Evaluation and optimization of surveillance systems for rare and emerging infectious diseases

Abstract

-Surveillance for rare and emerging infectious diseases poses a special challenge to veterinary services. Most emerging infectious diseases like bovine tuberculosis (bTB) are zoonoses, affecting both human and animal populations. Despite the low prevalence of such an emerging infectious disease at time of incursion, the surveillance system should be able to detect the presence of the disease as early as possible. Because passive surveillance is a relatively cost-effective and therefore commonly used process, it is the basic tool for infectious disease surveillance. Because of under-reporting in passive surveillance, cost-intensive active surveillance is often required to increase the sensitivity of the surveillance system. Using scenario tree modelling, the sensitivity of passive and active surveillance system components (SSC) can be quantified and an optimal, cost-effective surveillance system developed considering the contributions of each SSC. We illustrate this approach with the example of bTB surveillance in Switzerland where the surveillance system for bTB consists of meat inspection at the slaughterhouse (SLI), passive clinical surveillance on farm (CLIN) and human surveillance (HS). While the sensitivities for CLIN and HS were both negligible (<1%), SLI was assessed to be 55.6%. The scenario tree model showed that SLI is increasable up to 80.4% when the disease awareness of meat inspectors in Switzerland is enhanced. A hypothetical random survey (RS) was also compared with a targeted survey (TS) in high-risk strata of the cattle population, and the sensitivity of TS was 1.17-fold better than in RS but with 50% of the sample size.scenario tree modelling / surveillance system / emerging infectious disease / bovine tuberculosis / Switzerland

Brucellosis at the animal/ecosystem/human interface at the beginning of the 21st century

“…Analysis includes evaluation of several parameters such as the probability of exposure to an infectious agent as well as the cost and consequences of the specific measure application. Furthermore, animal movement controls may need to be considered (Hadorn and Stark, 2008). To illustrate this section, we present two examples for bovine brucellosis.…”

“…The key point for early detection is the sensitivity of the surveillance system, i.e., the ability to detect an outbreak as soon as possible (Hadorn and Stark, 2008). A review on the different brucellosis tests has recently been published .…”

Specification of data collection on animal diseases to increase the preparedness of the AHAW panel to answer future mandates – CFP/EFSA/AHAW/2010/01

“…Numerous statistical models exist, to evaluate control strategies (e.g. Hadorn & Stärk, 2008). Several examples can be found in the scientific literature that illustrates the usefulness of modelling in evaluating and adapting strategies for animal disease control.…”

Animal health and disease monitoring in the abattoir

“…In many cases testing of samples taken from abattoirs serves as the method to provide year on year proof of freedom from disease. For bTB, surveillance in countries that have the disease-free status depends predominantly on abattoir surveillance and to a lesser extent on reporting of clinical cases (Hadorn andStärk, 2008, Bessell et al, 2013). Bessell et al (2103) have modelled abattoir-only surveillance versus two levels of herd testing (yearly and 4-yearly) along with abattoir surveillance, at the same time including several levels of risk encountered by farms (e.g.…”