Modelling control strategies against classical swine fever: Influence of traders and markets using static and temporal networks in Ecuador.

Pig farming in Ecuador represents an important economic and cultural sector, challenged by classical swine fever (CSF). Recently, the National Veterinary Service (NVS), has dedicated its efforts to control the disease by implementing pig identification, mandatory vaccination against CSF and movement control. Our objective was to characterise pig premises according to risk criteria, to model the effect of movement restriction strategies and to consider the temporal evolution of the network. Social network analysis (SNA), SIRS (susceptible, infected, recovered, susceptible) network modelling and temporal analysis were used. The network contained 751,003 shipments and 6 million pigs from 2017 to 2019. Participating premises consisted of 144,118 backyard farms, 138 industrial farms, 21,337 traders and 51 markets. The 10 most influential markets, in the Andean highlands, received between 500 and 4600 pigs each week. The 10 most influential traders made about 3 shipments with 17 pigs per week. Simulations without control strategy resulted in an average CSF prevalence of 14.4 %; targeted movement restriction reduced the prevalence to 7.2 %, while with random movement restriction it was 13 %. Targeting the top 10 national traders and markets and one of the high-risk premises in every parish was one of the best strategies with the surveillance infrastructure available, highlighting its major influence and epidemiological importance in the network. When comparing the static network with its temporal counterpart, causal fidelity (c = 0.62) showed a 38 % overestimation in the number of transmission paths, also traversing the network required 4.39 steps, lasting approximately 233 days. In conclusion, NVS surveillance strategies could be more efficient by targeting the most at-risk premises, and in particular, taking into account the temporal information would make the risk assessment much more precise. This information could contribute to implement risk-based surveillance reducing the time to eradicate CSF and other infectious animal diseases.

Network analysis of pig movements in Ecuador: Strengthening surveillance of classical swine fever.

The analysis of domestic pig movements has become useful to understand the disease spread patterns and epidemiology, which facilitates the development of more effective animal diseases control strategies. The aim of this work was to analyse the static and spatial characteristics of the pig network, to identify its trading communities and to study the contribution of the network to the transmission of classical swine fever. In this regard, we used the pig movement records from the National Veterinary Service of Ecuador (2017-2019), using social network analysis and spatial analysis to construct a network with registered premises as nodes and their movements as edges. Furthermore, we also created a network of parishes as its nodes by aggregating their premises movements as edges. The annual network metrics showed an average diameter of 20.33, a number of neighbours of 2.61, a shortest path length of 4.39 and a clustering coefficient of 0.38 (small-world structure). The most frequent movements were to or from markets (55%). Backyard producers made up 89% of the network premises, and the top 2% of parishes (highest degree) contributed to 50% of the movements. The highest frequencies of movements between parishes were in the centre of the country, while the highest frequency of movements to abattoirs was in the south-west. Finally, the pattern of classical swine fever (CSF) disease outbreaks within the Ecuador network was likely the result of network transmission processes. In conclusion, our results represented the first exploratory analysis of domestic pig movements at premise and parish levels. The surveillance system could consider these results to improve its procedures and update the disease control and management policy, and allow the implementation of targeted or risk-based surveillance.

Evaluation of the performance of slaughterhouse surveillance for bovine tuberculosis detection in Castilla y Leon, Spain.

Post-mortem inspection (PMI) of routinely slaughtered cattle in abattoirs is an extremely valuable tool for detecting bovine tuberculosis (bTB) infected herds that can supplement active surveillance activities. However, its true performance is difficult to assess due to the multiple factors that may affect it. Here, we determined relative efficiencies in the detection of bTB-compatible lesions and probabilities of subsequent laboratory confirmation of abattoirs located in Castilla y Leon, one of the regions with the largest cattle population in Spain, between 2010 and 2017. The slaughtered animal population was split based on the results of the ante-mortem tests (reactors or non-reactors), and two generalized linear multivariable mixed models were fitted to each subpopulation to calculate the risk of lesion detection and laboratory confirmation per abattoir while accounting for the effect of potential confounding variables. Throughout the 8-year period, ∼30,000 reactors and >2.8 million non-reactor animals in the ante-mortem tests were culled in the abattoirs under study. Bovine TB compatible lesions were detected in 4,710 (16%) reactors and 828 (0.03%) non-reactor animals, of which >95% were confirmed as infected through bacteriology. The probability of disclosure of bTB-like lesions was associated with the animal subpopulation, type of source unit, the herd size, the year of slaughter, the breed and age of the animal, and/or the season of slaughter. The probabilities of detection of bTB-like lesions varied largely depending on the abattoir in both subpopulations, ranging from 603 to 3,070 per 10,000 animals for the reactors and 0.2-16.1 per 10,000 animals for the non-reactor animals. Results obtained here will help to quantify the performance of PMI in abattoirs in Castilla y Leon and the between-abattoir variability, and to identify animals at increased risk of having bTB-like lesions detected during PMI based on animal- and farm-related factors.

Spatio-temporal network analysis of pig trade to inform the design of risk-based disease surveillance.

Network analysis is a powerful tool to describe, estimate, and predict the role of pig trade in the spread of pathogens and generate essential patterns that can be used to understand, prevent, and mitigate possible outbreaks. This study aimed to describe the network between premises such as production herds, slaughterhouses, and traders of pig movements and identify heterogeneities in the connectivity of premises in the state of Santa Catarina, Brazil, using social network analysis (SNA). We used static and temporal network approaches to describe pig trade in the state by quantifying network attributes using SNA parameters, such as causal fidelity, loyalty, the proportion of node-loyalty, resilience of outgoing contact chains, and communities. Two indexes were implemented, the first one is a normalized index based on SNA-farm level measures and other index-based SNA-farm level measures considering the swineherd population size from all premises, both indexes were summarized by a municipality to target and rank surveillance activities. Within Santa Catarina, the southwest region played a key role in that 80 % of trade was concentrated in this region, and thus acted as a hub in the network. Besides, nine communities were found. The results also showed that premises were highly connected in the static network, with the network exhibiting low levels of fragmentation and loyalty. Also, just 11 % of the paths in the static network existed in the temporal network which accounted for the order in which edges occurred. Therefore, the use of time-respecting-paths was essential to not overestimate potential transmission pathways and outbreak sizes. Compared to static networks, the application of temporal network approaches was more suitable to capture the dynamics of pig trade and should be used to inform the design of riskbased disease surveillance.

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.

Quantifying the dynamics of pig movements improves targeted disease surveillance and control plans.

Tracking animal movements over time may fundamentally determine the success of disease control interventions. In commercial pig production growth stages determine animal transportation schedule, thus it generates time-varying contact networks showed to influence the dynamics of disease spread. In this study, we reconstructed pig networks of one Brazilian state from 2017 to 2018, comprising 351,519 movements and 48 million transported pigs. The static networks view did not capture time-respecting movement pathways. For this reason, we propose a time-dependent network approach. A susceptible-infected model was used to spread an epidemic over the pig network globally through the temporal between-farm networks, and locally by a stochastic model to account for within-farm dynamics. We propagated disease to calculate the cumulative contacts as a proxy of epidemic sizes and evaluate the impact of network-based disease control strategies in the absence of other intervention alternatives. The results show that targeting 1,000 farms ranked by degree would be sufficient and feasible to diminish disease spread considerably. Our modelling results indicated that independently from where initial infections were seeded (i.e. independent, commercial farms), the epidemic sizes and the number of farms needed to be targeted to effectively control disease spread were quite similar; indeed, this finding can be explained by the presence of contact among all pig operation types The proposed strategy limited the transmission the total number of secondarily infected farms to 29, over two simulated years. The identified 1,000 farms would benefit from enhanced biosecurity plans and improved targeted surveillance. Overall, the modelling framework provides a parsimonious solution for targeted disease surveillance when temporal movement data are available.

Risk factors associated with Leishmania exposure among dogs in a rural area of Ilha Solteira, SP, Brazil.

INTRODUCTION: We sought to determine risk factors (RFs) associated with the presence of antibodies against Leishmania in dogs from a rural area of Ilha Solteira, SP, Brazil. METHODS: Serum samples were collected from 250 dogs and tested using indirect enzyme-linked immunosorbent assay (ELISA) and indirect immunofluorescence antibody tests (IFATs). Data concerning dogs, their environment, and their owners' knowledge of leishmaniasis were collected using a questionnaire. To determine RFs for contact with the parasite, univariate statistical analysis based on chi-squared and Fisher's exact tests, followed by logistic regression, was used. RESULTS: It was found that 79/250 (31.6%) of the dogs were positive by IFAT, and 72/250 (28.8%) by ELISA. A total of 82/250 dogs (32.8%) were positive in at least one test. The RFs associated with occurrences of Leishmania exposure were large body size (OR = 2.25; 95% CI = 1.26-4.04; p = 0.003), presence of chickens (OR = 1.94; 95% CI = 1.05-3.65; p = 0.023), and lack of knowledge about Leishmania among dog owners (OR = 1.74; 95% CI = 0.96-3.21; p = 0.049). After multivariate analysis, the RFs for occurrence of Leishmania exposure in dogs that remained significantly associated were the dog's size (large dogs) (OR = 1.2; 95% CI = 1.06-1.35; p = 0.003) and presence of chickens on the properties (small farms) (OR = 1.15; 95% CI = 1.02-1.30; p = 0.023). CONCLUSIONS: These results may be useful for improving preventive practices to reduce the incidence of Leishmania exposure among dogs in rural areas.

Risk factors associated with Leishmania exposure among dogs in a rural area of Ilha Solteira, SP, Brazil

Abstract INTRODUCTION: We sought to determine risk factors (RFs) associated with the presence of antibodies against Leishmania in dogs from a rural area of Ilha Solteira, SP, Brazil. METHODS: Serum samples were collected from 250 dogs and tested using indirect enzyme-linked immunosorbent assay (ELISA) and indirect immunofluorescence antibody tests (IFATs). Data concerning dogs, their environment, and their owners' knowledge of leishmaniasis were collected using a questionnaire. To determine RFs for contact with the parasite, univariate statistical analysis based on chi-squared and Fisher's exact tests, followed by logistic regression, was used. RESULTS: It was found that 79/250 (31.6%) of the dogs were positive by IFAT, and 72/250 (28.8%) by ELISA. A total of 82/250 dogs (32.8%) were positive in at least one test. The RFs associated with occurrences of Leishmania exposure were large body size (OR = 2.25; 95% CI = 1.26-4.04; p = 0.003), presence of chickens (OR = 1.94; 95% CI = 1.05-3.65; p = 0.023), and lack of knowledge about Leishmania among dog owners (OR = 1.74; 95% CI = 0.96-3.21; p = 0.049). After multivariate analysis, the RFs for occurrence of Leishmania exposure in dogs that remained significantly associated were the dog's size (large dogs) (OR = 1.2; 95% CI = 1.06-1.35; p = 0.003) and presence of chickens on the properties (small farms) (OR = 1.15; 95% CI = 1.02-1.30; p = 0.023). CONCLUSIONS: These results may be useful for improving preventive practices to reduce the incidence of Leishmania exposure among dogs in rural areas.

Seroprevalence of Leptospira spp infection and its risk factors among domestic dogs in Bogotá, Colombia.

Different analytical tools were used to determine the seroprevalence of and risk factors associated with Leptospira spp infection in 192 domestic dogs (Canis familiaris) in Bogotá, Colombia. Using the microscopic agglutination test (MAT), a battery of 16 Leptospira serovars were tested. The seroprevalence of Leptospira spp was calculated as 36.46% (95% CI 0.30-0.43). A questionnaire was applied to the dogs' owners at the time of sampling and the variables "Water sources near home" and "Dog hunting rodents" were identified as risk factors for leptospirosis occurrence in the urban area of Bogotá. Geographical coordinates relating to the dogs' households were obtained in order to map out the spatial distribution of reactive and unreactive dogs. Additionally, we found that the mean annual precipitation was higher at geographical locations with reactive animals than at those with unreactive dogs (p < 0.05). Preventing exposure of dogs to rodents and waste-water bodies that could be contaminated with Leptospira might effectively reduce occurrences of leptospirosis. Moreover, promoting preventive programs and vaccination of dogs against leptospirosis in areas of higher precipitation and prior to rainy months could be an effective strategy for leptospirosis prevention.

Isolation and identification of Mycobacterium bovis in bovines with positive reaction to the tuberculin test in the state of Paraíba, northeast Brazil / Isolamento e identificação de Mycobacterium bovis em bovinos positivos no teste de tuberculinização no estado da Paraíba, nordeste do Brasil

In areas where human tuberculosis and bovine tuberculosis coexist, differentiation between M. bovis and M. tuberculosis is important for monitoring the spread of M. bovis among cattle and from cattle to humans. The objective of this study was to isolate and identify M. bovis in bovines with positive diagnosis identified on tuberculin test in the State of Paraíba, Northeastern Brazil. Thirty-two bovines that tested positive in the comparative tuberculin test were used, from which samples of any organ with lesions suggestive of tuberculosis were collected, as well as lymph nodes, when no gross lesions were observed. Samples were submitted to histopathological exam, mycobacterial culture, Ziehl-Neelsen staining and molecular diagnosis. Twenty-one (65.6%) animals presented lesions suggestive of tuberculosis. As to body region 77.7% of lesions were found in the thoracic cavity, 12.4% in the head and 9.9% in the abdominal cavity. Among 55 samples submitted to mycobacterial culture, mycobacteria were isolated in 31 (56.4%), being 13 (41.9%) identified as M. bovis and 18 (58.1%) as Mycobacterium spp. Conclusion is that isolation and identification of M. bovis and Mycobacterium spp. in cattle suggests that humans are exposed to the risk of infection. This reinforces the need for intensification and optimization of prevention and control measures foreseen in the Brazilian National Program for the Control and Eradication of Bovine Brucellosis and Tuberculosis. Mycobacteria isolation and identification surveys are, therefore, encouraged in other Northeastern states.(AU)

Em áreas onde a tuberculose humana e a tuberculose bovina coexistem, a diferenciação entre M. bovis e M. tuberculosis é importante para monitorar a disseminação de M. bovis entre bovinos e destes para os seres humanos. Objetivou-se neste estudo isolar e identificar M. bovis em bovinos com diagnóstico positivo pelo teste de tuberculinização no estado da Paraíba, nordeste do Brasil. Foram submetidos 32 bovinos positivos ao teste de tuberculinização comparativa, dos quais foram colhidas amostras de qualquer órgão com lesões sugestivas de tuberculose, e, nos casos em que não foram observadas lesões sugestivas, foram colhidas amostras de linfonodos. As amostras foram submetidas a exame histopatológico, cultivo micobacteriológico, coloração de Ziehl-Neelsen e diagnóstico molecular. Apresentaram lesões sugestivas de tuberculose 21 animais (65,6%). Com relação à distribuição das lesões de acordo com a região corporal, 77,7% localizavam-se na cavidade torácica, 12,4% na cabeça e 9,9% na cavidade abdominal. De 55 amostras submetidas ao cultivo de micobactérias, em 31 (56,4%) foram isoladas micobactérias, sendo que em 13 (41,9%) foi identificado M. bovis, e nas 18 restantes (58,1%) foi identificado Mycobacterium spp. Conclui-se que o isolamento e a identificação de M. bovis e Mycobacterium spp. em bovinos indicam que os seres humanos estão expostos ao risco de infecção. Isso reforça a necessidade de intensificação e otimização de medidas de prevenção e controle previstas no Programa Nacional de Controle e Erradicação da Brucelose e Tuberculose Bovina. Sugere-se a realização de estudos de isolamento e identificação de micobactérias em outros estados do Nordeste.(AU)