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Abstract: Indoor event locations are particularly affected by the SARS-CoV-2 pandemic. At large venues, only incomplete risk assessments exist, whereby no suitable measures can be derived. In this study, a physical and data-driven statistical model for a comprehensive infection risk assessment has been developed. At venues displacement ventilation concepts are often implemented. Here simplified theoretical assumptions fail for the prediction of relevant airflows for airborne transmission processes. Thus, with locally resolving trace gas measurements infection risks are computed more detailed. Coupled with epidemiological data such as incidences, vaccination rates, test sensitivities, and audience characteristics such as masks and age distribution, predictions of new infections (mean), situational R-values (mean), and individual risks on- and off-seat can be achieved for the first time. Using the Stuttgart State Opera as an example, the functioning of the model and its plausibility are tested and a sensitivity analysis is performed with regard to masks and tests. Besides a reference scenario on 2022-11-29, a maximum safety scenario with an obligation of FFP2 masks and rapid antigen tests as well as a minimum safety scenario without masks and tests are investigated. For these scenarios the new infections (mean) are 10.6, 0.25 and 13.0, respectively. The situational R-values (mean) - number of new infections caused by a single infectious person in a certain situation - are 2.75, 0.32 and 3.39, respectively. Besides these results a clustered consideration divided by age, masks and whether infections occur on-seat or off-seat are presented. In conclusion this provides an instrument that can enable policymakers and operators to take appropriate measures to control pandemics despite ongoing mass gathering events
The importance of distance to infectious source in spreading Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is undeniable. Since the COVID-19 outbreak, there has been a growing scholarship investigating its dynamics of spread using modelling. While this literature has thoroughly studied the effect of social distancing and infectious droplets profile on infection spread, there exists a gap, where distance as an independent parameter is studied, considering the behaviour and location of individuals. Distance can be analyzed independently of transmission routes, the size of droplets, the distance that droplets can travel and the air-circulation state in the indoor areas. In this thesis the probability of getting infected for each individual was modeled as a function of their distance to source and contact time. Data from three early pandemic outbreaks were used to choose the best candidate among the suggested models. Then we found the maximum likelihood estimator (MLE) of model parameters for each of these datasets. Four methods were used for calculating the confidence and credible intervals of the MLE values, since some of these methods did not provide valid results. The credible interval result of two out of three datasets show that increasing distance to the infectious source, in indoor spaces with the air-circulation system turned on, reduces the probability of getting infected. These results can be useful for studying similar infectious diseases, simulating the probability of getting infected in similar environments, finding effective baseline distances that result in low infection risks and informing policy makers on how they could craft policies which could slow down/stop such infections from spreading.
Provides the latest QMRA methodologies to determine infection risk cause by either accidental microbial infections or deliberate infections caused by terrorism • Reviews the latest methodologies to quantify at every step of the microbial exposure pathways, from the first release of a pathogen to the actual human infection • Provides techniques on how to gather information, on how each microorganism moves through the environment, how to determine their survival rates on various media, and how people are exposed to the microorganism • Explains how QMRA can be used as a tool to measure the impact of interventions and identify the best policies and practices to protect public health and safety • Includes new information on genetic methods • Techniques use to develop risk models for drinking water, groundwater, recreational water, food and pathogens in the indoor environment
In 2003, the word "coronavirus" spread across the globe, somewhat further than the virus that sparked the panic. In this book, expert researchers examine these devastating viruses through 23 state-of-the-art, widely applicable protocols with minute detail. Comprehensive and cutting-edge, the book serves as an ideal guide for all virologists and especially for those working with coronaviruses. Written by international experts, this book is relevant to a wide array of professions.
Issues for 1906-17 include reports on plague investigation in India, 6th-10th reports; and Plague supplements, no. 1-5; and Parasitology v.1-5.
Students spend much of their time in classrooms. In the face of the COVID-19 pandemic, understanding and reducing infectious disease transmission risk in indoor spaces such as classrooms is top priority. This research employed a spreadsheet-based disease transmission risk model to estimate the transmission risk of the SARS-CoV-2 virus that causes COVID-19 under varying classroom scenarios and in specific classes and classrooms at the University of Wyoming (UW). The conditions assessed include the effect of masking on disease transmission risk, how infection risk varies with community prevalence and ventilation rates, how class sizes affect COVID-19 risk, and how COVID-19 disease varies with population immunity. As COVID-19 spread, UW facilities dramatically increased building ventilation rates to help reduce the spread of the air-borne virus that causes COVID-19 by increasing air turnover (while also filtering the air) which my results suggest was a highly effective strategy. A secondary objective of this study was to survey carbon dioxide (CO2) concentrations in indoor public areas in Laramie, Wyoming. The highest carbon dioxide concentration found was in a bar at night (1290 ppm) and the lowest was in a grocery store during the day (779 ppm). Bars had the highest overall concentrations of CO2 at all times of the day. By contrast, measures taken in the UW classrooms sampled as part of the primary study showed a maximum CO2 concentration of 802 ppm even when fully occupied and at the end of a class period, illustrating the effectiveness of UW’s ventilation systems.
Disasters such as earthquakes, cyclones, floods, heat waves, nuclear accidents, and large scale pollution incidents take lives and cause exceptionally large health problems. The majority of large-scale disasters affect the most vulnerable populations, which are often comprised of people of extreme ages, in remote living areas, with endemic poverty, and with low literacy. Health-related emergency disaster risk management (Health-EDRM) [1] refers to the systematic analysis and management of health risks surrounding emergencies and disasters; it plays an important role in reducing hazards and vulnerability along with extending preparedness, response, and recovery measures. This concept encompasses risk analyses and interventions, such as accessible early warning systems, timely deployment of relief workers, and the provision of suitable drugs and medical equipment, to decrease the impact of disaster on people before, during, and after disaster events. Disaster risk profiling and interventions can be at the personal/household, community, and system/political levels; they can be targeted at specific health risks including respiratory issues caused by indoor burning, re-emergence of infectious disease due to low vaccination coverage, and gastrointestinal problems resulting from unregulated waste management. Unfortunately, there has been a major gap in the scientific literature regarding Health-EDRM. The aim of this Special Issue of IJERPH was to present papers describing/reporting the latest disaster and health risk analyses, as well as interventions for health-related disaster risk management, in an effort to address this gap and facilitate major global policies and initiatives for disaster risk reduction.
This guideline defines ventilation and then natural ventilation. It explores the design requirements for natural ventilation in the context of infection control, describing the basic principles of design, construction, operation and maintenance for an effective natural ventilation system to control infection in health-care settings.