Evaluating infection risks and importance of hand hygiene during the household laundry process using a quantitative microbial risk assessment approach.

BACKGROUND: Contaminated laundry contributes to infectious disease spread in residential and home health care settings. The objectives were to (1) evaluate pathogen transmission risks for individuals doing laundry, and (2) compare hand hygiene timing to reduce risks. METHODS: A quantitative microbial risk assessment using experimental data from a laundry washing effectiveness study was applied to estimate infection risks from SARS-CoV-2, rotavirus, norovirus, nontyphoidal Salmonella, and Escherichia coli in 4 laundry scenarios: 1 baseline scenario (no hand hygiene event) and 3 hand hygiene scenarios (scenario 1: after moving dirty clothes to the washing machine, scenario 2: after moving washed clothes to the dryer, and scenario 3: hand hygiene events following scenario 1 and 2). RESULTS: The average infection risks for the baseline scenario were all greater than 2 common risk thresholds (1.0×10-6and 1.0×10-4). For all organisms, scenario 1 yielded greater risk reductions (39.95%-99.86%) than scenario 2 (1.35%-55.25%). Scenario 3 further reduced risk, achieving 1.0×10-6(SARS-CoV-2) and 1.0×10-4risk thresholds (norovirus and E. coli). CONCLUSIONS: The modeled results suggest individuals should reduce hand-to-facial orifice (eyes, nose, and mouth) contacts and conduct proper hand hygiene when handling contaminated garments. More empirical data are needed to confirm the estimated risks. DATA AVAILABILITY STATEMENT: The data and code that support the findings of this study can be retrieved via a Creative Commons Zero v1.0 Universal license in GitHub at https://github.com/yhjung1231/Laundry-QMRAproject-2022.git DOI: http://doi.org/10.5281/zenodo.7122065.

The Changing Job of School Nurses during the COVID-19 Pandemic: A Media Content Analysis of Contributions to Stress.

School nurses and unlicensed assistive personnel (UAPs) are essential to the health and wellness of school children. However, most US schools do not have a full-time licensed nurse. During the COVID-19 pandemic, school nurses and UAPs have been integral in ensuring that the health needs of students were met. They have seen a marked increase in their responsibilities included implementing COVID-19 mitigation strategies, screening for symptoms, testing students and staff, conducting contact tracing and data collection, and ensuring the implementation of rapidly changing COVID-19 guidelines and protocols for schools. The objective of this study was to explore COVID-19 occupational changes and their contributions to stress among school nurses and UAPs through a content analysis of local and national media articles. A Google search of articles published between February 2020 and September 2021 was conducted using the following search terms: 'school nurse', 'COVID-19', 'health aide', 'stress', and 'experiences'. A search was also conducted in Nexis Uni. Articles were included if the topic discussed school nurses or UAPs and COVID-19. All articles that examined nurses in other settings were excluded from the review. We examined topics and themes temporally (from February 2020 to September 2021) and spatially (i.e. the frequency by US state). Overall, 496 media articles discussing school nurses and COVID-19 were included in our review. The highest volume of articles was from September 2021 (22%, 111/496). Other months with relatively high volume of articles included August 2020 (9%, 43/496), January 2021 (10%, 47/496), February 2021 (9%, 44/496), and August 2021 (8%, 39/496). These larger article volumes coincided with notable COVID-19 events, including returning to school in the fall (August 2020 and August 2021), school nurses assisting with vaccine rollouts among adults in the USA (January/February 2021), concerns regarding the delta variant (August/September 2021), and vaccine rollouts for children ages 12-15 (September 2021). The representation of articles spatially (national, state, regional, or local) was 66 (13%) articles at national level, 217 (44%) state level, 25 (5%) regional level, and 188 (38%) local news at the city and/or village level. Pennsylvania had the highest frequency of articles, but when standardized to the state population, Alaska had the highest rate of media per 100 000 people. Three major themes were identified in our analysis: (i) safety; (ii) pandemic-related fatigue/stress; and (iii) nursing shortage/budget. The most represented theme for articles before September 2021 was that of safety. Over time, the themes of pandemic-related fatigue/stress and nursing shortage/budget increased with the most notable increase being in September 2021. The COVID-19 pandemic has resulted in new occupational risks, burdens, and stressors experienced by school nurses and UAPs. School nurses play a critical role in disease surveillance, disaster preparedness, wellness and chronic disease prevention interventions, immunizations, mental health screening, and chronic disease education. Furthermore, they provide a safety net for our most vulnerable children. Given that school nurses were already over-burdened and under-resourced prior to the pandemic, characterization of these new burdens and stressors will inform emergency preparedness resources for school health personnel during future pandemics or outbreaks.

A Novel Application of Risk-Risk Tradeoffs in Occupational Health: Nurses' Occupational Asthma and Infection Risk Perceptions Related to Cleaning and Disinfection during COVID-19.

BACKGROUND: Nurses face the risk of new onset occupational asthma (OA) due to exposures to cleaning and disinfection (C&D) agents used to prevent infections in healthcare facilities. The objective of this study was to measure nurses' preferences when presented with simultaneous OA and respiratory viral infection (e.g., COVID-19) risks related to increased/decreased C&D activities. METHODS: Nurses working in healthcare for ≥1 year and without physician-diagnosed asthma were recruited for an online anonymous survey, including four risk-risk tradeoff scenarios between OA and respiratory infection with subsequent recovery (Infect and Recovery) or subsequent death (Infect and Death). Nurses were presented with baseline risks at hypothetical "Hospital 1", and were asked to choose Hospital 2 (increased OA risk to maintain infection risk), Hospital 3 (increased infection risk to maintain OA risk), or indicate that they were equally happy. RESULTS: Over 70% of nurses were willing to increase infection risk to maintain baseline OA risk if they were confident they would recover from the infection. However, even when the risk of infection leading to death was much lower than OA, most nurses were not willing to accept a larger (but still small) risk of death to avoid doubling their OA risk. Age, work experience, and ever having contracted or knowing anyone who has contracted a respiratory viral infection at work influenced choices. CONCLUSIONS: We demonstrate the novel application of a risk-risk tradeoff framework to address an occupational health issue. However, more data are needed to test the generalizability of the risk preferences found in this specific risk-risk tradeoff context.

Quantifying SARS-CoV-2 Infection Risk Within the Google/Apple Exposure Notification Framework to Inform Quarantine Recommendations.

Most early Bluetooth-based exposure notification apps use three binary classifications to recommend quarantine following SARS-CoV-2 exposure: a window of infectiousness in the transmitter, ≥15 minutes duration, and Bluetooth attenuation below a threshold. However, Bluetooth attenuation is not a reliable measure of distance, and infection risk is not a binary function of distance, nor duration, nor timing. We model uncertainty in the shape and orientation of an exhaled virus-containing plume and in inhalation parameters, and measure uncertainty in distance as a function of Bluetooth attenuation. We calculate expected dose by combining this with estimated infectiousness based on timing relative to symptom onset. We calibrate an exponential dose-response curve based on infection probabilities of household contacts. The probability of current or future infectiousness, conditioned on how long postexposure an exposed individual has been symptom-free, decreases during quarantine, with shape determined by incubation periods, proportion of asymptomatic cases, and asymptomatic shedding durations. It can be adjusted for negative test results using Bayes' theorem. We capture a 10-fold range of risk using six infectiousness values, 11-fold range using three Bluetooth attenuation bins, ∼sixfold range from exposure duration given the 30 minute duration cap imposed by the Google/Apple v1.1, and ∼11-fold between the beginning and end of 14 day quarantine. Public health authorities can either set a threshold on initial infection risk to determine 14-day quarantine onset, or on the conditional probability of current and future infectiousness conditions to determine both quarantine and duration.

Barriers to COVID-19 Intervention Implementation in K-5 Classrooms: A Survey of Teachers from a District with Mask Mandates despite a Statewide Mask Mandate Ban.

The study objective was to characterize K-5 teachers' risk perceptions and experiences with CDC COVID-19 classroom guidance in an Arizona school district with a mask mandate, conflicting with a statewide mask mandate ban. METHODS: Public school teachers (n = 111) were recruited between 14 December 2021, and 31 January 2022, for an anonymous online survey with questions on seven important topics related to: (1) population demographics, (2) teachers' perceptions of COVID-19 in the workplace, (3) masks, (4) physical distancing, (5) surface transmission routes, (6) air flow, and (7) contact tracing protocols. Descriptive statistics were calculated, and statistically significant differences in categorical responses by grade level taught were investigated with Fisher's exact test. RESULTS: There were 76 complete responses. No significant differences across grade levels were found. More than half (53%, 43/81) reported not feeling protected from occupational COVID-19 exposure. Lack of mask usage/enforcement was the most frequently listed reason (40%, 17/42). Physical distancing barriers included large student-teacher ratios. CONCLUSIONS: Consistent mask guidance at state and local levels, increased financial support, and lower student-teacher ratios may improve the implementation of CDC guidance for classrooms. Conflicting statewide and district-level school mask policies may negatively impact teachers' risk perceptions.

What Risks Does the Residential Laundry Process Pose?: A Quantitative Microbial Risk Assessment (QMRA) Study

Fomites are an important pathway for infectious disease spread in residential and home healthcare settings (i.e., nursing, assisted living, and retirement communities). Many healthcare professionals launder work clothes at home that may be contaminated by contact with infected patients. Through quantitative microbial risk assessment (QMRA), the study objectives were to (1) evaluate pathogen transmission risks for those doing laundry, and (2) compare infection control interventions to reduce laundering risks. A simulation model was used to evaluate exposure events related to laundry process. One baseline scenario (no handwashing) and three handwashing scenarios (scenario 1: after moving dirty clothes to washing machine, scenario 2: after moving wet clothes to dryer, scenario 3: after both of these previous steps) were evaluated. Each scenario involved a single user, three contacts with contaminated laundry, and three contacts with the face. Five representative microorganisms known to spread via intra-familial transmission were modeled: SARS-CoV-2, rotavirus, norovirus, nontyphoidal Salmonella, and Escherichia coli. The mean infection risks for the baseline scenario were all above a 1 in 1,000,000 risk threshold: 7.22 × 10

Transmission of Respiratory Viral Diseases to Health Care Workers: COVID-19 as an Example.

Health care workers (HCWs) can acquire infectious diseases, including coronavirus disease 2019 (COVID-19), from patients. Herein, COVID-19 is used with the source-pathway-receptor framework as an example to assess evidence for the roles of aerosol transmission and indirect contact transmission in viral respiratory infectious diseases. Evidence for both routes is strong for COVID-19 and other respiratory viruses, but aerosol transmission is likely dominant for COVID-19. Key knowledge gaps about transmission processes and control strategies include the distribution of viable virus among respiratory aerosols of different sizes, the mechanisms and efficiency by which virus deposited on the facial mucous membrane moves to infection sites inside the body, and the performance of source controls such as face coverings and aerosol containment devices. To ensure that HCWs are adequately protected from infection, guidelines and regulations must be updated to reflect the evidence that respiratory viruses are transmitted via aerosols.

Feasibility of a High-Volume Filter Sampler for Detecting SARS-CoV-2 RNA in COVID-19 Patient Rooms.

Aerosolization of SARS-CoV-2 by COVID-19 patients can put healthcare workers and susceptible individuals at risk of infection. Air sampling for SARS-CoV-2 has been conducted in healthcare settings, but methods vary widely and there is need for improvement. The objective of this study was to evaluate the feasibility of using a high-volume filter sampler, BioCapture z720, to detect SARS-CoV-2 in COVID-19 patient rooms in a medical intensive care unit, a dedicated COVID-19 ward, and at nurses' stations. In some locations, the BioSpot-VIVAS, known for high efficiency in the collection of virus-containing bioaerosols, was also operated. The samples were processed for SARS-CoV-2 RNA with multi-plex nested polymerase chain reaction. One of 28 samples collected with the high-volume filter sampler was positive for SARS-CoV-2; all 6 samples collected with BioSpot-VIVAS were negative for SARS-CoV-2. The high-volume filter sampler was more portable and less intrusive in patient rooms than the BioSpot-VIVAS, but limits of detection remain unknown for this device. This study will inform future work to evaluate the reliability of these types of instruments and inform best practices for their use in healthcare environments for SARS-CoV-2 air sampling.

Modeling fomite-mediated SARS-CoV-2 exposure through personal protective equipment doffing in a hospital environment.

Self-contamination during doffing of personal protective equipment (PPE) is a concern for healthcare workers (HCW) following SARS-CoV-2-positive patient care. Staff may subconsciously become contaminated through improper glove removal; so, quantifying this exposure is critical for safe working procedures. HCW surface contact sequences on a respiratory ward were modeled using a discrete-time Markov chain for: IV-drip care, blood pressure monitoring, and doctors' rounds. Accretion of viral RNA on gloves during care was modeled using a stochastic recurrence relation. In the simulation, the HCW then doffed PPE and contaminated themselves in a fraction of cases based on increasing caseload. A parametric study was conducted to analyze the effect of: (1a) increasing patient numbers on the ward, (1b) the proportion of COVID-19 cases, (2) the length of a shift, and (3) the probability of touching contaminated PPE. The driving factors for the exposure were surface contamination and the number of surface contacts. The results simulate generally low viral exposures in most of the scenarios considered including on 100% COVID-19 positive wards, although this is where the highest self-inoculated dose is likely to occur with median 0.0305 viruses (95% CI =0-0.6 viruses). Dose correlates highly with surface contamination showing that this can be a determining factor for the exposure. The infection risk resulting from the exposure is challenging to estimate, as it will be influenced by the factors such as virus variant and vaccination rates.

Comparing approaches for modelling indirect contact transmission of infectious diseases.

Mathematical models describing indirect contact transmission are an important component of infectious disease mitigation and risk assessment. A model that tracks microorganisms between compartments by coupled ordinary differential equations or a Markov chain is benchmarked against a mechanistic interpretation of the physical transfer of microorganisms from surfaces to fingers and subsequently to a susceptible person's facial mucosal membranes. The primary objective was to compare these models in their estimates of doses and changes in microorganism concentrations on hands and fomites over time. The abilities of the models to capture the impact of episodic events, such as hand hygiene, and of contact patterns were also explored. For both models, greater doses were estimated for the asymmetrical scenarios in which a more contaminated fomite was touched more often. Differing representations of hand hygiene in the Markov model did not notably impact estimated doses but affected pathogen concentration dynamics on hands. When using the Markov model, losses due to hand hygiene should be handled as separate events as opposed to time-averaging expected losses. The discrete event model demonstrated the effect of hand-to-mouth contact timing on the dose. Understanding how model design influences estimated doses is important for advancing models as reliable risk assessment tools.

Respirators, face masks, and their risk reductions via multiple transmission routes for first responders within an ambulance.

First responders may have high SARS-CoV-2 infection risks due to working with potentially infected patients in enclosed spaces. The study objective was to estimate infection risks per transport for first responders and quantify how first responder use of N95 respirators and patient use of cloth masks can reduce these risks. A model was developed for two Scenarios: an ambulance transport with a patient actively emitting a virus in small aerosols that could lead to airborne transmission (Scenario 1) and a subsequent transport with the same respirator or mask use conditions, an uninfected patient; and remaining airborne SARS-CoV-2 and contaminated surfaces due to aerosol deposition from the previous transport (Scenario 2). A compartmental Monte Carlo simulation model was used to estimate the dispersion and deposition of SARS-CoV-2 and subsequent infection risks for first responders, accounting for variability and uncertainty in input parameters (i.e., transport duration, transfer efficiencies, SARS-CoV-2 emission rates from infected patients, etc.). Infection risk distributions and changes in concentration on hands and surfaces over time were estimated across sub-Scenarios of first responder respirator use and patient cloth mask use. For Scenario 1, predicted mean infection risks were reduced by 69%, 48%, and 85% from a baseline risk (no respirators or face masks used) of 2.9 × 10-2 ± 3.4 × 10-2 when simulated first responders wore respirators, the patient wore a cloth mask, and when first responders and the patient wore respirators or a cloth mask, respectively. For Scenario 2, infection risk reductions for these same Scenarios were 69%, 50%, and 85%, respectively (baseline risk of 7.2 × 10-3 ± 1.0 × 10-2). While aerosol transmission routes contributed more to viral dose in Scenario 1, our simulations demonstrate the ability of face masks worn by patients to additionally reduce surface transmission by reducing viral deposition on surfaces. Based on these simulations, we recommend the patient wear a face mask and first responders wear respirators, when possible, and disinfection should prioritize high use equipment.

Modeling COVID-19 infection risks for a single hand-to-fomite scenario and potential risk reductions offered by surface disinfection.

We used a quantitative microbial risk assessment approach to relate log10 disinfection reductions of SARS-CoV-2 bioburden to COVID-19 infection risks. Under low viral bioburden, minimal log10 reductions may be needed to reduce infection risks for a single hand-to-fomite touch to levels lower than 1:1,000,000, as a risk comparison point. For higher viral bioburden conditions, log10 reductions of more than 2 may be needed to achieve median infection risks of less than 1:1,000,000.