Outbreaks of H5N1 in poultry in Thailand: the relative role of poultry production types in sustaining transmission and the impact of active surveillance in control

Modelling the transmission dynamics of H9N2 avian influenza viruses in a live bird market

H9N2 avian influenza viruses (AIVs) are a major concern for the poultry sector and human health in countries where this subtype is endemic. By fitting a model simulating H9N2 AIV transmission to data from a field experiment, we characterise the epidemiology of the virus in a live bird market in Bangladesh. Many supplied birds arrive already exposed to H9N2 AIVs, resulting in many broiler chickens entering the market as infected, and many indigenous backyard chickens entering with pre-existing immunity. Most susceptible chickens become infected within one day spent at the market, owing to high levels of viral transmission within market and short latent periods, as brief as 5.3 hours. Although H9N2 AIV transmission can be substantially reduced under moderate levels of cleaning and disinfection, effective risk mitigation also requires a range of additional interventions targeting markets and other nodes along the poultry production and distribution network.

A systematic review of mechanistic models used to study avian influenza virus transmission and control

The global spread of avian influenza A viruses in domestic birds is causing increasing socioeconomic devastation. Various mechanistic models have been developed to better understand avian influenza transmission and evaluate the effectiveness of control measures in mitigating the socioeconomic losses caused by these viruses. However, the results of models of avian influenza transmission and control have not yet been subject to a comprehensive review. Such a review could help inform policy makers and guide future modeling work. To help fill this gap, we conducted a systematic review of the mechanistic models that have been applied to field outbreaks. Our three objectives were to: (1) describe the type of models and their epidemiological context, (2) list estimates of commonly used parameters of low pathogenicity and highly pathogenic avian influenza transmission, and (3) review the characteristics of avian influenza transmission and the efficacy of control strategies according to the mechanistic models. We reviewed a total of 46 articles. Of these, 26 articles estimated parameters by fitting the model to data, one evaluated the effectiveness of control strategies, and 19 did both. Values of the between-individual reproduction number ranged widely: from 2.18 to 86 for highly pathogenic avian influenza viruses, and from 4.7 to 45.9 for low pathogenicity avian influenza viruses, depending on epidemiological settings, virus subtypes and host species. Other parameters, such as the durations of the latent and infectious periods, were often taken from the literature, limiting the models' potential insights. Concerning control strategies, many models evaluated culling (n = 15), while vaccination received less attention (n = 6). According to the articles reviewed, optimal control strategies varied between virus subtypes and local conditions, and depended on the overall objective of the intervention. For instance, vaccination was optimal when the objective was to limit the overall number of culled flocks. In contrast, pre-emptive culling was preferred for reducing the size and duration of an epidemic. Early implementation consistently improved the overall efficacy of interventions, highlighting the need for effective surveillance and epidemic preparedness.

Impact of palmiped farm density on the resilience of the poultry sector to highly pathogenic avian influenza H5N8 in France

We analysed the interplay between palmiped farm density and the vulnerability of the poultry production system to highly pathogenic avian influenza (HPAI) H5N8. To do so, we used a spatially-explicit transmission model, which was calibrated to reproduce the observed spatio-temporal distribution of outbreaks in France during the 2016-2017 epidemic of HPAI. Six scenarios were investigated, in which the density of palmiped farms was decreased in the municipalities with the highest palmiped farm density. For each of the six scenarios, we first calculated the spatial distribution of the basic reproduction number (R₀), i.e. the expected number of farms a particular farm would be likely to infect, should all other farms be susceptible. We also ran in silico simulations of the adjusted model for each scenario to estimate epidemic sizes and time-varying effective reproduction numbers. We showed that reducing palmiped farm density in the densest municipalities decreased substantially the size of the areas with high R₀ values (> 1.5). In silico simulations suggested that reducing palmiped farm density, even slightly, in the densest municipalities was expected to decrease substantially the number of affected poultry farms and therefore provide benefits to the poultry sector as a whole. However, they also suggest that it would not have been sufficient, even in combination with the intervention measures implemented during the 2016-2017 epidemic, to completely prevent the virus from spreading. Therefore, the effectiveness of alternative structural preventive approaches now needs to be assessed, including flock size reduction and targeted vaccination.

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.

Avian influenza transmission risk along live poultry trading networks in Bangladesh

Live animal markets are known hotspots of zoonotic disease emergence. To mitigate those risks, we need to understand how networks shaped by trading practices influence disease spread. Yet, those practices are rarely recorded in high-risk settings. Through a large cross-sectional study, we assessed the potential impact of live poultry trading networks’ structures on avian influenza transmission dynamics in Bangladesh. Networks promoted mixing between chickens sourced from different farming systems and geographical locations, fostering co-circulation of viral strains of diverse origins in markets. Viral transmission models suggested that the observed rise in viral prevalence from farms to markets was unlikely explained by intra-market transmission alone, but substantially influenced by transmission occurring in upstream network nodes. Disease control interventions should therefore alter the entire network structures. However, as networks differed between chicken types and city supplied, standardised interventions are unlikely to be effective, and should be tailored to local structural characteristics.

Spatial modelling for low pathogenicity avian influenza virus at the interface of wild birds and backyard poultry

Low pathogenicity avian influenza virus (LPAIV) is endemic in wild birds and poultry in Argentina, and active surveillance has been in place to prevent any eventual virus mutation into a highly pathogenic avian influenza virus (HPAIV), which is exotic in this country. Risk mapping can contribute effectively to disease surveillance and control systems, but it has proven a very challenging task in the absence of disease data. We used a combination of expert opinion elicitation, multicriteria decision analysis (MCDA) and ecological niche modelling (ENM) to identify the most suitable areas for the occurrence of LPAIV at the interface between backyard domestic poultry and wild birds in Argentina. This was achieved by calculating a spatially explicit risk index. As evidenced by the validation and sensitivity analyses, our model was successful in identifying high-risk areas for LPAIV occurrence. Also, we show that the risk for virus occurrence is significantly higher in areas closer to commercial poultry farms. Although the active surveillance systems have been successful in detecting LPAIV-positive backyard farms and wild birds in Argentina, our predictions suggest that surveillance efforts in those compartments could be improved by including high-risk areas identified by our model. Our research provides a tool to guide surveillance activities in the future, and presents a mixed methodological approach which could be implemented in areas where the disease is exotic or rare and a knowledge-driven modelling method is necessary.

Highly pathogenic avian influenza H5N8 in south-west France 2016-2017: A modeling study of control strategies

In the winter 2016-2017 the largest epidemic of highly pathogenic avian influenza (HPAI) ever recorded in the European Union spread to all 28 member states. France was hit particularly hard and reported a total of 484 infected premises (IPs) by March 2017. We developed a mathematical model to analyze the spatiotemporal evolution of the epidemic and evaluate the impact of control strategies. We estimated that farms rearing ducks were on average 2.5 times more infectious and 5.0 times more susceptible to HPAI than farms rearing other avian species. The implementation of surveillance zones around IPs reduced transmission by a factor of 1.8 on average. Compared to the strengthening of pre-emptive culling measures enforced by French authorities in February 2017, we found that a faster depopulation of diagnosed IPs would have had a larger impact on the total number of infections. For example, halving the time delay from detection to slaughter of infected animals would have reduced the total number of IPs by 52% and total cull numbers by 50% on average. This study showcases the possible contribution of modeling to inform and optimize control strategies during an outbreak.

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.

Estimating spatiotemporally varying malaria reproduction numbers in a near elimination setting

In 2016 the World Health Organization identified 21 countries that could eliminate malaria by 2020. Monitoring progress towards this goal requires tracking ongoing transmission. Here we develop methods that estimate individual reproduction numbers and their variation through time and space. Individual reproduction numbers, R_c, describe the state of transmission at a point in time and differ from mean reproduction numbers, which are averages of the number of people infected by a typical case. We assess elimination progress in El Salvador using data for confirmed cases of malaria from 2010 to 2016. Our results demonstrate that whilst the average number of secondary malaria cases was below one (0.61, 95% CI 0.55–0.65), individual reproduction numbers often exceeded one. We estimate a decline in R_c between 2010 and 2016. However we also show that if importation is maintained at the same rate, the country may not achieve malaria elimination by 2020.

Twenty one countries have been identified for malaria elimination by 2020 and their progress needs to be constantly evaluated. Here, the authors present a method that estimates individual reproduction numbers and their variation through time and space and use it to monitor elimination success in El Salvador between 2010 and 2016.

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.

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.

The significance of naturally occurring neuraminidase quasispecies of H5N1 avian influenza virus on resistance to oseltamivir: a point of concern

Viral adaptability and survival arise due to the presence of quasispecies populations that are able to escape the immune response or produce drug-resistant variants. However, the presence of H5N1 virus with natural mutations acquired without any drug selection pressure poses a great threat. Cloacal samples collected from the 2004-2005 epidemics in Thailand from Asian open-billed storks revealed one major and several minor quasispecies populations with mutations on the oseltamivir (OTV)-binding site of the neuraminidase gene (NA) without prior exposure to a drug. Therefore, this study investigated the binding between the NA-containing novel mutations and OTV drug using molecular dynamic simulations and plaque inhibition assay. The results revealed that the mutant populations, S236F mutant, S236F/C278Y mutant, A250V/V266A/P271H/G285S mutant and C278Y mutant, had a lower binding affinity with OTV as compared with the WT virus due to rearrangement of amino acid residues and increased flexibility in the 150-loop. This result was further emphasized through the IC50 values obtained for the major population and WT virus, 104.74 nM and 18.30 nM, respectively. Taken together, these data suggest that H5N1 viruses isolated from wild birds have already acquired OTV-resistant point mutations without any exposure to a drug.

The dawn of Structural One Health: a new science tracking disease emergence along circuits of capital

The One Health approach integrates health investigations across the tree of life, including, but not limited to, wildlife, livestock, crops, and humans. It redresses an epistemological alienation at the heart of much modern population health, which has long segregated studies by species. Up to this point, however, One Health research has also omitted addressing fundamental structural causes underlying collapsing health ecologies. In this critical review we unpack the relationship between One Health science and its political economy, particularly the conceptual and methodological trajectories by which it fails to incorporate social determinants of epizootic spillover. We also introduce a Structural One Health that addresses the research gap. The new science, open to incorporating developments across the social sciences, addresses foundational processes underlying multispecies health, including the place-specific deep-time histories, cultural infrastructure, and economic geographies driving disease emergence. We introduce an ongoing project on avian influenza to illustrate Structural One Health's scope and ambition. For the first time researchers are quantifying the relationships among transnational circuits of capital, associated shifts in agroecological landscapes, and the genetic evolution and spatial spread of a xenospecific pathogen.

Infections at the animal/human interface: shifting the paradigm from emergency response to prevention at source

The majority of emerging infectious diseases have their source in animals, and emergence occurs at the human/animal interface, when infections in animals breech the species barrier to infect humans, the population in which they are often first identified. The response is frequently characterized by a series of emergency activities to contain and manage the infection in human populations, and at the same time to identify the source of the infection in nature. If infection is found to have a source in animals, and if animals cause a continuous threat of human infection, culling is often recommended with severe economic impact. Currently, efforts are being undertaken for closer interaction at the animal/human interface through joint surveillance and risk assessment between the animal and human medicine sectors, and research is underway in geographic areas where emergence at the animal/human interface has occurred in the past. The goal of this research is to identify infectious organisms in tropical and other wild animals, to genetically sequence these organisms, and to attempt to predict which organisms have the potential to emerge in human populations. It may be more cost-effective to learn from past emergence events, and to shift the paradigm from disease surveillance, detection, and response in humans; to prevention of emergence at the source by understanding and mitigating the factors, or determinants, that influence animal infection. These determinants are clearly understood from the study of previous emergence events and include human-induced changes in natural environments, urban areas, and agricultural systems; raising and processing animal-based foods; and the roles of global trade, migration, and climate change. Better understanding of these factors learned from epidemiological investigation of past and present emergence events, and modeling and study of the cost-effectiveness of interventions that could result in their mitigation, could provide evidence necessary to better address the political and economic barriers to prevention of infections in animals. Such economically convincing arguments for change and mitigation are required because of the basic difference in animal health-driven by the need for profit; and human health-driven by the need to save lives.

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.

Estimating the transmissibility of H5N1 and the effect of vaccination in Indonesia

The spread of H5N1 avian influenza continues to pose an economic burden and a public health risk worldwide. Despite this, estimates of the transmissibility of infection exist in only a handful of settings and vary considerably. Using final size methods and flock-level infection data from a field trial of mass vaccination, we obtained the first estimates of the transmissibility of infection between and within flocks in Indonesia. We also found that outbreaks in areas designated as vaccination zones were less transmissible than in non-vaccination zones. However, this reduction is only comparable with a limited degree of protective vaccination coverage. Quantifying the overall effect of vaccination in these zones remains challenging. However, this result would appear to imply that, although the interventions applied in vaccination zones were not sufficient to completely prevent transmission in all areas, when outbreaks occur, they are less transmissible than those in areas where vaccination was not applied. This could be either a direct or an indirect effect of vaccination. Given the dynamism of small-scale poultry production in Indonesia, more regular vaccination may be required to ensure that infection is fully controlled in vaccination zones.

Surveillance strategy for early detection of unusual infectious disease events

New pathogens continue to emerge, and the increased connectedness of populations across the globe through international travel and trade favors rapid dispersal of any new disease. The ability to respond to such events has increased but the question is what ‘preparedness’ means at the level of the clinician. Clinicians deal with patients with unexplained illness on a daily basis, and even with syndromes highly indicative of infectious diseases, the cause of illness is often not detected, unless extensive and costly diagnostic work-ups are done. This review discusses innovations in diagnostics and surveillance aimed at early detection of unusual disease. Risk based approaches are promising, but optimal preparedness planning requires multidisciplinary partnerships across domains, and a global translational research agenda to develop tools, systems, and evidence for interventions.

A one health perspective on HPAI H5N1 in the Greater Mekong sub-region

Highly pathogenic avian influenza H5N1 has been a global concern for almost 10 years since its epidemic emergence in South-east Asia in 2003/2004. Despite large investment of resources into the region, the infection has not been eradicated and continues to result in outbreaks in poultry and a small number of human fatalities. This review synthesizes the knowledge base generated by a vast number of research activities conducted in the region and beyond, and adopts an interdisciplinary perspective consistent with the one health paradigm towards analysing the problem and formulating possible policy solutions. A key outcome of the work has been the need to integrate socio-economic and anthropological dimensions with any disease control and prevention activities traditionally informed by primarily epidemiological, virological and pathological attributes of the infection in poultry and wild waterbirds. Recommendations at a broad conceptual level are presented that acknowledge the diversity in the region with respect to livestock production, as well as the changing nature of the risk landscape as a consequence of the rapid economic development which some of the countries in the Greater Mekong sub-region are currently undergoing, as well as their strong trade links with China as the major economic power in East Asia.

Moment approximation of infection dynamics in a population of moving hosts

The modelling of contact processes between hosts is of key importance in epidemiology. Current studies have mainly focused on networks with stationary structures, although we know these structures to be dynamic with continuous appearance and disappearance of links over time. In the case of moving individuals, the contact network cannot be established. Individual-based models (IBMs) can simulate the individual behaviours involved in the contact process. However, with very large populations, they can be hard to simulate and study due to the computational costs. We use the moment approximation (MA) method to approximate a stochastic IBM with an aggregated deterministic model. We illustrate the method with an application in animal epidemiology: the spread of the highly pathogenic virus H5N1 of avian influenza in a poultry flock. The MA method is explained in a didactic way so that it can be reused and extended. We compare the simulation results of three models: 1. an IBM, 2. a MA, and 3. a mean-field (MF). The results show a close agreement between the MA model and the IBM. They highlight the importance for the models to capture the displacement behaviours and the contact processes in the study of disease spread. We also illustrate an original way of using different models of the same system to learn more about the system itself, and about the representation we build of it.

Biosecurity measures for backyard poultry in developing countries: a systematic review

BACKGROUND

Poultry represents an important sector in animal production, with backyard flocks representing a huge majority, especially in the developing countries. In these countries, villagers raise poultry to meet household food demands and as additional sources of incomes. Backyard production methods imply low biosecurity measures and high risk of infectious diseases, such as Newcastle disease or zoonosis such as Highly Pathogenic Avian Influenza (HPAI).We reviewed literature on biosecurity practices for prevention of infectious diseases, and published recommendations for backyard poultry and assessed evidence of their impact and feasibility, particularly in developing countries. Documents were sourced from the Food and Agriculture Organization (FAO) website, and from Pubmed and Google databases.

RESULTS

A total of 62 peer-reviewed and non-referred documents were found, most of which were published recently (after 2004) and focused on HPAI/H5N1-related biosecurity measures (64%). Recommendations addressed measures for flock management, feed and water management, poultry trade and stock change, poultry health management and the risk to humans. Only one general guideline was found for backyard poultry-related biosecurity; the other documents were drawn up for specific developing settings and only engaged their authors (e.g. consultants). These national guidelines written by consultants generated recommendations regarding measures derived from the highest standards of commercial poultry production. Although biosecurity principles of isolation and containment are described in most documents, only a few documents were found on the impact of measures in family poultry settings and none gave any evidence of their feasibility and effectiveness for backyard poultry.

CONCLUSIONS

Given the persistent threat posed by HPAI/H5N1 to humans in developing countries, our findings highlight the importance of encouraging applied research toward identifying sustained and adapted biosecurity measures for smallholder poultry flocks in low-income countries.