Dataset Information

New assessment of bovine tuberculosis risk factors in Belgium based on nationwide molecular epidemiology.

ABSTRACT: This assessment aimed to elaborate a statistical nationwide model for analyzing the space-time dynamics of bovine tuberculosis in search of potential risk factors that could be used to better target surveillance measures. A database comprising Mycobacterium bovis molecular profiles from all isolates obtained from Belgian outbreaks during the 1995-to-2006 period (n = 415) allowed the identification of a predominant spoligotype (SB0162). Various databases compiling 49 parameters to be tested were queried using a multiple stepwise logistic regression to assess bovine tuberculosis risk factors. Two isolate datasets were analyzed: the first included all Mycobacterium bovis isolates, while the second included only data related to the SB0162 type strain. When all Mycobacterium bovis isolates were included in the model, several risk factors were identified: history of bovine tuberculosis in the herd (P < 0.001), proximity of an outbreak (P < 0.001), cattle density (P < 0.001), and annual amplitude of mean middle-infrared temperature (P < 0.001). The approach restricted to the predominant SB0162 type strain additionally highlighted the proportion of movements from an infected area during the current year as a main risk factor (P = 0.009). This study identified several risk factors for bovine tuberculosis in cattle, highlighted the usefulness of molecular typing in the study of bovine tuberculosis epidemiology, and suggests a difference of behavior for the predominant type strain. It also emphasizes the role of animals' movements in the transmission of the disease and supports the importance of controlling trade movements.

SUBMITTER: Humblet MF

PROVIDER: S-EPMC2916604 | biostudies-literature | 2010 Aug

REPOSITORIES: biostudies-literature

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New assessment of bovine tuberculosis risk factors in Belgium based on nationwide molecular epidemiology.

Humblet M-F MF Gilbert M M Govaerts M M Fauville-Dufaux M M Walravens K K Saegerman C C

Journal of clinical microbiology 20100623 8

This assessment aimed to elaborate a statistical nationwide model for analyzing the space-time dynamics of bovine tuberculosis in search of potential risk factors that could be used to better target surveillance measures. A database comprising Mycobacterium bovis molecular profiles from all isolates obtained from Belgian outbreaks during the 1995-to-2006 period (n = 415) allowed the identification of a predominant spoligotype (SB0162). Various databases compiling 49 parameters to be tested were ...[more]

PMID: 20573869

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Project description:Bovine tuberculosis (bTB) infection is generally correlated with individual cattle's age, sex, body condition, and with husbandry practices such as herd composition, cattle movement, herd size, production system and proximity to wildlife-including bTB maintenance hosts. We tested the correlation between those factors and the prevalence of bTB, which is endemic in Ethiopia's highland cattle, in the Afar Region and Awash National Park between November 2013 and April 2015. A total of 2550 cattle from 102 herds were tested for bTB presence using the comparative intradermal tuberculin test (CITT). Data on herd structure, herd movement, management and production system, livestock transfer, and contact with wildlife were collected using semi-structured interviews with cattle herders and herd owners. The individual overall prevalence of cattle bTB was 5.5%, with a herd prevalence of 46%. Generalized Linear Mixed Models with a random herd-effect were used to analyse risk factors of cattle reactors within each herd. The older the age of the cattle and the lower the body condition the higher the chance of a positive bTB test result, but sex, lactation status and reproductive status were not correlated with bTB status. At herd level, General Linear Models showed that pastoral production systems with transhumant herds had a higher bTB prevalence than sedentary herds. A model averaging analysis identified herd size, contact with wildlife, and the interaction of herd size and contact with wildlife as significant risk factors for bTB prevalence in cattle. A subsequent Structural Equation Model showed that the probability of contact with wildlife was influenced by herd size, through herd movement. Larger herds moved more and grazed in larger areas, hence the probability of grazing in an area with wildlife and contact with either infected cattle or infected wildlife hosts increased, enhancing the chances for bTB infection. Therefore, future bTB control strategies in cattle in pastoral areas should consider herd size and movement as important risk factors.

Project description:A cross-sectional survey was conducted in selected districts of Bangladesh to estimate the prevalence of bovine tuberculosis (bTB), and to identify the risk factors for bTB. We included 1865 farmed cattle from 79 herds randomly selected from five districts. Herd and animal level data were collected using semi-structured interviews with cattle herd owners. The single intradermal comparative tuberculin test (SICTT) was used to estimate the prevalence of bTB. The risk factors were identified using mixed-effect multiple logistic regression analyses. The overall herd and animal level prevalences of bTB were estimated to be 45.6% (95% Confidence Interval [CI] = 34.3-57.2%) and 11.3 (95% CI = 9.9-12.8%), respectively, using the OIE recommended >4 mm cut-off. The true animal level prevalence of bTB was estimated to be 11.8 (95% Credible Interval = 2.1-20.3%). At the herd level, farm size, bTB history of the farm and type of husbandry were significantly associated with bTB status in univariable analysis. Similarly, age group, sex, pregnancy status and parity were significantly associated with bTB at cattle level. However, in multivariable analysis only herd size at the herd level and age group and pregnancy status at the cattle level were significant. Compared to a herd size of 1-10, the odds of bTB were 22.8 (95% CI: 5.2-100.9) and 45.6 times (95% CI: 5.0-417.7) greater in herd sizes of >20-50 and >50, respectively. The odds of bTB were 2.2 (95% CI: 1.0-4.5) and 2.5 times (95% CI: 1.1-5.4) higher in cattle aged >3-6 years and > 6 years, compared to cattle aged ≤1 year. Pregnancy increased the odds of bTB by 1.7 times (95% CI: 1.2-2.4) compared to non-pregnant cattle. Taken together, the results suggest high herd and animal level prevalence of bTB in these 5 districts, with the greatest risk of bTB in older and pregnant cattle within large herds (>20), and highlight an urgent need for continued surveillance and implementation of bTB control programs in Bangladesh.

Project description:BackgroundBovine tuberculosis (bTB) is a zoonotic disease of cattle caused by Mycobacterium bovis, widespread in England and Wales. It has high incidence towards the South West of England and Wales, with much lower incidence to the East and North. A stochastic simulation model was developed to simulate M. bovis transmission among cattle, transfer by cattle movements and transmission from environmental reservoirs (often wildlife and especially badgers). It distinguishes five surveillance streams, including herd tests, pre-movement testing and slaughter surveillance. The model thereby simulates interventions in bTB surveillance and control, and generates outputs directly comparable to detailed disease records. An anonymized version of the executable model with its input data has been released. The model was fitted to cattle bTB records for 2008-2010 in a cross-sectional comparison, and its projection was compared with records from 2010 to 2016 for validation.ResultsThe fitted model explained over 99% of the variation among numbers of breakdowns in four defined regions and surveillance streams in 2010. It classified 7800 (95% confidence interval c. 5500 - 14,000) holdings within high incidence regions as exposed to infectious environmental reservoirs, out of over 31,000 cattle holdings identified as potentially exposed to such sources. The model was consistent with previous estimates of low M. bovis transmission rate among cattle, but cattle to cattle transmission was clearly required to generate the number of cattle cases observed. When projected to 2016, the model as fitted to 2010 continued to match the distribution of bTB among counties, although it was notable that the actual distribution of bTB in 2010 was itself a close match for its distribution in 2016.ConclusionsThe close model fit demonstrated that cattle movements could generate breakdowns as observed in low incidence regions, if persistent environmental reservoirs such as wildlife maintained infection levels in the high incidence regions. The model suggests that environmental reservoirs may be a challenge for control, because, although many holdings are exposed to infection from wildlife or the environment, they are a minority of holdings. Large impacts on disease in wildlife will be required to avoid each individual transmission event to cattle.

Project description:BackgroundBovine brucellosis is a zoonotic disease that causes substantial economic losses and has a strong impact on public health. The main objective of this paper is to determine the risk factors for new infections of Brucella abortus on Colombian cattle farms previously certified as being free of brucellosis. A case-control study was conducted by comparing 98 cases (farms certified as brucellosis-free for three or more years but became infected) with 93 controls (farms that remained brucellosis-free during at least the previous three years). The farms were matched by herd size and geographical location (municipality). Information was obtained via a questionnaire completed by veterinary officers through a personal interview with the herd owners.ResultsTwo-thirds of the herds (67%) were dairy herds, 16% were beef herds, and 17% were dual-purpose (beef and milk) herds. After exploratory univariate analysis, all explanatory variables with a p-value of ≤0.20 were included in a logistic regression model using the forward stepwise method to select the model with the best goodness of fit. The significant risk factors were the replacement of animals from farms not certified as brucellosis-free compared to replacement from certified brucellosis-free farms (OR = 4.84, p-value < 0.001) and beef cattle farms compared to dairy cattle farms (OR = 3.61, p-value = 0.017). When herds with and without artificial insemination were compared, it was observed that farms that used natural breeding with bulls from non-certified herds had a higher risk than farms using artificial insemination (OR = 2.45, p-value = 0.037), but when the bulls came from brucellosis-free farms, farms with natural breeding were less affected (OR = 0.30, p-value = 0.004) than farms using artificial insemination, whether with frozen semen from certified brucellosis-free herds or fresh semen from uncontrolled herds. The latter is commonly sold to neighbouring farms.ConclusionsThe government should make efforts to inform farmers about the risks involved in the introduction of semen and replacement heifers from farms that are not certified as brucellosis-free and to establish measures to control these practices.

Project description:BackgroundImperfect diagnostic testing reduces the power to detect significant predictors in classical cross-sectional studies. Assuming that the misclassification in diagnosis is random this can be dealt with by increasing the sample size of a study. However, the effects of imperfect tests in longitudinal data analyses are not as straightforward to anticipate, especially if the outcome of the test influences behaviour. The aim of this paper is to investigate the impact of imperfect test sensitivity on the determination of predictor variables in a longitudinal study.Methodology/principal findingsTo deal with imperfect test sensitivity affecting the response variable, we transformed the observed response variable into a set of possible temporal patterns of true disease status, whose prior probability was a function of the test sensitivity. We fitted a Bayesian discrete time survival model using an MCMC algorithm that treats the true response patterns as unknown parameters in the model. We applied our approach to epidemiological data of bovine tuberculosis outbreaks in England and investigated the effect of reduced test sensitivity in the determination of risk factors for the disease. We found that reduced test sensitivity led to changes to the collection of risk factors associated with the probability of an outbreak that were chosen in the 'best' model and to an increase in the uncertainty surrounding the parameter estimates for a model with a fixed set of risk factors that were associated with the response variable.Conclusions/significanceWe propose a novel algorithm to fit discrete survival models for longitudinal data where values of the response variable are uncertain. When analysing longitudinal data, uncertainty surrounding the response variable will affect the significance of the predictors and should therefore be accounted for either at the design stage by increasing the sample size or at the post analysis stage by conducting appropriate sensitivity analyses.

Dataset Information

New assessment of bovine tuberculosis risk factors in Belgium based on nationwide molecular epidemiology.

Publications

New assessment of bovine tuberculosis risk factors in Belgium based on nationwide molecular epidemiology.

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