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Understanding the morbidity and lethality of diseases is necessary to evaluate the effectiveness of countermeasure against the epidemics (e.g., vaccination). To estimate them, detailed data on host population dynamics are required; however, estimating the population size for wildlife is often difficult. We aimed to elucidate the morbidity and lethality of classical swine fever (CSF) currently highly prevalent in the wild boar population in Japan. To this end, we estimated lethality rate, recovery rate, and case fatality ratio (CFR) of CSF without detailed data on the population estimates of wild boar. A mathematical model was constructed to describe the CSF dynamics and population dynamics of wild boar. We fitted the model to the (i) results of the reverse transcription polymerase chain reaction (RT-PCR) test for the CSFV gene and the (ii) results of the enzyme-linked immunosorbent assay (ELISA) test for the antibody against CSFV in sampled wild boar. In the 280 wild boar sampled from September 2018 to March 2019 in the major CSF-affected area in Japan, the lethality rate and recovery rate of CSF per week were estimated as 0.165 (95% confidence interval: 0.081–0.250) and 0.004 (0–0.009), respectively. While the estimate of lethality rate of CSF was similar with the estimates in previous studies, the recovery rate was lower than those reported previously. CFR was estimated as 0.959 (0.904–0.981) using our estimate of recovery rate. This study is the first to estimate lethality rate of CSF from the dynamics of CSF epidemics in the wild boar population. Since the value of CFR is sensitive to the value of recovery rate, the accuracy in the estimate of recovery rate is a key for the accurate estimation of CFR. A long-term transmission experiment of moderately virulent strains may lead to more accurate estimation of the recovery rate and CFR of CSF.

frontiers in veterinary science

Estimation of the Lethality Rate, Recovery Rate, and Case Fatality Ratio of Classical Swine Fever in Japanese Wild Boar: An Analysis of the Epidemics From September 2018 to March 2019