Network modeling of BVD transmission

Tinsley, Mark R.; Lewis, Fraser; Brülisauer, Franz

doi:10.1186/1297-9716-43-11

Cited by 35 publications

(37 citation statements)

References 29 publications

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“…Given the importance of BVDV, many statistical and epidemiological models have been developed to identify risk factors for BVDV transmission and opportunities for controlling disease more cost-effectively through targeted interventions [2,13,[30][31][32]. While most published studies agree that maintaining an open breeding herd is the primary risk factor for disease introductions [31][32][33][34][35], there are likely specific cohorts of purchased cattle that are at increased risk of generating outbreaks in the destination herd.…”

Section: Bvdv Epidemiologymentioning

confidence: 99%

“…An animal was classified as a purchased replacement breeding heifer (1) if the sex was registered as female, (2) if there were no recorded calvings prior to the movement, (3) if the animal was born on a different location than the destination farm, and (4) if the next recorded calving after the movement took place on the destination farm or, if there were no recorded calvings after the movement, that the animal survived beyond 30 months of age. It was assumed that animals intended for human consumption rather than breeding would be slaughtered by 30 months of age to comply with bovine spongiform encephalopathy (BSE) regulations in the United Kingdom [43].…”

Section: Cattle Movement Datamentioning

confidence: 99%

“…Background Infectious diseases cause significant financial losses for the cattle industry through their detrimental effects on animal health and performance [1]. As such, researchers are continually developing more sophisticated epidemiological models to better understand how disease control resources can be applied more cost-effectively across the large population of cattle herds [2][3][4]. Cattle movements have received particular attention in recent years both because of their central role in the epidemiology of many economically important cattle diseases [5][6][7] and because the movements of individual cattle have been explicitly recorded in databases across the European Union since 1998 [8].…”

Section: Introductionmentioning

confidence: 99%

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Not all cows are epidemiologically equal: quantifying the risks of bovine viral diarrhoea virus (BVDV) transmission through cattle movements

Gates

Humphry

Gunn

et al. 2014

Vet Res

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Many economically important cattle diseases spread between herds through livestock movements. Traditionally, most transmission models have assumed that all purchased cattle carry the same risk of generating outbreaks in the destination herd. Using data on bovine viral diarrhoea virus (BVDV) in Scotland as a case example, this study provides empirical and theoretical evidence that the risk of disease transmission varies substantially based on the animal and herd demographic characteristics at the time of purchase. Multivariable logistic regression analysis revealed that purchasing pregnant heifers and open cows sold with a calf at foot were associated with an increased risk of beef herds being seropositive for BVDV. Based on the results from a dynamic within-herd simulation model, these findings may be partly explained by the age-related probability of animals being persistently infected with BVDV as well as the herd demographic structure at the time of animal introductions. There was also evidence that an epidemiologically important network statistic, “betweenness centrality” (a measure frequently associated with the potential for herds to acquire and transmit disease), was significantly higher for herds that supplied these particular types of replacement beef cattle. The trends for dairy herds were not as clear, although there was some evidence that open heifers and open lactating cows were associated with an increased risk of BVDV. Overall, these findings have important implications for developing simulation models that more accurately reflect the industry-level transmission dynamics of infectious cattle diseases.

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Section: Bvdv Epidemiologymentioning

confidence: 99%

Section: Cattle Movement Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Not all cows are epidemiologically equal: quantifying the risks of bovine viral diarrhoea virus (BVDV) transmission through cattle movements

Gates

Humphry

Gunn

et al. 2014

Vet Res

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“…In 2014, the herd-level incidence had dropped to 0.12 %. As it is well established that BVD is introduced primarily through the movement of persistently infected animals (PI) or cows carrying a PI, farms which receive many animals from many farms are at higher risk to get infected and surveillance should target on such farms [24,[28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of farm-level parameters derived from animal movements for use in risk-based surveillance programmes of cattle in Switzerland

et al. 2015

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BackgroundThis study focused on the descriptive analysis of cattle movements and farm-level parameters derived from cattle movements, which are considered to be generically suitable for risk-based surveillance systems in Switzerland for diseases where animal movements constitute an important risk pathway.MethodsA framework was developed to select farms for surveillance based on a risk score summarizing 5 parameters. The proposed framework was validated using data from the bovine viral diarrhoea (BVD) surveillance programme in 2013.ResultsA cumulative score was calculated per farm, including the following parameters; the maximum monthly ingoing contact chain (in 2012), the average number of animals per incoming movement, use of mixed alpine pastures and the number of weeks in 2012 a farm had movements registered. The final score for the farm depended on the distribution of the parameters. Different cut offs; 50, 90, 95 and 99 %, were explored. The final scores ranged between 0 and 5. Validation of the scores against results from the BVD surveillance programme 2013 gave promising results for setting the cut off for each of the five selected farm level criteria at the 50th percentile. Restricting testing to farms with a score ≥ 2 would have resulted in the same number of detected BVD positive farms as testing all farms, i.e., the outcome of the 2013 surveillance programme could have been reached with a smaller survey.ConclusionsThe seasonality and time dependency of the activity of single farms in the networks requires a careful assessment of the actual time period included to determine farm level criteria. However, selecting farms in the sample for risk-based surveillance can be optimized with the proposed scoring system. The system was validated using data from the BVD eradication program. The proposed method is a promising framework for the selection of farms according to the risk of infection based on animal movements.

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“…In the following model, we consider the dwellings of the mammals that suffer the disease to be the "hosts," that is, hosts include human houses, peridomestic structures (e.g., corrals), and sylvatic dwellings (e.g., animal nests, caves, and rodent burrows). This approach is similar to that used to model transmission of bovine viral diarrhea among farm animals (Tinsley et al 2012).…”

mentioning

confidence: 99%

Household Model of Chagas Disease Vectors (Hemiptera: Reduviidae) Considering Domestic, Peridomestic, and Sylvatic Vector Populations

et al. 2013

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Disease transmission is difficult to model because most vectors and hosts have different generation times. Chagas disease is such a situation, where insect vectors have 1-2 generations annually and mammalian hosts, including humans, can live for decades. The hemataphagous triatominae vectors (Hemiptera: Reduviidae) of the causative parasite Trypanosoma cruzi (Kinetoplastida: Trypanosomatidae) usually feed on sleeping hosts, making vector infestation of houses, peridomestic areas, and wild animal burrows a central factor in transmission. Because of difficulties with different generation times, we developed a model considering the dwelling as the unit of infection, changing the dynamics from an indirect to a direct transmission model. In some regions, vectors only infest houses; in others, they infest corrals; and in some regions, they also infest wild animal burrows. We examined the effect of sylvatic and peridomestic vector populations on household infestation rates. Both sylvatic and peridomestic vectors increase house infestation rates, sylvatic much more than peridomestic, as measured by the reproductive number R0. The efficacy of manipulating parameters in the model to control vector populations was examined. When R0 > 1, the number of infested houses increases. The presence of sylvatic vectors increases R0 by at least an order of magnitude. When there are no sylvatic vectors, spraying rate is the most influential parameter. Spraying rate is relatively unimportant when there are sylvatic vectors; in this case, community size, especially the ratio of houses to sylvatic burrows, is most important. The application of this modeling approach to other parasites and enhancements of the model are discussed.

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Network modeling of BVD transmission

Cited by 35 publications

References 29 publications

Not all cows are epidemiologically equal: quantifying the risks of bovine viral diarrhoea virus (BVDV) transmission through cattle movements

Not all cows are epidemiologically equal: quantifying the risks of bovine viral diarrhoea virus (BVDV) transmission through cattle movements

Evaluation of farm-level parameters derived from animal movements for use in risk-based surveillance programmes of cattle in Switzerland

Household Model of Chagas Disease Vectors (Hemiptera: Reduviidae) Considering Domestic, Peridomestic, and Sylvatic Vector Populations

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