Novel estimation of African swine fever transmission parameters within smallholder villages in Lao P.D.R.

African Swine Fever (ASF) disease transmission parameters are crucial for making response and control decisions when faced with an outbreak, yet they are poorly quantified for smallholder and village contexts within Southeast Asia. Whilst disease-specific factors - such as latent and infectious periods - should remain reasonably consistent, host, environmental and management factors are likely to affect the rate of disease spread. These differences are investigated using Approximate Bayesian Computation with Sequential Monte-Carlo methods to provide disease parameter estimates in four naïve pig populations in villages of Lao People's Democratic Republic. The villages represent smallholder pig farmers of the Northern province of Oudomxay and the Southern province of Savannakhet, and the model utilised field mortality data to validate the transmission parameter estimates over the course of multiple model generations. The basic reproductive number between-pigs was estimated to range from 3.08 to 7.80, whilst the latent and infectious periods were consistent with those published in the literature for similar genotypes in the region (4.72 to 6.19 days and 2.63 to 5.50 days, respectively). These findings demonstrate that smallholder village pigs interact similarly to commercial pigs, however the spread of disease may occur slightly slower than in commercial study groups. Furthermore, the findings demonstrated that despite diversity across the study groups, the disease behaved in a consistent manner. This data can be used in disease control programs or for future modelling of ASF in smallholder contexts.

Simulating the mechanics behind sub-optimal mobility and the associated economic losses in dairy production.

Hoof disorders and sub-optimal mobility (SOM) are economically important health issues in dairy farming. Although the dynamics of hoof disorders have an important effect on cow mobility, they have not been considered in previous simulation models that estimate the economic loss of SOM. Furthermore, these models do not consider the varying severities of SOM. The objective of this study was to develop a novel bio-economic simulation model to simulate the dynamics of 8 hoof disorders: digital dermatitis (DD), interdigital hyperplasia (HYP), interdigital dermatitis/heel-horn erosion (IDHE), interdigital phlegmon (IP), overgrown hoof (OH), sole haemorrhage (SH), sole ulcer (SU) and white-line disease (WLD), their role in SOM, and estimate the economic loss of SOM in a herd of 125 dairy cows. A Reed-Frost model was used for DD and a Greenwood model for the other 7 hoof disorders. Economic analysis was conducted per mobility score according to a 5-point mobility scoring method (1 = perfect mobility; 5 = severely impaired mobility) by comparing a scenario with SOM and one without SOM. Parameters used in the model were based on literature and expert opinion and deemed credible during model validation rounds. Results showed that the mean cumulative incidence for maximum mobility scores 2-5 SOM episodes were respectively 34, 16, 7 and <1 episodes per 100 cows per pasture period and 39, 19, 8, <1 episodes per 100 cows per housing period. The mean total annual economic loss due to SOM resulting from the hoof disorders under study was €15,342: €122 per cow per year. The economic analysis uncovered direct economic losses that could be directly linked to SOM episodes and indirect economic losses that could not be directly linked to SOM episodes but arose due to the presence of SOM. The mean total annual direct economic loss for maximum mobility score 2-5 SOM episodes was €1129, €3098, €4354 and €480, respectively. The mean total annual indirect economic loss varied considerably between the 5th and 95th percentiles: €-6174 and €19,499, and had a mean of €6281. This loss was composed of additional indirect culling due to SOM (∼65%) and changes in the overall herd milk production (∼35%) because of additional younger replacement heifers entering the herd due to increased culling rates. The bio-economic model presented novel results with respect to indirect economic losses arising due to SOM. The results can be used to stimulate farmer awareness and promote better SOM management.

A stochastic modelling approach to determine the effect of diverse Staphylococcus aureus strains on the economic and epidemiological outcomes of mastitis intervention strategies in dairy cattle.

Staphylococcus aureus (S. aureus) strains with considerable genetic and phenotypic differences have previously been identified. The economic and epidemiologic impact of S. aureus mastitis has been investigated, but none of these studies took differences between strains into account. Here we aimed to investigate how differences between S. aureus strains affect the economic and epidemiologic outcome of various intervention strategies against clinical and subclinical intramammary infections. Five S. aureus strains were modelled using a stochastic bio-economic model simulating a dairy herd of 200 cows using single-day time steps. The strain characteristics of the five simulated S. aureus strains (general, contagious, spill-over, clinical and persistent) were based on divergent phenotypes as described in literature. Outcomes of the model included incidence (both clinical and subclinical), number of antibiotic treatment days, number of culled cows, and net income. Intervention strategies against clinical and subclinical intramammary infections were based on (variations of) intramammary antibiotic treatment, testing, and culling. Both single and multiple pathogen (intramammary infection caused by S. aureus, Escherichia coli, and non-aureus staphylococci) scenarios were simulated to determine the effect of the five S. aureus strains on the impact of 19 different intervention strategies. The results showed that the incidence (both clinical and subclinical), number of treatment days, number of culled cows, and net income varied considerably for the different S. aureus strains. Comparison of the model outcomes within and between strains showed that for most intervention strategies the relative impact differed per strain. However, the intervention strategy with the best outcome for most variables and strains was the culling of cows with a recovery probability lower than 50%. This shows that the relative economic and epidemiologic impact of most of the modelled intervention strategies were strain-dependent, while some intervention strategies were not strain-dependent. From this, we conclude that, depending on the intervention strategy applied on a farm, it could be advantageous to type S. aureus to determine whether it would be economically and epidemiologically beneficial for the existing intervention strategy to be changed.

A simulation study to investigate the added value in using differential somatic cell count as an additional indicator for udder health management in dairy herds.

Mastitis is one of the most costly diseases in dairy herds worldwide. Somatic cell count (SCC) is widely used as an indicator for subclinical intramammary infections (IMI) that may eventually cause mastitis in dairy herds. Differential somatic cell count (DSCC) has recently been introduced as an additional indicator for IMI. The objective of this study was to investigate the value of using DSCC as an additional indicator to select cows for testing and subsequent intervention for subclinical mastitis during the lactation. We parameterized an existing bio-economic simulation model for dairy herds to include DSCC. Then, we simulated three Danish dairy cattle herd situations with different pathogen distributions where the main pathogens were 1) Staphylococcus aureus, 2) Streptococcus agalactiae, and 3) Streptococcus uberis. In these herds, we simulated two different selection strategies for testing (bacterial culture) for subclinical IMI and various intervention strategies for test positive cases. The first selection strategy considered only SCC; cows were selected for testing if they had a low SCC measurement followed by two high SCC measurements. In the second selection strategy, cows additionally had to have a high DSCC measurement. Results showed that both selection strategies led to a similar net income and to a similar number of clinical and subclinical cases for all investigated intervention strategies. However, when using DSCC in the selection of animals, the number of treatment days and the number of cows culled in relation to IMI was reduced: The median annual number of treatment days was reduced by 25-38 days in herd 1, by 25-42 days in herd 2, and by 30-48 days in herd 3, depending on the intervention strategy. The median annual number of cows culled in relation to IMI was reduced by up to 8 cows (10 cows in herd 3) for one of the intervention strategies. Subject to limitations associated with model assumptions, these results suggest that considering DSCC when selecting cows for testing can reduce IMI related culling and the use of antibiotics without changing in-herd prevalence nor resulting in economic loss.

Differential Somatic Cell Count: Value for Udder Health Management.

Intramammary infection (IMI) can cause mastitis, which is one of the costliest and most prevalent diseases in dairy cattle herds. Somatic cell count (SCC) is a well-established parameter to indicate IMI, and it represents the total count of immune cells in the milk. The differential somatic cell count (DSCC) has also long been suggested to indicate IMI, but no machine was available until recently to provide this parameter automatically. Two new machines have recently been introduced to measure the milk DSCC as an additional indicator of IMI. Here we provide insights about the DSCC measured by these two machines and the value it may provide for udder health management, based on the available literature. We also provide perspectives for future research to investigate potential value in using the DSCC to improve udder health.

Economic and epidemiological impact of different intervention strategies for subclinical and clinical mastitis.

The objective of this study was to evaluate and compare different combinations of intervention strategies for contagious or opportunistic subclinical and clinical intramammary infections (IMI). We simulated two different Danish dairy cattle herds with ten different intervention strategies focusing on cow-specific treatment or culling, including three baseline strategies without subclinical interventions. In one herd, the main causative pathogen of IMI was Staphylococcus (S.) aureus. In the other herd, Streptococcus (St.) agalactiae was the main causative agent. For both herds, we investigated costs and effectiveness of all ten intervention strategies. Intervention strategies consisted of measures against clinical and subclinical IMI, with baselines given by purely clinical intervention strategies. Our results showed that strategies including subclinical interventions were more cost-effective than the respective baseline strategies. Increase in income and reduction of IMI cases came at the cost of increased antibiotic usage and an increased culling rate in relation to IMI. However, there were differences between the herds. In the St. agalactiae herd, the clinical intervention strategy did not seem to have a big impact on income and number of cases. However, intervention strategies which included cow-specific clinical interventions led to a higher income and lower number of cases in the S. aureus herd. The results show that intervention strategies including interventions against contagious or opportunistic clinical and subclinical IMI can be highly cost-effective, but should be herd-specific.

Effects of control measures on the spread of LA-MRSA among Danish pig herds between 2006 and 2015 - a simulation study.

There has been a rapid increase in Danish pig herds testing positive for livestock-associated Methicillin-resistant Staphylococcus aureus (LA-MRSA) since the first screening in 2008. Despite a national action plan to control LA-MRSA in the Danish pig population, 88% of pig herds tested positive in a 2016 cross-sectional study of 57 herds. The national action plan was initiated in April 2015 and aimed to reduce the spread of LA-MRSA among pig herds. However, its success is uncertain. We used a simulation model mimicking the spread of LA-MRSA among pig herds between 2006 and 2015 to evaluate the impact of control strategies if these had these been implemented in 2007 or 2010. The strategies were combinations of the following control measures: (1) a reduced number of herds using high-risk antibiotics, (2) a reduced probability of indirect transmission among herds via humans, (3) movement restrictions, and (4) voluntary eradication in 5-7.5% of the herds. Almost all tested control strategies simulated a reduction in the spread of LA-MRSA. The combination of two, three or four intervention strategies showed additive effects and led to larger reductions in the predicted herd prevalence. In addition, the prevalence of LA-MRSA-positive herds at the time when control measures were initiated influenced the effects of the control strategies. Combining the simulated control measures can be considered in future action plans to control LA-MRSA.

Economic and epidemiological impact of different intervention strategies for clinical contagious mastitis.

The overall aim of this study was to compare different intervention strategies for clinical intramammary infections (IMI). We conducted a simulation study to represent a Danish dairy cattle herd with IMI caused mostly by Staphylococcus aureus and 9 different intervention strategies for clinical IMI. A standard intervention of 3 d of treatment consisting of intramammary injections for all clinical cases was used. Two of the strategies reflected the use of more antibiotics and 6 strategies reflected cow-specific treatment or culling decisions. For these strategies, we assessed the cost and effectiveness of culling as an IMI intervention. Our results showed that nearly all strategies could reduce the number of IMI cases [e.g., a median of 37 clinical cases with the extended intramammary treatment over 5 d strategy (Basic5) and 30 clinical cases with the cow culled with recovery probability below 50% (Before50)] compared with the standard intervention (median of 42 clinical cases). This happened alongside either increased antibiotic usage (e.g., from a median of 123 treatment days up to 179 treatment days with strategy Basic5) or an increased number of cows culled in relation to IMI (e.g., from a median of 16 up to 24 cows with strategy Before50). Strategies with more antibiotics or reactive culling had a slightly higher net income (e.g., €190,014 median net income with strategy Basic5 or €196,995 with strategy Before50 compared with €187,666 with the standard strategy). This shows that a cow-specific clinical intervention approach can be cost-effective in reducing IMI incidence.

Drivers for Livestock-Associated Methicillin-Resistant Staphylococcus Aureus Spread Among Danish Pig Herds - A Simulation Study.

To gain insight into the rapid increase in the number of livestock-associated Methicillin-resistant Staphylococcus aureus (LA-MRSA)-positive herds in Denmark, we developed an individual-based Monte Carlo simulation model. We aimed to assess whether transmission of LA-MRSA via pig movements could explain the observed increase in the number of positive herds in Denmark, and to evaluate the effect of other between-herd transmission mechanisms. Pig movements alone were not sufficient to mimic the observed increase in LA-MRSA-positive herds in Denmark in any of the modelled scenarios. The model identified three factors that played important roles in the between-herd spread of LA-MRSA: (1) the within-herd dynamics, (2) the frequency and effectiveness of indirect transmissions, and (3) unexplainable introduction of LA-MRSA to swine herds. These factors can act as starting points for the development of LA-MRSA control programs in pig herds in order to limit the risk of its transmission to humans.

Building the foundation for veterinary register-based epidemiology: A systematic approach to data quality assessment and validation.

Epidemiological studies often use data from registers. Data quality is of vital importance for the quality of the research. The aim of this study was to suggest a structured workflow to assess the quality of veterinary national registers. As an example of how to use the workflow, the quality of the following three registers was assessed: the Central Husbandry Register (CHR), the database for movement of pigs (DMP) and the national Danish register of drugs for veterinary use (VetStat). A systematic quantitative assessment was performed, with calculation the proportion of farms and observations with "poor quality" of data. "Poor" quality was defined for each measure (variable) either as a mismatch between and/or within registers, registrations of numbers outside the expected range, or unbalanced in- and outgoing movements. Interviews were conducted to make a complementary qualitative assessment. The proportion of farms and observations within each quality measure varied. This study highlights the importance of systematic quality assessment of register data and suggests a systematic approach for such assessments and validations without the use of primary data.

A strain-, cow-, and herd-specific bio-economic simulation model of intramammary infections in dairy cattle herds.

Intramammary infections (IMI) in dairy cattle lead to economic losses for farmers, both through reduced milk production and disease control measures. We present the first strain-, cow- and herd-specific bio-economic simulation model of intramammary infections in a dairy cattle herd. The model can be used to investigate the cost-effectiveness of different prevention and control strategies against IMI. The objective of this study was to describe a transmission framework, which simulates spread of IMI causing pathogens through different transmission modes. These include the traditional contagious and environmental spread and a new opportunistic transmission mode. In addition, the within-herd transmission dynamics of IMI causing pathogens were studied. Sensitivity analysis was conducted to investigate the influence of input parameters on model predictions. The results show that the model is able to represent various within-herd levels of IMI prevalence, depending on the simulated pathogens and their parameter settings. The parameters can be adjusted to include different combinations of IMI causing pathogens at different prevalence levels, representing herd-specific situations. The model is most sensitive to varying the transmission rate parameters and the strain-specific recovery rates from IMI. It can be used for investigating both short term operational and long term strategic decisions for the prevention and control of IMI in dairy cattle herds.

Assessment of the Interrater Reliability of the Congress of Neurological Surgeons Microanastomosis Assessment Scale.

BACKGROUND: The potential for simulation-based learning in neurosurgical training has led the Congress of Neurosurgical Surgeons to develop a series of simulation modules. The Northwestern Objective Microanastomosis Assessment Tool (NOMAT) was created as the corresponding assessment tool for the Congress of Neurosurgical Surgeons Microanastomosis Module. The face and construct validity of the NOMAT have been previously established. OBJECTIVE: To further validate the NOMAT by determining its interrater reliability (IRR) between raters of varying levels of microsurgical expertise. METHODS: The NOMAT was used to assess residents' performance in a microanastomosis simulation module in 2 settings: Northwestern University and the Society of Neurological Surgeons 2014 Boot Camp at the University of Indiana. At Northwestern University, participants were scored by 2 experienced microsurgeons. At the University of Indiana, participants were scored by 2 postdoctoral fellows and an experienced microsurgeon. The IRR of NOMAT was estimated by computing the intraclass correlation coefficient using SPSS v22.0 (IBM, Armonk, New York). RESULTS: A total of 75 residents were assessed. At Northwestern University, 21 residents each performed microanastomosis on 2 model vessels of different sizes, one 3 mm and one 1 mm. At the University of Indiana, 54 residents performed a single microanastomosis procedure on 3-mm vessels. The intraclass correlation coefficient of the total NOMAT scores was 0.88 at Northwestern University and 0.78 at the University of Indiana. CONCLUSION: This study indicates high IRR for the NOMAT. These results suggest that the use of raters with varying levels of expertise does not compromise the precision or validity of the scale. This allows for a wider adoption of the scale and, hence, a greater potential educational impact.

Epidemiological and economic consequences of purchasing livestock infected with Mycobacterium avium subsp. paratuberculosis.

BACKGROUND: Paratuberculosis (PTB) is a chronic disease which may lead to reduced milk yield, lower animal welfare and death in cattle. The causative agent is Mycobacterium avium subsp. paratuberculosis (MAP). The economic consequences are particularly important incentives in the control and eradication of the infection. One strategy to control PTB in a herd is to purchase animals from farms with a low risk of MAP infection. We wanted to investigate the epidemiological and economic consequences of buying livestock from different supplier farms of low, medium or high risk, as well as farms with unknown status. We also wanted to estimate the probability of spontaneous fadeout if the farmer of an initially MAP-free herd bought a specified number of infected animals in a single year, or continually bought infected animals. This was achieved through simulation modeling, and the effects of consistently introducing one, five or ten infected animals annually into an initially infection-free herd was also modeled. RESULTS: Our findings show that once infected, a farm can relatively safely purchase animals from other low and medium-risk farms without experiencing an increase in the prevalence, highlighting the importance of certification programmes. Furthermore, farms free of MAP are highly susceptible and cannot purchase more than a small number of animals per year without having a high risk of being infected. The probability of spontaneous fadeout after 10 years was 82% when introducing a single infected animal into an initially MAP-free herd. When purchasing ten infected animals, this probability was 46%. The continual purchase of infected animals resulted in very low probabilities of spontaneous fadeout. CONCLUSIONS: We demonstrated that MAP-free farms can purchase a small number of animals, preferably from certified farms, each year and still remain free of MAP. Already infected farms have little risk of increasing the prevalence on a farm when purchasing animals from other farms.

Opportunities and challenges when pooling milk samples using ELISA.

Testing large quantities of samples in order to detect one or more test-positive sample(s) is expensive and time-consuming. It is possible to optimize this process by pooling samples. Two frameworks to produce different hierarchical and non-hierarchical pooling schemes were tested and compared to standard pooling. Their efficiency and the potential savings were determined as a function of prevalence and the number of pooled samples. The potential benefit of pooling samples is dependent upon the changes in the analytical sensitivity and specificity of the test used when diluting test-positive samples by pooling. To illustrate this, the sensitivity of antibody ELISA on pooled samples of bovine milk for Salmonella Dublin, Mycobacterium avium spp. paratuberculosis, and bovine virus diarrhea was tested. For these milk assays, the analytical sensitivity decreased rapidly with increasing pool sizes. The efficiency of pooling is usually only measured by the number of tests performed, yet real savings depend on all the costs involved in the pooling process. These may differ between laboratories depending on the available equipment and the salaries of the technicians, among other factors. Therefore, several cost parameters were introduced to describe the total cost and thereby calculate the total savings. In terms of overall savings, both tested schemes were potentially optimal depending on the prevalence, possible pool size, and the cost of retesting. For the pool sizes of interest in this study, the three-stage hierarchical pooling scheme was often marginally more efficient in terms of the total number of tests. However, if the price of re-pooling was high, the two-stage scheme performed better in terms of total savings. In addition, for low prevalences and the possibility of pooling a large number of samples, the two-stage non-hierarchical test may be more efficient, both in terms of number of tests and overall cost. In order to apply these results in different laboratory settings, a free Shiny WebApp was developed, to compare several pooling schemes with different cost parameters.

Simulating the Epidemiological and Economic Impact of Paratuberculosis Control Actions in Dairy Cattle.

We describe a new mechanistic bioeconomic model for simulating the spread of Mycobacterium avium subsp. paratuberculosis (MAP) within a dairy cattle herd. The model includes age-dependent susceptibility for infection; age-dependent sensitivity for detection; environmental MAP build up in five separate areas of the farm; in utero infection; infection via colostrum and waste milk, and it allows for realistic culling (i.e., due to other diseases) by including a ranking system. We calibrated the model using a unique dataset from Denmark, including 102 random farms with no control actions against spread of MAP. Likewise, four control actions recommended in the Danish MAP control program were implemented in the model based on reported management strategies in Danish dairy herds in a MAP control scheme. We tested the model parameterization in a sensitivity analysis. We show that a test-and-cull strategy is on average the most cost-effective solution to decrease the prevalence and increase the total net revenue on a farm with low hygiene, but not more profitable than no control strategy on a farm with average hygiene. Although it is possible to eradicate MAP from the farm by implementing all four control actions from the Danish MAP control program, it was not economically attractive since the expenses for the control actions outweigh the benefits. Furthermore, the three most popular control actions against the spread of MAP on the farm were found to be costly and inefficient in lowering the prevalence when used independently.

Simulating the epidemiological and economic effects of an African swine fever epidemic in industrialized swine populations.

African swine fever (ASF) is a notifiable infectious disease with a considerable impact on animal health and is currently one of the most important emerging diseases of domestic pigs. ASF was introduced into Georgia in 2007 and subsequently spread to the Russian Federation and several Eastern European countries. Consequently, there is a non-negligible risk of ASF spread towards Western Europe. Therefore it is important to develop tools to improve our understanding of the spread and control of ASF for contingency planning. A stochastic and dynamic spatial spread model (DTU-DADS) was adjusted to simulate the spread of ASF virus between domestic swine herds exemplified by the Danish swine population. ASF was simulated to spread via animal movement, low- or medium-risk contacts and local spread. Each epidemic was initiated in a randomly selected herd - either in a nucleus herd, a sow herd, a randomly selected herd or in multiple herds simultaneously. A sensitivity analysis was conducted on input parameters. Given the inputs and assumptions of the model, epidemics of ASF in Denmark are predicted to be small, affecting about 14 herds in the worst-case scenario. The duration of an epidemic is predicted to vary from 1 to 76days. Substantial economic damages are predicted, with median direct costs and export losses of €12 and €349 million, respectively, when epidemics were initiated in multiple herds. Each infectious herd resulted in 0 to 2 new infected herds varying from 0 to 5 new infected herds, depending on the index herd type.

The impact of resources for clinical surveillance on the control of a hypothetical foot-and-mouth disease epidemic in Denmark.

The objectives of this study were to assess whether current surveillance capacity is sufficient to fulfill EU and Danish regulations to control a hypothetical foot-and-mouth disease (FMD) epidemic in Denmark, and whether enlarging the protection and/or surveillance zones could minimize economic losses. The stochastic spatial simulation model DTU-DADS was further developed to simulate clinical surveillance of herds within the protection and surveillance zones and used to model spread of FMD between herds. A queuing system was included in the model, and based on daily surveillance capacity, which was 450 herds per day, it was decided whether herds appointed for surveillance would be surveyed on the current day or added to the queue. The model was run with a basic scenario representing the EU and Danish regulations, which includes a 3 km protection and 10 km surveillance zone around detected herds. In alternative scenarios, the protection zone was enlarged to 5 km, the surveillance zone was enlarged to 15 or 20 km, or a combined enlargement of the protection and surveillance zones was modelled. Sensitivity analysis included changing surveillance capacity to 200, 350 or 600 herds per day, frequency of repeated visits for herds in overlapping surveillance zones from every 14 days to every 7, 21 and 30 days, and the size of the zones combined with a surveillance capacity increased to 600 herds per day. The results showed that the default surveillance capacity is sufficient to survey herds on time. Extra resources for surveillance did not improve the situation, but fewer resources could result in larger epidemics and costs. Enlarging the protection zone was a better strategy than the basic scenario. Despite that enlarging the surveillance zone might result in shorter epidemic duration, and lower number of affected herds, it resulted frequently in larger economic losses.

Spatiotemporal patterns, annual baseline and movement-related incidence of Streptococcus agalactiae infection in Danish dairy herds: 2000-2009.

Several decades after the inception of the five-point plan for the control of contagious mastitis pathogens, Streptococcus agalactiae (S. agalactiae) persists as a fundamental threat to the dairy industry in many countries. A better understanding of the relative importance of within- and between-herd sources of new herd infections coupled with the spatiotemporal distribution of the infection, may aid in effective targeting of control efforts. Thus, the objectives of this study were: (1) to describe the spatiotemporal patterns of infection with S. agalactiae in the population of Danish dairy herds from 2000 to 2009 and (2) to estimate the annual herd-level baseline and movement-related incidence risks of S. agalactiae infection over the 10-year period. The analysis involved registry data on bacteriological culture of all bulk tank milk samples collected as part of the mandatory Danish S. agalactiae surveillance scheme as well as live cattle movements into dairy herds during the specified 10-year period. The results indicated that the predicted risk of a herd becoming infected with S. agalactiae varied spatiotemporally; the risk being more homogeneous and higher in the period after 2005. Additionally, the annual baseline risks yielded significant yet distinctive patterns before and after 2005 - the risk of infection being higher in the latter phase. On the contrary, the annual movement-related risks revealed a non-significant pattern over the 10-year period. There was neither evidence for spatial clustering of cases relative to the population of herds at risk nor spatial dependency between herds. Nevertheless, the results signal a need to beef up within-herd biosecurity in order to reduce the risk of new herd infections.