Pig Movements Research Articles

Modeling between-farm transmission dynamics of porcine epidemic diarrhea virus: Characterizing the dominant transmission routes

The role of transportation vehicles, pig movement between farms, proximity to infected premises, and feed deliveries has not been fully considered in the dissemination dynamics of porcine epidemic diarrhea virus (PEDV). This has limited efforts for disease prevention, control and elimination restricting the development of risk-based resource allocation to the most relevant modes of PEDV dissemination. Here, we modeled nine pathways of between-farm transmission represented by a contact network of pig movements between sites, farm-to-farm proximity (local transmission), four distinct contact networks of transportation vehicles (trucks that transport pigs from farm-to-farm and farm-to-markets, as well as trucks transporting feed and staff), the volume of animal by-products in feed diets (e.g., fat and meat-and-bone-meal) to reproduce PEDV transmission dynamics. The model was calibrated in space and time with weekly PEDV outbreaks. We investigated the model performance to identify outbreak locations and the contribution of each route in the dissemination of PEDV. The model estimated that 42.7% of the infections in sow farms were related to vehicles transporting feed, 34.5% of infected nurseries were associated with vehicles transporting pigs between farms, and for both farm types, local transmission or pig movements were the next most relevant transmission routes. On the other hand, finishers were most often (31.4%) infected via local transmission, followed by the vehicles transporting feed and pigs between farms. Feed ingredients did not significantly improve model calibration metrics, sensitivity, and specificity; therefore, it was considered to have a negligible contribution in the dissemination of PEDV. The proposed modeling framework provides an evaluation of PEDV transmission dynamics, ranking the most important routes of PEDV dissemination and granting the swine industry valuable information to focus efforts and resources on the most important transmission routes.

Optimising response to an introduction of African swine fever in wild pigs.

African swine fever virus (ASFv) is a virulent pathogen that threatens domestic swine industries globally and persists in wild boar populations in some countries. Persistence in wild boar can challenge elimination and prevent disease-free status, making it necessary to address wild swine in proactive response plans. In the United States, invasive wild pigs are abundant and found across a wide range of ecological conditions that could drive different epidemiological dynamics among populations. Information on the size of the control areas required to rapidly eliminate the ASFv in wild pigs and how this area should change with management constraints and local ecology is needed to optimize response planning. We developed a spatially explicit disease transmission model contrasting wild pig movement and contact ecology in two ecosystems in Southeastern United States. We simulated ASFv spread and determined the optimal response area (reported as the radius of a circle) for eliminating ASFv rapidly over a range of detection times (when ASFv was detected relative to the true date of introduction), culling capacities (proportion of wild pigs in the culling zone removed weekly) and wild pig densities. Large radii for response areas (14km) were needed under most conditions but could be shortened with early detection (≤ 8 weeks) and high culling capacities (≥ 15% weekly). Under most conditions, the ASFv was eliminated in less than 22 weeks using optimal control radii, although ecological conditions with high rates of wild pig movement required higher culling capacities (≥ 10% weekly) for elimination within 1 year. The results highlight the importance of adjusting response plans based on local ecology and show that wild pig movement is a better predictor of the optimal response area than the number of ASFv cases early in the outbreak trajectory. Our framework provides a tool for determining optimal control plans in different areas, guiding expectations of response impacts, and planning resources needed for rapid elimination.

Network analysis of live pig movements in North Macedonia: Pathways for disease spread.

Globalization of trade, and the interconnectivity of animal production systems, continues to challenge efforts to control disease. A better understanding of trade networks supports development of more effective strategies for mitigation for transboundary diseases like African swine fever (ASF), classical swine fever (CSF), and foot-and-mouth disease (FMD). North Macedonia, bordered to the north and east by countries with ongoing ASF outbreaks, recently reported its first incursion of ASF. This study aimed to describe the distribution of pigs and pig farms in North Macedonia, and to characterize the live pig movement network. Network analyses on movement data from 2017 to 2019 were performed for each year separately, and consistently described weakly connected components with a few primary hubs that most nodes shipped to. In 2019, the network demonstrated a marked decrease in betweenness and increase in communities. Most shipments occurred within 50 km, with movements <6 km being the most common (22.5%). Nodes with the highest indegree and outdegree were consistent across years, despite a large turnover among smallholder farms. Movements to slaughterhouses predominated (85.6%), with movements between farms (5.4%) and movements to market (5.8%) playing a lesser role. This description of North Macedonia's live pig movement network should enable implementation of more efficient and cost-effective mitigation efforts strategies in country, and inform targeted educational outreach, and provide data for future disease modeling, in the region.

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.

Influence of the shape on the hydraulic resistance of bypass channels inside a smart pig for low pressure gas pipeline inspection

The in-line smart pig for gas pipeline diagnostics is driven by the pumped gas and performs quality diagnostics only if its speed is constant, when the information reading is uniform along the length of the pipeline. In a low-pressure gas pipeline, if there are inhomogeneities on its walls, the condition of the pig speed constancy is easily broken, as the force of resistance to the pig movement on the stoppers is comparable with the difference of pressure forces acting on its ends. A central bypass channel of constant cross-section is usually used to control the pig velocity. The paper shows insufficiency of such method of regulation, leading to noticeable flow pulsations at the outlet of the channel. The use of variable cross-section of the bypass channel along its length in the form of a Laval nozzle to reduce flow pulsations is proposed. The numerical simulation of gas flow in Laval nozzles of different configuration is performed; it is shown that for all considered nozzles, the pressure pulsation at the channel outlet is 20-30 times less than that in the cylindrical channel, which simplifies the velocity control of such pig. However, it is not possible to completely avoid detachment of the flow from the walls of the expanding part of the nozzle, so in order to reduce the area of the detachment zone and reduce the flow resistance force, additional peripheral bypass channels connecting the inlet end of the pig with the diffuser section of the central bypass are added. Thus, a 40% reduction of gas flow resistance force through the bypass compared to the cylindrical bypass is obtained.

Effect of Olive oil on Osteoprotegerin Expression on the Tension side of Gingival Crevicular Fluid in the Orthodontic Tooth Movement of Old and Young Guinea Pigs

Background: Olive oil is a natural source of phytoestrogens and antioxidants similar to mammalian estrogen. The substance increases osteoblast differentiation and osteoprotegerin (OPG) expression. Objective of the study: To examine the effect of giving olive oil on OPG expression of gingival crevicular fluid in the orthodontic tooth movement among old and young guinea pigs. Methodology: The four groups of guinea pigs (n = 3) consisted of old guinea pigs given olive oil (OO), old controls (OC), the young given olive oil (YO), and young controls (YC). The teeth were movedreciprocally to distal by a 0.35 N open coil spring which was attached to the bracket of the lower incisors. The YO group was given olive oil at 0.7ml/day dosage and the OO group had 1.86ml olive oil administered per day until day 14. OPG expression was analyzed in gingival crevicular fluid (GCF) sample using the enzyme-linked immunosorbent assay (ELISA) on days 0, 7, and 14. Retrieved data was analyzed using Three-way ANOVA Statistic Test followed by Post Hoc LSD Test. Results: The statistical test showed that olive oil increased OPG expression in old and young guinea pigs (p&lt;0.05), and OPG OO expression was comparable to that in YC day 7. OPG YO expression was higher than OO (p &lt;0.05). Increasing duration of olive oil application led to higher OPG expression (p &lt;0.05). There was a correlation between olive oil and age and duration of administration (p &lt;0.05). Conclusion: Olive oil increased the OPG expression on GCF of old and young guinea pigs during orthodontic tooth movement, with the highest OPG expression in YO day 14.

Emerging infectious diseases may spread across pig trade networks in Thailand once introduced: a network analysis approach.

In Thailand, pork is one of the most consumed meats nationwide. Pig farming is hence an important business in the country. However, 95% of the farms were considered smallholders raising only 50 pigs or less. With limited budgets and resources, the biosecurity level in these farms is relatively low. Pig movements have been previously identified as a risk factor in the spread of infectious diseases. Therefore, the present study aimed to explicitly analyze the pig movement network structure and assess its vulnerability to the spread of emerging diseases in Thailand. We used official electronic records of nationwide pig movements throughout the year 2021 to construct a directed weighted one-mode network. Degree centrality, degree distribution, connected components, network community, and modularity were measured to explore the network architectures and properties. In this network, 484,483 pig movements were captured. In which, 379,948 (78.42%) were moved toward slaughterhouses and hence excluded from further analyses. From the remaining links, we suggested that the pig movement network in Thailand was vulnerable to the spread of emerging infectious diseases. Within the network, we found a strongly connected component (SCC) connecting 1044 subdistricts (38.6% of the nodes), a giant weakly connected component (GWCC) covering 98.2% of the nodes (2654/2704), and inter-regional communities with overall network modularity of 0.68. The disease may rapidly spread throughout the country. A better understanding of the nationwide pig movement networks is helpful in tailoring control interventions to cope with the newly emerged diseases once introduced.

Identifying-and-counting based monitoring scheme for pigs by integrating BLE tags and WBLCX antennas

Recently, the Internet of Things (IoT) technologies have been applied to pig monitoring. Among these, electronic tags help identify individual growing-finishing pigs. Nevertheless, the tags are insufficient to achieve accurate and reliable monitoring in pigsties. Instead, advanced processing data for individual behaviors, such as visit times in the feeding and resting areas and the number of movements between these areas, are required. Numerically measuring the movements of individual pigs in the pigsty is a precondition for obtaining these data. This paper proposes a monitoring scheme of a large herd of pigs for individual identification and counting. As a technical solution, a monitoring system is developed using Bluetooth low-energy (BLE) tags and wireless broadband leaky coaxial cable (WBLCX) antennas. The monitoring system collects access data transmitted from the BLE tags attached to individual pigs. Then the monitoring scheme estimates the location and movement of each pig by computing the collected data. A series of experiments was conducted to evaluate the detection characteristics between the BLE tags and the WBLCX antennas and to show their performances. In addition, the effectiveness for the proposed area-determination algorithm and the monitoring system was verified by field experiments on a pig farm in Japan. Our experimental results are summarized as follows. First, data comparisons between the area-determination algorithm and visual inspections confirmed the validity of the proposed monitoring scheme. Secondly, by the monitoring scheme, the area movements and the dwell times of pigs in a pigsty could be investigated. From the experimental results, the use of the proposed monitoring is expected to be able to observe the locations and movements for large herds of pigs in the pigsty. This paper proposes a monitoring scheme based on identifying and counting of individual pigs, explains the details of the monitoring scheme on the basis of hardware configurations, and verifies its effectiveness and feasibility via experiments.

African swine fever variants currently outside Africa

In 2007 African swine fever (ASF) type 2 entered Georgia and since then has progressively moved around the planet resulting in a global pandemic, which is responsible for killing many millions of pigs. Local spread occurs through wild pig movement but human movement of pork products and even pigs for hunting has resulted in movement over 1000s of kilometres. With the devastating impact of ASF type 2 on a pig farm the development of a suitable vaccine is essential. Unfortunately, in desperation, potential ASF vaccine candidates have been released. The premature release of vaccine candidates has created clinical confusion by reducing the clinical signs of ASF, in particular the high pyrexia usually seen in pigs infected with this virus. The lack of specific clinical signs can make identify of sick animals more difficult and this increases the potential for incursion across national borders.

Movements of free-range pigs in rural communities in Zambia: an explorative study towards future ring interventions for the control of Taenia solium

BackgroundTaenia solium typically affects resource-poor communities where pigs are allowed to roam freely, and sanitation and hygiene levels are suboptimal. Sustainable, long-term strategies are urgently needed to control the disease. Geographically targeted interventions, i.e. screening or treatment of taeniosis among people living near infected pigs (defined as ring screening and ring treatment, respectively), have been shown to be effective control options in Peru. However, these results might not be directly generalizable to sub-Saharan African settings. Pig movements play a vital role in the transmission and, consequently, the success of ring interventions against T. solium. The aim of the present study was to explore roaming patterns of pigs in T. solium endemic communities in Zambia as a first step toward evaluating whether ring interventions should be considered as a treatment option in Zambia.MethodsIn total, 48 free-roaming pigs in two rural neighborhoods in the Eastern Province of Zambia were tracked using a Global Positioning System (GPS) receiver. Tracking took place in April (end of the rainy season) 2019 and October (end of the dry season) 2019. The number of revisitations and the time spent within rings of different radii (50, 100 and 250 m) around the coordinates of each pig owner’s household were calculated for each pig.ResultsThe total tracking time for 43 pigs in the final analysis set ranged between 43 and 94 h. Pigs spent a median of 31% and 13% of the tracked time outside the 50- and 100-m radius, respectively, although large variations were observed between pigs. Overall, 25 pigs (58%) went outside the 250-m ring at least once, and individual excursions lasting up to 16 h were observed. In the dry season, 17 out of 23 pigs went outside the 250-m radius compared to only eight out of 20 pigs in the rainy season (P = 0.014).ConclusionsIn our study sites in Zambia, the majority of pigs spent most of their time within 50 or 100 m of their owner’s home, and these results are comparable with those on Peruvian pigs. Both radii could therefore be considered reasonable options in future ring interventions.Graphical

Summer habitat use and movements of invasive wild pigs (Sus scrofa) in Canadian agro-ecosystems

Resource selection informs understanding of a species’ ecology and is especially pertinent for invasive species. Since introduced to Canada, wild pigs ( Sus scrofa Linnaeus, 1978) remain understudied despite recognized negative impacts on native and agricultural systems globally. Elsewhere in North America, pigs typically use forests and forage in agricultural crops. We hypothesized Canadian wild pigs would behave similarly, and using GPS locations from 15 individuals, we examined diel and seasonal resource selection and movement in the Canadian prairie region. Forests were predominately selected during the day, while corn ( Zea mays L.), oilseeds, and wheat ( Triticum aestivum L.) were predominately selected at night. Forests and corn were consistently selected throughout the growing season. Wetlands and forests showed greater use rates than other habitats, with evident trade-offs as crop use increased with the timing of maturation. Activity was consistent with foraging in growing crops. Results indicate diel patterns were likely a function of short-term needs to avoid daytime anthropogenic risk, while seasonal patterns demonstrate how habitats that fill multiple functional roles — food, cover, and thermoregulation — can be optimized. Understanding selection by invasive species is an important step in understanding their potential environmental impacts in novel environments and informs their management.

Behavioral states in space and time: understanding landscape use by an invasive mammal

AbstractAnimal movement models can be used to understand species behavior and assist with implementation of management activities. We explored behavioral states of an invasive wild pig (Sus scrofa) population that recently colonized central Michigan, USA, 2014–2018. To quantify environmental factors related to wild pig movement ecology and spatio‐temporal landscape use, we predicted wild pig behavioral states relative to land cover type, landscape structure (i.e., edge and patch cohesion), and weather conditions. We used global positioning system (GPS)‐collars and monitored 8 wild pigs from 2014–2018. We fit local convex hulls and calculated movement metrics revealing 3 wild pig behavioral states (resting, exploratory, and relocating) and constructed a 3‐level model to predict behavioral state probabilities relative to biotic and abiotic conditions. Probabilities of exploratory and resting behaviors were higher nearer to riparian and open herbaceous cover types (oftentimes emergent marsh), indicating that these cover types provided security cover during activity and bedding. Hard mast cover types had a strong positive association with relocating behaviors. More cohesive patches of agriculture and shrub cover types were associated with higher probabilities of exploratory behaviors, while resting was more likely in continuous patches of agriculture (mostly mid‐summer corn). The probability of exploratory behaviors increased exponentially with warming ambient temperature. Our results may be used by managers to develop control strategies conducive to landscape and environmental conditions where the likelihood of encountering wild pigs is highest or targeting wild pigs when in a behavioral state most vulnerable to a particular removal technique.

Live pig markets are hotspots for spread of African swine fever virus in Nigeria.

Livestock trading through live animal markets are potential pathways for the introduction and spread of economically important pathogens like the African swine fever virus (ASFV) to new areas in several countries. Due to the high demand for live pigs in Nigeria both for restocking and slaughter, live pigs are sold at designated live pig markets (LPM) in the country. This involves movement of pigs over long distances. Despite, reports of ASF outbreaks following restocking of pigs bought from LPMs, there is paucity of information on the role of LPMs in the epidemiology of ASF. In this study, data and pig samples (whole blood, sera, tissue) were collected from 4 selected LPMs in Nigeria (Dawaki, Katsit, Numan and Pandam) between 2019 and 2020. Samples were analysed by polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA). Four genes of ASFV positive samples were characterized to identify the circulating genotypes. Results revealed trade activities involving transportation of pigs from these selected markets to 42 major cities and towns in thirteen (13) States of Nigeria. PCR results revealed an overall ASF prevalence of 10.77% (66/613). ASFV was confirmed by PCR in all the selected LPMs with a prevalence rate of 3.13%-23.81%. The phylogeny revealed genotype I and serogroup 4 based on the p72 protein that encodes the B646L gene and the EP402R gene encoding the CD2V. While sequence analysis of CVR of B602L gene revealed 8 tetrameric repeats variants, six of which have never been reported in Nigeria. Analysis of sera samples recorded a seroprevalence of 6.9% (16/217) within the study period. Findings from this study show that LPM are hotspots and channels for transmission and continuous spread of ASFV in Nigeria. Therefore, for ASF to be controlled in Nigeria, disease surveillance and regulation at LPMs are critical.

Modelling and assessing additional transmission routes for porcine reproductive and respiratory syndrome virus: Vehicle movements and feed ingredients.

Accounting for multiple modes of livestock disease dissemination in epidemiological models remains a challenge. We developed and calibrated a mathematical model for transmission of porcine reproductive and respiratory syndrome virus (PRRSV), tailored to fit nine modes of between-farm transmission pathways including: farm-to-farm proximity (local transmission), contact network of batches of pigs transferred between farms (pig movements), re-break probabilities for farms with previous PRRSV outbreaks, with the addition of four different contact networks of transportation vehicles (vehicles to transport pigs to farms, pigs to markets, feed and crew) and the amount of animal by-products within feed ingredients (e.g., animal fat or meat and bone meal). The model was calibrated on weekly PRRSV outbreaks data. We assessed the role of each transmission pathway considering the dynamics of specific types of production (i.e., sow, nursery). Although our results estimated that the networks formed by transportation vehicles were more densely connected than the network of pigs transported between farms, pig movements and farm proximity were the main PRRSV transmission routes regardless of farm types. Among the four vehicle networks, vehicles transporting pigs to farms explained a large proportion of infections, sow=20.9%; nursery=15%; and finisher=20.6%. The animal by-products showed a limited association with PRRSV outbreaks through descriptive analysis, and our model results showed that the contribution of animal fat contributed only 2.5% and meat and bone meal only .03% of the infected sow farms. Our work demonstrated the contribution of multiple routes of PRRSV dissemination, which has not been deeply explored before. It also provides strong evidence to support the need for cautious, measured PRRSV control strategies for transportation vehicles and further research for feed by-products modelling. Finally, this study provides valuable information and opportunities for the swine industry to focus effort on the most relevant modes of PRRSV between-farm transmission.

Shifting to sounders: Whole sounder removal eliminates wild pigs

AbstractWild pig (Sus scrofa) eradication in demographically open populations has seemed an impossible feat for managers, but more recently, whole sounder removal (WSR) has been proposed as a trapping strategy that has the potential to be successful in eradicating wild pigs from an area. However, little empirical data exist concerning implementation of whole sounder removal strategies. Our objective was to implement and describe wild pig management using WSR. We established a 27‐km2 area (northwest section) where sounders were removed using WSR and a 29‐km2 area (southeast section) where GPS collars were deployed on Lowndes Wildlife Management Area in Alabama. Prior to implementing WSR, we used game cameras over bait at a density of one camera/km2 in November 2014 and counted 65 and 100 individuals in our northwest and southeast sections, respectively. We began WSR July 2015 and by May 2016, we reduced the estimated population by 90%. However, due to births and seasonal movements of pigs in the periphery of the study area, the population fluctuated between 10–20 individuals from May 2016 to December 2017. In December 2017, we removed the last known remaining sounder, and using game cameras, observed no sounders in the northwest section for the following 7 months, the remaining length of the study. We determined that using the WSR approach can lead to a delay before inevitable recolonization. Therefore, WSR can be a successful tool to significantly reduce a wild pig population and potentially provide managers a pig‐free area.

The African swine fever threat to Australia

African swine fever (ASF) is not a new disease: its impact on domestic pig production in Africa was first documented 100 years ago. For most of the twentieth century ASF was considered a disease of Africa, with occasional incursions into Europe and the western hemisphere. However, during the past two decades, ASF has emerged as a truly global diseases, invading parts of Europe and spreading throughout Asia. By 2020, ASF had spread as far as Papua New Guinea. Why ASF has spread such distances so quickly is not well understood, however the movement of both live pigs and pork products undoubtedly is a major contributing factor. The role that wild pigs play in the spread and maintenance of ASF virus is a topic of ongoing debate. Adding to the complexity of the epidemiology of this disease, ASF virus can be transmitted by some tick species in particular ecosystems. Australia is vulnerable to an ASF virus incursion. The threat is further heightened by the uncertainty regarding whether our large and widely distributed feral pig population would become endemically infected, creating a barrier to eradication of the disease. Preventing an incursion of ASF virus relies on ongoing risk assessments based on where the virus currently exists, and the disease pathways for introduction. Within the Australian context, regulatory enforcement and surveillance of illegally important pork products is paramount to minimise the treat that ASF poses.

Descriptive and Multivariate Analysis of the Pig Sector in North Macedonia and Its Implications for African Swine Fever Transmission.

North Macedonia, a country in the Balkan region of Europe, is currently bordered to the north and east by countries with active African swine fever (ASF) outbreaks. The predominantly traditional backyard pig farming sector in this country is under imminent threat of disease incursion. The characteristics and practices of such sectors have rarely been described, and thus the implications for these factors on disease introduction and spread are poorly understood. Using a semi-structured questionnaire, 457 pig producers were interviewed, providing information on 77.7% of the pig population in North Macedonia. In addition, a pilot study of 25 pig producers in Kosovo was performed. This study aimed to provide a detailed description of the North Macedonian pig sector, to make comparisons with nearby Kosovo, and to identify areas with high-risk practices for targeted mitigation. Descriptive data were summarized. Results of the questionnaire were used to identify farm-level risk factors for disease introduction. These factors were used in the calculation of a biosecurity risk score. Kernel density estimation methods were used to generate density maps highlighting areas where the risk of disease introduction was particularly concentrated. Multiple correspondence analysis with hierarchical clustering on principal components was used to explore patterns in farm practices. Results show that farms were predominantly small-scale with high rates of turnover. Pig movement was predominantly local. The highest biosecurity risk scores were localized in the eastern regions of North Macedonia, concerningly the same regions with the highest frequency of wild boar sightings. Veterinarians were highly regarded, regularly utilized, and trusted sources of information. Practices that should be targeted for improvement include isolation of new pigs, and consistent application of basic sanitary practices including washing hands, use of disinfection mats, and separation of clean and dirty areas. This study provides the most complete description of the North Macedonian pig sector currently available. It also identifies regions and practices that could be targeted to mitigate the risk of disease incursion and spread. These results represent the first steps to quantify biosecurity gaps and high-risk behaviors in North Macedonia, providing baseline information to design risk-based, more cost-effective, prevention, surveillance, and control strategies.

Risk Analysis of the Transmission Route for the African Swine Fever Virus in Mainland China

African swine fever first broke out in mainland China in August 2018 and has caused a substantial loss to China’s pig industry. Numerous investigations have confirmed that trades and movements of infected pigs and pork products, feeding pigs with contaminative swills, employees, and vehicles carrying the virus are the main transmission routes of the African swine fever virus (ASFV) in mainland China. However, which transmission route is more risky and what is the specific transmission map are still not clear enough. In this study, we crawl the data related to pig farms and slaughterhouses from Baidu Map by writing the Python language and then construct the pig transport network. Following this, we establish an ASFV transmission model over the network based on probabilistic discrete-time Markov chains. Furthermore, we propose spatiotemporal backward detection and forward transmission algorithms in semi-directed weighted networks. Through the simulation and calculation, the risk of transmission routes is analyzed, and the results reveal that the infection risk for employees and vehicles with the virus is the highest, followed by contaminative swills, and the transportation of pigs and pork products is the lowest; the most likely transmission map is deduced, and it is found that ASFV spreads from northeast China to southwest China and then to west; in addition, the infection risk in each province at different times is assessed, which can provide effective suggestions for the prevention and control of ASFV.

African Swine Fever Virus (ASFV): Biology, Genomics and Genotypes Circulating in Sub-Saharan Africa.

African swine fever (ASF) is a highly infectious and fatal haemorrhagic disease of pigs that is caused by a complex DNA virus of the genus Asfivirus and Asfarviridae African suids family. The disease is among the most devastating pig diseases worldwide including Africa. Although the disease was first reported in the 19th century, it has continued to spread in Africa and other parts of the world. Globally, the rising demand for pork and concomitant increase in transboundary movements of pigs and pork products is likely to increase the risk of transmission and spread of ASF and pose a major challenge to the pig industry. Different genotypes of the ASF virus (ASFV) with varying virulence have been associated with different outbreaks in several countries in sub-Saharan Africa (SSA) and worldwide, and understanding genotype circulation will be important for ASF prevention and control strategies. ASFV genotypes unique to Africa have also been reported in SSA. This review briefly recounts the biology, genomics and genotyping of ASFV and provides an account of the different genotypes circulating in SSA. The review also highlights prevention, control and progress on vaccine development and identifies gaps in knowledge of ASFV genotype circulation in SSA that need to be addressed.

Spatial and temporal coevolution of N2 neuraminidase and H1 and H3 hemagglutinin genes of influenza A virus in US swine.

The neuraminidase (NA) and hemagglutinin (HA) are essential surface glycoproteins of influenza A virus (IAV). In this study, the evolution of subtype N2 NA paired with H1 and H3 subtype HA in swine was evaluated to understand if the genetic diversity of HA and NA were linked. Using time-scaled Bayesian phylodynamic analyses, the relationships of paired swine N2 with H1 or H3 from 2009 to 2018 were evaluated. These data demonstrated increased relative genetic diversity within the major N2 clades circulating in swine in the USA (N2.1998 between 2014 and 2017 and N2.2002 between 2010 and 2016). Preferential pairing was observed among specific NA and HA genetic clades. Gene reassortment between cocirculating influenza A strains resulted in novel pairings that persisted. The changes in genetic diversity in the NA gene were quantified using Bayesian phylodynamic analyses, and increases in diversity were observed subsequent to novel NA–HA reassortment events. The rate of evolution among NA–N2 clades and HA–H1 and HA–H3 clades were similar. Bayesian phylodynamic analyses demonstrated strong spatial patterns in N2 genetic diversity, but frequent interstate movement of rare N2 clades provided opportunity for reassortment and emergence of new N2–HA pairings. The frequent regional movement of pigs and their influenza viruses is an explanation for the documented patterns of reassortment and subsequent changes in gene diversity. The reassortment and evolution of NA and linked HA evolution may result in antigenic drift of both major surface glycoproteins, reducing vaccine efficacy, with subsequent impact on animal health.