1
|
Amenu K, McIntyre KM, Moje N, Knight-Jones T, Rushton J, Grace D. Approaches for disease prioritization and decision-making in animal health, 2000-2021: a structured scoping review. Front Vet Sci 2023; 10:1231711. [PMID: 37876628 PMCID: PMC10593474 DOI: 10.3389/fvets.2023.1231711] [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: 05/30/2023] [Accepted: 09/06/2023] [Indexed: 10/26/2023] Open
Abstract
This scoping review identifies and describes the methods used to prioritize diseases for resource allocation across disease control, surveillance, and research and the methods used generally in decision-making on animal health policy. Three electronic databases (Medline/PubMed, Embase, and CAB Abstracts) were searched for articles from 2000 to 2021. Searches identified 6, 395 articles after de-duplication, with an additional 64 articles added manually. A total of 6, 460 articles were imported to online document review management software (sysrev.com) for screening. Based on inclusion and exclusion criteria, 532 articles passed the first screening, and after a second round of screening, 336 articles were recommended for full review. A total of 40 articles were removed after data extraction. Another 11 articles were added, having been obtained from cross-citations of already identified articles, providing a total of 307 articles to be considered in the scoping review. The results show that the main methods used for disease prioritization were based on economic analysis, multi-criteria evaluation, risk assessment, simple ranking, spatial risk mapping, and simulation modeling. Disease prioritization was performed to aid in decision-making related to various categories: (1) disease control, prevention, or eradication strategies, (2) general organizational strategy, (3) identification of high-risk areas or populations, (4) assessment of risk of disease introduction or occurrence, (5) disease surveillance, and (6) research priority setting. Of the articles included in data extraction, 50.5% had a national focus, 12.3% were local, 11.9% were regional, 6.5% were sub-national, and 3.9% were global. In 15.2% of the articles, the geographic focus was not specified. The scoping review revealed the lack of comprehensive, integrated, and mutually compatible approaches to disease prioritization and decision support tools for animal health. We recommend that future studies should focus on creating comprehensive and harmonized frameworks describing methods for disease prioritization and decision-making tools in animal health.
Collapse
Affiliation(s)
- Kebede Amenu
- Global Burden of Animal Diseases (GBADs) Programme, University of Liverpool, Liverpool, United Kingdom
- Department of Microbiology, Immunology and Veterinary, Public Health, College of Veterinary Medicine and Agriculture, Addis Ababa University, Bishoftu, Ethiopia
- Animal and Human Health Program, International Livestock Research Institute (ILRI), Addis Ababa, Ethiopia
| | - K. Marie McIntyre
- Global Burden of Animal Diseases (GBADs) Programme, University of Liverpool, Liverpool, United Kingdom
- Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, United Kingdom
- Modelling, Evidence and Policy Group, School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Nebyou Moje
- Department of Biomedical Sciences, College of Veterinary Medicine and Agriculture, Addis Ababa University, Bishoftu, Ethiopia
| | - Theodore Knight-Jones
- Global Burden of Animal Diseases (GBADs) Programme, University of Liverpool, Liverpool, United Kingdom
- Animal and Human Health Program, International Livestock Research Institute (ILRI), Addis Ababa, Ethiopia
| | - Jonathan Rushton
- Global Burden of Animal Diseases (GBADs) Programme, University of Liverpool, Liverpool, United Kingdom
- Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Delia Grace
- Global Burden of Animal Diseases (GBADs) Programme, University of Liverpool, Liverpool, United Kingdom
- Food and Markets Department, Natural Resources Institute, University of Greenwich, London, United Kingdom
- Animal and Human Health Program, International Livestock Research Institute (ILRI), Nairobi, Kenya
| |
Collapse
|
2
|
Shi H, Zhou M, Zhang Z, Hu Y, Song S, Hui R, Wang L, Li G, Yao L. Molecular epidemiology, drug resistance, and virulence gene analysis of Streptococcus agalactiae isolates from dairy goats in backyard farms in China. Front Cell Infect Microbiol 2023; 12:1049167. [PMID: 36699728 PMCID: PMC9868259 DOI: 10.3389/fcimb.2022.1049167] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 12/08/2022] [Indexed: 01/11/2023] Open
Abstract
Streptococcus agalactiae infections may lead to clinical or subclinical mastitis in dairy animals when it invades the mammary gland. In this study, 51 S. agalactiae strains were isolated from 305 milk samples that were collected from goats with mastitis in 13 provinces of China. The antimicrobial resistance of S. agalactiae was determined by disk diffusion methods against 18 antibiotics from six classes. In addition, multilocus sequence typing (MLST), and the presence of resistance and virulence genes was determined by PCR analysis. Seven sequence types in five clonal complexes were identified according to MLST; CC103 and CC67 strains were predominant, with rates of 45.1% and 39.2%, respectively. All isolates (100%) were multiresistant to three or more antimicrobial agents. S. agalactiae isolates had a 100% resistance rate to penicillin, oxacillin, and amoxicillin, followed by doxycycline (82.4%), tetracycline (76.5%), and amikacin (74.5%). The lowest resistance was observed for ciprofloxacin (29.4%), which varied in five different regions. The detection rates of six classes of antimicrobial-related genes were calculated as follows: 33 (64.7%) for β-lactam-related resistance gene, 12 (23.5%) for tetracyclines, 11 (21.6%) for quinolone-related resistance genes, 10 (19.6%) for aminoglycosides, 7 (13.7%) for macrolides (ermA, ermB, and mefA), and 3 (5.9%) for lincosamide (lnu(B)). Regarding virulence genes, profile 1 (bca cfb-cspA-cylE-hylB-bibA-pavA-fbsA-fbsB) was the most prevalent, with a detection rate of 54.9%. This work provides a primary source related to the molecular epidemiology of S. agalactiae in dairy goat herds in China and will aid in the clinical treatment, prevention, and control of mastitis.
Collapse
Affiliation(s)
- Hongfei Shi
- Henan Provincial Engineering and Technology Center of Animal Disease Diagnosis and Integrated Control, Henan Provincial Engineering Laboratory of Insects Bio-reactor, Nanyang Normal University, Nanyang, China,*Correspondence: Hongfei Shi, ; Lunguang Yao,
| | - Mengxiao Zhou
- Henan Provincial Engineering and Technology Center of Animal Disease Diagnosis and Integrated Control, Henan Provincial Engineering Laboratory of Insects Bio-reactor, Nanyang Normal University, Nanyang, China
| | - Zhengtian Zhang
- Henan Provincial Engineering and Technology Center of Animal Disease Diagnosis and Integrated Control, Henan Provincial Engineering Laboratory of Insects Bio-reactor, Nanyang Normal University, Nanyang, China
| | - Yun Hu
- College of Animal Husbandry and Medical Engineering, Nanyang Vocational College of Agriculture, Nanyang, China
| | - Shiyang Song
- Animal Husbandry and Fishery Department, Heilongjiang State 853 Farm Limited Company, Shuangyashan, China
| | - Ruiqing Hui
- Henan Provincial Engineering and Technology Center of Animal Disease Diagnosis and Integrated Control, Henan Provincial Engineering Laboratory of Insects Bio-reactor, Nanyang Normal University, Nanyang, China
| | - Long Wang
- Henan Provincial Engineering and Technology Center of Animal Disease Diagnosis and Integrated Control, Henan Provincial Engineering Laboratory of Insects Bio-reactor, Nanyang Normal University, Nanyang, China
| | - Guoguang Li
- Henan Provincial Engineering and Technology Center of Animal Disease Diagnosis and Integrated Control, Henan Provincial Engineering Laboratory of Insects Bio-reactor, Nanyang Normal University, Nanyang, China
| | - Lunguang Yao
- Henan Provincial Engineering and Technology Center of Animal Disease Diagnosis and Integrated Control, Henan Provincial Engineering Laboratory of Insects Bio-reactor, Nanyang Normal University, Nanyang, China,*Correspondence: Hongfei Shi, ; Lunguang Yao,
| |
Collapse
|
3
|
|
4
|
Wang J, Chen J, Zhang S, Ding Y, Wang M, Zhang H, Liang R, Chen Q, Niu B. Risk assessment and integrated surveillance of foot-and-mouth disease outbreaks in Russia based on Monte Carlo simulation. BMC Vet Res 2021; 17:268. [PMID: 34376207 PMCID: PMC8353819 DOI: 10.1186/s12917-021-02967-x] [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: 03/23/2019] [Accepted: 07/16/2021] [Indexed: 11/21/2022] Open
Abstract
Background Foot-and-mouth disease (FMD) is a highly contagious disease of livestock worldwide. Russia is a big agricultural country with a wide geographical area where FMD outbreaks have become an obstacle for the development of the animal and animal products trade. In this study, we aimed to assess the export risk of FMD from Russia. Results After simulation by Monte Carlo, the results showed that the probability of cattle infected with FMD in the surveillance zone (Surrounding the areas where no epidemic disease has occurred within the prescribed time limit, the construction of buffer areas is called surveillance zone.) of Russia was 1.29 × 10− 6. The probability that at least one FMD positive case was exported from Russia per year in the surveillance zone was 6 %. The predicted number of positive cattle of the 39,530 - 50,576 exported from Russia per year was 0.06. A key node in the impact model was the probability of occurrence of FMD outbreaks in the Russian surveillance zone. By semi-quantitative model calculation, the risk probability of FMD defense system defects was 1.84 × 10− 5, indicating that there was a potential risk in the prevention and control measures of FMD in Russia. The spatial time scan model found that the most likely FMD cluster (P < 0.01) was in the Eastern and Siberian Central regions. Conclusions There was a risk of FMDV among cattle exported from Russia, and the infection rate of cattle in the monitored area was the key factor. Understanding the export risk of FMD in Russia and relevant epidemic prevention measures will help policymakers to develop targeted surveillance plans. Supplementary Information The online version contains supplementary material available at 10.1186/s12917-021-02967-x.
Collapse
Affiliation(s)
- Jianying Wang
- Shanghai Key Laboratory of Bio-Energy Crops, School of Life Sciences, Shanghai University, 200444, Shanghai, People's Republic of China
| | - Jiahui Chen
- Shanghai Key Laboratory of Bio-Energy Crops, School of Life Sciences, Shanghai University, 200444, Shanghai, People's Republic of China
| | - Shuwen Zhang
- Shanghai Key Laboratory of Bio-Energy Crops, School of Life Sciences, Shanghai University, 200444, Shanghai, People's Republic of China
| | - Yanting Ding
- Shanghai Key Laboratory of Bio-Energy Crops, School of Life Sciences, Shanghai University, 200444, Shanghai, People's Republic of China
| | - Minjia Wang
- Shanghai Key Laboratory of Bio-Energy Crops, School of Life Sciences, Shanghai University, 200444, Shanghai, People's Republic of China
| | - Hui Zhang
- Shanghai Key Laboratory of Bio-Energy Crops, School of Life Sciences, Shanghai University, 200444, Shanghai, People's Republic of China
| | - Ruirui Liang
- Shanghai Key Laboratory of Bio-Energy Crops, School of Life Sciences, Shanghai University, 200444, Shanghai, People's Republic of China
| | - Qin Chen
- Shanghai Key Laboratory of Bio-Energy Crops, School of Life Sciences, Shanghai University, 200444, Shanghai, People's Republic of China.
| | - Bing Niu
- Shanghai Key Laboratory of Bio-Energy Crops, School of Life Sciences, Shanghai University, 200444, Shanghai, People's Republic of China.
| |
Collapse
|
5
|
Schettino DN, Korennoy FI, Perez AM. Risk of Introduction of Classical Swine Fever Into the State of Mato Grosso, Brazil. Front Vet Sci 2021; 8:647838. [PMID: 34277750 PMCID: PMC8280757 DOI: 10.3389/fvets.2021.647838] [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: 12/30/2020] [Accepted: 05/28/2021] [Indexed: 11/13/2022] Open
Abstract
Classical swine fever (CSF) is considered one of the most important diseases of swine because of the far-reaching economic impact the disease causes to affected countries and regions. The state of Mato Grosso (MT) is part of Brazil's CSF-free zone. CSF status is uncertain in some of MT's neighboring States and countries, which has resulted in the perception that MT is at high risk for the disease. However, the risk for CSF introduction into MT has not been previously assessed. Here, we estimated that the risk for CSF introduction into the MT is highly heterogeneous. The risk associated with shipment of commercial pigs was concentrated in specific municipalities with intense commercial pig production, whereas the risk associated with movement of wild boars was clustered in certain municipalities located close to the state's borders, mostly in northern and southwestern MT. Considering the two pathways of possible introduction assessed here, these results demonstrate the importance of using alternative strategies for surveillance that target different routes and account for different likelihoods of introduction. These results will help to design, implement, and monitor surveillance activities for sustaining the CSF-free status of MT at times when Brazil plans to expand the recognition of disease-free status for other regions in the country.
Collapse
Affiliation(s)
- Daniella N Schettino
- Department of Veterinary Population Medicine, Center for Animal Health and Food Safety, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, United States.,Animal Health Coordination, Instituto de Defesa Agropecuária de Mato Grosso (INDEA-MT), Mato Grosso, Cuiabá, Brazil
| | - Fedor I Korennoy
- FGBI Federal Centre for Animal Health (FGBI ARRIAH), Vladimir, Russia
| | - Andres M Perez
- Department of Veterinary Population Medicine, Center for Animal Health and Food Safety, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, United States
| |
Collapse
|
6
|
Manyweathers J, Maru Y, Hayes L, Loechel B, Kruger H, Mankad A, Xie G, Woodgate R, Hernandez-Jover M. Using a Bayesian Network Predictive Model to Understand Vulnerability of Australian Sheep Producers to a Foot and Mouth Disease Outbreak. Front Vet Sci 2021; 8:668679. [PMID: 34179162 PMCID: PMC8226010 DOI: 10.3389/fvets.2021.668679] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 04/22/2021] [Indexed: 11/29/2022] Open
Abstract
To maintain and strengthen Australia's competitive international advantage in sheep meat and wool markets, the biosecurity systems that support these industries need to be robust and effective. These systems, strengthened by jurisdictional and livestock industry investments, can also be enhanced by a deeper understanding of individual producer risk of exposure to animal diseases and capacity to respond to these risks. This observational study developed a Vulnerability framework, built from current data from Australian sheep producers around behaviors and beliefs that may impact on their likelihood of Exposure and Response Capacity (willingness and ability to respond) to an emergency animal disease (EAD). Using foot and mouth disease (FMD) as a model, a cross-sectional survey gathered information on sheep producers' demographics, and their practices and beliefs around animal health management and biosecurity. Using the Vulnerability framework, a Bayesian Network (BN) model was developed as a first attempt to develop a decision making tool to inform risk based surveillance resource allocation. Populated by the data from 448 completed questionnaires, the BN model was analyzed to investigate relationships between variables and develop producer Vulnerability profiles. Respondents reported high levels of implementation of biosecurity practices that impact the likelihood of exposure to an EAD, such as the use of appropriate animal movement documentation (75.4%) and isolation of incoming stock (64.9%). However, adoption of other practices relating to feral animal control and biosecurity protocols for visitors were limited. Respondents reported a high uptake of Response Capacity practices, including identifying themselves as responsible for observing (94.6%), reporting unusual signs of disease in their animals (91.0%) and daily/weekly inspection of animals (90.0%). The BN analysis identified six Vulnerability typologies, with three levels of Exposure (high, moderate, low) and two levels of Response Capacity (high, low), as described by producer demographics and practices. The most influential Exposure variables on producer Vulnerability included adoption levels of visitor biosecurity and visitor access protocols. Findings from this study can guide decisions around resource allocation to improve Australia's readiness for EAD incursion and strengthen the country's biosecurity system.
Collapse
Affiliation(s)
- Jennifer Manyweathers
- Graham Centre for Agricultural Innovation, Charles Sturt University, Wagga Wagga, NSW, Australia.,School of Animal and Veterinary Sciences, Charles Sturt University, Wagga Wagga, NSW, Australia
| | - Yiheyis Maru
- Commonwealth Scientific and Industrial Research Organisation Land and Water, Canberra, ACT, Australia
| | - Lynne Hayes
- School of Animal and Veterinary Sciences, Charles Sturt University, Wagga Wagga, NSW, Australia
| | - Barton Loechel
- Commonwealth Scientific and Industrial Research Organisation, Brisbane, QLD, Australia
| | - Heleen Kruger
- Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES), Canberra, ACT, Australia
| | - Aditi Mankad
- Commonwealth Scientific and Industrial Research Organisation, Brisbane, QLD, Australia
| | - Gang Xie
- Quantitative Consulting Unit, Charles Sturt University, Wagga Wagga, NSW, Australia
| | - Rob Woodgate
- Graham Centre for Agricultural Innovation, Charles Sturt University, Wagga Wagga, NSW, Australia.,School of Animal and Veterinary Sciences, Charles Sturt University, Wagga Wagga, NSW, Australia
| | - Marta Hernandez-Jover
- Graham Centre for Agricultural Innovation, Charles Sturt University, Wagga Wagga, NSW, Australia.,School of Animal and Veterinary Sciences, Charles Sturt University, Wagga Wagga, NSW, Australia
| |
Collapse
|
7
|
Hayes L, Manyweathers J, Maru Y, Loechel B, Kelly J, Kruger H, Woodgate R, Hernandez-Jover M. Stakeholder mapping in animal health surveillance: A comparative assessment of networks in intensive dairy cattle and extensive sheep production in Australia. Prev Vet Med 2021; 190:105326. [PMID: 33735818 DOI: 10.1016/j.prevetmed.2021.105326] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2020] [Revised: 02/09/2021] [Accepted: 03/08/2021] [Indexed: 11/24/2022]
Abstract
The capacity to rapidly identify and respond to suspicion of animal disease is fundamental to protecting the integrity of the Australian livestock industry. An incursion of a nationally significant endemic, emerging or exotic animal disease could be disruptive and economically damaging for the industry, broader community and national economy. To counter this potential threat, a surveillance system that includes general and targeted activities exists at a jurisdictional and national level. Such a system requires a collaborative effort from all involved to work towards a common goal, reflecting the notion of shared responsibility. As in all systems, the animal health surveillance system can be enhanced or constrained by the relationships of the players involved. This study focusses on two livestock industries, dairy cattle and sheep, exploring the interrelationships between all stakeholders, and their role within the Australian animal health surveillance system. A stakeholder mapping exercise was undertaken, including a depiction of the perceived level of stakeholder interest and influence on producers' animal health surveillance practices and/or the surveillance system. Results from these activities were expanded upon through interviews. The findings reveal complex networks and a system that is, at times, constrained by institutional and individual barriers such as communication between and within stakeholders, and uncertainty about the consequences of reporting a suspected emergency disease. Whilst these challenges have the potential to negatively impact the robustness of the animal disease surveillance system, the study also provides clear evidence of strong and effective relationships amongst many of the key individuals and organisations.
Collapse
Affiliation(s)
- Lynne Hayes
- Graham Centre for Agricultural Innovation (NSW Department of Primary Industries and Charles Sturt University), Australia; School of Animal and Veterinary Sciences, Charles Sturt University, Australia.
| | - Jennifer Manyweathers
- Graham Centre for Agricultural Innovation (NSW Department of Primary Industries and Charles Sturt University), Australia
| | - Yiheyis Maru
- Commonwealth Scientific and Industrial Research Organisation, Canberra, ACT, 2601 Australia
| | - Barton Loechel
- Commonwealth Scientific and Industrial Research Organisation, Brisbane, QLD, 4001, Australia
| | - Jennifer Kelly
- Commonwealth Scientific and Industrial Research Organisation, Canberra, ACT, 2601 Australia
| | - Heleen Kruger
- Australian Bureau of Agricultural and Resource Economics and Sciences, Canberra, ACT, 2601, Australia
| | - Robert Woodgate
- Graham Centre for Agricultural Innovation (NSW Department of Primary Industries and Charles Sturt University), Australia; School of Animal and Veterinary Sciences, Charles Sturt University, Australia
| | - Marta Hernandez-Jover
- Graham Centre for Agricultural Innovation (NSW Department of Primary Industries and Charles Sturt University), Australia; School of Animal and Veterinary Sciences, Charles Sturt University, Australia
| |
Collapse
|
8
|
Manyweathers J, Maru Y, Hayes L, Loechel B, Kruger H, Mankad A, Xie G, Woodgate R, Hernandez-Jover M. The goat industry in Australia: Using Bayesian network analysis to understand vulnerability to a foot and mouth disease outbreak. Prev Vet Med 2020; 187:105236. [PMID: 33385617 DOI: 10.1016/j.prevetmed.2020.105236] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 12/09/2020] [Accepted: 12/11/2020] [Indexed: 11/15/2022]
Abstract
Australia's goat industry is one of the largest goat product exporters in the world, managing both farmed and wild caught animals. To protect and maintain the competitive advantage afforded to the Australian goat industry by the absence of many diseases endemic elsewhere, it is important to identify the vulnerability of producers to livestock disease incursions. This study developed a framework of producer vulnerability built from the beliefs and practices of producers that may impact on their likelihood of exposure and response capacity to an emergency animal disease (EAD), using foot and mouth disease as a model. A cross-sectional questionnaire gathered information on producer/enterprise demographics, animal health management and biosecurity practices, with 107 participating in the study. The biosecurity measures that were most commonly implemented by producers were always using animal movement documentation for purchased stock (74.7 %) and isolating new stock (73.1 %). However, moderate to low uptake of biosecurity protocols related to visitors to the property were reported. Response capacity variables such as checking animals daily (72.0 %) and record keeping (91.7 %) were reported by the majority of respondents, with 40.7 % reporting yearly veterinary inspection of their animals. Using the vulnerability framework, a Bayesian Network model was developed and populated by the survey data, and the relationships between variables were investigated. Six vulnerability profiles were developed, with three levels of exposure (high, moderate, low) and two levels of response capacity (high, low), as described by producer demographics and practices. The most sensitive exposure variables on producer vulnerability included implementation of visitor biosecurity and control of feral animals. Results from this study can inform risk based perspectives and decisions around biosecurity and surveillance resource allocation within the goat industry. The results also highlight opportunities for improving Australia's preparedness for a future EAD incursion by considering producer behaviour and beliefs by applying a vulnerability framework.
Collapse
Affiliation(s)
- Jennifer Manyweathers
- Graham Centre for Agricultural Innovation (NSW Department of Primary Industries and Charles Sturt University), Wagga Wagga, NSW, 2678, Australia.
| | - Yiheyis Maru
- Commonwealth Scientific and Industrial Research Organisation, Canberra, ACT, 2601, Australia
| | - Lynne Hayes
- School of Animal and Veterinary Sciences, Charles Sturt University, Wagga Wagga, NSW, 2678, Australia
| | - Barton Loechel
- Commonwealth Scientific and Industrial Research Organisation, Brisbane, QLD, 4001, Australia
| | - Heleen Kruger
- Australian Bureau of Agricultural and Resource Economics and Science, Canberra, ACT, 2601, Australia
| | - Aditi Mankad
- Commonwealth Scientific and Industrial Research Organisation, Brisbane, QLD, 4001, Australia
| | - Gang Xie
- Quantitative Consulting Unit, Charles Sturt University, Wagga Wagga, NSW, 2678, Australia
| | - Rob Woodgate
- Graham Centre for Agricultural Innovation (NSW Department of Primary Industries and Charles Sturt University), Wagga Wagga, NSW, 2678, Australia; School of Animal and Veterinary Sciences, Charles Sturt University, Wagga Wagga, NSW, 2678, Australia
| | - Marta Hernandez-Jover
- Graham Centre for Agricultural Innovation (NSW Department of Primary Industries and Charles Sturt University), Wagga Wagga, NSW, 2678, Australia; School of Animal and Veterinary Sciences, Charles Sturt University, Wagga Wagga, NSW, 2678, Australia
| |
Collapse
|
9
|
Brown VR, Miller RS, McKee SC, Ernst KH, Didero NM, Maison RM, Grady MJ, Shwiff SA. Risks of introduction and economic consequences associated with African swine fever, classical swine fever and foot-and-mouth disease: A review of the literature. Transbound Emerg Dis 2020; 68:1910-1965. [PMID: 33176063 DOI: 10.1111/tbed.13919] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 10/13/2020] [Accepted: 11/06/2020] [Indexed: 12/31/2022]
Abstract
African swine fever (ASF), classical swine fever (CSF) and foot-and-mouth disease (FMD) are considered to be three of the most detrimental animal diseases and are currently foreign to the U.S. Emerging and re-emerging pathogens can have tremendous impacts in terms of livestock morbidity and mortality events, production losses, forced trade restrictions, and costs associated with treatment and control. The United States is the world's top producer of beef for domestic and export use and the world's third-largest producer and consumer of pork and pork products; it has also recently been either the world's largest or second largest exporter of pork and pork products. Understanding the routes of introduction into the United States and the potential economic impact of each pathogen are crucial to (a) allocate resources to prevent routes of introduction that are believed to be more probable, (b) evaluate cost and efficacy of control methods and (c) ensure that protections are enacted to minimize impact to the most vulnerable industries. With two scoping literature reviews, pulled from global data, this study assesses the risk posed by each disease in the event of a viral introduction into the United States and illustrates what is known about the economic costs and losses associated with an outbreak.
Collapse
Affiliation(s)
- Vienna R Brown
- National Feral Swine Damage Management Program, United States Department of Agriculture, Animal and Plant Health Inspection Service, Fort Collins, CO, USA
| | - Ryan S Miller
- Center for Epidemiology and Animal Health, United States Department of Agriculture, Animal and Plant Health Inspection Service, Veterinary Services, Fort Collins, CO, USA
| | - Sophie C McKee
- National Feral Swine Damage Management Program, United States Department of Agriculture, Animal and Plant Health Inspection Service, Fort Collins, CO, USA.,Department of Economics, Colorado State University, Fort Collins, CO, USA
| | - Karina H Ernst
- National Feral Swine Damage Management Program, United States Department of Agriculture, Animal and Plant Health Inspection Service, Fort Collins, CO, USA.,Department of Economics, Colorado State University, Fort Collins, CO, USA
| | - Nicole M Didero
- National Feral Swine Damage Management Program, United States Department of Agriculture, Animal and Plant Health Inspection Service, Fort Collins, CO, USA.,Department of Economics, Colorado State University, Fort Collins, CO, USA
| | - Rachel M Maison
- Department of Biomedical Sciences, Colorado State University, Fort Collins, CO, USA
| | - Meredith J Grady
- Human Dimensions of Natural Resources Department, Colorado State University, Fort Collins, CO, USA
| | - Stephanie A Shwiff
- National Wildlife Research Center, United States Department of Agriculture, Animal and Plant Health Inspection Service, Fort Collins, CO, USA
| |
Collapse
|
10
|
Shi H, Li H, Zhang Y, Yang L, Hu Y, Wang Z, Duan L, Leng C, Yan B, Yao L. Genetic Diversity of Bovine Pestiviruses Detected in Backyard Cattle Farms Between 2014 and 2019 in Henan Province, China. Front Vet Sci 2020; 7:197. [PMID: 32363203 PMCID: PMC7181229 DOI: 10.3389/fvets.2020.00197] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Accepted: 03/25/2020] [Indexed: 11/13/2022] Open
Abstract
Bovine pestiviruses include Pestivirus A (BVDV-1), Pestivirus B (BVDV-2), and Pestivirus H, which was originally called HoBi-like pestivirus. We conducted an epidemiological investigation for pestiviruses circulating in backyard cattle farms in central China. RT-PCR assays and sequences analysis were conducted on 54 nasal swabs, 26 serum samples, and three lung samples from cattle with respiratory infections and identified 29 pestivirus strains, including 24 Pestivirus A and five Pestivirus H strains. Phylogenetic analysis based on partial 5'-UTR and Npro sequences showed that the genotypes of 24 Pestivirus A strains included Pestivirus A 1b (six isolates), Pestivirus A 1m (six isolates), Pestivirus A 1q (two isolates), Pestivirus A 1u (one isolates), and Pestivirus A 1o (nine isolates, a putative new sub-genotype). In addition, a single Pestivirus H agenotype included all five Pestivirus H strains. This study revealed extensive genetic variations within bovine pestivirus isolates derived from cattle in backyard farms in Central China, and this epidemiological information improves our understanding of the epidemics of bovine Pestiviruses, as well as will be useful in designing and evaluating diagnostic methods and developing more effective vaccines.
Collapse
Affiliation(s)
- Hongfei Shi
- Henan Provincial Engineering Laboratory of Insects Bio-reactor, Henan Provincal Engineering and Technology Center of Health Products for Livestock and Poultry, China-UK-NYNU-RRes Joint Libratory of Insect Biology, Nanyang Normal University, Nanyang, China
| | - Huan Li
- Henan Provincial Engineering Laboratory of Insects Bio-reactor, Henan Provincal Engineering and Technology Center of Health Products for Livestock and Poultry, China-UK-NYNU-RRes Joint Libratory of Insect Biology, Nanyang Normal University, Nanyang, China
| | - Yang Zhang
- Henan Provincial Engineering Laboratory of Insects Bio-reactor, Henan Provincal Engineering and Technology Center of Health Products for Livestock and Poultry, China-UK-NYNU-RRes Joint Libratory of Insect Biology, Nanyang Normal University, Nanyang, China
| | - Lulu Yang
- Henan Provincial Engineering Laboratory of Insects Bio-reactor, Henan Provincal Engineering and Technology Center of Health Products for Livestock and Poultry, China-UK-NYNU-RRes Joint Libratory of Insect Biology, Nanyang Normal University, Nanyang, China
| | - Yun Hu
- Henan Provincial Engineering Laboratory of Insects Bio-reactor, Henan Provincal Engineering and Technology Center of Health Products for Livestock and Poultry, China-UK-NYNU-RRes Joint Libratory of Insect Biology, Nanyang Normal University, Nanyang, China
| | - Zhicheng Wang
- Henan Provincial Engineering Laboratory of Insects Bio-reactor, Henan Provincal Engineering and Technology Center of Health Products for Livestock and Poultry, China-UK-NYNU-RRes Joint Libratory of Insect Biology, Nanyang Normal University, Nanyang, China
| | - Lisha Duan
- Henan Provincial Engineering Laboratory of Insects Bio-reactor, Henan Provincal Engineering and Technology Center of Health Products for Livestock and Poultry, China-UK-NYNU-RRes Joint Libratory of Insect Biology, Nanyang Normal University, Nanyang, China
| | - Chaoliang Leng
- Henan Provincial Engineering Laboratory of Insects Bio-reactor, Henan Provincal Engineering and Technology Center of Health Products for Livestock and Poultry, China-UK-NYNU-RRes Joint Libratory of Insect Biology, Nanyang Normal University, Nanyang, China
| | - Baolong Yan
- Department of Parasitology, School of Basic Medical Sciences, Wenzhou Medical University, Wenzhou, China
| | - Lunguang Yao
- Henan Provincal Engineering and Technology Center of Health Products for Livestock and Poultry, Key Laboratory of Ecological Security and Collaborative Innovation Centre of Water Security for Water Source Region of Mid-line of South-to-North Diversion Project of Henan Province, School of Agricultural Engineering, Nanyang Normal University, Nanyang, China
| |
Collapse
|
11
|
Manyweathers J, Maru Y, Hayes L, Loechel B, Kruger H, Mankad A, Xie G, Woodgate R, Hernandez-Jover M. Understanding the vulnerability of beef producers in Australia to an FMD outbreak using a Bayesian Network predictive model. Prev Vet Med 2019; 175:104872. [PMID: 31981953 DOI: 10.1016/j.prevetmed.2019.104872] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 11/22/2019] [Accepted: 12/17/2019] [Indexed: 10/25/2022]
Abstract
Effective and adaptable biosecurity and surveillance systems are crucial for maintaining and increasing Australia's competitive advantages in international markets, and for the production of high quality, safe animal products. These systems are continuously strengthened by ongoing government and industry investment. However, a better understanding of evolving disease risks and the country's capacity to respond to these risks is needed. This study developed a vulnerability framework based on characteristics and behaviours of livestock producers that impact exposure and response capacity to an emergency animal disease (EAD) outbreak among beef producers in Australia, with a focus on foot and mouth disease (FMD). This framework articulated producer vulnerability typologies to better inform surveillance resource allocation and future research direction. A cross-sectional study of beef producers in Australia was conducted to gather information on producers' demographics, husbandry characteristics, biosecurity and animal health management practices and beliefs, including those specific to FMD risk and response capacity. A Bayesian Network (BN) model was developed from the vulnerability framework, to investigate the complex interrelationships between variables and identify producer typologies. A total of 375 usable responses were obtained from the cross-sectional study. Regarding EAD exposure, producers implemented appropriate biosecurity practices for incoming stock, such as isolation (72.0 %), inspection for disease (88.7 %) and the use of vendor declarations (78.5 %); however, other biosecurity practices were limited, such as restriction of visitor access, visitor biosecurity requirements or feral animal control. In relation to response capacity, a moderate uptake of practices was observed. Whilst daily or weekly visual inspection of animals was reported by most producers (90.1 %), physical inspection was less frequent. Most producers would call a private veterinarian in response to unusual signs of disease in their cattle; however, over 40 % of producers did not cite calling a government veterinarian as a priority action. Most producers believe an FMD outbreak would have extremely serious consequences; however, their level of concern was moderate and their confidence in identifying FMD symptoms was low. The BN analysis identified six vulnerability typologies, with three levels of exposure (high, moderate, low) and two levels of response capacity (high, low), as described by producer demographics and practices. The model identified property size, number of cattle and exposure variables as the most influential to the overall producer vulnerability. Results from this study can inform how to best use current biosecurity and surveillance resources and identify where opportunities exist for improving Australia's preparedness for future EAD incursions.
Collapse
Affiliation(s)
- Jennifer Manyweathers
- Graham Centre for Agricultural Innovation (NSW Department of Primary Industries and Charles Sturt University), Wagga Wagga, NSW 2678, Australia.
| | - Yiheyis Maru
- Commonwealth Scientific and Industrial Research Organisation, Canberra, ACT 2601, Australia
| | - Lynne Hayes
- School of Animal and Veterinary Sciences, Charles Sturt University, Wagga Wagga, NSW 2678, Australia
| | - Barton Loechel
- Commonwealth Scientific and Industrial Research Organisation, Brisbane QLD 4001, Australia
| | - Heleen Kruger
- Australian Bureau of Agricultural and Resource Economics and Science, Canberra ACT 2601, Australia
| | - Aditi Mankad
- Commonwealth Scientific and Industrial Research Organisation, Brisbane QLD 4001, Australia
| | - Gang Xie
- Quantitative Consulting Unit, Charles Sturt University, Wagga Wagga, NSW 2678, Australia
| | - Rob Woodgate
- Graham Centre for Agricultural Innovation (NSW Department of Primary Industries and Charles Sturt University), Wagga Wagga, NSW 2678, Australia; School of Animal and Veterinary Sciences, Charles Sturt University, Wagga Wagga, NSW 2678, Australia
| | - Marta Hernandez-Jover
- Graham Centre for Agricultural Innovation (NSW Department of Primary Industries and Charles Sturt University), Wagga Wagga, NSW 2678, Australia; School of Animal and Veterinary Sciences, Charles Sturt University, Wagga Wagga, NSW 2678, Australia
| |
Collapse
|
12
|
Understanding animal health communication networks among smallholder livestock producers in Australia using stakeholder analysis. Prev Vet Med 2017; 144:89-101. [DOI: 10.1016/j.prevetmed.2017.05.026] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2017] [Revised: 05/18/2017] [Accepted: 05/31/2017] [Indexed: 11/17/2022]
|
13
|
Herrera-Ibatá DM, Martínez-López B, Quijada D, Burton K, Mur L. Quantitative approach for the risk assessment of African swine fever and Classical swine fever introduction into the United States through legal imports of pigs and swine products. PLoS One 2017; 12:e0182850. [PMID: 28797058 PMCID: PMC5552331 DOI: 10.1371/journal.pone.0182850] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2017] [Accepted: 07/25/2017] [Indexed: 11/18/2022] Open
Abstract
The US livestock safety strongly depends on its capacity to prevent the introduction of Transboundary Animal Diseases (TADs). Therefore, accurate and updated information on the location and origin of those potential TADs risks is essential, so preventive measures as market restrictions can be put on place. The objective of the present study was to evaluate the current risk of African swine fever (ASF) and Classical swine fever (CSF) introduction into the US through the legal importations of live pigs and swine products using a quantitative approach that could be later applied to other risks. Four quantitative stochastic risk assessment models were developed to estimate the monthly probabilities of ASF and CSF release into the US, and the exposure of susceptible populations (domestic and feral swine) to these introductions at state level. The results suggest a low annual probability of either ASF or CSF introduction into the US, by any of the analyzed pathways (5.5*10-3). Being the probability of introduction through legal imports of live pigs (1.8*10-3 for ASF, and 2.5*10-3 for CSF) higher than the risk of legally imported swine products (8.90*10-4 for ASF, and 1.56*10-3 for CSF). This could be caused due to the low probability of exposure associated with this type of commodity (products). The risk of feral pigs accessing to swine products discarded in landfills was slightly higher than the potential exposure of domestic pigs through swill feeding. The identification of the months at highest risk, the origin of the higher risk imports, and the location of the US states most vulnerable to those introductions (Iowa, Minnesota and Wisconsin for live swine and California, Florida and Texas for swine products), is valuable information that would help to design prevention, risk-mitigation and early-detection strategies that would help to minimize the catastrophic consequences of potential ASF/CSF introductions into the US.
Collapse
Affiliation(s)
- Diana María Herrera-Ibatá
- Department of Diagnostic Medicine/Pathobiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, United States of America
| | - Beatriz Martínez-López
- Center for Animal Disease Modelling and Surveillance (CADMS), University of California Davis, Davis, CA, United States of America
| | - Darla Quijada
- National Agricultural Biosecurity Center, Kansas State University, Manhattan, KS, United States of America
| | - Kenneth Burton
- National Agricultural Biosecurity Center, Kansas State University, Manhattan, KS, United States of America
| | - Lina Mur
- Department of Diagnostic Medicine/Pathobiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, United States of America
- * E-mail:
| |
Collapse
|