H7N9 and H5N1 avian influenza suitability models for China: accounting for new poultry and live-poultry markets distribution data

In the last two decades, two important avian influenza viruses infecting humans emerged in China, the highly pathogenic avian influenza (HPAI) H5N1 virus in the late nineties, and the low pathogenic avian influenza (LPAI) H7N9 virus in 2013. China is home to the largest population of chickens (4.83 billion) and ducks (0.694 billion), representing, respectively 23.1 and 58.6% of the 2013 world stock, with a significant part of poultry sold through live-poultry markets potentially contributing to the spread of avian influenza viruses. Previous models have looked at factors associated with HPAI H5N1 in poultry and LPAI H7N9 in markets. However, these have not been studied and compared with a consistent set of predictor variables. Significant progress was recently made in the collection of poultry census and live-poultry market data, which are key potential factors in the distribution of both diseases. Here we compiled and reprocessed a new set of poultry census data and used these to analyse HPAI H5N1 and LPAI H7N9 distributions with boosted regression trees models. We found a limited impact of the improved poultry layers compared to models based on previous poultry census data, and a positive and previously unreported association between HPAI H5N1 outbreaks and the density of live-poultry markets. In addition, the models fitted for the HPAI H5N1 and LPAI H7N9 viruses predict a high risk of disease presence for the area around Shanghai and Hong Kong. The main difference in prediction between the two viruses concerned the suitability of HPAI H5N1 in north-China around the Yellow sea (outlined with Tianjin, Beijing, and Shenyang city) where LPAI H7N9 has not spread intensely.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Potential Geographic Distribution of the Novel Avian-Origin Influenza A (H7N9) Virus

Background In late March 2013, a new avian-origin influenza virus emerged in eastern China. This H7N9 subtype virus has since infected 240 people and killed 60, and has awakened global concern as a potential pandemic threat. Ecological niche modeling has seen increasing applications as a useful tool in mapping geographic potential and risk of disease transmission. Methodology/Principals We developed two datasets based on seasonal variation in Normalized Difference Vegetation Index (NDVI) from the MODIS sensor to characterize environmental dimensions of H7N9 virus. One-third of well-documented cases was used to test robustness of models calibrated based on the remaining two-thirds, and model significance was tested using partial ROC approaches. A final niche model was calibrated using all records available. Conclusions/Significance Central-eastern China appears to represent an area of high risk for H7N9 spread, but suitable areas were distributed more spottily in the north and only along the coast in the south; highly suitable areas also were identified in western Taiwan. Areas identified as presenting high risk for H7N9 spread tend to present consistent NDVI values through the year, whereas unsuitable areas show greater seasonal variation.No current funding sources were specifically designate for this study, however, partial support was from the talent introduction program award to GZ in Tianjin Normal University (5RL127). No additional funding was received for this study. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

H7N9 and H5N1 avian influenza suitability models for China: accounting for new poultry and live-poultry markets distribution data

Risk maps are one of several sources used to inform risk-based disease surveillance and control systems, but their production can be hampered by lack of access to suitable disease data. In such situations, knowledge-driven spatial modeling methods are an alternative to data-driven approaches. This study used multicriteria decision analysis (MCDA) to identify areas in Asia suitable for the occurrence of highly pathogenic avian influenza virus (HPAIV) H5N1 in domestic poultry. Areas most suitable for H5N1 occurrence included Bangladesh, the southern tip and eastern coast of Vietnam, parts of north-central Thailand and large parts of eastern China. The predictive accuracy of the final model, as determined by the area under the receiver operating characteristic curve (ROC AUC), was 0.670 (95% CI 0.667-0.673) suggesting that, in data-scarce environments, MCDA provides a reasonable alternative to the data-driven approaches usually used to inform risk-based disease surveillance and control strategies

Influenza A H5N1 and H7N9 in China: A spatial risk analysis

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 1km[superscript 2] 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.The article is published at http://journals.plos.org/plosone/article?id=10.1371/journal.pone.017498

Live poultry trading drives China's H7N9 viral evolution and geographical network propagation

The on-going reassortment, human-adapted mutations, and spillover events of novel A(H7N9) avian influenza viruses pose a significant challenge to public health in China and globally. However, our understanding of the factors that disseminate the viruses and drive their geographic distributions is limited. We applied phylogenic analysis to examine the inter-subtype interactions between H7N9 viruses and the closest H9N2 lineages in China during 2010–2014. We reconstructed and compared the inter-provincial live poultry trading and viral propagation network via phylogeographic approach and network similarity technique. The substitution rates of the isolated viruses in live poultry markets and the characteristics of localized viral evolution were also evaluated. We discovered that viral propagation was geographically-structured and followed the live poultry trading network in China, with distinct north-to-east paths of spread and circular transmission between eastern and southern regions. The epicenter of H7N9 has moved from the Shanghai–Zhejiang region to Guangdong Province was also identified. Besides, higher substitution rate was observed among isolates sampled from live poultry markets, especially for those H7N9 viruses. Live poultry trading in China may have driven the network-structured expansion of the novel H7N9 viruses. From this perspective, long-distance geographic expansion of H7N9 were dominated by live poultry movements, while at local scales, diffusion was facilitated by live poultry markets with highly-evolved viruses

The Socioeconomic and Ecological Drivers of Avian Influenza Risks in China and at the International Level

abstract: Avian influenzas are zoonoses, or pathogens borne by wildlife and livestock that can also infect people. In recent decades, and especially since the emergence of highly pathogenic avian influenza (HPAI) H5N1 in 1996, these diseases have become a significant threat to animal and public health across the world. HPAI H5N1 has caused severe damage to poultry populations, killing, or prompting the culling of, millions of birds in Asia, Africa, and Europe. It has also infected hundreds of people, with a mortality rate of approximately 50%. This dissertation focuses on the ecological and socioeconomic drivers of avian influenza risk, particularly in China, the most populous country to be infected. Among the most significant ecological risk factors are landscapes that serve as “mixing zones” for wild waterfowl and poultry, such as rice paddy, and nearby lakes and wetlands that are important breeding and wintering habitats for wild birds. Poultry outbreaks often involve cross infections between wild and domesticated birds. At the international level, trade in live poultry can spread the disease, especially if the imports are from countries not party to trade agreements with well-developed biosecurity standards. However, these risks can be mitigated in a number of ways. Protected habitats, such as Ramsar wetlands, can segregate wild bird and poultry populations, thereby lowering the chance of interspecies transmission. The industrialization of poultry production, while not without ethical and public health problems, can also be risk-reducing by causing wild-domestic segregation and allowing for the more efficient application of surveillance, vaccination, and other biosecurity measures. Disease surveillance is effective at preventing the spread of avian influenza, including across international borders. Economic modernization in general, as reflected in rising per-capita GDP, appears to mitigate avian influenza risks at both the national and sub-national levels. Poultry vaccination has been effective in many cases, but is an incomplete solution because of the practical difficulties of sustained and widespread implementation. The other popular approach to avian influenza control is culling, which can be highly expensive and raise ethical concerns about large-scale animal slaughter. Therefore, it is more economically efficient, and may even be more ethical, to target the socio-ecological drivers of avian influenza risks, including by implementing the policies discussed here.Dissertation/ThesisDoctoral Dissertation Biology 201

Network and Algebraic Topology of Influenza Evolution

Evolution is a force that has molded human existence since its divergence from chimpanzees about 5.4 million years ago. In that same amount of time, an influenza virus, which replicates every six hours, would have undergone an equivalent number of generations over only a hundred years. The fast replication times of influenza, coupled with its high mutation rate, make the virus a perfect model to study real-time evolution at a mega-Darwin scale, more than a million times faster than human evolution. While recent developments in high-throughput sequencing provide an optimal opportunity to dissect their genetic evolution, a concurrent growth in computational tools is necessary to analyze the large influx of complex genomic data. In my thesis, I present novel computational methods to examine different aspects of influenza evolution. I first focus on seasonal influenza, particularly the problems that hamper public health initiatives to combat the virus. I introduce two new approaches: 1. The q2-coefficient, a method of quantifying pathogen surveillance, and 2. FluGraph, a technique that employs network topology to track the spread of seasonal influenza around the world. The second chapter of my thesis examines how mutations and reassortment combine to alter the course of influenza evolution towards pandemic formation. I highlight inherent deficiencies in the current phylogenetic paradigm for analyzing evolution and offer a novel methodology based on algebraic topology that comprehensively reconstructs both vertical and horizontal evolutionary events. I apply this method to viruses, with emphasis on influenza, but foresee broader application to cancer cells, bacteria, eukaryotes, and other taxa

Host and tissue tropisms of avian influenza A viruses

Wild birds are the natural reservoirs of Influenza A viruses (IAVs) which cause occasional pandemics and seasonal epidemics. Avian IAVs can be transmitted from wild birds to domestic poultry, low mammals, and humans. It is well accepted that avian IAVs prefer to sialic acids (Sia) α2,3-linked galactose (SAα2,3-Gal), whereas human IAVs to α2,6-linked galactose (SAα2,6-Gal). However, SAα2,3-Gal in wild bird tissues is widely distributed with little variation while some subtypes of avian IAVs have species preference. The different isolation rates among wild bird species cannot be explained by avian IAVs binding to SAα2,3-Gal alone. Specifically, this dissertation had the following aims: Firstly, to determine distribution of glycan receptors across respiratory and gastrointestinal tissues of wild birds and domestic poultry; Secondly, to determine the viral-receptor binding specificity of avian IAVs; Thirdly, to understand the role of glycan motifs in shaping virus evolution during the natural history of IAVs, especially from wild bird to poultry transmission. We found that avian H7 and H10 viruses acquired the binding ability to SAα2,6-Gal without adaptation, furthermore, we evaluated one of these H10 virus that possess the ability of binding to SAα2,6-Gal in ferret model and found it could cause aerosol and contact transmissions. On the other hand, H7 viruses have strong binding avidity to SLex which are present widely in epithelial cells of chicken trachea, which could facilitate the transmission of avian H7 viruses from waterfowl to poultry. Lastly, we found that H7 viruses from waterfowl bound both Neu5Ac and Neu5Gc while chicken isolates from China only prefer to Neu5Ac. Of interest, we found Neu5Gc was found in mallards but not in chickens, which indicated that viruses reduce or lost binding ability to Neu5Gc by adapting in chicken. In summary, this dissertation focused on certain subtypes of avian IAVs, which have caused threats to domestic poultry and public health, and primary avian species for influenza risk. The glycan substructures may play an important role in avian IAVs transmission and adaptation. The knowledge derived from this dissertation will help identify species for influenza surveillance in wild birds and facilitate risk assessment of avian IAVs