Spatial distribution of poultry farms using point pattern modelling: A method to address livestock environmental impacts and disease transmission risks.

The distribution of farm locations and sizes is paramount to characterize patterns of disease spread. With some regions undergoing rapid intensification of livestock production, resulting in increased clustering of farms in peri-urban areas, measuring changes in the spatial distribution of farms is crucial to design effective interventions. However, those data are not available in many countries, their generation being resource-intensive. Here, we develop a farm distribution model (FDM), which allows the prediction of locations and sizes of poultry farms in countries with scarce data. The model combines (i) a Log-Gaussian Cox process model to simulate the farm distribution as a spatial Poisson point process, and (ii) a random forest model to simulate farm sizes (i.e. the number of animals per farm). Spatial predictors were used to calibrate the FDM on intensive broiler and layer farm distributions in Bangladesh, Gujarat (Indian state) and Thailand. The FDM yielded realistic farm distributions in terms of spatial clustering, farm locations and sizes, while providing insights on the factors influencing these distributions. Finally, we illustrate the relevance of modelling realistic farm distributions in the context of epidemic spread by simulating pathogen transmission on an array of spatial distributions of farms. We found that farm distributions generated from the FDM yielded spreading patterns consistent with simulations using observed data, while random point patterns underestimated the probability of large outbreaks. Indeed, spatial clustering increases vulnerability to epidemics, highlighting the need to account for it in epidemiological modelling studies. As the FDM maintains a realistic distribution of farm location and sizes, its use to inform mathematical models of disease transmission is particularly relevant for regions where these data are not available.

The impact of surveillance and control on highly pathogenic avian influenza outbreaks in poultry in Dhaka division, Bangladesh.

In Bangladesh, the poultry industry is an economically and socially important sector, but it is persistently threatened by the effects of H5N1 highly pathogenic avian influenza. Thus, identifying the optimal control policy in response to an emerging disease outbreak is a key challenge for policy-makers. To inform this aim, a common approach is to carry out simulation studies comparing plausible strategies, while accounting for known capacity restrictions. In this study we perform simulations of a previously developed H5N1 influenza transmission model framework, fitted to two separate historical outbreaks, to assess specific control objectives related to the burden or duration of H5N1 outbreaks among poultry farms in the Dhaka division of Bangladesh. In particular, we explore the optimal implementation of ring culling, ring vaccination and active surveillance measures when presuming disease transmission predominately occurs from premises-to-premises, versus a setting requiring the inclusion of external factors. Additionally, we determine the sensitivity of the management actions under consideration to differing levels of capacity constraints and outbreaks with disparate transmission dynamics. While we find that reactive culling and vaccination policies should pay close attention to these factors to ensure intervention targeting is optimised, across multiple settings the top performing control action amongst those under consideration were targeted proactive surveillance schemes. Our findings may advise the type of control measure, plus its intensity, that could potentially be applied in the event of a developing outbreak of H5N1 amongst originally H5N1 virus-free commercially-reared poultry in the Dhaka division of Bangladesh.

Changing Geographic Patterns and Risk Factors for Avian Influenza A(H7N9) Infections in Humans, China.

The fifth epidemic wave of avian influenza A(H7N9) virus in China during 2016-2017 demonstrated a geographic range expansion and caused more human cases than any previous wave. The factors that may explain the recent range expansion and surge in incidence remain unknown. We investigated the effect of anthropogenic, poultry, and wetland variables on all epidemic waves. Poultry predictor variables became much more important in the last 2 epidemic waves than they were previously, supporting the assumption of much wider H7N9 transmission in the chicken reservoir. We show that the future range expansion of H7N9 to northern China may increase the risk of H7N9 epidemic peaks coinciding in time and space with those of seasonal influenza, leading to a higher risk of reassortments than before, although the risk is still low so far.

Avian influenza A (H5N1) outbreaks in different poultry farm types in Egypt: the effect of vaccination, closing status and farm size.

BACKGROUND: The Avian Influenza A (H5N1) virus is endemic in poultry in Egypt. The winter of 2014/2015 was particularly worrying as new clusters of HPAI A (H5N1) virus emerged, leading to an important number of AI A (H5N1) outbreaks in poultry farms and sporadic human cases. To date, few studies have investigated the distribution of HPAI A (H5N1) outbreaks in Egypt in relation to protective / risk factors at the farm level, a gap we intend to fill. The aim of the study was to analyse passive surveillance data that were based on observation of sudden and high mortality of poultry or drop in duck or chicken egg production, as a basis to better understand and discuss the risk of HPAI A (H5N1) presence at the farm level in large parts of the Nile Delta. RESULTS: The probability of HPAI A (H5N1) presence was associated with several characteristics of the farms. Vaccination status, absence of windows/openings in the farm and the number of birds per cycle of production were found to be protective factors, whereas the presence of a duck farm with significant mortality or drop in egg production in the village was found to be a risk factor. CONCLUSIONS: Results demonstrate the key role of several prevention and biosecurity measures to reduce HPAI A (H5N1) virus circulation, which could promote better poultry farm biosecurity in Egypt.

Genetic Characterization of Lumpy Skin Disease Viruses Circulating in Lesotho Cattle.

Lumpy skin disease is one of the fast-spreading viral diseases of cattle and buffalo that can potentially cause severe economic impact. Lesotho experienced LSD for the first time in 1947 and episodes of outbreaks occurred throughout the decades. In this study, eighteen specimens were collected from LSD-clinically diseased cattle between 2020 and 2022 from Mafeteng, Leribe, Maseru, Berea, and Mohales' Hoek districts of Lesotho. A total of 11 DNA samples were analyzed by PCR and sequencing of the extracellular enveloped virus (EEV) glycoprotein, G-protein-coupled chemokine receptor (GPCR), 30 kDa RNA polymerase subunit (RPO30), and B22R genes. All nucleotide sequences of the above-mentioned genes confirmed that the PCR amplicons of clinical samples are truly LSDV, as they were identical to respective LSDV isolates on the NCBI GenBank. Two of the elevem samples were further characterized by whole-genome sequencing. The analysis, based on both CaPV marker genes and complete genome sequences, revealed that the LSDV isolates from Lesotho cluster with the NW-like LSDVs, which includes the commonly circulating LSDV field isolates from Africa, the Middle East, the Balkans, Turkey, and Eastern Europe.

Characterising Biosecurity Initiatives Globally to Support the Development of a Progressive Management Pathway for Terrestrial Animals: A Scoping Review.

While biosecurity is of increasing importance globally, there is still limited evidence of the factors or elements that support the progressive and sustainable scaling up of biosecurity along the value chains from the local to the global level. To gain insight into the current body of literature on biosecurity, a mixed-methods approach was used based on a scoping literature review and an online survey with subject matter experts. Six databases were searched for published literature, and textual information from titles and abstracts of all included records (n = 266) were analysed through inductive content analysis to build biosecurity-relevant categories and identify strengths, weaknesses, opportunities, and threats (SWOT) of existing biosecurity systems or initiatives (such as projects or programs). Most records focused on initiatives in high-income countries, traditional livestock species (pigs, poultry, and large ruminants), and the production stage and had a disease-specific focus. No records described a comprehensive or global framework to progressively scale up biosecurity. Overall, the findings highlight the need for initiatives such as the FAO Progressive Management Pathway for Terrestrial Animal Biosecurity (FAO-PMP-TAB), which is a stepwise approach for strengthening biosecurity management along value chains to enhance the health, resilience, and sustainability of animal sectors. The findings highlight important elements and provide recommendations useful for developing approaches or a global framework to progressively improve biosecurity management.

Serological evidence of SARS-CoV-2 infection in dromedary camels and domestic bovids in Oman.

SARS-CoV-2 has demonstrated the ability to infect a wide range of animal species. Here, we investigated SARS-CoV-2 infection in livestock species in Oman and provided serological evidence of SARS-CoV-2 infection in cattle, sheep, goats, and dromedary camel using the surrogate virus neutralization and plaque reduction neutralization tests. To better understand the extent of SARS-CoV-2 infection in animals and associated risks, "One Health" epidemiological investigations targeting animals exposed to COVID-19 human cases should be implemented with integrated data analysis of the epidemiologically linked human and animal cases.

One health systems strengthening in countries: Tripartite tools and approaches at the human-animal-environment interface.

Unexpected pathogen transmission between animals, humans and their shared environments can impact all aspects of society. The Tripartite organisations-the Food and Agriculture Organization of the United Nations (FAO), the World Health Organization (WHO), and the World Organisation for Animal Health (WOAH)-have been collaborating for over two decades. The inclusion of the United Nations Environment Program (UNEP) with the Tripartite, forming the 'Quadripartite' in 2021, creates a new and important avenue to engage environment sectors in the development of additional tools and resources for One Health coordination and improved health security globally. Beginning formally in 2010, the Tripartite set out strategic directions for the coordination of global activities to address health risks at the human-animal-environment interface. This paper highlights the historical background of this collaboration in the specific area of health security, using country examples to demonstrate lessons learnt and the evolution and pairing of Tripartite programmes and processes to jointly develop and deliver capacity strengthening tools to countries and strengthen performance for iterative evaluations. Evaluation frameworks, such as the International Health Regulations (IHR) Monitoring and Evaluation Framework, the WOAH Performance of Veterinary Services (PVS) Pathway and the FAO multisectoral evaluation tools for epidemiology and surveillance, support a shared global vision for health security, ultimately serving to inform decision making and provide a systematic approach for improved One Health capacity strengthening in countries. Supported by the IHR-PVS National Bridging Workshops and the development of the Tripartite Zoonoses Guide and related operational tools, the Tripartite and now Quadripartite, are working alongside countries to address critical gaps at the human-animal-environment interface.

Development of core competencies for field veterinary epidemiology training programs.

A workforce with the adequate field epidemiology knowledge, skills and abilities is the foundation of a strong and effective animal health system. Field epidemiology training is conducted in several countries to meet the increased global demand for such a workforce. However, core competencies for field veterinary epidemiology have not been identified and agreed upon globally, leading to the development of different training curricula. Having a set of agreed core competencies can harmonize field veterinary epidemiology training. The Food and Agriculture Organization of the United Nations (FAO) initiated a collective, iterative, and participative process to achieve this and organized two expert consultative workshops in 2018 to develop core competencies for field veterinary epidemiology at the frontline and intermediate levels. Based on these expert discussions, 13 competencies were identified for the frontline and intermediate levels. These competencies were organized into three domains: epidemiological surveillance and studies; field investigation, preparedness and response; and One Health, communication, ethics and professionalism. These competencies can be used to facilitate the development of field epidemiology training curricula for veterinarians, adapted to country training needs, or customized for training other close disciplines. The competencies can also be useful for mentors and employers to monitor and evaluate the progress of their mentees, or to guide the selection process during the recruitment of new staff.

Detection of highly pathogenic avian influenza in Sekong Province Lao PDR 2018-Potential for improved surveillance and management in endemic regions.

Significant global efforts have been directed towards understanding the epidemiology of highly pathogenic avian influenza (HPAI) across poultry production systems and in wild-bird reservoirs, yet understanding of disease dynamics in the village poultry setting remains limited. This article provides a detailed account of the first laboratory-confirmed outbreak of HPAI in the south-eastern provinces of Lao PDR, which occurred in a village in Sekong Province in October 2018. Perspectives from an anthropologist conducting fieldwork at the time of the outbreak, clinical and epidemiological observations by an Australian veterinarian are combined with laboratory characterization and sequencing of the virus to provide insights about disease dynamics, biosecurity, outbreak response and impediments to disease surveillance. Market-purchased chickens were considered the likely source of the outbreak. Observations highlighted the significance of a-lack-of pathognomonic clinical signs and commonness of high-mortality poultry disease with consequent importance of laboratory diagnosis. Sample submission and testing was found to be efficient, despite the village being far from the national veterinary diagnostic laboratory. Extensively raised poultry play key roles in ritual, livelihoods and nutrition of rural Lao PDR people. Unfortunately, mass mortality of chickens due to diseases such as HPAI and Newcastle disease (ND) imposes a significant burden on smallholders in Lao PDR, as in most other SE Asian countries. We observed that high mortality of chickens is perceived by locals as a new 'normal' in raising poultry; this sense of it being 'normal' is a disincentive to reporting of mortality events. Establishing effective people-centred disease-surveillance approaches with local benefit, improving market-biosecurity and veterinary-service support to control vaccine-preventable poultry diseases could all reduce mass-mortality event frequency, improve veterinary-producer relationships and increase the likelihood that mortality events are reported. Priority in each of these aspects should be on working with smallholders and local traders, appreciating and respecting their perspectives and local knowledge.

Geographical and Historical Patterns in the Emergences of Novel Highly Pathogenic Avian Influenza (HPAI) H5 and H7 Viruses in Poultry.

Over the years, the emergence of novel H5 and H7 highly pathogenic avian influenza viruses (HPAI) has been taking place through two main mechanisms: first, the conversion of a low pathogenic into a highly pathogenic virus, and second, the reassortment between different genetic segments of low and highly pathogenic viruses already in circulation. We investigated and summarized the literature on emerging HPAI H5 and H7 viruses with the aim of building a spatio-temporal database of all these recorded conversions and reassortments events. We subsequently mapped the spatio-temporal distribution of known emergence events, as well as the species and production systems that they were associated with, the aim being to establish their main characteristics. From 1959 onwards, we identified a total of 39 independent H7 and H5 LPAI to HPAI conversion events. All but two of these events were reported in commercial poultry production systems, and a majority of these events took place in high-income countries. In contrast, a total of 127 reassortments have been reported from 1983 to 2015, which predominantly took place in countries with poultry production systems transitioning from backyard to intensive production systems. Those systems are characterized by several co-circulating viruses, multiple host species, regular contact points in live bird markets, limited biosecurity within value chains, and frequent vaccination campaigns that impose selection pressures for emergence of novel reassortants. We conclude that novel HPAI emergences by these two mechanisms occur in different ecological niches, with different viral, environmental and host associated factors, which has implications in early detection and management and mitigation of the risk of emergence of novel HPAI viruses.

Modelling H5N1 in Bangladesh across spatial scales: Model complexity and zoonotic transmission risk.

Highly pathogenic avian influenza H5N1 remains a persistent public health threat, capable of causing infection in humans with a high mortality rate while simultaneously negatively impacting the livestock industry. A central question is to determine regions that are likely sources of newly emerging influenza strains with pandemic causing potential. A suitable candidate is Bangladesh, being one of the most densely populated countries in the world and having an intensifying farming system. It is therefore vital to establish the key factors, specific to Bangladesh, that enable both continued transmission within poultry and spillover across the human-animal interface. We apply a modelling framework to H5N1 epidemics in the Dhaka region of Bangladesh, occurring from 2007 onwards, that resulted in large outbreaks in the poultry sector and a limited number of confirmed human cases. This model consisted of separate poultry transmission and zoonotic transmission components. Utilising poultry farm spatial and population information a set of competing nested models of varying complexity were fitted to the observed case data, with parameter inference carried out using Bayesian methodology and goodness-of-fit verified by stochastic simulations. For the poultry transmission component, successfully identifying a model of minimal complexity, which enabled the accurate prediction of the size and spatial distribution of cases in H5N1 outbreaks, was found to be dependent on the administration level being analysed. A consistent outcome of non-optimal reporting of infected premises materialised in each poultry epidemic of interest, though across the outbreaks analysed there were substantial differences in the estimated transmission parameters. The zoonotic transmission component found the main contributor to spillover transmission of H5N1 in Bangladesh was found to differ from one poultry epidemic to another. We conclude by discussing possible explanations for these discrepancies in transmission behaviour between epidemics, such as changes in surveillance sensitivity and biosecurity practices.

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

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

Could Changes in the Agricultural Landscape of Northeastern China Have Influenced the Long-Distance Transmission of Highly Pathogenic Avian Influenza H5Nx Viruses?

In the last few years, several reassortant subtypes of highly pathogenic avian influenza viruses (HPAI H5Nx) have emerged in East Asia. These new viruses, mostly of subtype H5N1, H5N2, H5N6, and H5N8 belonging to clade 2.3.4.4, have been found in several Asian countries and have caused outbreaks in poultry in China, South Korea, and Vietnam. HPAI H5Nx also have spread over considerable distances with the introduction of viruses belonging to the same 2.3.4.4 clade in the U.S. (2014-2015) and in Europe (2014-2015 and 2016-2017). In this paper, we examine the emergence and spread of these new viruses in Asia in relation to published datasets on HPAI H5Nx distribution, movement of migratory waterfowl, avian influenza risk models, and land-use change analyses. More specifically, we show that between 2000 and 2015, vast areas of northeast China have been newly planted with rice paddy fields (3.21 million ha in Heilongjiang, Jilin, and Liaoning) in areas connected to other parts of Asia through migratory pathways of wild waterfowl. We hypothesize that recent land use changes in northeast China have affected the spatial distribution of wild waterfowl, their stopover areas, and the wild-domestic interface, thereby altering transmission dynamics of avian influenza viruses across flyways. Detailed studies of the habitat use by wild migratory birds, of the extent of the wild-domestic interface, and of the circulation of avian influenza viruses in those new planted areas may help to shed more light on this hypothesis, and on the possible impact of those changes on the long-distance patterns of avian influenza transmission.

Global mapping of highly pathogenic avian influenza H5N1 and H5Nx clade 2.3.4.4 viruses with spatial cross-validation.

Global disease suitability models are essential tools to inform surveillance systems and enable early detection. We present the first global suitability model of highly pathogenic avian influenza (HPAI) H5N1 and demonstrate that reliable predictions can be obtained at global scale. Best predictions are obtained using spatial predictor variables describing host distributions, rather than land use or eco-climatic spatial predictor variables, with a strong association with domestic duck and extensively raised chicken densities. Our results also support a more systematic use of spatial cross-validation in large-scale disease suitability modelling compared to standard random cross-validation that can lead to unreliable measure of extrapolation accuracy. A global suitability model of the H5 clade 2.3.4.4 viruses, a group of viruses that recently spread extensively in Asia and the US, shows in comparison a lower spatial extrapolation capacity than the HPAI H5N1 models, with a stronger association with intensively raised chicken densities and anthropogenic factors.

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.

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.