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Dias M, Gomes B, Pena P, Cervantes R, Beswick A, Duchaine C, Kolk A, Madsen AM, Oppliger A, Pogner C, Duquenne P, Wouters IM, Crook B, Viegas C. Filling the knowledge gap: Scoping review regarding sampling methods, assays, and further requirements to assess airborne viruses. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 946:174016. [PMID: 38908595 DOI: 10.1016/j.scitotenv.2024.174016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Revised: 06/12/2024] [Accepted: 06/13/2024] [Indexed: 06/24/2024]
Abstract
Assessment of occupational exposure to viruses is crucial to identify virus reservoirs and sources of dissemination at an early stage and to help prevent spread between employees and to the general population. Measuring workers' exposure can facilitate assessment of the effectiveness of protective and mitigation measures in place. The aim of this scoping review is to give an overview of available methods and those already implemented for airborne virus' exposure assessment in different occupational and indoor environments. The results retrieved from the different studies may contribute to the setting of future standards and guidelines to ensure a reliable risk characterization in the occupational environments crucial for the implementation of effective control measures. The search aimed at selecting studies between January 1st 2010 and June 30th 2023 in the selected databases. Fifty papers on virus exposure assessment fitted the eligibility criteria and were selected for data extraction. Overall, this study identified gaps in knowledge regarding virus assessment and pinpointed the needs for further research. Several discrepancies were found (transport temperatures, elution steps, …), as well as a lack of publication of important data related to the exposure conditions (contextual information). With the available information, it is impossible to compare results between studies employing different methods, and even if the same methods are used, different conclusions/recommendations based on the expert judgment have been reported due to the lack of consensus in the contextual information retrieved and/or data interpretation. Future research on the field targeting sampling methods and in the laboratory regarding the assays to employ should be developed bearing in mind the different goals of the assessment.
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Affiliation(s)
- Marta Dias
- H&TRC - Health & Technology Research Center, ESTeSL - Escola Superior de Tecnologia e Saúde, Instituto Politécnico de Lisboa, Portugal; NOVA National School of Public Health, Public Health Research Centre, Comprehensive Health Research Center, CHRC, REAL, CCAL, NOVA University Lisbon, Lisbon, Portugal
| | - Bianca Gomes
- H&TRC - Health & Technology Research Center, ESTeSL - Escola Superior de Tecnologia e Saúde, Instituto Politécnico de Lisboa, Portugal; CE3C-Center for Ecology, Evolution and Environmental Change, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisbon, Portugal
| | - Pedro Pena
- H&TRC - Health & Technology Research Center, ESTeSL - Escola Superior de Tecnologia e Saúde, Instituto Politécnico de Lisboa, Portugal; NOVA National School of Public Health, Public Health Research Centre, Comprehensive Health Research Center, CHRC, REAL, CCAL, NOVA University Lisbon, Lisbon, Portugal
| | - Renata Cervantes
- H&TRC - Health & Technology Research Center, ESTeSL - Escola Superior de Tecnologia e Saúde, Instituto Politécnico de Lisboa, Portugal; NOVA National School of Public Health, Public Health Research Centre, Comprehensive Health Research Center, CHRC, REAL, CCAL, NOVA University Lisbon, Lisbon, Portugal
| | - Alan Beswick
- Health and Safety Executive Science and Research Centre, Buxton SK17 9JN, UK
| | - Caroline Duchaine
- Département de biochimie, microbiologie et bio-informatique, Université Laval, Québec, Canada
| | - Annette Kolk
- Institute for Occupational Safety and Health of the German Social Accident Insurance, Alte Heerstraße 111, 53757 Sankt Augustin, Germany
| | - Anne Mette Madsen
- National Research Centre for the Working Environment, Lersø Parkallé 105, 2100 Copenhagen Ø, Denmark
| | | | | | | | - Inge M Wouters
- Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, the Netherlands
| | - Brian Crook
- Health and Safety Executive Science and Research Centre, Buxton SK17 9JN, UK
| | - Carla Viegas
- H&TRC - Health & Technology Research Center, ESTeSL - Escola Superior de Tecnologia e Saúde, Instituto Politécnico de Lisboa, Portugal; NOVA National School of Public Health, Public Health Research Centre, Comprehensive Health Research Center, CHRC, REAL, CCAL, NOVA University Lisbon, Lisbon, Portugal.
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2
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Alberts F, Berke O, Maboni G, Petukhova T, Poljak Z. Utilizing machine learning and hemagglutinin sequences to identify likely hosts of influenza H3Nx viruses. Prev Vet Med 2024; 233:106351. [PMID: 39353303 DOI: 10.1016/j.prevetmed.2024.106351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Revised: 08/16/2024] [Accepted: 09/25/2024] [Indexed: 10/04/2024]
Abstract
Influenza is a disease that represents both a public health and agricultural risk with pandemic potential. Among the subtypes of influenza A virus, H3 influenza virus can infect many avian and mammalian species and is therefore a virus of interest to human and veterinary public health. The primary goal of this study was to train and validate classifiers for the identification of the most likely host species using the hemagglutinin gene segment of H3 viruses. A five-step process was implemented, which included training four machine learning classifiers, testing the classifiers on the validation dataset, and further exploration of the best-performing model on three additional datasets. The gradient boosting machine classifier showed the highest host-classification accuracy with a 98.0 % (95 % CI [97.01, 98.73]) correct classification rate on an independent validation dataset. The classifications were further analyzed using the predicted probability score which highlighted sequences of particular interest. These sequences were both correctly and incorrectly classified sequences that showed considerable predicted probability for multiple hosts. This showed the potential of using these classifiers for rapid sequence classification and highlighting sequences of interest. Additionally, the classifiers were tested on a separate swine dataset composed of H3N2 sequences from 1998 to 2003 from the United States of America, and a separate canine dataset composed of canine H3N2 sequences of avian origin. These two datasets were utilized to look at the applications of predicted probability and host convergence over time. Lastly, the classifiers were used on an independent dataset of environmental sequences to explore the host identification of environmental sequences. The results of these classifiers show the potential for machine learning to be used as a host identification technique for viruses of unknown origin on a species-specific level.
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Affiliation(s)
- Famke Alberts
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, Ontario, Canada.
| | - Olaf Berke
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, Ontario, Canada; Centre for Public Health and Zoonoses, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, Ontario, Canada; Centre for Advancing Responsible and Ethical Artificial Intelligence, University of Guelph, 50 Stone Road East, Guelph, Ontario, Canada.
| | - Grazieli Maboni
- Athens Veterinary Diagnostic Laboratory, Department of Infectious Diseases, College of Veterinary Medicine, University of Georgia, 501 D.W.Brooks Drive Athens, GA, USA.
| | - Tatiana Petukhova
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, Ontario, Canada.
| | - Zvonimir Poljak
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, Ontario, Canada; Centre for Public Health and Zoonoses, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, Ontario, Canada.
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3
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McBride DS, Nolting JM, Nelson SW, Spurck MM, Bliss NT, Kenah E, Trock SC, Bowman AS. Shortening Duration of Swine Exhibitions to Reduce Risk for Zoonotic Transmission of Influenza A Virus. Emerg Infect Dis 2022; 28:2035-2042. [PMID: 36084650 PMCID: PMC9514346 DOI: 10.3201/eid2810.220649] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Reducing zoonotic influenza A virus (IAV) risk in the United States necessitates mitigation of IAV in exhibition swine. We evaluated the effectiveness of shortening swine exhibitions to <72 hours to reduce IAV risk. We longitudinally sampled every pig daily for the full duration of 16 county fairs during 2014-2015 (39,768 nasal wipes from 6,768 pigs). In addition, we estimated IAV prevalence at 195 fairs during 2018-2019 to test the hypothesis that <72-hour swine exhibitions would have lower IAV prevalence. In both studies, we found that shortening duration drastically reduces IAV prevalence in exhibition swine at county fairs. Reduction of viral load in the barn within a county fair is critical to reduce the risk for interspecies IAV transmission and pandemic potential. Therefore, we encourage fair organizers to shorten swine shows to protect the health of both animals and humans.
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Baig TA, Zhang M, Smith BL, King MD. Environmental Effects on Viable Virus Transport and Resuspension in Ventilation Airflow. Viruses 2022; 14:616. [PMID: 35337023 PMCID: PMC8950092 DOI: 10.3390/v14030616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 03/12/2022] [Accepted: 03/14/2022] [Indexed: 01/27/2023] Open
Abstract
To understand how SARS-CoV-2 spreads indoors, in this study bovine coronavirus was aerosolized as simulant into a plexiglass chamber with coupons of metal, wood and plastic surfaces. After aerosolization, chamber and coupon surfaces were swiped to quantify the virus concentrations using quantitative polymerase chain reaction (qPCR). Bio-layer interferometry showed stronger virus association on plastic and metal surfaces, however, higher dissociation from wood in 80% relative humidity. Virus aerosols were collected with the 100 L/min wetted wall cyclone and the 50 L/min MD8 air sampler and quantitated by qPCR. To monitor the effect of the ventilation on the virus movement, PRD1 bacteriophages as virus simulants were disseminated in a ¾ scale air-conditioned hospital test room with twelve PM2.5 samplers at 15 L/min. Higher virus concentrations were detected above the patient's head and near the foot of the bed with the air inlet on the ceiling above, exhaust bottom left on the wall. Based on room layout, air measurements and bioaerosol collections computational flow models were created to visualize the movement of the virus in the room airflow. The addition of air curtain at the door minimized virus concentration while having the inlet and exhaust on the ceiling decreased overall aerosol concentration. Controlled laboratory experiments were conducted in a plexiglass chamber to gain more insight into the fundamental behavior of aerosolized SARS-CoV-2 and understand its fate and transport in the ambient environment of the hospital room.
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Affiliation(s)
| | | | | | - Maria D. King
- Aerosol Technology Laboratory, Biological & Agricultural Engineering Department, Texas A&M University, College Station, TX 77843, USA; (T.A.B.); (M.Z.); (B.L.S.)
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Chen X, Wang W, Qin Y, Zou J, Yu H. Global epidemiology of human infections with variant influenza viruses, 1959-2021: A descriptive study. Clin Infect Dis 2022; 75:1315-1323. [PMID: 35231106 DOI: 10.1093/cid/ciac168] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND Although human case numbers of variant influenza viruses have increased worldwide, the epidemiology of human cases and human-to-human transmissibility of different variant viruses remain uncertain. METHODS We used descriptive statistics to summarize the epidemiologic characteristics of variant virus infections. The hospitalization rate, case-fatality and hospitalization-fatality risks were used to assess disease severity. Transmissibility of variant viruses between humans was determined by the effective reproductive number (Re) and probability of infection following exposure to human cases. RESULTS We identified 707 cases of variant viruses from 1959-2021, and their spatiotemporal/demographic characteristics changed across subtypes. The clinical severity of cases of variant viruses was generally mild; cases older than 18 years with underlying conditions were associated with hospitalization. Of 69 clusters of human infections with variant viruses (median cluster size: 2), the upper limit of Re was 0.09 (H1N1v, H1N2v and H3N2v: 0.20 vs. 0.18 vs. 0.05), while it was not significantly different from the pooled estimates for avian influenza A(H7N9) and A(H5N1) viruses (0.10). Moreover, contacts of H5N1 cases (15.7%) had a significantly higher probability of infection than contacts of individuals with H7N9 (4.2%) and variant virus infections (4.2-7.2%). CONCLUSIONS The epidemiology of cases of variant viruses varied across time periods, geographical regions and subtypes during 1959-2021. The transmissibility of different variant viruses between humans remains limited. However, given the continuous evolution of viruses and the rapidly evolving epidemiology of cases of variant viruses, improving the surveillance systems for human variant virus infections is needed worldwide.
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Affiliation(s)
- Xinghui Chen
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Wei Wang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Ying Qin
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Junyi Zou
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Hongjie Yu
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
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6
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Cryptocurrency as Epidemiologically Safe Means of Transactions: Diminishing Risk of SARS-CoV-2 Spread. MATHEMATICS 2021. [DOI: 10.3390/math9243263] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
In comparison with other respiratory viruses, the current COVID-19 pandemic’s rapid seizing the world can be attributed to indirect (contact) way of transmission of SARS-CoV-2 virus in addition to the regular airborne way. A significant part of indirect transmission is made through cash bank notes. SARS-CoV-2 remains on cash paper money for period around four times larger than influenza A virus and is absorbed by cash notes two and a half times more effectively than influenza A (our model). During the pandemic, cryptocurrencies have gained attractiveness as an “epidemiologically safe” means of transactions. On the basis of the authors’ gallop polls performed online with social networks users in 44 countries in 2020–2021 (the total number of clear responses after the set repair 32,115), around 14.7% of surveyed participants engaged in cryptocurrency-based transactions during the pandemic. This may be one of the reasons of significant rise of cryptocurrencies rates since mid-March 2020 till the end of 2021. The paper discusses the reasons for cryptocurrency attractiveness during the COVID-19 pandemic. Among them, there are fear of SARS-CoV-2 spread via cash contacts and the ability of the general population to mine cryptocurrencies. The article also provides a breakdown of the polled audience profile to determine the nationalities that have maximal level of trust to saving and transacting money as cryptocurrencies.
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Kanji JN, Pabbaraju K, Croxen M, Detmer S, Bastien N, Li Y, Majer A, Keshwani H, Zelyas N, Achebe I, Jones C, Rutz M, Jacobs A, Lehman K, Hinshaw D, Tipples G. Characterization of Swine Influenza A(H1N2) Variant, Alberta, Canada, 2020. Emerg Infect Dis 2021; 27:3045-3051. [PMID: 34808085 PMCID: PMC8632177 DOI: 10.3201/eid2712.210298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Influenza strains circulating among swine populations can cause outbreaks in humans. In October 2020, we detected a variant influenza A subtype H1N2 of swine origin in a person in Alberta, Canada. We initiated a public health, veterinary, and laboratory investigation to identify the source of the infection and determine whether it had spread. We identified the probable source as a local pig farm where a household contact of the index patient worked. Phylogenetic analysis revealed that the isolate closely resembled strains found at that farm in 2017. Retrospective and prospective surveillance using molecular testing did not identify any secondary cases among 1,532 persons tested in the surrounding area. Quick collaboration between human and veterinary public health practitioners in this case enabled a rapid response to a potential outbreak.
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Aerosol Transmission from Infected Swine to Ferrets of an H3N2 Virus Collected from an Agricultural Fair and Associated with Human Variant Infections. J Virol 2020; 94:JVI.01009-20. [PMID: 32522849 DOI: 10.1128/jvi.01009-20] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Accepted: 05/28/2020] [Indexed: 12/14/2022] Open
Abstract
Influenza A viruses (IAV) sporadically transmit from swine to humans, typically associated with agricultural fairs in the United States. A human seasonal H3 virus from the 2010-2011 IAV season was introduced into the U.S. swine population and termed H3.2010.1 to differentiate it from the previous swine H3 virus. This H3N2 lineage became widespread in the U.S. commercial swine population, subsequently spilling over into exhibition swine, and caused a majority of H3N2 variant (H3N2v) cases in humans in 2016 and 2017. A cluster of human H3N2v cases were reported at an agricultural fair in 2017 in Ohio, where 2010.1 H3N2 IAV was concurrently detected in exhibition swine. Genomic analysis showed that the swine and human isolates were nearly identical. In this study, we evaluated the propensity of a 2010.1 H3N2 IAV (A/swine/Ohio/A01354299/2017 [sw/OH/2017]) isolated from a pig in the agricultural fair outbreak to replicate in ferrets and transmit from swine to ferret. sw/OH/2017 displayed robust replication in the ferret respiratory tract, causing slight fever and moderate weight loss. Further, sw/OH/2017 was capable of efficient respiratory droplet transmission from infected pigs to contact ferrets. These findings establish a model for evaluating the propensity of swine IAV to transmit from pig to ferret as a measure of risk to the human population. The identification of higher-risk swine strains can then be targeted for control measures to limit the dissemination at human-swine interfaces to reduce the risk of zoonotic infections and to inform pandemic planning.IMPORTANCE A recently emerged lineage of human-like H3N2 (H3.2010.1) influenza A virus (IAV) from swine has been frequently detected in commercial and exhibition swine in recent years and has been associated with H3N2 variant cases in humans from 2016 and 2017. To demonstrate a model for characterizing the potential for zoonotic transmission associated with swine IAV, we performed an in vivo study of transmission between pigs infected with an H3.2010.1 H3N2 IAV and aerosol contact ferrets. The efficient interspecies transmission demonstrated for the H3.2010.1 IAV in swine emphasizes the need for further characterization of viruses circulating at the swine-human interface for transmission potential prior to human spillover and the development and implementation of more robust vaccines and control strategies to mitigate human exposure to higher-risk swine strains.
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Li Y, Edwards J, Huang B, Shen C, Cai C, Wang Y, Zhang G, Robertson I. Risk of zoonotic transmission of swine influenza at the human-pig interface in Guangdong Province, China. Zoonoses Public Health 2020; 67:607-616. [PMID: 32506781 DOI: 10.1111/zph.12723] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Revised: 03/24/2020] [Accepted: 04/25/2020] [Indexed: 12/27/2022]
Abstract
A cross-sectional survey was conducted from 2015 to 2018 to assess the risk of zoonotic influenza to humans at the human-pig interface in Guangdong Province, south China. One hundred and fifty-three pig farmers, 21 pig traders and 16 pig trade workers were recruited using convenience sampling and surveyed at local pig farms, live pig markets and slaughterhouses, respectively. Questionnaires were administered to collect information on the biosecurity and trading practices adopted and their knowledge and beliefs about swine influenza (SI). Most (12 of 16) trade workers said they would enter piggeries to collect pigs and only six of 11 said they were always asked to go through an on-farm disinfection procedure before entry. Only 33.7% of the interviewees believed that SI could infect humans, although pig farmers were more likely to believe this than traders and trade workers (p < .01). Several unsafe practices were reported by interviewees. 'Having vaccination against seasonal flu' (OR = 3.05, 95% CI: 1.19-8.93), 'Believe that SI can cause death in pigs' (no/yes: OR = 8.69, 95% CI: 2.71-36.57; not sure/yes: OR = 4.46, 95% CI: 1.63-14.63) and 'Keep on working when getting mild flu symptoms' (OR = 3.80, 95% CI: 1.38-11.46) were significantly and positively correlated to 'lacking awareness of the zoonotic risk of SI'. 'Lacking awareness of the zoonotic risk of SI' (OR = 3.19, 95% CI: 1.67-6.21), 'Keep on working when getting mild flu symptoms' (OR = 3.59, 95% CI: 1.57-8.63) and 'Don't know SI as a pig disease' (OR = 3.48, 95% CI: 1.02-16.45) were significantly and positively correlated to 'not using personal protective equipment when contacting pigs'. The findings of this study would benefit risk mitigation against potential pandemic SI threats in the human-pig interface in China.
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Affiliation(s)
- Yin Li
- School of Veterinary Medicine, Murdoch University, Perth, WA, Australia.,China Animal Health and Epidemiology Center, Qingdao, China
| | - John Edwards
- School of Veterinary Medicine, Murdoch University, Perth, WA, Australia.,China Animal Health and Epidemiology Center, Qingdao, China
| | - Baoxu Huang
- School of Veterinary Medicine, Murdoch University, Perth, WA, Australia.,China Animal Health and Epidemiology Center, Qingdao, China
| | - Chaojian Shen
- China Animal Health and Epidemiology Center, Qingdao, China
| | - Chang Cai
- School of Veterinary Medicine, Murdoch University, Perth, WA, Australia
| | - Youming Wang
- China Animal Health and Epidemiology Center, Qingdao, China
| | - Guihong Zhang
- South China Agriculture University, Guangzhou, China
| | - Ian Robertson
- School of Veterinary Medicine, Murdoch University, Perth, WA, Australia.,Hubei International Scientific and Technological Cooperation Base of Veterinary Epidemiology, Key Laboratory of Preventive Veterinary Medicine in Hubei Province, Hubei Province, China
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10
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Li Y, Huang B, Shen C, Cai C, Wang Y, Edwards J, Zhang G, Robertson ID. Pig trade networks through live pig markets in Guangdong Province, China. Transbound Emerg Dis 2020; 67:1315-1329. [PMID: 31903722 PMCID: PMC7228257 DOI: 10.1111/tbed.13472] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2019] [Revised: 12/27/2019] [Accepted: 12/27/2019] [Indexed: 11/28/2022]
Abstract
This study used social network analysis to investigate the indirect contact network between counties through the movement of live pigs through four wholesale live pig markets in Guangdong Province, China. All 14,118 trade records for January and June 2016 were collected from the markets and the patterns of pig trade in these markets analysed. Maps were developed to show the movement pathways. Evaluating the network between source counties was the primary objective of this study. A 1‐mode network was developed. Characteristics of the trading network were explored, and the degree, betweenness and closeness were calculated for each source county. Models were developed to compare the impacts of different disease control strategies on the potential magnitude of an epidemic spreading through this network. The results show that pigs from 151 counties were delivered to the four wholesale live pig markets in January and/or June 2016. More batches (truckloads of pigs sourced from one or more piggeries) were traded in these markets in January (8,001) than in June 2016 (6,117). The pigs were predominantly sourced from counties inside Guangdong Province (90%), along with counties in Hunan, Guangxi, Jiangxi, Fujian and Henan provinces. The major source counties (46 in total) contributed 94% of the total batches during the two‐month study period. Pigs were sourced from piggeries located 10 to 1,417 km from the markets. The distribution of the nodes' degrees in both January and June indicates a free‐scale network property, and the network in January had a higher clustering coefficient (0.54 vs. 0.39) and a shorter average pathway length (1.91 vs. 2.06) than that in June. The most connected counties of the network were in the central, northern and western regions of Guangdong Province. Compared with randomly removing counties from the network, eliminating counties with higher betweenness, degree or closeness resulted in a greater reduction of the magnitude of a potential epidemic. The findings of this study can be used to inform targeted control interventions for disease spread through this live pig market trade network in south China.
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Affiliation(s)
- Yin Li
- School of Veterinary Medicine, Murdoch University, Perth, WA, Australia.,China Animal Health and Epidemiology Center, Qingdao, China
| | - Baoxu Huang
- School of Veterinary Medicine, Murdoch University, Perth, WA, Australia.,China Animal Health and Epidemiology Center, Qingdao, China
| | - Chaojian Shen
- China Animal Health and Epidemiology Center, Qingdao, China
| | - Chang Cai
- Research and Innovation Office, Murdoch University, Murdoch, WA, Australia.,China Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology, Zhejiang Agricultural and Forestry University, Hangzhou, China
| | - Youming Wang
- China Animal Health and Epidemiology Center, Qingdao, China
| | - John Edwards
- School of Veterinary Medicine, Murdoch University, Perth, WA, Australia.,China Animal Health and Epidemiology Center, Qingdao, China
| | - Guihong Zhang
- South China Agriculture University, Guangzhou, China
| | - Ian D Robertson
- School of Veterinary Medicine, Murdoch University, Perth, WA, Australia.,China-Australia Joint Research and Training Centre for Veterinary Epidemiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
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11
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Li Y, Edwards J, Wang Y, Zhang G, Cai C, Zhao M, Huang B, Robertson ID. Prevalence, distribution and risk factors of farmer reported swine influenza infection in Guangdong Province, China. Prev Vet Med 2019; 167:1-8. [PMID: 31027710 DOI: 10.1016/j.prevetmed.2019.03.011] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Revised: 02/12/2019] [Accepted: 03/13/2019] [Indexed: 01/27/2023]
Abstract
A cross-sectional study was undertaken to better understand the husbandry, management and biosecurity practices of pig farms in Guangdong Province (GD), China to identify risk factors for farmer reported swine influenza (SI) on their farms. Questionnaires were administered to 153 owners/managers of piggeries (average of 7 from each of the 21 prefectures in GD). Univariable and multivariable logistic regression analyses were used to identify risk factors for farmer reported SI in piggeries during the six months preceding the questionnaire administration. The ability of wild birds to enter piggeries (OR 2.50, 95% CI: 1.01-6.16), the presence of poultry on a pig-farm (OR 3.24, 95% CI: 1.52-6.94) and no biosecurity measures applied to workers before entry to the piggery (OR 2.65, 95% CI: 1.04-6.78) were found to increase the likelihood of SI being reported by farmers in a multivariable logistic regression model. The findings of this study highlight the importance of understanding the local pig industry and the practices adopted when developing control measures to reduce the risk of SI to pig farms.
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Affiliation(s)
- Y Li
- China Animal Health and Epidemiology Center, Qingdao, Shandong, PR China; School of Veterinary Medicine, Murdoch University, Perth, WA, Australia.
| | - J Edwards
- China Animal Health and Epidemiology Center, Qingdao, Shandong, PR China; School of Veterinary Medicine, Murdoch University, Perth, WA, Australia
| | - Y Wang
- China Animal Health and Epidemiology Center, Qingdao, Shandong, PR China
| | - G Zhang
- South China Agriculture University, Guangzhou, Guangdong, PR China
| | - C Cai
- School of Veterinary Medicine, Murdoch University, Perth, WA, Australia
| | - M Zhao
- Department of Agriculture of Guangdong Province, Guangzhou, Guangdong, PR China
| | - B Huang
- China Animal Health and Epidemiology Center, Qingdao, Shandong, PR China
| | - I D Robertson
- School of Veterinary Medicine, Murdoch University, Perth, WA, Australia; China-Australia Joint Research and Training Center for Veterinary Epidemiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, Hubei, PR China
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12
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Prost K, Kloeze H, Mukhi S, Bozek K, Poljak Z, Mubareka S. Bioaerosol and surface sampling for the surveillance of influenza A virus in swine. Transbound Emerg Dis 2019; 66:1210-1217. [PMID: 30715792 DOI: 10.1111/tbed.13139] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Revised: 12/19/2018] [Accepted: 01/23/2019] [Indexed: 12/15/2022]
Abstract
Influenza A virus in swine is of significant importance to human and veterinary public health. Environmental sampling techniques that prove practical would enhance surveillance for influenza viruses in swine. The primary objective of this study was to demonstrate the feasibility of bioaerosol and surface sampling for the detection of influenza virus in swine barns with a secondary objective of piloting a mobile application for data collection. Sampling was conducted at a large swine operation between July 2016 and August 2017. Swine oral fluids and surface swabs were collected from multiple rooms. Room-level air samples were collected using four bioaerosol samplers: a low volume polytetrafluoroethylene (PTFE) filter sampler, the National Institute for Occupational Safety and Health's low volume cyclone sampler, a 2-stage Andersen impactor and/or one high volume cyclonic sampler. Samples were analysed using quantitative RT-PCR. Data and results were reported using a mobile data application. Eighty-nine composite oral fluid samples, 70 surface swabs and 122 bioaerosol samples were analysed. Detection rates for influenza virus RNA in swine barn samples were 71.1% for oral fluids, 70.8% for surface swabs and 71.1% for the PTFE sampler. Analysis revealed a statistically significant relationship between the results of the PTFE sampler and the surface swabs with oral fluid results (p < 0.001 and p < 0.01 respectively). In addition, both the PTFE sampler (p < 0.01) and surface swabs (p = 0.03) significantly correlated with, and predicted oral fluid results. Bioaerosol sampling using PTFE samplers is an effective hands-off approach for detecting influenza virus activity among swine. Further study is required for the implementation of this approach for surveillance and risk assessment of circulating influenza viruses of swine origin. In addition, mobile data collection stands to be an invaluable tool in the field by allowing secure, real-time reporting of sample collection and results.
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Affiliation(s)
- Karren Prost
- Sunnybrook Research Institute, Toronto, ON, Canada
| | - Harold Kloeze
- Canadian Network for Public Health Intelligence, National Microbiology Laboratory, Winnipeg, MB, Canada
| | - Shamir Mukhi
- Canadian Network for Public Health Intelligence, National Microbiology Laboratory, Winnipeg, MB, Canada
| | - Katie Bozek
- Sunnybrook Research Institute, Toronto, ON, Canada
| | - Zvonimir Poljak
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | - Samira Mubareka
- Sunnybrook Research Institute, Toronto, ON, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
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