization difficulties and underutilization of epidemiological tools, description of the spatio-temporal spread of these diseases in the field is limited. The objectives of this retrospective observational cross-sectional study were to (a) investigate the existence of space–time clusters (hotspots); and (b) investigate the association between genetic similarity and spatial proximity for both pathogens using molecular typing and a recently developed Core-Genome Multilocus Sequencing Typing (cgMLST) scheme. ORT (n = 103) and PM (n = 69) isolates from confirmed disease outbreaks from one commercial company between 2013 and 2021 were obtained from a veterinary diagnostic laboratory, characterized using a cgMLST scheme and visualized using a minimum spanning tree. Spatio-temporal cluster analysis using SaTScanTM and a Spearman’s rank correlation were performed to investigate clustering and any association between allelic diversity and geospatial distance. The cgMLST sequencing revealed three allelic clusters for ORT and thirteen clusters for PM. The spatio-temporal analysis revealed two significant clusters for PM, one with a 259.3 km cluster containing six cases between May and July 2018 and a 9 km cluster containing five cases between February 2019 and February 2021. No spatio-temporal clusters were found for ORT. A weak negative correlation between allelic diversity and geospatial distance was observed for ORT (r = −0.04, p < 0.01) and a weak positive correlation was observed for PM (r = 0.11, p < 0.01). This study revealed regional spatio-temporal clusters for PM in commercial turkey sites between 2018 and 2021 and provided additional insight into bacterial strain subgroups and the geographical spread of ORT and PM over time. Full article
(This article belongs to the Special Issue Spatio-Temporal Analysis of Veterinary Infectious Diseases)
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18 pages, 3142 KiB  
Article
Mapping the Dynamics of Contemporary PRRSV-2 Evolution and Its Emergence and Spreading Hotspots in the U.S. Using Phylogeography
by Nakarin Pamornchainavakul, Igor A. D. Paploski, Dennis N. Makau, Mariana Kikuti, Albert Rovira, Samantha Lycett, Cesar A. Corzo and Kimberly VanderWaal
Pathogens 2023, 12(5), 740; https://doi.org/10.3390/pathogens12050740 - 20 May 2023
Cited by 4 | Viewed by 3033
Abstract
The repeated emergence of new genetic variants of PRRSV-2, the virus that causes porcine reproductive and respiratory syndrome (PRRS), reflects its rapid evolution and the failure of previous control efforts. Understanding spatiotemporal heterogeneity in variant emergence and spread is critical for future outbreak [...] Read more.
The repeated emergence of new genetic variants of PRRSV-2, the virus that causes porcine reproductive and respiratory syndrome (PRRS), reflects its rapid evolution and the failure of previous control efforts. Understanding spatiotemporal heterogeneity in variant emergence and spread is critical for future outbreak prevention. Here, we investigate how the pace of evolution varies across time and space, identify the origins of sub-lineage emergence, and map the patterns of the inter-regional spread of PRRSV-2 Lineage 1 (L1)—the current dominant lineage in the U.S. We performed comparative phylogeographic analyses on subsets of 19,395 viral ORF5 sequences collected across the U.S. and Canada between 1991 and 2021. The discrete trait analysis of multiple spatiotemporally stratified sampled sets (n = 500 each) was used to infer the ancestral geographic region and dispersion of each sub-lineage. The robustness of the results was compared to that of other modeling methods and subsampling strategies. Generally, the spatial spread and population dynamics varied across sub-lineages, time, and space. The Upper Midwest was a main spreading hotspot for multiple sub-lineages, e.g., L1C and L1F, though one of the most recent emergence events (L1A(2)) spread outwards from the east. An understanding of historical patterns of emergence and spread can be used to strategize disease control and the containment of emerging variants. Full article
(This article belongs to the Special Issue Spatio-Temporal Analysis of Veterinary Infectious Diseases)
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