Coronavirus disease 2019 (COVID-19) infection prevention practices that exceed Centers for Disease Control and Prevention (CDC) guidance: Balancing extra caution against impediments to care.

In a survey of infection prevention programs, leaders reported frequent clinical and infection prevention practice modifications to avoid coronavirus disease 2019 (COVID-19) exposure that exceeded national guidance. Future pandemic responses should emphasize balanced approaches to precautions, prioritize educational campaigns to manage safety concerns, and generate an evidence-base that can guide appropriate infection prevention practices.

Examining Cash Expenditures and Associated HIV-Related Behaviors Using Financial Diaries in Women Employed by Sex Work in Rural Uganda: Findings from the Kyaterekera Study.

BACKGROUND: Women employed by sex work (WESW) have a high risk of human immunodeficiency virus (HIV) infection and experience economic barriers in accessing care. However, few studies have described their financial lives and the relationship between expenditures and HIV-related behaviors. METHODS: This exploratory study used financial diaries to collect expenditure and income data from WESW in Uganda over 6 months. Data were collected as part of a larger trial that tested the efficacy of an HIV prevention intervention method. Descriptive statistics were used to quantify women's income, relative expenditures, and negative cash balances. Bivariate and multivariate logistic regressions were used to examine the odds of sexual risk behavior or use of HIV medications for several cash scenarios. RESULTS: A total of 163 WESW were enrolled; the participants mean age was 32 years old. Sex work was the sole source of employment for most WESW (99%); their average monthly income was $62.32. Food accounted for the highest proportion of spending (44%) followed by sex work (20%) and housing expenditures (11%). WESW spent the least on health care (5%). Expenditures accounted for a large but variable proportion of these women's income (56% to 101%). Most WESW (74%) experienced a negative cash balance. Some also reported high sex work (28%), health care (24%), and education (28%) costs. The prevalence of condomless sex (77%) and sex with drugs/alcohol (70%) was high compared to use of ART/PrEP (Antiretroviral therapy/Pre-exposure prophylaxis) medications (45%). Women's cash expenditures were not statistically significantly associated with HIV-related behaviors. However, the exploratory study observed a consistent null trend of lower odds of condomless sex (adjusted odds ratio (AOR) = 0.70, 95% confidence interval (CI): 0.28-1.70), sex with drugs/alcohol (AOR = 0.93, 95% CI: 0.42-2.05), and use of ART/PrEP (AOR = 0.80, 95% CI: 0.39-1.67) among women who experienced a negative cash balance versus those who did not. Similar trends were observed for other cash scenarios. CONCLUSION: Financial diaries are a feasible tool to assess the economic lives of vulnerable women. Despite having paid work, most WESW encountered a myriad of financial challenges with limited spending on HIV prevention. Financial protections and additional income-generating activities may improve their status. More robust research is needed to understand the potentially complex relationship between income, expenditures, and HIV risk among vulnerable sex workers.

ADAPTATION OF DOMAIN-SPECIFIC TRANSFORMER MODELS WITH TEXT OVERSAMPLING FOR SENTIMENT ANALYSIS OF SOCIAL MEDIA POSTS ON COVID-19 VACCINE

Covid-19 has spread across the world, and several vaccines have been developed to counter its surge. To identify the correct sentiments that are associated with the vaccines from social media posts, we fine-tune various state-of-the-art pretrained transformer models on tweets that are associated with Covid-19 vaccines. Specifically, we use the recently introduced state-of-the-art RoBERTa, XLNet, and BERT pre-trained transformer models, and the domain-specific CT-BERT and BERTweet transformer models that have been pre-trained on Covid-19 tweets. We further explore the option of text augmentation by oversampling using the language model-based oversampling technique (LMOTE) to improve the accuracies of these models – specifically, for small sample data sets where there is an imbalanced class distribution among the positive, negative, and neutral sentiment classes. Our results summarize our findings on the suitability of text oversampling for imbalanced small-sample data sets that are used to fine-tune state-of-the-art pre-trained transformer models as well as the utility of domain-specific transformer models for the classification task. © 2023 Author(s). This is an open access publication, which can be used, distributed and reproduced in any medium according to the Creative Commons CC-BY 4.0 License.

Romantic love in the age of COVID-19

The article reflects on the importance of having a romantic love between the partners to cope up with the stress during the COVID-19 pandemic. Authors decided to measure the love styles as romantic "attitudes," and did considerable research to develop a questionnaire to assess degree of agreement with the six love styles. Authors assumed that virtually everyone could agree to a greater or lesser extent with the questions reflecting each love style, and therefore people did not have to pick only one style as self-representative. Authors first published a long form of their scale called the Love Attitudes Scale (LAS) and later a shortened form of the scale named the Love Attitudes Scale-Short Form. Authors purpose is to propose ways in which these love styles/love attitudes might function in this incredibly challenging "in-your-face" time of COVID. The goal is to be helpful. As longtime scholars and marital partners (43 years), they are living this pandemic a day at a time, just as you are. This era of a global pandemic is unfamiliar and frightening to all who view its gravity in a clear-eyed fashion. Yet this is also a time when love and caring (in this case for a romantic partner) can deepen a relationship profoundly. We humans are far from perfect, but loving is in our nature. These love styles offer one way of viewing romantic, partnered love. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Monitoring Multiple U.S. Government-Supported Covid-19 Vaccine Trials

Operation Warp Speed was a partnership created to accelerate the development of Covid-19 vaccines. The National Institutes of Health oversaw one data and safety monitoring board to review/monitor all Operation Warp Speed trials. This article describes the challenges faced in monitoring these trials and provides ideas for future similar endeavors.

Beyond Costs: Pragmatic Considerations for Pooling of SARS-CoV-2 Test Samples for Nursing Home Surveillance.

Pooling of samples can increase throughput and reduce costs for large-scale SARS-CoV-2 testing when incidence is low. In a cross-sectional study of serial SARS-CoV-2 sampling of staff and residents at three nursing homes, laboratory labor constraints limited the feasibility of pooling prior to the maximal incidence that favored cost savings. IMPORTANCE This study highlights the pragmatic considerations surrounding SARS-CoV-2 sample pooling beyond accuracy and costs. We performed a cost analysis to determine the percent positivity at which pooling would reduce costs versus single testing. We found that the need for a stable amount of daily work hours staffed by a highly trained workforce was a major limitation in pooling as test positivity increased. For the COVID-19 pandemic and future pandemic threats, laboratories should carefully consider the thresholds at which sample pooling is beneficial, with a particular focus on the impact on laboratory staff.

Value of a confidential COVID-19 helpline for nursing home staff.

We hosted a confidential helpline to address concerns about COVID-19 prevention among staff in 12 nursing homes in Orange County, California. We fielded 301 inquiries from April 2021-April 2022, most commonly involving questions about vaccines (40%), nursing home COVID-19 prevention (28%), SARS-CoV-2 variants (18%), symptom reporting (10%), and home and community COVID-19 prevention (5%). During COVID-19 surges, staff dominantly expressed fear, anger, and exhaustion. During nadirs, sentiment shifted towards optimism and acceptance.

The Impact of Virtual Interviews on Recruitment and Implicit Bias.

BACKGROUND AND OBJECTIVES: The COVID-19 pandemic accelerated virtual residency interview adoption. The impact of virtual interviews on program directors' (PD) National Residency Matching Program (NRMP) Match satisfaction, their future interview plans, and their perceptions about virtual interviews' influence on bias are unknown. We report the results of a survey of family medicine (FM) PDs about these topics after mandatory virtual interviews in 2020-2021. METHODS: A national survey of all FM PDs was conducted in April 2021 (n=619). The response rate was 46.37% (n=287). Questions asked whether PDs conducted virtual interviews, as well as PDs' general perceptions of virtual interviews' impact on administrative burden, diversity and bias; PD's ability to communicate program culture and assess applicants' alignment with program values; PD's satisfaction with Match results; and plans for interview structure postpandemic. RESULTS: Two hundred forty-four (93.1%) respondents performed only virtual interviews; 83.9% (n=220) conducting virtual interviews were satisfied with Match results, with no difference between programs with all virtual interviews vs others (OR 1.2, P=.994). PDs who communicated program values and involved residents in virtual interviews experienced higher Match satisfaction (OR 7.6, P<.001; OR 4.21, P=.001). PDs concerned about virtual interviews increasing bias against minorities before 2020 were still concerned after (OR 8.81, P<.001) and had lower Match satisfaction (OR 0.24, P=.001). CONCLUSIONS: Most FM PDs conducted entirely virtual interviews in 2020 and were satisfied with the Match. Interview processes including residents and conveying residency culture increased Match satisfaction. PDs are concerned about bias in virtual interviews, but more investigation about bias is needed.

Asthma admission among children in Hong Kong during the first year of the COVID-19 pandemic.

BACKGROUND: Multiple nonpharmaceutical interventions (NPIs) had been introduced in Hong Kong during coronavirus disease 2019 (COVID-19) pandemic. The impact on asthma admission, which was closely related to viral infection, was of concern. OBJECTIVE: The study aimed to identify the impact of NPIs on pediatric asthma admissions and their association with respiratory viruses. METHODS: We conducted a retrospective observational study to compare the difference in pediatric asthma hospital admission rates between pre-COVID-19 and COVID-19 periods. Information on demographics, nasopharyngeal specimen results, ventilatory support, intensive care admission, hospital stay duration, asthma control therapy, and previous admission episodes was collected. Weather parameters including temperature, rainfall, humidity, and air quality data that was reflected by the air quality health index were recorded. RESULTS: A total of 1808 pediatric asthma admissions were recorded during the pre-COVID-19 period while there were 62 admissions during COVID-19 period, among which 54 admissions from the pre-COVID-19 period and 4 admissions from COVID-19 period were excluded. Weekly pediatric asthma admissions per total pediatric admissions during COVID-19 was one-third of that during the pre-COVID-19 period (0.3% vs. 0.9%, p < 0.001). During COVID-19 period, a significantly lower percentage of respiratory virus isolates was noted (58.6% vs. 72.6%, p = 0.019). Poisson regression analysis showed that the COVID-19 period (odds ratio [OR] = 0.202, 95% confidence interval  [CI, 0.16-0.26]; p ≤ 0.001), summer vacation period (OR = 0.512, 95% CI [0.43-0.62]; p ≤ 0.001), and humidity (OR = 0.99, 95% CI [0.98-1.00]; p = 0.004) were independent protective factors for asthma admission. CONCLUSIONS: There was a significant reduction in pediatric asthma hospitalizations and respiratory virus isolates in the first year of COVID-19 pandemic in Hong Kong with the implementation of NPIs. Rhinovirus remained the key respiratory virus isolate. Incorporation of appropriate NPIs in long run could reduce virus infection-related pediatric asthma admission.

Secondary Cases of Delta Variant Coronavirus Disease 2019 Among Vaccinated Healthcare Workers With Breakthrough Infections is Rare.

In a retrospective, cohort study at 4 medical centers with high coronavirus disease 2019 vaccination rates, we evaluated breakthrough severe acute respiratory syndrome coronavirus 2 Delta variant infections in vaccinated healthcare workers. Few work-related secondary cases were identified. Breakthrough cases were largely due to unmasked social activities outside of work.

A platform trial design for preventive vaccines against Marburg virus and other emerging infectious disease threats.

BACKGROUND: The threat of a possible Marburg virus disease outbreak in Central and Western Africa is growing. While no Marburg virus vaccines are currently available for use, several candidates are in the pipeline. Building on knowledge and experiences in the designs of vaccine efficacy trials against other pathogens, including SARS-CoV-2, we develop designs of randomized Phase 3 vaccine efficacy trials for Marburg virus vaccines. METHODS: A core protocol approach will be used, allowing multiple vaccine candidates to be tested against controls. The primary objective of the trial will be to evaluate the effect of each vaccine on the rate of virologically confirmed Marburg virus disease, although Marburg infection assessed via seroconversion could be the primary objective in some cases. The overall trial design will be a mixture of individually and cluster-randomized designs, with individual randomization done whenever possible. Clusters will consist of either contacts and contacts of contacts of index cases, that is, ring vaccination, or other transmission units. RESULTS: The primary efficacy endpoint will be analysed as a time-to-event outcome. A vaccine will be considered successful if its estimated efficacy is greater than 50% and has sufficient precision to rule out that true efficacy is less than 30%. This will require approximately 150 total endpoints, that is, cases of confirmed Marburg virus disease, per vaccine/comparator combination. Interim analyses will be conducted after 50 and after 100 events. Statistical analysis of the trial will be blended across the different types of designs. Under the assumption of a 6-month attack rate of 1% of the participants in the placebo arm for both the individually and cluster-randomized populations, the most likely sample size is about 20,000 participants per arm. CONCLUSION: This event-driven design takes into the account the potentially sporadic spread of Marburg virus. The proposed trial design may be applicable for other pathogens against which effective vaccines are not yet available.

Dynamic Topic Modeling of Covid-19 Vaccine-Related Tweets

The Covid-19 pandemic has made a huge impact on the world. Vaccines are regarded as the universal solution to mitigate the spread of the pandemic. Vaccination programs have been initiated by all countries in the past one year or so. The public opinion about vaccinations has been dynamically changing during this period. We intend to track the perception of the masses since the arrival of the vaccines, through social media posts, and reflect on the reasons behind the dynamically evolving ideas of people. For this purpose, we propose the use of Latent Dirichlet Allocation (LDA) for topic modeling from vaccine-related discussions on the popular social media platform Twitter, in five temporal phases, in the duration of 20 December 2020 to 16 October 2021. The time windows are determined such that the tweets are equally distributed in each time slice. The ten most relevant terms in the top-10 topics in each time window are determined and presented in the form of bar charts. The relevancy of a term is interpreted as the sum of probabilistic scores associated with that term in the top-10 topics identified by LDA in a particular time period. The bar charts are further analyzed for inferring the topics of discussion in a particular phase of time. © 2022 ACM.

Determinants of hospital outcomes for patients with COVID-19 in the University of Pennsylvania Health System.

There is growing evidence that racial and ethnic minorities bear a disproportionate burden from COVID-19. Temporal changes in the pandemic epidemiology and diversity in the clinical course require careful study to identify determinants of poor outcomes. We analyzed 6255 hospitalized individuals with PCR-confirmed SARS-CoV-2 infection from one of 5 hospitals in the University of Pennsylvania Health System between March 2020 and March 2021, using electronic health records to assess risk factors and outcomes through 8 weeks post-admission. Discharge, readmission and mortality outcomes were analyzed in a multi-state model with multivariable Cox models for each transition. Mortality varied markedly over time, with cumulative incidence (95% CI) 30 days post-admission of 19.1% (16.9, 21.3) in March-April 2020, 5.7% (4.2, 7.5) in July-October 2020 and 10.5% (9.1,12.0) in January-March 2021; 26% of deaths occurred after discharge. Average age (SD) at admission varied from 62.7 (17.6) to 54.8 (19.9) to 60.5 (18.1); mechanical ventilation use declined from 21.3% to 9-11%. Compared to Caucasian, Black race was associated with more severe disease at admission, higher rates of co-morbidities and residing in a low-income zip code. Between-race risk differences in mortality risk diminished in multivariable models; while admitting hospital, increasing age, admission early in the pandemic, and severe disease and low blood pressure at admission were associated with increased mortality hazard. Hispanic ethnicity was associated with fewer baseline co-morbidities and lower mortality hazard (0.57, 95% CI: 0.37, .087). Multi-state modeling allows for a unified framework to analyze multiple outcomes throughout the disease course. Morbidity and mortality for hospitalized COVID-19 patients varied over time but post-discharge mortality remained non-trivial. Black race was associated with more risk factors for morbidity and with treatment at hospitals with lower mortality. Multivariable models suggest there are not between-race differences in outcomes. Future work is needed to better understand the identified between-hospital differences in mortality.

Covid-19 Vaccine Sentiment Analysis During Second Wave in India by Transfer Learning Using XLNet

The Covid-19 pandemic has created a world-wide crisis from the perspectives of health and economy. Vaccination is one of the prime means by which herd immunity could be developed. Social media platforms such as Twitter has played a major role in building public opinion as the vaccination drive got underway in several countries. In this paper, we present a tweet-based sentiment analysis of the two popularly administered vaccines in India Covishield and Covaxin during the second wave of the pandemic in India, from March 2021 to September 2021, which was attributed to the Delta mutant of the coronavirus. We use unlabeled Covid-19 vaccine-related tweets downloaded from a large-scale dataset from March 2021 to September 2021, and employ transfer learning for classifying the unlabeled tweets. The contributions of this paper are: - sentiment analysis of unlabeled vaccine-related tweets by training a transformer model on pre-trained XLNet (transformer) features derived from a labeled non-Covid Twitter dataset, a time-line of public sentiments for the two vaccines administered in India, and word clouds of high-frequency adjective unigrams after sentiment analysis, as evidence. © 2022, Springer Nature Switzerland AG.

SARS-CoV-2 accessory proteins reveal distinct serological signatures in children.

The antibody response magnitude and kinetics may impact clinical severity, serological diagnosis and long-term protection of COVID-19, which may play a role in why children experience lower morbidity. We therefore tested samples from 122 children in Hong Kong with symptomatic (n = 78) and asymptomatic (n = 44) SARS-CoV-2 infections up to 200 days post infection, relative to 71 infected adults (symptomatic n = 61, and asymptomatic n = 10), and negative controls (n = 48). We assessed serum IgG antibodies to a 14-wide antigen panel of structural and accessory proteins by Luciferase Immuno-Precipitation System (LIPS) assay and circulating cytokines. Infected children have lower levels of Spike, Membrane, ORF3a, ORF7a, ORF7b antibodies, comparable ORF8 and elevated E-specific antibodies than adults. Combination of two unique antibody targets, ORF3d and ORF8, can accurately discriminate SARS-CoV-2 infection in children. Principal component analysis reveals distinct pediatric serological signatures, and the highest contribution to variance from adults are antibody responses to non-structural proteins ORF3d, NSP1, ORF3a and ORF8. From a diverse panel of cytokines that can modulate immune priming and relative inflammation, IL-8, MCP-1 and IL-6 correlate with the magnitude of pediatric antibody specificity and severity. Antibodies to SARS-CoV-2 internal proteins may become an important sero surveillance tool of infection with the roll-out of vaccines in the pediatric population.

Becoming an anti-racist interprofessional healthcare organization: Our journey.

The COVID-19 pandemic amplified the egregious disproportionate burden of disease based on race, ethnicity, and failure of organizations to address structural racism. This paper describes a journey by members of the National Academies of Practice (NAP) who came together to address diversity, equity, and inclusion (DEI). Through collaborative efforts, a virtual, interactive workshop was designed and delivered at NAP's 2021 Virtual Forum to facilitate discussions about DEI priorities across professions and to initiate a sustainable action plan toward achieving inclusive excellence. Resulting discoveries and reflections led us to the essential question: can we truly become an anti-racist interprofessional healthcare organization?

Becoming an anti-racist interprofessional healthcare organization: Our journey

The COVID-19 pandemic amplified the egregious disproportionate burden of disease based on race, ethnicity, and failure of organizations to address structural racism. This paper describes a journey by members of the National Academies of Practice (NAP) who came together to address diversity, equity, and inclusion (DEI). Through collaborative efforts, a virtual, interactive workshop was designed and delivered at NAP's 2021 Virtual Forum to facilitate discussions about DEI priorities across professions and to initiate a sustainable action plan toward achieving inclusive excellence. Resulting discoveries and reflections led us to the essential question: can we truly become an anti-racist interprofessional healthcare organization?

The Impact of Coronavirus Disease 2019 (COVID-19) on Healthcare-Associated Infections.

BACKGROUND: The profound changes wrought by coronavirus disease 2019 (COVID-19) on routine hospital operations may have influenced performance on hospital measures, including healthcare-associated infections (HAIs). We aimed to evaluate the association between COVID-19 surges and HAI and cluster rates. METHODS: In 148 HCA Healthcare-affiliated hospitals, from 1 March 2020 to 30 September 2020, and a subset of hospitals with microbiology and cluster data through 31 December 2020, we evaluated the association between COVID-19 surges and HAIs, hospital-onset pathogens, and cluster rates using negative binomial mixed models. To account for local variation in COVID-19 pandemic surge timing, we included the number of discharges with a laboratory-confirmed COVID-19 diagnosis per staffed bed per month. RESULTS: Central line-associated blood stream infections (CLABSI), catheter-associated urinary tract infections (CAUTI), and methicillin-resistant Staphylococcus aureus (MRSA) bacteremia increased as COVID-19 burden increased. There were 60% (95% confidence interval [CI]: 23-108%) more CLABSI, 43% (95% CI: 8-90%) more CAUTI, and 44% (95% CI: 10-88%) more cases of MRSA bacteremia than expected over 7 months based on predicted HAIs had there not been COVID-19 cases. Clostridioides difficile infection was not significantly associated with COVID-19 burden. Microbiology data from 81 of the hospitals corroborated the findings. Notably, rates of hospital-onset bloodstream infections and multidrug resistant organisms, including MRSA, vancomycin-resistant enterococcus, and Gram-negative organisms, were each significantly associated with COVID-19 surges. Finally, clusters of hospital-onset pathogens increased as the COVID-19 burden increased. CONCLUSIONS: COVID-19 surges adversely impact HAI rates and clusters of infections within hospitals, emphasizing the need for balancing COVID-related demands with routine hospital infection prevention.