Microbial Risk Analysis最新文献

Pertussis (whooping cough) has been nearly eradicated during the 20th century, first of all due to an organized and comprehensive vaccination campaign that lasted for decades. Generations of doctors educated in Serbia (and other countries) rarely had an opportunity to see the clinical picture of pertussis. However, during 2023, the number of registered cases of pertussis in Serbia has increased several times. This is why the health authorities were forced to declare danger of an epidemic. During 2023, in Belgrade, around 1000 cases were registered. During the two months of 2024, 400 cases were registered. Some of them have ended with lethal outcome. This paper reports for the first time the biosynthesis reaction and thermodynamic properties of biosynthesis (enthalpy, entropy and Gibbs energy) of Bordetella pertussis, the cause of whooping cough. Moreover, a mechanistic model of multiplication of B. pertussis was developed. The mechanistic model was related to the pathogenesis of pertussis.

In the past two years, Covid-19 has emerged as the most severe and pressing public health issue, causing a great deal of damage to societal and economic welfare, as well as causing illness and mortality. The operators in wastewater treatment plants (WWTPs), particularly those employed in rural communities, appear to often exhibit a lack of adherence to proper safety protocols by not utilizing sufficient protective equipment while handling unprocessed sewage samples throughout the different phases of wastewater treatment and disposal. This study aimed at examining the potential health risk of infection among WWTP operators, as a result of unintentional ingestion of wastewater during routine duties in facilities that receive influent containing Severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) from various areas. This study examined the prevalence of SARS-CoV-2 in grab samples of untreated wastewater samples using the real-time quantitative polymerase chain reaction (RT-qPCR) technique and quantitative microbial risk assessment (QMRA) model was employed on three probable exposure of SARS-CoV-2 scenarios that are expressed as moderate, aggressive and extreme (2 mL, 10 mL, 20 mL) to evaluate the probability of infection to WWTP workers based on the 6 h that the workers spent in WWTPs performing their daily activities which exposed them to potential health risk of various pathogens. At the highest SARS-CoV-2 genome of 266.23 × 10² gc/mL, the findings indicated that there was no statistically significant difference in the probability of infections with respect to seasonal differences because the P(i) value was greater than 0.05 (p > 0.05). Overall, P(i) was highly significant across all volumetric scenarios in the study with p value that was p < 0.001. The probability of getting infected during the different seasons is assumed to be low since there was no statistically difference in P(i) with respect to season however it can be assumed that there is a high chance of getting infected regardless of volumetric intake. Our study suggests that the risk of accidental occupational exposure to SARS-CoV-2 in raw wastewater is negligible to workers whereby workers would perform their daily activities without wearing protective gear. Nevertheless, the importance and work of WWTPs by workers should not be overlooked. Regardless of the situation, it is widely recognized that residential wastewater poses a potential risk of infection due to the presence of several enteric pathogens, therefore, it is crucial to ensure that those who are occupationally exposed to untreated wastewater are well equipped with suitable personal protective equipment (PPE).

Greywater reuse is a strategy to address water scarcity, necessitating the selection of treatment processes that balance cost-efficiency and human health risks. A key aspect in evaluating these risks is understanding pathogen contamination levels in greywater, a complex task due to intermittent pathogen occurrences. To address this, faecal indicator organisms like E. coli are often monitored as proxies to evaluate faecal contamination levels and infer pathogen concentrations. However, the wide variability in faecal indicator concentrations poses challenges in their modelling for quantitative microbial risk assessment (QMRA). Our study critically assesses the adequacy of parametric models in predicting the variability in E. coli concentrations in greywater. We found that models that build on summary statistics, like medians and standard deviations, can substantially underestimate the variability in E. coli concentrations. More appropriate models may provide more accurate estimations of, and uncertainty around, peak E. coli concentrations. To demonstrate this, a Poisson lognormal distribution model is fit to a data set of E. coli concentrations measured in shower and laundry greywater sources. This model estimated arithmetic mean E. coli concentrations in laundry waters at approximately 1.0E + 06 MPN 100 mL⁻¹. These results are around 2.0 log₁₀ units higher than estimations from a previously used hierarchical lognormal model based on aggregated summary data from multiple studies. Such differences are considerable when assessing human health risks and setting pathogen reduction targets for greywater reuse. This research highlights the importance of making raw monitoring data available for more accurate statistical evaluations than those based on summary statistics. It also emphasizes the crucial role of model comparison, selection, and validation to inform policy-relevant outcomes.

Survival curves of bacterial vegetative cells or spores subjected to an inactivation process are often log-linear and then described by the d-value parameter. However, non log-linear, convex, shapes might be also observed particularly when mild inactivation treatments are applied. Our objective was to investigate whether the 3-parameters Weibull model (logN₀, $\delta$, p) could be used to go beyond a simple fitting of convex curve by providing information related to bacterial variability. First, survival curves were simulated to mimic the behaviour of a cocktail containing bacterial vegetative cells or spores undergoing an inactivation treatment, on which the Weibull model was fitted. Second, a mathematical model was developed to describe the link between the Weibull parameters p and delta with the d-values of sub-populations of bacterial vegetative cells or spores (considering as well the percentage of each sub-population). Based on this model, it was shown that the Weibull model can be used to go beyond a simple description of a convex curve. For instance, if p is estimated around 0.8, that means the presence of a resistant sub-population, but with a limited resistant variability (ratio of resistance from 1.5 to 4). In contrast, if p is estimated to 0.3–04 that means the presence of a resistant sub-population in a small proportion (less than 10 %) combined with a large resistant variability (ratio of 10 or more). This study shows that the Weibull model can be used in combination with the new model developed here to decipher vegetative cell or spore resistance variability, with application in food industry processes such as thermal or physical inactivation treatment as well as cleaning and disinfection verification procedure.

For thousands of years, medicine has made efforts to study and heal infectious diseases. For centuries, medicine and biology have attempted to study the mechanisms of development of infectious diseases. For 100 years, virology has tried to understand and describe different viruses and reveal the secrets of pathophysiology of infections. Several decades ago, the efforts of biomedical scientists were joined by chemists. Since then viruses have been explored not only as biological systems, but also as chemical systems. With the beginning of the COVID-19 pandemic, biothermodynamics has made its contribution to the research on driving forces and mechanisms of lifecycles of viruses, the virus-host interaction. Since then, viruses have been analyzed as biological, chemical and thermodynamic systems. After reporting of chemical and thermodynamic properties of SARS-CoV, MERS-CoV, SARS-CoV-2, Ebola, Mpox, West Nile virus and bacteriophages, this paper reports for the first time the empirical formulas (unit carbon formulas) of Rotavirus A, as well as its thermodynamic properties of virus-host interaction at the membrane (antigen-receptor binding) and virus-host interaction in the cytoplasm (virus multiplication). The virus-host interactions are essentially chemical reactions, the driving force of which is Gibbs energy (of binding and biosynthesis).

A question is often asked about what tomorrow brings. During the last 4 years of the COVID-19 pandemic, this question was asked with every appearance of a new SARS-CoV-2 variant. It seems that science has an ability to offer a relatively reliable answer. Theoretical and experimental research have allowed a deep insight into structure and function of SARS-CoV-2. Moreover, the developed mechanistic models allow prediction of virus-host interactions. In August 2023, the Omicron BA.2.86 Pirola variant was detected. Taught by the bad experience from 2019 to 2023, when every new variant that appeared during SARS-CoV-2 evolution has caused a new pandemic wave, the question was raised whether this will be the case with the new variant. Research presented in this paper shows that the driving force for antigen-receptor binding of the Omicron BA.2.86 variant is lower than that of the BN.1 and similar to that of the other variants. Based on the presented research, it seems that the new variant will not be more aggressive relative to the previous variants. The movement in the number of newly infected cases in USA in the period between August and mid-October 2023 is in favor of this prediction.

Airborne viral transmission in confined spaces, such as elevators, could lead to the spread of diseases such as COVID-19. A quantitative study of viral transmission in enclosed spaces, with a focus on assessing the efficacy of the present ventilation methods is hard to find. Additionally, there is a lack of guidelines for viral dispersion. The non-availability of such information reduces overall effectiveness in controlling the spread of the virus. A properly designed ventilation system for the elevator car will benefit in both pandemic situations as well as non-pandemic situations, especially for people using hospital elevators. For better control of the airborne viral transmission spread, it is essential to study the airflow in elevator cars. Exposure to high-emitter coughing for one minute by a SARS-CoV-2-infected person in an elevator can increase the risk of the virus reaching the lungs by generating a viral load that may remain airborne for a long time. There is little that has been considered for lessening the anticipated viral load in the elevator car. In this paper, we use a two-step approach. The first step is the risk assessment, and the second is risk mitigation. The risk is assessed by computing the probable viral load a healthy passenger will be subjected to during the typical travel in an elevator car contaminated by the ride of an infectious person. It is seen that the ventilation provided as per the minimum permissible requirements by various international codes is inadequate to maintain the viral load in the elevator car below the risky levels. To come up with the risk mitigation strategies, the required ventilation in the car was computed using a Computational Fluid Dynamics (CFD) model. Further, mathematical models are developed to enable quick calculations during the design of the elevator car ventilation system. Our CFD study shows that in the case of a 20-passenger capacity elevator car, with doors open, a 2000 Cubic Feet per Minute (CFM) airflow will disperse most of the viral load in less than one minute. In this paper, we give easy-to-follow design guidelines, and mathematical models to enable quick calculations during the design of the elevator car ventilation system. This study is useful for practicing engineers to achieve effective ventilation of the elevator car to curtail the spread of viral transmission.

Brazilian sheep farming is an ancient socioeconomic activity of great importance for maintaining income and generating family employment. Brazil is the largest producer of sheep in South America, making it a strategic country for the control of infectious diseases such as scrapie. In the present study, scrapie was officially reported in 74 cases in nine Brazilian states between 2005 and 2021. Among all Brazilian regions, the South with 54.06 % (40/74), the Midwest with 28.38 % (21/74), and the Southeast with 16.21 % (12/74) stood out with higher relative frequencies in the number of cases of the disease. Among the states, Santa Catarina presented 35.14 % of the notified cases, and the risk of incidence (IR) was 91.9 per 100,000 sheep. The years with the highest reported cases were 2012 (17 cases and IR = 2.11) and 2017 (16 cases and IR = 6.17). There was the formation of a primary cluster in the year 2017, formed only by the state of Santa Catarina, with relative risk (RRs) = 313.97, and a secondary cluster formed by the states of Mato Grosso, Mato Grosso do Sul, Goiás, Tocantins, Minas Gerais, and São Paulo in the period from 2006 to 2009, with RRs = 27.92. All of the states with reported cases shared borders, demonstrating the disease's ability to spread across state lines. Scrapie must be prevented from spreading in Brazil by implementing active surveillance measures.

Since 2019, when it appeared in Wuhan, in the wild type form later labeled Hu-1, SARS-CoV-2 mutated dozens of times and evolved towards increase in infectivity and decrease or maintenance of constant pathogenicity through dozens of variants. The last of them are Omicron EG.5 and EG.5.1. Until 2019, an empirical formula was known only for the poliovirus. Until now empirical formulas and thermodynamic properties were reported for all variants of SARS-CoV-2 and some other viruses. Also, models were developed that describe the biothermodynamic background of SARS-CoV-2 interaction with its human host. With every new mutation in SARS-CoV-2, the question is raised about the further evolution of the virus. This paper reports for the first time empirical formulas and molar masses of Omicron EG.5 and EG.5.1 variants, as well as thermodynamic properties (enthalpy, entropy and Gibbs energy) of formation and biosynthesis. Moreover, the driving force of virus multiplication was analyzed, as well as multiplication rate and pathogenicity of Omicron EG.5 and EG.5.1.

From July to October, West Nile virus is the leading cause of mosquito born disease in Europe and North America. This paper reports for the first time a chemical and thermodynamic analysis of the West Nile virus particles, genome and proteins, as well as interactions with its host organism. The empirical formula of mature West Nile virus particles was found through the atom counting method. Based on the empirical formula, biosynthesis reactions were formulated, which describe the formation of new virus live matter. Based on the biosynthesis reactions, Gibbs energy of biosynthesis was determined, which represents the physical driving force for the production of viral and host cell components. Gibbs energy of biosynthesis of the West Nile virus was found to be several times more negative than that of its host tissues. Due to the more negative Gibbs energy of biosynthesis, the West Nile virus components are produced much faster than those of its host cells. This allows the virus to hijack the host cell metabolism. Therefore, the virus-host interactions of the West Nile virus were explained through chemical and thermodynamic analysis.