Modelling the wind-borne spread of highly pathogenic avian influenza virus between farms

Detection of a Reassortant Swine- and Human-Origin H3N2 Influenza A Virus in Farmed Mink in British Columbia, Canada

INTRODUCTION

In December 2021, influenza A viruses (IAV) were detected in a population of farmed mink in British Columbia, Canada. Circulation of IAVs in farmed mink populations has raised public health concerns due to similarities between mustelid and human respiratory physiology, potentially facilitating spillover of zoonotic influenzas from livestock.

METHODS

Oropharyngeal specimens were collected from mink as part of a surveillance program for SARS-CoV-2. Diagnostic RT-qPCR testing was performed using a multiplex assay targeting SARS-CoV-2, IAV, influenza B virus and respiratory syncytial virus. Whole viral genome sequencing was conducted on IAV-positive specimens, followed by phylogenetic analysis with other animal and human IAV genome sequences from large global databases.

RESULTS

IAVs were detected in 17 of 65 mink by RT-qPCR. Based on genomic sequencing and phylogenetic analysis, these IAVs were subtyped as H3N2s that originated from reassortment of swine H3N2 (clade 1990.4 h), human seasonal H1N1 (pdm09) and swine H1N2 (clade 1A.1.1.3). This reassortant has been subsequently observed in swine in several Midwest American states, as well as in swine and turkeys in Ontario, suggesting its spillover into farmed mink in British Columbia was incidental to its broader dissemination in North American swine populations.

CONCLUSIONS

These detections reaffirm the need for extensive genomic surveillance of IAVs in swine populations to monitor reassortments that might become public health concerns. They also highlight the need for closer surveillance of IAVs in mink to preserve animal health, protect agricultural interests, and monitor potential zoonotic threats.

Biosecurity Implications, Transmission Routes and Modes of Economically Important Diseases in Domestic Fowl and Turkey

The poultry industry is a critical source of affordable protein worldwide; however, it faces continuous threats from various poultry diseases that significantly impact public health, economic stability, and food security. Knowledge of and examination of the transmission routes, risk factors, and environmental survival characteristics of the most important pathogens affecting poultry populations, as well as the importance of strict biosecurity, are pivotal. Transmission routes are split into direct and vector-borne pathways, and indirect ways, which include infections via contaminated surfaces and vector-borne pathways, including insects and rodents. Avian influenza virus and Newcastle disease virus spread through respiratory droplets, and their transmission risk increases with increasing stocking density. While other pathogens (e.g., infectious bursal disease virus and Salmonella spp.), to persist long-term in the environments, for example, feed and litter, increasing the probability to persist long-term in the environments, for example, feed and litter, increasing the probability of infection. The long-term resilience of pathogens in multiple pathogens in various environmental conditions highlights the role of biosecurity, sanitation, and hygiene controls in preventing disease outbreaks. High stocking density in production systems, suboptimal ventilation, and inadequate biosecurity controls further increase transmission risks. This paper summarizes important disease transmissions and reinforces the need for strict biosecurity protocols and routine health monitoring to prevent the spread of pathogens within and beyond poultry facilities. These strategies can support safe poultry production, address growing global demand, and ensure food safety and public health.

Association between highly pathogenic avian influenza outbreaks and weather conditions in Japan

Highly pathogenic avian influenza (HPAI) poses a significant threat to animal and public health, with outbreaks occurring globally. HPAI poses significant challenges due to its high mortality rate and public health concerns, with outbreaks spreading globally since the emergence of the H5N1 virus in 2003. In Japan, HPAI outbreaks have been particularly prevalent during autumn and winter seasons, with the 2022-2023 winter experiencing the most severe outbreak to date. However, limited research has directly examined the association between HPAI outbreaks and weather conditions in Japan. Here we show that specific weather conditions are associated with an increased risk of HPAI outbreaks on poultry farms in Japan. By analyzing databases of HPAI cases and meteorological data from 2020-2023, we found that higher average air temperatures two to three weeks prior, lower average wind speeds four weeks prior, and longer sunlight hours two and four weeks prior to outbreaks were significantly associated with increased risk of HPAI outbreaks in Japan. These results suggest that weather may influence environmental survival and transmission of the virus, as well as patterns of wild bird movement that could seed new outbreaks. These findings enhance our understanding of the factors influencing HPAI transmission dynamics and highlight the importance of integrating weather forecasts into disease surveillance and prevention strategies.

Viral shedding and environmental dispersion of two clade 2.3.4.4b H5 high pathogenicity avian influenza viruses in experimentally infected mule ducks: implications for environmental sampling

High pathogenicity avian influenza viruses (HPAIVs) have caused major epizootics in recent years, with devastating consequences for poultry and wildlife worldwide. Domestic and wild ducks can be highly susceptible to HPAIVs, and infection leads to efficient viral replication and massive shedding (i.e., high titres for an extended time), contributing to widespread viral dissemination. Importantly, ducks are known to shed high amounts of virus in the earliest phase of infection, but the dynamics and impact of environmental contamination on the epidemiology of HPAIV outbreaks are poorly understood. In this study, we monitored mule ducks experimentally infected with two H5N8 clade 2.3.4.4b goose/Guangdong HPAIVs sampled in France in 2016-2017 and 2020-2021 epizootics. We investigated viral shedding dynamics in the oropharynx, cloaca, conjunctiva, and feathers; bird-to-bird viral transmission; and the role of the environment in viral spread and as a source of samples for early detection and surveillance. Our findings showed that viral shedding started before the onset of clinical signs, i.e., as early as 1 day post-inoculation (dpi) or post-contact exposure, peaked at 4 dpi, and lasted for up to 14 dpi. The detection of viral RNA in aerosols, dust, and water samples mirrored viral shedding dynamics, and viral isolation from these environmental samples was successful throughout the experiment. Our results confirm that mule ducks can shed high HPAIV titres through the four excretion routes tested (oropharyngeal, cloacal, conjunctival, and feather) while being asymptomatic and that environmental sampling could be a non-invasive tool for early viral RNA detection in HPAIV-infected farms.

Avian Influenza Virus A(H5Nx) and Prepandemic Candidate Vaccines: State of the Art

Avian influenza virus has been long considered the main threat for a future pandemic. Among the possible avian influenza virus subtypes, A(H5N1) clade 2.3.4.4b is becoming enzootic in mammals, representing an alarming step towards a pandemic. In particular, genotype B3.13 has recently caused an outbreak in US dairy cattle. Since pandemic preparedness is largely based on the availability of prepandemic candidate vaccine viruses, in this review we will summarize the current status of the enzootics, and challenges for H5 vaccine manufacturing and delivery.

Exposure variables in veterinary epidemiology: are they telling us what we think they are?

This manuscript summarizes a presentation delivered by the first author at the 2024 symposium for the Calvin Schwabe Award for Lifetime Achievement in Veterinary Epidemiology and Preventive Medicine, which was awarded to Dr. Jan Sargeant. Epidemiologic research plays a crucial role in understanding the complex relationships between exposures and health outcomes. However, the accuracy of the conclusions drawn from these investigations relies upon the meticulous selection and measurement of exposure variables. Appropriate exposure variable selection is crucial for understanding disease etiologies, but it is often the case that we are not able to directly measure the exposure variable of interest and use proxy measures to assess exposures instead. Inappropriate use of proxy measures can lead to erroneous conclusions being made about the true exposure of interest. These errors may lead to biased estimates of associations between exposures and outcomes. The consequences of such biases extend beyond research concerns as health decisions can be made based on flawed evidence. Recognizing and mitigating these biases are essential for producing reliable evidence that informs health policies and interventions, ultimately contributing to improved population health outcomes. To address these challenges, researchers must adopt rigorous methodologies for exposure variable selection and validation studies to minimize measurement errors.

Quantitative Risk Assessment of Wind-Supported Transmission of Highly Pathogenic Avian Influenza Virus to Dutch Poultry Farms via Fecal Particles from Infected Wild Birds in the Environment

A quantitative microbial risk assessment model was developed to estimate the probability that the aerosolization of fecal droppings from wild birds in the vicinity of poultry farms would result in the infection of indoor-housed poultry with highly pathogenic avian influenza virus (HPAIv) in the Netherlands. Model input parameters were sourced from the scientific literature and experimental data. The availability of data was diverse across input parameters, and especially parameters on the aerosolization of fecal droppings, survival of HPAIv and dispersal of aerosols were uncertain. Model results indicated that the daily probability of infection of a single poultry farm is very low, with a median value of 7.5 × 10-9. Accounting for the total number of poultry farms and the length of the bird-flu season, the median overall probability of at least one HPAIv-infected poultry farm during the bird-flu season is 2.2 × 10-3 (approximately once every 455 years). This is an overall estimate, averaged over different farm types, virus strains and wild bird species, and results indicate that uncertainty is relatively high. Based on these model results, we conclude that it is unlikely that this introduction route plays an important role in the occurrence of HPAIv outbreaks in indoor-housed poultry.

Investigating the uses of machine learning algorithms to inform risk factor analyses: The example of avian infectious bronchitis virus (IBV) in broiler chickens

Infectious bronchitis virus (IBV) is a contagious coronavirus causing respiratory and urogenital disease in chickens and is responsible for significant economic losses for both the broiler and table egg layer industries. Despite IBV being regularly monitored using standard epidemiologic surveillance practices, knowledge and evidence of risk factors associated with IBV transmission remain limited. The study objective was to compare risk factor modeling outcomes between a traditional stepwise variable selection approach and a machine learning-based random forest Boruta algorithm using routinely collected IBV antibody titer data from broiler flocks. IBV antibody sampling events (n = 1111) from 166 broiler sites between 2016 and 2021 were accessed. Ninety-two geospatial-related and poultry-density variables were obtained using a geographic information system and data sets from publicly available sources. Seventeen and 27 candidate variables were screened to potentially have an association with elevated IBV antibody titers according to the manual selection and machine learning algorithm, respectively. Selected variables from both methods were further investigated by construction of multivariable generalized mixed logistic regression models. Six variables were shortlisted by both screening methods, which included year, distance to urban areas, main roads, landcover, density of layer sites and year, however, final models for both approaches only shared year as an important predictor. Despite limited significance of clinical outcomes, this work showcases the potential of a novel explorative modeling approach in combination with often unutilized resources such as publicly available geospatial data, surveillance health data and machine learning as potential supplementary tools to investigate risk factors related to infectious diseases.

Optimizing environmental viral surveillance: bovine serum albumin increases RT-qPCR sensitivity for high pathogenicity avian influenza H5Nx virus detection from dust samples

IMPORTANCE

With the circulation of high pathogenicity avian influenza viruses having intensified considerably in recent years, the European Union is considering the vaccination of farmed birds. A prerequisite for this vaccination is the implementation of drastic surveillance protocols. Environmental sampling is a relevant alternative to animal sampling. However, environmental samples often contain inhibitory compounds in large enough quantities to inhibit RT-qPCR reactions. As bovine serum albumin is a molecule used in many fields to overcome this inhibitory effect, we tested its use on dust samples from poultry farms in areas heavily affected by HPAIV epizootics. Our results show that its use significantly increases the sensitivity of the method.

The role of vaccination and environmental factors on outbreaks of high pathogenicity avian influenza H5N1 in Bangladesh

High Pathogenicity Avian Influenza (HPAI) H5N1 outbreaks continue to wreak havoc on the global poultry industry and threaten the health of wild bird populations, with sporadic spillover in humans and other mammals, resulting in widespread calls to vaccinate poultry. Bangladesh has been vaccinating poultry since 2012, presenting a prime opportunity to study the effects of vaccination on HPAI H5N1circulation in both poultry and wild birds. We investigated the efficacy of vaccinating commercial poultry against HPAI H5N1 along with climatic and socio-economic factors considered potential drivers of HPAI H5N1 outbreak risk in Bangladesh. Using a multivariate modeling approach, we estimated that the rate of outbreaks was 18 times higher before compared to after vaccination, with winter months having a three times higher chance of outbreaks than summer months. Variables resulting in small but significant increases in outbreak rate were relatively low ambient temperatures for the time of year, literacy rate, chicken and duck density, crop density, and presence of highways; this may be attributable to low temperatures supporting viral survival outside the host, higher literacy driving reporting rate, density of the host reservoir, and spread of the virus through increased connectivity. Despite the substantial impact of vaccination on outbreaks, we note that HPAI H5N1 is still enzootic in Bangladesh; vaccinated poultry flocks have high rates of H5N1 prevalence, and spillover to wild birds has increased. Vaccination in Bangladesh thus bears the risk of supporting "silent spread," where the vaccine only provides protection against disease and not also infection. Our findings underscore that poultry vaccination can be part of holistic HPAI mitigation strategies when accompanied by monitoring to avoid silent spread.

Association of climatic variables with risk of transmission of influenza in Guangzhou, China, 2005-2021

BACKGROUND

Climatic variables constitute important extrinsic determinants of transmission and seasonality of influenza. Yet quantitative evidence of independent associations of viral transmissibility with climatic factors has thus far been scarce and little is known about the potential effects of interactions between climatic factors on transmission.

OBJECTIVE

This study aimed to examine the associations of key climatic factors with risk of influenza transmission in subtropical Guangzhou.

METHODS

Influenza epidemics were identified over a 17-year period using the moving epidemic method (MEM) from a dataset of N = 295,981 clinically- and laboratory-confirmed cases of influenza in Guangzhou. Data on eight key climatic variables were collected from China Meteorological Data Service Centre. Generalized additive model combined with the distributed lag non-linear model (DLNM) were developed to estimate the exposure-lag-response curve showing the trajectory of instantaneous reproduction number (R_t) across the distribution of each climatic variable after adjusting for depletion of susceptible, inter-epidemic effect and school holidays. The potential interaction effects of temperature, humidity and rainfall on influenza transmission were also examined.

RESULTS

Over the study period (2005-21), 21 distinct influenza epidemics with varying peak timings and durations were identified. Increasing air temperature, sunshine, absolute and relative humidity were significantly associated with lower R_t, while the associations were opposite in the case of ambient pressure, wind speed and rainfall. Rainfall, relative humidity, and ambient temperature were the top three climatic contributors to variance in transmissibility. Interaction models found that the detrimental association between high relative humidity and transmissibility was more pronounced at high temperature and rainfall.

CONCLUSION

Our findings are likely to help understand the complex role of climatic factors in influenza transmission, guiding informed climate-related mitigation and adaptation policies to reduce transmission in high density subtropical cities.

Dispersion characteristics of bioaerosols during treatment of rural solid waste in northwest China

In rural China, the release of bioaerosols containing pathogens from solid waste dumps poses a potential health risk to the local population. Here, we sampled bioaerosols from rural solid waste-treatment in four provinces of northwest China to investigate their emission and dispersion characteristics in order to provide a scientific basis for control and risk reduction of bioaerosols released from rural sanitation facilities. The airborne bioaerosol concentrations and particle size distributions were calculated using an Anderson six-stage airborne microbial sampler and counting with its internal Petri dish culture. High-throughput sequencing was used to characterize the microbial composition at different sampling sites and to explore possible influencing factors, while the health risk associated with exposure was estimated based on average daily dose-rate. The highest concentration point values of bacteria and fungi in bioaerosols near the solid waste were 63,617 ± 15,007 and 8044 ± 893 CFU/m³, respectively. Furthermore, the highest concentration point values of Enterobacteriaceae was 502 ± 35 CFU/m³. Most bioaerosols were coarse particles larger than 3.3 μm. Potentially pathogenic genera of winter-indicator species detected in the air were primarily Delftia, Rhodococcus and Aspergillus. The composition of solid waste and environmental conditions are important factors in determining the characteristics of bioaerosols. Local residents are exposed to bioaerosols mainly through inhalation. Children are at a particularly high risk of exposure through both inhalation and skin contact. The results of this study show that bioaerosols in the vicinity of rural solid waste dumps pose a health risk to the surrounding population. More suitable risk assessment criteria for rural areas should be established, and corresponding control and protection measures should be taken from three aspects: generation source and transmission pathway, as well as the recipient.

The Role of Airborne Particles in the Epidemiology of Clade 2.3.4.4b H5N1 High Pathogenicity Avian Influenza Virus in Commercial Poultry Production Units

Since October 2021, Europe has experienced the largest avian influenza virus (AIV) epizootic, caused by clade 2.3.4.4b H5N1 high pathogenicity AIV (HPAIV), with over 284 poultry infected premises (IPs) and 2480 dead H5N1-positive wild birds detected in Great Britain alone. Many IPs have presented as geographical clusters, raising questions about the lateral spread between premises by airborne particles. Airborne transmission over short distances has been observed for some AIV strains. However, the risk of airborne spread of this strain remains to be elucidated. We conducted extensive sampling from IPs where clade 2.3.4.4b H5N1 HPAIVs were confirmed during the 2022/23 epizootic, each representing a major poultry species (ducks, turkeys, and chickens). A range of environmental samples were collected inside and outside houses, including deposited dust, feathers, and other potential fomites. Viral RNA (vRNA) and infectious viruses were detected in air samples collected from inside and outside but in close proximity to infected houses, with vRNA alone being detected at greater distances (≤10 m) outside. Some dust samples collected outside of the affected houses contained infectious viruses, while feathers from the affected houses, located up to 80 m away, only contained vRNA. Together, these data suggest that airborne particles harboring infectious HPAIV can be translocated short distances (<10 m) through the air, while macroscopic particles containing vRNA might travel further (≤80 m). Therefore, the potential for airborne transmission of clade 2.3.4.4b H5N1 HPAIV between premises is considered low. Other factors, including indirect contact with wild birds and the efficiency of biosecurity, represent greater importance in disease incursion.

Combined Phylogeographic Analyses and Epidemiologic Contact Tracing to Characterize Atypically Pathogenic Avian Influenza (H3N1) Epidemic, Belgium, 2019

The high economic impact and zoonotic potential of avian influenza call for detailed investigations of dispersal dynamics of epidemics. We integrated phylogeographic and epidemiologic analyses to investigate the dynamics of a low pathogenicity avian influenza (H3N1) epidemic that occurred in Belgium during 2019. Virus genomes from 104 clinical samples originating from 85% of affected farms were sequenced. A spatially explicit phylogeographic analysis confirmed a dominating northeast to southwest dispersal direction and a long-distance dispersal event linked to direct live animal transportation between farms. Spatiotemporal clustering, transport, and social contacts strongly correlated with the phylogeographic pattern of the epidemic. We detected only a limited association between wind direction and direction of viral lineage dispersal. Our results highlight the multifactorial nature of avian influenza epidemics and illustrate the use of genomic analyses of virus dispersal to complement epidemiologic and environmental data, improve knowledge of avian influenza epidemiologic dynamics, and enhance control strategies.

Monitoring Wind-Borne Particle Matter Entering Poultry Farms via the Air-Inlet: Highly Pathogenic Avian Influenza Virus and Other Pathogens Risk

Wind-supported transport of particle matter (PM) contaminated with excreta from highly pathogenic avian influenza virus (HPAIv)-infected wild birds may be a HPAIv-introduction pathway, which may explain infections in indoor-housed poultry. The primary objective of our study was therefore to measure the nature and quantity of PM entering poultry houses via air-inlets. The air-inlets of two recently HPAIv-infected poultry farms (a broiler farm and a layer farm) were equipped with mosquito-net collection bags. PM was harvested every 5 days for 25 days. Video-camera monitoring registered wild bird visits. PM was tested for avian influenza viruses (AIV), Campylobacter and Salmonella with PCR. Insects, predominantly mosquitoes, were tested for AIV, West Nile, Usutu and Schmallenberg virus. A considerable number of mosquitoes and small PM amounts entered the air-inlets, mostly cobweb and plant material, but no wild bird feathers. Substantial variation in PM entering between air-inlets existed. In stormy periods, significantly larger PM amounts may enter wind-directed air-inlets. PM samples were AIV and Salmonella negative and insect samples were negative for all viruses and bacteria, but several broiler and layer farm PM samples tested Campylobacter positive. Regular wild (water) bird visits were observed near to the poultry houses. Air-borne PM and insects-potentially contaminated with HPAIv or other pathogens-can enter poultry air-inlets. Implementation of measures limiting this potential introduction route are recommended.

Influenza A and B outbreaks differed in their associations with climate conditions in Shenzhen, China

Under the variant climate conditions in the transitional regions between tropics and subtropics, the impacts of climate factors on influenza subtypes have rarely been evaluated. With the available influenza A (Flu-A) and influenza B (Flu-B) outbreak data in Shenzhen, China, which is an excellent example of a transitional marine climate, the associations of multiple climate variables with these outbreaks were explored in this study. Daily laboratory-confirmed influenza virus and climate data were collected from 2009 to 2015. Potential impacts of daily mean/maximum/minimum temperatures (T/T_max/T_min), relative humidity (RH), wind velocity (V), and diurnal temperature range (DTR) were analyzed using the distributed lag nonlinear model (DLNM) and generalized additive model (GAM). Under its local climate partitions, Flu-A mainly prevailed in summer months (May to June), and a second peak appeared in early winter (December to January). Flu-B outbreaks usually occurred in transitional seasons, especially in autumn. Although low temperature caused an instant increase in both Flu-A and Flu-B risks, its effect could persist for up to 10 days for Flu-B and peak at 17 C (relative risk (RR) = 14.16, 95% CI: 7.46-26.88). For both subtypes, moderate-high temperature (28 C) had a significant but delayed effect on influenza, especially for Flu-A (RR = 26.20, 95% CI: 13.22-51.20). The Flu-A virus was sensitive to RH higher than 76%, while higher Flu-B risks were observed at both low (< 65%) and high (> 83%) humidity. Flu-A was active for a short term after exposure to large DTR (e.g., DTR = 10 C, RR = 12.45, 95% CI: 6.50-23.87), whereas Flu-B mainly circulated under stable temperatures. Although the overall wind speed in Shenzhen was low, moderate wind (2-3 m/s) was found to favor the outbreaks of both subtypes. This study revealed the thresholds of various climatic variables promoting influenza outbreaks, as well as the distinctions between the flu subtypes. These data can be helpful in predicting seasonal influenza outbreaks and minimizing the impacts, based on integrated forecast systems coupled with short-term climate models.

Associations between Temperature and Influenza Activity: A National Time Series Study in China

Previous studies have reported that temperature is the main meteorological factor associated with influenza activity. This study used generalized additive models (GAMs) to explore the relationship between temperature and influenza activity in China. From the national perspective, the average temperature (AT) had an approximately negative linear correlation with the incidence of influenza, as well as a positive rate of influenza H1N1 virus (A/H1N1). Every degree that the monthly AT rose, the influenza cases decreased by 2.49% (95%CI: 1.24%–3.72%). The risk of influenza cases reached a peak at −5.35 °C with RRs of 2.14 (95%CI: 1.38–3.33) and the monthly AT in the range of −5.35 °C to 18.31 °C had significant effects on the incidence of influenza. Every degree that the weekly AT rose, the positive rate of A/H1N1 decreased by 5.28% (95%CI: 0.35%–9.96%). The risk of A/H1N1 reached a peak at −3.14 °C with RRs of 4.88 (95%CI: 1.01–23.75) and the weekly AT in the range of −3.14 °C to 17.25 °C had significant effects on the incidence of influenza. Our study found that AT is negatively associated with influenza activity, especially for A/H1N1. These findings indicate that temperature could be integrated into the current influenza surveillance system to develop early warning systems to better predict and prepare for the risks of influenza.

Non-respiratory particles emitted by guinea pigs in airborne disease transmission experiments

Animal models are often used to assess the airborne transmissibility of various pathogens, which are typically assumed to be carried by expiratory droplets emitted directly from the respiratory tract of the infected animal. We recently established that influenza virus is also transmissible via "aerosolized fomites," micron-scale dust particulates released from virus-contaminated surfaces (Asadi et al. in Nat Commun 11(1):4062, 2020). Here we expand on this observation, by counting and characterizing the particles emitted from guinea pig cages using an Aerodynamic Particle Sizer (APS) and an Interferometric Mie Imaging (IMI) system. Of over 9000 airborne particles emitted from guinea pig cages and directly imaged with IMI, none had an interference pattern indicative of a liquid droplet. Separate measurements of the particle count using the APS indicate that particle concentrations spike upwards immediately following animal motion, then decay exponentially with a time constant commensurate with the air exchange rate in the cage. Taken together, the results presented here raise the possibility that a non-negligible fraction of airborne influenza transmission events between guinea pigs occurs via aerosolized fomites rather than respiratory droplets, though the relative frequencies of these two routes have yet to be definitively determined.

Infection Risk Assessment of COVID-19 through Aerosol Transmission: a Case Study of South China Seafood Market

The Corona Virus Disease 2019 (COVID-19) is rapidly spreading throughout the world. Aerosol is a potential transmission route. We conducted the quantitative microbial risk assessment (QMRA) to evaluate the aerosol transmission risk by using the South China Seafood Market as an example. The key processes were integrated, including viral shedding, dispersion, deposition in air, biologic decay, lung deposition, and the infection risk based on the dose-response model. The available hospital bed for COVID-19 treatment per capita (1.17 × 10-3) in Wuhan was adopted as a reference for manageable risk. The median risk of a customer to acquire SARS-CoV-2 infection via the aerosol route after 1 h of exposure in the market with one infected shopkeeper was about 2.23 × 10-5 (95% confidence interval: 1.90 × 10-6 to 2.34 × 10-4). The upper bound could increase and become close to the manageable risk with multiple infected shopkeepers. More detailed risk assessment should be conducted in poorly ventilated markets with multiple infected cases. The uncertainties were mainly due to the limited information on the dose-response relation and the viral shedding which need further studies. The risk rapidly decreased outside the market due to the dilution by ambient air and became below 10-6 at 5 m away from the exit.

Characteristics of microbial aerosol particles dispersed downwind from rural sanitation facilities: Size distribution, source tracking and exposure risk

Bioaerosols containing pathogens released from waste and wastewater treatment facilities pose potential health risks to workers on-site and residents downwind. In this study, sampling sites were set up at rural garbage stations (GS-1 and GS-2) and sewage treatment station (STS) to investigate the emission and diffusion characteristics of bioaerosols. High-throughput sequencing was utilized to assay the intestinal bacteria population, while the health risks associated with bioaerosols exposure were estimated based on average daily dose rates (DD). Traceability analysis was used to determine the percentages of intestinal bacteria from GS-1, GS-2 and STS. The recorded emission levels of bioaerosols in the air surrounding GS-1, GS-2, and STS were 5053, 6299, and 4795 CFU/m³, containing 1599, 2244, and 2233 CFU/m³ of intestinal bacteria, respectively. Most of the bioaerosols were coarse particles with size larger than 4.7 μm. Methylobacterium, Rhizobium, Pseudomonas, Enterobacteriaceae, and Brucella presented in the air were originally in rural waste and wastewater. STS and GS-2 were potential sources of intestinal bacteria. With increasing distance from the sources, the concentration of bioaerosols decreased gradually. On-site workers and residents were predominantly affected by bioaerosols through inhalation. The exposure risks via inhalation and skin contact for children were much higher than that for adults. The purpose of this study was to provide preliminary data for bioaerosols control and their risks reduction released from rural sanitation facilities.

Multi-Scale Airborne Infectious Disease Transmission

Airborne disease transmission is central to many scientific disciplines including agriculture, veterinary biosafety, medicine, and public health. Legal and regulatory standards are in place to prevent agricultural, nosocomial, and community airborne disease transmission. However, the overall importance of the airborne pathway is underappreciated, e.g.,, US National Library of Medicine's Medical Subjects Headings (MESH) thesaurus lacks an airborne disease transmission indexing term. This has practical consequences as airborne precautions to control epidemic disease spread may not be taken when airborne transmission is important, but unrecognized. Publishing clearer practical methodological guidelines for surveillance studies and disease outbreak evaluations could help address this situation.To inform future work, this paper highlights selected, well-established airborne transmission events - largely cases replicated in multiple, independently conducted scientific studies. Methodologies include field experiments, modeling, epidemiology studies, disease outbreak investigations and mitigation studies. Collectively, this literature demonstrates that airborne viruses, bacteria, and fungal pathogens have the capability to cause disease in plants, animals, and humans over multiple distances - from near range (< 5 m) to continental (> 500 km) in scale. The plausibility and implications of undetected airborne disease transmission are discussed, including the notable underreporting of disease burden for several airborne transmitted diseases.

How mechanistic modelling supports decision making for the control of enzootic infectious diseases

Controlling enzootic diseases, which generate a large cumulative burden and are often unregulated, is needed for sustainable farming, competitive agri-food chains, and veterinary public health. We discuss the benefits and challenges of mechanistic epidemiological modelling for livestock enzootics, with particular emphasis on the need for interdisciplinary approaches. We focus on issues arising when modelling pathogen spread at various scales (from farm to the region) to better assess disease control and propose targeted options. We discuss in particular the inclusion of farmers' strategic decision-making, the integration of within-host scale to refine intervention targeting, and the need to ground models on data.

A Mathematical Framework for Predicting Lifestyles of Viral Pathogens

Despite being similar in structure, functioning, and size, viral pathogens enjoy very different, usually well-defined ways of life. They occupy their hosts for a few days (influenza), for a few weeks (measles), or even lifelong (HCV), which manifests in acute or chronic infections. The various transmission routes (airborne, via direct physical contact, etc.), degrees of infectiousness (referring to the viral load required for transmission), antigenic variation/immune escape and virulence define further aspects of pathogenic lifestyles. To survive, pathogens must infect new hosts; the success determines their fitness. Infection happens with a certain likelihood during contact of hosts, where contact can also be mediated by vectors. Besides structural aspects of the host-contact network, three parameters appear to be key: the contact rate and the infectiousness during contact, which encode the mode of transmission, and third the immunity of susceptible hosts. On these grounds, what can be said about the reproductive success of viral pathogens? This is the biological question addressed in this paper. The answer extends earlier results of the author and makes explicit connection to another basic work on the evolution of pathogens. A mathematical framework is presented that models intra- and inter-host dynamics in a minimalistic but unified fashion covering a broad spectrum of viral pathogens, including those that cause flu-like infections, childhood diseases, and sexually transmitted infections. These pathogens turn out as local maxima of numerically simulated fitness landscapes. The models involve differential and integral equations, agent-based simulation, networks, and probability.

Phylodynamic analysis and evaluation of the balance between anthropic and environmental factors affecting IBV spreading among Italian poultry farms

Infectious bronchitis virus (IBV) control is mainly based on wide vaccine administration. Although effective, its efficacy is not absolute, the viral circulation is not prevented and some side effects cannot be denied. Despite this, the determinants of IBV epidemiology and the factors affecting its circulation are still largely unknown and poorly investigated. In the present study, 361 IBV QX (the most relevant field genotype in Italy) sequences were obtained between 2012 and 2016 from the two main Italian integrated poultry companies. Several biostatistical and bioinformatics approaches were used to reconstruct the history of the QX genotype in Italy and to assess the effect of different environmental, climatic and social factors on its spreading patterns. Moreover, two structured coalescent models were considered in order to investigate if an actual compartmentalization occurs between the two integrated poultry companies and the role of a third "ghost" deme, representative of minor industrial poultry companies and the rural sector. The obtained results suggest that the integration of the poultry companies is an effective barrier against IBV spreading, since the strains sampled from the two companies formed two essentially-independent clades. Remarkably, the only exceptions were represented by farms located in the high densely populated poultry area of Northern Italy. The inclusion of a third deme in the model revealed the likely role of other poultry companies and rural farms (particularly concentrated in Northern Italy) as sources of strain introduction into one of the major poultry companies, whose farms are mainly located in the high densely populated poultry area of Northern Italy. Accordingly, when the effect of different environmental and urban parameters on IBV geographic spreading was investigated, no factor seems to contribute to IBV dispersal velocity, being poultry population density the only exception. Finally, the different viral population pattern observed in the two companies over the same time period supports the pivotal role of management and control strategies on IBV epidemiology. Overall, the present study results stress the crucial relevance of human action rather than environmental factors, highlighting the direct benefits that could derive from improved management and organization of the poultry sector on a larger scale.

Exploring the Wind-Borne Spread of Highly Pathogenic Avian Influenza H5N8 During the 2016-2017 Epizootic in France

In winter 2016-2017, highly pathogenic avian influenza (HPAI) H5N8 virus spread in France, causing an unprecedented epizootic. During the epidemic, southwest France, where most outbreaks were reported, experienced severe weather, with three consecutive storms (Leiv, Kurt, and Marcel) from 3 to 5 February 2017. Although little information is available, one hypothesis is that the spread of HPAI-H5N8 from an infected poultry holding could have been passively facilitated by prevailing wind during the risk period. The aim of this study was therefore to assess the contribution of the wind-borne route to the spatial distribution of HPAI H5N8 outbreaks during the risk period at the beginning of February 2017. The PERLE model, an atmospheric dispersion model (ADM) developed by Météo-France, the French meteorological agency, was used to generate the predicted area at risk of infection from a suspected point source. Model outputs show that the spatial pattern of dust-particle deposition was directed east-southeast in accordance with wind direction. This contrasted with the spatial distribution of HPAI H5N8 outbreaks, which spread westward. These observations suggest that the wind-borne route alone was insufficient to explain the spatial distribution of outbreaks over large distances in southwest France at the beginning of February 2017. Finally, this study illustrates the relevance of close collaboration between governmental authorities, veterinary research institutes, and meteorological agencies involving interdisciplinary research for successful outbreak investigations.

The complex associations of climate variability with seasonal influenza A and B virus transmission in subtropical Shanghai, China

Most previous studies focused on the association between climate variables and seasonal influenza activity in tropical or temperate zones, little is known about the associations in different influenza types in subtropical China. The study aimed to explore the associations of multiple climate variables with influenza A (Flu-A) and B virus (Flu-B) transmissions in Shanghai, China. Weekly influenza virus and climate data (mean temperature (MeanT), diurnal temperature range (DTR), relative humidity (RH) and wind velocity (Wv)) were collected between June 2012 and December 2018. Generalized linear models (GLMs), distributed lag non-linear models (DLNMs) and regression tree models were developed to assess such associations. MeanT exerted the peaking risk of Flu-A at 1.4 °C (2-weeks' cumulative relative risk (RR): 14.88, 95% confidence interval (CI): 8.67-23.31) and 25.8 °C (RR: 12.21, 95%CI: 6.64-19.83), Flu-B had the peak at 1.4 °C (RR: 26.44, 95%CI: 11.52-51.86). The highest RR of Flu-A was 23.05 (95%CI: 5.12-88.45) at DTR of 15.8 °C, that of Flu-B was 38.25 (95%CI: 15.82-87.61) at 3.2 °C. RH of 51.5% had the highest RR of Flu-A (9.98, 95%CI: 4.03-26.28) and Flu-B (4.63, 95%CI: 1.95-11.27). Wv of 3.5 m/s exerted the peaking RR of Flu-A (7.48, 95%CI: 2.73-30.04) and Flu-B (7.87, 95%CI: 5.53-11.91). DTR ≥ 12 °C and MeanT <22 °C were the key drivers for Flu-A and Flu-B, separately. The study found complex non-linear relationships between climate variability and different influenza types in Shanghai. We suggest the careful use of meteorological variables in influenza prediction in subtropical regions, considering such complex associations, which may facilitate government and health authorities to better minimize the impacts of seasonal influenza.

A tracing method of airborne bacteria transmission across built environments

Disease transmission across built environments has been found to be a serious health risk. Airborne transmission is a vital route of disease infection caused by bacteria and virus. However, tracing methods of airborne bacteria in both lab and field research failed to veritably express the transporting process of microorganism in the air. A new tracing method of airborne bacteria used for airborne transmission was put forward and demonstrated its feasibility by conducting a field evaluation on the basis of genetic modification and bioaerosol technology. A specific gene fragment (pFPV-mCherry fluorescent protein plasmid) was introduced into nonpathogenic E. coli DH5α as tracer bacteria by high-voltage electroporation. Gel electrophoresis and DNA sequencing proved the success of the synthesis. Genetic stability, effect of aerosolization on the survival rate of tracer bacteria, and the application of the tracer bacteria to the airborne bacteria transmission were examined in both lab and field. Both the introduced plasmid stability rates of tracer E. coli in pre-aerosolization and post-aerosolization were above 95% in five test days. Survival rate of tracer E. coli at 97.5% ± 1.2% through aerosolization was obtained by an air-atomizer operated at an air pressure of 30 Psi. In the field experiment, the airborne transmission of E. coli between poultry houses was proved and emitted E. coli was more easily transmitted into self-house than adjacent house due to the ventilation design and weather condition. Our results suggested that the tracing method of airborne bacteria was available for the investigation of airborne microbial transmission across built environments.

A review of knowledge discovery process in control and mitigation of avian influenza

In the last several decades, avian influenza virus has caused numerous outbreaks around the world. These outbreaks pose a significant threat to the poultry industry and also to public health. When an avian influenza (AI) outbreak occurs, it is critical to make informed decisions about the potential risks, impact, and control measures. To this end, many modeling approaches have been proposed to acquire knowledge from different sources of data and perspectives to enhance decision making. Although some of these approaches have shown to be effective, they do not follow the process of knowledge discovery in databases (KDD). KDD is an iterative process, consisting of five steps, that aims at extracting unknown and useful information from the data. The present review attempts to survey AI modeling methods in the context of KDD process. We first divide the modeling techniques used in AI into two main categories: data-intensive modeling and small-data modeling. We then investigate the existing gaps in the literature and suggest several potential directions and techniques for future studies. Overall, this review provides insights into the control of AI in terms of the risk of introduction and spread of the virus.

Airborne transmission may have played a role in the spread of 2015 highly pathogenic avian influenza outbreaks in the United States

The unprecedented 2015 outbreaks of highly pathogenic avian influenza (HPAI) H5N2 in the U.S. devastated its poultry industry and resulted in over $3 billion economic impacts. Today HPAI continues eroding poultry operations and disrupting animal protein supply chains around the world. Anecdotal evidence in 2015 suggested that in some cases the AI virus was aerially introduced into poultry houses, as abnormal bird mortality started near air inlets of the infected houses. This study modeled air movement trajectories and virus concentrations that were used to assess the probability or risk of airborne transmission for the 77 HPAI cases in Iowa. The results show that majority of the positive cases in Iowa might have received airborne virus, carried by fine particulate matter, from infected farms within the state (i.e., intrastate) and infected farms from the neighboring states (i.e., interstate). The modeled airborne virus concentrations at the Iowa recipient sites never exceeded the minimal infective doses for poultry; however, the continuous exposure might have increased airborne infection risks. In the worst-case scenario (i.e., maximum virus shedding rate, highest emission rate, and longest half-life), 33 Iowa cases had > 10% (three cases > 50%) infection probability, indicating a medium to high risk of airborne transmission for these cases. Probability of airborne HPAI infection could be affected by farm type, flock size, and distance to previously infected farms; and more importantly, it can be markedly reduced by swift depopulation and inlet air filtration. The research results provide insights into the risk of airborne transmission of HPAI virus via fine dust particles and the importance of preventative and containment strategies such as air filtration and quick depopulation of infected flocks.

Neighbourhood contacts and trade movements drive the regional spread of bovine viral diarrhoea virus (BVDV)

To explore the regional spread of endemic pathogens, investigations are required both at within and between population levels. The bovine viral diarrhoea virus (BVDV) is such a pathogen, spreading among cattle herds mainly due to trade movements and neighbourhood contacts, and causing an endemic disease with economic consequences. To assess the contribution of both transmission routes on BVDV regional and local spread, we developed an original epidemiological model combining data-driven and mechanistic approaches, accounting for heterogeneous within-herd dynamics, animal movements and neighbourhood contacts. Extensive simulations were performed over 9 years in an endemic context in a French region with high cattle density. The most uncertain model parameters were calibrated on summary statistics of epidemiological data, highlighting that neighbourhood contacts and within-herd transmission should be high. We showed that neighbourhood contacts and trade movements complementarily contribute to BVDV spread on a regional scale in endemically infected and densely populated areas, leading to intense fade-out/colonization events: neighbourhood contacts generate the vast majority of outbreaks (72%) but mostly in low immunity herds and correlated to a rather short presence of persistently infected animals (P); trade movements generate fewer infections but could affect herds with higher immunity and generate a prolonged presence of P. Both movements and neighbourhood contacts should be considered when designing control or eradication strategies for densely populated region.

Genetic analysis identifies potential transmission of low pathogenic avian influenza viruses between poultry farms

Poultry can become infected with low pathogenic avian influenza (LPAI) viruses via (in)direct contact with infected wild birds or by transmission of the virus between farms. This study combines routinely collected surveillance data with genetic analysis to assess the contribution of between‐farm transmission to the overall incidence of LPAI virus infections in poultry. Over a 10‐year surveillance period, we identified 35 potential cases of between‐farm transmission in the Netherlands, of which 10 formed geographical clusters. A total of 21 LPAI viruses were isolated from nine potential between‐farm transmission cases, which were further studied by genetic and epidemiological analysis. Whole genome sequence analysis identified close genetic links between infected farms in seven cases. The presence of identical deletions in the neuraminidase stalk region and minority variants provided additional indications of between‐farm transmission. Spatiotemporal analysis demonstrated that genetically closely related viruses were detected within a median time interval of 8 days, and the median distance between the infected farms was significantly shorter compared to farms infected with genetically distinct viruses (6.3 versus 69.0 km; p < 0.05). The results further suggest that between‐farm transmission was not restricted to holdings of the same poultry type and not related to the housing system. Although separate introductions from the wild bird reservoir cannot be excluded, our study indicates that between‐farm transmission occurred in seven of nine virologically analysed cases. Based on these findings, it is likely that between‐farm transmission contributes considerably to the incidence of LPAI virus infections in poultry.

Identifying outbreaks of Porcine Epidemic Diarrhea virus through animal movements and spatial neighborhoods

The spread of pathogens in swine populations is in part determined by movements of animals between farms. However, understanding additional characteristics that predict disease outbreaks and uncovering landscape factors related to between-farm spread are crucial steps toward risk mitigation. This study integrates animal movements with environmental risk factors to identify the occurrence of porcine epidemic diarrhea virus (PEDV) outbreaks. Using weekly farm-level incidence data from 332 sow farms, we applied machine-learning algorithms to quantify associations between risk factors and PEDV outbreaks with the ultimate goal of training predictive models and to identify the most important factors associated with PEDV occurrence. Our best algorithm was able to correctly predict whether an outbreak occurred during one-week periods with >80% accuracy. The most important predictors included pig movements into neighboring farms. Other important neighborhood attributes included hog density, environmental and weather factors such as vegetation, wind speed, temperature, and precipitation, and topographical features such as slope. Our neighborhood-based approach allowed us to simultaneously capture disease risks associated with long-distance animal movement as well as local spatial dynamics. The model presented here forms the foundation for near real-time disease mapping and will advance disease surveillance and control for endemic swine pathogens in the United States.

RETRACTED: An epidemiological investigation of associated risk factors with equine influenza (H3N8) epidemic 2015-16 in Pakistan

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been retracted at the request of the Editors-in-Chief. The article duplicates significant parts of a paper that had already appeared in Preventative Veterinary Medicine, 149, 132-139; https://doi.org/10.1016/j.prevetmed.2017.12.005. One of the conditions of submission of a paper for publication is that authors declare explicitly that the paper has not been previously published and is not under consideration for publication elsewhere. Re-use of any data should be appropriately cited. As such this article represents a misuse of the scientific publishing system. The scientific community takes a very strong view on this matter and apologies are offered to readers of the journal that this was not detected during the submission process.

Dynamics of the 2004 avian influenza H5N1 outbreak in Thailand: The role of duck farming, sequential model fitting and control

The Highly Pathogenic Avian Influenza (HPAI) subtype H5N1 virus persists in many countries and has been circulating in poultry, wild birds. In addition, the virus has emerged in other species and frequent zoonotic spillover events indicate that there remains a significant risk to human health. It is crucial to understand the dynamics of the disease in the poultry industry to develop a more comprehensive knowledge of the risks of transmission and to establish a better distribution of resources when implementing control. In this paper, we develop a set of mathematical models that simulate the spread of HPAI H5N1 in the poultry industry in Thailand, utilising data from the 2004 epidemic. The model that incorporates the intensity of duck farming when assessing transmision risk provides the best fit to the spatiotemporal characteristics of the observed outbreak, implying that intensive duck farming drives transmission of HPAI in Thailand. We also extend our models using a sequential model fitting approach to explore the ability of the models to be used in “real time” during novel disease outbreaks. We conclude that, whilst predictions of epidemic size are estimated poorly in the early stages of disease outbreaks, the model can infer the preferred control policy that should be deployed to minimise the impact of the disease.

Spatio-temporal patterns of highly pathogenic avian influenza virus subtype H5N8 spread, France, 2016 to 2017

IntroductionFrance is one of Europe's foremost poultry producers and the world's fifth largest producer of poultry meat. In November 2016, highly pathogenic avian influenza (HPAI) virus subtype H5N8 emerged in poultry in the country. As of 23 March 2017, a total of 484 confirmed outbreaks were reported, with consequences on animal health and socio-economic impacts for producers. Methods: We examined the spatio-temporal distribution of outbreaks that occurred in France between November 2016 and March 2017, using the space-time K-function and space-time permutation model of the scan statistic test. Results: Most outbreaks affected duck flocks in south-west France. A significant space-time interaction of outbreaks was present at the beginning of the epidemic within a window of 8 km and 13 days. This interaction disappeared towards the epidemic end. Five spatio-temporal outbreak clusters were identified in the main poultry producing areas, moving sequentially from east to west. The average spread rate of the epidemic front wave was estimated to be 5.5 km/week. It increased from February 2017 and was negatively associated with the duck holding density. Conclusion: HPAI-H5N8 infections varied over time and space in France. Intense transmission events occurred at the early stages of the epidemic, followed by long-range jumps in the disease spread towards its end. Findings support strict control strategies in poultry production as well as the maintenance of high biosecurity standards for poultry holdings. Factors and mechanisms driving HPAI spread need to be further investigated.

Health risks from exposure to Legionella in reclaimed water aerosols: Toilet flushing, spray irrigation, and cooling towers

The use of reclaimed water brings new challenges for the water industry in terms of maintaining water quality while increasing sustainability. Increased attention has been devoted to opportunistic pathogens, especially Legionella pneumophila, due to its growing importance as a portion of the waterborne disease burden in the United States. Infection occurs when a person inhales a mist containing Legionella bacteria. The top three uses for reclaimed water (cooling towers, spray irrigation, and toilet flushing) that generate aerosols were evaluated for Legionella health risks in reclaimed water using quantitative microbial risk assessment (QMRA). Risks are compared using data from nineteen United States reclaimed water utilities measured with culture-based methods, quantitative PCR (qPCR), and ethidium-monoazide-qPCR. Median toilet flushing annual infection risks exceeded 10^-4 considering multiple toilet types, while median clinical severity infection risks did not exceed this value. Sprinkler and cooling tower risks varied depending on meteorological conditions and operational characteristics such as drift eliminator performance. However, the greatest differences between risk scenarios were due to 1) the dose response model used (infection or clinical severity infection) 2) population at risk considered (residential or occupational) and 3) differences in laboratory analytical method. Theoretical setback distances necessary to achieve a median annual infection risk level of 10^-4 are proposed for spray irrigation and cooling towers. In both cooling tower and sprinkler cases, Legionella infection risks were non-trivial at potentially large setback distances, and indicate other simultaneous management practices could be needed to manage risks. The sensitivity analysis indicated that the most influential factors for variability in risks were the concentration of Legionella and aerosol partitioning and/or efficiency across all models, highlighting the importance of strategies to manage Legionella occurrence in reclaimed water.

Airborne Detection of H5N8 Highly Pathogenic Avian Influenza Virus Genome in Poultry Farms, France

In southwestern France, during the winter of 2016-2017, the rapid spread of highly pathogenic avian influenza H5N8 outbreaks despite the implementation of routine control measures, raised the question about the potential role of airborne transmission in viral spread. As a first step to investigate the plausibility of that transmission, air samples were collected inside, outside and downwind from infected duck and chicken facilities. H5 avian influenza virus RNA was detected in all samples collected inside poultry houses, at external exhaust fans and at 5 m distance from poultry houses. For three of the five flocks studied, in the sample collected at 50-110 m distance, viral genomic RNA was detected. The measured viral air concentrations ranged between 4.3 and 6.4 log₁₀ RNA copies per m³, and their geometric mean decreased from external exhaust fans to the downwind measurement point. These findings are in accordance with the possibility of airborne transmission and question the procedures for outbreak depopulation.

Impacts of Intensive Livestock Production on Human Health in Densely Populated Regions

In several regions worldwide, the presence of livestock in close proximity to residential areas raises questions about public health implications. The rapid expansion of large-scale livestock farms, increasingly interwoven with urbanized areas, and its potential impact on neighboring residents' health has hardly been accompanied by any research. The current situation in densely populated livestock farming areas could be regarded as a "natural experiment." Most scientific and public health initiatives have focused on emerging zoonoses and antimicrobial resistance as potential health threats. In this commentary, we emphasize the importance of respiratory health effects of noninfectious air pollutant emissions from livestock farms.

The simulated air flow pattern around a moving animal transport vehicle as the basis for a prospective biosecurity risk assessment

Research that investigates bioaerosol emissions from animal transport vehicles (ATVs) and their importance in the spread of harmful airborne agents while the ATVs travel on roads is limited. To investigate the dynamical behaviour of theoretically released particles from a moving ATV, the open-source computational fluid dynamics (CFD) software OpenFOAM was used to calculate the external and internal air flow fields with passive and forced ventilated openings of a common ATV moving at a speed of 80 km/h. In addition to a computed flow rate of approximately 40,000 m3/h crossing the interior of the ATV, the visualization of the trajectories has demonstrated distinct patterns of the spatial distribution of potentially released bioaerosols in the vicinity of the ATV. Although the front openings show the highest air flow to the outside, the recirculations of air masses between the interior of the ATV and the atmosphere also occur, which complicate the emission and the dispersion characterizations. To specify the future emission rates of ATVs, a database of bioaerosol concentrations within the ATV is necessary in conjunction with high-performance computing resources to simulate the potential dispersion of bioaerosols in the environment.

Human Q fever incidence is associated to spatiotemporal environmental conditions

Airborne pathogenic transmission from sources to humans is characterised by atmospheric dispersion and influence of environmental conditions on deposition and reaerosolisation. We applied a One Health approach using human, veterinary and environmental data regarding the 2009 epidemic in The Netherlands, and investigated whether observed human Q fever incidence rates were correlated to environmental risk factors. We identified 158 putative sources (dairy goat and sheep farms) and included 2339 human cases. We performed a high-resolution (1 × 1 km) zero-inflated regression analysis to predict incidence rates by Coxiella burnetii concentration (using an atmospheric dispersion model and meteorological data), and environmental factors - including vegetation density, soil moisture, soil erosion sensitivity, and land use data - at a yearly and monthly time-resolution. With respect to the annual data, airborne concentration was the most important predictor variable (positively correlated to incidence rate), followed by vegetation density (negatively). The other variables were also important, but to a less extent. High erosion sensitive soils and the land-use fractions "city" and "forest" were positively correlated. Soil moisture and land-use "open nature" were negatively associated. The geographical prediction map identified the largest Q fever outbreak areas. The hazard map identified highest hazards in a livestock dense area. We conclude that environmental conditions are correlated to human Q fever incidence rate. Similar research with data from other outbreaks would be needed to more firmly establish our findings. This could lead to better estimations of the public health risk of a C. burnetii outbreak, and to more detailed and accurate hazard maps that could be used for spatial planning of livestock operations.

Spread of Coxiella burnetii between dairy cattle herds in an enzootic region: modelling contributions of airborne transmission and trade

Q fever, a worldwide zoonotic disease caused by Coxiella burnetii, is a looming concern for livestock and public health. Epidemiological features of inter-herd transmission of C. burnetii in cattle herds by wind and trade of cows are poorly understood. We present a novel dynamic spatial model describing the inter-herd regional spread of C. burnetii in dairy cattle herds, quantifying the ability of airborne transmission and animal trade in C. burnetii propagation in an enzootic region. Among all the new herd infections, 92% were attributed to airborne transmission and the rest to cattle trade. Infections acquired following airborne transmission were shown to cause relatively small and ephemeral intra-herd outbreaks. On the contrary, disease-free herds purchasing an infectious cow experienced significantly higher intra-herd prevalence. The results also indicated that, for short duration, both transmission routes were independent from each other without any synergistic effect. The model outputs applied to the Finistère department in western France showed satisfactory sensitivity (0.71) and specificity (0.80) in predicting herd infection statuses at the end of one year in a neighbourhood of 3 km around expected incident herds, when compared with data. The model developed here thus provides important insights into the spread of C. burnetii between dairy cattle herds and paves the way for implementation and assessment of control strategies.

Aerosol Disinfection Capacity of Slightly Acidic Hypochlorous Acid Water Towards Newcastle Disease Virus in the Air: An In Vivo Experiment

Existence of bioaerosol contaminants in farms and outbreaks of some infectious organisms with the ability of transmission by air increase the need for enhancement of biosecurity, especially for the application of aerosol disinfectants. Here we selected slightly acidic hypochlorous acid water (SAHW) as a candidate and evaluated its virucidal efficacy toward a virus in the air. Three-day-old conventional chicks were challenged with 25 doses of Newcastle disease live vaccine (B1 strain) by spray with nebulizer (particle size <3 μm in diameter), while at the same time reverse osmosis water as the control and SAHW containing 50 or 100 parts per million (ppm) free available chlorine in pH 6 were sprayed on the treated chicks with other nebulizers. Exposed chicks were kept in separated cages in an isolator and observed for clinical signs. Oropharyngeal swab samples were collected from 2 to 5 days postexposure from each chick, and then the samples were titrated with primary chicken kidney cells to detect the virus. Cytopathic effects were observed, and a hemagglutination test was performed to confirm the result at 5 days postinoculation. Clinical signs (sneezing) were recorded, and the virus was isolated from the control and 50 ppm treatment groups, while no clinical signs were observed in and no virus was isolated from the 100 ppm treatment group. The virulent Newcastle disease virus (NDV) strain Sato, too, was immediately inactivated by SAHW containing 50 ppm chlorine in the aqueous phase. These data suggest that SAHW containing 100 ppm chlorine can be used for aerosol disinfection of NDV in farms.

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.

Dynamics of Escherichia coli Virulence Factors in Dairy Herds and Farm Environments in a Longitudinal Study in the United States

Pathogenic Escherichia coli or its associated virulence factors have been frequently detected in dairy cow manure, milk, and dairy farm environments. However, it is unclear what the long-term dynamics of E. coli virulence factors are and which farm compartments act as reservoirs. This study assessed the occurrence and dynamics of four E. coli virulence factors (eae, stx1, stx2, and the gamma allele of the tir gene [γ-tir]) on three U.S. dairy farms. Fecal, manure, water, feed, milk, and milk filter samples were collected from 2004 to 2012. Virulence factors were measured by postenrichment quantitative PCR (qPCR). All factors were detected in most compartments on all farms. Fecal and manure samples showed the highest prevalence, up to 53% for stx and 21% for γ-tir in fecal samples and up to 84% for stx and 44% for γ-tir in manure. Prevalence was low in milk (up to 1.9% for stx and 0.7% for γ-tir). However, 35% of milk filters were positive for stx and 20% were positive for γ-tir. All factors were detected in feed and water. Factor prevalence and levels, expressed as qPCR cycle threshold categories, fluctuated significantly over time, with no clear seasonal signal independent from year-to-year variability. Levels were correlated between fecal and manure samples, and in some cases autocorrelated, but not between manure and milk filters. Shiga toxins were nearly ubiquitous, and 10 to 18% of the lactating cows were potential shedders of E. coli O157 at least once during their time in the herds. E. coli virulence factors appear to persist in many areas of the farms and therefore contribute to transmission dynamics.

Wind-Mediated Spread of Low-Pathogenic Avian Influenza Virus into the Environment during Outbreaks at Commercial Poultry Farms

Avian influenza virus-infected poultry can release a large amount of virus-contaminated droppings that serve as sources of infection for susceptible birds. Much research so far has focused on virus spread within flocks. However, as fecal material or manure is a major constituent of airborne poultry dust, virus-contaminated particulate matter from infected flocks may be dispersed into the environment. We collected samples of suspended particulate matter, or the inhalable dust fraction, inside, upwind and downwind of buildings holding poultry infected with low-pathogenic avian influenza virus, and tested them for the presence of endotoxins and influenza virus to characterize the potential impact of airborne influenza virus transmission during outbreaks at commercial poultry farms. Influenza viruses were detected by RT-PCR in filter-rinse fluids collected up to 60 meters downwind from the barns, but virus isolation did not yield any isolates. Viral loads in the air samples were low and beyond the limit of RT-PCR quantification except for one in-barn measurement showing a virus concentration of 8.48 x 10(4) genome copies/m(3). Air samples taken outside poultry barns had endotoxin concentrations of ~50 EU/m(3) that declined with increasing distance from the barn. Atmospheric dispersion modeling of particulate matter, using location-specific meteorological data for the sampling days, demonstrated a positive correlation between endotoxin measurements and modeled particulate matter concentrations, with an R(2) varying from 0.59 to 0.88. Our data suggest that areas at high risk for human or animal exposure to airborne influenza viruses can be modeled during an outbreak to allow directed interventions following targeted surveillance.