Anthropogenic factors and the risk of highly pathogenic avian influenza H5N1: prospects from a spatial-based model

Spatio-temporal dynamics and drivers of highly pathogenic avian influenza H5N1 in Chile

Introduction

Highly pathogenic avian influenza A H5N1 clade 2.3.4.4b (hereafter H5N1) is causing vast impacts on biodiversity and poultry around the globe. In Chile, lethal H5N1 cases have been reported in a wide range of wild bird species, marine mammals, backyard and industrial poultry, and humans. This study describes the spatio-temporal patterns of the current epizootic of H5N1 in Chile and test drivers that could be associated with outbreak occurrence.

Methods

We used H5N1 cases reported by the Chilean National Animal Health Authority from 5 December 2022 to 5 April 2023. These included wild bird cases confirmed through an avian influenza-specific real-time reverse transcription PCR assay (RT-qPCR), obtained from passive and active surveillance. Data were analyzed to detect the presence of H5N1 clusters under space-time permutation probability modeling, the association of H5N1 with distance and days since the first outbreak through linear regression, and the correlation of H5N1 presence with a number of ecological and anthropogenic variables using general linear modeling.

Results

From 445 H5N1 identified outbreaks involving 613 individual cases in wild birds, a consistent wave-like spread of H5N1 from north to south was identified, which may help predict hotspots of outbreak risk. For instance, seven statistically significant clusters were identified in central and northern Chile, where poultry production and wildlife mortality are concentrated. The presence of outbreaks was correlated with landscape-scale variables, notably temperature range, bird richness, and human footprint.

Discussion

In less than a year, H5N1 has been associated with the unusual mortality of >100,000 individuals of wild animals in Chile, mainly coastal birds and marine mammals. It is urgent that scientists, the poultry sector, local communities, and national health authorities co-design and implement science-based measures from a One Health perspective to avoid further H5N1 spillover from wildlife to domestic animals and humans, including rapid removal and proper disposal of wild dead animals and the closure of public areas (e.g., beaches) reporting high wildlife mortalities.

Multifaceted analysis of temporal and spatial distribution and risk factors of global poultry HPAI-H5N1, 2005-2023

The purpose of this study was to analyze the characteristics of occurrence and spread of highly pathogenic avian influenza H5N1 (HPAI-H5N1) globally, understand its spatiotemporal characteristics, investigate the risk factors influencing outbreaks, and identify high-risk areas for disease occurrence. We collected the data on global poultry HPAI-H5N1 outbreaks from January 2005 to April 2023, and conducted a thorough analysis of the spatial and temporal characteristics of the disease through time series decomposition and directional distribution analysis. Additionally, an ecological niche model was established to explore the major factors influencing the occurrence of HPAI-H5N1 and to pinpoint high-risk areas. Our findings revealed that HPAI-H5N1 outbreaks were cyclical, and seasonal, exhibiting a rising trend, with a predominant northwest-southeast transmission direction. The ecological niche model highlighted that species factors and economic trade factors are critical in influencing the outbreak of HPAI-H5N1. Variables such as chicken and duck density, population density, isothermality, and road density, contributed to importantly risk of outbreaks. High-risk areas for HPAI-H5N1 occurrence were primarily identified in Europe, West Africa, Southeast Asia, and Southeast China. This study provided valuable insights into the spatial and temporal distribution characteristics and risk factors of global poultry HPAI-H5N1 outbreaks. The identification of high-risk areas provides essential information that can be used to develop more effective prevention and control policies.

A case-control study of the infection risk of H5N8 highly pathogenic avian influenza in Japan during the winter of 2020-2021

In Japan, outbreaks of H5N8 highly pathogenic avian influenza (HPAI) were reported between November 2020 and March 2021 in 52 poultry farms. Understanding HPAI epidemiology would help poultry industries improve their awareness of the disease and enhance the immediate implementation of biosecurity measures. This study was a simulation-based matched case-control study to elucidate the risk factors associated with HPAI outbreaks in chicken farms in Japan. Data were collected from 42 HPAI-affected farms and 463 control farms that were within a 5-km radius of each case farm but remained uninfected. When infected farms were detected as clusters, one farm was randomly selected from each cluster, considering the possibility that the cluster was formed by farm-to-farm transmission within an epidemic area. For each case farm, up to three control farms were selected within a 5-km radius. Overall, 26 case farms (16 layer and 10 broiler farms) and 75 control farms (45 layer and 30 broiler farms) were resampled 1000 times for the conditional logistic regression model with explanatory variables comprising geographical factors and farm flock size. A larger flock size and shorter distance to water bodies from the farm were found to increase infection risk in layer farms. Similarly, in broiler farms, a shorter distance to water bodies increased infection risk. On larger farms, frequent access of farm staff and instrument carriages to premises could lead to increased infection risk. Waterfowl visiting water bodies around farms may also be associated with infection risk.

The role of vaccination and environmental factors on outbreaks of high pathogenicity avian influenza H5N1 in Bangladesh

High Pathogenicity Avian Influenza (HPAI) H5N1 outbreaks continue to wreak havoc on the global poultry industry and threaten the health of wild bird populations, with sporadic spillover in humans and other mammals, resulting in widespread calls to vaccinate poultry. Bangladesh has been vaccinating poultry since 2012, presenting a prime opportunity to study the effects of vaccination on HPAI H5N1circulation in both poultry and wild birds. We investigated the efficacy of vaccinating commercial poultry against HPAI H5N1 along with climatic and socio-economic factors considered potential drivers of HPAI H5N1 outbreak risk in Bangladesh. Using a multivariate modeling approach, we estimated that the rate of outbreaks was 18 times higher before compared to after vaccination, with winter months having a three times higher chance of outbreaks than summer months. Variables resulting in small but significant increases in outbreak rate were relatively low ambient temperatures for the time of year, literacy rate, chicken and duck density, crop density, and presence of highways; this may be attributable to low temperatures supporting viral survival outside the host, higher literacy driving reporting rate, density of the host reservoir, and spread of the virus through increased connectivity. Despite the substantial impact of vaccination on outbreaks, we note that HPAI H5N1 is still enzootic in Bangladesh; vaccinated poultry flocks have high rates of H5N1 prevalence, and spillover to wild birds has increased. Vaccination in Bangladesh thus bears the risk of supporting "silent spread," where the vaccine only provides protection against disease and not also infection. Our findings underscore that poultry vaccination can be part of holistic HPAI mitigation strategies when accompanied by monitoring to avoid silent spread.

Emerging and re-emerging zoonotic viral diseases in Southeast Asia: One Health challenge

The ongoing significant social, environmental, and economic changes in Southeast Asia (SEA) make the region highly vulnerable to the emergence and re-emergence of zoonotic viral diseases. In the last century, SEA has faced major viral outbreaks with great health and economic impact, including Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), arboviruses, highly pathogenic avian influenza (H5N1), and Severe Acute Respiratory Syndrome (SARS-CoV); and so far, imported cases of Middle East Respiratory Syndrome Coronavirus (MERS-CoV). Given the recent challenging experiences in addressing emerging zoonotic diseases, it is necessary to redouble efforts to effectively implement the "One Health" initiative in the region, which aims to strengthen the human-animal-plant-environment interface to better prevent, detect and respond to health threats while promoting sustainable development. This review provides an overview of important emerging and re-emerging zoonotic viral diseases in SEA, with emphasis on the main drivers behind their emergency, the epidemiological situation from January 2000 to October 2022, and the importance of One Health to promote improved intervention strategies.

Risk Prediction of Three Different Subtypes of Highly Pathogenic Avian Influenza Outbreaks in Poultry Farms: Based on Spatial Characteristics of Infected Premises in South Korea

From 2003 to 2017, highly pathogenic avian influenza (HPAI) epidemics, particularly H5N1, H5N8, and H5N6 infections in poultry farms, increased in South Korea. More recently, these subtypes of HPAI virus resurged and spread nationwide, heavily impacting the entire poultry production and supply system. Most outbreaks in poultry holdings were concentrated in the southwestern part of the country, accounting for 58.3% of the total occurrences. This geographically persistent occurrence demanded the investigation of spatial risk factors related to the HPAI outbreak and the prediction of the risk of emerging HPAI outbreaks. Therefore, we investigated 12 spatial variables for the three subtypes of HPAI virus-infected premises [(IPs), 88 H5N1, 339 H5N8, and 335 H5N6 IPs]. Then, two prediction models using statistical and machine learning algorithm approaches were built from a case-control study on HPAI H5N8 epidemic, the most prolonged outbreak, in 339 IPs and 626 non-IPs. Finally, we predicted the risk of HPAI H5N1 and H5N6 occurrence at poultry farms using a Bayesian logistic regression and machine learning algorithm model [extreme gradient boosting (XGBoost) model] built on the case-control study. Several spatial variables showed similar distribution between two subtypes of IPs, although there were distinct heterogeneous distributions of spatial variables among the three IP subtypes. The case-control study indicated that the density of domestic duck farms and the minimum distance to live bird markets were leading risk factors for HPAI outbreaks. The two prediction models showed high predictive performance for H5N1 and H5N6 occurrences [an area under the curve (AUC) of receiver operating characteristic of Bayesian model > 0.82 and XGBoost model > 0.97]. This finding emphasizes that spatial characteristics of the poultry farm play a vital role in the occurrence and forecast of HPAI outbreaks. Therefore, this finding is expected to contributing to developing prevention and control strategies.

Spatiotemporal analysis of highly pathogenic avian influenza (H5N1) outbreaks in poultry in Egypt (2006 to 2017)

Background

In Egypt, the highly pathogenic avian influenza (HPAI) subtype H5N1 is endemic and possesses a severe impact on the poultry. To provide a better understanding of the distributional characteristics of HPAI H5N1 outbreaks in Egypt, this study aimed to explore the spatiotemporal pattern and identify clusters of HPAI H5N1 outbreaks in Egypt from 2006 to 2017.

Results

The Epidemic curve (EC) was constructed through time series analysis; in which six epidemic waves (EWs) were revealed. Outbreaks mainly started in winter peaked in March and ended in summer. However, newly emerged thermostable clades (2.2.1.1 and 2.2.1.2) during the 4th EW enabled the virus to survive and cause infection in warmer months with a clear alteration in the seasonality of the epidemic cycle in the 5th EW. The endemic situation became more complicated by the emergence of new serotypes. As a result, the EC ended up without any specific pattern since the 6th EW to now. The spatial analysis showed that the highest outbreak density was recorded in the Nile Delta considering it as the ‘Hot spot’ region. By the 6th EW, the outbreak extended to include the Nile valley. From spatiotemporal cluster epidemics, clustering in the Delta was a common feature in all EWs with primary clusters consistently detected in the hot-spot region, but the location and size varied with each EW. The highest Relative Risk (RR) regions in an EW were noticed to contain the primary clusters of the next EW and were found to include stopover sites for migratory wild birds. They were in Fayoum, Dakahlia, Qalyobiya, Sharkia, Kafr_Elsheikh, Giza, Behera, Menia, and BeniSuef governorates. Transmission of HPAI H5N1 occurred from one location to another directly resulted in a series of outbreaks forming neighboring secondary clusters. The absence of geographical borders between the governorates in addition to non-restricted movements of poultry and low vaccination and surveillance coverage contributed to the wider spread of infection all over Egypt and to look like one epidemiological unit.

Conclusion

Our findings can help in better understanding of the characteristics of HPAI H5N1 outbreaks and the distribution of outbreak risk, which can be used for effective disease control strategies.

Graphical abstract

Preventive effect of on-farm biosecurity practices against highly pathogenic avian influenza (HPAI) H5N6 infection on commercial layer farms in the Republic of Korea during the 2016-17 epidemic: A case-control study

Highly pathogenic avian influenza virus (HPAIv) H5N6 has destructive consequences on the global poultry production system. Recently, a growing number of layer farms have been heavily damaged from the HPAIv epidemic due to the increased virulence of the virus and the intensification of the production system. Therefore, stakeholders should implement effective preventive practices at the farm level that are aligned with contingency measures at the national level to minimize poultry losses. However, numerous biosecurity protocols for layer farm workers to follow have been developed, impeding efficient prevention and control. Furthermore, the effectiveness of biosecurity practices varies with the geographical condition and inter-farm contact structures. Hence, the objective of our study was to examine the preventive effect of five biosecurity actions commonly practiced at layer farms in the Republic of Korea against HPAIv H5N6: (i) fence installation around a farm, ii) rodent control inside a farm; iii) disinfection booth for visitors for disinfection protocols, iv) an anterior room in the sheds before entering the bird area and v) boots changes when moving between sheds in the same farm. We conducted a case-control study on 114 layer case farms and 129 layer control farms during the 2016-17 HPAI epidemic. The odds ratios for five on-farm biosecurity practices implemented in those study groups were estimated as a preventive effect on the HPAI infection with covariates, including seven geographical conditions and three network metrics using Bayesian hierarchical logistic regression and geographical location weighted logistic regression. The results showed that the use of a disinfection booth for personnel reduced the odds of HPAIv H5N6 infection (adjusted odds ratio [AOR] = 0.002, 95 % credible interval [CrI] = 0.00007 - 0.025) with relatively small spatial variation (minimum AOR - maximum AOR: 0.084-0.263). Changing boots between sheds on the same farm reduced the odds of HPAIv H5N6 infection (AOR = 0.160, 95 % CrI = 0.024-0.852) with relatively wide spatial variation (minimum AOR - maximum AOR = 0.270-0.688). Therefore, enhanced personnel biosecurity protocols at the farm of entry for layer farms is recommended to effectively prevent and respond to HPAIv H5N6 infection under different local condition. Our study provides an important message for layer farmers to effectively implement on-farm biosecurity actions against HPAIv H5N6 infection at their farms by setting priorities based on their spatial condition and network position.

Two-stage algorithms for visually exploring spatio-temporal clustering of avian influenza virus outbreaks in poultry farms

The development of visual tools for the timely identification of spatio-temporal clusters will assist in implementing control measures to prevent further damage. From January 2015 to June 2020, a total number of 1463 avian influenza outbreak farms were detected in Taiwan and further confirmed to be affected by highly pathogenic avian influenza subtype H5Nx. In this study, we adopted two common concepts of spatio-temporal clustering methods, the Knox test and scan statistics, with visual tools to explore the dynamic changes of clustering patterns. Since most (68.6%) of the outbreak farms were detected in 2015, only the data from 2015 was used in this study. The first two-stage algorithm performs the Knox test, which established a threshold of 7 days and identified 11 major clusters in the six counties of southwestern Taiwan, followed by the standard deviational ellipse (SDE) method implemented on each cluster to reveal the transmission direction. The second algorithm applies scan likelihood ratio statistics followed by AGC index to visualize the dynamic changes of the local aggregation pattern of disease clusters at the regional level. Compared to the one-stage aggregation approach, Knox-based and AGC mapping were more sensitive in small-scale spatio-temporal clustering.

Analyzing Spatial Dependency of the 2016-2017 Korean HPAI Outbreak to Determine the Effective Culling Radius

Highly pathogenic avian influenza (HPAI) outbreaks are a threat to human health and cause extremely large financial losses to the poultry industry due to containment measures. Determining the most effective control measures, especially the culling radius, to minimize economic impacts yet contain the spread of HPAI is of great importance. This study examines the factors influencing the probability of a farm being infected with HPAI during the 2016-2017 HPAI outbreak in Korea. Using a spatial random effects logistic model, only a few factors commonly associated with a higher risk of HPAI infection were significant. Interestingly, most density-related factors, poultry and farm, were not significantly associated with a higher risk of HPAI infection. The effective culling radius was determined to be two ranges: 0.5-2.2 km and 2.7-3.0 km. This suggests that the spatial heterogeneity, due to local characteristics and/or the characteristics of the HPAI virus(es) involved, should be considered to determine the most effective culling radius in each region. These findings will help strengthen biosecurity control measures at the farm level and enable authorities to quickly respond to HPAI outbreaks with effective countermeasures to suppress the spread of HPAI.

Transport of Moving Duck Flocks in Indonesia and Vietnam: Management Practices That Potentially Impact Avian Pathogen Dissemination

Highly pathogenic avian influenza (HPAI) virus is endemic in Indonesia and Vietnam, where “moving” duck production is commonly practiced. Questionnaire surveys were conducted with transporters of “moving” duck flocks in Indonesia (N = 55) and Vietnam (N = 43). The main purpose of transportation was to transport duck flocks between rice paddies used for scavenging. Trucks were commonly utilized for transport in both countries (Indonesia: 98.2%, 54/55; Vietnam: 37.2%, 16/43), while boats were only used in Vietnam (62.8%, 27/43). Transporters in Vietnam moved larger flocks and traveled over longer distances. Deaths of ducks due to diseases were reported in both countries (Indonesia: 16.4%, 9/55; Vietnam: 4.7%, 2/43; p = 0.11). Throwing away of carcasses was the primary method of disposal of dead birds in Indonesia (60.0%, 33/55), but was not practiced in Vietnam (p < 0.001), while more transporters in Vietnam (34.9%, 15/43) buried carcasses compared to Indonesia (6.8%, 4/55; p = 0.001). Consumption of carcasses (20.9%, 9/43), sale of dead ducks (14.0%, 6/43) and processing of ducks for fish feed (9.3%, 4/43) was conducted in Vietnam, but not in Indonesia. Vehicles were predominantly cleaned in rivers and stored outside in Vietnam, while cleaning and storage was usually conducted in houses/garages in Indonesia. In conclusion, we identified management practices that potentially impact transmission of avian pathogens, such as HPAI virus. In Indonesia, unsafe management practices were related to multipurpose usage of transport vehicles and disposal of birds in the environment, while in Vietnam, they were related to the mixing of birds during transport, the processing of dead carcasses and the storage and cleaning of transport vehicles.

Effects of Spatial Characteristics on the Spread of the Highly Pathogenic Avian Influenza (HPAI) in Korea

This paper examines the effects of regional characteristics on the spread of the highly pathogenic avian influenza (HPAI) during Korea’s 2016–2017 outbreak. A spatial econometric model is used to determine the effects of regional characteristics on HPAI dispersion using data from 162 counties in Korea. Results indicate the existence of spatial dependence, suggesting that the occurrence of HPAI in a county is significantly influenced by neighboring counties. We found that larger size poultry, including laying hens, breeders, and ducks are significantly associated with a greater incidence of HPAI. Among poultry, we found ducks as the greatest source of the spread of HPAI. Our findings suggest that those regions that are spatially dependent with respect to the spread of HPAI, such as counties that intensively breed ducks, should be the focus of surveillance to prevent future epidemics of HPAI.

Evaluation of insulated isothermal PCR devices for the detection of avian influenza virus

Highly pathogenic avian influenza viruses (HPAIVs) and low pathogenic avian influenza viruses (LPAIVs) represent important threats to the poultry industry and global human health. Due to the high rates of avian influenza virus (AIV) transmission, controlling AIV outbreaks is challenging. HPAIV is known to be transmitted from wild birds to domestic ducks, from which it can be transmitted to layer and broiler chickens. Therefore, surveillance of AIV in domestic ducks and chickens in advance of outbreaks can prevent its spread and enable timely implementation of disease control measures. Certain molecular diagnostic tools can be applied in the field for faster AIV detection. In this study, we evaluated the AIV-detection ability of two insulated isothermal PCR (iiPCR) devices, POCKIT™Micro DUO Nucleic Acid Analyzer (POCKIT DUO) and POCKIT™ Central Nucleic Acid Analyzer (POCKIT Central). We found that the analytical, in vivo and clinical performances of the two POCKIT devices were comparable to those of real-time reverse transcription PCR. Due to their brief protocols and short detection times, POCKIT DUO and POCKIT Central represent promising molecular diagnostic devices for the reliable detection of AIV.

Landscape effects and spatial patterns of avian influenza virus in Danish wild birds, 2006-2020

Avian influenza (AI) is a contagious disease of birds with zoonotic potential. AI virus (AIV) can infect most bird species, but clinical signs and mortality vary. Assessing the distribution and factors affecting AI presence can direct targeted surveillance to areas at risk of disease outbreaks, or help identify disease hotspots or areas with inadequate surveillance. Using virus surveillance data from passive and active AIV wild bird surveillance, 2006−2020, we investigated the association between the presence of AIV and a range of landscape factors and game bird release. Furthermore, we assessed potential bias in the passive AIV surveillance data submitted by the public, via factors related to public accessibility. Lastly, we tested the AIV data for possible hot‐ and cold spots within Denmark. The passive surveillance data was biased regarding accessibility to areas (distance to roads, cities and coast) compared to random locations within Denmark. For both the passive and active AIV surveillance data, we found significant (p < .01) associations with variables related to coast, wetlands and cities, but not game bird release. We used these variables to predict the risk of AIV presence throughout Denmark, and found high‐risk areas concentrated along the coast and fjords. For both passive and active surveillance data, low‐risk clusters were mainly seen in Jutland and northern Zealand, whereas high‐risk clusters were found in Jutland, Zealand, Funen and the southern Isles such as Lolland and Falster. Our results suggest that landscape affects AIV presence, as coastal areas and wetlands attract waterfowl and migrating birds and therefore might increase the potential for AIV transmission. Our findings have enabled us to create risk maps of AIV presence in wild birds and pinpoint high‐risk clusters within Denmark. This will aid targeted surveillance efforts within Denmark and potentially aid in planning the location of future poultry farms.

The Impact of Selected Risk Factors on The Occurrence of Highly Pathogenic Avian Influenza in Commercial Poultry Flocks in Poland

Introduction

Introduction of highly pathogenic avian influenza virus (HPAIV) into a country and its further spread may have a devastating impact on the poultry industry and lead to serious economic consequences. Various risk factors may increase the probability of HPAI outbreak occurrence but their relative influence is often difficult to determine. The study evaluates how the densities of selected poultry species and proximity to the areas inhabited by wild birds impacted HPAI outbreak occurrence during the recently reported epidemics in Poland.

Material and methods

The analysis was developed using these risk factors in the locations of affected and randomly chosen unaffected commercial farms. Generalised linear and non-linear models, specifically logistic regression, classification tree and random forest, were used to indicate the most relevant risk factors, to quantify their association with HPAI outbreak occurrence, and to develop a map depicting spatial risk distribution.

Results

The most important risk factors comprised the densities of turkeys, geese and ducks. The abundance of these species of poultry in an area increased the probability of HPAI occurrence, and their farming intensity in several areas of central, western, eastern and northern Poland put these areas at the highest risk.

Conclusion

The results may improve the targeting of active surveillance, strengthen biosecurity in the areas at risk and contribute to early detection of HPAI in outbreak reoccurrences.

Identification of Areas at Increased Risk of Highly Pathogenic Avian Influenza Occurrence in Commercial Poultry in Poland

The objective of the study was to identify the areas at increased risk of highly pathogenic avian influenza (HPAI) occurrence in commercial poultry in Poland. To identify the risk factors related to the occurrence of HPAI outbreaks, the opinions of Polish experts were combined with literature-driven knowledge. The relative impact of each risk factor was determined using a multicriteria decision analysis approach. The applied model suggests that the greatest risk of HPAI occurrence is concentrated in several counties in the eastern, western, and central parts of the country. The most influential risk actors responsible for HPAI occurrence in Poland included waterfowl density and proximity to waterbodies. The model had a high predictive value (area under the curve = 0.78). The developed spatial risk assessment of HPAI occurrence provides a valuable source of information for risk managers and can contribute to early detection of potential outbreaks of HPAI in poultry.

Agricultural and geographic factors shaped the North American 2015 highly pathogenic avian influenza H5N2 outbreak

The 2014-2015 highly pathogenic avian influenza (HPAI) H5NX outbreak represents the largest and most expensive HPAI outbreak in the United States to date. Despite extensive traditional and molecular epidemiological studies, factors associated with the spread of HPAI among midwestern poultry premises remain unclear. To better understand the dynamics of this outbreak, 182 full genome HPAI H5N2 sequences isolated from commercial layer chicken and turkey production premises were analyzed using evolutionary models able to accommodate epidemiological and geographic information. Epidemiological compartmental models embedded in a phylogenetic framework provided evidence that poultry type acted as a barrier to the transmission of virus among midwestern poultry farms. Furthermore, after initial introduction, the propagation of HPAI cases was self-sustainable within the commercial poultry industries. Discrete trait diffusion models indicated that within state viral transitions occurred more frequently than inter-state transitions. Distance and sample size were very strongly supported as associated with viral transition between county groups (Bayes Factor > 30.0). Together these findings indicate that the different types of midwestern poultry industries were not a single homogenous population, but rather, the outbreak was shaped by poultry industries and geographic factors.

A Novel Prediction of Quaternary Structural Type of Proteins with Gene Ontology

BACKGROUND

The information of quaternary structure attributes of proteins is very important because it is closely related to the biological functions of proteins. With the rapid development of new generation sequencing technology, we are facing a challenge: how to automatically identify the four-level attributes of new polypeptide chains according to their sequence information (i.e., whether they are formed as just as a monomer, or as a hetero-oligomer, or a homo-oligomer).

OBJECTIVE

In this article, our goal is to find a new way to represent protein sequences, thereby improving the prediction rate of protein quaternary structure.

METHODS

In this article, we developed a prediction system for protein quaternary structural type in which a protein sequence was expressed by combining the Pfam functional-domain and gene ontology. turn protein features into digital sequences, and complete the prediction of quaternary structure through specific machine learning algorithms and verification algorithm.

RESULTS

Our data set contains 5495 protein samples. Through the method provided in this paper, we classify proteins into monomer, or as a hetero-oligomer, or a homo-oligomer, and the prediction rate is 74.38%, which is 3.24% higher than that of previous studies. Through this new feature extraction method, we can further classify the four-level structure of proteins, and the results are also correspondingly improved.

CONCLUSION

After the applying the new prediction system, compared with the previous results, we have successfully improved the prediction rate. We have reason to believe that the feature extraction method in this paper has better practicability and can be used as a reference for other protein classification problems.

The Geographic Variation of Surveillance and Zoonotic Spillover Potential of Influenza Viruses in Domestic Poultry and Swine

Background

Avian and swine influenza viruses circulate worldwide and pose threats to both animal and human health. The design of global surveillance strategies is hindered by information gaps on the geospatial variation in virus emergence potential and existing surveillance efforts.

Methods

We developed a spatial framework to quantify the geographic variation in outbreak emergence potential based on indices of potential for animal-to-human and secondary human-to-human transmission. We then compared our resultant raster model of variation in emergence potential with the global distribution of recent surveillance efforts from 359105 reports of surveillance activities.

Results

Our framework identified regions of Southeast Asia, Eastern Europe, Central America, and sub-Saharan Africa with high potential for influenza virus spillover. In the last 15 years, however, we found that 78.43% and 49.01% of high-risk areas lacked evidence of influenza virus surveillance in swine and domestic poultry, respectively.

Conclusions

Our work highlights priority areas where improved surveillance and outbreak mitigation could enhance pandemic preparedness strategies.

Dynamics of the 2004 avian influenza H5N1 outbreak in Thailand: The role of duck farming, sequential model fitting and control

The Highly Pathogenic Avian Influenza (HPAI) subtype H5N1 virus persists in many countries and has been circulating in poultry, wild birds. In addition, the virus has emerged in other species and frequent zoonotic spillover events indicate that there remains a significant risk to human health. It is crucial to understand the dynamics of the disease in the poultry industry to develop a more comprehensive knowledge of the risks of transmission and to establish a better distribution of resources when implementing control. In this paper, we develop a set of mathematical models that simulate the spread of HPAI H5N1 in the poultry industry in Thailand, utilising data from the 2004 epidemic. The model that incorporates the intensity of duck farming when assessing transmision risk provides the best fit to the spatiotemporal characteristics of the observed outbreak, implying that intensive duck farming drives transmission of HPAI in Thailand. We also extend our models using a sequential model fitting approach to explore the ability of the models to be used in “real time” during novel disease outbreaks. We conclude that, whilst predictions of epidemic size are estimated poorly in the early stages of disease outbreaks, the model can infer the preferred control policy that should be deployed to minimise the impact of the disease.

Comparative Epidemiology of Highly Pathogenic Avian Influenza Virus H5N1 and H5N6 in Vietnamese Live Bird Markets: Spatiotemporal Patterns of Distribution and Risk Factors

Highly pathogenic avian influenza (HPAI) H5N1 virus has been circulating in Vietnam since 2003, whilst outbreaks of HPAI H5N6 virus are more recent, having only been reported since 2014. Although the spatial distribution of H5N1 outbreaks and risk factors for virus occurrence has been extensively studied, there have been no comparative studies for H5N6. Data collected through active surveillance of Vietnamese live bird markets (LBMs) between 2011 and 2015 were used to explore and compare the spatiotemporal distributions of H5N1- and H5N6-positive LBMs. Conditional autoregressive models were developed to quantify spatiotemporal associations between agroecological factors and the two HPAI strains using the same set of predictor variables. Unlike H5N1, which exhibited a strong north–south divide, with repeated occurrence in the extreme south of a cluster of high-risk provinces, H5N6 was homogeneously distributed throughout Vietnam. Similarly, different agroecological factors were associated with each strain. Sample collection in the months of January and February and higher average maximum temperature were associated with higher likelihood of H5N1-positive market-day status. The likelihood of market days being positive for H5N6 increased with decreased river density, and with successive Rounds of data collection. This study highlights marked differences in spatial patterns and risk factors for H5N1 and H5N6 in Vietnam, suggesting the need for tailored surveillance and control approaches.

Global spatial risk pattern of highly pathogenic avian influenza H5N1 virus in wild birds: A knowledge-fusion based approach

Highly pathogenic avian influenza (HPAI) H5N1 viruses have continuously circulated throughout much of the world since 2003, resulting in huge economic losses and major public health problems. Wild birds have played an important role in the spread of H5N1 HPAI. To understand its spatial distribution, H5N1 HPAI have been studied by many disciplines from different perspectives, but only one kind of disciplinary knowledge was involved, which has provided limited progress in understanding. Combining risk information from different disciplines based on knowledge fusion can provide more accurate and detailed information. In this study, local k function, phylogenetic tree analysis, and logistic spatial autoregressive models were used to explore the global spatial pattern of H5N1 HPAI based on outbreak data in wild birds, genetic sequences, and risk factors, respectively. On this basis, Dempster-Shafer (D-S) evidence theory was further applied to study the spatial distribution of H5N1 HPAI. We found D-S evidence theory was more robust and reliable than the other three methods, providing technical and methodological support for application to the research of other diseases. The shortest distance to wild bird migration routes, roads and railways, elevation, the normalized difference vegetation index (NDVI), land use and land cover (LULC) and infant mortality rates (IMR) were significantly associated with the occurrence of H5N1 HPAI. The high-risk areas were mainly located in Northern and Central Europe, the eastern Mediterranean, and East and Southeast Asia. High-risk clusters were closely related to the social, economic and ecological environment of the region. Locations where the potential transmission risk remains high should be prioritized for control efforts.

Identification of high risk areas for avian influenza outbreaks in California using disease distribution models

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.

Conservation, development and the management of infectious disease: avian influenza in China, 2004-2012

There is growing evidence that wildlife conservation measures have mixed effects on the emergence and spread of zoonotic disease. Wildlife conservation has been found to have both positive (dilution) and negative (contagion) effects. In the case of avian influenza H5N1 in China, the focus has been on negative effects. Lakes and wetlands attracting migrating waterfowl have been argued to be disease hotspots. We consider the implications of waterfowl conservation for H5N1 infections in both poultry and humans between 2004 and 2012. We model both environmental and economic risk factors. Environmental risk factors comprise the conditions that structure interaction between wild and domesticated birds. Economic risk factors comprise the cost of disease, biosecurity measures and disease risk mitigation. We find that H5N1 outbreaks in poultry populations are indeed sensitive to the existence of wild-domesticated bird mixing zones, but not in the way we would expect from the literature. We find that risk is decreasing in protected migratory bird habitat. Since the number of human cases is increasing in the number of poultry outbreaks, as expected, the implication is that the protection of wetlands important for migratory birds offers unexpected human health benefits.This article is part of the themed issue 'Conservation, biodiversity and infectious disease: scientific evidence and policy implications'.

Movement and contact patterns of long-distance free-grazing ducks and avian influenza persistence in Vietnam

Presence of ducks, and in particular of free-grazing ducks, has consistently been shown to be one of the most important risk factors for highly pathogenic avian influenza outbreaks which has compromised poultry production in South-East Asia since the early 2000s and continues to threaten public health, farmers’ livelihood and food security. Although free-grazing duck production has been practised for decades in South-East Asia, there are few published studies describing this production system, which is suspected to play an important role in the maintenance of avian influenza viruses. This study aimed at describing quantitatively the long-distance free-grazing duck production system in South Vietnam, characterising the movement and contact patterns of the duck flocks, and identifying potential associations between farming practices, movement and contact patterns and the circulation of avian influenza viruses. We conducted interviews among stakeholders involved in the free-grazing duck production system (duck farmers, transporters and rice paddy owners) in combination with a virological cross-sectional survey in South Vietnam. Results show that both direct and indirect contacts between free-grazing duck flocks were frequent and diverse. The flocks were transported extensively across district and province boundaries, mainly by boat but also by truck or on foot. A third of the investigated flocks had a positive influenza A virology test, indicating current circulation of avian influenza viruses, but none were positive for H5 subtypes. The age and size of the flock as well as its location at the time of sampling were associated with the risk of influenza A circulation in the flocks. These findings should be considered when developing risk assessment models of influenza virus spread aimed at informing the development of improved biosecurity practices leading to enhanced animal health, sustainable animal production and reliable income for farmers.

Economic growth, urbanization, globalization, and the risks of emerging infectious diseases in China: A review

Three interrelated world trends may be exacerbating emerging zoonotic risks: income growth, urbanization, and globalization. Income growth is associated with rising animal protein consumption in developing countries, which increases the conversion of wild lands to livestock production, and hence the probability of zoonotic emergence. Urbanization implies the greater concentration and connectedness of people, which increases the speed at which new infections are spread. Globalization-the closer integration of the world economy-has facilitated pathogen spread among countries through the growth of trade and travel. High-risk areas for the emergence and spread of infectious disease are where these three trends intersect with predisposing socioecological conditions including the presence of wild disease reservoirs, agricultural practices that increase contact between wildlife and livestock, and cultural practices that increase contact between humans, wildlife, and livestock. Such an intersection occurs in China, which has been a "cradle" of zoonoses from the Black Death to avian influenza and SARS. Disease management in China is thus critical to the mitigation of global zoonotic risks.

Globalized Perspectives on Infectious Disease Management and Trade in Africa: A Conceptual Framework for Assessing Risk in Developing Country Settings

In the era of globalization, internationalized representations of infectious disease threats have profound implications for understandings of infectious disease problems and their management in developing countries, particularly in Sub-Saharan Africa. By examining the policy implications of the key narratives around public health, animal health and trade, it becomes possible to clarify the relationship between global understandings of infectious disease risk and their impact on the development of local responses to disease problems. We highlight the tensions that resource-constrained countries face in the nexus of animal health-public health and trade, including the perception that resource-constrained countries are both source and victims of potential infectious disease threats. Given this scenario, it is important to think about how developing countries, particularly those in Sub-Saharan Africa, can approach infectious disease risk management as it relates to pandemic scale threats such as avian and pandemic influenza. We outline some of the key considerations in defining and assessing disease risk using avian and pandemic influenza in Zambia as an example. We conclude that the key to the feasibility of the analysis of the risk of multi-sectoral affecting emerging infectious diseases such as zoonotic avian influenza is flexibility in how risk is framed across the public health, animal health and trade systems.

Quantitative assessment of a spatial multicriteria model for highly pathogenic avian influenza H5N1 in Thailand, and application in Cambodia

The Highly Pathogenic Avian Influenza H5N1 (HPAI) virus is now considered endemic in several Asian countries. In Cambodia, the virus has been circulating in the poultry population since 2004, with a dramatic effect on farmers' livelihoods and public health. In Thailand, surveillance and control are still important to prevent any new H5N1 incursion. Risk mapping can contribute effectively to disease surveillance and control systems, but is a very challenging task in the absence of reliable disease data. In this work, we used spatial multicriteria decision analysis (MCDA) to produce risk maps for HPAI H5N1 in poultry. We aimed to i) evaluate the performance of the MCDA approach to predict areas suitable for H5N1 based on a dataset from Thailand, comparing the predictive capacities of two sources of a priori knowledge (literature and experts), and ii) apply the best method to produce a risk map for H5N1 in poultry in Cambodia. Our results showed that the expert-based model had a very high predictive capacity in Thailand (AUC = 0.97). Applied in Cambodia, MCDA mapping made it possible to identify hotspots suitable for HPAI H5N1 in the Tonlé Sap watershed, around the cities of Battambang and Kampong Cham, and along the Vietnamese border.

Clade-level Spatial Modelling of HPAI H5N1 Dynamics in the Mekong Region Reveals New Patterns and Associations with Agro-Ecological Factors

The highly pathogenic avian influenza (HPAI) H5N1 virus has been circulating in Asia since 2003 and diversified into several genetic lineages, or clades. Although the spatial distribution of its outbreaks was extensively studied, differences in clades were never previously taken into account. We developed models to quantify associations over time and space between different HPAI H5N1 viruses from clade 1, 2.3.4 and 2.3.2 and agro-ecological factors. We found that the distribution of clades in the Mekong region from 2004 to 2013 was strongly regionalised, defining specific epidemiological zones, or epizones. Clade 1 became entrenched in the Mekong Delta and was not supplanted by newer clades, in association with a relatively higher presence of domestic ducks. In contrast, two new clades were introduced (2.3.4 and 2.3.2) in northern Viet Nam and were associated with higher chicken density and more intensive chicken production systems. We suggest that differences in poultry production systems in these different epizones may explain these associations, along with differences in introduction pressure from neighbouring countries. The different distribution patterns found at the clade level would not be otherwise apparent through analysis treating all outbreaks equally, which requires improved linking of disease outbreak records and genetic sequence data.

Cultural Practices Shaping Zoonotic Diseases Surveillance: The Case of Highly Pathogenic Avian Influenza and Thailand Native Chicken Farmers

Effectiveness of current passive zoonotic disease surveillance systems is limited by the under-reporting of disease outbreaks in the domestic animal population. Evaluating the acceptability of passive surveillance and its economic, social and cultural determinants appears a critical step for improving it. A participatory rural appraisal was implemented in a rural subdistrict of Thailand. Focus group interviews were used to identify sanitary risks perceived by native chicken farmers and describe the structure of their value chain. Qualitative individual interviews with a large diversity of actors enabled to identify perceived costs and benefits associated with the reporting of HPAI suspicions to sanitary authorities. Besides, flows of information on HPAI suspected cases were assessed using network analysis, based on data collected through individual questionnaires. Results show that the presence of cockfighting activities in the area negatively affected the willingness of all chicken farmers and other actors to report suspected HPAI cases. The high financial and affective value of fighting cocks contradicted the HPAI control policy based on mass culling. However, the importance of product quality in the native chicken meat value chain and the free veterinary services and products delivered by veterinary officers had a positive impact on suspected case reporting. Besides, cockfighting practitioners had a significantly higher centrality than other actors in the information network and they facilitated the spatial diffusion of information. Social ties built in cockfighting activities and the shared purpose of protecting valuable cocks were at the basis of the diffusion of information and the informal collective management of diseases. Building bridges with this informal network would greatly improve the effectiveness of passive surveillance.

Disease Control, Public Health and Food Safety: Food Policy Lessons from Sub-Saharan Africa

This chapter reviews the agro-economic environment in Sub-Saharan Africa as it relates to animal production, public health, and disease control to contextualize the concept of risk and food safety. Drawing mostly from the experience of Zambia, it analyzes food safety actors and interests in Sub-Saharan Africa, and provides an outline of the general regulatory framework that is in place on the continent, to explain how food safety governance is impacted by different interest groups and agendas. Two case studies are provided, zoonotic tuberculosis and avian influenza. The chapter demonstrates how the two zoonoses, both important food safety concerns, have been prioritized differently in the case of Zambia, as a result of multiple socio-political and economic factors. The chapter concludes that, in order to be useful, a definition of food safety risks should include multiple contextual issues and stakeholders along the food supply chain. It is important to keep in mind what national food safety governance actors perceive the risks to be, and how their definitions fit into the broader picture of food safety in general. Food safety governance regulatory processes should take into consideration local realities, local food supply chains and local food safety threats to ensure the appropriateness and sustainability of any and all disease control measures instituted. Context will always matter, and therefore, local ecological, biological and policy considerations should be given primacy.

Characteristics of commercial and traditional village poultry farming in Mali with a focus on practices influencing the risk of transmission of avian influenza and Newcastle disease

We aimed at characterizing commercial and traditional village poultry farming in Mali, with a focus on practices influencing the risk of transmission of avian influenza and Newcastle disease. Surveys were conducted in 2009-2011 in a study area covering approximately 98% of the Malian poultry population. Among the 282 commercial farms investigated, of which 64 had not been known by the government authorities, 83% were located within a 50km radius from the capitals of the country and regions and 54% had low biosecurity standard. Among the 152 randomly selected village household flocks investigated, characteristics were overall similar to those in other African countries but some differences were notable including a large flock size (median 44 poultry), a low presence of ducks and geese (11% and 1.1% of flocks, respectively), vaccination against Newcastle disease being common (49% of flocks), a low proportion of households selling sick and dead birds (0.7% and 0%, respectively) and limited cohabitation between poultry and humans at night. Our recommendations to limit the risk of disease transmission include (1) for commercial farms, to introduce compulsory farm registration and accreditation, to increase technical proficiency and access to credit for farms with low biosecurity, and to support poultry producer associations; (2) for village poultry, to promote better quarantine and management of sick and dead birds. Such detailed knowledge of country-specific characteristics of poultry production systems is essential to be able to develop more efficient disease risk management policies.

Evidence for the Convergence Model: The Emergence of Highly Pathogenic Avian Influenza (H5N1) in Viet Nam

Building on a series of ground breaking reviews that first defined and drew attention to emerging infectious diseases (EID), the 'convergence model' was proposed to explain the multifactorial causality of disease emergence. The model broadly hypothesizes disease emergence is driven by the co-incidence of genetic, physical environmental, ecological, and social factors. We developed and tested a model of the emergence of highly pathogenic avian influenza (HPAI) H5N1 based on suspected convergence factors that are mainly associated with land-use change. Building on previous geospatial statistical studies that identified natural and human risk factors associated with urbanization, we added new factors to test whether causal mechanisms and pathogenic landscapes could be more specifically identified. Our findings suggest that urbanization spatially combines risk factors to produce particular types of peri-urban landscapes with significantly higher HPAI H5N1 emergence risk. The work highlights that peri-urban areas of Viet Nam have higher levels of chicken densities, duck and geese flock size diversities, and fraction of land under rice or aquaculture than rural and urban areas. We also found that land-use diversity, a surrogate measure for potential mixing of host populations and other factors that likely influence viral transmission, significantly improves the model's predictability. Similarly, landscapes where intensive and extensive forms of poultry production overlap were found at greater risk. These results support the convergence hypothesis in general and demonstrate the potential to improve EID prevention and control by combing geospatial monitoring of these factors along with pathogen surveillance programs.

Modelling the species jump: towards assessing the risk of human infection from novel avian influenzas

The scientific understanding of the driving factors behind zoonotic and pandemic influenzas is hampered by complex interactions between viruses, animal hosts and humans. This complexity makes identifying influenza viruses of high zoonotic or pandemic risk, before they emerge from animal populations, extremely difficult and uncertain. As a first step towards assessing zoonotic risk of influenza, we demonstrate a risk assessment framework to assess the relative likelihood of influenza A viruses, circulating in animal populations, making the species jump into humans. The intention is that such a risk assessment framework could assist decision-makers to compare multiple influenza viruses for zoonotic potential and hence to develop appropriate strain-specific control measures. It also provides a first step towards showing proof of principle for an eventual pandemic risk model. We show that the spatial and temporal epidemiology is as important in assessing the risk of an influenza A species jump as understanding the innate molecular capability of the virus. We also demonstrate data deficiencies that need to be addressed in order to consistently combine both epidemiological and molecular virology data into a risk assessment framework.

Highly Pathogenic Avian Influenza H5N1 in Mainland China

Highly pathogenic avian influenza (HPAI) H5N1 has posed a significant threat to both humans and birds, and it has spanned large geographic areas and various ecological systems throughout Asia, Europe and Africa, but especially in mainland China. Great efforts in control and prevention of the disease, including universal vaccination campaigns in poultry and active serological and virological surveillance, have been undertaken in mainland China since the beginning of 2006. In this study, we aim to characterize the spatial and temporal patterns of HPAI H5N1, and identify influencing factors favoring the occurrence of HPAI H5N1 outbreaks in poultry in mainland China. Our study shows that HPAI H5N1 outbreaks took place sporadically after vaccination campaigns in poultry, and mostly occurred in the cold season. The positive tests in routine virological surveillance of HPAI H5N1 virus in chicken, duck, goose as well as environmental samples were mapped to display the potential risk distribution of the virus. Southern China had a higher positive rate than northern China, and positive samples were mostly detected from chickens in the north, while the majority were from duck in the south, and a negative correlation with monthly vaccination rates in domestic poultry was found (R = -0.19, p value = 0.005). Multivariate panel logistic regression identified vaccination rate, interaction between distance to the nearest city and national highway, interaction between distance to the nearest lake and wetland, and density of human population, as well as the autoregressive term in space and time as independent risk factors in the occurrence of HPAI H5N1 outbreaks, based on which a predicted risk map of the disease was derived. Our findings could provide new understanding of the distribution and transmission of HPAI H5N1 in mainland China and could be used to inform targeted surveillance and control efforts in both human and poultry populations to reduce the risk of future infections.

Agro-environmental determinants of avian influenza circulation: a multisite study in Thailand, Vietnam and Madagascar

Outbreaks of highly pathogenic avian influenza have occurred and have been studied in a variety of ecological systems. However, differences in the spatial resolution, geographical extent, units of analysis and risk factors examined in these studies prevent their quantitative comparison. This study aimed to develop a high-resolution, comparative study of a common set of agro-environmental determinants of avian influenza viruses (AIV) in domestic poultry in four different environments: (1) lower-Northern Thailand, where H5N1 circulated in 2004-2005, (2) the Red River Delta in Vietnam, where H5N1 is circulating widely, (3) the Vietnam highlands, where sporadic H5N1 outbreaks have occurred, and (4) the Lake Alaotra region in Madagascar, which features remarkable similarities with Asian agro-ecosystems and where low pathogenic avian influenza viruses have been found. We analyzed H5N1 outbreak data in Thailand in parallel with serological data collected on the H5 subtype in Vietnam and on low pathogenic AIV in Madagascar. Several agro-environmental covariates were examined: poultry densities, landscape dominated by rice cultivation, proximity to a water body or major road, and human population density. Relationships between covariates and AIV circulation were explored using spatial generalized linear models. We found that AIV prevalence was negatively associated with distance to the closest water body in the Red River Delta, Vietnam highlands and Madagascar. We also found a positive association between AIV and duck density in the Vietnam highlands and Thailand, and with rice landscapes in Thailand and Madagascar. Our findings confirm the important role of wetlands-rice-ducks ecosystems in the epidemiology of AI in diverse settings. Variables influencing circulation of the H5 subtype in Southeast Asia played a similar role for low pathogenic AIV in Madagascar, indicating that this area may be at risk if a highly virulent strain is introduced.

Spatio-temporal epidemiology of highly pathogenic avian influenza (subtype H5N1) in poultry in eastern India

In India, majority outbreaks of highly pathogenic avian influenza (HPAI) H5N1 have occurred in eastern states of West Bengal, Assam and Tripura. This study aimed to identify disease clusters and risk factors of HPAI H5N1 in these states, for targeted surveillance and disease control. A spatial scan statistic identified two significant disease clusters in West Bengal and Assam, occurring during January and November-December 2008, respectively. Key risk factors were identified at sub-district level using bootstrapped logistic regression and boosted regression trees model. With both methods, HPAI H5N1 outbreaks in backyard poultry were associated with accessibility in terms of time taken to access a city with >50,000 persons, human population density and duck density (P<0.005). In addition, areas at lower elevation were also identified as high risk by BRT model. It is recommended that risk-based surveillance should be implemented in high duck density areas and all live-bird markets in high-throughput locations.

Intervention strategies to reduce the risk of zoonotic infection with avian influenza viruses: scientific basis, challenges and knowledge gaps

A range of measures has been recommended and used for the control and prevention of avian influenza. These measures are based on the assessment of local epidemiological situations, field observations and other scientific information. Other non-technical factors are (or in some cases should be) taken into account when developing and recommending control measures. The precise effects under field conditions of most individual interventions applied to control and prevent avian influenza have not been established or subjected to critical review, often because a number of measures are applied simultaneously without controls. In most cases, the combination of measures used results in control or elimination of the virus although there are some countries where this has not been the case. In others, especially those with low poultry density, it is not clear whether the link between the adoption of a set of measures and the subsequent control of the disease is causative. This article discusses the various measures recommended, with particular emphasis on stamping out and vaccination, examines how these measures assist in preventing zoonotic infections with avian influenza viruses and explores gaps in knowledge regarding their effectiveness.

Zero-inflated models for identifying disease risk factors when case detection is imperfect: application to highly pathogenic avian influenza H5N1 in Thailand

Logistic regression models integrating disease presence/absence data are widely used to identify risk factors for a given disease. However, when data arise from imperfect surveillance systems, the interpretation of results is confusing since explanatory variables can be related either to the occurrence of the disease or to the efficiency of the surveillance system. As an alternative, we present spatial and non-spatial zero-inflated Poisson (ZIP) regressions for modelling the number of highly pathogenic avian influenza (HPAI) H5N1 outbreaks that were reported at subdistrict level in Thailand during the second epidemic wave (July 3rd 2004 to May 5th 2005). The spatial ZIP model fitted the data more effectively than its non-spatial version. This model clarified the role of the different variables: for example, results suggested that human population density was not associated with the disease occurrence but was rather associated with the number of reported outbreaks given disease occurrence. In addition, these models allowed estimating that 902 (95% CI 881-922) subdistricts suffered at least one HPAI H5N1 outbreak in Thailand although only 779 were reported to veterinary authorities, leading to a general surveillance sensitivity of 86.4% (95% CI 84.5-88.4). Finally, the outputs of the spatial ZIP model revealed the spatial distribution of the probability that a subdistrict could have been a false negative. The methodology presented here can easily be adapted to other animal health contexts.

Mapping amyotrophic lateral sclerosis lake risk factors across northern New England

Background

Amyotrophic lateral sclerosis (ALS) is a progressive, fatal neurodegenerative disease with a lifetime risk of developing as 1 in 700. Despite many recent discoveries about the genetics of ALS, the etiology of sporadic ALS remains largely unknown with gene-environment interaction suspected as a driver. Water quality and the toxin beta methyl-amino-alanine produced by cyanobacteria are suspected environmental triggers. Our objective was to develop an eco-epidemiological modeling approach to characterize the spatial relationships between areas of higher than expected ALS incidence and lake water quality risk factors derived from satellite remote sensing as a surrogate marker of exposure.

Methods

Our eco-epidemiological modeling approach began with implementing a spatial clustering analysis that was informed by local indicators of spatial autocorrelation to identify locations of normalized excess ALS counts at the census tract level across northern New England. Next, water quality data for all lakes over 6 hectares (n = 4,453) were generated using Landsat TM band ratio regression techniques calibrated with in situ lake sampling. Derived lake water quality risk maps included chlorophyll-a (Chl-a), Secchi depth (SD), and total nitrogen (TN). Finally, a spatially-aware logistic regression modeling approach was executed characterizing relationships between the derived lake water quality metrics and ALS hot spots.

Results

Several distinct ALS hot spots were identified across the region. Remotely sensed lake water quality indicators were successfully derived; adjusted R² values ranged between 0.62-0.88 for these indicators based on out-of-sample validation. Map products derived from these indicators represent the first wall-to-wall metrics of lake water quality across the region. Logistic regression modeling of ALS case membership in localized hot spots across the region, i.e., census tracts with higher than expected ALS counts, showed the following: increasing average SD within a radius of 30 km corresponds with a decrease in the odds of belonging to an ALS hot spot by 59%; increasing average TN within a radius of 30 km and average Chl-a concentration within a radius of 10 km correspond with increased odds of belonging to an ALS hot spot by 167% and 4%, respectively.

Conclusions

The strengths of satellite remote sensing information can help overcome traditional field limitations and spatiotemporal data gaps to provide the public health community valuable exposure data. Geographic scale needs to be diligently considered when evaluating relationships among ecological processes, risk factors, and human health outcomes. Broadly, we found that poorer lake water quality was significantly associated with increased odds of belonging to an ALS cluster in the region. These findings support the hypothesis that sporadic ALS (sALS) can, in part, be triggered by environmental water-quality indicators and lake conditions that promote harmful algal blooms.

Rivers and flooded areas identified by medium-resolution remote sensing improve risk prediction of the highly pathogenic avian influenza H5N1 in Thailand

Thailand experienced several epidemic waves of the highly pathogenic avian influenza (HPAI) H5N1 between 2004 and 2005. This study investigated the role of water in the landscape, which has not been previously assessed because of a lack of high-resolution information on the distribution of flooded land at the time of the epidemic. Nine Landsat 7 - Enhanced Thematic Mapper Plus scenes covering 174,610 km(2) were processed using k-means unsupervised classification to map the distribution of flooded areas as well as permanent lakes and reservoirs at the time of the main epidemic HPAI H5N1 wave of October 2004. These variables, together with other factors previously identified as significantly associated with risk, were entered into an autologistic regression model in order to quantify the gain in risk explanation over previously published models. We found that, in addition to other factors previously identified as associated with risk, the proportion of land covered by flooding along with expansion of rivers and streams, derived from an existing, sub-district level (administrative level no. 3) geographical information system database, was a highly significant risk factor in this 2004 HPAI epidemic. These results suggest that water-borne transmission could have partly contributed to the spread of HPAI H5N1 during the epidemic. Future work stemming from these results should involve studies where the actual distribution of small canals, rivers, ponds, rice paddy fields and farms are mapped and tested against farm-level data with respect to HPAI H5N1.

Risk factors for infectious diseases in backyard poultry farms in the Poyang Lake area, China

Emergence and transmission of infectious diseases have an enormous impact on the poultry industry and present a serious threat to the health of humans and wild birds. Noncommercial poultry operations, such as backyard poultry facilities in China, are potential sources of virus exchange between commercial poultry and wild birds. It is particularly critical in wetland areas where backyard poultry have close contact with commercial poultry and migratory birds, therefore increasing the risk of contracting infectious diseases. To evaluate the transmission risks, a cross-sectional study was undertaken in the Poyang Lake area, China, involving 309 residents in the backyard poultry farms in three counties (Region A, B, and C) of Jiangxi Province. We examined the backyard poultry population, poultry species, presence of poultry deaths from infectious diseases, food sources, and biosecurity practices. Region B ranked highest for biosecurity while region C ranked lowest. The risks of infectious diseases were assessed by adjusted odds ratio based on multivariate logistic regression analysis. Potential risk factors in the three regions of the study site were compared. In Region A, significant factor was contact of poultry with wild birds (OR: 6.573, 95% CI: 2.148–20.115, P=0.001). In Region B, the most significant factor was contact of poultry with neighboring backyard waterfowls (OR: 3.967, 95% CI: 1.555–10.122, P=0.004). In Region C, significant factors were poultry purchase from local live bird markets (OR: 3.740, 95% CI: 1.243–11.255, P=0.019), and contact of poultry with wild birds (OR: 3.379, 95% CI: 1.058–10.791, P=0.040). In summary, backyard poultry was significantly affected by neighboring commercial poultry and close contact with wild birds. The results are expected to improve our understanding of the transmission risks of infectious diseases in a typical backyard poultry environment in rural China, and address the need to improve local farming practices and take preventive measures.

Social network analysis used to assess the relationship between the spread of avian influenza and movement patterns of backyard chickens in Ratchaburi, Thailand

In this study, we describe the movement and trading patterns of the backyard chicken in Ratchaburi, Thailand by using social network analysis with egocentric approach. From questionnaire results, we found that there is a close relationship between chicken owners' houses and fresh markets, and we concluded that this relationship needs attention from authorities to prevent future outbreaks of avian flu. Control measures should be applied over pathways to prevent and control highly pathogenic avian influenza subtype H5N1 in the backyard farming system. Results of our study may be useful to relevant authorities and researchers seeking to understand how H5N1 spreads in Ratchaburi. This may reflect on the spread of H5N1 throughout Thailand.

Distribution and dynamics of risk factors associated with highly pathogenic avian influenza H5N1

Within China's Poyang Lake region, close interactions between wild migratory birds and domestic poultry are common and provide an opportunity for the transmission and subsequent outbreaks of highly pathogenic avian influenza (HPAI) virus. We overlaid a series of ecological factors associated with HPAI to map the risk of HPAI in relation to natural and anthropogenic variables, and we identified two hotspots for potential HPAI outbreaks in the Poyang Lake region as well as three corridors connecting the two hotspot areas. In hotspot I, there is potential for migratory birds to bring new avian influenza (AI) strains that can reassort with existing strains to form new AI viruses. Hotspot II features high-density poultry production where outbreaks of endemic AI viruses are likely. The three communication corridors that link the two hotspots further promote HPAI H5N1 transmission and outbreaks and lead to the persistence of AI viruses in the Poyang Lake region. We speculate that the region's unevenly distributed poultry supply-and-demand system might be a key factor inducing HPAI H5N1 transmission and outbreaks in the Poyang Lake region.

Genetics: A New Landscape for Medical Geography

The emergence and re-emergence of human pathogens resistant to medical treatment will present a challenge to the international public health community in the coming decades. Geography is uniquely positioned to examine the progressive evolution of pathogens across space and through time, and to link molecular change to interactions between population and environmental drivers. Landscape as an organizing principle for the integration of natural and cultural forces has a long history in geography, and, more specifically, in medical geography. Here, we explore the role of landscape in medical geography, the emergent field of landscape genetics, and the great potential that exists in the combination of these two disciplines. We argue that landscape genetics can enhance medical geographic studies of local-level disease environments with quantitative tests of how human-environment interactions influence pathogenic characteristics. In turn, such analyses can expand theories of disease diffusion to the molecular scale and distinguish the important factors in ecologies of disease that drive genetic change of pathogens.

Risk factors for exposure to influenza a viruses, including subtype H5 viruses, in Thai free-grazing ducks

Free-grazing ducks (FGD) have been associated with highly pathogenic avian influenza (HPAI) H5N1 outbreaks and may be a viral reservoir. In July-August 2010, we assessed influenza exposure of Thai FGD and risk factors thereof. Serum from 6254 ducks was analysed with enzyme-linked immunosorbent assay (ELISA) to detect antibodies to influenza A nucleoprotein (NP), and haemagglutinin H5 protein. Eighty-five per cent (5305 ducks) were seropositive for influenza A. Of the NP-seropositive sera tested with H5 assays (n = 1423), 553 (39%) were H5 ELISA positive and 57 (4%) suspect. Twelve per cent (74 of 610) of H5 ELISA-positive/suspect ducks had H5 titres ≥ 1 : 20 by haemagglutination inhibition. Risk factors for influenza A seropositivity include older age, poultry contact, flock visitors and older purchase age. Study flocks had H5 virus exposure as recently as March 2010, but no HPAI H5N1 outbreaks have been identified in Thailand since 2008, highlighting a need for rigorous FGD surveillance.