Open web-based application to optimise sampling strategies for active surveillance activities at the herd level

Design of efficient active surveillance sampling schemes is challenging because optimal surveillance strategies may differ depending on the epidemiological conditions of the farm, including infection status, structure, management, or resources for conducting samplings. We present ‘OptisampleTM’, an open web-based application designed to optimise farm sampling strategies to substantiate freedom of infection considering also costs of testing. In addition to herd size, expected prevalence, test sensitivity, and desired level of confidence, this tool takes into account the risk of disease introduction at different stages of the production cycle, the structure of the herd, and the procedures used to select the samples over time. We illustrate its functionality through its application for active surveillance of porcine reproductive and respiratory syndrome virus (PRRSv) in hypothetical swine herds under different epidemiological conditions. Diverse sampling schemes for each farm were simulated and the most cost-effective strategy was estimated for each farm. The model shows the importance of considering the epidemiological context and the process of sampling selection to demonstrate freedom from disease. The approach demonstrated for PRRSv may be easily extended to other animal disease surveillance systems using the web-based application available at https://final.shinyapps. io/optisampleTM/.