Contact structures in the poultry industry in Great Britain: exploring transmission routes for a potential avian influenza virus epidemic

Optimizing sample collection methods for detection of respiratory viruses in poultry housing environments

Viral respiratory diseases, such as avian influenza, Newcastle disease, infectious bronchitis, and infectious laryngotracheitis, have considerable negative economic implications for poultry. Ensuring the virus-free status of a premises by environmental sampling after cleaning and disinfection is essential for lifting a quarantine and/or safely restocking the premises following an outbreak. The objectives of this study were to identify optimal sample collection devices and to determine the locations in poultry housing which are best for poultry respiratory virus sample collection. Chickens exposed to infectious bronchitis virus, which was used as a representative virus for enveloped poultry respiratory viruses, were housed in floor-pens in either a curtain-sided wood framed house or a cement block house. Foam swabs, cellulose sponges, polyester swabs, dry cotton gauze and pre-moistened cotton gauze were evaluated for comparative efficiency in recovering viral RNA. Cotton gauze pre-moistened with the viral transport media had the highest sensitivity among the devices (wood-framed house: 78% positive, geometric mean titer [GMT] of 2.6 log₁₀ 50% egg infectious doses [EID₅₀ ] equivalents/ml; cement-block houses: 55% positive, GMT of 1.7 log₁₀ EID₅₀ equivalents/ml). Targeting virus deposition sites is also crucial for efficient virus elimination procedures and subsequent testing, therefore 10 locations within the houses were compared for virus detection. In both housing types the highest viral RNA loads were recovered from the top of drinker lines within the pen. Places the chickens could contact directly (e.g., feeder rim) or were contacted by caretaker feet (hallway floor) also yielded higher levels of viral RNA more consistently. These results will facilitate the establishment of efficient environmental sampling procedures for respiratory viruses of poultry. This article is protected by copyright. All rights reserved.

Livestock Network Analysis for Rhodesiense Human African Trypanosomiasis Control in Uganda

Background: Infected cattle sourced from districts with established foci for Trypanosoma brucei rhodesiense human African trypanosomiasis (rHAT) migrating to previously unaffected districts, have resulted in a significant expansion of the disease in Uganda. This study explores livestock movement data to describe cattle trade network topology and assess the effects of disease control interventions on the transmission of rHAT infectiousness. Methods: Network analysis was used to generate a cattle trade network with livestock data which was collected from cattle traders (n = 197) and validated using random graph methods. Additionally, the cattle trade network was combined with a susceptible, infected, recovered (SIR) compartmental model to simulate spread of rHAT (R _o 1.287), hence regarded as "slow" pathogen, and evaluate the effects of disease interventions. Results: The cattle trade network exhibited a low clustering coefficient (0.5) with most cattle markets being weakly connected and a few being highly connected. Also, analysis of the cattle movement data revealed a core group comprising of cattle markets from both eastern (rHAT endemic) and northwest regions (rHAT unaffected area). Presence of a core group may result in rHAT spread to unaffected districts and occurrence of super spreader cattle market or markets in case of an outbreak. The key cattle markets that may be targeted for routine rHAT surveillance and control included Namutumba, Soroti, and Molo, all of which were in southeast Uganda. Using effective trypanosomiasis such as integrated cattle injection with trypanocides and spraying can sufficiently slow the spread of rHAT in the network. Conclusion: Cattle trade network analysis indicated a pathway along which T. b. rhodesiense could spread northward from eastern Uganda. Targeted T. b. rhodesiense surveillance and control in eastern Uganda, through enhanced public-private partnerships, would serve to limit its spread.

Role of Live-Duck Movement Networks in Transmission of Avian Influenza, France, 2016-2017

The relative roles that movement and proximity networks play in the spread of highly pathogenic avian influenza (HPAI) viruses are often unknown during an epidemic, preventing effective control. We used network analysis to explore the devastating epidemic of HPAI A(H5N8) among poultry, in particular ducks, in France during 2016–2017 and to estimate the likely contribution of live-duck movements. Approximately 0.2% of live-duck movements could have been responsible for between-farm transmission events, mostly early during the epidemic. Results also suggest a transmission risk of 35.5% when an infected holding moves flocks to another holding within 14 days before detection. Finally, we found that densely connected groups of holdings with sparse connections between groups overlapped farmer organizations, which represents important knowledge for surveillance design. This study highlights the importance of movement bans in zones affected by HPAI and of understanding transmission routes to develop appropriate HPAI control strategies.

Identification of optimal sample collection devices and sampling locations for the detection of environmental viral contamination in wire poultry cages

Environmental testing of poultry premises after an outbreak of an infectious disease like avian influenza (AI) or Newcastle disease is essential to promptly verify virus‐free status and subsequently return to normal operations. In an attempt to establish an optimized sampling protocol, a laboratory study simulating an AI virus‐contaminated poultry house with wire layer cages was conducted. Three sample collection devices, pre‐moistened cotton gauze, dry cotton gauze and a foam swab, were evaluated with each of four sample locations within a cage and when sampling all four locations with one device. Virus was detected with quantitative real‐time RT‐PCR utilizing a standard curve of a quantified homologous isolate of AI virus to determine titre equivalents of virus. The pre‐moistened gauze detected the most virus RNA (100% positive, geometric mean titre [GMT): 3.2 log₁₀ 50% embryo infectious doses [EID₅₀] equivalents per 25 cm²) in all four sample locations compared to dry gauze (93% positive, GMT: 2.6 EID₅₀ equivalents per 25 cm²) and foam swabs (95% positive, GMT: 2.8 log10 EID₅₀ equivalents per 25 cm²). The highest viral RNA loads were observed from the cage floor, and when the four locations were sampled with the same device. Overall, the pre‐moistened gauze performed the best, and sampling multiple locations within a cage with the same device would likely optimize detection of residual virus.

Knowledge and remaining gaps on the role of animal and human movements in the poultry production and trade networks in the global spread of avian influenza viruses - A scoping review

Poultry production has significantly increased worldwide, along with the number of avian influenza (AI) outbreaks and the potential threat for human pandemic emergence. The role of wild bird movements in this global spread has been extensively studied while the role of animal, human and fomite movement within commercial poultry production and trade networks remains poorly understood. The aim of this work is to better understand these roles in relation to the different routes of AI spread. A scoping literature review was conducted according to the PRISMA guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) using a search algorithm combining twelve domains linked to AI spread and animal/human movements within poultry production and trade networks. Only 28 out of 3,978 articles retrieved dealt especially with the role of animal, human and fomite movements in AI spread within the international trade network (4 articles), the national trade network (8 articles) and the production network (16 articles). While the role of animal movements in AI spread within national trade networks has been largely identified, human and fomite movements have been considered more at risk for AI spread within national production networks. However, the role of these movements has never been demonstrated with field data, and production networks have only been partially studied and never at international level. The complexity of poultry production networks and the limited access to production and trade data are important barriers to this knowledge. There is a need to study the role of animal and human movements within poultry production and trade networks in the global spread of AI in partnership with both public and private actors to fill this gap.

Pig trade networks through live pig markets in Guangdong Province, China

This study used social network analysis to investigate the indirect contact network between counties through the movement of live pigs through four wholesale live pig markets in Guangdong Province, China. All 14,118 trade records for January and June 2016 were collected from the markets and the patterns of pig trade in these markets analysed. Maps were developed to show the movement pathways. Evaluating the network between source counties was the primary objective of this study. A 1‐mode network was developed. Characteristics of the trading network were explored, and the degree, betweenness and closeness were calculated for each source county. Models were developed to compare the impacts of different disease control strategies on the potential magnitude of an epidemic spreading through this network. The results show that pigs from 151 counties were delivered to the four wholesale live pig markets in January and/or June 2016. More batches (truckloads of pigs sourced from one or more piggeries) were traded in these markets in January (8,001) than in June 2016 (6,117). The pigs were predominantly sourced from counties inside Guangdong Province (90%), along with counties in Hunan, Guangxi, Jiangxi, Fujian and Henan provinces. The major source counties (46 in total) contributed 94% of the total batches during the two‐month study period. Pigs were sourced from piggeries located 10 to 1,417 km from the markets. The distribution of the nodes' degrees in both January and June indicates a free‐scale network property, and the network in January had a higher clustering coefficient (0.54 vs. 0.39) and a shorter average pathway length (1.91 vs. 2.06) than that in June. The most connected counties of the network were in the central, northern and western regions of Guangdong Province. Compared with randomly removing counties from the network, eliminating counties with higher betweenness, degree or closeness resulted in a greater reduction of the magnitude of a potential epidemic. The findings of this study can be used to inform targeted control interventions for disease spread through this live pig market trade network in south China.

Virucidal Efficacy of a Quaternary Ammonium Compound with Food Additive-Grade Calcium Hydroxide Toward Avian Influenza Virus and Newcastle Disease Virus on Abiotic Carriers

The virucidal efficacies of a 0.2% food additive-grade calcium hydroxide [FdCa(OH)₂] solution, a quaternary ammonium compound (QAC) diluted at 1:500 (QACx500), and their mixture [Mix500; FdCa(OH)₂ powder added at a final concentration of 0.2% to QACx500] were investigated as fomites for avian influenza virus (AIV) and Newcastle disease virus (NDV) on abiotic carriers (steel, rubber, and plastic) at two different temperatures (room temperature [RT; 25 ± 2 C] and 2 C). These viruses were seeded on coupons (5 cm×5 cm) of rubber, steel, or plastic with 5% fetal bovine serum. After complete drying, the coupons were covered with the test solutions at RT or 2 C. After fixed incubation periods, viruses were recovered from the coupons and titrated. At RT, Mix500 required a short time (3 min) to inactivate AIV and NDV to effective levels (≥3 log virus reduction) on rubber, steel, and plastic carriers compared with QAC or FdCa(OH)_2. At low temperature, QACx500 inactivated AIV on steel and plastic carriers to effective levels within 60 min, whereas Mix500 did so within 10 min. QACx500 and FdCa(OH)₂ solutions could inactivate NDV on steel and plastic carriers within 20 and 10 min, respectively, and Mix500 could do so within 3 min. Viruses on the carriers required longer incubation periods for inactivation at 2 C than at 25 C. These results demonstrate desirable synergistic virucidal effects of Mix500 for important poultry viruses on abiotic carriers, while indicating high applicability within poultry farming.

When resolution does matter: Modelling indirect contacts in dairy farms at different levels of detail

Animal exchanges are considered the major pathway for between-farm transmission of many livestock infectious diseases. Yet, vehicles and operators visiting several farms during routine activities can also contribute to disease spread. Indeed, if contaminated, they can act as mechanical vectors of fomites, generating indirect contacts between visited farms. While data on animal exchanges is often available in national databases, information about the daily itineraries of trucks and operators is rare because difficult to obtain. Thus, some unavoidable approximations have been frequently introduced in the description of indirect contacts in epidemic models. Here, we showed that the level of detail in such description can significantly affect the predictions on disease dynamics. Our analyses focused on the potential spread of a disease in a dairy farm system subject of a comprehensive data collection campaign on calf transportations. We developed two temporal multilayer networks to model between-farm contacts generated by either animal exchanges (direct contacts) and connections operated by trucks moving calves (indirect contacts). The complete model used the full knowledge of the daily trucks' itineraries, while the partial informed one used only a subset of such available information. To account for various conditions of pathogen survival ability and effectiveness of cleaning operations, we performed a sensitivity analysis on trucks' contamination period. An accurate description of indirect contacts was crucial both to correctly predict the final size of epidemics and to identify the seed farms responsible for generating the most severe outbreaks. The importance of detailed information emerged even more clearly in the case of short contamination periods. Our conclusions could be extended to between-farm contacts generated by other vehicles and operators. Overcoming these information gaps would be decisive for a deeper understanding of epidemic spread in livestock and to develop effective control plans.

Charles KM, Bonney PJ, Malladi S, Culhane M, Goldsmith TJ, Halvorson DA, Cardona CJ. Analysis of geographic location and pathways for influenza A virus infection of commercial upland game bird and conventional poultry farms in the United States of America

BACKGROUND

Avian influenza (AI) is an infectious viral disease that affects several species and has zoonotic potential. Due to its associated health and economic repercussions, minimizing AI outbreaks is important. However, most control measures are generic and mostly target pathways important for the conventional poultry farms producing chickens, turkeys, and eggs and may not target other pathways that may be specific to the upland game bird sector. The goal of this study is to provide evidence to support the development of novel strategies for sector-specific AI control by comparing and contrasting practices and potential pathways for spread in upland game bird farms with those for conventional poultry farms in the United States. Farm practices and processes, seasonality of activities, geographic location and inter-farm distance were analyzed across the sectors. All the identified differences were framed and discussed in the context of their associated pathways for virus introduction into the farm and subsequent between-farm spread.

RESULTS

Differences stemming from production systems and seasonality, inter-farm distance and farm densities were evident and these could influence both fomite-mediated and local-area spread risks. Upland game bird farms operate under a single, independent owner rather than being contracted with or owned by a company with other farms as is the case with conventional poultry. The seasonal marketing of upland game birds, largely driven by hunting seasons, implies that movements are seasonal and customer-vendor dynamics vary between industry groups. Farm location analysis revealed that, on average, an upland game bird premises was 15.42 km away from the nearest neighboring premises with birds compared to 3.74 km for turkey premises. Compared to turkey premises, the average poultry farm density in a radius of 10 km of an upland game bird premises was less than a half, and turkey premises were 3.8 times (43.5% compared with 11.5%) more likely to fall within a control area during the 2015 Minnesota outbreak.

CONCLUSIONS

We conclude that the existing differences in the seasonality of production, isolated geographic location and epidemiological seclusion of farms influence AI spread dynamics and therefore disease control measures should be informed by these and other factors to achieve success.

Social network analysis for poultry HPAI transmission

In this survey study, the networks among poultry farms and related poultry enterprises in two counties in China (Feixi County in Anhui Province and Beizhen city in Liaoning Province) were analysed and evaluated focusing on the connectivity of contacts, movements, and potential pathogen transmission. The Feixi County poultry production network exhibited greater connectivity, which incorporated approximately 94% of the farms interviewed in a major component (a set of connected farms not linked with each other), mainly due to linkages of backyard farms through local produce stores and individual agents, whilst the Beizhen City network was more fragmented owing to independent in-house operations (from breed, raise, to slaughter and process) of a few large companies, with multiple smaller components. A range of factors influencing the contacts/movements among farms (act as bridges) were identified in this study. Ability to predict the pathway with the network characteristics on the basis of the factors, such as entity type and geographic location, is useful for developing risk-based approaches for disease prevention, surveillance, early detection, and effective controlling.

Exploring contacts facilitating transmission of influenza A(H5N1) virus between poultry farms in West Java, Indonesia: A major role for backyard farms?

Highly pathogenic avian influenza virus (HPAIV) H5N1 has been reported in Asia, including Indonesia since 2003. Although several risk factors related to the HPAIV outbreaks in poultry in Indonesia have been identified, little is known of the contact structure of farms of different poultry production types (backyard chickens, broilers, layers, and ducks). This study aims to quantify the contact rates associated with the movement of people, and movements of live birds and products and equipment that affect the risk of HPAIV H5N1 transmission between poultry farms in Indonesia. On 124 poultry farms in 6 districts in West Java, logbooks were distributed to record the movements of farmers/staff and visitors and their poultry contacts. Most movements in backyard chicken, commercial native chicken, broiler and duck farms were visits to and from other poultry farms, whilst in layer farms visits to and from poultry companies, visits to egg collection houses and visit from other poultry farms were most frequent. Over 75% of persons visiting backyard chicken and duck farms had previously visited other poultry farms on the same day. Visitors of backyard chicken farms had the highest average contact rate, either direct contact with poultry on other farms before the visits (1.35 contact/day) or contact during their visits in the farms (10.03 contact/day). These results suggest that backyard chicken farms are most at risk for transmission of HPAIV compared to farms of the other poultry production types. Since visits of farm-to-farm were high, backyard farms could also a potential source for HPAIV transmission to commercial poultry farms.

Modelling farm-to-farm disease transmission through personnel movements: from visits to contacts, and back

Infectious diseases in livestock can be transmitted through fomites: objects able to convey infectious agents. Between-farm spread of infections through fomites is mostly due to indirect contacts generated by on-farm visits of personnel that can carry pathogens on their clothes, equipment, or vehicles. However, data on farm visitors are often difficult to obtain because of the heterogeneity of their nature and privacy issues. Thus, models simulating disease spread between farms usually rely on strong assumptions about the contribution of indirect contacts on infection spread. By using data on veterinarian on-farm visits in a dairy farm system, we built a simple simulation model to assess the role of indirect contacts on epidemic dynamics compared to cattle movements (i.e. direct contacts). We showed that including in the simulation model only specific subsets of the information available on indirect contacts could lead to outputs widely different from those obtained with the full-information model. Then, we provided a simple preferential attachment algorithm based on the probability to observe consecutive on-farm visits from the same operator that allows overcoming the information gaps. Our results suggest the importance of detailed data and a deeper understanding of visit dynamics for the prevention and control of livestock diseases.

The use of social network analysis to examine the transmission of Salmonella spp. within a vertically integrated broiler enterprise

To better understand factors influencing infectious agent dispersal within a livestock population information is needed on the nature and frequency of contacts between farm enterprises. This study uses social network analysis to describe the contact network within a vertically integrated broiler poultry enterprise to identify the potential horizontal and vertical transmission pathways for Salmonella spp. Nodes (farms, sheds, production facilities) were identified and the daily movement of commodities (eggs, birds, feed, litter) and people between nodes were extracted from routinely kept farm records. Three time periods were examined in detail, 1- and 8- and 17-weeks of the production cycle and contact networks were described for all movements, and by commodity and production type. All nodes were linked by at least one movement during the study period but network density was low indicating that all potential pathways between nodes did not exist. Salmonella spp. transmission via vertical or horizontal pathways can only occur along directed pathways when those pathways are present. Only two locations (breeder or feed nodes) were identified where the transmission of a single Salmonella spp. clone could theoretically percolate through the network to the broiler or processing nodes. Only the feed transmission pathway directly connected all parts of the network.

Exploring pig trade patterns to inform the design of risk-based disease surveillance and control strategies

An understanding of the patterns of animal contact networks provides essential information for the design of risk-based animal disease surveillance and control strategies. This study characterises pig movements throughout England and Wales between 2009 and 2013 with a view to characterising spatial and temporal patterns, network topology and trade communities. Data were extracted from the Animal and Plant Health Agency (APHA)'s RADAR (Rapid Analysis and Detection of Animal-related Risks) database, and analysed using descriptive and network approaches. A total of 61,937,855 pigs were moved through 872,493 movements of batches in England and Wales during the 5-year study period. Results show that the network exhibited scale-free and small-world topologies, indicating the potential for diseases to quickly spread within the pig industry. The findings also provide suggestions for how risk-based surveillance strategies could be optimised in the country by taking account of highly connected holdings, geographical regions and time periods with the greatest number of movements and pigs moved, as these are likely to be at higher risk for disease introduction. This study is also the first attempt to identify trade communities in the country, information which could be used to facilitate the pig trade and maintain disease-free status across the country in the event of an outbreak.

Live bird markets characterization and trading network analysis in Mali: Implications for the surveillance and control of avian influenza and Newcastle disease

Live bird markets (LBMs) play an important role in the transmission of avian influenza (AI) and Newcastle disease (ND) viruses in poultry. Our study had two objectives: (1) characterizing LBMs in Mali with a focus on practices influencing the risk of transmission of AI and ND, and (2) identifying which LBMs should be targeted for surveillance and control based on properties of the live poultry trade network. Two surveys were conducted in 2009-2010: a descriptive study in all 96 LBMs of an area encompassing approximately 98% of the Malian poultry population and a network analysis study in Sikasso county, the main poultry supplying county for the capital city Bamako. Regarding LBMs' characteristics, risk factors for the presence of AI and ND viruses (being open every day, more than 2 days before a bird is sold, absence of zoning to segregate poultry-related work flow areas, waste removal or cleaning and disinfecting less frequently than on a daily basis, trash disposal of dead birds and absence of manure processing) were present in 80-100% of the LBMs. Furthermore, LBMs tended to have wide catchment areas because of consumers' preference for village poultry meat, thereby involving a large number of villages in their supply chain. In the poultry trade network from/to Sikasso county, 182 traders were involved and 685 links were recorded among 159 locations. The network had a heterogeneous degree distribution and four hubs were identified based on measures of in-degrees, out-degrees and betweenness: the markets of Medine and Wayerma and the fairs of Farakala and Niena. These results can be used to design biosecurity-improvement interventions and to optimize the prevention, surveillance and control of transmissible poultry diseases in Malian LBMs. Further studies should investigate potential drivers (seasonality, prices) of the poultry trade network and the acceptability of biosecurity and behavior-change recommendations in the Malian socio-cultural context.

Atmospheric dispersion modelling of bioaerosols that are pathogenic to humans and livestock - A review to inform risk assessment studies

In this review we discuss studies that applied atmospheric dispersion models (ADM) to bioaerosols that are pathogenic to humans and livestock in the context of risk assessment studies. Traditionally, ADMs have been developed to describe the atmospheric transport of chemical pollutants, radioactive matter, dust, and particulate matter. However, they have also enabled researchers to simulate bioaerosol dispersion. To inform risk assessment, the aims of this review were fourfold, namely (1) to describe the most important physical processes related to ADMs and pathogen transport, (2) to discuss studies that focused on the application of ADMs to pathogenic bioaerosols, (3) to discuss emission and inactivation rate parameterisations, and (4) to discuss methods for conversion of concentrations to infection probabilities (concerning quantitative microbial risk assessment). The studies included human, livestock, and industrial sources. Important factors for dispersion included wind speed, atmospheric stability, topographic effects, and deposition. Inactivation was mainly governed by humidity, temperature, and ultraviolet radiation. A majority of the reviewed studies, however, lacked quantitative analyses and application of full quantitative microbial risk assessments (QMRA). Qualitative conclusions based on geographical dispersion maps and threshold doses were encountered frequently. Thus, to improve risk assessment for future outbreaks and releases, we recommended determining well-quantified emission and inactivation rates and applying dosimetry and dose-response models to estimate infection probabilities in the population at risk.

Characterization of the live salmonid movement network in Ireland: Implications for disease prevention and control

Live fish movement is considered as having an important role in the transmission of infectious diseases. For that reason, interventions for cost-effective disease prevention and control rely on a sound understanding of the patterns of live fish movements in a region or country. Here, we characterize the network of live fish movements in the Irish salmonid farming industry during 2013, using social network analysis and spatial epidemiology methods, and identify interventions to limit the risk of disease introduction and spread. In the network there were 62 sites sending and/or receiving fish, with a total of 130 shipments (84 arcs) comprising approx. 17.2 million fish during the year. Atlantic salmon shipments covered longer distances than trout shipments, with some traversing the entire country. The average shipment of Atlantic salmon was 146,186 (SD 194,344) fish, compared to 77,928 (127,009) for trout, however, variability was high. There were 3 periods where shipments peaked (February-April, June-September, and November), which were related to specific stages of fish. The network was disconnected and had two major weak components, the first one with 39 nodes (mostly Atlantic salmon sites), and the second one with 10 nodes (exclusively trout sites). Correlation between in and out-degree at each site and assortativity coefficient were slightly low and non-significant: -0.08 (95% CI: -0.22, 0.06) and -0.13 (95% CI: -0.36, 0.08), respectively, indicating random mixing with regard to node degree. Although competing models also produced a good fit to degree distribution, it is likely that the network possesses both small-world and scale-free topology. This would facilitate the spread and persistence of infection in the salmon production system, but would also facilitate the design of risk-based surveillance strategies by targeting hubs, bridges or cut-points. Using Infomap community detection algorithms, 2 major communities were identified within the giant weak component, which were linked by only 4 nodes. Communities found had no correspondence with geographical zones within the country, which could potentially hinder the implementation of zoning strategies for disease control and eradication. Three significant spatial clusters of node centrality measures were detected, two in county Donegal (betweenness and outcloseness) and one in county Galway (incloseness), highlighting the importance of these locations as hot spots of highly central sites with a higher potential for both introduction and spread of infection. These results will assist in the design and implementation of measures to reduce the sanitary risks emerging from live fish trade within Ireland.

Controlling infectious disease through the targeted manipulation of contact network structure

Individuals in human and animal populations are linked through dynamic contact networks with characteristic structural features that drive the epidemiology of directly transmissible infectious diseases. Using animal movement data from the British cattle industry as an example, this analysis explores whether disease dynamics can be altered by placing targeted restrictions on contact formation to reconfigure network topology. This was accomplished using a simple network generation algorithm that combined configuration wiring with stochastic block modelling techniques to preserve the weighted in- and out-degree of individual nodes (farms) as well as key demographic characteristics of the individual network connections (movement date, livestock market, and animal production type). We then tested a control strategy based on introducing additional constraints into the network generation algorithm to prevent farms with a high in-degree from selling cattle to farms with a high out-degree as these particular network connections are predicted to have a disproportionately strong role in spreading disease. Results from simple dynamic disease simulation models predicted significantly lower endemic disease prevalences on the trade restricted networks compared to the baseline generated networks. As expected, the relative magnitude of the predicted changes in endemic prevalence was greater for diseases with short infectious periods and low transmission probabilities. Overall, our study findings demonstrate that there is significant potential for controlling multiple infectious diseases simultaneously by manipulating networks to have more epidemiologically favourable topological configurations. Further research is needed to determine whether the economic and social benefits of controlling disease can justify the costs of restricting contact formation.

Characteristics of airborne Staphylococcus aureus (including MRSA) in Chinese public buildings

The aim of this study was to evaluate the concentration and size distribution of airborne culturable Staphylococcus aureus (S. aureus) (including MRSA) in Chinese public buildings. Air samples were collected, using six-stage Andersen sampler from five different public buildings in one large Chinese community. The mean indoor concentrations of the total and respirable airborne S. aureus were 72 and 50 CFU/m3 in the general hospital, 72 and 49 CFU/m3 in the kindergarten, 76 and 52 CFU/m3 in the hotel, 84 and 57 CFU/m3 in the movie theater, and 55 and 40 CFU/m3 in the university classroom. Respirable S. aureus amounted to approximately 57-73 % of the total S. aureus concentrations. Mean total and respirable concentrations of airborne MRSA were 32 and 20 CFU/m3 in the general hospital, 20 and 13 CFU/m3 in the kindergarten, 23 and 16 CFU/m3 in the hotel, 33 and 20 CFU/m3 in the movie theater, and 24 and 17 CFU/m3 in the university classroom. Respirable MRSA amounted to approximately 61-72 % of the total MRSA concentrations. The ratios of indoor and outdoor concentration for airborne S. aureus and MRSA were more than 1.0 in all the investigated public buildings. The size distribution results showed relatively high collection rates on stage 4 (2.1-3.3 μm) for both airborne culturable S. aureus and MRSA regardless of the type of public buildings.

Alteration of protein levels during influenza virus H1N1 infection in host cells: a proteomic survey of host and virus reveals differential dynamics

We studied the dynamics of the proteome of influenza virus A/PR/8/34 (H1N1) infected Madin-Darby canine kidney cells up to 12 hours post infection by mass spectrometry based quantitative proteomics using the approach of stable isotope labeling by amino acids in cell culture (SILAC). We identified 1311 cell proteins and, apart from the proton channel M2, all major virus proteins. Based on their abundance two groups of virus proteins could be distinguished being in line with the function of the proteins in genesis and formation of new virions. Further, the data indicate a correlation between the amount of proteins synthesized and their previously determined copy number inside the viral particle. We employed bioinformatic approaches such as functional clustering, gene ontology, and pathway (KEGG) enrichment tests to uncover co-regulated cellular protein sets, assigned the individual subsets to their biological function, and determined their interrelation within the progression of viral infection. For the first time we are able to describe dynamic changes of the cellular and, of note, the viral proteome in a time dependent manner simultaneously. Through cluster analysis, time dependent patterns of protein abundances revealed highly dynamic up- and/or down-regulation processes. Taken together our study provides strong evidence that virus infection has a major impact on the cell status at the protein level.

How should social mixing be measured: comparing web-based survey and sensor-based methods

Background

Contact surveys and diaries have conventionally been used to measure contact networks in different settings for elucidating infectious disease transmission dynamics of respiratory infections. More recently, technological advances have permitted the use of wireless sensor devices, which can be worn by individuals interacting in a particular social context to record high resolution mixing patterns. To date, a direct comparison of these two different methods for collecting contact data has not been performed.

Methods

We studied the contact network at a United States high school in the spring of 2012. All school members (i.e., students, teachers, and other staff) were invited to wear wireless sensor devices for a single school day, and asked to remember and report the name and duration of all of their close proximity conversational contacts for that day in an online contact survey. We compared the two methods in terms of the resulting network densities, nodal degrees, and degree distributions. We also assessed the correspondence between the methods at the dyadic and individual levels.

Results

We found limited congruence in recorded contact data between the online contact survey and wireless sensors. In particular, there was only negligible correlation between the two methods for nodal degree, and the degree distribution differed substantially between both methods. We found that survey underreporting was a significant source of the difference between the two methods, and that this difference could be improved by excluding individuals who reported only a few contact partners. Additionally, survey reporting was more accurate for contacts of longer duration, and very inaccurate for contacts of shorter duration. Finally, female participants tended to report more accurately than male participants.

Conclusions

Online contact surveys and wireless sensor devices collected incongruent network data from an identical setting. This finding suggests that these two methods cannot be used interchangeably for informing models of infectious disease dynamics.

An exploration of how perceptions of the risk of avian influenza in poultry relate to urbanization in Vietnam

This research examined how perceptions of outbreaks of highly pathogenic avian influenza (HPAI) subtype H5N1 in poultry are related to urbanization. Via in-depth interviews with village leaders, household farmers, and large farm operators in modern, transitional, and traditional communes in the north of Vietnam, we explored behaviors, attitudes, cultural values, and traditions that might amplify or attenuate HPAI outbreaks. We also explored conceptualizations of urbanization and its impacts on animal husbandry and disease outbreaks. Qualitative theme analyses identified the key impacts, factors related to HPAI outbreaks, and disease prevention and management strategies. The analyses also highlighted how urbanization improves some aspects of life (e.g., food security, family wealth and health, more employment opportunities, and improved infrastructure), but simultaneously poses significant challenges for poultry farming and disease management. Awareness of qualitative aspects of HPAI risk perceptions and behaviors and how they vary with urbanization processes may help to improve the prevention and management of emerging infectious diseases.

A metapopulation model for highly pathogenic avian influenza: implications for compartmentalization as a control measure

Although the compartmentalization of poultry industry components has substantial economic implications, and is therefore a concept with huge significance to poultry industries worldwide, the current requirements for compartment status are generic to all OIE member countries. We examined the consequences for potential outbreaks of highly pathogenic avian influenza in the British poultry industry using a metapopulation modelling framework. This framework was used to assess the effectiveness of compartmentalization relative to zoning control, utilizing empirical data to inform the structure of potential epidemiological contacts within the British poultry industry via network links and spatial proximity. Conditions were identified where, despite the efficient isolation of poultry compartments through the removal of network-mediated links, spatially mediated airborne spread enabled spillover of infection with nearby premises making compartmentalization a more ‘risky’ option than zoning control. However, when zoning control did not effectively inhibit long-distance network links, compartmentalization became a relatively more effective control measure than zoning. With better knowledge of likely distance ranges for airborne spread, our approach could help define an appropriate minimum inter-farm distance to provide more specific guidelines for compartmentalization in Great Britain.

Implications of within-farm transmission for network dynamics: consequences for the spread of avian influenza

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Cross-scale dynamics were investigated for avian influenza in British poultry.

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Transmission risk is dependent on the assumed within-flock transmission mode.

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Transmission risk may not scale with transmissibility or flock size.

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Transmission risk corresponds with between-farm impact for 28% of farms.

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These results have implications for targeted disease control at the farm-level.

The importance of considering coupled interactions across multiple population scales has not previously been studied for highly pathogenic avian influenza (HPAI) in the British commercial poultry industry. By simulating the within-flock transmission of HPAI using a deterministic S-E-I-R model, and by incorporating an additional environmental class representing infectious faeces, we tracked the build-up of infectious faeces within a poultry house over time. A measure of the transmission risk (TR) was computed for each farm by linking the amount of infectious faeces present each day of an outbreak with data describing the daily on-farm visit schedules for a major British catching company. Larger flocks tended to have greater levels of these catching-team visits. However, where density-dependent contact was assumed, faster outbreak detection (according to an assumed mortality threshold) led to a decreased opportunity for catching-team visits to coincide with an outbreak. For this reason, maximum TR-levels were found for mid-range flock sizes (~25,000–35,000 birds). When assessing all factors simultaneously using multivariable linear regression on the simulated outputs, those related to the pattern of catching-team visits had the largest effect on TR, with the most important movement-related factor depending on the mode of transmission. Using social network analysis on a further database to inform a measure of between-farm connectivity, we identified a large fraction of farms (28%) that had both a high TR and a high potential impact at the between farm level. Our results have counter-intuitive implications for between-farm spread that could not be predicted based on flock size alone, and together with further knowledge of the relative importance of transmission risk and impact, could have implications for improved targeting of control measures.

Avian influenza transmission risks: analysis of biosecurity measures and contact structure in Dutch poultry farming

In the 2003 epidemic of highly pathogenic avian influenza in Dutch poultry, between-farm virus transmission continued for considerable time despite control measures. Gaining more insight into the mechanisms of this spread is necessary for the possible development of better control strategies. We carried out an in-depth interview study aiming to systematically explore all the poultry production activities to identify the activities that could potentially be related to virus introduction and transmission. One of the between-farm contact risks that were identified is the movement of birds between farms during thinning with violations of on-farm biosecurity protocols. In addition, several other risky management practices, risky visitor behaviours and biosecurity breaches were identified. They include human and fomite contacts that occurred without observing biosecurity protocols, poor waste management practices, presence of other animal species on poultry farms, and poor biosecurity against risks from farm neighbourhood activities. Among the detailed practices identified, taking cell phones and jewellery into poultry houses, not observing shower-in protocols and the exchange of unclean farm equipment were common. Also, sometimes certain protocols or biosecurity facilities were lacking. We also asked the interviewed farmers about their perception of transmission risks and found that they had divergent opinions about the visitor- and neighbourhood-associated risks. We performed a qualitative assessment of contact risks (as transmission pathways) based on contact type, corresponding biosecurity practices, and contact frequency. This assessment suggests that the most risky contact types are bird movements during thinning and restocking, most human movements accessing poultry houses and proximity to other poultry farms. The overall risk posed by persons and equipment accessing storage rooms and the premises-only contacts was considered to be medium. Most of the exposure risks are considered to be similar for layer and broiler farms. Our results, including those on farmer opinions, are relevant for the communication with farmers and poultry-related businesses about practices and risks. We conclude by providing recommendations for improvement of control strategies.

Controlling epidemic spread by social distancing: do it well or not at all

BACKGROUND

Existing epidemiological models have largely tended to neglect the impact of individual behaviour on the dynamics of diseases. However, awareness of the presence of illness can cause people to change their behaviour by, for example, staying at home and avoiding social contacts. Such changes can be used to control epidemics but they exact an economic cost. Our aim is to study the costs and benefits of using individual-based social distancing undertaken by healthy individuals as a form of control.

METHODS

Our model is a standard SIR model superimposed on a spatial network, without and with addition of small-world interactions. Disease spread is controlled by allowing susceptible individuals to temporarily reduce their social contacts in response to the presence of infection within their local neighbourhood. We ascribe an economic cost to the loss of social contacts, and weigh this against the economic benefit gained by reducing the impact of the epidemic. We study the sensitivity of the results to two key parameters, the individuals' attitude to risk and the size of the awareness neighbourhood.

RESULTS

Depending on the characteristics of the epidemic and on the relative economic importance of making contacts versus avoiding infection, the optimal control is one of two extremes: either to adopt a highly cautious control, thereby suppressing the epidemic quickly by drastically reducing contacts as soon as disease is detected; or else to forego control and allow the epidemic to run its course. The worst outcome arises when control is attempted, but not cautiously enough to cause the epidemic to be suppressed. The next main result comes from comparing the size of the neighbourhood of which individuals are aware to that of the neighbourhood within which transmission can occur. The control works best when these sizes match and is particularly ineffective when the awareness neighbourhood is smaller than the infection neighbourhood. The results are robust with respect to inclusion of long-range, small-world links which destroy the spatial structure, regardless of whether individuals can or cannot control them. However, addition of many non-local links eventually makes control ineffective.

CONCLUSIONS

These results have implications for the design of control strategies using social distancing: a control that is too weak or based upon inaccurate knowledge, may give a worse outcome than doing nothing.

Enhancing Bayesian risk prediction for epidemics using contact tracing

Contact-tracing data (CTD) collected from disease outbreaks has received relatively little attention in the epidemic modeling literature because it is thought to be unreliable: infection sources might be wrongly attributed, or data might be missing due to resource constraints in the questionnaire exercise. Nevertheless, these data might provide a rich source of information on the disease transmission rate. This paper presents a novel methodology for combining CTD with rate-based contact network data to improve posterior precision, and therefore predictive accuracy. We present an advancement in Bayesian inference for epidemics that assimilates these data and is robust to partial contact tracing. Using a simulation study based on the British poultry industry, we show how the presence of CTD improves posterior predictive accuracy and can directly inform a more effective control strategy.

Generating social network data using partially described networks: an example informing avian influenza control in the British poultry industry

BACKGROUND

Targeted sampling can capture the characteristics of more vulnerable sectors of a population, but may bias the picture of population level disease risk. When sampling network data, an incomplete description of the population may arise leading to biased estimates of between-host connectivity. Avian influenza (AI) control planning in Great Britain (GB) provides one example where network data for the poultry industry (the Poultry Network Database or PND), targeted large premises and is consequently demographically biased. Exposing the effect of such biases on the geographical distribution of network properties could help target future poultry network data collection exercises. These data will be important for informing the control of potential future disease outbreaks.

RESULTS

The PND was used to compute between-farm association frequencies, assuming that farms sharing the same slaughterhouse or catching company, or through integration, are potentially epidemiologically linked. The fitted statistical models were extrapolated to the Great Britain Poultry Register (GBPR); this dataset is more representative of the poultry industry but lacks network information. This comparison showed how systematic biases in the demographic characterisation of a network, resulting from targeted sampling procedures, can bias the derived picture of between-host connectivity within the network.

CONCLUSIONS

With particular reference to the predictive modeling of AI in GB, we find significantly different connectivity patterns across GB when network estimates incorporate the more demographically representative information provided by the GBPR; this has not been accounted for by previous epidemiological analyses. We recommend ranking geographical regions, based on relative confidence in extrapolated estimates, for prioritising further data collection. Evaluating whether and how the between-farm association frequencies impact on the risk of between-farm transmission will be the focus of future work.

The potential spread of highly pathogenic avian influenza virus via dynamic contacts between poultry premises in Great Britain

BACKGROUND

Highly pathogenic avian influenza (HPAI) viruses have had devastating effects on poultry industries worldwide, and there is concern about the potential for HPAI outbreaks in the poultry industry in Great Britain (GB). Critical to the potential for HPAI to spread between poultry premises are the connections made between farms by movements related to human activity. Movement records of catching teams and slaughterhouse vehicles were obtained from a large catching company, and these data were used in a simulation model of HPAI spread between farms serviced by the catching company, and surrounding (geographic) areas. The spread of HPAI through real-time movements was modelled, with the addition of spread via company personnel and local transmission.

RESULTS

The model predicted that although large outbreaks are rare, they may occur, with long distances between infected premises. Final outbreak size was most sensitive to the probability of spread via slaughterhouse-linked movements whereas the probability of onward spread beyond an index premises was most sensitive to the frequency of company personnel movements.

CONCLUSIONS

Results obtained from this study show that, whilst there is the possibility that HPAI virus will jump from one cluster of farms to another, movements made by catching teams connected fewer poultry premises in an outbreak situation than slaughterhouses and company personnel. The potential connection of a large number of infected farms, however, highlights the importance of retaining up-to-date data on poultry premises so that control measures can be effectively prioritised in an outbreak situation.

Seasonality and heterogeneity of live fish movements in Scottish fish farms

Movement of live animals is a key contributor to disease spread. Farmed Atlantic salmon Salmo salar, rainbow trout Onchorynchus mykiss and brown/sea trout Salmo trutta are initially raised in freshwater (FW) farms; all the salmon and some of the trout are subsequently moved to seawater (SW) farms. Frequently, fish are moved between farms during their FW stage and sometimes during their SW stage. Seasonality and differences in contact patterns across production phases have been shown to influence the course of an epidemic in livestock; however, these parameters have not been included in previous network models studying disease transmission in salmonids. In Scotland, farmers are required to register fish movements onto and off their farms; these records were used in the present study to investigate seasonality and heterogeneity of movements for each production phase separately for farmed salmon, rainbow trout and brown/sea trout. Salmon FW-FW and FW-SW movements showed a higher degree of heterogeneity in number of contacts and different seasonal patterns compared with SW-SW movements. FW-FW movements peaked from May to July and FW-SW movements peaked from March to April and from October to November. Salmon SW-SW movements occurred more consistently over the year and showed fewer connections and number of repeated connections between farms. Therefore, the salmon SW-SW network might be treated as homogeneous regarding the number of connections between farms and without seasonality. However, seasonality and production phase should be included in simulation models concerning FW-FW and FW-SW movements specifically. The number of rainbow trout FW-FW and brown/sea trout FW-FW movements were different from random. However, movements from other production phases were too low to discern a seasonal pattern or differences in contact pattern.

Uncertainties in the governance of animal disease: an interdisciplinary framework for analysis

Uncertainty is an inherent feature of strategies to contain animal disease. In this paper, an interdisciplinary framework for representing strategies of containment, and analysing how uncertainties are embedded and propagated through them, is developed and illustrated. Analysis centres on persistent, periodic and emerging disease threats, with a particular focus on cryptosporidiosis, foot and mouth disease and avian influenza. Uncertainty is shown to be produced at strategic, tactical and operational levels of containment, and across the different arenas of disease prevention, anticipation and alleviation. The paper argues for more critically reflexive assessments of uncertainty in containment policy and practice. An interdisciplinary approach has an important contribution to make, but is absent from current real-world containment policy.

How backyard poultry flocks influence the effort required to curtail avian influenza epidemics in commercial poultry flocks

This paper summarizes the evidence that the contribution of backyard poultry flocks to the on-going transmission dynamics of an avian influenza epidemic in commercial flocks is modest at best. Nevertheless, while disease control strategies need not involve the backyard flocks, an analysis of the contribution of each element of the next generation matrix to the basic reproduction number indicates that models which ignores the contribution of backyard flocks in estimating the effort required of strategies focused one host type (e.g. commercial flocks only) necessarily underestimate the level of effort to an extent that may matter to policy makers.

Impact of the implementation of rest days in live bird markets on the dynamics of H5N1 highly pathogenic avian influenza

Live bird markets (LBMs) act as a network 'hub' and potential reservoir of infection for domestic poultry. They may therefore be responsible for sustaining H5N1 highly pathogenic avian influenza (HPAI) virus circulation within the poultry sector, and thus a suitable target for implementing control strategies. We developed a stochastic transmission model to understand how market functioning impacts on the transmission dynamics. We then investigated the potential for rest days-periods during which markets are emptied and disinfected-to modulate the dynamics of H5N1 HPAI within the poultry sector using a stochastic meta-population model. Our results suggest that under plausible parameter scenarios, HPAI H5N1 could be sustained silently within LBMs with the time spent by poultry in markets and the frequency of introduction of new susceptible birds' dominant factors determining sustained silent spread. Compared with interventions applied in farms (i.e. stamping out, vaccination), our model shows that frequent rest days are an effective means to reduce HPAI transmission. Furthermore, our model predicts that full market closure would be only slightly more effective than rest days to reduce transmission. Strategies applied within markets could thus help to control transmission of the disease.

Epidemics and control strategies for diseases of farmed salmonids: a parameter study

The susceptibility of the English and Welsh fish farming and fisheries industry to emergent diseases is assessed using a stochastic simulation model. The model dynamics operate on a network comprising directed transport and river contacts, as well as undirected local and fomite transmissions. The directed connections cause outward transmission risk to be geographically more confined than inward risk. We consider reactive, proactive, and hybrid methods of control which correspond to a mixture of policy and the ease of disease detection. An explicit investigation of the impact of laboratory capacity is made. General quantified guidelines are derived to mitigate future epidemics.

Use of epidemiologic models in the control of highly pathogenic avian influenza

In the past decades, mathematical models have become more and more accepted as a tool to develop surveillance programs and to evaluate the efficacy of intervention measures for the control of infectious diseases such as highly pathogenic avian influenza. Predictive models are used to simulate the effect of various control measures on the course of an epidemic; analytical models are used to analyze data from outbreaks or from experiments. A key parameter in both types of models is the reproductive ratio, which indicates whether virus can be transmitted in the population, resulting in an epidemic, or not. Parameters obtained from real data using the analytical models can subsequently be used in predictive models to evaluate control strategies or surveillance programs. Examples of the use of these models are described here.

Exact epidemic models on graphs using graph-automorphism driven lumping

The dynamics of disease transmission strongly depends on the properties of the population contact network. Pair-approximation models and individual-based network simulation have been used extensively to model contact networks with non-trivial properties. In this paper, using a continuous time Markov chain, we start from the exact formulation of a simple epidemic model on an arbitrary contact network and rigorously derive and prove some known results that were previously mainly justified based on some biological hypotheses. The main result of the paper is the illustration of the link between graph automorphisms and the process of lumping whereby the number of equations in a system of linear differential equations can be significantly reduced. The main advantage of lumping is that the simplified lumped system is not an approximation of the original system but rather an exact version of this. For a special class of graphs, we show how the lumped system can be obtained by using graph automorphisms. Finally, we discuss the advantages and possible applications of exact epidemic models and lumping.

Contribution of company affiliation and social contacts to risk estimates of between-farm transmission of avian influenza

Background

Models of between-farm transmission of pathogens have identified service vehicles and social groups as risk factors mediating the spread of infection. Because of high levels of economic organization in much of the poultry industry, we examined the importance of company affiliation, as distinct from social contacts, in a model of the potential spread of avian influenza among broiler poultry farms in a poultry-dense region in the United States. The contribution of company affiliation to risk of between-farm disease transmission has not been previously studied.

Methodology/Principal Findings

We obtained data on the nature and frequency of business and social contacts through a national survey of broiler poultry growers in the United States. Daily rates of contact were estimated using Monte Carlo analysis. Stochastic modeling techniques were used to estimate the exposure risk posed by a single infectious farm to other farms in the region and relative risk of exposure for farms under different scenarios. The mean daily rate of vehicular contact was 0.82 vehicles/day. The magnitude of exposure risk ranged from <1% to 25% under varying parameters. Risk of between-farm transmission was largely driven by company affiliation, with farms in the same company group as the index farm facing as much as a 5-fold increase in risk compared to farms contracted with different companies. Employment of part-time workers contributed to significant increases in risk in most scenarios, notably for farms who hired day-laborers. Social visits were significantly less important in determining risk.

Conclusions/Significance

Biosecurity interventions should be based on information on industry structure and company affiliation, and include part-time workers as potentially unrecognized sources of viral transmission. Modeling efforts to understand pathogen transmission in the context of industrial food animal production should consider company affiliation in addition to geospatial factors and pathogen characteristics. Restriction of social contacts among farmers may be less useful in reducing between-farm transmission.

Evaluation of interventions and vaccination strategies for low pathogenicity avian influenza: spatial and space-time analyses and quantification of the spread of infection

In recent years the control of low pathogenicity avian influenza (LPAI) viruses of the H5 and H7 subtypes has increasingly become a concern. We evaluated the measures (stamping out, controlled marketing, emergency and preventive vaccination, farm density reduction and restocking in homogenous areas) implemented to control the LPAI epidemics that occurred in Italy between 2000 and 2005, using a combination of spatial and space-time analyses and estimates of the basic reproduction ratio (R0). Clustering of infected farms decreased over the years, indicating the effectiveness of the control strategies implemented. Controlled marketing [relative risk (RR) 0.46, 95% confidence interval (CI) 0.27-0.80], emergency (RR 0.47, 95% CI 0.39-0.57) and preventive vaccination (RR 0.19, 95% CI 0.09-0.41) were the most effective measures, yet R0<1 was only for preventive vaccination. Our results are useful for identifying the most effective measures for reducing the risk of the spread of LPAI and optimizing the allocation of resources.

Preventable H5N1 avian influenza epidemics in the British poultry industry network exhibit characteristic scales

Epidemics are frequently simulated on redundantly wired contact networks, which have many more links between sites than are minimally required to connect all. Consequently, the modelled pathogen can travel numerous alternative routes, complicating effective containment strategies. These networks have moreover been found to exhibit 'scale-free' properties and percolation, suggesting resilience to damage. However, realistic H5N1 avian influenza transmission probabilities and containment strategies, here modelled on the British poultry industry network, show that infection dynamics can additionally express characteristic scales. These system-preferred scales constitute small areas within an observed power law distribution that exhibit a lesser slope than the power law itself, indicating a slightly increased relative likelihood. These characteristic scales are here produced by a network-pervading intranet of so-called hotspot sites that propagate large epidemics below the percolation threshold. This intranet is, however, extremely vulnerable; targeted inoculation of a mere 3-6% (depending on incorporated biosecurity measures) of the British poultry industry network prevents large and moderate H5N1 outbreaks completely, offering an order of magnitude improvement over previously advocated strategies affecting the most highly connected 'hub' sites. In other words, hotspots and hubs are separate functional entities that do not necessarily coincide, and hotspots can make more effective inoculation targets. Given the ubiquity and relevance of networks (epidemics, Internet, power grids, protein interaction), recognition of this spreading regime elsewhere would suggest a similar disproportionate sensitivity to such surgical interventions.