Optimizing surveillance for early disease detection: Expert guidance for Ostreid herpesvirus surveillance design and system sensitivity calculation.

Abstract To keep pace with rising opportunities for disease emergence and spread, surveillance in aquaculture must enable the early detection of both known and new pathogens. Conventional surveillance systems (designed to provide proof of disease freedom) may not support detection outside of periodic sampling windows, leaving substantial blind spots to pathogens that emerge in other times and places. To address this problem, we organized an expert panel to envision optimal systems for early disease detection, focusing on Ostreid herpesvirus 1 (OsHV-1), a pathogen of panzootic consequence to oyster industries. The panel followed an integrative group process to identify and weight surveillance system traits perceived as critical to the early detection of OsHV-1. Results offer a road map with fourteen factors to consider when building surveillance systems geared to early detection; factor weights can be used by planners and analysts to compare the relative value of different designs or enhancements. The results were also used to build a simple, but replicable, model estimating the system sensitivity (SSe) of observational surveillance and, in turn, the confidence in disease freedom that negative reporting can provide. Findings suggest that optimally designed observational systems can contribute substantially to both early detection and disease freedom confidence. In contrast, active surveillance as a singular system is likely insufficient for early detection. The strongest systems combined active with observational surveillance and engaged joint industry and government involvement: results suggest that effective partnerships can generate highly sensitive systems, whereas ineffective partnerships may seriously erode early detection capability. Given the costs of routine testing, and the value (via averted losses) of early detection, we conclude that observational surveillance is an important and potentially very effective tool for health management and disease prevention on oyster farms, but one that demands careful planning and participation. This evaluation centered on OsHV-1 detection in farmed oyster populations. However, many of the features likely generalize to other pathogens and settings, with the important caveat that the pathogens need to manifest via morbidity or mortality events in the species, life stages and environments under observation.