Evaluation of surveillance strategies for bovine tuberculosis (Mycobacterium bovis) using an individual based epidemiological model
Introduction
Due to effective eradication programs that started at the beginning of the 20th century, the Netherlands is practically bovine tuberculosis-free (BTB-free) since the mid 1950s. The European Union granted the Netherlands the official BTB-free status in 1992 (Emmerzaal et al., 1999). An advantage of this status is that the expensive yearly tuberculination of bovine herds is no longer obligatory. Visual inspection of the carcasses at the slaughterhouse and an efficient back tracing system remain obligatory, next to tuberculination of imported animals. The BTB-free status is discontinued if more than 0.1% of the bovine herds is infected in a calendar year, i.e. about 60 herds in the Netherlands in 2002 (Emmerzaal et al., 1999, Veling et al., 1993).
In the 1990s, nine outbreaks have occurred in Dutch bovine herds. The primary infected herds had a high prevalence (tuberculination test prevalence up to 80%) at the moment of detection, and the last outbreak in 1999 resulted in 10 infected herds. Thus, several infected animals must have passed the visual inspections without being detected (Emmerzaal et al., 1999). This raised the question whether the current surveillance method of visual inspection of carcasses is efficient enough to detect an outbreak before the number of infected herds increases above a certain level, being the danger zone of loosing the official BTB-free status.
In this study, we describe the epidemiological evaluation of six surveillance strategies. These are the current visual inspection of carcasses at the slaughterhouse (SL), the ELISA (enzyme-linked immunosorbent assay) test on blood samples of carcasses at the slaughterhouse (ELISA-B), the γ-interferon test on blood samples of carcasses at the slaughterhouse (GAMMA-B), comparative tuberculination of all animals of the herd (CT), single tuberculination of all animals with a confirmation test of positives with comparative tuberculination (ST + CT) and the ELISA test on samples of bulk milk (ELISA-M).
Because of the low specificity of single tuberculination, it is only used in combination with comparative tuberculination in many EU-countries. Positive single tuberculinated animals are re-tested with comparative tuberculination and found positive if both tests are positive. Comparative tuberculination (CT) without prior testing by single tuberculination is used in Ireland. The ELISA tests on samples of blood or bulk milk is a test currently in development. The objective of the bulk milk test is to develop a method, where samples of the milk of a herd can be used to determine whether one or more animals are infected, without testing individual animals in the herd.
In this paper, we evaluate which of the above-mentioned surveillance strategy is adequate to maintain the official BTB-free status. This is done by simulation of the BTB and cattle dynamics, as it currently exists in the Netherlands. We compare the surveillance strategy by the time until detection of the infection and by number of infected herds at the moment of detection for each surveillance strategy.
The most effective method in terms of short detection time and low number of infected farms does not have to be the cheapest method. In another paper, we describe the economical analysis of the results of this study (Van Asseldonk et al., in press).
Section snippets
Model description
We evaluated the six surveillance strategies by simulating BTB-outbreaks in a population of cattle herds. Unfortunately, available models of BTB spread are developed for countries with high incidence of the disease (e.g. the infection is endemic in Ireland, England and New Zealand) (Barlow, 1994, Barlow et al., 1997, Griffin and Williams, 1999). In these countries wildlife reservoirs for BTB (e.g. badgers in Ireland and England and possums in New Zealand) are subject of debate. In the
Results
After introduction of the infection in the first herd two possible scenarios exist. The first possibility is that the infection spreads within the herd and establishes itself. In this case, the infection can spread to other herds. The other possibility is that the infection does not establish itself in the herd (minor outbreak). Examples of these two scenarios are given in Fig. 1. In our simulations 6.8% (34) of the introductions ended in a minor outbreak. In a number of cases some of the
Discussion
The results of the simulated outbreaks for visual inspection of carcasses in the slaughterhouse were validated with detailed data of the 1999-outbreak in the Netherlands by comparison of time until detection, prevalence and number of infected farms.
For the 1999-outbreak, the time until detection was estimated between 220 and 430 weeks (Paaijmans, 2002, Van Roermund et al., 2003). The median of the simulations (302 weeks) is well within this range. According to the model, variation is large and
Acknowledgements
We thank Aline de Koeijer for contributions during the development of the model. Maarten de Gee is thankfully noticed for his useful comments on the model and thereby reducing stochasticity of the model. We thank Egbert van Nes for answering questions on the Monte Carlo elasticity analysis. Furthermore, we are grateful to Marleen Paaijmans, Annet Velthuis, Douwe Bakker and Fred van Zijderveld for their advise during parameter estimation.
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2018, EpidemicsCitation Excerpt :In fact, data obtained under experimental conditions (Neill et al., 1988, 1989; Costello et al., 1998; Dean et al., 2005) may not be representative of the infection dynamics under natural field conditions. Some authors have based their parameter estimations on data obtained from field studies, but with a low number of observations (Fischer et al., 2005; Pérez et al., 2002; Barlow et al., 1997), which may not reflect the whole complexity and variability of bTB spread among different farms. On the other hand, when local (Bekara et al., 2014; Álvarez et al., 2012a) or national-based data sets are used (O’Hare et al., 2014; Conlan et al., 2012; Kao et al., 1997), they are unlikely to contain the level of detail needed for the accurate estimation of transmission parameters.