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Kohnle L, Das T, Uddin MH, Nath SC, Mohsin MAS, Mahmud R, Biswas PK, Hoque MA, Pfeiffer DU, Fournié G. Amplification of avian influenza virus circulation along poultry marketing chains in Bangladesh: A controlled field experiment. Prev Vet Med 2024; 231:106302. [PMID: 39137554 PMCID: PMC11387981 DOI: 10.1016/j.prevetmed.2024.106302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 06/16/2024] [Accepted: 07/29/2024] [Indexed: 08/15/2024]
Abstract
The prevalence of avian influenza viruses is commonly found to increase dramatically as birds are transported from farms to live bird markets. Viral transmission dynamics along marketing chains are, however, poorly understood. To address this gap, we implemented a controlled field experiment altering chicken supply to a live bird market in Chattogram, Bangladesh. Broilers and backyard chickens traded along altered (intervention) and conventional (control) marketing chains were tested for avian influenza viruses at different time points. Upon arrival at the live bird market, the odds of detecting avian influenza viruses did not differ between control and intervention groups. However, 12 h later, intervention group odds were lower, particularly for broilers, indicating that viral shedding in live bird markets resulted partly from infections occurring during transport and trade. Curtailing avian influenza virus prevalence in live bird markets requires mitigating risk in marketing chain nodes preceding chickens' delivery at live bird markets.
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Affiliation(s)
- Lisa Kohnle
- City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong Special Administrative Region of China.
| | - Tridip Das
- Chattogram Veterinary and Animal Sciences University, Zakir Hossain Rd, Khulshi, Chattogram 4202, Bangladesh; Charles Sturt University, Boorooma Street, North Wagga, Wagga Wagga, NSW, Australia.
| | - Md Helal Uddin
- Chattogram Veterinary and Animal Sciences University, Zakir Hossain Rd, Khulshi, Chattogram 4202, Bangladesh.
| | - Sanjib Chandra Nath
- Chattogram Veterinary and Animal Sciences University, Zakir Hossain Rd, Khulshi, Chattogram 4202, Bangladesh.
| | - Md Abu Shoieb Mohsin
- Chattogram Veterinary and Animal Sciences University, Zakir Hossain Rd, Khulshi, Chattogram 4202, Bangladesh.
| | - Rashed Mahmud
- Chattogram Veterinary and Animal Sciences University, Zakir Hossain Rd, Khulshi, Chattogram 4202, Bangladesh.
| | - Paritosh Kumar Biswas
- Chattogram Veterinary and Animal Sciences University, Zakir Hossain Rd, Khulshi, Chattogram 4202, Bangladesh.
| | - Md Ahasanul Hoque
- Chattogram Veterinary and Animal Sciences University, Zakir Hossain Rd, Khulshi, Chattogram 4202, Bangladesh.
| | - Dirk Udo Pfeiffer
- City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong Special Administrative Region of China; Royal Veterinary College, Hawkshead Lane, North Mymms, London, Hertfordshire AL9 7TA, United Kingdom.
| | - Guillaume Fournié
- Royal Veterinary College, Hawkshead Lane, North Mymms, London, Hertfordshire AL9 7TA, United Kingdom; Université de Lyon, INRAE, VetAgro Sup, UMR EPIA, VetAgro Sup veterinary campus, 1, avenue Bourgelat, Marcy-l'Etoile 69280, France; Université Clermont Auvergne, INRAE, VetAgro Sup, UMR EPIA, Clermont-Auvergne-Rhône-Alpes, THEIX site, Saint Genes Champanelle, France.
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2
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Xie K, Lin B, Sun X, Zhu P, Liu C, Liu G, Cao X, Pan J, Qiu S, Yuan X, Liang M, Jiang J, Yuan L. Identification and classification of the genomes of novel microviruses in poultry slaughterhouse. Front Microbiol 2024; 15:1393153. [PMID: 38756731 PMCID: PMC11096546 DOI: 10.3389/fmicb.2024.1393153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 04/11/2024] [Indexed: 05/18/2024] Open
Abstract
Microviridae is a family of phages with circular ssDNA genomes and they are widely found in various environments and organisms. In this study, virome techniques were employed to explore potential members of Microviridae in a poultry slaughterhouse, leading to the identification of 98 novel and complete microvirus genomes. Using a similarity clustering network classification approach, these viruses were found to belong to at least 6 new subfamilies within Microviridae and 3 higher-level taxonomic units. Genome size, GC content and genome structure of these new taxa showed evident regularities, validating the rationality of our classification method. Our method can divide microviruses into about 45 additional detailed clusters, which may serve as a new standard for classifying Microviridae members. Furthermore, by addressing the scarcity of host information for microviruses, the current study significantly broadened their host range and discovered over 20 possible new hosts, including important pathogenic bacteria such as Helicobacter pylori and Vibrio cholerae, as well as different taxa demonstrated different host specificities. The findings of this study effectively expand the diversity of the Microviridae family, providing new insights for their classification and identification. Additionally, it offers a novel perspective for monitoring and controlling pathogenic microorganisms in poultry slaughterhouse environments.
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Affiliation(s)
- Keming Xie
- School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, Guangdong, China
- Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization, Ministry of Agriculture and Rural Affairs, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, Guangdong, China
| | - Benfu Lin
- Huadu District Animal Health Supervision Institution, Guangzhou, Guangdong, China
| | - Xinyu Sun
- School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, Guangdong, China
| | - Peng Zhu
- Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization, Ministry of Agriculture and Rural Affairs, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, Guangdong, China
- College of Marine Ecology and Environment, Shanghai Ocean University, Shanghai, China
| | - Chang Liu
- Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization, Ministry of Agriculture and Rural Affairs, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, Guangdong, China
| | - Guangfeng Liu
- Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization, Ministry of Agriculture and Rural Affairs, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, Guangdong, China
| | - Xudong Cao
- Department of Chemical and Biological Engineering, University of Ottawa, Ottawa, ON, Canada
| | - Jingqi Pan
- School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, Guangdong, China
| | - Suiping Qiu
- School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, Guangdong, China
| | - Xiaoqi Yuan
- School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, Guangdong, China
| | - Mengshi Liang
- School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, Guangdong, China
| | - Jingzhe Jiang
- School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, Guangdong, China
- Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization, Ministry of Agriculture and Rural Affairs, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, Guangdong, China
| | - Lihong Yuan
- School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, Guangdong, China
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3
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KADOTA C, MIYAOKA Y, KABIR MH, HAKIM H, HASAN MA, SHOHAM D, MURAKAMI H, TAKEHARA K. Evaluation of chlorine dioxide in liquid state and in gaseous state as virucidal agent against avian influenza virus and infectious bronchitis virus. J Vet Med Sci 2023; 85:1040-1046. [PMID: 37648459 PMCID: PMC10600528 DOI: 10.1292/jvms.23-0194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Accepted: 08/20/2023] [Indexed: 09/01/2023] Open
Abstract
The antiviral activity of chlorine dioxide (ClO2) in liquid (ClO2 gas dissolved liquid) and gaseous state against avian influenza virus (AIV) and infectious bronchitis virus (IBV) was evaluated. To evaluate the effect of ClO2 in liquid state, suspension tests (10 ppm) and carrier tests in dropping / wiping techniques (100 ppm) were performed. In the suspension test, virus titers were reduced below the detection limit within 15 sec after treatment, in spite of the presence of an accompanying organic matter. In the carrier test by dropping technique, AIV and IBV were reduced to below the detection limit in 1 and 3 min, respectively. Following wiping technique, no virus was detected in the wiping sheets after 30 sec of reaction. Both viruses adhering to the carriers were also reduced by 3 logs, thereby indicating that they were effectively inactivated. In addition, the effect of ClO2 gas against IBV in aerosols was evaluated. After the exposure of sprayed IBV to ClO2 gas for a few seconds, 94.2% reduction of the virus titer was observed, as compared to the pre-treatment control. Altogether, hence, ClO2 has an evident potential to be an effective disinfectant for the prevention and control of AIV and IBV infections on poultry farms.
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Affiliation(s)
- Chisaki KADOTA
- Laboratory of Animal Health, Department of Veterinary
Medicine, Faculty of Agriculture, Tokyo University of Agriculture and Technology, Tokyo,
Japan
| | - Yu MIYAOKA
- Laboratory of Animal Health, Cooperative Division of
Veterinary Sciences, Graduate School of Agriculture, Tokyo University of Agriculture and
Technology, Tokyo, Japan
| | - Md Humayun KABIR
- Laboratory of Animal Health, Cooperative Division of
Veterinary Sciences, Graduate School of Agriculture, Tokyo University of Agriculture and
Technology, Tokyo, Japan
| | - Hakimullah HAKIM
- Laboratory of Animal Health, Cooperative Division of
Veterinary Sciences, Graduate School of Agriculture, Tokyo University of Agriculture and
Technology, Tokyo, Japan
| | - Md Amirul HASAN
- Laboratory of Animal Health, Cooperative Division of
Veterinary Sciences, Graduate School of Agriculture, Tokyo University of Agriculture and
Technology, Tokyo, Japan
| | - Dany SHOHAM
- Begin-Sadat Center for Strategic Studies, Bar-Ilan
University, Ramat Gan, Israel
| | - Harumi MURAKAMI
- Laboratory of Animal Health, Department of Veterinary
Medicine, Faculty of Agriculture, Tokyo University of Agriculture and Technology, Tokyo,
Japan
- Laboratory of Animal Health, Cooperative Division of
Veterinary Sciences, Graduate School of Agriculture, Tokyo University of Agriculture and
Technology, Tokyo, Japan
| | - Kazuaki TAKEHARA
- Laboratory of Animal Health, Department of Veterinary
Medicine, Faculty of Agriculture, Tokyo University of Agriculture and Technology, Tokyo,
Japan
- Laboratory of Animal Health, Cooperative Division of
Veterinary Sciences, Graduate School of Agriculture, Tokyo University of Agriculture and
Technology, Tokyo, Japan
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Wang Z, Li H, Li Y, Wu Z, Ai H, Zhang M, Rong L, Blinov ML, Tong Q, Liu L, Sun H, Pu J, Feng W, Liu J, Sun Y. Mixed selling of different poultry species facilitates emergence of public-health-threating avian influenza viruses. Emerg Microbes Infect 2023; 12:2214255. [PMID: 37191631 DOI: 10.1080/22221751.2023.2214255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
Live poultry markets (LPMs) are regarded as hubs for avian influenza virus (AIV) transmission in poultry and are a major risk factor in human AIV infections. We performed an AIV surveillance study at a wholesale LPM, where different poultry species were sold in separate stalls, and nine retail LPMs, which received poultry from the wholesale LPM but where different poultry species were sold in one stall, in Guangdong province from 2017 to 2019. A higher AIV isolation rate was observed at the retail LPMs than the wholesale LPM. H9N2 was the dominant AIV subtype and was mainly present in chickens and quails. The genetic diversity of H9N2 viruses was greater at the retail LPMs, where a complex system of two-way transmission between different poultry species had formed. The isolated H9N2 viruses could be classed into four genotypes: G57 and the three novel genotypes, NG164, NG165, and NG166. The H9N2 AIVs isolated from chickens and quails at the wholesale LPM only belonged to the G57 and NG164 genotypes, respectively. However, the G57, NG164, and NG165 genotypes were identified in both chickens and quails at the retail LPMs. We found that the replication and transmission of the NG165 genotype were more adaptive to both poultry and mammalian models than those of its precursor genotype, NG164. Our findings revealed that mixed poultry selling at retail LPMs has increased the genetic diversity of AIVs, which might facilitate the emergence of novel viruses that threaten public health.
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Affiliation(s)
- Zhen Wang
- National Key Laboratory of Veterinary Public Health Security, Key Laboratory for Prevention and Control of Avian Influenza and Other Major Poultry Diseases and Key Laboratory of Animal Epidemiology of Ministry of Agriculture and Rural Affairs, College of Veterinary Medicine, China Agricultural University, Beijing, People's Republic of China
- State Key Laboratories of Agrobiotechnology, and Department of Microbiology and Immunology, College of Biological Science, China Agricultural University, Beijing, People's Republic of China
| | - Hongkui Li
- Liaoning Agricultural Development Service Center, Shenyang, People's Republic of China
| | - Yuhan Li
- National Key Laboratory of Veterinary Public Health Security, Key Laboratory for Prevention and Control of Avian Influenza and Other Major Poultry Diseases and Key Laboratory of Animal Epidemiology of Ministry of Agriculture and Rural Affairs, College of Veterinary Medicine, China Agricultural University, Beijing, People's Republic of China
| | - Zhuanli Wu
- National Key Laboratory of Veterinary Public Health Security, Key Laboratory for Prevention and Control of Avian Influenza and Other Major Poultry Diseases and Key Laboratory of Animal Epidemiology of Ministry of Agriculture and Rural Affairs, College of Veterinary Medicine, China Agricultural University, Beijing, People's Republic of China
| | - Hui Ai
- National Key Laboratory of Veterinary Public Health Security, Key Laboratory for Prevention and Control of Avian Influenza and Other Major Poultry Diseases and Key Laboratory of Animal Epidemiology of Ministry of Agriculture and Rural Affairs, College of Veterinary Medicine, China Agricultural University, Beijing, People's Republic of China
| | - Ming Zhang
- Department of Epidemiology and Biostatistics, University of Georgia, Athens, GA, USA
| | - Libin Rong
- Department of Mathematics, University of Florida, Gainesville, FL, USA
| | - Michael L Blinov
- Center for Cell Analysis and Modeling, University of Connecticut School of Medicine, Farmington, CT, USA
| | - Qi Tong
- National Key Laboratory of Veterinary Public Health Security, Key Laboratory for Prevention and Control of Avian Influenza and Other Major Poultry Diseases and Key Laboratory of Animal Epidemiology of Ministry of Agriculture and Rural Affairs, College of Veterinary Medicine, China Agricultural University, Beijing, People's Republic of China
| | - Litao Liu
- National Key Laboratory of Veterinary Public Health Security, Key Laboratory for Prevention and Control of Avian Influenza and Other Major Poultry Diseases and Key Laboratory of Animal Epidemiology of Ministry of Agriculture and Rural Affairs, College of Veterinary Medicine, China Agricultural University, Beijing, People's Republic of China
| | - Honglei Sun
- National Key Laboratory of Veterinary Public Health Security, Key Laboratory for Prevention and Control of Avian Influenza and Other Major Poultry Diseases and Key Laboratory of Animal Epidemiology of Ministry of Agriculture and Rural Affairs, College of Veterinary Medicine, China Agricultural University, Beijing, People's Republic of China
| | - Juan Pu
- National Key Laboratory of Veterinary Public Health Security, Key Laboratory for Prevention and Control of Avian Influenza and Other Major Poultry Diseases and Key Laboratory of Animal Epidemiology of Ministry of Agriculture and Rural Affairs, College of Veterinary Medicine, China Agricultural University, Beijing, People's Republic of China
| | - Wenhai Feng
- State Key Laboratories of Agrobiotechnology, and Department of Microbiology and Immunology, College of Biological Science, China Agricultural University, Beijing, People's Republic of China
| | - Jinhua Liu
- National Key Laboratory of Veterinary Public Health Security, Key Laboratory for Prevention and Control of Avian Influenza and Other Major Poultry Diseases and Key Laboratory of Animal Epidemiology of Ministry of Agriculture and Rural Affairs, College of Veterinary Medicine, China Agricultural University, Beijing, People's Republic of China
| | - Yipeng Sun
- National Key Laboratory of Veterinary Public Health Security, Key Laboratory for Prevention and Control of Avian Influenza and Other Major Poultry Diseases and Key Laboratory of Animal Epidemiology of Ministry of Agriculture and Rural Affairs, College of Veterinary Medicine, China Agricultural University, Beijing, People's Republic of China
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5
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Gržinić G, Piotrowicz-Cieślak A, Klimkowicz-Pawlas A, Górny RL, Ławniczek-Wałczyk A, Piechowicz L, Olkowska E, Potrykus M, Tankiewicz M, Krupka M, Siebielec G, Wolska L. Intensive poultry farming: A review of the impact on the environment and human health. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 858:160014. [PMID: 36368402 DOI: 10.1016/j.scitotenv.2022.160014] [Citation(s) in RCA: 47] [Impact Index Per Article: 47.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 10/15/2022] [Accepted: 11/03/2022] [Indexed: 06/16/2023]
Abstract
Poultry farming is one of the most efficient animal husbandry methods and it provides nutritional security to a significant number of the world population. Using modern intensive farming techniques, global production has reached 133.4 mil. t in 2020, with a steady growth each year. Such intensive growth methods however lead to a significant environmental footprint. Waste materials such as poultry litter and manure can pose a serious threat to environmental and human health, and need to be managed properly. Poultry production and waste by-products are linked to NH3, N2O and CH4 emissions, and have an impact on global greenhouse gas emissions, as well as animal and human health. Litter and manure can contain pesticide residues, microorganisms, pathogens, pharmaceuticals (antibiotics), hormones, metals, macronutrients (at improper ratios) and other pollutants which can lead to air, soil and water contamination as well as formation of antimicrobial/multidrug resistant strains of pathogens. Dust emitted from intensive poultry production operations contains feather and skin fragments, faeces, feed particles, microorganisms and other pollutants, which can adversely impact poultry health as well as the health of farm workers and nearby inhabitants. Fastidious odours are another problem that can have an adverse impact on health and quality of life of workers and surrounding population. This study discusses the current knowledge on the impact of intensive poultry farming on environmental and human health, as well as taking a look at solutions for a sustainable future.
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Affiliation(s)
- Goran Gržinić
- Department of Environmental Toxicology, Faculty of Health Sciences, Medical University of Gdansk, Dębowa Str. 23A, 80-204 Gdansk, Poland.
| | - Agnieszka Piotrowicz-Cieślak
- Department of Plant Physiology, Genetics and Biotechnology, University of Warmia and Mazury, Oczapowskiego Str. 1A, 10-719 Olsztyn, Poland
| | - Agnieszka Klimkowicz-Pawlas
- Department of Soil Science Erosion and Land Protection, Institute of Soil Science and Plant Cultivation - State Research Institute, Czartoryskich Str. 8, 24-100 Puławy, Poland
| | - Rafał L Górny
- Laboratory of Biohazards, Department of Chemical, Aerosol and Biological Hazards, Central Institute for Labour Protection - National Research Institute, Czerniakowska Str. 16, 00-701 Warsaw, Poland
| | - Anna Ławniczek-Wałczyk
- Laboratory of Biohazards, Department of Chemical, Aerosol and Biological Hazards, Central Institute for Labour Protection - National Research Institute, Czerniakowska Str. 16, 00-701 Warsaw, Poland
| | - Lidia Piechowicz
- Department of Microbiology, Faculty of Medicine, Medical University of Gdansk, Dębowa Str. 25, 80-204 Gdansk, Poland
| | - Ewa Olkowska
- Department of Environmental Toxicology, Faculty of Health Sciences, Medical University of Gdansk, Dębowa Str. 23A, 80-204 Gdansk, Poland
| | - Marta Potrykus
- Department of Environmental Toxicology, Faculty of Health Sciences, Medical University of Gdansk, Dębowa Str. 23A, 80-204 Gdansk, Poland
| | - Maciej Tankiewicz
- Department of Environmental Toxicology, Faculty of Health Sciences, Medical University of Gdansk, Dębowa Str. 23A, 80-204 Gdansk, Poland
| | - Magdalena Krupka
- Department of Plant Physiology, Genetics and Biotechnology, University of Warmia and Mazury, Oczapowskiego Str. 1A, 10-719 Olsztyn, Poland
| | - Grzegorz Siebielec
- Department of Soil Science Erosion and Land Protection, Institute of Soil Science and Plant Cultivation - State Research Institute, Czartoryskich Str. 8, 24-100 Puławy, Poland
| | - Lidia Wolska
- Department of Environmental Toxicology, Faculty of Health Sciences, Medical University of Gdansk, Dębowa Str. 23A, 80-204 Gdansk, Poland
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6
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Islam A, Islam S, Amin E, Hasan R, Hassan MM, Miah M, Samad MA, Shirin T, Hossain ME, Rahman MZ. Patterns and risk factors of avian influenza A(H5) and A(H9) virus infection in pigeons and quail at live bird markets in Bangladesh, 2017-2021. Front Vet Sci 2022; 9:1016970. [PMID: 36387379 PMCID: PMC9645412 DOI: 10.3389/fvets.2022.1016970] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 10/06/2022] [Indexed: 07/21/2023] Open
Abstract
The avian influenza virus (AIV) impacts poultry production, food security, livelihoods, and the risk of transmission to humans. Poultry, like pigeons and quail farming, is a growing sector in Bangladesh. However, the role of pigeons and quails in AIV transmission is not fully understood. Hence, we conducted this study to investigate the prevalence and risk factors of AIV subtypes in pigeons and quails at live bird markets (LBMs) in Bangladesh. We collected oropharyngeal and cloacal swab samples from 626 birds in 8 districts of Bangladesh from 2017 to 2021. We tested the swab samples for the matrix gene (M gene) followed by H5, H7, and H9 subtypes using real-time reverse transcriptase-polymerase chain reaction (rRT-PCR). We then used exploratory analysis to investigate the seasonal and temporal patterns of AIV and a mixed effect logistic model to identify the variable that influences the presence of AIV in pigeons and quails. The overall prevalence of AIV was 25.56%. We found that the prevalence of AIV in pigeons is 17.36%, and in quail is 38.75%. The prevalence of A/H5, A/H9, and A/H5/H9 in quail is 4.17, 17.92, and 1.67%, respectively. Furthermore, the prevalence of A/H5, A/H9, and A/H5/H9 in pigeons is 2.85, 2.59, and 0.26%. We also found that the prevalence of AIV was higher in the dry season than in the wet season in both pigeons and quail. In pigeons, the prevalence of A/untyped (40%) increased considerably in 2020. In quail, however, the prevalence of A/H9 (56%) significantly increased in 2020. The mixed-effect logistic regression model showed that the vendors having waterfowl (AOR: 2.13; 95% CI: 1.04-4.33), purchasing birds from the wholesale market (AOR: 2.96; 95% CI: 1.48-5.92) instead of farms, mixing sick birds with the healthy ones (AOR: 1.60; 95% CI: 1.04-2.45) and mingling unsold birds with new birds (AOR: 3.07; 95% CI: 2.01-4.70) were significantly more likely to be positive for AIV compared with vendors that did not have these characteristics. We also found that the odds of AIV were more than twice as high in quail (AOR: 2.57; 95% CI: 1.61-4.11) as in pigeons. Furthermore, the likelihood of AIV detection was 4.19 times higher in sick and dead birds (95% CI: 2.38-7.35) than in healthy birds. Our study revealed that proper hygienic practices at the vendors in LBM are not maintained. We recommend improving biosecurity practices at the vendor level in LBM to limit the risk of AIV infection in pigeons and quail in Bangladesh.
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Affiliation(s)
- Ariful Islam
- Centre for Integrative Ecology, School of Life and Environmental Science, Deakin University, Melbourne, VA, Australia
- EcoHealth Alliance, New York, NY, United States
- Institute of Epidemiology, Disease Control and Research (IEDCR), Dhaka, Bangladesh
| | - Shariful Islam
- Institute of Epidemiology, Disease Control and Research (IEDCR), Dhaka, Bangladesh
| | - Emama Amin
- Institute of Epidemiology, Disease Control and Research (IEDCR), Dhaka, Bangladesh
| | - Rashedul Hasan
- One Health Laboratory, International Center for Diarrheal Diseases Research, Bangladesh (icddr, b), Dhaka, Bangladesh
| | - Mohammad Mahmudul Hassan
- Queensland Alliance for One Health Sciences, School of Veterinary Science, University of Queensland, Brisbane, QLD, Australia
| | - Mojnu Miah
- One Health Laboratory, International Center for Diarrheal Diseases Research, Bangladesh (icddr, b), Dhaka, Bangladesh
| | - Mohammed Abdus Samad
- National Reference Laboratory for Avian Influenza, Bangladesh Livestock Research Institute (BLRI), Savar, Bangladesh
| | - Tahmina Shirin
- Institute of Epidemiology, Disease Control and Research (IEDCR), Dhaka, Bangladesh
| | - Mohammad Enayet Hossain
- One Health Laboratory, International Center for Diarrheal Diseases Research, Bangladesh (icddr, b), Dhaka, Bangladesh
| | - Mohammed Ziaur Rahman
- One Health Laboratory, International Center for Diarrheal Diseases Research, Bangladesh (icddr, b), Dhaka, Bangladesh
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7
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Tang H, Kang J, Shen C, Wang Y, Robertson ID, Cai C, Edwards J, Huang B, Bruce M. Benefit-cost analysis of a H7N9 vaccination program in poultry in Guangxi, China. Prev Vet Med 2022; 200:105580. [PMID: 35032782 DOI: 10.1016/j.prevetmed.2022.105580] [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: 09/22/2021] [Revised: 12/23/2021] [Accepted: 01/06/2022] [Indexed: 11/28/2022]
Abstract
China launched a H7N9 vaccination program in poultry, starting from the Guangxi and Guangdong provinces in July 2017, followed by other provinces in September 2017, as a response to a steep increase of H7N9 influenza human infections from September 2016. Since then, H5-H7 bivalent vaccine has been used in the nationwide avian influenza compulsory vaccination program to replace the existing H5N1 vaccine. However, the economic returns of the H7N9 vaccination program in China have never been adequately assessed. This study was designed to evaluate the economic value of the H7N9 vaccination program in Guangxi by assessing the benefits and costs of the program compared to not vaccinating against H7N9. A benefit-cost analysis (BCA) was undertaken to evaluate the adoption of a vaccination program against H7N9 in each of three consecutive years from July 2017 to June 2020 with the baseline scenario (the absence of H7N9 vaccination in the 12-month period July 2016 to June 2017). Both animal and public health perspectives were included in the BCA framework and took account of both the private and public sectors. Benefit-Cost Ratio (BCR) of the three-year H7N9 vaccination program was 18.6 (90 %PI: 15.4; 21.8), and total Net Present Values reached to CNY 1.63 billion (90 %PI: 1.37 billion; 1.89 billion). The extra revenue generated by the yellow broiler industry comprised 93.8 % of the total benefits after adoption of H7N9 vaccination program in Guangxi. While cost-savings in public health and animal health expenditure avoided were 3.6 % and 2.6 %, respectively. Total costs arising from adoption of the revised vaccination program over the three years were CNY 12.46 million (90 %PI: 11.49 million; 14.14 million), CNY 34.87 million (90 %PI: 31.88 million; 40.06 million), and CNY 44.28 million (90 %PI: 39.66 million; 52.27 million), respectively. Sensitivity analysis found the yellow broiler wholesale prices contributed 97.7 % of the variance of the total NPV of three vaccination years. The study results demonstrate the significant economic advantage of implementing a vaccination program against H7N9 in Guangxi. It also offers a new set of evidence to China's H7N9 vaccination policy and debates around economic values of conducting routine avian influenza vaccination.
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Affiliation(s)
- Hao Tang
- China Animal Health and Epidemiology Centre, Qingdao, China; School of Veterinary Medicine, Murdoch University, Perth, Australia.
| | - Jingli Kang
- China Animal Health and Epidemiology Centre, Qingdao, China
| | - Chaojian Shen
- China Animal Health and Epidemiology Centre, Qingdao, China
| | - Youming Wang
- China Animal Health and Epidemiology Centre, Qingdao, China
| | - Ian D Robertson
- School of Veterinary Medicine, Murdoch University, Perth, Australia; Hubei International Scientific and Technological Cooperation Base of Veterinary Epidemiology, Huazhong Agricultural University, Wuhan, China
| | - Chang Cai
- China Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology, Zhejiang Agricultural and Forestry University, Hangzhou, China
| | - John Edwards
- China Animal Health and Epidemiology Centre, Qingdao, China; School of Veterinary Medicine, Murdoch University, Perth, Australia
| | - Baoxu Huang
- China Animal Health and Epidemiology Centre, Qingdao, China
| | - Mieghan Bruce
- School of Veterinary Medicine, Murdoch University, Perth, Australia; Centre for Biosecurity and One Health, Harry Butler Institute, Murdoch University, Perth, Australia.
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8
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Guo J, Song W, Ni X, Liu W, Wu J, Xia W, Zhou X, Wang W, He F, Wang X, Fan G, Zhou K, Chen H, Chen S. Pathogen change of avian influenza virus in the live poultry market before and after vaccination of poultry in southern China. Virol J 2021; 18:213. [PMID: 34715890 PMCID: PMC8554751 DOI: 10.1186/s12985-021-01683-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 10/18/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The fifth wave of H7N9 avian influenza virus caused a large number of human infections and a large number of poultry deaths in China. Since September 2017, mainland China has begun to vaccinate poultry with H5 + H7 avian influenza vaccine. We investigated the avian influenza virus infections in different types of live poultry markets and samples before and after genotype H5 + H7 vaccination in Nanchang, and analyzed the changes of the HA subtypes of AIVs. METHODS From 2016 to 2019, we monitored different live poultry markets and collected specimens, using real-time reverse transcription polymerase chain reaction (RT-PCR) technology to detect the nucleic acid of type A avian influenza virus in the samples. The H5, H7 and H9 subtypes of influenza viruses were further classified for the positive results. The χ2 test was used to compare the differences in the separation rates of different avian influenza subtypes. RESULTS We analyzed 5,196 samples collected before and after vaccination and found that the infection rate of AIV in wholesale market (21.73%) was lower than that in retail market (24.74%) (P < 0.05). Among all the samples, the positive rate of sewage samples (33.90%) was the highest (P < 0.001). After vaccination, the positive rate of H5 and H7 subtypes decreased, and the positive rate of H9 subtype and untypable HA type increased significantly (P < 0.001). The positive rates of H9 subtype in different types of LPMs and different types of samples increased significantly (P < 0.01), and the positive rates of untypable HA type increased significantly in all environmental samples (P < 0.05). CONCLUSIONS Since vaccination, the positive rates of H5 and H7 subtypes have decreased, but the positive rates of H9 subtypes have increased to varying degrees in different testing locations and all samples. This results show that the government should establish more complete measures to achieve long-term control of the avian influenza virus.
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Affiliation(s)
- Jin Guo
- The Collaboration Unit for Field Epidemiology of State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Key Laboratory of Animal-Origin and Vector-Borne Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, 330038, People's Republic of China.,School of Public Health, Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang University, Nanchang, 330006, People's Republic of China
| | - Wentao Song
- The Collaboration Unit for Field Epidemiology of State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Key Laboratory of Animal-Origin and Vector-Borne Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, 330038, People's Republic of China
| | - Xiansheng Ni
- The Collaboration Unit for Field Epidemiology of State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Key Laboratory of Animal-Origin and Vector-Borne Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, 330038, People's Republic of China
| | - Wei Liu
- The Collaboration Unit for Field Epidemiology of State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Key Laboratory of Animal-Origin and Vector-Borne Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, 330038, People's Republic of China
| | - Jingwen Wu
- The Collaboration Unit for Field Epidemiology of State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Key Laboratory of Animal-Origin and Vector-Borne Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, 330038, People's Republic of China
| | - Wen Xia
- The Collaboration Unit for Field Epidemiology of State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Key Laboratory of Animal-Origin and Vector-Borne Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, 330038, People's Republic of China
| | - Xianfeng Zhou
- The Collaboration Unit for Field Epidemiology of State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Key Laboratory of Animal-Origin and Vector-Borne Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, 330038, People's Republic of China
| | - Wei Wang
- The Collaboration Unit for Field Epidemiology of State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Key Laboratory of Animal-Origin and Vector-Borne Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, 330038, People's Republic of China
| | - Fenglan He
- The Collaboration Unit for Field Epidemiology of State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Key Laboratory of Animal-Origin and Vector-Borne Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, 330038, People's Republic of China
| | - Xi Wang
- The Collaboration Unit for Field Epidemiology of State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Key Laboratory of Animal-Origin and Vector-Borne Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, 330038, People's Republic of China
| | - Guoyin Fan
- The Collaboration Unit for Field Epidemiology of State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Key Laboratory of Animal-Origin and Vector-Borne Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, 330038, People's Republic of China
| | - Kun Zhou
- The Collaboration Unit for Field Epidemiology of State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Key Laboratory of Animal-Origin and Vector-Borne Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, 330038, People's Republic of China
| | - Haiying Chen
- The Collaboration Unit for Field Epidemiology of State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Key Laboratory of Animal-Origin and Vector-Borne Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, 330038, People's Republic of China
| | - Shengen Chen
- The Collaboration Unit for Field Epidemiology of State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Key Laboratory of Animal-Origin and Vector-Borne Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, 330038, People's Republic of China.
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9
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Tang H, Fournié G, Li J, Zou L, Shen C, Wang Y, Cai C, Edwards J, Robertson ID, Huang B, Bruce M. Analysis of the movement of live broilers in Guangxi, China and implications for avian influenza control. Transbound Emerg Dis 2021; 69:e775-e787. [PMID: 34693647 DOI: 10.1111/tbed.14351] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 03/24/2021] [Accepted: 10/12/2021] [Indexed: 11/29/2022]
Abstract
Most Chinese provinces have a daily-updated database of live animal movements; however, the data are not efficiently utilized to support interventions to control H7N9 and other avian influenzas. Based on official records, this study assessed the spatio-temporal patterns of live broilers moved out of and within Guangxi in 2017. The yearly and monthly networks were analyzed for inter- and intra-provincial movements, respectively. Approximately 200,000 movements occurred in 2017, involving the transport of 200 million live broilers from Guangxi. Although Guangxi exported to 24 out of 32 provinces of China, 95% of inter-provincial movements occurred with three bordering provinces. Within Guangxi, counties were highly connected through the live broiler movements, creating conditions for rapid virus spreading throughout the province. Interestingly, a peak in movements during the Chinese Lunar New Year celebrations, late January in 2017, was not observed in this study, likely due to H7N9-related control measures constraining live bird trading. Both intra- and inter-provincial movements in March 2017 were significantly higher than in other months of that year, suggesting that dramatic price changes may influence the movement's network and reshape the risk pathways. However, despite these variations, the same small proportion of counties (less than 20%) exporting/importing more than 90% of inter- and intra-provincial movements remains the same throughout the year. Interventions, particularly surveillance and improving biosecurity, targeted to those counties are thus likely to be more effective for avian influenza risk mitigation than implemented indiscriminately. Additionally, simulations further demonstrated that targeting counties according to their degree or betweenness in the movement network would be the most efficient way to limit disease transmission via broiler movements. The study findings provide evidence to support the design of risk-based control interventions for H7N9 and all other avian influenza viruses in broiler value chains in Guangxi.
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Affiliation(s)
- Hao Tang
- China Animal Health and Epidemiology Centre, Qingdao, China.,School of Veterinary Medicine, Murdoch University, Perth, Australia
| | | | - Jinming Li
- China Animal Health and Epidemiology Centre, Qingdao, China
| | - Lianbin Zou
- Guangxi Centre of Animal Disease Prevention and Control, Nanning, China
| | - Chaojian Shen
- China Animal Health and Epidemiology Centre, Qingdao, China
| | - Youming Wang
- China Animal Health and Epidemiology Centre, Qingdao, China
| | - Chang Cai
- China Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology, Zhejiang Agricultural and Forestry University, Hangzhou, China
| | - John Edwards
- China Animal Health and Epidemiology Centre, Qingdao, China.,School of Veterinary Medicine, Murdoch University, Perth, Australia
| | - Ian D Robertson
- School of Veterinary Medicine, Murdoch University, Perth, Australia.,Hubei International Scientific and Technological Cooperation Base of Veterinary Epidemiology, Huazhong Agricultural University, Wuhan, China
| | - Baoxu Huang
- China Animal Health and Epidemiology Centre, Qingdao, China
| | - Mieghan Bruce
- School of Veterinary Medicine, Murdoch University, Perth, Australia.,Centre for Biosecurity and One Health, Harry Butler Institute, Murdoch University, Perth, Australia
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10
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Yazdekhasti A, Wang J, Zhang L, Ma J. A multi-period multi-modal stochastic supply chain model under COVID pandemic: A poultry industry case study in Mississippi. TRANSPORTATION RESEARCH. PART E, LOGISTICS AND TRANSPORTATION REVIEW 2021; 154:102463. [PMID: 34512109 PMCID: PMC8418151 DOI: 10.1016/j.tre.2021.102463] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2021] [Revised: 08/09/2021] [Accepted: 08/17/2021] [Indexed: 05/31/2023]
Abstract
The poultry industry is one of the most important agricultural sectors, which constitutes a significant part of the per capita consumption of protein and meat. Integrating operations of poultry industry sections including production, distribution and consumption becomes vital. Although the proper poultry supply chain has been established and made plenty of benefits for a long time, the global outbreak of COVID-19 shows that operations under pandemic are still challenge for the poultry industry. In this paper, the impacts of pandemic on poultry industry is investigated by developing a multi-period multi-modal stochastic poultry supply chain. Two models are developed aiming to mitigate the negative effects of pandemic occurrence through product stocking policy. In the first model, distribution system is in accordance with a multi-component structure, while the second model allows direct connections between suppliers (farmers) and demanders (customers). In both models, poultry productions are negatively affected by COVID 19. Due to the complexity of the model, a hybrid solution approach based on Branch and Cut and Dynamic Programming is developed. To validate the performance of the proposed model and solution procedure, a case study on the broiler industry in the state of Mississippi is performed. The results show that storing poultry products in the pre-pandemic along with direct logistics during pandemic period can save the broiler supply chain cost up to 30%.
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Affiliation(s)
- Amin Yazdekhasti
- Department of Industrial Engineering, Daneshpajoohan Pishro Higher Education Institute, Isfahan, Iran
| | - Jun Wang
- Department of Civil and Environmental Engineering, Mississippi State University, Mississippi State, MS 39762, USA
| | - Li Zhang
- Department of Civil and Environmental Engineering, Mississippi State University, Mississippi State, MS 39762, USA
| | - Junfeng Ma
- Department of Industrial and Systems Engineering, Mississippi State University, Mississippi State, MS 39762, USA
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11
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Liu W, Li D, Yang C, Chen F, Jia R, Jia L, Xia X, Fan S, Tan Q, Ke Y, Chen Y, Li H, Zhan L, Liu X, You J, Fu X, Li D, Zhang L, Wang C, Han L. Environmental contamination with SARS-CoV-2 in COVID-19 hospitals in Wuhan, China, 2020. Environ Microbiol 2021; 23:7373-7381. [PMID: 34347340 PMCID: PMC8441894 DOI: 10.1111/1462-2920.15695] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 07/28/2021] [Accepted: 07/28/2021] [Indexed: 01/22/2023]
Abstract
Coronavirus disease 2019 (COVID-19) pandemic has caused high number of infections and deaths of healthcare workers globally. Distribution and possible transmission route of SARS-CoV-2 in hospital environment should be clarified. We herein collected 431 environmental (391 surface and 40 air) samples in the intensive care unit (ICU) and general wards (GWs) of three hospitals in Wuhan, China from February 21 to March 4, 2020, and detected SARS-CoV-2 RNA by real-time quantitative PCR. The viral positive rate in the contaminated areas was 17.8% (28/157), whereas there was no virus detected in the clean areas. Higher positive rate (22/59, 37.3%) was found in ICU than that in GWs (3/63, 4.8%). The surfaces of computer keyboards and mouse in the ICU were the most contaminated (8/10, 80.0%), followed by the ground (6/9, 66.7%) and outer glove (2/5, 40.0%). From 17 air samples in the contaminated areas, only one sample collected at a distance of around 30 cm from the patient was positive. Enhanced surface disinfection and hand hygiene effectively decontaminated the virus from the environment. This finding might help understand the transmission route and contamination risk of SARS-CoV-2 and evaluate the effectiveness of infection prevention and control measures in healthcare facilities.
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Affiliation(s)
- Wei Liu
- Chinese PLA Center for Disease Control & Prevention, Beijing, China.,Huoshenshan Hospital, Wuhan, China
| | - Dingchen Li
- Chinese PLA Center for Disease Control & Prevention, Beijing, China
| | - Chaojie Yang
- Chinese PLA Center for Disease Control & Prevention, Beijing, China.,Huoshenshan Hospital, Wuhan, China
| | - Fangyan Chen
- Chinese PLA Center for Disease Control & Prevention, Beijing, China
| | - Ruizhong Jia
- Chinese PLA Center for Disease Control & Prevention, Beijing, China.,Huoshenshan Hospital, Wuhan, China
| | - Leili Jia
- Chinese PLA Center for Disease Control & Prevention, Beijing, China.,Huoshenshan Hospital, Wuhan, China
| | | | | | - Qing Tan
- Huoshenshan Hospital, Wuhan, China
| | - Yuehua Ke
- Chinese PLA Center for Disease Control & Prevention, Beijing, China.,Huoshenshan Hospital, Wuhan, China
| | - Yong Chen
- Chinese PLA Center for Disease Control & Prevention, Beijing, China.,Huoshenshan Hospital, Wuhan, China
| | | | | | - Xiong Liu
- Chinese PLA Center for Disease Control & Prevention, Beijing, China.,Huoshenshan Hospital, Wuhan, China
| | | | | | - Dan Li
- Hubei Maternal and Child Health Hospital (Guanggu District), Wuhan, China
| | - Lin Zhang
- Hubei Maternal and Child Health Hospital (Guanggu District), Wuhan, China
| | - Changjun Wang
- Chinese PLA Center for Disease Control & Prevention, Beijing, China.,Huoshenshan Hospital, Wuhan, China
| | - Li Han
- Chinese PLA Center for Disease Control & Prevention, Beijing, China.,Huoshenshan Hospital, Wuhan, China
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12
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Acke S, Couvreur S, Bramer WM, Schmickler MN, De Schryver A, Haagsma JA. Global infectious disease risks associated with occupational exposure among non-healthcare workers: a systematic review of the literature. Occup Environ Med 2021; 79:63-71. [PMID: 34035182 PMCID: PMC8685622 DOI: 10.1136/oemed-2020-107164] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 02/07/2021] [Accepted: 02/12/2021] [Indexed: 12/03/2022]
Abstract
Objectives Employees in non-healthcare occupations may be in several ways exposed to infectious agents. Improved knowledge about the risks is needed to identify opportunities to prevent work-related infectious diseases. The objective of the current study was to provide an updated overview of the published evidence on the exposure to pathogens among non-healthcare workers. Because of the recent SARS-CoV-2 outbreaks, we also aimed to gain more evidence about exposure to several respiratory tract pathogens. Methods Eligible studies were identified in MEDLINE, Embase and Cochrane between 2009 and 8 December 2020. The protocol was registered with International Prospective Register of Systematic Reviews (CRD42019107265). An additional quality assessment was applied according to the Equator network guidelines. Results The systematic literature search yielded 4620 papers of which 270 met the selection and quality criteria. Infectious disease risks were described in 37 occupational groups; 18 of them were not mentioned before. Armed forces (n=36 pathogens), livestock farm labourers (n=31), livestock/dairy producers (n=26), abattoir workers (n=22); animal carers and forestry workers (both n=16) seemed to have the highest risk. In total, 111 pathogen exposures were found. Many of these occupational groups (81.1%) were exposed to respiratory tract pathogens. Conclusion Many of these respiratory tract pathogens were readily transmitted where employees congregate (workplace risk factors), while worker risk factors seemed to be of increasing importance. By analysing existing knowledge of these risk factors, identifying new risks and susceptible risk groups, this review aimed to raise awareness of the issue and provide reliable information to establish more effective preventive measures.
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Affiliation(s)
- Sofie Acke
- Family Medicine and Population Health (FAMPOP), Faculty of Medicine and Health Sciences, University of Antwerp, Wilrijk, Belgium.,Research and Development, Mensura Occupational Health Services, Brussel, Belgium
| | - Simon Couvreur
- Department of Twin Research, King's College London, London, UK
| | | | | | - Antoon De Schryver
- Family Medicine and Population Health (FAMPOP), Faculty of Medicine and Health Sciences, University of Antwerp, Wilrijk, Belgium
| | - Juanita A Haagsma
- Department of Public Health, Erasmus MC, Rotterdam, Zuid-Holland, The Netherlands
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13
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Fate of Biodegradable Engineered Nanoparticles Used in Veterinary Medicine as Delivery Systems from a One Health Perspective. Molecules 2021; 26:molecules26030523. [PMID: 33498295 PMCID: PMC7863917 DOI: 10.3390/molecules26030523] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 01/11/2021] [Accepted: 01/15/2021] [Indexed: 12/16/2022] Open
Abstract
The field of veterinary medicine needs new solutions to address the current challenges of antibiotic resistance and the need for increased animal production. In response, a multitude of delivery systems have been developed in the last 20 years in the form of engineered nanoparticles (ENPs), a subclass of which are polymeric, biodegradable ENPs, that are biocompatible and biodegradable (pbENPs). These platforms have been developed to deliver cargo, such as antibiotics, vaccines, and hormones, and in general, have been shown to be beneficial in many regards, particularly when comparing the efficacy of the delivered drugs to that of the conventional drug applications. However, the fate of pbENPs developed for veterinary applications is poorly understood. pbENPs undergo biotransformation as they are transferred from one ecosystem to another, and these transformations greatly affect their impact on health and the environment. This review addresses nanoparticle fate and impact on animals, the environment, and humans from a One Health perspective.
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14
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Hood G, Roche X, Brioudes A, von Dobschuetz S, Fasina FO, Kalpravidh W, Makonnen Y, Lubroth J, Sims L. A literature review of the use of environmental sampling in the surveillance of avian influenza viruses. Transbound Emerg Dis 2021; 68:110-126. [PMID: 32652790 PMCID: PMC8048529 DOI: 10.1111/tbed.13633] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Revised: 05/07/2020] [Accepted: 05/13/2020] [Indexed: 02/05/2023]
Abstract
This literature review provides an overview of use of environmental samples (ES) such as faeces, water, air, mud and swabs of surfaces in avian influenza (AI) surveillance programs, focussing on effectiveness, advantages and gaps in knowledge. ES have been used effectively for AI surveillance since the 1970s. Results from ES have enhanced understanding of the biology of AI viruses in wild birds and in markets, of links between human and avian influenza, provided early warning of viral incursions, allowed assessment of effectiveness of control and preventive measures, and assisted epidemiological studies in outbreaks, both avian and human. Variation exists in the methods and protocols used, and no internationally recognized guidelines exist on the use of ES and data management. Few studies have performed direct comparisons of ES versus live bird samples (LBS). Results reported so far demonstrate reliance on ES will not be sufficient to detect virus in all cases when it is present, especially when the prevalence of infection/contamination is low. Multiple sample types should be collected. In live bird markets, ES from processing/selling areas are more likely to test positive than samples from bird holding areas. When compared to LBS, ES is considered a cost-effective, simple, rapid, flexible, convenient and acceptable way of achieving surveillance objectives. As a non-invasive technique, it can minimize effects on animal welfare and trade in markets and reduce impacts on wild bird communities. Some limitations of environmental sampling methods have been identified, such as the loss of species-specific or information on the source of virus, and taxonomic-level analyses, unless additional methods are applied. Some studies employing ES have not provided detailed methods. In others, where ES and LBS are collected from the same site, positive results have not been assigned to specific sample types. These gaps should be remedied in future studies.
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Affiliation(s)
- Grace Hood
- Food and Agriculture Organization of the United NationsRomeItaly
| | - Xavier Roche
- Food and Agriculture Organization of the United NationsRomeItaly
| | - Aurélie Brioudes
- Food and Agriculture Organization of the United NationsRegional Office for Asia and the PacificBangkokThailand
| | | | | | | | - Yilma Makonnen
- Food and Agriculture Organization of the United Nations, Sub-Regional Office for Eastern AfricaAddis AbabaEthiopia
| | - Juan Lubroth
- Food and Agriculture Organization of the United NationsRomeItaly
| | - Leslie Sims
- Asia Pacific Veterinary Information ServicesMelbourneAustralia
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15
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Abstract
The risk of emergence and spread of novel human pathogens originating from an animal reservoir has increased in the past decades. However, the unpredictable nature of disease emergence makes surveillance and preparedness challenging. Knowledge of general risk factors for emergence and spread, combined with local level data is needed to develop a risk-based methodology for early detection. This involves the implementation of the One Health approach, integrating human, animal and environmental health sectors, as well as social sciences, bioinformatics and more. Recent technical advances, such as metagenomic sequencing, will aid the rapid detection of novel pathogens on the human-animal interface.
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16
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Yi L, Duan C, Tao J, Huang Y, Xing M, Zhu Z, Tan C, Chen X. Disease Outbreak, Health Scare, and Distance Decay: Evidence from HPAI Shocks in Chinese Meat Sector. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E8009. [PMID: 33143249 PMCID: PMC7662287 DOI: 10.3390/ijerph17218009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2020] [Revised: 10/14/2020] [Accepted: 10/27/2020] [Indexed: 11/16/2022]
Abstract
Background: During zoonotic disease shocks (ZDSs), zoonotic disease outbreaks (ZDOs) can induce public health scares (PHSs), causing meat price risks (MPRs). Nevertheless, spatial spillovers of zoonotic disease shocks in meat markets remain unclear. We explore how zoonotic disease outbreaks and public health scares locally and spatially spill over to meat price risks, and whether spatial spillovers of public health scares decay with distance. Methods: (i) We construct a long panel covering 30 provinces and 121 months, using highly pathogenic avian influenza (HPAI) epidemics as exogenous shocks in Chinese meat sector. (ii) We decompose zoonotic disease shocks into zoonotic disease outbreaks (objective incident) and public health scares (subjective information) and examine their spillovers to meat price risks. (iii) We identify distance-decaying spatial spillovers of public health scares, by running our dynamic SAR models 147 times, from 80 km to 3000 km with 20 km as incremental value, in a setting with risk-level heterogeneity. Results: (i) Zoonotic disease outbreaks themselves only cause local and neighboring meat price risks for high-risk meat, not for low-risk or substitute meat. (ii) Public health scares exacerbate local and neighboring meat price risks for high-risk and low-risk meat, and local meat price risks for substitute meat. (iii) Spatial spillovers of public health scares are distance-decaying and U-shaped, with four spatial attenuation boundaries, and distance turning point is shorter for high-risk meat (500 km) than for low-risk meat (800 km). Conclusions: We complement the literature by arguing that health scares induced by disease outbreaks negatively spill over to meat prices, with U-shaped distance-decaying spatial effects. This suggests low interregional spatial market integration in meat products, due to distance decay of nonstandardized information and local government control effects, across provincial boundaries. To the best of our knowledge, we are the first to document nonmonotonic distance decay of health scare effects on food prices, previously not found by the literature.
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Affiliation(s)
- Lan Yi
- Institute of Agricultural Economics & Technology, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (L.Y.); (M.X.); (X.C.)
- Sub-Center for Agricultural Economics & Technology, Hubei Center for Agricultural Science & Technology Innovation, Wuhan 430064, China
- Hubei Academy of Rural Revitalization, Wuhan 430064, China
- College of Economics & Management, Huazhong Agricultural University, Wuhan 430070, China; (Y.H.); (C.T.)
- Hubei Rural Development Research Center, Wuhan 430070, China
| | - Congcong Duan
- College of Economics & Management, Huazhong Agricultural University, Wuhan 430070, China; (Y.H.); (C.T.)
- Hubei Rural Development Research Center, Wuhan 430070, China
| | - Jianping Tao
- College of Economics & Management, Huazhong Agricultural University, Wuhan 430070, China; (Y.H.); (C.T.)
- Hubei Rural Development Research Center, Wuhan 430070, China
| | - Yong Huang
- College of Economics & Management, Huazhong Agricultural University, Wuhan 430070, China; (Y.H.); (C.T.)
- Hubei Rural Development Research Center, Wuhan 430070, China
| | - Meihua Xing
- Institute of Agricultural Economics & Technology, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (L.Y.); (M.X.); (X.C.)
- Sub-Center for Agricultural Economics & Technology, Hubei Center for Agricultural Science & Technology Innovation, Wuhan 430064, China
- Hubei Academy of Rural Revitalization, Wuhan 430064, China
| | - Zhongkun Zhu
- National School of Development, Peking University, Beijing 100871, China;
| | - Caifeng Tan
- College of Economics & Management, Huazhong Agricultural University, Wuhan 430070, China; (Y.H.); (C.T.)
- Hubei Rural Development Research Center, Wuhan 430070, China
- Department of Agricultural and Resource Economics, North Carolina State University, Raleigh, NC 27695, USA
| | - Xinglin Chen
- Institute of Agricultural Economics & Technology, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (L.Y.); (M.X.); (X.C.)
- Sub-Center for Agricultural Economics & Technology, Hubei Center for Agricultural Science & Technology Innovation, Wuhan 430064, China
- Hubei Academy of Rural Revitalization, Wuhan 430064, China
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17
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Chen Y, Cheng J, Xu Z, Hu W, Lu J. Live poultry market closure and avian influenza A (H7N9) infection in cities of China, 2013-2017: an ecological study. BMC Infect Dis 2020; 20:369. [PMID: 32448137 PMCID: PMC7245998 DOI: 10.1186/s12879-020-05091-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2020] [Accepted: 05/13/2020] [Indexed: 01/24/2023] Open
Abstract
Background Previous studies have proven that the closure of live poultry markets (LPMs) was an effective intervention to reduce human risk of avian influenza A (H7N9) infection, but evidence is limited on the impact of scale and duration of LPMs closure on the transmission of H7N9. Method Five cities (i.e., Shanghai, Suzhou, Shenzhen, Guangzhou and Hangzhou) with the largest number of H7N9 cases in mainland China from 2013 to 2017 were selected in this study. Data on laboratory-confirmed H7N9 human cases in those five cities were obtained from the Chinese National Influenza Centre. The detailed information of LPMs closure (i.e., area and duration) was obtained from the Ministry of Agriculture. We used a generalized linear model with a Poisson link to estimate the effect of LPMs closure, reported as relative risk reduction (RRR). We used classification and regression trees (CARTs) model to select and quantify the dominant factor of H7N9 infection. Results All five cities implemented the LPMs closure, and the risk of H7N9 infection decreased significantly after LPMs closure with RRR ranging from 0.80 to 0.93. Respectively, a long-term LPMs closure for 10–13 weeks elicited a sustained and highly significant risk reduction of H7N9 infection (RRR = 0.98). Short-time LPMs closure with 2 weeks in every epidemic did not reduce the risk of H7N9 infection (p > 0.05). Partially closed LPMs in some suburbs contributed only 35% for reduction rate (RRR = 0.35). Shenzhen implemented partial closure for first 3 epidemics (p > 0.05) and all closure in the latest 2 epidemic waves (RRR = 0.64). Conclusion Our findings suggest that LPMs all closure in whole city can be a highly effective measure comparing with partial closure (i.e. only urban closure, suburb and rural remain open). Extend the duration of closure and consider permanently closing the LPMs will help improve the control effect. The effect of LPMs closure seems greater than that of meteorology on H7N9 transmission.
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Affiliation(s)
- Ying Chen
- School of Public Health, Key Laboratory of Tropical Diseases Control of Ministry of Education, One Health Center of Excellence for Research &Training, Sun Yat-sen University, Guangzhou, China.,School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia
| | - Jian Cheng
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia
| | - Zhiwei Xu
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia
| | - Wenbiao Hu
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia
| | - Jiahai Lu
- School of Public Health, Key Laboratory of Tropical Diseases Control of Ministry of Education, One Health Center of Excellence for Research &Training, Sun Yat-sen University, Guangzhou, China.
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