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Yun S, Hong MJ, Yang MS, Jeon HJ, Lee WS. Assessment of the spatiotemporal risk of avian influenza between waterfowl and poultry farms during the annual cycle: A spatial prediction study focused on seasonal distribution changes in resident waterfowl in South Korea. Transbound Emerg Dis 2022; 69:e3128-e3140. [PMID: 35894239 DOI: 10.1111/tbed.14669] [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: 03/31/2022] [Revised: 07/13/2022] [Accepted: 07/21/2022] [Indexed: 11/26/2022]
Abstract
Previous studies and efforts to prevent and manage avian influenza (AI) outbreaks have mainly focused on the wintering season. However, outbreaks of AI have been reported in the summer, including the breeding season of waterfowl. Additionally, the spatial distribution of waterfowl can easily change during the annual cycle due to their life-cycle traits and the presence of both migrants and residents in the population. Thus, we assessed the spatiotemporal variation in AI exposure risk in poultry due to spatial distribution changes in three duck species included in both major residents and wintering migrants in South Korea, the mandarin, mallard and spot-billed duck, during wintering (October-March), breeding (April-June) and whole annual seasons. To estimate seasonal ecological niche variations among the three duck species, we applied pairwise ecological niche analysis using the Pianka index. Subsequently, seasonal distribution models were projected by overlaying the monthly ranges estimated by the maximum entropy model. Finally, we overlaid each seasonal distribution range onto a poultry distribution map of South Korea. We found that the mandarin had less niche overlap with the mallard and spot-billed duck during the wintering season than during the breeding season, whereas the mallard had less niche overlap with the mandarin and spot-billed duck during the breeding season than during the wintering season. Breeding and annual distribution ranges of the mandarin and spot-billed duck, but not the mallard, were similar or even wider than their wintering ranges. Similarly, the mandarin and spot-billed duck showed more extensive overlap proportions between poultry and their distributional ranges during both the breeding and annual seasons than during the wintering season. These results suggest that potential AI exposure in poultry can occur more widely in the summer than in winter, depending on sympatry with the host duck species. Future studies considering the population density and variable pathogenicity of AI are required.
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Affiliation(s)
- Seongho Yun
- Korea Institute of Ornithology, Kyung Hee University, Seoul, Republic of Korea
| | - Mi-Jin Hong
- Korea Institute of Ornithology, Kyung Hee University, Seoul, Republic of Korea.,Department of Biology, Kyung Hee University, Seoul, Republic of Korea
| | - Min-Seung Yang
- Korea Institute of Ornithology, Kyung Hee University, Seoul, Republic of Korea.,Department of Biology, Kyung Hee University, Seoul, Republic of Korea
| | - Hye-Jeong Jeon
- Korea Institute of Ornithology, Kyung Hee University, Seoul, Republic of Korea.,Department of Biology, Kyung Hee University, Seoul, Republic of Korea
| | - Who-Seung Lee
- Environment Assessment Group, Korea Environment Institute, Sejong, Republic of Korea
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Ahmad S, Koh KY, Lee JI, Suh GH, Lee CM. Interpolation of Point Prevalence Rate of the Highly Pathogenic Avian Influenza Subtype H5N8 Second Phase Epidemic in South Korea. Vet Sci 2022; 9:vetsci9030139. [PMID: 35324867 PMCID: PMC8954420 DOI: 10.3390/vetsci9030139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 03/09/2022] [Accepted: 03/10/2022] [Indexed: 11/29/2022] Open
Abstract
Humans and animals are both susceptible to highly pathogenic avian influenza (HPAI) viruses. In the future, HPAI has the potential to be a source of zoonoses and pandemic disease drivers. It is necessary to identify areas of high risk that are more vulnerable to HPAI infections. In this study, we applied unbiased predictions based on known information to find points of localities with a high probability of point prevalence rate. To carry out such predictions, we utilized the inverse distance weighting (IDW) and kriging method, with the help of the R statistical computing program. The provinces of Jeollanam-do, Gyeonggi-do, Chungcheongbuk-do and Ulsan have high anticipated risk. This research might aid in the management of avian influenza threats associated with various potential risks.
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Affiliation(s)
- Saleem Ahmad
- Veterinary Public Health Lab, College of Veterinary Medicine, Chonnam National University, Gwangju 61186, Korea; (S.A.); (K.-Y.K.); (J.-i.L.)
| | - Kye-Young Koh
- Veterinary Public Health Lab, College of Veterinary Medicine, Chonnam National University, Gwangju 61186, Korea; (S.A.); (K.-Y.K.); (J.-i.L.)
| | - Jae-il Lee
- Veterinary Public Health Lab, College of Veterinary Medicine, Chonnam National University, Gwangju 61186, Korea; (S.A.); (K.-Y.K.); (J.-i.L.)
| | - Guk-Hyun Suh
- Department of Veterinary Internal Medicine, College of Veterinary Medicine and BK21 FOUR Program, Chonnam National University, Gwangju 61186, Korea;
| | - Chang-Min Lee
- Department of Veterinary Internal Medicine, College of Veterinary Medicine and BK21 FOUR Program, Chonnam National University, Gwangju 61186, Korea;
- Correspondence:
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3
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Yoo DS, Lee K, Beatriz ML, Chun BC, Belkhiria J, Lee KN. Spatiotemporal risk assessment for avian influenza outbreak based on the dynamics of habitat suitability for wild birds. Transbound Emerg Dis 2021; 69:e953-e967. [PMID: 34738338 DOI: 10.1111/tbed.14376] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 10/26/2021] [Accepted: 10/27/2021] [Indexed: 11/26/2022]
Abstract
Highly pathogenic avian influenza (HPAI) has predominantly damaged the poultry industry worldwide. The fundamental prevention and control strategy for HPAI includes early detection and timely intervention enforcement through a systematic surveillance system for wild birds based on the ecological understanding of the dynamics of wild birds' movements. Our study aimed to develop a spatiotemporal risk assessment model for avian influenza (AI) infection in wild birds to empower surveillance information for a contingency strategy. For this purpose, first, we predicted the monthly habitat suitability of seven waterfowl species, using 227,671 Global Positioning System (GPS) tracking records of 562 birds from 2014 to 2018 in the Republic of Korea (ROK). Then, that predicted habitat suitability and 421 coordinates of AI detection sites in wild birds were used to build the risk assessment model. Subsequently, we compared the monthly predicted risk of avian influenza virus (AIv) identification in wild birds between case and non-case poultry farms with HPAI H5N6 outbreak in the ROK between 2016 and 2017. The results reported considerable variation of monthly habitat suitability of seven waterfowls and the impact of predicting AI occurrences in wild birds. The high habitat suitability for spot-billed ducks (contribution rate in November = 40.9%) and mallards (contribution rate in January = 34.3%) significantly contributed to predicting the average risk of AIv identification in wild birds, with high predictive performance [the monthly mean of area under the curve (AUC) = 0.978]. Moreover, our model showed that the averaged risk of identification AI in wild birds was significantly higher in HPAI infected premises, with infected domestic duck holdings exhibiting a significantly higher risk than the chicken farms in November. This study suggests that animal health authority establishes a risk-based HPAI surveillance system grounded on the ecological nature of wild birds to improve the effectiveness of prevention and preparedness of emerging epidemics.
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Affiliation(s)
- Dae-Sung Yoo
- Department of Public Health, Graduate School, Korea University, Seoul, Republic of Korea
| | - Kyuyoung Lee
- Center for Animal Disease Modeling and Surveillance (CADMS), Department of Medicine and Epidemiology, School of Veterinary Medicine, University of California, Davis, California, USA
| | - Martínez López Beatriz
- Center for Animal Disease Modeling and Surveillance (CADMS), Department of Medicine and Epidemiology, School of Veterinary Medicine, University of California, Davis, California, USA
| | - Byung Chul Chun
- Department of Public Health, College of Medicine, Korea University, Seoul, Republic of Korea
| | - Jaber Belkhiria
- One Health Institute, School of Veterinary Medicine, University of California, Davis, California, USA
| | - Kwang-Nyeong Lee
- Department of Public Health, Graduate School, Korea University, Seoul, Republic of Korea
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4
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Ratnadass A, Deguine JP. Crop protection practices and viral zoonotic risks within a One Health framework. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 774:145172. [PMID: 33610983 DOI: 10.1016/j.scitotenv.2021.145172] [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: 11/03/2020] [Revised: 01/10/2021] [Accepted: 01/10/2021] [Indexed: 06/12/2023]
Abstract
Recent viral zoonotic epidemics have been attributed partially to the negative impact of human activities on ecosystem biodiversity. Agricultural activities, particularly conventional crop protection (CP) practices, are a major threat to global biodiversity, ecosystem health and human health. Here we review interactions between CP practices and viral zoonoses (VZs), the first time this has been done. It should be noted that a) VZs stand at the interface between human, animal and ecosystem health; b) some VZs involve arthropod vectors that are affected by CP practices; and c) some crop pests, or their natural enemies are vertebrate reservoirs/carriers of certain VZs, and their contact with humans or domestic animals is affected by CP practices. Our review encompasses examples highlighting interactions between VZs and CP practices, both efficiency improvement-based (i.e. conventional with agrochemical insecticides and rodenticides), substitution-based (i.e. mainly with physical/mechanical or biopesticidal pest control), and redesign-based (i.e. mainly with conservation biological pest control, including some forms of crop-livestock integration). These CP practices mainly target arthropod and vertebrate pests. They also target, to a lesser extent, weeds and plant pathogens. Conventional and some physical/mechanical control methods and some forms of biopesticidal and crop-livestock integration practices were found to have mixed outcomes in terms of VZ risk management. Conversely, practices based on biological control by habitat conservation of arthropod or vertebrate natural enemies, falling within the Agroecological Crop Protection (ACP) framework, result in VZ prevention at various scales (local to global, and short-term to long-term). ACP addresses major global challenges including climate resilience, biodiversity conservation and animal welfare, and helps integrate plant health within the extended "One Health" concept.
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Affiliation(s)
- Alain Ratnadass
- CIRAD, UPR HortSys, F-97455 Saint-Pierre, Réunion, France; HortSys, Univ Montpellier, CIRAD, Montpellier, France.
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Ibarra-Zapata E, Gaytán-Hernández D, Gallegos-García V, González-Acevedo CE, Meza-Menchaca T, Rios-Lugo MJ, Hernández-Mendoza H. Geospatial modelling to estimate the territory at risk of establishment of influenza type A in Mexico - An ecological study. GEOSPATIAL HEALTH 2021; 16. [PMID: 34000788 DOI: 10.4081/gh.2021.956] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 03/16/2021] [Indexed: 06/12/2023]
Abstract
The aim of this study was to estimate the territory at risk of establishment of influenza type A (EOITA) in Mexico, using geospatial models. A spatial database of 1973 outbreaks of influenza worldwide was used to develop risk models accounting for natural (natural threat), anthropic (man-made) and environmental (combination of the above) transmission. Then, a virus establishment risk model; an introduction model of influenza A developed in another study; and the three models mentioned were utilized using multi-criteria spatial evaluation supported by geographically weighted regression (GWR), receiver operating characteristic analysis and Moran's I. The results show that environmental risk was concentrated along the Gulf and Pacific coasts, the Yucatan Peninsula and southern Baja California. The identified risk for EOITA in Mexico were: 15.6% and 4.8%, by natural and anthropic risk, respectively, while 18.5% presented simultaneous environmental, natural and anthropic risk. Overall, 28.1% of localities in Mexico presented a High/High risk for the establishment of influenza type A (area under the curve=0.923, P<0.001; GWR, r2=0.840, P<0.001; Moran's I =0.79, P<0.001). Hence, these geospatial models were able to robustly estimate those areas susceptible to EOITA, where the results obtained show the relation between the geographical area and the different effects on health. The information obtained should help devising and directing strategies leading to efficient prevention and sound administration of both human and financial resources.
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Affiliation(s)
- Enrique Ibarra-Zapata
- Center for Research and Postgraduate Studies, Faculty of Agronomy, Autonomous University of San Luis Potosí, San Luis Potosí, S.L.P..
| | - Darío Gaytán-Hernández
- Faculty of Nursing and Nutrition, Autonomous University of San Luis Potosí, San Luis Potosí, S.L.P..
| | - Verónica Gallegos-García
- Faculty of Nursing and Nutrition, Autonomous University of San Luis Potosí, San Luis Potosí, S.L.P..
| | | | - Thuluz Meza-Menchaca
- Laboratory of Human Genomics, Faculty of Medicine, Veracruzana University, Xalapa, Veracruz.
| | - María Judith Rios-Lugo
- Faculty of Nursing and Nutrition, Autonomous University of San Luis Potosí, San Luis Potosí, S.L.P..
| | - Héctor Hernández-Mendoza
- Desert Zones Research Institute, Autonomous University of San Luis Potosí, San Luis Potosí, S.L.P.; University of Central Mexico, San Luis Potosí, S.L.P..
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Rabinovich JE, Alvarez Costa A, Muñoz IJ, Schilman PE, Fountain-Jones NM. Machine-learning model led design to experimentally test species thermal limits: The case of kissing bugs (Triatominae). PLoS Negl Trop Dis 2021; 15:e0008822. [PMID: 33684127 PMCID: PMC7971882 DOI: 10.1371/journal.pntd.0008822] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 03/18/2021] [Accepted: 01/10/2021] [Indexed: 12/18/2022] Open
Abstract
Species Distribution Modelling (SDM) determines habitat suitability of a species across geographic areas using macro-climatic variables; however, micro-habitats can buffer or exacerbate the influence of macro-climatic variables, requiring links between physiology and species persistence. Experimental approaches linking species physiology to micro-climate are complex, time consuming and expensive. E.g., what combination of exposure time and temperature is important for a species thermal tolerance is difficult to judge a priori. We tackled this problem using an active learning approach that utilized machine learning methods to guide thermal tolerance experimental design for three kissing-bug species: Triatoma infestans, Rhodnius prolixus, and Panstrongylus megistus (Hemiptera: Reduviidae: Triatominae), vectors of the parasite causing Chagas disease. As with other pathogen vectors, triatomines are well known to utilize micro-habitats and the associated shift in microclimate to enhance survival. Using a limited literature-collected dataset, our approach showed that temperature followed by exposure time were the strongest predictors of mortality; species played a minor role, and life stage was the least important. Further, we identified complex but biologically plausible nonlinear interactions between temperature and exposure time in shaping mortality, together setting the potential thermal limits of triatomines. The results from this data led to the design of new experiments with laboratory results that produced novel insights of the effects of temperature and exposure for the triatomines. These results, in turn, can be used to better model micro-climatic envelope for the species. Here we demonstrate the power of an active learning approach to explore experimental space to design laboratory studies testing species thermal limits. Our analytical pipeline can be easily adapted to other systems and we provide code to allow practitioners to perform similar analyses. Not only does our approach have the potential to save time and money: it can also increase our understanding of the links between species physiology and climate, a topic of increasing ecological importance.
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Affiliation(s)
- Jorge E. Rabinovich
- Centro de Estudios Parasitológicos y de Vectores (CEPAVE CONICET-CCT La Plata, UNLP), National University of La Plata, La Plata, Argentina
| | - Agustín Alvarez Costa
- Laboratorio de Ecofisiología de Insectos, Departamento de Biodiversidad y Biología Experimental, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
- Instituto de Biodiversidad y Biología Experimental y Aplicada (IBBEA), CONICET–Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Ignacio J. Muñoz
- Laboratorio de Ecofisiología de Insectos, Departamento de Biodiversidad y Biología Experimental, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
- Instituto de Biodiversidad y Biología Experimental y Aplicada (IBBEA), CONICET–Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Pablo E. Schilman
- Laboratorio de Ecofisiología de Insectos, Departamento de Biodiversidad y Biología Experimental, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
- Instituto de Biodiversidad y Biología Experimental y Aplicada (IBBEA), CONICET–Universidad de Buenos Aires, Buenos Aires, Argentina
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7
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Moriguchi S, Hosoda R, Ushine N, Kato T, Hayama SI. Surveillance system for avian influenza in wild birds and implications of its improvement with insights into the highly pathogenic avian influenza outbreaks in Japan. Prev Vet Med 2020; 187:105234. [PMID: 33360671 DOI: 10.1016/j.prevetmed.2020.105234] [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: 05/11/2020] [Revised: 11/03/2020] [Accepted: 12/09/2020] [Indexed: 12/09/2022]
Abstract
Since the re-emergence of a highly pathogenic avian influenza (HPAI) in 2004, outbreaks of the viral subtypes HPAI, H5N1, H5N8, and H5N6 in wild birds, poultry, and zoo birds have occurred in Japan. In 2008, a nation-wide avian influenza (AI) surveillance program was started for the early detection of the HPAI virus (HPAIV) and for the assessment of HPAIV infection among wild birds. In this study, we aimed to conduct an overview of the AI surveillance system of wild birds in Japan, including those in the regions and prefectures, to assess its overall performance and develop insights on its improvement. We analyzed past surveillance data in Japan and conducted questionnaire surveys for the officers in 11 regional branches of the Ministry of Environment and the nature conservation divisions of 47 prefectures to acquire details regarding those AI surveillance. We found that the early detection of HPAIV in wild birds was successfully achieved in only one of the five outbreak seasons during the 2008-2019 period in Japan, and the assessment of HPAIV infection had possibly not been adequate in the national surveillance system. In the winter season, AI surveillance in most prefectures were mainly conducted by means of passive surveillance through reported dead birds and active surveillance through collected waterbird feces. Conversely, less than half of the prefectures conducted bird monitoring, patrolling in migratory bird habitats, and AI antigen testing in rescued birds. In areas surrounding HPAI occurrence sites (<10 km), bird monitoring and patrolling efforts were enhanced. However, AI testing efforts in waterbird feces and rescued birds were decreased. The AI surveillance for endangered bird species and in national wildlife protection areas was conducted by the branches of the Ministry of Environment and by the prefectures. Based on our results, we concluded that for maximum efficiency, legislation which specialized in wildlife pathogens should be necessary to prepare adequate national budget and testing capacity for appropriate surveillance system with periodical assessment for surveillance results and the system.
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Affiliation(s)
- Sachiko Moriguchi
- Laboratory of Wildlife Medicine, School of Veterinary Medicine, Nippon Veterinary and Life Science University, Tokyo, Japan.
| | - Rin Hosoda
- Laboratory of Wildlife Medicine, School of Veterinary Medicine, Nippon Veterinary and Life Science University, Tokyo, Japan
| | - Nana Ushine
- Laboratory of Wildlife Medicine, School of Veterinary Medicine, Nippon Veterinary and Life Science University, Tokyo, Japan
| | - Takuya Kato
- Laboratory of Wildlife Medicine, School of Veterinary Medicine, Nippon Veterinary and Life Science University, Tokyo, Japan
| | - Shin-Ichi Hayama
- Laboratory of Wildlife Medicine, School of Veterinary Medicine, Nippon Veterinary and Life Science University, Tokyo, Japan
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Belkhiria J, Hijmans RJ, Boyce W, Crossley BM, Martínez-López B. Identification of high risk areas for avian influenza outbreaks in California using disease distribution models. PLoS One 2018; 13:e0190824. [PMID: 29385158 PMCID: PMC5791985 DOI: 10.1371/journal.pone.0190824] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2017] [Accepted: 12/20/2017] [Indexed: 11/18/2022] Open
Abstract
The coexistence of different types of poultry operations such as free range and backyard flocks, large commercial indoor farms and live bird markets, as well as the presence of many areas where wild and domestic birds co-exist, make California susceptible to avian influenza outbreaks. The 2014-2015 highly pathogenic Avian Influenza (HPAI) outbreaks affecting California and other states in the United States have underscored the need for solutions to protect the US poultry industry against this devastating disease. We applied disease distribution models to predict where Avian influenza is likely to occur and the risk for HPAI outbreaks is highest. We used observations on the presence of Low Pathogenic Avian influenza virus (LPAI) in waterfowl or water samples at 355 locations throughout the state and environmental variables relevant to the disease epidemiology. We used two algorithms, Random Forest and MaxEnt, and two data-sets Presence-Background and Presence-Absence data. The models performed well (AUCc > 0.7 for testing data), particularly those using Presence-Background data (AUCc > 0.85). Spatial predictions were similar between algorithms, but there were large differences between the predictions with Presence-Absence and Presence-Background data. Overall, predictors that contributed most to the models included land cover, distance to coast, and broiler farm density. Models successfully identified several counties as high-to-intermediate risk out of the 8 counties with observed outbreaks during the 2014-2015 HPAI epizootics. This study provides further insights into the spatial epidemiology of AI in California, and the high spatial resolution maps may be useful to guide risk-based surveillance and outreach efforts.
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Affiliation(s)
- Jaber Belkhiria
- Center for Animal Disease Modeling and Surveillance, Department of Medicine & Epidemiology, School of Veterinary Medicine, University of California, Davis, California, United States of America
| | - Robert J Hijmans
- Department of Environmental Science & Policy, University of California, Davis, California, United States of America
| | - Walter Boyce
- Department of Pathology, Microbiology & Immunology, School of Veterinary Medicine, University of California, Davis, California, United States of America
| | - Beate M Crossley
- California Animal Health and Food Safety Lab, School of Veterinary Medicine, University of California, Davis, California, United States of America
| | - Beatriz Martínez-López
- Center for Animal Disease Modeling and Surveillance, Department of Medicine & Epidemiology, School of Veterinary Medicine, University of California, Davis, California, United States of America
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9
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Onuma M, Kakogawa M, Yanagisawa M, Haga A, Okano T, Neagari Y, Okano T, Goka K, Asakawa M. Characterizing the temporal patterns of avian influenza virus introduction into Japan by migratory birds. J Vet Med Sci 2017; 79:943-951. [PMID: 28484128 PMCID: PMC5447987 DOI: 10.1292/jvms.16-0604] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
The objectives of the present study were to observe the temporal pattern of avian influenza virus (AIV) introduction into Japan and to determine which migratory birds play an important role in introducing AIV. In total, 19,407
fecal samples from migratory birds were collected at 52 sites between October 2008 and May 2015. Total nucleic acids extracted from the fecal samples were subjected to reverse transcription loop–mediated isothermal amplification
to detect viral RNA. Species identification of host migratory birds was conducted by DNA barcoding for positive fecal samples. The total number of positive samples was 352 (prevalence, 1.8%). The highest prevalence was observed in
autumn migration, and a decrease in prevalence was observed. During autumn migration, central to southern Japan showed a prevalence higher than the overall prevalence. Thus, the main AIV entry routes may involve crossing the Sea
of Japan and entry through the Korean Peninsula. Species identification was successful in 221 of the 352 positive samples. Two major species sequences were identified: the Mallard/Eastern Spot-billed duck group (115 samples;
52.0%) and the Northern pintail (61 samples; 27.6%). To gain a better understanding of the ecology of AIV in Japan and the introduction pattern of highly pathogenic avian influenza viruses, information regarding AIV prevalence by
species, the prevalence of hatch-year migratory birds, migration patterns and viral subtypes in fecal samples using egg inoculation and molecular-based methods in combination is required.
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Affiliation(s)
- Manabu Onuma
- Ecological Risk Assessment and Control Section, Center for Environmental Biology and Ecosystem, National Institute for Environmental Studies, 16-2, Onogawa, Tsukuba, Ibaraki 305-8506, Japan
| | - Masayoshi Kakogawa
- Kobe Animal Kingdom, Kobe, Hyogo 650-0047, Japan.,Department of Pathobiology, Graduate School of Veterinary Medicine, Rakuno Gakuen University, Ebetsu, Hokkaido 069-8501, Japan
| | - Masae Yanagisawa
- Pathological and Physiochemical Examination Division, Laboratory Department, Animal Quarantine Service, 11-1, Haramachi, Isogoku, Yokohama, Kanagawa 235-0008, Japan
| | - Atsushi Haga
- Ecological Risk Assessment and Control Section, Center for Environmental Biology and Ecosystem, National Institute for Environmental Studies, 16-2, Onogawa, Tsukuba, Ibaraki 305-8506, Japan
| | - Tomomi Okano
- Ecological Genetics Analysis Section, Center for Environmental Biology and Ecosystem, National Institute for Environmental Studies, 16-2, Onogawa, Tsukuba, Ibaraki 305-8506, Japan
| | - Yasuko Neagari
- Biological Resource Laboratory, Laboratory for Intellectual Fundamentals for Environmental Studies, National Institute for Environmental Studies, 16-2, Onogawa, Tuskuba, Ibaraki 305-8506, Japan
| | - Tsukasa Okano
- Ecological Genetics Analysis Section, Center for Environmental Biology and Ecosystem, National Institute for Environmental Studies, 16-2, Onogawa, Tsukuba, Ibaraki 305-8506, Japan
| | - Koichi Goka
- Ecological Risk Assessment and Control Section, Center for Environmental Biology and Ecosystem, National Institute for Environmental Studies, 16-2, Onogawa, Tsukuba, Ibaraki 305-8506, Japan
| | - Mitsuhiko Asakawa
- Department of Pathobiology, Graduate School of Veterinary Medicine, Rakuno Gakuen University, Ebetsu, Hokkaido 069-8501, Japan
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Influenza A H5N1 and H7N9 in China: A spatial risk analysis. PLoS One 2017; 12:e0174980. [PMID: 28376125 PMCID: PMC5380336 DOI: 10.1371/journal.pone.0174980] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2016] [Accepted: 03/19/2017] [Indexed: 11/19/2022] Open
Abstract
Background Zoonotic avian influenza poses a major risk to China, and other parts of the world. H5N1 has remained endemic in China and globally for nearly two decades, and in 2013, a novel zoonotic influenza A subtype H7N9 emerged in China. This study aimed to improve upon our current understanding of the spreading mechanisms of H7N9 and H5N1 by generating spatial risk profiles for each of the two virus subtypes across mainland China. Methods and findings In this study, we (i) developed a refined data set of H5N1 and H7N9 locations with consideration of animal/animal environment case data, as well as spatial accuracy and precision; (ii) used this data set along with environmental variables to build species distribution models (SDMs) for each virus subtype in high resolution spatial units of 1km2 cells using Maxent; (iii) developed a risk modelling framework which integrated the results from the SDMs with human and chicken population variables, which was done to quantify the risk of zoonotic transmission; and (iv) identified areas at high risk of H5N1 and H7N9 transmission. We produced high performing SDMs (6 of 8 models with AUC > 0.9) for both H5N1 and H7N9. In all our SDMs, H7N9 consistently showed higher AUC results compared to H5N1, suggesting H7N9 suitability could be better explained by environmental variables. For both subtypes, high risk areas were primarily located in south-eastern China, with H5N1 distributions found to be more diffuse and extending more inland compared to H7N9. Conclusions We provide projections of our risk models to public health policy makers so that specific high risk areas can be targeted for control measures. We recommend comparing H5N1 and H7N9 prevalence rates and survivability in the natural environment to better understand the role of animal and environmental transmission in human infections.
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Belkhiria J, Alkhamis MA, Martínez-López B. Application of Species Distribution Modeling for Avian Influenza surveillance in the United States considering the North America Migratory Flyways. Sci Rep 2016; 6:33161. [PMID: 27624404 PMCID: PMC5021976 DOI: 10.1038/srep33161] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2016] [Accepted: 08/23/2016] [Indexed: 02/06/2023] Open
Abstract
Highly Pathogenic Avian Influenza (HPAI) has recently (2014-2015) re-emerged in the United States (US) causing the largest outbreak in US history with 232 outbreaks and an estimated economic impact of $950 million. This study proposes to use suitability maps for Low Pathogenic Avian Influenza (LPAI) to identify areas at high risk for HPAI outbreaks. LPAI suitability maps were based on wild bird demographics, LPAI surveillance, and poultry density in combination with environmental, climatic, and socio-economic risk factors. Species distribution modeling was used to produce high-resolution (cell size: 500m x 500m) maps for Avian Influenza (AI) suitability in each of the four North American migratory flyways (NAMF). Results reveal that AI suitability is heterogeneously distributed throughout the US with higher suitability in specific zones of the Midwest and coastal areas. The resultant suitability maps adequately predicted most of the HPAI outbreak areas during the 2014-2015 epidemic in the US (i.e. 89% of HPAI outbreaks were located in areas identified as highly suitable for LPAI). Results are potentially useful for poultry producers and stakeholders in designing risk-based surveillance, outreach and intervention strategies to better prevent and control future HPAI outbreaks in the US.
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Affiliation(s)
- Jaber Belkhiria
- Center for Animal Disease Modeling and Surveillance, Department of Medicine & Epidemiology, School of Veterinary Medicine, University of California Davis, California, United States of America
| | - Moh A. Alkhamis
- Environmental & Life Sciences Research Center, Kuwait Institute for Scientific Research, Kuwait
- Veterinary Population Medicine Department, Veterinary Medical Center, University of Minnesota, St. Paul, Minnesota, United States of America
| | - Beatriz Martínez-López
- Center for Animal Disease Modeling and Surveillance, Department of Medicine & Epidemiology, School of Veterinary Medicine, University of California Davis, California, United States of America
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Predicting Avian Influenza Co-Infection with H5N1 and H9N2 in Northern Egypt. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2016; 13:ijerph13090886. [PMID: 27608035 PMCID: PMC5036719 DOI: 10.3390/ijerph13090886] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/18/2016] [Revised: 08/22/2016] [Accepted: 09/01/2016] [Indexed: 11/26/2022]
Abstract
Human outbreaks with avian influenza have been, so far, constrained by poor viral adaptation to non-avian hosts. This could be overcome via co-infection, whereby two strains share genetic material, allowing new hybrid strains to emerge. Identifying areas where co-infection is most likely can help target spaces for increased surveillance. Ecological niche modeling using remotely-sensed data can be used for this purpose. H5N1 and H9N2 influenza subtypes are endemic in Egyptian poultry. From 2006 to 2015, over 20,000 poultry and wild birds were tested at farms and live bird markets. Using ecological niche modeling we identified environmental, behavioral, and population characteristics of H5N1 and H9N2 niches within Egypt. Niches differed markedly by subtype. The subtype niches were combined to model co-infection potential with known occurrences used for validation. The distance to live bird markets was a strong predictor of co-infection. Using only single-subtype influenza outbreaks and publicly available ecological data, we identified areas of co-infection potential with high accuracy (area under the receiver operating characteristic (ROC) curve (AUC) 0.991).
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13
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Moriguchi S, Onuma M, Goka K. Spatial assessment of the potential risk of avian influenza A virus infection in three raptor species in Japan. J Vet Med Sci 2016; 78:1107-15. [PMID: 26972333 PMCID: PMC4976265 DOI: 10.1292/jvms.15-0551] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Avian influenza A, a highly pathogenic avian influenza, is a lethal infection in certain
species of wild birds, including some endangered species. Raptors are susceptible to avian
influenza, and spatial risk assessment of such species may be valuable for conservation
planning. We used the maximum entropy approach to generate potential distribution models
of three raptor species from presence-only data for the mountain hawk-eagle
Nisaetus nipalensis, northern goshawk Accipiter
gentilis and peregrine falcon Falco peregrinus, surveyed
during the winter from 1996 to 2001. These potential distribution maps for raptors were
superimposed on avian influenza A risk maps of Japan, created from data on incidence of
the virus in wild birds throughout Japan from October 2010 to March 2011. The avian
influenza A risk map for the mountain hawk-eagle showed that most regions of Japan had a
low risk for avian influenza A. In contrast, the maps for the northern goshawk and
peregrine falcon showed that their high-risk areas were distributed on the plains along
the Sea of Japan and Pacific coast. We recommend enhanced surveillance for each raptor
species in high-risk areas and immediate establishment of inspection systems. At the same
time, ecological risk assessments that determine factors, such as the composition of prey
species, and differential sensitivity of avian influenza A virus between bird species
should provide multifaceted insights into the total risk assessment of endangered
species.
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Affiliation(s)
- Sachiko Moriguchi
- Invasive Alien Species Research Team, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan
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Sero-surveillance and risk factors for avian influenza and Newcastle disease virus in backyard poultry in Oman. Prev Vet Med 2015; 122:145-53. [DOI: 10.1016/j.prevetmed.2015.09.011] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2015] [Revised: 09/08/2015] [Accepted: 09/20/2015] [Indexed: 11/21/2022]
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15
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Qiu J, Li R, Xu X, Hong X, Xia X, Yu C. Spatiotemporal pattern and risk factors of the reported novel avian-origin influenza A(H7N9) cases in China. Prev Vet Med 2014; 115:229-37. [DOI: 10.1016/j.prevetmed.2014.03.030] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2013] [Revised: 03/27/2014] [Accepted: 03/28/2014] [Indexed: 12/09/2022]
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