Assessment of the sensitivity of the bovine tuberculosis eradication program in a high prevalence region of Spain using scenario tree modeling

Maria Luisa de la Cruz, Pilar Pozo, Anna Grau, Jesus Nacar, Javier Bezos, Andres Perez, Lucas Dominguez, Jose Luis Saez, Olga Minguez, Lucia de Juan, Julio Alvarez

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5 Scopus citations

Abstract

In spite of the efforts invested to eradicate bovine tuberculosis (bTB) in cattle, the disease is still present in several developed countries, including Spain. Among the factors related with disease persistence in high prevalence areas, the lack of sensitivity of the screening test for detection of infected herds [single intradermal tuberculin (SIT) test] can play a major role. Here, a scenario tree model mimicking the diagnostic test scheme in place in the region of Castilla y Leon (Spain) was developed to estimate the probability of detecting bTB in an infected-non detected officially tuberculosis free (OTF) herd (herd sensitivity, HSe). In order to do so the probability of detecting at least one positive animal in the SIT test with/without post-mortem (detection of lesions and culture) confirmation in an infected herd was estimated using Monte Carlo simulation through @RISK (Palisade Co, NY, USA). Uncertainty on the accuracy of the diagnostic tests was introduced in the model using distributions based on the literature. The performance of the model was evaluated by comparing the predicted number of SIT/post-mortem positive animals in infected herds with those observed in newly detected bTB-infected herds in the region in 2011–2015. The estimated HSe of the SIT test was 76.2% (95% probability interval: 19.8–97.6). According to the model, bTB infection would be then confirmed through culture in 65.3% (95% PI: 50.0–82.3) of the herds detected through the SIT test, so that overall the proportion of infected-non detected OTF herds in which the infection could be confirmed after the initial SIT test was 49.6% (95% PI: 9.75–80.3). The predicted HSe of both SIT test and culture was directly correlated with herd size. Results from the model suggest a moderate but highly variable HSe of the current surveillance system in place for bTB detection in OTF herds located in high prevalence areas, that could be maximized by performing multiple tests within a year as indicated in the Spanish eradication program (with a median SIT HSe of 87% when two consecutive tests were considered). In addition, these results highlight the usefulness of performing subsequent SIT tests to rule out infection in SIT-positive herds even when the causative agent cannot be isolated.

Original languageEnglish (US)
Article number104800
JournalPreventive Veterinary Medicine
Volume173
DOIs
StatePublished - Dec 1 2019

Bibliographical note

Funding Information:
Pilar Pozo is the recipient of a pre-doctoral grant of the National Program for the Promotion of Talent and Its Employability of the Spanish Ministry of Economy, Industry and Competitiveness (MINECO) ( DI-15-08098 ). Javier Bezos is recipient of a Juan de la Cierva Incorporación Research contract ( IJCI-2015-24805 ) funded by the MINECO. JA is recipient of a Ramón y Cajal postdoctoral contract from the Spanish Ministry of Economy, Industry and Competitiveness (MINECO) ( RYC-2016-20422 ). This work was supported by the Programa de Tecnologías Avanzadas en Vigilancia Sanitaria (TAVS) from the Comunidad de Madrid (ref. S2013/ABI-2747 ) and is a contribution to the project RTI2018-096010-B-C22 (Ministerio de Ciencia, Innovación y Universidades).

Funding Information:
Pilar Pozo is the recipient of a pre-doctoral grant of the National Program for the Promotion of Talent and Its Employability of the Spanish Ministry of Economy, Industry and Competitiveness (MINECO) (DI-15-08098). Javier Bezos is recipient of a Juan de la Cierva Incorporaci?n Research contract (IJCI-2015-24805) funded by the MINECO. JA is recipient of a Ram?n y Cajal postdoctoral contract from the Spanish Ministry of Economy, Industry and Competitiveness (MINECO) (RYC-2016-20422). This work was supported by the Programa de Tecnolog?as Avanzadas en Vigilancia Sanitaria (TAVS) from the Comunidad de Madrid (ref. S2013/ABI-2747) and is a contribution to the project RTI2018-096010-B-C22 (Ministerio de Ciencia, Innovaci?n y Universidades).

Publisher Copyright:
© 2019 Elsevier B.V.

Keywords

  • Bovine tuberculosis
  • Cattle
  • Diagnosis
  • Herd sensitivity
  • Scenario tree modelling
  • Surveillance

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