Case Counts Research Articles

Comparison of Biochemical and Hematological Profiles in Patients of Extrapulmonary and Pulmonary Tuberculosis at a Tertiary Care Center.

Background Tuberculosis (TB) is a disease of global concern, especially in countries like India. Pulmonary TB (PTB) and extrapulmonary TB (EPTB) differ a lot when it comes to presentations, treatment, and outcomes. The biochemical and hematological test can serve as a marker reflecting the response to treatment in various types of TB, resulting in a better prognosis. Therefore, this study was conducted to compare the biochemical and hematological profiles in patients of extrapulmonary and pulmonary tuberculosis in adults and children. Methods TB cases were divided into four categories: PTB adult, EPTB adult, PTB pediatrics, and EPTB pediatrics. Forty-nine patients in each category were selected, resulting in a total of 196 patients. The sample size was met via convenience sampling. A total of 27 parameters were compared. Mann-Whitney U tests were used for statistical analysis. Results It was observed that serum calcium levels in PTB cases (11.65, 1.15; median and inter-quartile range (IQR), respectively) were significantly different from those in EPTB cases (9.18, 1.03; p<0.001). The median serum sodium levels in EPTB cases (139.49, 6.86) were higher than in PTB cases (130.10, 5.77; p<0.001). For total platelet count levels, a significant difference was observed between PTB (337.00, 180.75) and EPTB cases (278, 159.25; p=0.006). In EPTB cases, the total red blood count (RBC) count levels (4.47, 0.96) were higher than in PTB cases (4.24, 0.89; p=0.036). Biochemical and hematological parameters between pediatrics and adult age groups were compared, and it was observed that the median values (IQR) of serum phosphorus, total white blood cells (WBC), and platelet count in pediatric cases were 5.16 (1.09), 14.75 (6.03), and 350.00 (155.75), respectively, and were higher from those in adult cases 3.78 (0.97); 8.35 (6.66) and 264 (181.5), respectively (p<0.001). For serum creatinine levels, a significant rise was observed between PTB 0.54 (0.19) and EPTB cases 0.57 (0.16) (p<0.001).It was also observed that alanine transaminase (ALT) levels were higher in adults (18.90 (17.83)) than in the pediatric age group (24.70 (28.67); p=0.042) while alkaline phosphatase (ALP) was higher in the pediatric age group (108.95 (78.37)) than in adults (94.25 (47.92); p=0.003). Conclusion Serum calcium levels and total WBC counts were higher in PTB cases, while the levels of serum sodium and total RBC counts were higher in EPTB cases. ALT, serum phosphorus, total WBC counts, and total platelet counts were higher in the pediatric age group, while ALP, serum urea, and creatinine levels were higher in adults. Increased tissue damage and severity of disease in the pediatric age group, reactive thrombocytosis due to biogenesis in lungs, and abnormal anti-diuretic hormone secretion in PTB cases may be possible explanations for these findings. These findings may help clinicians in the early identification of potential complications, and further studies on these parameters should be conducted.

Tragedy or transformation? Online survey of nurse spirituality during the COVID pandemic.

To describe positive and negative spiritual responses to providing COVID-related nursing care among nurses working in hospitals. The COVID pandemic has intensified and publicised the threats to nurse well-being. Absent from the recommendations for promoting nurse well-being is recognition of how nurses' spirituality and/or religiosity is affected by the strain of COVID caring or how it may be affecting their well-being. Cross-sectional, descriptive observational, mixed methods study. Data were collected from 523 registered nurses employed in three Southern California hospitals during March-May, 2022 when these hospitals' COVID case counts were <15%. Using Online survey methods, data were obtained using the Religious/Spiritual Struggles Scale-Short Form, Moral Injury Symptom Scale-Healthcare Professionals, Post-traumatic Growth Inventory and demographic and work-related items. STROBE guidelines for cross-sectional observational studies were observed. The mean for religious/spiritual struggles was 1.98 (range of 1-5, comparable to a little bit). Although roughly half of the sample reported the struggles were not experienced/did not apply, 23%-36.5% reported experiencing these struggles at least somewhat. The most frequent struggle was to find ultimate meaning. The mean observed for moral injury was 6.5 (range of 1-10); applying established criteria indicated it was troubling for at least 50%. The mean for post-traumatic growth was 4 (on a scale of 0-6); using established criteria, 41% experienced PTG. Quantitative findings were illustrated by the qualitative responses that occasionally expressed spiritual tragedy and transformation concurrently. The professional work of nursing impacts nurses in invisible, spiritual ways that can be tragic and/or transformative. Interventions to address nurses' mental health challenges must include attention to these invisible struggles. Nurses' mental health challenges must be met in part by addressing how they can surmount spiritual tragedy-and allow spiritual transformation.

Estimating the propagation of both reported and undocumented COVID-19 cases in Spain: a panel data frontier approximation of epidemiological models.

We use a stochastic frontier analysis (SFA) approach to model the propagation of the COVID-19 epidemic across geographical areas. The proposed models permit reported and undocumented cases to be estimated, which is important as case counts are overwhelmingly believed to be undercounted. The models can be estimated using only epidemic-type data but are flexible enough to permit these reporting rates to vary across geographical cross-section units of observation. We provide an empirical application of our models to Spanish data corresponding to the initial months of the original outbreak of the virus in early 2020. We find remarkable rates of under-reporting that might explain why the Spanish Government took its time to implement strict mitigation strategies. We also provide insights into the effectiveness of the national and regional lockdown measures and the influence of socio-economic factors in the propagation of the virus.

Association of antiviral drugs and their possible mechanisms with DRESS syndrome using data mining algorithms.

Antiviral drugs are not known for drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome. The current study aims is to find out the association of antiviral drugs and their possible mechanism with DRESS.Data mining algorithmssuch as proportional reporting ratio that is, PRR (≥2) with associated χ2 value (>4), reporting odds ratio that is, ROR (≥2) with 95% confidence interval and case count (≥3) were calculated to identify a possible signal. Further, molecular docking studies were conducted to check the interaction of selected antiviral drugs with possible targets.The potential signal of DRESS was found to be associated with abacavir, acyclovir, ganciclovir, lamivudine, lopinavir, nevirapine, ribavirin, ritonavir, and zidovudine among all selected antiviral drugs. Further, subgroup analysis has also shown a potential signal in different age groups and gender. The sensitivity analysis results have shown a decrease in the strength of the signal, however, there was no significant impact on the outcome except for acyclovir. The docking results have indicated the possible involvement of human leukocyte antigen(HLA)*B1502 and HLA*B5801.The positive signal of DRESS was found with selected antiviral drugs except for acyclovir.

Elective Hand Surgery Is Delayed among Private Insurance Holders.

Patients with private healthcare plans often defer nonemergent or elective procedures toward the end of the year once they have met their deductible. No previous studies have evaluated how insurance status and hospital setting may affect surgical timing for upper extremity procedures. Our study aimed to evaluate the influence of insurance and hospital setting on end-of-the-year surgical cases for elective carpometacarpal (CMC) arthroplasty, carpal tunnel, cubital tunnel, and trigger finger release, and nonelective distal radius fixation. Insurance provider and surgical dates were gathered from two institutions' electronic medical records (one university, one physician-owned hospital) for those undergoing CMC arthroplasty, carpal tunnel release, cubital tunnel release, trigger finger release, and distal radius fixation from January 2010 to December 2019. Dates were converted into corresponding fiscal quarters (Q1-Q4). Using the Poisson exact test, comparisons were made between the case volume rate of Q1-Q3 and Q4 for private insurance and then for public insurance. Overall, case counts were greater in Q4 than the rest of the year at both institutions. There was a significantly greater proportion of privately insured patients undergoing hand and upper extremity surgery at the physician-owned hospital than the university center (physician owned: 69.7%, university: 50.3%; P < 0.001). Privately insured patients underwent CMC arthroplasty and carpal tunnel release at a significantly greater rate in Q4 compared with Q1-Q3 for both institutions. Publicly insured patients did not experience an increase in carpal tunnel releases during the same period at both institutions. Privately insured patients underwent elective CMC arthroplasty and carpal tunnel release procedures in Q4 at a significantly greater rate than publicly insured patients. This finding suggests private insurance status, and potentially deductibles, influence surgical decision making and timing. Further work is needed to evaluate the impact of deductibles on surgical planning and the financial and medical impact of delaying elective surgeries.

Impact of the COVID-19 Pandemic on the Reported Incidence of Select Bacterial Enteric Diseases in Canada, 2020.

The aim of this study was to describe the impact of the COVID-19 pandemic on reported cases and clusters of select enteric diseases in Canada, for the period of March 2020 to December 2020. Weekly counts of laboratory confirmed cases of Salmonella, Shigella, Shiga toxin-producing Escherichia coli (STEC), and Listeria monocytogenes were obtained from laboratory surveillance data. These data were supplemented with epidemiological information on the suspected source of illness, collected for cases identified within whole genome sequencing clusters. Incidence rate ratios were calculated for each pathogen. All data were compared with a prepandemic reference period. Decreases in the number of reported cases in 2020 compared with the previous 5-year period were noted for Salmonella, Shigella, Escherichia coli O157, and non-O157 STEC. Reported number of cases for L. monocytogenes in 2020 remained similar to those of the previous 5-year period. There was a considerable decline (59.9%) in the number of cases associated with international travel compared with a 10% decline in the number of domestic cases. Comparison of reported incidence rates of clustered versus sporadic cases for each pathogen showed little variation. This study represents the first formal assessment of the impact of COVID-19 on reported enteric diseases in Canada. Reported case counts across several pathogens saw notable declines in 2020 compared with prepandemic levels, with restrictions on international travel playing a key role. Additional research is needed to understand how limitations on social gatherings, lock downs, and other public health measures have impacted enteric diseases.

Nosocomial outbreaks of aseptic meningitis: A public health concern

Nosocomial outbreaks of aseptic meningitis: A public health concern

Abstract P110: Hypothalamic Amenorrhea Phenotype and Cardiovascular Disease Risk

Introduction: Hypothalamic amenorrhea (HA) is a neuroendocrine disorder characterized by ovulatory dysfunction, anovulation, and infertility, which can be prolonged for months to years. Menstrual cycle irregularity and amenorrhea identify individuals with higher CVD risk, but existing evidence has not examined HA separately from polycystic ovary syndrome (PCOS). It remains unknown whether HA is associated with CVD events across the lifecourse. Hypothesis: We hypothesized that the HA phenotype (oligo/amenorrhea without PCOS traits) would identify individuals at increased risk for CVD. Methods: Nurses’ Health Study II participants with available information on menstrual cycle characteristics who were premenopausal and free of CVD at baseline comprised the analytic sample (n=83,281). Menstrual cycle regularity was retrospectively reported for ages 18-22y on the baseline questionnaire in 1989 while the 1993 biennial questionnaire captured current menstrual cycle regularity (at ages 29-49y); PCOS traits (severe acne, hirsutism) were additionally ascertained in 1993. Participants were followed for confirmed incident CVD (MI, stroke, and fatal CHD) from 1993 through 2017. Cox proportional hazards models estimated hazard ratios (HR) and 95% confidence intervals (CI) for the relationship between HA and CVD, adjusted for age, race/ethnicity, parental education, parental history of CVD &lt;60y, and behavioral risk factors (smoking, physical activity, diet, alcohol intake, body mass index). Results: Thirteen percent of participants (n=11,071) ever had HA: 8.5% of participants (n=7,081) had HA at ages 18-22y while 6.5% (n=5,428) had HA at ages 29-46y. Persistent HA (HA at both 18-22y and 29-46 y) was identified in 1.7% of participants (n=1,438). CVD events occurred in 253 individuals who ever had HA (HA at either 18-22y or 29-46y) and 1,228 individuals without the HA phenotype. Individuals who ever had HA had a 20% higher rate of CVD (CI: 1.05-1.38). HA phenotype at ages 18-22y was not associated with CVD risk (HR=1.14; CI: 0.96-1.35) while HA phenotype at ages 29-46y was associated with a 30% higher rate of CVD (CI: 1.10-1.54) compared to individuals without HA phenotype. Individuals with persistent HA across both age ranges had a 69% higher rate of CVD (CI: 1.24-2.28). Underlying associations were strongest between ever HA and stroke (HR=1.25; CI: 1.03-1.51) and between persistent HA and CHD (HR=1.90; CI: 1.27-2.86), although case counts were small. Conclusions: HA phenotype in mid-adulthood identified individuals at increased risk of CVD compared to those without HA. As there are multiple HA subtypes, defined by varying combinations of psychosocial stress, anxiety, physical activity and weight loss, future studies should examine which HA subtypes are associated with CVD risk.

State and Federal Legislators' Responses on Social Media to the Mental Health and Burnout of Health Care Workers Throughout the COVID-19 Pandemic: Natural Language Processing and Sentiment Analysis.

Burnout and the mental health burden of the COVID-19 pandemic have disproportionately impacted health care workers. The links between state policies, federal regulations, COVID-19 case counts, strains on health care systems, and the mental health of health care workers continue to evolve. The language used by state and federal legislators in public-facing venues such as social media is important, as it impacts public opinion and behavior, and it also reflects current policy-leader opinions and planned legislation. The objective of this study was to examine legislators' social media content on Twitter and Facebook throughout the COVID-19 pandemic to thematically characterize policy makers' attitudes and perspectives related to mental health and burnout in the health care workforce. Legislators' social media posts about mental health and burnout in the health care workforce were collected from January 2020 to November 2021 using Quorum, a digital database of policy-related documents. The total number of relevant social media posts per state legislator per calendar month was calculated and compared with COVID-19 case volume. Differences between themes expressed in Democratic and Republican posts were estimated using the Pearson chi-square test. Words within social media posts most associated with each political party were determined. Machine-learning was used to evaluate naturally occurring themes in the burnout- and mental health-related social media posts. A total of 4165 social media posts (1400 tweets and 2765 Facebook posts) were generated by 2047 unique state and federal legislators and 38 government entities. The majority of posts (n=2319, 55.68%) were generated by Democrats, followed by Republicans (n=1600, 40.34%). Among both parties, the volume of burnout-related posts was greatest during the initial COVID-19 surge. However, there was significant variation in the themes expressed by the 2 major political parties. Themes most correlated with Democratic posts were (1) frontline care and burnout, (2) vaccines, (3) COVID-19 outbreaks, and (4) mental health services. Themes most correlated with Republican social media posts were (1) legislation, (2) call for local action, (3) government support, and (4) health care worker testing and mental health. State and federal legislators use social media to share opinions and thoughts on key topics, including burnout and mental health strain among health care workers. Variations in the volume of posts indicated that a focus on burnout and the mental health of the health care workforce existed early in the pandemic but has waned. Significant differences emerged in the content posted by the 2 major US political parties, underscoring how each prioritized different aspects of the crisis.

Implicit feedback policies for COVID-19: why “zero-COVID” policies remain elusive

Successful epidemic modeling requires understanding the implicit feedback control strategies used by populations to modulate the spread of contagion. While such strategies can be replicated with intricate modeling assumptions, here we propose a simple model where infection dynamics are described by a three parameter feedback policy. Rather than model individuals as directly controlling the contact rate which governs the spread of disease, we model them as controlling the contact rate’s derivative, resulting in a dynamic rather than kinematic model. The feedback policy used by populations across the United States which best fits observations is proportional-derivative control, where learned parameters strongly correlate with observed interventions (e.g., vaccination rates and mobility restrictions). However, this results in a non-zero “steady-state” of case counts, implying current mitigation strategies cannot eradicate COVID-19. Hence, we suggest making implicit policies a function of cumulative cases, resulting in proportional-integral-derivative control with higher potential to eliminate COVID-19.

Evaluation of Nuclear Parameters in Relation to Regional Lymph Node Involvement in Oral Squamous Cell Carcinoma: A Cytomorphometric Study

Background: Up-regulation of ribosome biogenesis encodes the factors related to carcinogenesis. It has been shown that the nucleus diameter and number of nucleoli increase from normal mucosa to oral squamous cell carcinoma (OSCC). The relationship between nuclear parameters and lymph node involvement in OSCC has not been established, yet. The aim of this study was to evaluate the nuclear parameters comprising nucleoli count and nucleus: nucleoli ratio in relation to regional lymph node involvement in OSCC. Methods: Thirty-four formalin-fixed, paraffin embedded sections from different histopathologic grades of OSCC were stained with methyl green-pyronin. Mean number of nucleoli and nucleus: nucleoli ratio were calculated in 100 tumor cells from 10 random selected fields and compared based on lymph node involvement. Results: Nucleoli count in cases with metastasis to regional lymph nodes was not significantly different from that in cases without regional lymph nodes involvement (P=0.29). The difference of nucleus: nucleoli ratio in cases with and without lymph nodes involvement were not significant (P=0.52). No significant correlation was found between the nucleoli count and lymph node involvement (r=0.08, P=0.78). The correlation between nucleus: nucleoli ratio and lymph node involvement was significant (r=0.58, P=0.02). Conclusion: The nucleus: nucleoli ratio of tumoral cells in OSCC was correlated to lymph node involvement. Based on the results, nucleus: nucleoli ratio can potentially be a useful tool to determine the lymph node involvement in OSCC.

Investigating the impact of environmental factors on West Nile virus human case prediction in Ontario, Canada.

West Nile virus is the most common mosquito borne disease in North America and the leading cause of viral encephalitis. West Nile virus is primarily transmitted between birds and mosquitoes while humans are incidental, dead-end hosts. Climate change may increase the risk of human infections as climatic variables have been shown to affect the mosquito life cycle, biting rate, incubation period of the disease in mosquitoes, and bird migration patterns. We develop a zero-inflated Poisson model to investigate how human West Nile virus case counts vary with respect to mosquito abundance and infection rates, bird abundance, and other environmental covariates. We use a Bayesian paradigm to fit our model to data from 2010-2019 in Ontario, Canada. Our results show mosquito infection rate, temperature, precipitation, and crow abundance are positively correlated with human cases while NDVI and robin abundance are negatively correlated with human cases. We find the inclusion of spatial random effects allows for more accurate predictions, particularly in years where cases are higher. Our model is able to accurately predict the magnitude and timing of yearly West Nile virus outbreaks and could be a valuable tool for public health officials to implement prevention strategies to mitigate these outbreaks.

Typhoid Fever Surveillance, Incidence Estimates, and Progress Toward Typhoid Conjugate Vaccine Introduction - Worldwide, 2018-2022.

Typhoid fever, an acute febrile illness caused by Salmonella enterica serovar Typhi (S. Typhi), is endemic in many low- and middle-income countries† (1). In 2015, an estimated 11-21 million typhoid fever cases and 148,000-161,000 associated deaths occurred worldwide (2). Effective prevention strategies include improved access to and use of infrastructure supporting safe water, sanitation, and hygiene (WASH); health education; and vaccination (1). The World Health Organization (WHO) recommends programmatic use of typhoid conjugate vaccines for typhoid fever control and prioritization of vaccine introduction in countries with the highest typhoid fever incidence or high prevalence of antimicrobial-resistant S. Typhi (1). This report describes typhoid fever surveillance, incidence estimates, and the status of typhoid conjugate vaccine introduction during 2018-2022. Because routine surveillance for typhoid fever has low sensitivity, population-based studies have guided estimates of case counts and incidence in 10 countries since 2016 (3-6). In 2019, an updated modeling study estimated that 9.2 million (95% CI = 5.9-14.1) typhoid fever cases and 110,000 (95% CI = 53,000-191,000) deaths occurred worldwide, with the highest estimated incidence in the WHO South-East Asian (306 cases per 100,000 persons), Eastern Mediterranean (187), and African (111) regions (7). Since 2018, five countries (Liberia, Nepal, Pakistan, Samoa [based on self-assessment], and Zimbabwe) with estimated high typhoid fever incidence (≥100 cases per 100,000 population per year) (8), high antimicrobial resistance prevalence, or recent outbreaks introduced typhoid conjugate vaccines into their routine immunization programs (2). To guide vaccine introduction decisions, countries should consider all available information, including surveillance of laboratory-confirmed cases, population-based and modeling studies, and outbreak reports. Establishing and strengthening typhoid fever surveillance will be important to measure vaccine impact.

Optimized workplace risk mitigation measures for SARS-CoV-2 in 2022

596 million SARS-CoV-2 cases have been reported and over 12 billion vaccine doses have been administered. As vaccination rates increase, a gap in knowledge exists regarding appropriate thresholds for escalation and de-escalation of workplace COVID-19 preventative measures. We conducted 133,056 simulation experiments, evaluating the spread of SARS-CoV-2 virus in hypothesized working environments subject to COVID-19 infections from the community. We tested the rates of workplace-acquired infections based on applied isolation strategies, community infection rates, methods and scales of testing, non-pharmaceutical interventions, variant predominance, vaccination coverages, and vaccination efficacies. When 75% of a workforce is vaccinated with a 70% efficacious vaccine against infection, then no masking or routine testing + isolation strategies are needed to prevent workplace-acquired omicron variant infections when the community infection rate per 100,000 persons is ≤ 1. A CIR ≤ 30, and ≤ 120 would result in no workplace-acquired infections in this same scenario against the delta and alpha variants, respectively. Workforces with 100% worker vaccination can prevent workplace-acquired infections with higher community infection rates. Identifying and isolating workers with antigen-based SARS-CoV-2 testing methods results in the same or fewer workplace-acquired infections than testing with slower turnaround time polymerase chain reaction methods. Risk migration measures such as mask-wearing, testing, and isolation can be relaxed, or escalated, in commensurate with levels of community infections, workforce immunization, and risk tolerance. The interactive heatmap we provide can be used for immediate, parameter-based case count predictions to inform institutional policy making. The simulation approach we have described can be further used for future evaluation of strategies to mitigate COVID-19 spread.

Mathematical modeling of pneumococcal transmission dynamics in response to PCV13 infant vaccination in Germany predicts increasing IPD burden due to serotypes included in next-generation PCVs.

Two next-generation pneumococcal conjugate vaccines (PCVs), a 15- and a 20-valent PCV (PCV15 and PCV20), have recently been licensed for use in adults, and PCV15 has also been licensed in children. We developed a dynamic transmission model specific for Germany, with the aim to predict carriage prevalence and invasive pneumococcal disease (IPD) burden for serotypes included in these vaccines. The model allows to follow serotype distributions longitudinally both in the absence and presence of PCV vaccinations. We considered eight age cohorts and seven serotype groups according to the composition of different pneumococcal vaccines. This comprises the additional serotypes contained in PCV15 and PCV20 but not in PCV13. The model predicted that by continuing the current vaccine policy (standard vaccination with PCV13 in children and with PPSV23 in adults) until 2031, IPD case counts due to any serotype in children <2 years of age will remain unchanged. There will be a continuous decrease of IPD cases in adults aged 16-59y, but a 20% increase in adults ≥60y. Furthermore, there will be a steady decrease of the proportion of carriage and IPD due to serotypes included in PCV7 and PCV13 over the model horizon and a steady rise of non-PCV13 serotypes in carriage and IPD. The highest increase for both pneumococcal carriage and absolute IPD case counts was predicted for serotypes 22F and 33F (included in both PCV15 and PCV20) and serotypes 8, 10A, 11A, 12F, and 15B (included in PCV20 only), particularly in older adults. Between 2022 and 2031, serotypes included in PCV20 only are expected to cause 19.7-25.3% of IPD cases in adults ≥60y. We conclude that introduction of next-generation PCVs for adults may prevent a substantial and increasing proportion of adult IPDs, with PCV20 having the potential to provide the broadest protection against pneumococcal disease.

Forecasting hospital-level COVID-19 admissions using real-time mobility data

BackgroundFor each of the COVID-19 pandemic waves, hospitals have had to plan for deploying surge capacity and resources to manage large but transient increases in COVID-19 admissions. While a lot of effort has gone into predicting regional trends in COVID-19 cases and hospitalizations, there are far fewer successful tools for creating accurate hospital-level forecasts.MethodsLarge-scale, anonymized mobile phone data has been shown to correlate with regional case counts during the first two waves of the pandemic (spring 2020, and fall/winter 2021). Building off this success, we developed a multi-step, recursive forecasting model to predict individual hospital admissions; this model incorporates the following data: (i) hospital-level COVID-19 admissions, (ii) statewide test positivity data, and (iii) aggregate measures of large-scale human mobility, contact patterns, and commuting volume.ResultsIncorporating large-scale, aggregate mobility data as exogenous variables in prediction models allows us to make hospital-specific COVID-19 admission forecasts 21 days ahead. We show this through highly accurate predictions of hospital admissions for five hospitals in Massachusetts during the first year of the COVID-19 pandemic.ConclusionsThe high predictive capability of the model was achieved by combining anonymized, aggregated mobile device data about users’ contact patterns, commuting volume, and mobility range with COVID hospitalizations and test-positivity data. Mobility-informed forecasting models can increase the lead-time of accurate predictions for individual hospitals, giving managers valuable time to strategize how best to allocate resources to manage forthcoming surges.

High rates of observed face mask use at Colorado universities align with students’ opinions about masking and support the safety and viability of in-person higher education during the COVID-19 pandemic

BackgroundOver the course of the COVID-19 pandemic, colleges and universities have focused on creating policies, such as mask mandates, to minimize COVID-19 transmission both on their campuses and in the surrounding community. Adherence to and opinions about these policies remain largely unknown.MethodsThe Centers for Disease Control and Prevention (CDC) developed a cross-sectional study, the Mask Adherence and Surveillance at Colleges and Universities Project (MASCUP!), to objectively and inconspicuously measure rates of mask use at institutes of higher education via direct observation. From February 15 through April 11, 2021 the University of Colorado Boulder (CU, n = 2,808 observations) and Colorado State University Fort Collins (CSU, n = 3,225 observations) participated in MASCUP! along with 52 other institutes of higher education (n = 100,353 observations) spanning 21 states and the District of Columbia. Mask use was mandatory at both Colorado universities and student surveys were administered to assess student beliefs and attitudes.ResultsWe found that 91.7%, 93.4%, and 90.8% of persons observed at indoor locations on campus wore a mask correctly at University of Colorado, Colorado State University, and across the 52 other schools, respectively. Student responses to questions about masking were in line with these observed rates of mask use where 92.9% of respondents at CU and 89.8% at CSU believe that wearing masks can protect the health of others. Both Colorado universities saw their largest surges in COVID-19 cases in the fall of 2020, with markedly lower case counts during the mask observation window in the spring of 2021.ConclusionHigh levels of mask use at Colorado’s two largest campuses aligned with rates observed at other institutes across the country. These high rates of use, coupled with positive student attitudes about mask use, demonstrate that masks were widely accepted and may have contributed to reduced COVID-19 case counts. This study supports an emerging body of literature substantiating masks as an effective, low-cost measure to reduce disease transmission and establishes masking (with proper education and promotion) as a viable tactic to reduce respiratory disease transmission on college campuses.

Study of Local Fatigue Methods (TCD, N-SIF, and ESED) on Notches and Defects Related to Numerical Efficiency

The fatigue strength of structural components is strongly affected by notches and imperfections. Both can be treated similarly, as local notch fatigue strength methods can also be applied to interior defects. Even though Murakami’s √area approach is commonly used in the threshold-based fatigue design of single imperfections, advanced concepts such as the Theory of Critical Distances (TCD), Notch Stress Intensity Factors (N-SIF), or Elastic Strain Energy Density (ESED) methods provide additional insight into the local fatigue strength distribution of irregularly shaped defects under varying uniaxial load vectors. The latter methods are based on the evaluation of the elastic stress field in the vicinity of the notch for each single load vector. Thus, this work provides numerically efficient methods to assess the local fatigue strength by means of TCD, N-SIF, and ESED, targeting the minimization of the required load case count, optimization of stress field evaluation data points, and utilization of multi-processing. Furthermore, the Peak Stress Method (PSM) is adapted for large opening angles, as in the case of globular defects. In detail, two numerical strategies are devised and comprehensively evaluated, either using a sub-case-based stress evaluation of the defect vicinity with an unchanged mesh pattern and varying load vector on the exterior model region with optimized load angle stepping or by the invocation of stress and strain tensor transformation equations to derive load angle-dependent result superposition while leaving the initial mesh unaltered. Both methods provide numerically efficient fatigue post-processing, as the mesh in the evaluated defect region is retained for varying load vectors. The key functions of the fatigue strength assessment, such as the evaluation of appropriate planar notch radius and determination of notch opening angle for the discretized imperfections, are presented. Although the presented numerical methods apply to planar simulation studies, the basic methodology can be easily expanded toward spatial fatigue assessment.

Evolution of COVID-19 Health Disparities in Arizona.

COVID-19 burdens are disproportionally high in underserved and vulnerable communities in Arizona. As the pandemic progressed, it is unclear if the initial associated health disparities have changed. This study aims to elicit the dynamic landscape of COVID-19 disparities at the community level and identify newly emerging vulnerable subpopulations. Findings from this study can inform interventions to increase health equity among minoritized communities in the Southwest, other regions of the US, and globally. We compiled biweekly COVID-19 case counts of 274 zip code tabulation areas (ZCTAs) in Arizona from October 21, 2020, to November 25, 2021, a time spanning multiple waves of COVID-19 case growth. Within each biweekly period, we tested the associations between the growth rate of COVID-19 cases and the population composition in a ZCTA including race/ethnicity, income, employment, and age using multiple regression analysis. We then compared the associations across time periods to discover temporal patterns of health disparities. The association between the percentage of Latinx population and the COVID-19 growth rate was positive before April 2021 but gradually converted to negative afterwards. The percentage of Black population was not associated with the COVID-19 growth rate at the beginning of the study but became positive after January 2021 which persisted till the end of the study period. Young median age and high unemployment rate emerged as new risk factors around mid-August 2021. Based on these findings, we identified 37 ZCTAs that were highly vulnerable to future fast escalation of COVID-19 cases. As the pandemic progresses, vulnerabilities associated with Latinx ethnicity improved gradually, possibly bolstered by culturally responsive programs in Arizona to support Latinx. Still communities with disadvantaged social determinants of health continued to struggle. Our findings inform the need to adjust current resource allocations to support the design and implementation of new interventions addressing the emerging vulnerabilities at the community level.

The dynamic relationship between COVID-19 cases and SARS-CoV-2 wastewater concentrations across time and space: Considerations for model training data sets

During the COVID-19 pandemic, wastewater-based surveillance has been used alongside diagnostic testing to monitor infection rates. With the decline in cases reported to public health departments due to at-home testing, wastewater data may serve as the primary input for epidemiological models, but training these models is not straightforward. We explored factors affecting noise and bias in the ratio between wastewater and case data collected in 26 sewersheds in California from October 2020 to March 2022. The strength of the relationship between wastewater and case data appeared dependent on sampling frequency and population size, but was not increased by wastewater normalization to flow rate or case count normalization to testing rates. Additionally, the lead and lag times between wastewater and case data varied over time and space, and the ratio of log-transformed individual cases to wastewater concentrations changed over time. This ratio decreased between the Epsilon/Alpha and Delta variant surges of COVID-19 and increased during the Omicron BA.1 variant surge, and was also related to the diagnostic testing rate. Based on this analysis, we present a framework of scenarios describing the dynamics of the case to wastewater ratio to aid in data handling decisions for ongoing modeling efforts.