Greer Amy L, Spence Kelsey, Gardner Emma
Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, N1G 2W1, Canada.
BMC Vet Res. 2017 Jan 5;13(1):8. doi: 10.1186/s12917-016-0922-2.
The United States swine industry was first confronted with porcine epidemic diarrhea virus (PEDV) in 2013. In young pigs, the virus is highly pathogenic and the associated morbidity and mortality has a significant negative impact on the swine industry. We have applied the IDEA model to better understand the 2014 PEDV outbreak in Ontario, Canada. Using our simple, 2-parameter IDEA model, we have evaluated the early epidemic dynamics of PEDV on Ontario swine farms.
We estimated the best-fit R and control parameter (d) for the between farm transmission component of the outbreak by fitting the model to publically available cumulative incidence data. We used maximum likelihood to compare model fit estimates for different combinations of the R and d parameters. Using our initial findings from the iterative fitting procedure, we projected the time course of the epidemic using only a subset of the early epidemic data. The IDEA model projections showed excellent agreement with the observed data based on a 7-day generation time estimate. The best-fit estimate for R was 1.87 (95% CI: 1.52 - 2.34) and for the control parameter (d) was 0.059 (95% CI: 0.022 - 0.117). Using data from the first three generations of the outbreak, our iterative fitting procedure suggests that R and d had stabilized sufficiently to project the time course of the outbreak with reasonable accuracy.
The emergence and spread of PEDV represents an important agricultural emergency. The virus presents a significant ongoing threat to the Canadian swine industry. Developing an understanding of the important epidemiological characteristics and disease transmission dynamics of a novel pathogen such as PEDV is critical for helping to guide the implementation of effective, efficient, and economically feasible disease control and prevention strategies that are able to help decrease the impact of an outbreak.
美国养猪业于2013年首次遭遇猪流行性腹泻病毒（PEDV）。在仔猪中，该病毒具有高致病性，其相关的发病率和死亡率对养猪业产生了重大负面影响。我们应用IDEA模型来更好地理解2014年加拿大安大略省的PEDV疫情爆发情况。通过我们简单的双参数IDEA模型，我们评估了PEDV在安大略省养猪场的早期流行动态。
通过将模型拟合公开可用的累计发病率数据，我们估计了疫情爆发中农场间传播部分的最佳拟合R值和控制参数（d）。我们使用最大似然法比较不同R值和d参数组合的模型拟合估计。利用迭代拟合过程的初步结果，我们仅使用早期疫情数据的一个子集来预测疫情的时间进程。基于7天代时估计，IDEA模型预测与观察数据显示出极好的一致性。R的最佳拟合估计值为1.87（95%置信区间：1.52 - 2.34），控制参数（d）的最佳拟合估计值为0.059（95%置信区间：0.022 - 0.117）。利用疫情爆发前三代的数据，我们的迭代拟合过程表明，R和d已充分稳定，能够以合理的准确性预测疫情的时间进程。
PEDV的出现和传播是一个重要的农业突发事件。该病毒对加拿大养猪业构成了重大的持续威胁。了解像PEDV这样的新型病原体的重要流行病学特征和疾病传播动态对于指导实施有效、高效且经济可行的疾病控制和预防策略至关重要，这些策略有助于减少疫情爆发的影响。
