Dynamic assessment of the risk of airborne viral infection.
Ontology highlight
ABSTRACT:
SUBMITTER: Cammarata A
PROVIDER: S-EPMC8597137 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Human-infecting pathogens that transmit through the air pose a significant threat to public health. As a prominent instance, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused the COVID-19 pandemic has affected the world in an unprecedented manner over the past few years. Despite the dissipating pandemic gloom, the lessons we have learned in dealing with pathogen-laden aerosols should be thoroughly reviewed because the airborne transmission risk may have been grossly underestimated. From a bioanalytical chemistry perspective, on-site airborne pathogen detection can be an effective non-pharmaceutic intervention (NPI) strategy, with on-site airborne pathogen detection and early-stage infection risk evaluation reducing the spread of disease and enabling life-saving decisions to be made. In light of this, we summarize the recent advances in highly efficient pathogen-laden aerosol sampling approaches, bioanalytical sensing technologies, and the prospects for airborne pathogen exposure measurement and evidence-based transmission interventions. We also discuss open challenges facing general bioaerosols detection, such as handling complex aerosol samples, improving sensitivity for airborne pathogen quantification, and establishing a risk assessment system with high spatiotemporal resolution for mitigating airborne transmission risks. This review provides a multidisciplinary outlook for future opportunities to improve the on-site airborne pathogen detection techniques, thereby enhancing the preparedness for more on-site bioaerosols measurement scenarios, such as monitoring high-risk pathogens on airplanes, weaponized pathogen aerosols, influenza variants at the workplace, and pollutant correlated with sick building syndromes.
| S-EPMC10712221 | biostudies-literature
Project description:In the case of airborne diseases, pathogen copies are transmitted by droplets of respiratory tract fluid that are exhaled by the infectious that stay suspended in the air for some time and, after partial or full drying, inhaled as aerosols by the susceptible. The risk of infection in indoor environments is typically modelled using the Wells-Riley model or a Wells-Riley-like formulation, usually assuming the pathogen dose follows a Poisson distribution (mono-pathogen assumption). Aerosols that hold more than one pathogen copy, i.e. poly-pathogen aerosols, break this assumption even if the aerosol dose itself follows a Poisson distribution. For the largest aerosols where the number of pathogen in each aerosol can sometimes be several hundred or several thousand, the effect is non-negligible, especially in diseases where the risk of infection per pathogen is high. Here we report on a generalization of the Wells-Riley model and dose-response models for poly-pathogen aerosols by separately modeling each number of pathogen copies per aerosol, while the aerosol dose itself follows a Poisson distribution. This results in a model for computational risk assessment suitable for mono-/poly-pathogen aerosols. We show that the mono-pathogen assumption significantly overestimates the risk of infection for high pathogen concentrations in the respiratory tract fluid. The model also includes the aerosol removal due to filtering by the individuals which becomes significant for poorly ventilated environments with a high density of individuals, and systematically includes the effects of facemasks in the infectious aerosol source and sink terms and dose calculations.
| S-EPMC8031403 | biostudies-literature
Project description:OBJECTIVE:To determine the susceptibility of the endometrium to infection by-and thereby potential damage from-SARS-CoV-2. DESIGN:Analysis of SARS-Cov-2 infection-related gene expression from endometrial transcriptomic data sets. SETTING:Infertility research department affiliated with a public hospital. PATIENT(S):Gene expression data from five studies in 112 patients with normal endometrium collected throughout the menstrual cycle. INTERVENTION(S):None. MAIN OUTCOME MEASURE(S):Gene expression and correlation between viral infectivity genes and age throughout the menstrual cycle. RESULT(S):Gene expression was high for TMPRSS4, CTSL, CTSB, FURIN, MX1, and BSG; medium for TMPRSS2; and low for ACE2. ACE2, TMPRSS4, CTSB, CTSL, and MX1 expression increased toward the window of implantation. TMPRSS4 expression was positively correlated with ACE2, CTSB, CTSL, MX1, and FURIN during several cycle phases; TMPRSS2 was not statistically significantly altered across the cycle. ACE2, TMPRSS4, CTSB, CTSL, BSG, and MX1 expression increased with age, especially in early phases of the cycle. CONCLUSION(S):Endometrial tissue is likely safe from SARS-CoV-2 cell entry based on ACE2 and TMPRSS2 expression, but susceptibility increases with age. Further, TMPRSS4, along with BSG-mediated viral entry into cells, could imply a susceptible environment for SARS-CoV-2 entry via different mechanisms. Additional studies are warranted to determine the true risk of endometrial infection by SARS-CoV-2 and implications for fertility treatments.
| S-EPMC7298504 | biostudies-literature
Project description:In the last years, many studies have focused on risk assessment of exposure of workers to airborne particulate matter (PM). Several studies indicate a strong correlation between PM and adverse health outcomes, as a function of particle size. In the last years, the study of atmospheric particulate matter has focused more on particles less than 10 μm or 2.5 μm in diameter; however, recent studies identify in particles less than 0.1 μm the main responsibility for negative cardiovascular effects. The present paper deals with the determination of 66 organic compounds belonging to six different classes of persistent organic pollutants (POPs) in the ultrafine, fine and coarse fractions of PM (PM < 0.1 µm; 0.1 < PM < 2.5 µm and 2.5 < PM < 10 µm) collected in three outdoor workplaces and in an urban outdoor area. Data obtained were analyzed with principal component analysis (PCA), in order to underline possible correlation between sites and classes of pollutants and characteristic emission sources. Emission source studies are, in fact, a valuable tool for both identifying the type of emission source and estimating the strength of each contamination source, as useful indicator of environment healthiness. Moreover, both carcinogenic and non-carcinogenic risks were determined in order to estimate human health risk associated to study sites. Risk analysis was carried out evaluating the contribution of pollutant distribution in PM size fractions for all the sites. The results highlighted significant differences between the sites and specific sources of pollutants related to work activities were identified. In all the sites and for all the size fractions of PM both carcinogenic and non-carcinogenic risk values were below acceptable and safe levels of risks recommended by the regulatory agencies.
| S-EPMC8073354 | biostudies-literature
Project description:On-site quantification and early-stage infection risk assessment of airborne severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with high spatiotemporal resolution is a promising approach for mitigating the spread of coronavirus disease 2019 (COVID-19) pandemic and informing life-saving decisions. Here, a condensation (hygroscopic growth)-assisted bioaerosol collection and plasmonic photothermal sensing (CAPS) system for on-site quantitative risk analysis of SARS-CoV-2 virus-laden aerosols is presented. The CAPS system provided rapid thermoplasmonic biosensing results after an aerosol-to-hydrosol sampling process in COVID-19-related environments including a hospital and a nursing home. The detection limit reached 0.25 copies/µL in the complex aerosol background without further purification. More importantly, the CAPS system enabled direct measurement of the SARS-CoV-2 virus exposures with high spatiotemporal resolution. Measurement and feedback of the results to healthcare workers and patients via a QR-code are completed within two hours. Based on a dose-responseµ model, it is used the plasmonic biosensing signal to calculate probabilities of SARS-CoV-2 infection risk and estimate maximum exposure durations to an acceptable risk threshold in different environmental settings.
| S-EPMC9762303 | biostudies-literature
Project description:BACKGROUND:To develop an individually-tailored dynamic risk assessment model following a multistep, multifactorial process of the Correa's gastric cancer model. METHODS:First, we estimated the state-to-state transition rates following Correa's five-step carcinogenic model and assessed the effect of risk factors, including Helicobacter pylori infection, history of upper gastrointestinal disease, lifestyle, and dietary habits, on the step-by-step transition rates using data from a high-risk population in Matsu Islands, Taiwan. Second, we incorporated information on the gastric cancer carcinogenesis affected by genomic risk factors (including inherited susceptibility and irreversible genomic changes) based on literature to generate a genetic and epigenetic risk assessment model by using a simulated cohort identical to the Matsu population. The combination of conventional and genomic risk factors enables us to develop the personalized transition risk scores and composite scores. RESULTS:The state-by-state transition rates per year were 0.0053, 0.7523, 0.1750, and 0.0121 per year from normal mucosa to chronic active gastritis, chronic active gastritis to atrophic gastritis, atrophic gastritis to intestinal metaplasia, and intestinal metaplasia to gastric cancer, respectively. Compared with the median risk group, the most risky decile had a 5.22-fold risk of developing gastric cancer, and the least risky decile around one-twelfth of the risk. The median 10-year risk for gastric cancer incidence was 0.77%. The median lifetime risk for gastric cancer incidence was 5.43%. By decile, the 10-year risk ranged from 0.06 to 4.04% and the lifetime risk ranged from 0.42 to 21.04%. CONCLUSIONS:We demonstrate how to develop a personalized dynamic risk assessment model with the underpinning of Correa's cascade to stratify the population according to their risk for progression to gastric cancer. Such a risk assessment model not only facilitates the development of an individually-tailored preventive strategy with treatment for H. pylori infection and endoscopic screening but also provides short-term and long-term indicators to evaluate the program effectiveness.
| S-EPMC6245882 | biostudies-other
Project description:The threat of an influenza A virus pandemic stems from continual virus spillovers from reservoir species, a tiny fraction of which spark sustained transmission in humans. To date, no pandemic emergence of a new influenza strain has been preceded by detection of a closely related precursor in an animal or human. Nonetheless, influenza surveillance efforts are expanding, prompting a need for tools to assess the pandemic risk posed by a detected virus. The goal would be to use genetic sequence and/or biological assays of viral traits to identify those non-human influenza viruses with the greatest risk of evolving into pandemic threats, and/or to understand drivers of such evolution, to prioritize pandemic prevention or response measures. We describe such efforts, identify progress and ongoing challenges, and discuss three specific traits of influenza viruses (hemagglutinin receptor binding specificity, hemagglutinin pH of activation, and polymerase complex efficiency) that contribute to pandemic risk.
| S-EPMC5156527 | biostudies-literature
Project description:The role of personalized ventilation (PV) in protecting against airborne disease transmission between occupants was evaluated by considering two scenarios with different PV alignments. The possibility that PV may facilitate the transport of exhaled pathogens was explored by performing experiments with droplets and applying PV to a source or/and a target manikin. The risk of direct and indirect exposure to droplets in the inhalation zone of the target was estimated, with these exposure types defined according to their different origins. The infection risk of influenza A, a typical disease transmitted via air, was predicted based on a dose-response model. Results showed that the flow interactions between PV and the infectious exhaled flow would facilitate airborne transmission between occupants in two ways. First, application of PV to the source caused more than 90% of indirect exposure of the target. Second, entrainment of the PV jet directly from the infectious exhalation increased direct exposure of the target by more than 50%. Thus, these scenarios for different PV application modes indicated that continuous exposure to exhaled influenza A virus particles for 2 h would correspond with an infection probability ranging from 0.28 to 0.85. These results imply that PV may protect against infection only when it is maintained with a high ventilation efficiency at the inhalation zone, which can be realized by reduced entrainment of infectious flow and higher clean air volume. Improved PV design methods that could maximize the positive effects of PV on disease control in the human microenvironment are discussed.
| S-EPMC7260576 | biostudies-literature
Project description:ObjectiveThe relationship between specific humidity and influenza/SARS-CoV-2 in the Netherlands is evaluated over time and at regional level.DesignParametric and non-parametric correlation coefficients are calculated to quantify the relationship between humidity and influenza, using five years of weekly data. Bayesian spatio-temporal models-with a Poisson and a Gaussian likelihood-are estimated to find the relationship between regional humidity and the daily cases of SARS-CoV-2 in the municipalities and provinces of the Netherlands.ResultsAn inverse (negative) relationship is observed between specific humidity and the incidence of influenza between 2015 and 2019. The space-time analysis indicates that an increase of specific humidity of one gram of water vapor per kilogram of air (1 g/kg) is related to a reduction of approximately 5% in the risk of COVID-19 infections.ConclusionsThe increase in humidity during the outbreak of the SARS-CoV-2 in the Netherlands may have helped to reduce the risk of regional COVID-19 infections. Policies that lead to an increase in household specific humidity to over 6g/Kg will help reduce the spread of respiratory viruses such as influenza and SARS-CoV-2.
| S-EPMC8139177 | biostudies-literature
Project description:The lack of quantitative risk assessment of airborne transmission of COVID-19 under practical settings leads to large uncertainties and inconsistencies in our preventive measures. Combining in situ measurements and computational fluid dynamics simulations, we quantify the exhaled particles from normal respiratory behaviors and their transport under elevator, small classroom, and supermarket settings to evaluate the risk of inhaling potentially virus-containing particles. Our results show that the design of ventilation is critical for reducing the risk of particle encounters. Inappropriate design can significantly limit the efficiency of particle removal, create local hot spots with orders of magnitude higher risks, and enhance particle deposition causing surface contamination. Additionally, our measurements reveal the presence of a substantial fraction of faceted particles from normal breathing and its strong correlation with breathing depth.
| S-EPMC7493749 | biostudies-literature