Fischer E A J, van Roermund H J W, Hemerik L, van Asseldonk M A P M, de Jong M C M
Quantitative Veterinary Epidemiology, Animal Sciences Group, Wageningen University and Research Centre, P.O. Box 65, 8200 AB Lelystad, The Netherlands.
Prev Vet Med. 2005 Mar 15;67(4):283-301. doi: 10.1016/j.prevetmed.2004.12.002.
The Netherlands holds the bovine tuberculosis-free (BTB-free) status according to European Union standards, but in recent years small outbreaks of the infection have occurred. After the last outbreak in 1999 with 10 infected herds the question raised if the current surveillance system, visual inspection of carcasses at the slaughterhouse, is efficient enough to detect infected cattle in time and to maintain the official BTB-free status. Through epidemiological modelling, the risk of a major outbreak is quantified, using one of six surveillance strategies. These are the currently used visual inspection of carcasses at the slaughterhouse (SL), the ELISA test on blood samples of carcasses at the slaughterhouse (ELISA-B), the gamma-interferon test on blood samples of carcasses at the slaughterhouse (GAMMA-B), comparative tuberculination of the herd (CT), the combined method of single and comparative tuberculination of the herd (ST+CT) and the ELISA test on samples of bulk milk (ELISA-M). Test frequency of the last three methods was varied as well. A stochastic individual based model (IBM) was developed to simulate a chain of infected herds, where each individual animal is followed in time. The model mimics the nation-wide situation after the introduction of one infected animal into one herd. BTB-transmission is simulated with an S-E(1)-E(2)-I state transition model. Output is time until detection of the infection, prevalence in the detected herd and the number of infected herds at the time of detection. For the assessment 500 simulations were used, representing 500 BTB-introductions. Model robustness to parameter values was analysed with Monte Carlo elasticity analysis, for which 1000 simulations were used. Results of median time until detection and median number of infected farms at detection for SL (302 weeks and seven farms) were in agreement with estimates from an outbreak in the Netherlands in 1999. ELISA-B and GAMMA-B performed better than SL with a much lower median time until detection (189 and 97 weeks, respectively). The results for the tuberculination methods (ST+CT and CT) and ELISA-M depended heavily on the frequency in which the tests were performed. The tuberculination methods ST+CT and CT yield comparable results and detect the infection sooner than SL, also at the lowest tested frequency of once in 5 years. ELISA-M is comparable with SL at frequencies of once in 4 or 5 years, and this test works well at frequencies of once a year or higher. Our study results are used for an economical optimisation analysis of the six surveillance strategies.
根据欧盟标准，荷兰保持无牛结核病（BTB-free）状态，但近年来出现了小规模感染疫情。在1999年最后一次疫情爆发，有10个牛群感染后，人们提出了当前的监测系统，即在屠宰场对胴体进行目视检查，是否足以及时检测出感染牛并维持官方无牛结核病状态的问题。通过流行病学建模，使用六种监测策略之一对重大疫情爆发的风险进行了量化。这六种策略分别是目前在屠宰场对胴体进行的目视检查（SL）、对屠宰场胴体血样进行的ELISA检测（ELISA-B）、对屠宰场胴体血样进行的γ-干扰素检测（GAMMA-B）、牛群的比较结核菌素试验（CT）、牛群单次和比较结核菌素试验的联合方法（ST+CT）以及对原料乳样本进行的ELISA检测（ELISA-M）。后三种方法的检测频率也有所不同。开发了一个基于个体的随机模型（IBM）来模拟一系列感染牛群，其中对每只动物进行随时间跟踪。该模型模拟了将一只感染动物引入一个牛群后全国范围内的情况。使用S-E(1)-E(2)-I状态转换模型模拟牛结核病传播。输出结果包括感染检测所需时间、检测到的牛群中的患病率以及检测时感染牛群的数量。为了进行评估，使用了500次模拟，代表500次牛结核病引入情况。通过蒙特卡洛弹性分析对模型对参数值的稳健性进行了分析，为此使用了1000次模拟。SL检测所需的中位时间（302周）和检测时感染农场的中位数量（7个农场）的结果与荷兰1999年一次疫情爆发的估计结果一致。ELISA-B和GAMMA-B的表现优于SL，检测所需的中位时间要低得多（分别为189周和97周）。结核菌素试验方法（ST+CT和CT）以及ELISA-M的结果在很大程度上取决于检测的频率。结核菌素试验方法ST+CT和CT产生的结果相当，并且比SL更早检测到感染，即使在最低检测频率（每5年一次）下也是如此。ELISA-M在每4年或5年一次的频率下与SL相当，并且在每年一次或更高频率下效果良好。我们的研究结果用于对这六种监测策略进行经济优化分析。
