Current and potential use of animal disease data by stakeholders in the global south and north.

What cannot be measured will not be managed. The Global Burden of Animal Diseases (GBADs) will generate information on animal disease burdens by species, production system, type and gender of farmer and consumer, geographical region, and time period. To understand the demand for burden of animal disease (BAD) data and how end-users might benefit from this, we reviewed the literature on animal diseases prioritisation processes (ADPP) and conducted a survey of BAD information users. The survey covered their current use of data and prioritizations as well as their needs for different, more, and better information. We identified representative (geography, sector, species) BAD experts from the authors' networks and publicly available documents and e-mailed 1485 experts. Of 791 experts successfully contacted, 271 responded (34% response rate), and 185 complete and valid responses were obtained. Most respondents came from the public sector followed by academia/research, and most were affiliated to institutions in low- and middle-income countries (LMICs). Of the six ADPPs commonly featured in literature, only three were recognised by more than 40% of experts. An additional 23 ADPPs were used. Awareness of ADDPs varied significantly by respondents. Respondents ranked animal disease priorities. We used exploded logit to combine first, second and third disease priorities to better understand prioritzation and their determinants. Expert priorities differed significantly from priorities identified by the ADDPs, and also from the priorities stated veterinary services as reported in a survey for a World Organisation of Animal Health (WOAH) technical item. Respondents identified 15 different uses of BAD data. The most common use was presenting evidence (publications, official reports, followed by disease management, policy development and proposal writing). Few used disease data for prioritzation or resource allocation, fewer routinely used economic data for decision making, and less than half were aware of the use of decision support tools (DSTs). Nearly all respondents considered current BAD metrics inadequate, most considered animal health information insufficiently available and not evidence-based, and most expressed concerns that decision-making processes related to animal health lacked transparency and fairness. Cluster analysis suggested three clusters of BAD users and will inform DSTs to help them better meet their specific objectives. We conclude that there is a lack of satisfaction with current BAD information, and with existing ADDPs, contributing to sub-optimal decision making. Improved BAD data would have multiple uses by different stakeholders leading to better evidenced decisions and policies; moreover, clients will need support (including DSTs) to optimally use BAD information.

Contribution of the veterinary profession to the Australian animal health surveillance system and opportunities for future contributions.

Animal health surveillance is crucial for early detection of emergency animal diseases and effective responses. However, surveillance systems are complex and rely on the contributions of many animal health stakeholders. Veterinarians are key stakeholders in this system, given their role and skills in investigating, diagnosing, and reporting notifiable diseases. This study investigated the contribution of the veterinary workforce to the Australian animal health surveillance system and opportunities for future involvement. To achieve the aims of the study, an online cross-sectional survey among the veterinary profession was conducted. Descriptive statistics and regression analyses were used to provide an overview and investigate drivers of attitudes and practices of veterinarians in relation to animal health surveillance. A total of 311 usable responses were obtained, with 191 being from veterinarians who worked in private practice in the previous 12 months. Among private practitioners, 58.6% worked with companion animals, 34.0% were mixed practice veterinarians and 7.3% were equine veterinarians. Over half (56.6%) of all participants considered themselves active participants in the local animal disease management system. The level of confidence in understanding the reporting system and knowing and identifying signs of endemic and exotic diseases was moderate among those working in private practice, with companion animal veterinarians reporting the lowest levels of confidence (p < 0.05). Approximately 40% of veterinarians had taken samples for diagnosis for notifiable diseases in the last year, with just over 20% reporting a notifiable disease. Awareness of and participation in training and surveillance programs for animal diseases by veterinarians was low, with those working in private practice having lower levels of both awareness and participation for most programs. In relation to potential future contribution to the surveillance system, over half of participants reported being interested and available to undertake surveillance work on behalf of the government, with those in mixed practice reporting higher levels of interest (69.6%) compared to those in companion (49.5%) and equine practice (30.8%). However, key challenges identified were related to perceived conflict of interest, and tensions between client needs and government agenda, followed by profitability and suitability of the business. This study provides evidence of a significant existing contribution by the veterinary profession to the surveillance system, and the capacity and willingness to increase this contribution. However, there are gaps in awareness, confidence and participation, as well as financial and veterinary-client relationship challenges that should be considered in any future planning to strengthen the Australian surveillance system.

[Proceedings of the International Symposium of the World Association of Veterinary Laboratory Diagnosticians, 2023]. / Compte-rendu du Symposium international de la Société mondiale des Laboratoires vétérinaires de diagnostic, 2023.

The International Symposium of the World Association of Veterinary Laboratory Diagnosticians (ISWAVLD) is the unmissable biannual meeting of all diagnostic veterinary laboratories including biologists, veterinarians and other scientists involved in laboratory diagnostics. It took place at the Lyon Convention Centre (29 June-1 July 2023). It was a pleasant and enriching moment, which allowed participants to discover and/or discuss new diagnostic methods and the epidemiology of animal diseases, around all themes involving veterinarians (animal health, but also environmental and human health, and food safety).

Adoption of veterinary vaccines, determining factors, and barriers in Southwest Ethiopia: Implications for livestock health and disease management strategies.

In Ethiopia, the use of veterinary vaccines to control animal diseases is an effective strategy. A study conducted in Southwest Ethiopia from October 2020 to October 2021 aimed to determine the adoption level of veterinary vaccines and factors affecting their use. The study used multistage random sampling to select districts and interviewed 476 farmers who had either adopted or not adopted the vaccines. The study found that certain diseases should be prioritized for vaccination to safeguard the health of cattle, sheep, goats, and poultry. These include anthrax (19.12 %), blackleg (17.65 %), foot and mouth disease (10.50 %), and lumpy skin disease (8.82 %) in cattle, and pasteurellosis (18.07 %), contagious caprine pleuropneumonia (15.97 %), peste des petits ruminants (14.15 %), and Orf (13.45 %) in sheep and goats. Newcastle disease (21.85 %), infectious bursal disease (19.33 %), and coccidiosis (17.02 %) were identified as high-priority diseases for flock health. Overall, 30.7 % of farmers were adopters of veterinary vaccines, while 69.3 % were non-adopters. The study identified several factors that influence the likelihood of adopting veterinary vaccines, including breed type (OR = 9.1, p < 0.0001), production size (OR = 9.7, p < 0.0001), production type (OR = 2.7, p < 0.0001), and farm location (OR = 9.8, p = 0.001). Common barriers to vaccination included a lack of disease knowledge, high vaccine costs, limited vaccine availability, and administration difficulties. Insights from the study can guide strategies for promoting veterinary vaccine adoption in Ethiopia. Stakeholders should pay attention to these findings since vaccine use is crucial for controlling animal diseases, enhancing animal health, and preventing economic losses. Further research is needed to investigate factors affecting enhanced veterinary vaccine adoption.

Rationalising development of classification systems describing livestock production systems for disease burden analysis within the Global Burden of Animal Diseases programme.

The heterogeneity that exists across the global spectrum of livestock production means that livestock productivity, efficiency, health expenditure and health outcomes vary across production systems. To ensure that burden of disease estimates are specific to the represented livestock population and people reliant upon them, livestock populations need to be systematically classified into different types of production system, reflective of the heterogeneity across production systems. This paper explores the data currently available of livestock production system classifications and animal health through a scoping review as a foundation for the development of a framework that facilitates more specific estimates of livestock disease burdens. A top-down framework to classification is outlined based on a systematic review of existing classification methods and provides a basis for simple grouping of livestock at global scale. The proposed top-down classification framework, which is dominated by commodity focus of production along with intensity of resource use, may have less relevance at the sub-national level in some jurisdictions and will need to be informed and adapted with information on how countries themselves categorize livestock and their production systems. The findings in this study provide a foundation for analysing animal health burdens across a broad level of production systems. The developed framework will fill a major gap in how livestock production and health are currently approached and analysed.

Identifying target areas for risk-based surveillance and control of transboundary animal diseases: a seasonal analysis of slaughter and live-trade cattle movements in Uganda.

Animal movements are a major driver for the spread of Transboundary Animal Diseases (TADs). These movements link populations that would otherwise be isolated and hence create opportunities for susceptible and infected individuals to meet. We used social network analysis to describe the seasonal network structure of cattle movements in Uganda and unravel critical network features that identify districts or sub-regions for targeted risk-based surveillance and intervention. We constructed weighted, directed networks based on 2019 between-district cattle movements using official livestock mobility data; the purpose of the movement ('slaughter' vs. 'live trade') was used to subset the network and capture the risks more reliably. Our results show that cattle trade can result in local and long-distance disease spread in Uganda. Seasonal variability appears to impact the structure of the network, with high heterogeneity of node and edge activity identified throughout the seasons. These observations mean that the structure of the live trade network can be exploited to target influential district hubs within the cattle corridor and peripheral areas in the south and west, which would result in rapid network fragmentation, reducing the contact structure-related trade risks. Similar exploitable features were observed for the slaughter network, where cattle traffic serves mainly slaughter hubs close to urban centres along the cattle corridor. Critically, analyses that target the complex livestock supply value chain offer a unique framework for understanding and quantifying risks for TADs such as Foot-and-Mouth disease in a land-locked country like Uganda. These findings can be used to inform the development of risk-based surveillance strategies and decision making on resource allocation. For instance, vaccine deployment, biosecurity enforcement and capacity building for stakeholders at the local community and across animal health services with the potential to limit the socio-economic impact of outbreaks, or indeed reduce their frequency.

A web-based geographic information system monitoring wildlife diseases in Abruzzo and Molise regions, Southern Italy.

BACKGROUND: Nowadays there is a worldwide consensus on the importance of conducting wildlife disease surveillance. Indeed, 60% of emerging infectious diseases are zoonotic in nature, and the majority of these (71.8%) originate in wildlife. Surveillance of wildlife diseases is crucial to prevent negative effects on human and animal health. Data digitization and sharing are among the main goals for the present and coming years. Geographic Information Systems (GIS) are increasingly used to analyze the geographical distribution of diseases and the relationships between pathogenic factors and their geographic environments. METHODS: Wild animal's samples collected in the Abruzzo and Molise regions and delivered to our laboratory are entered in our Laboratory Information System and processed to be displayed through the Web-GIS mash-up presented in this paper. We built it using both open source and proprietary solutions, to produce data driven interactive maps, charts and tables to help to understand the epidemiology of wild animal diseases, their spread and trend. RESULTS: Since 2013, 9.606 samples collected from wild animals have been analyzed in the laboratories of the IZS-Teramo and have been recorded in the system, facilitating the reporting to the judicial authorities and the identification of highly risky areas to set up control and repression measures. Moreover, thanks to the monitoring health protocol, a canine distemper epidemic in wolves has been detected and monitored in its temporal and spatial evolution, as well as cases of bovine tuberculosis in wild boars. CONCLUSIONS: While it is more evident that the starting point is to choose the right sampling method, it is for sure less obvious that the information system in which data is stored is equally important. In fact, it should give the possibility to consult it in an easy and instructive way. GIS allows immediately grasping the spatial relationships between the data itself and those between the data and the territory; it is an important tool to support veterinary services in managing epidemic and non-epidemic emergencies and performing epidemiological investigations, but also to examine control plans and identify new gaps and challenges.

A new methodology to extrapolate disease freedom to an area using surveillance results from selected aquatic populations.

According to Chapter 1.4 of the World Organisation for Animal Health (WOAH) Aquatic Animal Health Code, an entire country or zone can be classified as free of a disease only if there is compelling evidence that all susceptible populations within the country or zone are free. However, the methods for achieving freedom are not prescribed in the WOAH standards and guidelines. Within this context, this paper describes a novel methodology to determine if surveillance results can be extrapolated from a study population to a target population. A framework of six criteria was developed to standardize a method for extrapolating surveillance results to other susceptible populations that have not been sampled. Criteria 1 assesses the internal validity for the freedom claim on the source population. Criteria 2 assesses which other susceptible populations have a non-negligible probability of exposure. Criteria 3 assesses whether the risk of infection upon exposure of the source population is the same or greater than each of the other susceptible populations. Finally, Criteria 4, 5 and 6 assess if the other susceptible populations would transmit the infection to the source population or if they have the same exposure pathways as the source population. We illustrate the use of this novel methodology using two hypothetical case scenarios. The presented methodology has the advantage of being applicable either retrospectively or prospectively. When applied retrospectively, it can be used to assess if the surveillance results of the source population can be extrapolated to the target population. When applied prospectively it can be used to design a more efficient surveillance system by selecting source populations from which it is easier to extrapolate surveillance results to the rest of the target population. Conclusions drawn using this methodology depend on the validity of the assumptions made when working through the methodology. We therefore recommend cautious application of the criteria and thorough review of all assumptions.

Prioritization of livestock diseases by pastoralists in Oloitoktok Sub County, Kajiado County, Kenya.

INTRODUCTION: Livestock diseases are a big challenge for the livelihood of pastoralists in sub-Saharan Africa because they reduce livestock productivity and increase mortality. Based on the literature available there is limited understanding on how pastoralists prioritize these diseases in the context of their culture, ecosystems and livelihoods. A study was conducted to provide insights on lay prioritization of animal diseases by pastoralists in Kenya. METHODOLOGY: A qualitative study was undertaken between March and July 2021. Thirty in-depth interviews and six focus group discussions (FGDs) were conducted with community members to explore community attitudes on livestock diseases prioritization. Male and female livestock keepers were purposively selected and interviewed and they were all long-term residents of the area. Fourteen key informant interviews (KIIs) were conducted with professionals from different key sectors to provide detailed stakeholder perspectives on livestock diseases. The interviews were analyzed thematically using the QSR Nvivo software to identify the emerging themes related to the study objectives. RESULTS: The pastoralists prioritized livestock diseases based on effect on their economic wellbeing, cultural values and utilization of ecosystem services. There were gender variabilities in how diseases were prioritized among the pastoralists. Men cited high priority diseases as foot and mouth disease and contagious bovine pleuropneumonia due to their regular occurrence and effect on livelihood. Notably, women regarded coenuruses as very important because it affected sheep and goats with a high mortality rate and lumpy skin disease because it rendered the meat from the carcasses inedible. Malignant catarrhal fever and trypanosomiasis were noted as some of the common diseases in the livestock-wildlife interface but not cited as priority diseases. Challenges related to disease control in pastoralist contexts exist including limited access to livestock treatment services, inadequate information on disease impact and complex environmental factors. CONCLUSION: This study sheds light on the body of knowledge in Kenya regarding livestock diseases and their prioritization by livestock keepers. This could aid in the development of a common disease control framework and prioritization at the local level which would take into consideration the dynamic socio-cultural, ecological, livelihood and economic contexts of the communities.

The World Animal Health Information System as a tool to support decision-making and research in animal health.

The World Animal Health Information System (WAHIS) collects and publishes a wealth of information gathered by individual countries' Veterinary Services, including detailed country-specific information on outbreaks of diseases listed by the World Organisation for Animal Health (WOAH, founded as OIE), including emerging diseases, in domestic animals and wildlife, and non-listed diseases in wildlife. The data set is one of the most comprehensive in the world, with 182 Members obliged to report this information to WOAH in a timely manner. As such, the data provide invaluable input for Veterinary Services, animal health researchers and stakeholders to gain insight into risk from infectious diseases, for example through the development of predictive models and risk assessments to address the risk from trade of animal products, globalisation, or movement of wildlife or vectors across country borders. This paper reviews previous analyses that have been conducted using WAHIS data and outlines ways in which these data can be used for preparedness and risk assessment.

Le Système mondial d'information zoosanitaire (WAHIS) collecte et publie une grande quantité d'informations recueillies auprès des Services vétérinaires nationaux, parmi lesquelles des données détaillées spécifiques aux pays sur les foyers de maladies listées par l'Organisation mondiale de la santé animale (OMSA, fondée en tant qu'OIE), dont les maladies émergentes, chez les animaux domestiques et dans la faune sauvage, ainsi que de maladies non listées affectant la faune sauvage. Cet ensemble de données est l'un des plus exhaustifs du monde puisque les 182 Membres de l'OMSA ont l'obligation de lui faire remonter ces informations dans WAHIS dans des délais spécifiés. Ces données sont précieuses pour les Services vétérinaires, les chercheurs travaillant dans le domaine de la santé animale et les parties prenantes car elles permettent de mieux comprendre les risques relatifs aux maladies infectieuses, notamment grâce aux modèles prédictifs et aux évaluations de risques pour traiter le risque lié au commerce de produits d'origine animale, à la mondialisation, aux mouvements de la faune sauvage ou aux vecteurs entre les pays. Les auteurs font le point sur des analyses antérieures qui ont été menées en utilisant les données de WAHIS et soulignent comment ces données peuvent être utilisées dans le cadre d'un travail de préparation et d'évaluation des risques.

El Sistema Mundial de Información Zoosanitaria (WAHIS) colecta y publica una gran cantidad de datos recogidos por los Servicios Veterinarios de cada país, en particular detallada información sobre brotes de enfermedades listadas por la Organización Mundial de Sanidad Animal (OMSA, fundada como OIE), incluidas las enfermedades emergentes, que hayan afectado a los animales domésticos o la fauna silvestre, así como enfermedades no listadas que afectan a la fauna silvestre. Se trata de uno de los conjuntos de datos más completos del mundo, ya que los 182 Miembros tienen la obligación de comunicar esta información a la OMSA dentro de plazos determinados. Estos datos son una fuente de información de gran utilidad para los Servicios Veterinarios, los investigadores que trabajan en sanidad animal y demás partes interesadas porque permiten mejorar la comprensión de los riesgos derivados de las enfermedades infecciosas, por ejemplo elaborando modelos predictivos y evaluaciones de riesgo que ayuden a manejar los riesgos ligados al comercio de productos de origen animal, la globalización o al movimiento transfronterizo de animales salvajes o vectores de enfermedad. Los autores repasan una serie de análisis previamente realizados con datos de WAHIS y explican en síntesis cómo pueden utilizarse estos datos con fines de preparación y evaluación de riesgos.

Informatics progress of the Global Burden of Animal Diseases programme towards data for One Health.

The Global Burden of Animal Diseases (GBADs) programme will provide data-driven evidence that policy-makers can use to evaluate options, inform decisions, and measure the success of animal health and welfare interventions. The GBADs' Informatics team is developing a transparent process for identifying, analysing, visualising and sharing data to calculate livestock disease burdens and drive models and dashboards. These data can be combined with data on other global burdens (human health, crop loss, foodborne diseases) to provide a comprehensive range of information on One Health, required to address such issues as antimicrobial resistance and climate change. The programme began by gathering open data from international organisations (which are undergoing their own digital transformations). Efforts to achieve an accurate estimate of livestock numbers revealed problems in finding, accessing and reconciling data from different sources over time. Ontologies and graph databases are being developed to bridge data silos and improve the findability and interoperability of data. Dashboards, data stories, a documentation website and a Data Governance Handbook explain GBADs data, now available through an application programming interface. Sharing data quality assessments builds trust in such data, encouraging their application to livestock and One Health issues. Animal welfare data present a particular challenge, as much of this information is held privately and discussions continue regarding which data are the most relevant. Accurate livestock numbers are an essential input for calculating biomass, which subsequently feeds into calculations of antimicrobial use and climate change. The GBADs data are also essential to at least eight of the United Nations Sustainable Development Goals.

Le programme " Impact mondial des maladies animales " (GBADs) a pour but de réunir des éléments probants axés sur des données, qui soient exploitables par les décideurs politiques pour évaluer les solutions envisagées, fonder leurs décisions et mesurer le succès des interventions dans les domaines de la santé et du bien-être des animaux. L'équipe informatique du GBADs a conçu un processus transparent pour l'identification, l'analyse, la visualisation et le partage des données, grâce auquel il sera possible d'estimer l'impact des maladies du bétail et de réaliser des modèles et des tableaux de bord sur le sujet. Les données ainsi réunies peuvent être combinées avec celles couvrant d'autres problématiques ayant un impact mondial (santé humaine, pertes de récoltes, maladies d'origine alimentaire) afin de fournir l'éventail complet d'informations Une seule santé requis pour faire face à des enjeux tels que la résistance aux agents antimicrobiens ou le changement climatique. La première phase du programme a consisté à recueillir des données ouvertes auprès de diverses organisations internationales (qui procèdent également à leur propre transformation numérique). Les efforts déployés pour parvenir à une estimation précise des effectifs des cheptels ont mis en lumière les difficultés à trouver les données détenues par différentes sources, à y accéder et à les recouper au fil du temps. Des ontologies et des bases de données graphiques sont en cours d'élaboration pour résoudre le problème des silos de données et pour améliorer la facilité de recherche et l'interopérabilité des données. Les données du GBADs sont désormais expliquées sous forme de tableaux de bord, de récits construits à partir des données, ainsi que dans un site web documentaire et un Manuel de gouvernance des données, tous disponibles via une interface de programmation d'applications. Le partage des évaluations de la qualité des données renforce la confiance dans ces dernières et encourage à les appliquer pour traiter les problématiques affectant l'élevage ou relevant de l'approche Une seule santé. Les données relatives au bien-être animal présentent une difficulté particulière : elles sont, pour l'essentiel, détenues à titre privé et la question de savoir quelles sont les données les plus pertinentes est toujours en discussion. Les effectifs des cheptels doivent avoir été déterminés de manière précise afin de calculer la biomasse animale, élément qui entre par la suite dans le calcul des quantités d'agents antimicrobiens utilisés et des indicateurs du changement climatique. Les données du programme GBADs sont également essentielles au regard d'au moins huit des objectifs de développement durable des Nations Unies.

El programa sobre el Impacto Global de las Enfermedades Animales (GBADs) proporcionará información contrastada y basada en el uso de datos de la que luego puedan servirse los planificadores de políticas para valorar distintas opciones, decidir con conocimiento de causa y medir la eficacia de una u otra intervención en materia de sanidad y bienestar animales. El equipo informático encargado del GBADs está preparando un proceso transparente destinado a seleccionar, analizar, visualizar y poner en común datos que ayuden a calcular la carga de enfermedades del ganado y a guiar la elaboración de modelos y paneles de control. Estos datos pueden ser combinados con datos referidos a otros grandes problemas planetarios (salud humana, pérdida de cultivos, enfermedades de transmisión alimentaria) para obtener el repertorio completo de información en clave de Una sola salud que se necesita para abordar problemáticas como la resistencia a los antimicrobianos o el cambio climático. El programa empezó por reunir datos abiertos procedentes de organizaciones internacionales (inmersas, por otra parte, en su propio proceso de transformación digital). La labor emprendida para estimar con exactitud las cifras de ejemplares del mundo pecuario reveló ciertos problemas a la hora de encontrar, obtener y conciliar datos de distintas fuentes a lo largo del tiempo. Ahora se están elaborando ontologías y bases de datos gráficos para crear conexiones entre los "silos de datos" y lograr que los datos sean a la vez más compatibles entre sí y más fáciles de localizar. Paneles de control, interpretaciones narrativas de los datos ("data stories"), un sitio web de documentación y un manual de gestión de datos ayudan a explicar y aprehender los datos del GBADs, accesibles ahora por medio de una interfaz de programación de aplicaciones. El hecho de poner en común las evaluaciones de la calidad de los datos genera mayor confianza en esta información, promoviendo con ello su aplicación en temas de ganadería y de Una sola salud. Los datos de bienestar animal plantean una particular dificultad, pues gran parte de esta información está en manos privadas y todavía no está claro cuáles son los datos de mayor interés. Disponer de cifras exactas sobre el número de cabezas de ganado es fundamental para efectuar los cálculos de biomasa que después se utilizan para hacer otros cómputos referidos al uso de antimicrobianos y al cambio climático. Los datos del GBADs son asimismo esenciales para al menos ocho de los Objetivos de Desarrollo Sostenible de las Naciones Unidas.

Animal disease surveillance: How to represent textual data for classifying epidemiological information.

The value of informal sources in increasing the timeliness of disease outbreak detection and providing detailed epidemiological information in the early warning and preparedness context is recognized. This study evaluates machine learning methods for classifying information from animal disease-related news at a fine-grained level (i.e., epidemiological topic). We compare two textual representations, the bag-of-words method and a distributional approach, i.e., word embeddings. Both representations performed well for binary relevance classification (F-measure of 0.839 and 0.871, respectively). Bag-of-words representation was outperformed by word embedding representation for classifying sentences into fine-grained epidemiological topics (F-measure of 0.745). Our results suggest that the word embedding approach is of interest in the context of low-frequency classes in a specialized domain. However, this representation did not bring significant performance improvements for binary relevance classification, indicating that the textual representation should be adapted to each classification task.

The ripple effect of animal disease outbreaks on food systems: The case of African Swine Fever on the Chinese pork market.

Research on animal health economics has emphasised the importance of accounting for the indirect economic effects of animal disease outbreaks. Although recent studies have advanced in this direction by assessing consumer and producer welfare losses due to asymmetric price adjustments, potential over-shifting effects along the supply chain and spill-overs to substitute markets have been under-examined. This study contributes to this field of research by assessing the direct and indirect effects of the African swine fever (ASF) outbreak on the pork market in China. We employ impulse response functions estimated by local projection to calculate the price adjustments for consumers and producers, as well as the cross-effect in other meat markets. The results show that the ASF outbreak led to increases in both farmgate and retail prices but the rise in retail prices exceeded the corresponding change in farmgate prices. Furthermore, beef and chicken prices also rose, demonstrating the spill-over impacts of the outbreak to other markets. Overall, the evidence illustrates that a disruption in one part of a food system can have significant ripple effects across other parts of the system.

A long-term negative effect of monetary incentives on the participatory surveillance of animal disease: a pilot study in Chiang Mai, Thailand.

BACKGROUND: In general, animal diseases have a significant impact on public health; accordingly, an effective animal disease surveillance system is an important control system that requires efficient and engaging participants in the long run. The purpose of this study is to assess the impact of monetary and social motivation on animal disease surveillance. We hypothesized that there are two sorts of motivation based on Fiske's relational theory (1992): monetary incentives (monetary markets) and nonmonetary incentives (social markets). METHODS: In Chiang Mai Province, Northern Thailand, we analyzed data from a pilot project that began in 2014 and used a mobile application to report on signs that identify animal health problems. A total of 67 participants from 17 different areas in the central part of the province participated in this study. Participants in this study were divided into two groups: those who received monetary incentives and those who received social incentives. RESULTS: According to the findings, the monetary market group's effort was significantly higher than that of the social market group during the time when the volunteers in the monetary market group were paid. However, in the long run, the monetary market group reported significantly less than the social market group. Social incentive, on the other hand, was more efficient once the payment period ended. CONCLUSIONS: Social incentive outperformed monetary motivation in terms of efficiency and sustainability in the long run. Not only did the volunteers who were offered monetary incentive put in less effort than those who were offered the social incentive, but they were also not remotivated by the social incentive after the payment period had ended.