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.

EPINEST, an agent-based model to simulate epidemic dynamics in large-scale poultry production and distribution networks.

The rapid intensification of poultry production raises important concerns about the associated risks of zoonotic infections. Here, we introduce EPINEST (EPIdemic NEtwork Simulation in poultry Transportation systems): an agent-based modelling framework designed to simulate pathogen transmission within realistic poultry production and distribution networks. We provide example applications to broiler production in Bangladesh, but the modular structure of the model allows for easy parameterization to suit specific countries and system configurations. Moreover, the framework enables the replication of a wide range of eco-epidemiological scenarios by incorporating diverse pathogen life-history traits, modes of transmission and interactions between multiple strains and/or pathogens. EPINEST was developed in the context of an interdisciplinary multi-centre study conducted in Bangladesh, India, Vietnam and Sri Lanka, and will facilitate the investigation of the spreading patterns of various health hazards such as avian influenza, Campylobacter, Salmonella and antimicrobial resistance in these countries. Furthermore, this modelling framework holds potential for broader application in veterinary epidemiology and One Health research, extending its relevance beyond poultry to encompass other livestock species and disease systems.

Modelling flock heterogeneity in the transmission of peste des petits ruminants virus and its impact on the effectiveness of vaccination for eradication.

Peste des petits ruminants (PPR) is an acute infectious disease of small ruminants targeted for global eradication by 2030. The Global Strategy for Control and Eradication (GSCE) recommends mass vaccination targeting 70% coverage of small ruminant populations in PPR-endemic regions. These small ruminant populations are diverse with heterogeneous mixing patterns that may influence PPR virus (PPRV) transmission dynamics. This paper evaluates the impact of heterogeneous mixing on (i) PPRV transmission and (ii) the likelihood of different vaccination strategies achieving PPRV elimination, including the GSCE recommended strategy. We develop models simulating heterogeneous transmission between hosts, including a metapopulation model of PPRV transmission between villages in lowland Ethiopia fitted to serological data. Our results demonstrate that although heterogeneous mixing of small ruminant populations increases the instability of PPRV transmission-increasing the chance of fadeout in the absence of intervention-a vaccination coverage of 70% may be insufficient to achieve elimination if high-risk populations are not targeted. Transmission may persist despite very high vaccination coverage (>90% small ruminants) if vaccination is biased towards more accessible but lower-risk populations such as sedentary small ruminant flocks. These results highlight the importance of characterizing small ruminant mobility patterns and identifying high-risk populations for vaccination and support a move towards targeted, risk-based vaccination programmes in the next phase of the PPRV eradication programme. Our modelling approach also illustrates a general framework for incorporating heterogeneous mixing patterns into models of directly transmitted infectious diseases where detailed contact data are limited. This study improves understanding of PPRV transmission and elimination in heterogeneous small ruminant populations and should be used to inform and optimize the design of PPRV vaccination programmes.

Antimicrobial Resistance in Escherichia coli and Its Correlation with Antimicrobial Use on Commercial Poultry Farms in Bangladesh.

Antimicrobial resistance is a global concern, posing risks to human and animal health. This research quantified antimicrobial resistance (AMR) in E. coli isolates from poultry fecal and environmental samples in Bangladesh and explored their association with antimicrobial use (AMU). We screened 725 fecal and 250 environmental samples from 94 conventional broilers and 51 Sonali farms for E. coli presence using MALDI-TOF mass spectrometry. AMU data were collected at flock levels, expressed as treatment incidence (TI), while minimum inhibitory concentrations (MIC) for 14 antibiotics were determined on five fecal E. coli isolates per farm and on all environmental isolates. MIC results were interpreted using human clinical breakpoints and EUCAST epidemiological cut-off values (ECOFFs). Acquired resistance against commonly used antimicrobial agents such as ciprofloxacin, tetracycline and ampicillin, was extremely high and predominantly clinically relevant. There was a moderate correlation between fecal and environmental antibiotic resistance index (ARI), but there was no significant correlation between AMU and AMR, suggesting that the observed AMR prevalence is unrelated to current AMU in poultry, but may be due to high historical AMU. A high level of multidrug resistance, including against critically important antimicrobials, was found in both farm types. Therefore, an AMR/AMU surveillance program is urgently needed in the poultry production sector of Bangladesh.

Genetic diversity, recombination and cross-species transmission of a waterbird gammacoronavirus in the wild.

Viruses emerging from wildlife can cause outbreaks in humans and domesticated animals. Predicting the emergence of future pathogens and mitigating their impacts requires an understanding of what shapes virus diversity and dynamics in wildlife reservoirs. In order to better understand coronavirus ecology in wild species, we sampled birds within a coastal freshwater lagoon habitat across 5 years, focussing on a large population of mute swans (Cygnus olor) and the diverse species that they interact with. We discovered and characterised the full genome of a divergent gammacoronavirus belonging to the Goose coronavirus CB17 species. We investigated the genetic diversity and dynamics of this gammacoronavirus using untargeted metagenomic sequencing of 223 faecal samples from swans of known age and sex, and RT-PCR screening of 1632 additional bird samples. The virus circulated persistently within the bird community; virus prevalence in mute swans exhibited seasonal variations, but did not change with swan age-class or epidemiological year. One whole genome was fully characterised, and revealed that the virus originated from a recombination event involving an undescribed gammacoronavirus species. Multiple lineages of this gammacoronavirus co-circulated within our study population. Viruses from this species have recently been detected in aquatic birds from both the Anatidae and Rallidae families, implying that host species habitat sharing may be important in shaping virus host range. As the host range of the Goose coronavirus CB17 species is not limited to geese, we propose that this species name should be updated to 'Waterbird gammacoronavirus 1'. Non-invasive sampling of bird coronaviruses may provide a tractable model system for understanding the evolutionary and cross-species dynamics of coronaviruses.

Quantitative and qualitative analysis of antimicrobial usage and biosecurity on broiler and Sonali farms in Bangladesh.

Antimicrobial use (AMU) is a major contributing factor to the rising threat of antimicrobial resistance (AMR) in human and animals. To control AMR, indiscriminate antibiotic use needs to be restricted, preventive measures such as biosecurity must be prioritized and proper action plans must be implemented. This study aimed to quantify and associate AMU and biosecurity status of broiler and Sonali farms in Bangladesh. Data on all antimicrobial treatments administered during a batch production cycle and antimicrobials purchased over a year were collected from 94 conventional broiler and 51 Sonali (cross-breed) farms from the northern and southeast regions of Bangladesh. Flock-level AMU was quantified using Treatment Incidence (TI) per 100 days based on the Defined Daily Dose (TIDDDvet) expressing the number of days per 100 animal-days at risk that the flock receives a standard dose of antimicrobials. The biosecurity status (external and internal) of these farms was assessed by means of the Biocheck.UGent scoring system and the correlation between biosecurity and TIDDDvet were assessed by Pearson's correlation coefficients. Median flock TIDDDvet was 60 and 58 for broilers and Sonali flocks, indicating that the birds were treated around 60% and 58% of their lifetime with an antimicrobial dose, respectively. Minimum and maximum values of TIDDDvet ranged from 18 -188 and 31-212 in broilers and Sonali, respectively. Fluoroquinolones, sulfonamides, tetracyclines and aminopenicillins were the most frequently used antimicrobial classes. The mean external and internal biosecurity scores were 39% and 61% for broilers and 44% and 61% for Sonali, respectively. There was a statistically significant difference in the external biosecurity score in broiler farms in the two regions (p ≤ 0.001), whereas, the internal biosecurity score was borderline not statistically significantly different (p = 0.065). The biosecurity score was negatively correlated with AMU in broiler and sonali farms both for external (R2 =-0.38; -0.36) and internal biosecurity (R2 =-0.33; -0.32), respectively. As most of the farmers treated their birds with antimicrobials for a very large part of the production, it could be concluded that there is a high overuse of antimicrobials both in broiler and Sonali poultry production in Bangladesh. This study also highlighted a low level of farm biosecurity practices. Overuse of antimicrobials and low level of biosecurity practice may be due to a lack of knowledge, ignorance, avoid loss and/or lack of monitoring by governmental agencies. Therefore, urgent action is required to increase awareness and biosecurity levels and to reduce AMU in these production systems.

Contrasting seasonality of African swine fever outbreaks and its drivers.

The seasonality of African swine fever (ASF) outbreaks in domestic pigs differs between temperate and subtropical/tropical regions. We hypothesise that variations in the importance of wild boar-to-farm and farm-to-farm transmission routes shape these contrasting patterns, and we emphasise the implications for effective ASF control.

Mapping of dressed and processed poultry products in Bangladesh: Identifying the food safety risks for policy intervention.

Bangladesh's commercial poultry production is growing rapidly, including the commercial processing of poultry. This expansion of poultry processing plants is fueled by the belief that this sub-sector provides safer food and has less food-borne disease risks compared to traditional live bird markets (LBMs). The purpose of this study is to describe Bangladesh's dressed and processed poultry production and distribution network (PDN), identify what and where quality control occurs, and suggest where improvements could be made. Engaging with PDN for dressed and processed poultry, we used in-depth interviews with key informants to identify the stakeholders involved and their connections with other poultry PDNs. In addition, we mapped out the supply and distribution of dressed and processed poultry and quality control processes occurring throughout the network. We argue that dressed and processed poultry PDNs are closely connected with traditional PDNs such as LBMs, with multiple crossover points between them. Also, there is a lack of consistency in quality control testing and a lack of meat traceability. Consequently, perceptions of dressed and processed poultry being safer than birds from LBMs needs to be treated with caution. Otherwise, unsubstantiated consumer confidence in dressed poultry may inadvertently increase the risk of food-borne diseases from these products.

Simulating contact networks for livestock disease epidemiology: a systematic review.

Contact structure among livestock populations influences the transmission of infectious agents among them. Models simulating realistic contact networks therefore have important applications for generating insights relevant to livestock diseases. This systematic review identifies and compares such models, their applications, data sources and how their validity was assessed. From 52 publications, 37 models were identified comprising seven model frameworks. These included mathematical models (n = 8; including generalized random graphs, scale-free, Watts-Strogatz and spatial models), agent-based models (n = 8), radiation models (n = 1) (collectively, considered 'mechanistic'), gravity models (n = 4), exponential random graph models (n = 9), other forms of statistical model (n = 6) (statistical) and random forests (n = 1) (machine learning). Overall, nearly half of the models were used as inputs for network-based epidemiological models. In all models, edges represented livestock movements, sometimes alongside other forms of contact. Statistical models were often applied to infer factors associated with network formation (n = 12). Mechanistic models were commonly applied to assess the interaction between network structure and disease dissemination (n = 6). Mechanistic, statistical and machine learning models were all applied to generate networks given limited data (n = 13). There was considerable variation in the approaches used for model validation. Finally, we discuss the relative strengths and weaknesses of model frameworks in different use cases.

Mapping chicken production and distribution networks in Vietnam: An analysis of socio-economic factors and their epidemiological significances.

The growing chicken industry in Viet Nam has an increasingly important contribution to the country's food security, but its development requires careful planning to prevent disease risks. This study characterizes the chicken production and distribution networks in Vietnam and identifies potential factors that could promote disease emergence and transmission. Qualitative data were collected from interviews with 29 key informants from five stakeholder groups representing the main nodes from chicken production and distribution networks (PDN). Three main networks were identified based on production type: a colored broiler and spent hen network, a white (or exotic) broiler network, and an egg network. Colored chickens and spent hens are the most preferred commodity by vietnamese consumers and their PDN is composed of production units differing in their scale and management and with long distribution chains involving numerous small-scale independent stakeholders. Live bird markets plays a central role in this network, which is driven by consumers' preference for live chickens. The white chicken network presents an important duality, as it is composed of both a large number of independent household farms and traders operating independently with little chain coordination, and of large farms contracted by vertically-integrated companies. The egg PDN was the most organized network, being mostly controlled by large vertically-integrated companies. High level specialization and diversification of stakeholders is found in all three networks. Stakeholders' perceptions of the main factors promoting disease risk along the PDN were the low biosecurity in household farms and live bird markets, mobile traders, the informal slaughter of birds and the management of sick birds. Findings from this study can be used to plan future studies to support food system planners in the development of safer poultry production and distribution in Vietnam.

Elasticity and substitutability of food demand and emerging disease risk on livestock farms.

Disease emergence in livestock is a product of environment, epidemiology and economic forces. The environmental factors contributing to novel pathogen emergence in humans have been studied extensively, but the two-way relationship between farm microeconomics and outbreak risk has received comparably little attention. We introduce a game-theoretic model where farmers produce and sell two goods, one of which (e.g. pigs, poultry) is susceptible to infection by a pathogen. We model market and epidemiological effects at both the individual farm level and the community level. We find that in the case of low demand elasticity for livestock meat, the presence of an animal pathogen causing production losses can lead to a bistable system where two outcomes are possible: (i) successful disease control or (ii) maintained disease circulation, where farmers slaughter their animals at a low rate, face substantial production losses, but maintain large herds because of the appeal of high meat prices. Our observations point to the potentially critical effect of price elasticity of demand for livestock products on the success or failure of livestock disease control policies. We show the potential epidemiological benefits of (i) policies aimed at stabilizing livestock product prices, (ii) subsidies for alternative agricultural activities during epidemics, and (iii) diversifying agricultural production and sources of proteins available to consumers.

Revealing the Relational Mechanisms of Research for Development Through Social Network Analysis.

Achieving impact through research for development programmes (R4D) requires engagement with diverse stakeholders across the research, development and policy divides. Understanding how such programmes support the emergence of outcomes, therefore, requires a focus on the relational aspects of engagement and collaboration. Increasingly, evaluation of large research collaborations is employing social network analysis (SNA), making use of its relational view of causation. In this paper, we use three applications of SNA within similar large R4D programmes, through our work within evaluation of three Interidsiplinary Hubs of the Global Challenges Research Fund, to explore its potential as an evaluation method. Our comparative analysis shows that SNA can uncover the structural dimensions of interactions within R4D programmes and enable learning about how networks evolve through time. We reflect on common challenges across the cases including navigating different forms of bias that result from incomplete network data, multiple interpretations across scales, and the challenges of making causal inference and related ethical dilemmas. We conclude with lessons on the methodological and operational dimensions of using SNA within monitoring, evaluation and learning (MEL) systems that aim to support both learning and accountability. Supplementary Information: The online version contains supplementary material available at 10.1057/s41287-023-00576-y.

Pour que les programmes de recherche pour le développement (R4D ou Research for Developmement en anglais) aient un impact, il faut un engagement entre diverses parties prenantes dans les domaines de la recherche, du développement et des politiques. Il est nécessaire de se concentrer sur les aspects relationnels de l'engagement et de la collaboration si l'on souhaite comprendre la façon dont ce type de programme permet l'émergence de résultats. L'évaluation des grands consortia de recherche utilise de plus en plus fréquemment l'analyse des réseaux sociaux (SNA ou social network analysis en anglais) en appliquant sa vision relationnelle de la causalité. Dans cet article, en vue d'explorer son potentiel en tant que méthode d'évaluation, nous utilisons trois applications d'analyse des réseaux sociaux au sein de grands programmes R4D similaires dans le cadre de notre travail d'évaluation de trois pôles interdisciplinaires du Fonds de recherche sur les défis mondiaux. Notre analyse comparative montre que l'analyse des réseaux sociaux peut révéler les dimensions structurelles des interactions au sein de ces programmes et permettre d'apprendre comment les réseaux évoluent dans le temps. Nous menons une réflexion quant aux défis communs qui émanent de ces cas, y compris la gestion de différentes formes de biais qui résultent de données de réseau incomplètes, de multiples interprétations sur des échelles différentes et les défis liés au fait d'établir une inférence causale et les dilemmes éthiques connexes. Nous concluons par des leçons sur les dimensions méthodologiques et opérationnelles de l'utilisation de l'analyse des réseaux sociaux dans les systèmes de suivi, d'évaluation et d'apprentissage (SEA) qui visent à soutenir à la fois l'apprentissage et la redevabilité.

Social and cognitive factors influencing commercial chicken farmers' antimicrobial usage in Bangladesh.

Adapting the Social Cognitive Theory framework, we conducted a cross-sectional study on 137 commercial chicken farms in Bangladesh to investigate factors influencing the behaviour of farmers towards the application of antimicrobials to their birds. Almost all farmers used antimicrobials to treat poultry diseases, while 38.6% also were using them to promote healthy growth of chickens and 10.2% to increase egg production or improve meat quality. Using Structural Equation Modeling (SEM), we identified that inappropriate usage of antimicrobials (behaviour) was strongly driven by farmers' short-term goals to maintain the health of their chickens in a production cycle (ß = 0.813, p = 0.029), rather than long-term concerns. Farmers' perception about their ability to control antimicrobial administration based on their skills and opportunities (self-efficacy) marginally influenced the short-term goals of antimicrobial usage (ß = 0.301, p = 0.073). The results of this study can be used to develop targeted education programs for farmers, to reduce the application of antimicrobials in their poultry flocks.

Bidirectional Movement of Emerging H5N8 Avian Influenza Viruses Between Europe and Asia via Migratory Birds Since Early 2020.

Migratory birds play a critical role in the rapid spread of highly pathogenic avian influenza (HPAI) H5N8 virus clade 2.3.4.4 across Eurasia. Elucidating the timing and pattern of virus transmission is essential therefore for understanding the spatial dissemination of these viruses. In this study, we surveyed >27,000 wild birds in China, tracked the year-round migration patterns of 20 bird species across China since 2006, and generated new HPAI H5N8 virus genomic data. Using this new data set, we investigated the seasonal transmission dynamics of HPAI H5N8 viruses across Eurasia. We found that introductions of HPAI H5N8 viruses to different Eurasian regions were associated with the seasonal migration of wild birds. Moreover, we report a backflow of HPAI H5N8 virus lineages from Europe to Asia, suggesting that Europe acts as both a source and a sink in the global HPAI virus transmission network.

Antibiotic usage practices and its drivers in commercial chicken production in Bangladesh.

Irrational and inappropriate use of antibiotics in commercial chicken production can contribute to the development of antimicrobial resistance. We aimed to assess antibiotic usage in commercial chicken production in Bangladesh, and identify factors associated with this practice. We conducted a large-scale cross-sectional study to collect information on antibiotic usage in commercial chickens from January to May 2021. Structured interviews were conducted with 288 broiler, 288 layer and 192 Sonali (locally-produced cross-bred) farmers in 20 sub-districts across Bangladesh. The frequency of antibiotic usage, the types of antibiotics and purpose of usage were estimated for each production type. Adjusted odds ratios (aOR) were calculated to measure the association between antibiotic usage and factors related to the characteristics of the farms and farmers using multivariable logistic regression models. The proportion of farms, irrespective of their production type, reporting usage of antibiotics in the 24 hours preceding the interview was 41% (n = 314, 95% CI: 37-44%). Forty-five percent (n = 344, 41-48%) reported antibiotic usage in the last 72 hours, 86% (n = 658, 83-88%) in the last 14 days, and almost all farms, 98% (n = 753, 97-99%), had used antibiotics since the start of their production cycle. Use of antibiotics in the 24 hours preceding an interview was more frequently reported in broiler (OR 1.91, 95% CI: 1.36-2.69) and Sonali (OR 1.94, 95% CI: 1.33-2.33) than layer farms. Oxytetracycline (23-31%, depending on production type), doxycycline (18-25%), ciprofloxacin (16-26%) and amoxicillin (16-44%) were the most frequently used antibiotics. Antibiotics were reported to be used for both treatment and prophylactic purposes on most farms (57-67%). Usage of antibiotics in the 24h preceding an interview was significantly associated with the occurrence of any illnesses in chickens (aOR broiler: 41.22 [95% CI:13.63-124.62], layer: aOR 36.45[9.52-139.43], Sonali: aOR 28.47[4.97-162.97]). Antibiotic usage was mainly advised by veterinary practitioners (45-71%, depending on production type), followed by feed dealers (21-40%) and farmers (7-13%). Improvement of chicken health through good farming practices along with changes in key stakeholders (feed dealers and practitioners) attitudes towards antibiotic recommendations to farmers, may help to reduce the levels of antibiotic usage and thus contribute to mitigate antimicrobial resistance.

Sequestration and Destruction of Rinderpest Virus-Containing Material 10 Years after Eradication.

In 2021, the world marked 10 years free from rinderpest. The United Nations Food and Agriculture Organization and World Organisation for Animal Health have since made great strides in consolidating, sequencing, and destroying stocks of rinderpest virus-containing material, currently kept by only 14 known institutions. This progress must continue.

Measures, Gaps, and Mitigation Strategies in Bangladesh's COVID-19 Response.

The Coronavirus Disease 2019 (COVID-19) spread rapidly from China to most other countries around the world in early 2020 killing millions of people. To prevent virus spread, world governments implemented a variety of response measures. This paper's objectives were to discuss the country's adopted measures to combat the virus through June 2020, identify gaps in the measures' effectiveness, and offer possible mitigations to those gaps. The measures taken included screening device deployment across international air and land ports, flight suspensions and closures from COVID-19 affected countries, and declaration and extension of a national public holiday (equivalent to lockdowns in other countries). Identified gaps were test kit, PPE, ICU beds, and ventilator shortages, limited public awareness, and insufficient coordination and collaboration among national and international partners. Proper and timely risk mapping, preparedness, communication, coordination, and collaboration among governments and organizations, and public awareness and engagement would have provided sufficient COVID-19 mitigation in Bangladesh.