Indirect Transmission Routes Research Articles

The multi-dimensional challenges of controlling respiratory virus transmission in indoor spaces: Insights from the linkage of a microscopic pedestrian simulation and SARS-CoV-2 transmission model.

SARS-CoV-2 transmission in indoor spaces, where most infection events occur, depends on the types and duration of human interactions, among others. Understanding how these human behaviours interface with virus characteristics to drive pathogen transmission and dictate the outcomes of non-pharmaceutical interventions is important for the informed and safe use of indoor spaces. To better understand these complex interactions, we developed the Pedestrian Dynamics-Virus Spread model (PeDViS), an individual-based model that combines pedestrian behaviour models with virus spread models incorporating direct and indirect transmission routes. We explored the relationships between virus exposure and the duration, distance, respiratory behaviour, and environment in which interactions between infected and uninfected individuals took place and compared this to benchmark 'at risk' interactions (1.5 metres for 15 minutes). When considering aerosol transmission, individuals adhering to distancing measures may be at risk due to the buildup of airborne virus in the environment when infected individuals spend prolonged time indoors. In our restaurant case, guests seated at tables near infected individuals were at limited risk of infection but could, particularly in poorly ventilated places, experience risks that surpass that of benchmark interactions. Combining interventions that target different transmission routes can aid in accumulating impact, for instance by combining ventilation with face masks. The impact of such combined interventions depends on the relative importance of transmission routes, which is hard to disentangle and highly context dependent. This uncertainty should be considered when assessing transmission risks upon different types of human interactions in indoor spaces. We illustrated the multi-dimensionality of indoor SARS-CoV-2 transmission that emerges from the interplay of human behaviour and the spread of respiratory viruses. A modelling strategy that incorporates this in risk assessments can help inform policy makers and citizens on the safe use of indoor spaces with varying inter-human interactions.

Automated Protocol for Monitoring Droplets and Fomites on Surfaces

During the COVID-19 pandemic, extensive efforts focused on developing a better understanding of indirect transmission routes, environmental monitoring of fomites, and suitable surveillance strategies, providing new perspectives to also face other communicable diseases. Rapid methods for monitoring environmental contamination are strongly needed to support risk assessment, epidemiological surveillance and prevent infections from spreading. We optimized and automatized a protocol based on fomite detection by qPCR, using a microbial-signature approach based on marker genes belonging to the microbiota of droplets or different biological fluids. The procedure was implemented by exploiting the available tools developed for SARS-CoV-2 tracing, such as flocked swab sampling, real-time PCR equipment and automatic extraction of nucleic acids. This approach allowed scaling up, simplifying, and speeding up the extraction step of environmental swabs, processing at least 48 samples within 45 min vs. 90 min for about 24 samples by manual protocols. A comparison of microflora data by Next-Generation Sequencing (NGS) strongly supports the effectiveness of this semiautomated extraction procedure, providing good quality DNA with comparable representation of species as shown by biodiversity indexes. Today, equipment for qPCR is widely available and relatively inexpensive; therefore this approach may represent a promising tool for hospital hygiene in surveilling fomites associated with SARS-CoV-2 or other pathogen’s transmission.

Analysis of a non-integer order compartmental model for cholera and COVID-19 incorporating human and environmental transmissions

Fractional differential operators have increasingly gained wider applications in epidemiological modelling due to their ability to capture memory effect in their definitions; an attribute which lacks in the concept of classical integer derivatives. In this paper, employing the Caputo fractional operator with singular kernel, the co-dynamical model for cholera and COVID-19 diseases is proposed and analyzed, incorporating both direct and indirect transmission routes for cholera. The necessary conditions for existence of the unique solution of the proposed model are studied. Using the results from fixed point theory, Ulam-Hyers stability analysis of the system is performed. The model is fitted to real data from Pakistan and the optimized order of the fractional derivative for which the system fits well to data is obtained. Other numerical assessments of the model are also executed. Phase portraits of the infected classes with different initial conditions and various order of the fractional derivative are obtained in the cases when the reproduction number and . It is observed that the trajectories for the infected compartments tend towards the infection-free steady state when and the endemic steady state when irrespective of the initial conditions and the order of the fractional derivative. Increment in the COVID-19 vaccine efficacy, keeping the vaccination rate fixed at , resulted in a decline in the COVID-19 disease. Also, increasing the COVID-19 vaccination rate, keeping the vaccine efficacy for COVID-19 fixed at , led to a decline in the COVID-19 associated reproduction number. The simulations also pointed out the impact of COVID-19 and cholera vaccinations, direct and indirect transmissions of cholera.

Dynamical analysis of an age-structured cholera transmission model on complex networks

Cholera is a water- and food-borne infectious disease caused by the bacterium Vibrio cholerae. In this paper, we present a novel modeling framework to investigate the effect of infection age on cholera transmission in a heterogeneous population. Our model is constructed on a system with infection age on complex networks, including both direct and indirect transmission routes and demographics. The basic reproduction number R0 is derived as the spectral radius of the next generation operator, and it is verified that R0 is a sharp threshold that determines whether cholera becomes extinct or not. Numerical simulations are performed to confirm the theoretical results. Furthermore, the sensitivity analysis of the basic reproduction number to the parameters suggests that the implementation of effective drug treatment for infected individuals and the timely removal of pathogens from contaminated water are beneficial to control the spread of cholera.

Within-herd transmission of Mycoplasma bovis infections after initial detection in dairy cows

Mycoplasma bovis outbreaks in cattle, including pathogen spread between age groups, are not well understood. Our objective was to estimate within-herd transmission across adult dairy cows, youngstock and calves. Results from 3 tests (PCR, ELISA, and culture) per cow and 2 tests (PCR and ELISA) per youngstock and calf were utilized in an age-stratified Susceptible-Infected-Removed/Recovered (SIR) model to estimate within-herd transmission parameters, pathways, and potential effects of farm management practices. A cohort of adult cows, youngstock and calves on 20 Dutch dairy farms with a clinical outbreak of M. bovis in adult cows were sampled, with collection of blood, conjunctival fluid and milk from cows, and blood and conjunctival fluid from calves and youngstock, 5 times over a timespan of 12 wk. Any individual with at least 1 positive laboratory test was considered M. bovis-positive. Transmission dynamics were modeled using an age-stratified SIR model featuring 3 age strata. Associations with farm management practices were explored using Fisher's Exact tests and Poisson regression. Estimated transmission parameters were highly variable among herds and cattle-age groups. Notably, transmission from cows to cows, youngstock, or to calves was associated with R-values ranging from 1.0 to 80 secondarily infected cows per herd, 1.2 to 38 secondarily infected youngstock per herd, and 0.1 to 91 secondarily infected calves per herd, respectively. In case of transmission from youngstock to youngstock, calves or to cows, R-values were 0.7 to 96 secondarily infected youngstock per herd, 1.1 to 76 secondarily infected calves per herd, and 0.1 to 107 secondarily infected cows per herd. For transmission from calves to calves, youngstock or to cows, R-values were 0.5 to 60 secondarily infected calves per herd, 1.1 to 41 secondarily infected youngstock per herd, and 0.1 to 47 secondarily infected cows per herd. Among on-farm transmission pathways, cow-to-youngstock, cow-to-calf and cow-to-cow were identified as most significant contributors, with calf-to-calf and calf-to-youngstock also having noteworthy roles. Youngstock-to-youngstock was also implicated, albeit to a lesser extent. Whereas the primary focus was a clinical outbreak of M. bovis among adult dairy cows, it was evident that transmission extended to calves and youngstock, contributing to overall spread. Factors influencing transmission and specific transmission pathways were associated with internal biosecurity (separate caretakers for various age groups, number of people involved), external biosecurity (contractors, external employees), as well as indirect transmission routes (number of feed and water stations).

The effect of landscape, transmission mode and social behavior on disease transmission: Simulating the transmission of chronic wasting disease in white-tailed deer (Odocoileus virginianus) populations using a spatially explicit agent-based model

We developed a spatially explicit agent-based model (ABM), DeerLandscapeDisease (DLD), to investigate the effects of landscape structure, disease transmission, and management alternatives on dynamics of chronic wasting disease (CWD) in white-tailed deer (Odocoileus virginianus). We fitted biased random walk models to data from GPS-collared deer to simulate movements of individual deer and deer groups in an agricultural landscape with fragmented forest patches and a forest-dominated landscape. We estimated behavioral and demographic parameters from field data and published literature of deer ecology. We considered both direct and indirect transmission routes and assumed that bioavailability of infectious pathogens deposited in the environment decreased exponentially over time. We tuned transmission parameters to match observed trajectories of CWD prevalence in Wisconsin, and assumed that infection probability during an encounter was equal for all age classes. Thus, infection prevalence varied with sex- and age-specific behavior.DLD simulations demonstrated significant effects of landscape structure, social behavior and transmission mode on temporal changes in prevalence. Prevalence rose faster and reached higher levels in fragmented forest landscapes due to aggregation of deer within small forest patches. Furthermore, simulation results suggested that CWD might be driven through a mix of frequency- and density-dependent processes, potentially facilitating coexistence of CWD and deer populations. These results demonstrate the utility of ABMs and the importance of including spatial and behavioral heterogeneity when modeling disease transmission.

Assessing the impact of adherence to Non-pharmaceutical interventions and indirect transmission on the dynamics of COVID-19: a mathematical modelling study.

Adherence to public health policies such as the non-pharmaceutical interventions implemented against COVID-19 plays a major role in reducing infections and controlling the spread of the diseases. In addition, understanding the transmission dynamics of the disease is also important in order to make and implement efficient public health policies. In this paper, we developed an SEIR-type compartmental model to assess the impact of adherence to COVID-19 non-pharmaceutical interventions and indirect transmission on the dynamics of the disease. Our model considers both direct and indirect transmission routes and stratifies the population into two groups: those that adhere to COVID-19 non-pharmaceutical interventions (NPIs) and those that do not adhere to the NPIs. We compute the control reproduction number and the final epidemic size relation for our model and study the effect of different parameters of the model on these quantities. Our results show that there is a significant benefit in adhering to the COVID-19 NPIs.

Indirect exposure to novel coronavirus (SARS-CoV-2): an overview of current knowledge

This review chronicles the indirect transmission method which seems to be overlooked by most people and makes attempts to document the various transmission ways with a hope that such information may strengthen the knowledge base of researchers towards methods of eradicating the pandemic. Current knowledge of transmission and exposure of SARS-CoV-2 has been explained. Various researchers have put forward different ways of exposure and transmission. Literature does not reveal whether the indirect transmission route is the dominant one. However, total lockdown could be a veritable means to reduce both direct and indirect transmission routes. In many countries where the indirect transmission has been reduced, the scourge of the virus is less. The work creates awareness on the need to watch out for those routes of transmissions that may not be popular and suggested vital knowledge gaps that need to fill.

Illustration of Different Disease Transmission Routes in a Pig Trade Network by Monopartite and Bipartite Representation

Simple SummaryBesides direct animal movements between farms; indirect transmission routes of pathogens can have an immense impact on network structure and disease spread in animal trade networks. This study integrated these indirect transmission routes between farms via transport companies or feed supply as bipartite networks; which were compared to the monopartite animal movements network representing the direct transmission route. Both bipartite networks were projected on farm level to enable a comparison to the monopartite network. The number of edges increased immensely from the monopartite animal movements network to both projected networks. Thus, farms can be highly connected over indirect connections, although they are not directly trading animals. The ranking of the animals according to their centrality parameters, indicating their importance for the network, showed moderate correlations only between the animal movements and the transportation network. The epidemiological models based on the different network representations revealed significantly more infected farms for the networks including indirect transmission routes compared to the direct animal movements. Indirect transmission routes had an immense impact on the outcome of centrality parameters, as well as on the spreading process within the network. This knowledge is needed to understand disease spread and to establish reliable prevention and control measurements.Besides the direct transport of animals, also indirect transmission routes, e.g., contact via contaminated vehicles, have to be considered. In this study, the transmission routes of a German pig trade network were illustrated as a monopartite animal movements network and two bipartite networks including information of the transport company and the feed producer which were projected on farm level (n = 866) to enable a comparison. The networks were investigated with the help of network analysis and formed the basis for epidemiological models to evaluate the impact of different transmission routes on network structure as well as on potential epidemic sizes. The number of edges increased immensely from the monopartite animal movements network to both projected networks. The median centrality parameters revealed clear differences between the three representations. Furthermore, moderate correlation coefficients ranging from 0.55 to 0.68 between the centrality values of the animal movements network and the projected transportation network were obtained. The epidemiological models revealed significantly more infected farms for both projected networks (70% to 100%) compared to the animal movements network (1%). The inclusion of indirect transmission routes had an immense impact on the outcome of centrality parameters as well as on the results of the epidemiological models.

Evaluation of direct and indirect transmission of fungal spores in ants

Parasite transmission plays a central role in disease dynamics, but little is known about the extent to which direct and indirect transmission contributes to disease dynamics in group-living animals. Quantifying transmission by contact or exposure is challenging, as direct measurements of pathogen transmission are often impractical and individual behaviour is largely unknown. Here, we attempt to tackle these twin problems through the use of a generalist entomopathogenic fungus Metarhizium robertsii to study direct and indirect transmission in the black carpenter ant Camponotus pennsylvanicus. We provide evidence that large quantities of fungal conidia (spores) can be acquired over time on the ant’s cuticle and significant amounts are shed into the environment, allowing indirect transmission. Unexposed ants in the nest can be infected either through direct (i.e. social contacts) or indirect (i.e. acquisition from the environment) transmission, potentially leading to the same mortality as if all individuals of a nest would have been directly exposed to the pathogen. Our findings highlight the importance of indirect transmission routes in a species of social living organisms.

Epidemiological analysis of the 2015–2017 African swine fever outbreaks in Estonia

African swine fever (ASF) was first detected in the Estonian wild boar population in September 2014, while the first domestic pig farm was affected in July 2015. In the present study, we aimed to analyse, retrospectively, the epidemiology of the disease in all 26 outbreaks in domestic pig herds that occurred in Estonia during the period 2015–2017. Formal interviews were conducted to estimate the high-risk period for every farm, and to identify the possible origin of the ASF virus and the mode of virus introduction. Furthermore, the clinical manifestation of the disease as well as the course of the disease within the farm were investigated. Survival analysis was used to calculate herd incidence and to estimate outbreak risk. A hierarchical Bayesian space–time model was used to analyse the associations between outbreaks and ASF occurrence in wild boar. The spatial and temporal distribution of outbreaks was analysed to characterise the ASF epidemic in the Estonian domestic pig population from 2015 to 2017.The estimated high-risk period varied from seven to 20 days with a median of 11 days. On most of the affected farms, the first clinical signs were mild and not specific to ASF despite the high virulence of the circulating virus. Morbidity and mortality were often limited to a single pen or unit of the farm. The highest mortality (29.7%) was seen on backyard farms with 1–10 pigs and the lowest (0.7%) on large commercial farms (>1000 pigs). The spread of the virus within affected farms has been slow and the contagiousness of the virus has been relatively low. Farms of all sizes and types have been at risk, including large commercial farms operating at a high biosecurity level. In none of the affected farms could the specific route of introduction be verified. However, the findings suggested that virus introduction occurred via indirect transmission routes due to insufficient biosecurity. The total herd incidence of outbreaks was similar across all three years, being 2.4% in 2015 and 2016, and 2.0% in 2017. All outbreaks occurred from June to September, during the warmest period of the year. The results suggest that the increase in ASF cases in local wild boar populations is the main risk factor leading to the infection of farms; 88% of outbreaks occurred in areas where ASF virus was detected in wild boar prior to the outbreak, within a radius of 15 km from the outbreak farm.

The Potential Role of Synanthropic Rodents and Flies in the Transmission of Enterocytozoon bieneusi on a Dairy Cattle farm in China.

Enterocytozoon bieneusi causes microsporidiosis, a condition with complex epidemiology involving both direct and indirect transmission routes. To assess the potential role of synanthropic rodents and flies in the transmission of this pathogen, a total of 277 cattle fecal samples, 199 synanthropic rodents, and 50 batches of 20 flies were collected from a cattle farm. These samples were screened for the presence of E.bieneusi by PCR and sequencing of the internal transcribed spacer (ITS) region of the rRNA gene. The positive rates of cattle, synanthropic rodents, and flies were 11.9% (33/277), 4.0% (8/199) and 12.0% (6/50), respectively. Nineteen genotypes were identified, including 11 known genotypes (BEB6, I, COS-I, EbpC, D, J, CHS5, CHG1 to CHG3 and CHG14) and eight novel genotypes (named CHC9 to CHC16). The dominant genotype detected in the present study, BEB6, was found in all three categories of hosts. Moreover, human pathogenic genotypes D and EbpC were also observed in both synanthropic rodents and flies. These results demonstrate that synanthropic rodents and flies may act as biological disseminator or mechanical vector in the transmission of microsporidiosis to humans. Efforts should be made to minimize threats from these commensal animals to public health.

Review of transmission routes of 24 infectious diseases preventable by biosecurity measures and comparison of the implementation of these measures in pig herds in six European countries.

This study aimed to review the transmission routes of important infectious pig diseases and to translate these into biosecurity measures preventing or reducing the transmission between and within pig herds. Furthermore, it aimed to identify the level of implementation of these measures in different European countries and discuss the observed variations to identify potentials for improvement. First, a literature review was performed to show which direct and indirect transmission routes of 24 infectious pig diseases can be prevented through different biosecurity measures. Second, a quantitative analysis was performed using the Biocheck.UGent™, a risk-based scoring system to evaluate biosecurity in pig herds, to obtain an insight into the implementation of these biosecurity measures. The database contained farm-specific biosecurity data from 574 pig farms in Belgium, Denmark, France, Germany, the Netherlands and Sweden, entered between January 2014 and January 2016. Third, a qualitative analysis based on a review of literature and other relevant information resources was performed for every subcategory of internal and external biosecurity in the Biocheck.UGent™ questionnaire. The quantitative analysis indicated that at the level of internal, external and overall biosecurity, Denmark had a significantly distinct profile with higher external biosecurity scores and less variation than the rest of the countries. This is likely due to a widely used specific pathogen-free (SPF) system with extensive focus on biosecurity since 1971 in Denmark. However, the observed pattern may also be attributed to differences in data collection methods. The qualitative analysis identified differences in applied policies, legislation, disease status, pig farm density, farming culture and habits between countries that can be used for shaping country-specific biosecurity advice to attain improved prevention and control of important pig diseases in European pig farms.

Think globally, act locally: Phylodynamic reconstruction of infectious bronchitis virus (IBV) QX genotype (GI-19 lineage) reveals different population dynamics and spreading patterns when evaluated on different epidemiological scales.

Infectious bronchitis virus (IBV) represents one of the poultry industry major threats, particularly in high density producing countries. The emergence and spread of new IBV genotypes have frustrated the various disease control efforts implemented over time. Despite that, few comprehensive and large scale studies have been performed to understand the international and local spreading dynamics of this virus. In the present work, these phenomena were evaluated by implementing a Bayesian phylodynamic approach to reconstruct the epidemiological patterns and population history of the QX genotype (currently renamed GI-19 lineage), the most relevant IBV lineage of the Old-World. Our analysis, based on 807 partial S1 sequences of strains collected from 18 countries between 1993 and 2015, demonstrates that this genotype originated in China well before its first identification. After a prolonged local circulation, it started spreading to other European, Asian and Middle East countries in successive waves, which were mirrored by concomitant fluctuations in viral population size. Interestingly, the within-Europe spread was characterized by a higher estimated migration rate compared with the inter-continental one, potentially reflecting the closer geographic and economic relationships among these countries. Nevertheless, the colonization of new states by the GI-19 lineage appeared to occur mostly by single introduction events in both intra and inter-continental spread, likely because of epidemiological factor and health policy combination which seems to prevent the frequent introduction and mixing of different strains. On the other hand, the within Italy QX circulation reconstruction showed a much more intricate connection network among different locations, evidencing the difficulty in controlling IBV spread especially in highly densely poultry populated areas. The presence of several well supported epidemiological links among distantly related Italian regions testifies that animal transportation and indirect transmission routes rather than local airborne diffusion contribute to the QX success and persistence at local scale. Globally, the spreading dynamics and evolution of the QX genotype were reconstructed from its very origin to nowadays, demonstrating the need of more effective direct control measures, particularly within each country. Unfortunately, the incompleteness of available molecular epidemiology data represents an insurmountable limit which leaves many questions currently unsolved, thus highlighting the compulsoriness of a structured monitoring and data sharing system implementation.

Using expert judgments to improve chronic wasting disease risk management in Canada

ABSTARCTChronic wasting disease (CWD) is a neurodegenerative, protein misfolding disease affecting cervids in North America in epidemic proportions. While the existence of CWD has been known for more than 40 years, risk management efforts to date have not been able to curtail the spread of this condition. An expert elicitation exercise was carried out in May 2011 to obtain the views of international experts on both the etiology of CWD and possible CWD risk management strategies. This study presents the results of the following three components of the elicitation exercise: (1) expert views of the most likely scenarios for the evolution of the CWD among cervid populations in Canada, (2) ranking analyses of the importance of direct and indirect transmission routes, and (3) rating analyses of CWD control measures in farmed and wild cervids. The implications of these findings for the development of CWD risk management strategies are described in a Canadian context.

Testing of the Adhesion of Herpes Simplex Virus on Textile Substrates and Its Inactivation by Household Laundry Processes

Viral infections like Herpes simplex increasingly pose a serious threat to European health care systems and welfare of the population. Indirect transmission routes of infections via inanimate surfaces are often underestimated. In this study, we investigated the adhesion and persistence of Herpes simplex virus on cotton fabrics as well as its inactivation by domestic laundry. Virus adhesion to textile fibers was distinct, because viral DNA was detectable on fabrics for at least 48 hours after contamination as well as after home laundry. Particles remained infectious for several hours at room temperature and partially for 48 hours at 2℃ - 8℃. Nevertheless, domestic laundry was able to inactivate virus particles given that detergents were adequately used. This confirmed that standard household laundry processes, as established in Europe, are a suitable tool to reduce infectious Herpes virus particles from textiles, thereby supporting the prevention of infections circulating in the household and community.

Fabric-skin models to assess infection transfer for impetigo contagiosa in a kindergarten scenario.

Children in community bodies like kindergartens are predisposed to suffer from impetigo. To consider important measures for infection prevention, direct and indirect transmission routes of pathogens must be revealed. Therefore, we studied the role of skin and fabrics in the spread of the impetigo pathogen Staphylococcus aureus and the strain Streptococcus equi (surrogate to Streptococcus pyogenes) in order to assess infection transfer in realistic scenarios. The transmission of test strains was studied with standardized fabric-skin models using a technical artificial skin and fabrics of different fiber types commonly occurring in German kindergartens. In synthetic pus, both test strains persisted on artificial skin and fabrics for at least 4 h. Friction enhanced transfer, depending on the fiber type or fabric construction. In a skin-to-skin setup, the total transfer was higher than via fabrics and no decrease in the transmission rates from donor to recipients could be observed after successive direct skin contacts. Children in kindergartens may be at risk of transmission for impetigo pathogens, especially via direct skin contact, but also by the joint use of fabrics, like towels or handicraft materials. Fabric-skin models used in this study enable further insight into the transmission factors for skin infections on the basis of a practical approach.

Stochastic spatio-temporal modelling of African swine fever spread in the European Union during the high risk period

African swine fever (ASF) is a notifiable viral pig disease with high mortality and serious socio-economic consequences. Since ASF emerged in Georgia in 2007 the disease has spread to several neighbouring countries and cases have been detected in areas bordering the European Union (EU). It is uncertain how fast the virus would be able to spread within the unrestricted European trading area if it were introduced into the EU. This project therefore aimed to develop a model for the spread of ASF within and between the 27 Member States (MS) of the EU during the high risk period (HRP) and to identify MS during that period would most likely contribute to ASF spread (“super-spreaders”) or MS that would most likely receive cases from other MS (“super-receivers”).A stochastic spatio-temporal state-transition model using simulated individual farm records was developed to assess silent ASF virus spread during different predefined HRPs of 10–60 days duration. Infection was seeded into farms of different pig production types in each of the 27 MS. Direct pig-to-pig transmission and indirect transmission routes (pig transport lorries and professional contacts) were considered the main pathways during the early stages of an epidemic. The model was parameterised using data collated from EUROSTAT, TRACES, a questionnaire sent to MS, and the scientific literature.Model outputs showed that virus circulation was generally limited to 1–2 infected premises per outbreak (95% IQR: 1–4; maximum: 10) with large breeder farms as index case resulting in most infected premises. Seven MS caused between-MS spread due to intra-Community trade during the first 10 days after seeding infection. For a HRP of 60 days from virus introduction, movements of infected pigs will originate at least once from 16 MS, with 6 MS spreading ASF in more than 10% of iterations. Two thirds of all intra-Community spread was linked to six trade links only. Denmark, the Netherlands, Lithuania and Latvia were identified as “super-spreaders”; Germany and Poland as “super-receivers”. In the sensitivity analysis, the total number of premises per country involved in intra-Community trade was found to be a key determinant for the between-MS spread dynamic and needs to be further investigated. It was concluded that spread during the HRP is likely to be limited, especially if the HRP is short. This emphasises the importance of having good disease awareness in all MS for early disease detection.