Measuring airborne microorganisms and dust from livestock houses

Airborne transmission has been suspected to be responsible for epidemics of highly infectious disease in livestock production. In such transmission, the pathogenic microorganisms may associate with dust particles. However, the extent to which airborne transmission plays a role in the spread of diseases between farms, and the relationship between microorganisms and dust remain unclear. In order to better understand airborne transmission and to set up effective control techniques, this study investigated the performance of multi-stage air scrubbers on the reduction of emissions of microorganisms and dust from pig houses, and to evaluate the effectiveness and efficiency of different sampling devices for collecting microorganisms and dust. In winter, multi-stage scrubbers reduced emissions of airborne total bacteria by between 46% and 85%, PM10 by between 61% and 93%, PM2.5 by between 47% and 90%, and ammonia by between 70% and 100%. The EU reference dust sampler with an impaction pre-separator, which was designed for sampling dust in ambient air, could not be used to sample PM2.5 in livestock houses where dust concentrations were high, because overloading occurred. A sampler with a cyclone pre-separator was more tolerant of dust loads in livestock houses and was validated as a reference equivalent sampler. The method for evaluating the efficiency of bioaerosol samplers for airborne microorganisms was appropriate. It calculated the physical and biological sampling efficiencies separately, by excluding the viability losses in the non-sampling processes. The Andersen six-stage impactor, the All Glass Impinger (AGI-30) and the MD-8 had higher physical efficiencies than the OMNI-3000. The Andersen impactor and the AGI-30 had high (100%) biological efficiencies on sampling all five aerosolized microbial species (Enterococcus faecalis, Escherichia coli, Campylobacter jejuni, Mycoplasma synoviae and Gumboro vaccine virus). C. jejuni and Gumboro vaccine virus were inactivated by the OMNI-3000 during sampling, whereas E. coli and C. jejuni were inactivated by MD8. As a result, these two bioaerosol samplers had lower biological efficiencies. Although recipient broilers became infected, no culturable airborne Campylobacter were detected by the Andersen impactor, the AGI-30 and the OMNI-3000 in an airborne transmission of Campylobacter in broilers. From this study we concluded that installing multi-stage scrubbers at the air exhausts makes it possible to appreciably reduce aerial pollutant emissions from livestock production systems. As PM samplers with cyclone pre-separators are less vulnerable to high dust loadings, it is recommended that they are used to sample dust in livestock production systems. The efficiency of the bioaerosol samplers varies according to the microbial species sampled. Suitable samplers can be selected on the basis of their efficiencies and detection limits. Low aerial concentrations of specific microbial species are difficult to detect with current bioaerosol samplers. Knowledge gaps still exist throughout the process of long-distance airborne transmission of microorganisms, from suspension and transportation to deposition and infection. </p

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Health care facility ventilation design greatly affects disease transmission by aerosols. The desire to control infection in hospitals and at the same time to reduce their carbon footprint motivates the use of unconventional solutions for building design and associated control measures. This paper considers indoor sources and types of infectious aerosols, and pathogen viability and infectivity behaviors in response to environmental conditions. Aerosol dispersion, heat and mass transfer, deposition in the respiratory tract, and infection mechanisms are discussed, with an emphasis on experimental and modeling approaches. Key building design parameters are described that include types of ventilation systems (mixing, displacement, natural and hybrid), air exchange rate, temperature and relative humidity, air flow distribution structure, occupancy, engineered disinfection of air (filtration and UV radiation), and architectural programming (source and activity management) for health care facilities. The paper describes major findings and suggests future research needs in methods for ventilation design of health care facilities to prevent airborne infection risk

Risk of Listeria monocytogenes ingestion in consuming coleslaw purchased from food vendors in the Accra metropolis

It is very important that in managing food safety risks, the food, associated pathogen(s) and/or situations that lead to food borne illness are identified. It is also important to determine the magnitude of impact the risk has on public health (risk assessment). The microbial hazard Listeria monocytogenes has been associated with the vegetable cabbage (Brassica oleracea) and coleslaw an example of minimally processed vegetables with cabbage forming the predominant vegetable. This study was carried out to determine the prevalence and concentration of Listeria monocytogenes in fresh cabbage obtained from informal markets and commercially prepared ready-to-eat (RTE) coleslaw from food vendors in the Accra Metropolis. Detection and enumeration of L. monocytogenes was done using the 2009 edition of Health Protection Agency of Wales, UK standards for detection and enumeration of Listeria spp. To determine the magnitude of the impact of this hazard on public health, an exposure assessment through consumer survey was conducted with 300 vegetable consumers to determine how much (serving size) and how often (frequency/consumption rate) minimally processed vegetables such as coleslaw were consumed. Washing and/or decontamination of vegetables is an important step in managing the identified hazard (or risk). Thus the study determined the effectiveness of some common washing and decontamination methods on reducing the contamination level by Listeria monocytogenes in fresh cabbage. Results from the survey suggested that 55% of respondents consumed about one soup ladle (approximately 80g) of minimally processed vegetables including coleslaw on daily basis. Listeria monocytogenes was detected in 23 out of 24 samples of fresh cabbage (95.8% prevalence rate) obtained from informal markets and road side stalls. The prevalence rate for ready-to-eat coleslaw was 80.1%. Mean concentration of the pathogen in fresh cabbage was determined to be 29.79 ± 0.4 cfu/25g of fresh cabbage; RTE coleslaw had 25.51 ± 0.5 cfu/25g of RTE coleslaw. Risk assessment was conducted using the probabilistic approach. Data obtained from the detection and enumeration analysis were fitted into the risk model together with certain factors that influence the food beginning from farm till it reached the consumer (farm-to-fork). Using Monte Carlo simulations, the risk of ingesting Listeria monocytogenes on consuming commercially prepared coleslaw obtained from food vendors in Accra Metropolis was estimated as 90%. Although some washing methods in terms of concentration of disinfectant, pH and temperature reduced contamination level by L. monocytogenes; log reductions were not statistically significant (P > 0.05). Contact time between cabbage and washing solution (irrespective of concentration of disinfectant, pH and temperature) significantly reduced (P = 0.044) contamination level by the hazard

Using mathematical models to develop tuberculosis control strategies in Bangladesh

Md Abdul Kuddus used mathematical modelling to investigate the transmission of tuberculosis in Bangladesh, and identify optimal intervention strategies. He found that without rapid improvements in treatment quality the incidence of drug-resistant tuberculosis will continue to rise; whilst reasonable scale-ups of existing control measures can eliminate all tuberculosis in Bangladesh

Infectious diseases among animals : combining models with data

To eradicate or control the spread of infectious diseases, knowledge on the spread of the infection between (groups of) animals is necessary. Models can include such information and can subsequently be used to observe the efficacy of various control measures in fighting the infection. However, the availability of information and data to build and quantify these models is essential for applying such models in real life. In this thesis, models on the spread of infectious diseases in animals are always combined with data concerning the host, the infectious agent, their interactions and often also case data from epidemic or endemic disease situations. To do so, various infections that are present in the Netherlands are discussed. We show that for Phocine Distemper Virus (PDV) the data of the epidemic in 1988 show that clustering of animals has a strong influence on the transmission and survival of the animals. A previously applied model to analyse the seal situation did not fit the data very well. A model that incorporates the clustering of the animals on sand banks gave a better fit. Due to their clustering, the death rate was higher than could be expected from the first model. To control and eradicate Infectious Bovine Rhinotracheitis (IBR) it is known that the persistence of the infection in previously infected animals may cause a delay in eradication. We have quantified the probability for such a virus to reactivate in the field, and combined that with a model that calculates the expected time to extinction. Thus, control measures in the eradication process can easily be compared for efficacy and a time frame can be defined. The control of BSE was an important issue in the last decade, but due to limited data, exact advice was difficult to find. By quantifying the transmission parameters, the various control measures can be compared for efficacy. Now that more information is available concerning risks for humans and cattle, optimisation of the surveillance and control can be introduced based on such models. The age distribution of BSE cases offers information on the efficacy of BSE control in the past, but also concerning the prevalence of the infection in the future. Risk assessment and modelling are especially important for countries that would like to prove the absence of BSE in their country. Monitoring of an animal disease situation may have many purposes, for instance to prove freedom from infection for a certain farm or country. In the last chapter of the thesis, we give an opening for extended modelling to quantify the risk of missing a new outbreak in a country that has the Free from disease status. An integrated approach of transmission models that specifically includes the frequency of sampling over time enables us to calculate the probability that an epidemic escapes from detectio

Investigation into the changing colonisation of skin bacteria during isotretinoin treatment for acne vulgaris

Poster presentatio

Predictive modelling of climate change impacts on disease dynamics in Tanzania

Climate and the environment are key determinants impacting various aspects of disease transmission, including lifecycle, survivability and prevalence. Recent changes in both the long-term climatology, and short term El Niño events are impacting the spatial distribution of disease, increasing the number of people being at higher risk of contracting fatal diseases. These changes are particularly detrimental in developing countries, where socioeconomic conditions hinder access to disease prevention and treatment. This thesis explores climate, environment and disease interactions using multiple epidemiological modelling methodologies to develop an informative framework within which disease risk can be assessed, to aid decision-making. Statistical analysis of the impact of extreme events indicate that El Niño has a significant impact on the Tanzanian climate, which differs by location. Spatial modelling results demonstrate that by 2050 under RCP 8.5 mean malaria risk will initially reduce by 4.7%, which then reverses to an increase of 8.9% in 2070. Overall, analysis indicates increases in mean malaria risk. Biological modelling indicates that the predicted increases in malaria risk are likely a result of the reduction in time taken to complete the sporogonic and gonotrophic cycles due to increasingly optimum environmental conditions. The novel approach applied here contributes the development of a new model in environmental epidemiology. This thesis concludes that epidemiological modelling results could be beneficial in aiding decision makers to prepare for the impact of climate and environmental change, with a recommendation to continue research in this area with a particular focus on understudied and developing countries

Spatially-Explicit Agent-Based Modeling of Ecosystem Change and Epizootiological Impacts on Caribbean Spiny Lobster, \u3ci\u3ePanulirus argus\u3c/i\u3e

Agent-based models explicitly incorporate interactions and variation at the individual level, just as in the real world. As a result, agent-based models are realistic, intuitive, and generally less complex mathematically than their analytical counterparts. Their primary disadvantage is the large amount of detailed data required to construct and parameterize them. Although the use of agent-based simulation is increasing in ecology, they are highly specific, so are rarely used for development of theory. To demonstrate the flexibility and utility of this approach I developed a multi-species, agent-based, spatially-explicit model of the spiny lobster nursery of southern Florida that incorporates changing salinities, temperatures, and harmful algal blooms, and used it to evaluate the likely consequences of changes in hydrology due to the Comprehensive Everglades Restoration Program on the spiny lobster and associated hard-bottom communities. I found that water quality changes associated with the restoration effort will likely reduce lobster recruitment in Florida Bay 6–24% and will likely prevent the restoration of loggerhead sponges and vase sponges on which the lobster depends for shelter in Florida Bay. Then, I extended the model, incorporating disease dynamics appropriate to Panulirus argus Virus 1, including disease states, contact transmission, and two density-independent transmission mechanisms, to explore the effects of changes in host sociality on disease dynamics. I showed that when susceptible hosts avoid diseased conspecifics in a manner consistent with that demonstrated by P. argus in a system dominated by contact transmission, persistence of the disease requires an exogenous source. I also examined the effects of increased host aggregation on disease transmission. I found that in the absence of disease avoidance, outbreaks occurred rapidly, and by the end of the 10 year simulation, PaV1 was maintained continuously at unrealistically high levels. However, the disease avoidance behavior reduced simulated outbreak intensities and durations, and in the absence of other sources of PaV1, resulted in extinction of the disease within five years. Both the density independent infection of EBJs and the simulated arrival of infected cohorts of postlarvae maintained the disease in the larger population as a consequence of the long period between exposure and death