A novel approach for directly incorporating disease into fish stock assessment: a case study with seroprevalence data

• Published in: Canadian journal of fisheries and aquatic sciences Vol. 79; no. 4; pp. 611 - 630
• Main Authors: Trochta, John T, Groner, Maya L, Hershberger, Paul K, Branch, Trevor A
• Format: Journal Article
• Language: English
• Published: 1840 Woodward Drive, Suite 1, Ottawa, ON K2C 0P7 Canadian Science Publishing 01.04.2022; NRC Research Press; Canadian Science Publishing NRC Research Press
• Subjects: Age; Analysis; Animals; Antibodies; Case studies; Clupea pallasii; Disease; Diseases; Epidemic models; Epidemiology; Estimation; Fish; Fish populations; Hemorrhage; Hemorrhagic septicemia; Infections; Mortality; Population; Population biology; Population dynamics; Populations; Prevalence studies (Epidemiology); Serology; Simulation; Stock assessment; Stock assessment (Wildlife management); Viruses; United States
• ISSN: 0706-652X; 1205-7533
• DOI: 10.1139/cjfas-2021-0094

When estimating mortality from disease with fish population models, common disease surveillance data such as infection prevalence are not always informative, especially for fast-acting diseases that may go unobserved in infrequently sampled populations. In these cases, seroprevalence — the proportion of fish with measurable antibody levels in their blood — may be more informative. In cases of life-long immunity, seroprevalence data require less frequent sampling intervals than infection prevalence data and can reflect the cumulative exposure history of fish. We simulation tested the usefulness of seroprevalence data in an age-structured fish stock assessment model using viral hemorrhagic septicemia virus (VHSV) in Pacific herring (Clupea pallasii) as a case study. We developed a novel epidemiological model to simulate population dynamics and seroprevalence data and fitted to these data in an integrated catch-at-age model with equations that estimate age- and time-varying mortality from disease. We found that simulated seroprevalence data can provide accurate estimates of infection history and disease-associated mortality. Importantly, even models that misspecified nonstationary processes in background or disease-associated mortality, but included seroprevalence data, accurately estimated annual infection and population abundance.