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. 2021 Sep;22(5):e71.
doi: 10.4142/jvs.2021.22.e71.

Basic reproduction number of African swine fever in wild boars (Sus scrofa) and its spatiotemporal heterogeneity in South Korea

Affiliations

Basic reproduction number of African swine fever in wild boars (Sus scrofa) and its spatiotemporal heterogeneity in South Korea

Jun-Sik Lim et al. J Vet Sci. 2021 Sep.

Abstract

Background: African swine fever (ASF) is a hemorrhagic fever occurring in wild boars (Sus scrofa) and domestic pigs. The epidemic situation of ASF in South Korean wild boars has increased the risk of ASF in domestic pig farms. Although basic reproduction number (R0) can be applied for control policies, it is challenging to estimate the R0 for ASF in wild boars due to surveillance bias, lack of wild boar population data, and the effect of ASF-positive wild boar carcass on disease dynamics.

Objectives: This study was undertaken to estimate the R0 of ASF in wild boars in South Korea, and subsequently analyze the spatiotemporal heterogeneity.

Methods: We detected the local transmission clusters using the spatiotemporal clustering algorithm, which was modified to incorporate the effect of ASF-positive wild boar carcass. With the assumption of exponential growth, R0 was estimated for each cluster. The temporal change of the estimates and its association with the habitat suitability of wild boar were analyzed.

Results: Totally, 22 local transmission clusters were detected, showing seasonal patterns occurring in winter and spring. Mean value of R0 of each cluster was 1.54. The estimates showed a temporal increasing trend and positive association with habitat suitability of wild boar.

Conclusions: The disease dynamics among wild boars seems to have worsened over time. Thus, in areas with a high elevation and suitable for wild boars, practical methods need to be contrived to ratify the control policies for wild boars.

Keywords: African swine fever; South Korea; basic reproduction number; space-time clustering; wild boar.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Fig. 1
Fig. 1. Diagram illustrating the course of infection of ASF, and the parameters in the spatiotemporal clustering algorithm: E for the time of exposure to ASFV; I for the time to be infectious after the latent period from E; R for the time of death after infectious period from I; Duration of viable virus for the time period for transmission viability of ASFV from the R; D for the time of detection after detection delay from R; Buffer for death and Buffer for detection for the time periods for cases that were infected at the initial stage of the infectious period, and infected just before detection of the ASF-positive carcass, respectively.
ASF, African swine fever; ASFV, African swine fever virus.
Fig. 2
Fig. 2. Spatiotemporal distributions for the identified local transmission clusters in each corresponding period: October 2019 to July 2020 (Top); September 2020 to December 2020 (Middle); December 2020 to April 2021 (Bottom): Non included represents the cases which were not included in the identified clusters in each corresponding period.
Fig. 3
Fig. 3. Plots showing the seasonality of the identified local transmission clusters. Colors are assigned with their corresponding period. Grey area is for the unobserved period after May 2021.
Fig. 4
Fig. 4. Plot showing the estimated basic reproduction number (labeled as dot) and its 95% confidence interval for each cluster. The colors are assigned with their corresponding period.
Fig. 5
Fig. 5. Plots showing the association between habitat suitability of wild boar and basic reproduction number. (A) Ridge plots showing the distribution with habitat suitability of wild boar for each cluster. Cluster ID was ordered with its estimated basic reproduction number; (B) Scatter plot and regression line showing the association between the median habitat suitability of wild boars of each cluster and its basic reproduction number.

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