RESUMO
Since African Swine Fever (ASF) was detected in the Dominican Republic in July 2021, it has negatively impacted the country's swine industry. Assessing the epidemiological situation is crucial to helping local authorities and industry stakeholders control the disease. Here, data on 155 reported outbreaks in the Dominican Republic from November 2022 to June 2023 were evaluated. Descriptive spatiotemporal analysis was performed to characterize disease distribution and spread, and between-herd R0 was calculated for the study period. The Knox test and a space-time permutation model were used to evaluate clustering. Data on clinical presentation, biosecurity measures, and suspected reasons for introduction were categorized and summarized. The majority (78%) of outbreaks occurred on backyard farms which generally had low biosecurity. Across farm types, the majority of pigs were still alive at the time of depopulation. Spatiotemporal findings and R0 estimates suggest an endemic pattern of disease geographically located centrally within the country. Clustering was detected even at small temporal and spatial distances due to outbreaks amongst neighboring backyard farms. These results provide critical information on the current state of the ASF epidemic in the Dominican Republic and will aid government officials and swine industry leaders in developing effective ASF control strategies.
RESUMO
Economically relevant pathogens, such as African swine fever virus (ASFV), have been shown to survive when experimentally inoculated in some feed ingredients under the environmental conditions in transoceanic transport models. However, these models did not characterize the likelihood of virus survival under various time and temperature processes that feed ingredients undergo before they are added to swine diets. Here, we developed a quantitative risk assessment model to estimate the probability that one or more corn or soybean meal ocean vessels (25,000 tonnes) contaminated with ASFV would be imported into the United States annually. This final probability estimate was conditionally based on five likelihoods: the probability of initial ASFV contamination (p0), ASFV inactivation during processing (p1) and transport (p2), recontamination (pR), and ASFV inactivation while awaiting customs clearance at United States entry (p3). The probability of ASFV inactivation was modelled using corn and soybean (extruded or solvent extracted) processing conditions (times and temperatures), D-values (time to reduce 90% or 1-log) estimated from studies of ASFV thermal inactivation in pork serum (p1), and survival in feed ingredients during transoceanic transport (p2 and p3). 'What-if' scenarios using deterministic values for p0 and pR (1%, 10%, 25%, 50%, 75%, and 100%) were used to explore their impact on risk. The model estimated complete inactivation of ASFV after extrusion or solvent extraction processes regardless of the initial ASFV contamination probability assumed. The value of recontamination (ranging from 1% to 75%) was highly influential on the risk of one ASFV-contaminated soybean meal vessel entering the United States. Median risk estimates ranged from 0.064% [0.006%-0.60%; 95% probability interval (PI)], assuming a pR of 1.0%, up to 4.67% (0.45%-36.50% 95% PI) assuming a pR of 75.0%. This means that at least one vessel with ASFV-contaminated soybean meal would be imported once every 1563-21 years, respectively. When all raw corn was assumed to be contaminated (p0 = 100%), and no recontamination was assumed to occur (pR = 0%), the median probability of one vessel with ASFV-contaminated corn entering the United States was 2.02% (0.28%-9.43% 95% PI) or once every 50 years. Values of recontamination between 1% and 75% did not substantially change the risk of corn. Days of transport, virus survival during transport (D-value), and number of vessels shipped were the parameters most influential for increased likelihood of a vessel with ASFV-contaminated soybean meal or corn entering the United States. The model helped to identify knowledge gaps that are most influential on output values and serves as a framework that could be updated and parameterized as new scientific information becomes available. We propose that the quantitative risk assessment model developed in this study can be used as a framework for estimating the risk of ASFV entry into the United States and other ASFV-free countries through other types of imported feed ingredients that may potentially become contaminated. Ultimately, this model can be used to develop risk mitigation strategies and critical control points for inactivating ASFV during feed ingredient processing, storage, and transport, and contribute to the design and implementation of biosecurity measures to prevent the introduction of ASFV into the United States and other ASFV-free countries.
