Prioritizing live bird markets at risk of avian influenza H5N1 virus contamination for intervention: a simple tool for low resource settings

Approaches for disease prioritization and decision-making in animal health, 2000-2021: a structured scoping review

This scoping review identifies and describes the methods used to prioritize diseases for resource allocation across disease control, surveillance, and research and the methods used generally in decision-making on animal health policy. Three electronic databases (Medline/PubMed, Embase, and CAB Abstracts) were searched for articles from 2000 to 2021. Searches identified 6, 395 articles after de-duplication, with an additional 64 articles added manually. A total of 6, 460 articles were imported to online document review management software (sysrev.com) for screening. Based on inclusion and exclusion criteria, 532 articles passed the first screening, and after a second round of screening, 336 articles were recommended for full review. A total of 40 articles were removed after data extraction. Another 11 articles were added, having been obtained from cross-citations of already identified articles, providing a total of 307 articles to be considered in the scoping review. The results show that the main methods used for disease prioritization were based on economic analysis, multi-criteria evaluation, risk assessment, simple ranking, spatial risk mapping, and simulation modeling. Disease prioritization was performed to aid in decision-making related to various categories: (1) disease control, prevention, or eradication strategies, (2) general organizational strategy, (3) identification of high-risk areas or populations, (4) assessment of risk of disease introduction or occurrence, (5) disease surveillance, and (6) research priority setting. Of the articles included in data extraction, 50.5% had a national focus, 12.3% were local, 11.9% were regional, 6.5% were sub-national, and 3.9% were global. In 15.2% of the articles, the geographic focus was not specified. The scoping review revealed the lack of comprehensive, integrated, and mutually compatible approaches to disease prioritization and decision support tools for animal health. We recommend that future studies should focus on creating comprehensive and harmonized frameworks describing methods for disease prioritization and decision-making tools in animal health.

Defining "Sector 3" Poultry Layer Farms in Relation to H5N1-HPAI-An Example from Java, Indonesia

To help guide surveillance and control of highly pathogenic avian influenza subtype H5N1 (H5N1-HPAI), the Food and Agriculture Organization of the United Nations in 2004 devised a poultry farm classification system based on a combination of production and biosecurity practices. Four "Sectors" were defined, and this scheme has been widely adopted within Indonesia to guide national surveillance and control strategies. Nevertheless, little detailed research into the robustness of this classification system has been conducted, particularly as it relates to independent, small to medium-sized commercial poultry farms (Sector 3). Through an analysis of questionnaire data collected as part of a survey of layer farms in western and central Java, all of which were classified as Sector 3 by local veterinarians, we provide benchmark data on what defines this sector. A multivariate analysis of the dataset, using hierarchical cluster analysis, identified three groupings of the farms, which were defined by a combination of production-and biosecurity-related variables, particularly those related to farm size and (the lack of) washing and disinfection practices. Nevertheless, the relationship between production-related variables and positive biosecurity practices was poor, and larger farms did not have an overall higher total biosecurity score than small or medium-sized ones. Further research is required to define the properties of poultry farms in Indonesia that are most closely related to effective biosecurity and the prevention of H5N1-HPAI.