Network analysis of dairy cattle movement and associations with bovine tuberculosis spread and control in emerging dairy belts of Ethiopia

The role of syndromic knowledge in Ethiopian veterinarians' treatment of cattle

Veterinarians play a significant role in the treatment and prevention of livestock diseases at the farm level, safeguarding public health and ensuring food safety. In sub-Saharan Africa, access to quality veterinary services is a major challenge for livestock farmers due to the low number of publicly employed veterinarians, underfunding and privatisation of veterinary services. Low investment in veterinary services and infrastructure, including a lack of laboratories for diagnosis, has made veterinarians rely on their experience and knowledge of cattle disease symptoms developed over years of practice to diagnose and treat cattle diseases. A cross-sectional survey using a role-play approach was used to collect data on knowledge regarding cattle diseases among veterinarians in veterinary clinics and private practices in Addis Ababa, Oromia and Adama regions in Ethiopia. Veterinarians were given a number of disease scenarios based on "fictive disease symptoms" that are commonly manifested in a sick cow and asked to identify the disease what personal biosecurity they would use, diagnostic tests they would perform, treatments they would prescribe, treatment costs, and additional services and inputs they would recommend to the farmer. The results show that veterinarians could identify endemic cattle diseases through symptoms. The majority of veterinarians did not find it important to report notifiable diseases, a behaviour which could hamper disease surveillance and outbreak response. The advice and services the veterinarians said they would offer and recommend to farmers included improvement in feeding, vaccination, use of artificial insemination, and adoption of farm biosecurity measures that can reduce disease prevalence, and improve food safety, animal health and welfare. Low use of personal protective equipment and other protective biosecurity measures among veterinarians could expose them to zoonotic diseases. The study concludes that there is a need for increased funding for continuous training, improved access to animal health-related information, and investment in infrastructure such as laboratories to enable veterinarians to deliver quality animal health services.

Mapping Bovine Tuberculosis in Colombia, 2001-2019

INTRODUCTION

Bovine tuberculosis is a zoonotic disease of significant impact, particularly in countries where a pastoral economy is predominant. Despite its importance, few studies have analysed the disease's behaviour in Colombia, and none have developed maps using geographic information systems (GIS) to characterise it; as such, we developed this study to describe the temporal-spatial distribution of bovine tuberculosis in Colombia over a period of 19 years.

METHODS

A retrospective cross-sectional descriptive study, based on reports by the Colombian Agricultural Institute (ICA), surveillance of tuberculosis on cattle farms in Colombia from 2001 to 2019 was carried out. The data were converted into databases using Microsoft Access 365®, and multiple epidemiological maps were generated with the QGIS® version 3.36 software coupled to shape files of all the country's departments.

RESULTS

During the study period, 5273 bovine tuberculosis cases were identified in multiple different departments of Colombia (with a mean of 278 cases/year). Regarding its temporal distribution, the number of cases varied from a maximum of 903 cases (17.12% of the total) in 2015 to a minimum of 0 between 2001 and 2004 and between 2017 and 2019 (between 2005 and 2016, the minimum was 46 cases, 0.87%).

CONCLUSIONS

GIS are essential for understanding the temporospatial behaviour of zoonotic diseases in Colombia, as is the case for bovine tuberculosis, with its potential implications for the Human and One Health approaches.

BCG vaccination reduces bovine tuberculosis transmission, improving prospects for elimination

Bacillus Calmette-Guérin (BCG) is a routinely used vaccine for protecting children against Mycobacterium tuberculosis that comprises attenuated Mycobacterium bovis. BCG can also be used to protect livestock against M. bovis; however, its effectiveness has not been quantified for this use. We performed a natural transmission experiment to directly estimate the rate of transmission to and from vaccinated and unvaccinated calves over a 1-year exposure period. The results show a higher indirect efficacy of BCG to reduce transmission from vaccinated animals that subsequently become infected [74%; 95% credible interval (CrI): 46 to 98%] compared with direct protection against infection (58%; 95% CrI: 34 to 73%) and an estimated total efficacy of 89% (95% CrI: 74 to 96%). A mechanistic transmission model of bovine tuberculosis (bTB) spread within the Ethiopian dairy sector was developed and showed how the prospects for elimination may be enabled by routine BCG vaccination of cattle.

New insight into social relationships in dairy cows and how time of birth, parity, and relatedness affect spatial interactions later in life

Social interactions between cows play a fundamental role in the daily activities of dairy cattle. Real-time location systems provide on a continuous and automated basis information about the position of individual cows inside barns, offering a valuable opportunity to monitor dyadic social contacts. Understanding dyadic social interactions could be applied to enhance the stability of the social structure promoting animal welfare and to model disease transmission in dairy cattle. This study aimed to identify the effect of different cow characteristics on the likelihood of the formation and persistence of social contacts in dairy cattle. The individual position of the lactating cows was automatically collected once per second for 2 wk, using an ultra-wideband system on a Swedish commercial farm consisting of almost 200 dairy cows inside a freestall barn. Social networks were constructed using the position data of 149 cows with available information on all characteristics during the study period. Social contacts were considered as a binary variable indicating whether a cow pair was within 2.5 m of each other for at least 10 min per day. The role of cow characteristics in social networks was studied by applying separable temporal exponential random graph models. Our results revealed that cows of the same parity interacted more consistently, as well as those born within 7 d of each other or closely related by pedigree. The repeatability of the topological parameters indicated a consistent short-term stability of the individual animal roles within the social network structure. Additional research is required to elucidate the underlying mechanisms governing the long-term evolution of social contacts among dairy cattle and to investigate the relationship between these networks and the transmission of diseases in the dairy cattle population.

Network analysis of pig movement data as an epidemiological tool: an Austrian case study

Animal movements represent a major risk for the spread of infectious diseases in the domestic swine population. In this study, we adopted methods from social network analysis to explore pig trades in Austria. We used a dataset of daily records of swine movements covering the period 2015-2021. We analyzed the topology of the network and its structural changes over time, including seasonal and long-term variations in the pig production activities. Finally, we studied the temporal dynamics of the network community structure. Our findings show that the Austrian pig production was dominated by small-sized farms while spatial farm density was heterogeneous. The network exhibited a scale-free topology but was very sparse, suggesting a moderate impact of infectious disease outbreaks. However, two regions (Upper Austria and Styria) may present a higher structural vulnerability. The network also showed very high assortativity between holdings from the same federal state. Dynamic community detection revealed a stable behavior of the clusters. Yet trade communities did not correspond to sub-national administrative divisions and may be an alternative zoning approach to managing infectious diseases. Knowledge about the topology, contact patterns, and temporal dynamics of the pig trade network can support optimized risk-based disease control and surveillance strategies.

Training needs assessment of veterinary practitioners in Ethiopia

Pastoral and agro-pastoral farming are extensively practised in Ethiopia, and the main livestock kept are cattle, goats, sheep, poultry, and camels. The livestock sector is faced with complex challenges including limited availability of well-trained and skilled animal health professionals. The objective of this study was to identify and prioritise areas for training with the goal of providing evidence to guide strategies to improve the skills, delivery, and governance of veterinary services across Ethiopia. A cross-sectional survey was developed and administered electronically to veterinary professionals in Ethiopia using the Qualtrics platform. Data were collected on select parameters including demographics, diseases of economic significance, diagnosis, disease prevention, biosecurity, disease control, treatment, epidemiology, One Health, disease reporting, and the participants’ opinions about training. The survey data was downloaded in Microsoft Excel and descriptive statistics performed. A total of 234 veterinary professionals completed the survey. Most participants were male (89.7%) and aged between 26 and 35 years (81.2%). Of the total respondents, 56.4% worked in government and 8.5% in private practice. Most participants perceived training on laboratory diagnostic testing, disease prevention, antimicrobial resistance, antibiotic sensitivity testing, basic epidemiology, and clinical procedures, as most beneficial. In addition, most respondents would like to receive training on diseases affecting cattle, poultry, and small ruminants. The findings from this study provide baseline information on priority training areas for veterinary professionals and could potentially contribute to national efforts to develop and implement a continuing professional development programme in the veterinary domain, in view of improving veterinary service delivery.

Inferring Mycobacterium bovis transmission between cattle and badgers using isolates from the Randomised Badger Culling Trial

Mycobacterium bovis (M. bovis) is a causative agent of bovine tuberculosis, a significant source of morbidity and mortality in the global cattle industry. The Randomised Badger Culling Trial was a field experiment carried out between 1998 and 2005 in the South West of England. As part of this trial, M. bovis isolates were collected from contemporaneous and overlapping populations of badgers and cattle within ten defined trial areas. We combined whole genome sequences from 1,442 isolates with location and cattle movement data, identifying transmission clusters and inferred rates and routes of transmission of M. bovis. Most trial areas contained a single transmission cluster that had been established shortly before sampling, often contemporaneous with the expansion of bovine tuberculosis in the 1980s. The estimated rate of transmission from badger to cattle was approximately two times higher than from cattle to badger, and the rate of within-species transmission considerably exceeded these for both species. We identified long distance transmission events linked to cattle movement, recurrence of herd breakdown by infection within the same transmission clusters and superspreader events driven by cattle but not badgers. Overall, our data suggests that the transmission clusters in different parts of South West England that are still evident today were established by long-distance seeding events involving cattle movement, not by recrudescence from a long-established wildlife reservoir. Clusters are maintained primarily by within-species transmission, with less frequent spill-over both from badger to cattle and cattle to badger.

A Longitudinal Study of Cattle Productivity in Intensive Dairy Farms in Central Ethiopia

Ethiopia is witnessing an emergence of intensive urban dairy farming. The aims of this study were to capture cattle productivity parameters in selected intensive dairy farms in and around Addis Ababa (Central Ethiopia). The study is a pre-requisite and baseline for further economic analysis of diseases such as bovine tuberculosis (BTB) and to assess some of the current challenges faced by farm owners for optimal animal performances. Hence, a 3-year longitudinal observational study was conducted for the first time in Ethiopia, in 24 dairy farms with intensive husbandry, including a total of 1,705 dairy animals. Herd characteristics, animal movement, and productivity parameters (fertility, morbidity, mortality) were recorded in a herd-book. Whereas, half the farms saw their animals increase in number over the 3 years, 37.5% (mainly large farms) saw their herd size decrease. Offtakes accounted for 76.6% of all animal exits. One hundred and ninety (11.1%) animals died of natural causes. Highest mortality was observed in young stock (13.9%). Overall, diseases were the leading cause for death (57.5%). The majority of calves (69%) that died, did so within the first week of life. Mean calving interval (CI) was 483.2 days. Successful conception after artificial insemination (AI) was 66.1% with Addis Ababa and smaller farms faring worst. Mean time interval from calving to first service was 152 days. Date of birth to first service was 592.2 days and date of birth to first calving was 794.7 days. In conclusion, the study showed sub-optimal productivity performances in intensive dairy cattle and highlighted some of the current gaps and challenges in urban dairy productivity.

Characterization and influencing factors of the pig movement network in Hunan Province, China

In terms of pig production in China, Hunan was the third largest province where the number of hogs accounted for 9.0 % of the national number of hogs in 2017. To propose the precise strategy for supervision of pig movements in Hunan Province, a weighted directed one-mode network was constructed using the data from the electronic animal health certificate platform in 2017. The nodes were designed as districts in Hunan and edges as flows of pig movement between districts. Social network analysis was used to analyse network characteristics and generalized linear models were performed to ascertain the socioeconomic factors that affect the pig movement network. During 2017, the pig movement network within the Hunan Province was composed of 122 nodes and 8562 directed connections, with a total of 510,973 shipments and 17,815,040 pigs moved. The network displayed a small-world topology, which had a higher clustering coefficient (0.4 vs. 0.1) and shorter average shortest path length (1.8 vs. 3.7) compared with equivalent random networks. The degree centrality positively correlated with closeness centrality (r = 0.99, P < 0.001) as well as betweenness centrality (r = 0.91, P < 0.001). After restricting the cross-regional pig movements in areas with the top 10 % of degree centrality, the number of pigs was reduced by nearly 50 % in the network, whereas the number of pigs was reduced by 94.0 % when movement restrictions were implemented in areas with the top 50 % of degree centrality. Observed network metrics showed an upward trend during the months of 2017, peaking in November and December. Generalized linear models showed that the size of the human population and per capita gross domestic product were the most important socioeconomic drivers of pig movements. The pig movement network in Hunan Province is a small-world network in which the introduction and spread of diseases may be quicker. More human, material, and financial resources should be allocated to areas with higher centrality. Swine movements were seasonal, and the inspection and quarantine work should be reinforced in the fourth quarter, especially in November and December. Pig movements were more active in areas with larger populations and advanced economy, and stricter supervision in these areas should be implemented. Our findings contribute to understanding the movement of pigs and the associated influencing factors in a big pig producing province in China, and the supervision strategies proposed in this study can be extended to other regions in China if proved to be viable.

Population structure and transmission of Mycobacterium bovis in Ethiopia

Bovine tuberculosis (bTB) is endemic in cattle in Ethiopia, a country that hosts the largest national cattle herd in Africa. The intensive dairy sector, most of which is peri-urban, has the highest prevalence of disease. Previous studies in Ethiopia have demonstrated that the main cause is Mycobacterium bovis, which has been investigated using conventional molecular tools including deletion typing, spoligotyping and Mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR). Here we use whole-genome sequencing to examine the population structure of M. bovis in Ethiopia. A total of 134 M. bovis isolates were sequenced including 128 genomes from 85 mainly dairy cattle and six genomes isolated from humans, originating from 12 study sites across Ethiopia. These genomes provided a good representation of the previously described population structure of M. bovis, based on spoligotyping and demonstrated that the population is dominated by the clonal complexes African 2 (Af2) and European 3 (Eu3). A range of within-host diversity was observed amongst the isolates and evidence was found for both short- and long-distance transmission. Detailed analysis of available genomes from the Eu3 clonal complex combined with previously published genomes revealed two distinct introductions of this clonal complex into Ethiopia between 1950 and 1987, likely from Europe. This work is important to help better understand bTB transmission in cattle in Ethiopia and can potentially inform national strategies for bTB control in Ethiopia and beyond.

Dynamics and risk of transmission of bovine tuberculosis in the emerging dairy regions of Ethiopia

The Ethiopian government has several initiatives to expand and intensify the dairy industry; however, the risk of bovine tuberculosis (bTB) spread is a challenge. To assess the rate of expansion and risk factors for transmission of bTB within-herds, we carried out a repeated cross-sectional survey at two time points, 2016/17 and 2018, in three regional cities, namely, Gondar, Hawassa and Mekelle, representing the emerging dairy belts of Ethiopia. The total number of herds involved was 128, comprising an average of 2303 cattle in each round. The Single Intradermal Comparative Cervical Tuberculin (SICCT) test was used to identify reactor status and data on herd-level risk factors were collected using a structured questionnaire. In the first survey, the apparent prevalence of bTB, as measured by the SICCT test, was 4.5% (95% CI 3.7–5.4%) at the individual animal-level and 24% (95% CI 17.5–32%) at the herd-level. There was no statistically significant change in the overall apparent prevalence or regional distribution at the second survey, consistent with the infection being endemic. The incidence rate was estimated at 3.6 (95% CI 2.8–4.5) and 6.6 (95% CI 3.0–12.6) cases/100 cattle (or herd)-years at the animal- and herd-levels, respectively. Risk factors significantly associated with the within-herd transmission of bTB were age group and within-herd apparent prevalence at the start of the observation period. We noted that farmers voluntarily took steps to remove reactor cattle from their herds as a consequence of the information shared after the first survey. Removal of reactors between surveys was associated with a reduced risk of transmission within these herds. However, with no regulatory barriers to the sale of reactor animals, such actions could potentially lead to further spread between herds. We therefore advocate the importance of setting up regulations and then establishing a systematic bTB surveillance programme to monitor the impact prior to implementing any control measures in Ethiopia.

Use of Network Analysis and Spread Models to Target Control Actions for Bovine Tuberculosis in a State from Brazil

Livestock movements create complex dynamic interactions among premises that can be represented, interpreted, and used for epidemiological purposes. These movements are a very important part of the production chain but may also contribute to the spread of infectious diseases through the transfer of infected animals over large distances. Social network analysis (SNA) can be used to characterize cattle trade patterns and to identify highly connected premises that may act as hubs in the movement network, which could be subjected to targeted control measures in order to reduce the transmission of communicable diseases such as bovine tuberculosis (TB). Here, we analyzed data on cattle movement and slaughterhouse surveillance for detection of TB-like lesions (TLL) over the 2016-2018 period in the state of Rio Grande do Sul (RS) in Brazil with the following aims: (i) to characterize cattle trade describing the static full, yearly, and monthly snapshots of the network contact trade, (ii) to identify clusters in the space and contact networks of premises from which animals with TLL originated, and (iii) to evaluate the potential of targeted control actions to decrease TB spread in the cattle population of RS using a stochastic metapopulation disease transmission model that simulated within-farm and between-farm disease spread. We found heterogeneous densities of premises and animals in the study area. The analysis of the contact network revealed a highly connected (~94%) trade network, with strong temporal trends, especially for May and November. The TLL cases were significantly clustered in space and in the contact network, suggesting the potential for both local (e.g., fence-to-fence) and movement-mediated TB transmission. According to the disease spread model, removing the top 7% connected farms based on degree and betweenness could reduce the total number of infected farms over three years by >50%. In conclusion, the characterization of the cattle network suggests that highly connected farms may play a role in TB dissemination, although being close to infected farms was also identified as a risk factor for having animals with TLL. Surveillance and control actions based on degree and betweenness could be useful to break the transmission cycle between premises in RS.

Genotype Diversity of Mycobacterium bovis and Pathology of Bovine Tuberculosis in Selected Emerging Dairy Regions of Ethiopia

Bovine tuberculosis (bTB) is endemic in Ethiopia with higher prevalence in cattle, particularly in the central parts. Spread of Mycobacterium bovis (M. bovis) to wider regions is inevitable in uncontrolled conditions. This study was conducted to explore the pathology, characterize M. bovis strains, and describe genotypic diversity to demonstrate possible epidemiological links in emerging dairy areas of Ethiopia, namely, Mekelle and Gondar. Twenty-seven bTB positive cattle identified by the Single Intradermal Comparative Cervical Tuberculin (SICCT) test were subjected to post-mortem inspection to determine lesion distribution and pathological score. Samples from tissues with visible tuberculous or suspected non-visible lesions were processed and cultured following a standard protocol. Isolates identified as M. bovis by Region of Difference (RD)-based Polymerase Chain Reaction (PCR) were also spoligotyped to determine their spoligotype patterns. Post-mortem inspection of visceral organs indicated bTB suggestive lesions in 41% of the animals, with 25% being in the lungs. Lymph nodes from 77% of the animals had lesions. Fifty-five isolates identified from 24 of the slaughtered animals were confirmed as M. bovis. No other mycobacterial species were isolated. Spoligotyping classified strains from 21 of these animals into seven spoligotype patterns: SB0133, SB0134, SB1176, SB2233, SB2290, SB2467, and SB2520. More than one spoligotype were identified from five of these animals, and none of the last four spoligotypes had been reported in Ethiopia before. SB0134 was the most predominant type (47%) followed by SB0133 (25.5%). SB0133, SB2290, SB2467, and SB1176 are spoligotypes lacking spacers 3–7, characteristics of M. bovis strains of the African 2 (Af2) clonal complex, while SB0134, SB2233, and SB2520 do not belong to any of the established clonal complexes and likely to have a different evolutionary history. Despite a small sample size, the present study showed strain diversity with multiple genotypes identified in a single herd and even within a single animal, and the genotypes showed no sign of geographical localization, which could be a consequence of significant movement of bTB diseased cattle around the country, spreading the disease. Therefore, any future control programme of bTB in Ethiopia needs to address the risks of cattle movement.

Spatial and network characteristics of Irish cattle movements

Our aim was to examine, for the first time, the spatial and network characteristics of cattle movements between herds in the Republic of Ireland (ROI), to inform policy and research of relevance to the surveillance and management of disease in Irish cattle. We analysed movements in 2016 as discrete herd to herd pairings (degree), herd to herd pairings by date of move (contacts) and herd to herd pairings by date and individual animal (transfers), and looked at each of these as movements out of a herd (out degree, out contacts, out transfers) and into a herd (in degree, in contacts, in transfers). We found that the frequency distributions, by herd, of these six move types were all heavily right skewed but in the case of the 'out' data types more closely followed a log-normal than the scale free distribution often reported for livestock movement data. For each distinct herd to herd contact in a given direction, over 90 % occurred only once, whereas the maximum number of occurrences was 62. Herd-level Spearman rank correlations between inward moves (represented as in degree, in contacts, in transfers) and outward moves (out degree, out contacts, out transfers) were weak or even negative whereas correlations between different measures of outward moves or inward moves (e.g. out degree vs. out contacts, in transfers vs. in degree) were stronger. Correlations between these variables and the network measure betweenness varied between r = 0.513 and r = 0.587. Some herds took part in a relatively large number of movements whilst also retaining their cattle for long periods (> 100 days) between moves. In and out degree, contacts and transfers were mapped across Ireland on a 5 km grid, and additionally normalized per 1000 animals and per herd. We found considerable variation in the number of movements by county. Approximately half of transfers were conducted within a single county, but the number and distance of between county movements varied considerably by county of origin and county of destination, with the proportion of moves completed within a single county correlated with its size. Herds exchanging cattle via a market were generally further apart than when moves were made directly herd to herd. For contacts, the distances moved away from the herd were on average greater for origin herds in the west of ROI whereas distances moved to a herd were generally greater for destination herds in the centre-east and the north-west.

Mycobacterium bovis Population Structure in Cattle and Local Badgers: Co-Localisation and Variation by Farm Type

Bovine tuberculosis surveillance in Northern Ireland includes Multiple-Locus Variable number tandem repeat Analysis (MLVA) to determine the Mycobacterium bovis genetic type present in both cattle and the predominant wildlife host, the European badger (Meles meles). These data are useful for investigating clusters of infection and understanding the scale at which interspecific transmission may occur. We utilised a comprehensive dataset of routinely sampled isolates from infected cattle and from badgers killed in road-traffic accidents to investigate the spatial co-location of MLVA types in, and between, the badger and cattle populations. Furthermore, we investigated the hypothesis that the type of farming enterprise might explain some variation in this relationship. MLVA types were spatially co-localised in cattle and road-traffic accident (RTA) badger hosts, indicative of a shared epidemic. Dairy herds were more likely to have at least one MLVA type in common with nearby RTA badgers, compared to non-dairy herd types. Marginally more MLVA spatial clustering was observed in non-dairy herds, which may be a consequence of relatively more between-herd movements. For the cattle population, local transmission mechanisms such as infection from contiguous herds, infectious wildlife and short-range between-herd cattle movements appear primarily to drive the epidemic: there appears to be a more limited role for long-range movements. Animal management practices are likely to be the driving force behind this observation, as beef rearing is associated with elevated numbers of animal movements compared to dairy herds.

Mapping livestock movements in Sahelian Africa

In the dominant livestock systems of Sahelian countries herds have to move across territories. Their mobility is often a source of conflict with farmers in the areas crossed, and helps spread diseases such as Rift Valley Fever. Knowledge of the routes followed by herds is therefore core to guiding the implementation of preventive and control measures for transboundary animal diseases, land use planning and conflict management. However, the lack of quantitative data on livestock movements, together with the high temporal and spatial variability of herd movements, has so far hampered the production of fine resolution maps of animal movements. This paper proposes a general framework for mapping potential paths for livestock movements and identifying areas of high animal passage potential for those movements. The method consists in combining the information contained in livestock mobility networks with landscape connectivity, based on different mobility conductance layers. We illustrate our approach with a livestock mobility network in Senegal and Mauritania in the 2014 dry and wet seasons.

Effects of trading networks on the risk of bovine tuberculosis incidents on cattle farms in Great Britain

Trading animals between farms and via markets can provide a conduit for spread of infections. By studying trading networks, we might better understand the dynamics of livestock diseases. We constructed ingoing contact chains of cattle farms in Great Britain that were linked by trading, to elucidate potential pathways for the transmission of infection and to evaluate their effect on the risk of a farm experiencing a bovine tuberculosis (bTB) incident. Our findings are consistent with variation in bTB risk associated with region, herd size, disease risk area and history of previous bTB incidents on the root farm and nearby farms. However, we also identified effects of both direct and indirect trading patterns, such that connections to more farms in the England High-Risk Area up to three movements away from the root farm increased the odds of a bTB incident, while connections with more farms in the England Low-Risk Area up to eight movements away decreased the odds. Relative to other risk factors for bTB, trading behaviours are arguably more amenable to change, and consideration of risks associated with indirect trading, as well direct trading, might therefore offer an additional approach to bTB control in Great Britain.

Dynamics of livestock-associated methicillin resistant Staphylococcus aureus in pig movement networks: Insight from mathematical modeling and French data

Livestock-associated methicillin resistant Staphylococcus aureus (LA-MRSA) colonizes livestock animals worldwide, especially pigs and calves. Although frequently carried asymptomatically, LA-MRSA can cause severe infections in humans. It is therefore important to better understand LA-MRSA spreading dynamics within pig farms and over pig movement networks, and to compare different strategies of control and surveillance. For this purpose, we propose a stochastic meta-population model of LA-MRSA spread along the French pig movement network (n = 10,542 farms), combining within- and between-farm dynamics, based on detailed data on breeding practices and pig movements between holdings. We calibrate the model using French epidemiological data. We then identify farm-level factors associated with the spreading potential of LA-MRSA in the network. We also show that, assuming control measures applied in a limited (n = 100) number of farms, targeting farms depending on their centrality in the network is the only way to significantly reduce LA-MRSA global prevalence. Finally, we investigate the scenario of emergence of a new LA-MRSA strain, and find that the farms with the highest indegree would be the best sentinels for a targeted surveillance of such a strain's introduction.