ArticlePloS one2017
Influenza A H5N1 and H7N9 in China: A spatial risk analysis.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Ecology and environment predict spatially stratified risk of H5 highly pathogenic avian influenza clade 2.3.4.4b in wild birds across Europe.Scientific reports · 2025Article
- Development of a zoonotic influenza distribution assessment and ranking system (ZIDAR): Technical application in Nepal to support cross-sectoral risk-based surveillance.One health (Amsterdam, Netherlands) · 2025Article
- Environmental monitoring and spatiotemporal trend analysis of avian influenza virus in Xinjiang, 2021-2023.BMC infectious diseases · 2025Article
- Investigation of human infection with H5N6 avian influenza cases in Sichuan Province from 2014 to 2024: a retrospective study.Frontiers in public health · 2025Article
- Based on the MaxEnt model the analysis of influencing factors and simulation of potential risk areas of human infection with avian influenza A (H7N9) in China.Frontiers in cellular and infection microbiology · 2024Article
- Evaluation of Pre-Pandemic Trivalent COBRA HA Vaccine in Mice Pre-Immune to Historical H1N1 and H3N2 Influenza Viruses.Viruses · 2023Article
- Effects of Receptor Specificity and Conformational Stability of Influenza A Virus Hemagglutinin on Infection and Activation of Different Cell Types in Human PBMCs.Frontiers in immunology · 2022Article
- Designing a multi-epitope vaccine to provoke the robust immune response against influenza A H7N9.Scientific reports · 2021Article
- A framework for the risk prediction of avian influenza occurrence: An Indonesian case study.PloS one · 2021Article
- Spatial modeling, risk mapping, change detection, and outbreak trend analysis of coronavirus (COVID-19) in Iran (days between February 19 and June 14, 2020).International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2020Article
- Emergence of human avian influenza A(H7N9) virus infections in Wenshan City in Southwest China, 2017.BMC infectious diseases · 2020Article
- Identifying Risk Factors Of A(H7N9) Outbreak by Wavelet Analysis and Generalized Estimating Equation.International journal of environmental research and public health · 2019Article
- Characterising routes of H5N1 and H7N9 spread in China using Bayesian phylogeographical analysis.Emerging microbes & infections · 2018Article
- The temporal distribution of new H7N9 avian influenza infections based on laboratory-confirmed cases in Mainland China, 2013-2017.Scientific reports · 2018Article
- Avian influenza overview October 2016-August 2017.EFSA journal. European Food Safety Authority · 2017Article
- Article
Corrections and comments
- Erratum issued
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundZoonotic 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
findingsIn 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.
conclusionsWe 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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