Risk Of COVID-19 Research Articles

Association of superoxide dismutase and catalase genetic variants and their gene-gene interactions with the severity of COVID-19

BACKGROUND: Since the outbreak of COVID-19 infection, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), oxidative stress has been proposed as an important player in its severity. This increased the interest in studying antioxidant systems to evaluate their possible role in counteracting disease progression. AIM: The aim of the current study was to investigate the association of single nucleotide polymorphism (SNP) of superoxide dismutase (SOD) and catalase (CAT) genes with the severity of COVID-19. MATERIALS AND METHODS: Study subjects were divided into two groups based on the severity of their symptoms. Allele-specific PCR was used for genotyping, and multifactor dimensionality reduction (MDR) analysis was performed to investigate the SNP–SNP interaction models. RESULTS: The results showed a significant association of SOD2 rs4880 with the severity of COVID-19 (p = 0.002). SOD2 47TT genotype was significantly more frequent among patients with severe COVID-19 (OR 4.34; 95% CI 1.72–10.96). The three-locus SNP–SNP interaction model, resulted from MDR analysis, was statistically significant (0.55 × 10–4, OR 3.81; 95% CI 1.96–7.42). Carriers of SOD1 7958G * SOD2 47T * CAT 262C allele combination had a higher risk of severe COVID-19 (p = 0.0045, OR 2.84, 95% CI 1.40–5.78). CONCLUSIONS: The obtained results contribute to better understanding of COVID-19 pathogenesis and suggest novel potential prognostic biomarkers of the infection.

An Evaluation of the Maternal Patient Experience through Natural Language Processing Techniques: The Case of Twitter Data in the United States during COVID-19

The healthcare sector constantly investigates ways to improve patient outcomes and provide more patient-centered care. Delivering quality medical care involves ensuring that patients have a positive experience. Most healthcare organizations use patient survey feedback to measure patients’ experiences. However, the power of social media can be harnessed using artificial intelligence and machine learning techniques to provide researchers with valuable insights into understanding patient experience and care. Our primary research objective is to develop a social media analytics model to evaluate the maternal patient experience during the COVID-19 pandemic. We used the “COVID-19 Tweets” Dataset, which has over 28 million tweets, and extracted tweets from the US with words relevant to maternal patients. The maternal patient cohort was selected because the United States has the highest percentage of maternal mortality and morbidity rate among the developed countries in the world. We evaluated patient experience using natural language processing (NLP) techniques such as word clouds, word clustering, frequency analysis, and network analysis of words that relate to “pains” and “gains” regarding the maternal patient experience, which are expressed through social media. The pandemic showcased the worries of mothers and providers on the risks of COVID-19. However, many people also shared how they survived the pandemic. Both providers and maternal patients had concerns regarding the pregnancy risks due to COVID-19. This model will help process improvement experts without domain expertise to understand the various domain challenges efficiently. Such insights can help decision-makers improve the patient care system.

Adaptation of French general practitioners for the management of nursing home patients during COVID-19 in 2020: a multilevel analysis.

To describe French general practioners' (GPs) adaptation strategies to ensure follow-up care of nursing home patients during the first wave of COVID-19 (May 2020) and to identify factors associated with each strategy. A national cross-sectional study was conducted with online questionnaires in May 2020 among GPs practicing in France (metropolitan and overseas) and usually providing nursing home visits before pandemic. The outcome was defined as the GPs' adaptation strategies for managing nursing home patients and was categorized into four groups: Maintenance of Nursing Home Visits NHV (reference), Stopping NHV, Numeric adaptation (teleconsultations only), Mixed adaptation (NHV and teleconsultations). The probability of adaptation strategies was analyzed by multilevel logistic models in which the GPs represented level 1 and the counties level 2. We applied three random-intercept multilevel logistic models with the county of GP's practice as random effect. This analysis included 2,146 responses by GPs coming from 98 French counties. Overall, 40.4% of GPs maintained NHV, while other strategies were: Stopping visits (24.1%), Numeric adaptation (15.4%), Mixed adaptation (20.1%). Several individual (age, training GP, perceived status of being at high risk of severe COVID, compliance with temporary delegation of the patient's management) and territorial factors (excess mortality rate due to COVID-19, GPs' density, proportion of over-75s, presence of reinforcement measures for nursing home patients) were identified as associated with each strategy. This study highlights a rapid adaptation of general practice to keep supporting nursing home patients. Heterogeneity of adaptation strategies could reflect both the lack of national guidelines and the heterogeneity among GPs' usual practices. Policymakers should take actions at a territorial level (subnational) to strengthen support to nursing home patients considering adaptations to the local context of the pandemic outbreak and perspective of local actors.

Satellite fans’ nostalgia buffers negative emotions and increases well-being and travel intention

This study aimed to examine how satellite fans perceived the risk of COVID-19 and its influence on their emotions (i.e., nostalgia, depression, and frustration), well-being, and intention to travel to the stadium of European Professional Football Leagues (EPFL) teams in the future. A total of 511 EPFL fans in Singapore participated in this study. Results showed that the perceived risk of COVID-19 increased depression and frustration; satellite fans who felt frustrated were more likely to feel depressed and nostalgic, and nostalgia positively affected well-being and travel intention. In addition, we found that the satellite fans who felt well were more likely to visit the stadium of their favorite EPFL teams. We identified the buffering role of nostalgia, which contributes to advancing the literature on sports tourism development and provides a deeper understanding of the behaviors of sports fans during the COVID-19 pandemic.

Neutralizing Antibody Immune Correlates for a Recombinant Protein Vaccine in the COVAIL Trial.

For COVAIL recipients of a COVID-19 Sanofi booster vaccine, neutralizing antibody titers were assessed as a correlate of risk (CoR) of COVID-19. Peak and exposure-proximal titers were inverse CoRs with covariate-adjusted hazard ratios (95% confidence intervals) 0.30 (0.11, 0.78) and 0.25 (0.07, 0.85) per 10-fold increase in weighted average titer.

A Population-Based Study of SARS-CoV-2 IgG Antibody Responses to Vaccination in Manitoba.

Understanding variables that influence antibody responses to COVID-19 vaccination within a population can provide valuable information on future vaccination strategies. In this population-based study, we examined the antibody responses to COVID-19 vaccination in Manitoba using residual serum specimens collected between January 2021 and March 2022 (n = 20,365). Samples were tested for spike and nucleocapsid IgG against SARS-CoV-2 using clinically validated assays. We assessed the impacts of multiple factors on post-vaccination antibody titres including type of vaccine, age, sex, geographic location, number of doses received, and timing of vaccination. Our investigation demonstrated that vaccination with one dose of Moderna mRNA-1273 elicited higher anti-spike IgG titres overall compared to Pfizer BNT162b2 vaccination, while one dose of Pfizer BNT162b2 followed by a second dose of Moderna mRNA-1273 exhibited higher titres than two doses of Pfizer BNT162b2 or Moderna mRNA-1273, irrespective of age. Age and time post-vaccination had considerable effects on antibody responses, with older age groups exhibiting lower anti-spike IgG titres than younger ages, and titres of those vaccinated with Pfizer BNT162b2 waning faster than those vaccinated with Moderna mRNA-1273 or a combination of Pfizer BNT162b2 and Moderna mRNA-1273. Antibody titres did not appear to be affected by sex or geographic location. Our results identify how factors such as age and type of vaccine can influence antibody responses to vaccination, and how antibody titres wane over time. This information highlights the importance of tailoring vaccine regimens to specific populations, especially those at increased risk of severe COVID-19 and can be used to inform future vaccination strategies, scheduling of booster doses, and public health measures.

Interaction between economic status and healthy lifestyle in long COVID among Chinese older population: a cross-sectional study

ObjectivesTo estimate the interaction between economic status (ES) and healthy lifestyle in long COVID among Chinese older people infected with SARS-CoV-2.DesignA cross-sectional study based on the Peking University Health Cohort...

Effects of social networking sites on strengthening self-protective behaviors after COVID-19 recovery among the working-aged population

This study aimed to investigate the effects of social networking sites (SNS) on strengthening self-protective behaviors after COVID-19 to prevent post-COVID-19 conditions in the working-age population in Thailand. Data were collected through a cross-sectional online survey of 400 working-aged Thais. Multiple regression analysis (MRA) was employed to analyze the data at a 0.05 significance level. The findings revealed that YouTube (beta = .275) and Facebook (beta = .182) positively impact self-protective behaviors while Twitter (beta = .237), Facebook (beta = .198) and Tiktok (beta = .119) influence attitudes towards these behaviors. Additionally, Twitter (beta = .206) and LINE (beta = .145) affect subjective norms. YouTube (beta = .288) and LINE (beta = .165) significantly enhance self-efficacy. This study contributes to the broader understanding of how social networking sites can reinforce self-protective behaviors against long COVID-19 among the working-age population. This study contributes valuable insights into the role of social networking sites in promoting health behaviors after COVID-19. The findings offer practical implications for health communication planning by expanding knowledge on the effectiveness of these platforms. Policymakers, social marketers and health organizations can leverage these insights to design targeted interventions to reduce the risk of COVID-19 and prevent future COVID-19 outbreaks at both national and international levels.

Integrating transcriptomics, eQTL, and Mendelian randomization to dissect monocyte roles in severe COVID-19 and gout flare.

There are considerable similarities between the pathophysiology of gout flare and the dysregulated inflammatory response in severe COVID-19 infection. Monocytes are the key immune cells involved in the pathogenesis of both diseases. Therefore, it is critical to elucidate the molecular basis of the function of monocytes in gout and COVID-19 in order to develop more effective therapeutic approaches. The single-cell RNA sequencing (scRNA-seq), large-scale genome-wide association studies (GWAS), and expression quantitative trait loci (eQTL) data of gout and severe COVID-19 were comprehensively analyzed. Cellular heterogeneity and intercellular communication were identified using the scRNA-seq datasets, and the monocyte-specific differentially expressed genes (DEGs) between COVID-19, gout and normal subjects were screened. In addition, the correlation of the DEGs with severe COVID-19 and gout flare was analyzed through GWAS statistics and eQTL data. The scRNA-seq analysis exhibited that the proportion of classical monocytes was increased in both severe COVID-19 and gout patient groups compared to healthy controls. Differential expression analysis and MR analysis showed that NLRP3 was positively associated with the risk of severe COVID-19 and involved 11 SNPs, of which rs4925547 was not significantly co-localized. In contrast, IER3 was positively associated with the risk of gout and involved 9 SNPs, of which rs1264372 was significantly co-localized. Monocytes have a complex role in gout flare and severe COVID-19, which underscores the potential mechanisms and clinical significance of the interaction between the two diseases.

Systemic Functional Linguistics: Mood Analysis on Risk and Vulnerability to COVID-19

Purpose: This study examines Risk and Vulnerability to COVID-19 using Systemic Functional Linguistics (SFL) mood analysis to understand health messages and their functional meaning. Methodology: Hallidyan (1994) SFL Mood analysis framework, Tabular orientation. The sample was selected health messages. Analysis of 50 clauses Findings: 29 clauses were imperative (58%), 21 clauses were declarative (42%), No interrogative or exclamatory clauses found. Health messages primarily contained instructions or directions related to COVID-19 risk and vulnerability Unique Contribution to Theory, Practice and Policy: The study provides a foundation for understanding interpersonal metafunction of language in health communication. It serves as a starting point for learners and beginners in SFL mood analysis. Tabulated data presentation facilitates easy understanding and analysis.

DNA Damage in Moderate and Severe COVID-19 Cases: Relation to Demographic, Clinical, and Laboratory Parameters.

The ability of the SARS-CoV-2 virus to cause DNA damage in infected humans requires its study as a potential indicator of COVID-19 progression. DNA damage was studied in leukocytes of 65 COVID-19 patients stratified by sex, age, and disease severity in relation to demographic, clinical, and laboratory parameters. In a combined group of COVID-19 patients, DNA damage was shown to be elevated compared to controls (12.44% vs. 5.09%, p < 0.05). Severe cases showed higher DNA damage than moderate cases (14.66% vs. 10.65%, p < 0.05), and males displayed more damage than females (13.45% vs. 8.15%, p < 0.05). DNA damage is also correlated with international normalized ratio (INR) (r = 0.471, p < 0.001) and creatinine (r = 0.326, p < 0.05). In addition to DNA damage, severe COVID-19 is associated with age, C-reactive protein (CRP), and creatinine. Receiver operating characteristic analysis identified age, INR, creatinine, DNA damage, and CRP as significant predictors of disease severity, with cut-off values of 72.50 years, 1.46 s, 78.0 µmol/L, 9.72%, and 50.0 mg/L, respectively. The results show that DNA damage correlates with commonly accepted COVID-19 risk factors. These findings underscore the potential of DNA damage as a biomarker for COVID-19 severity, suggesting its inclusion in prognostic assessments to facilitate early intervention and improve patient outcomes.

Connectedness of global energy markets with global agricultural, natural resources, and socially responsible investments using extended GFI

PurposeThe study aims to investigate the risk transmission from COVID-19 to global agriculture, energy, natural resources/mining and environmentally/socially responsible investments. Additionally, it explores the connectedness of global energy indices with global agriculture, natural resources/mining and environmentally/socially responsible investments. The study develops a new COVID-19-based Global Fear Index (GFI) to achieve the objectives, thus contributing to the prevailing literature.Design/methodology/approachThe data of Global indices are selected from January 2020 to December 2021. The study uses multivariate BEKK-GARCH and TVP-VAR models to explore COVID-19 risk transmission and connectedness between global indices.FindingsSignificant shock and volatility transmissions from COVID-19 to all global indices are observed. Results show that global agriculture, natural resource/mining markets and environmentally and socially responsible investments are safe havens during COVID-19. Furthermore, these global investment choices are barely connected with global energy indices.Practical implicationsPortfolio managers and investors should invest in global indices to gauge the risk-adjusted return during the pandemic and upcoming health-related risks. Investors in energy sectors are advised to diversify the risk by adding safe-haven assets to their portfolios.Social implicationsThe findings shed light on the importance of environmentally and socially responsible investments as a separate asset class where ecologically friendly and socially sentimental investors could invest in diversifying the risk of their portfolios.Originality/valueThe paper offers valuable insights to policymakers and investors regarding asset pricing, risk management and financial market stability during pandemic-type emergencies.

Crowd-sourced machine learning prediction of long COVID using data from the National COVID Cohort Collaborative

BackgroundWhile many patients seem to recover from SARS-CoV-2 infections, many patients report experiencing SARS-CoV-2 symptoms for weeks or months after their acute COVID-19 ends, even developing new symptoms weeks after infection. These long-term effects are called post-acute sequelae of SARS-CoV-2 (PASC) or, more commonly, Long COVID. The overall prevalence of Long COVID is currently unknown, and tools are needed to help identify patients at risk for developing long COVID. MethodsA working group of the Rapid Acceleration of Diagnostics-radical (RADx-rad) program, comprised of individuals from various NIH institutes and centers, in collaboration with REsearching COVID to Enhance Recovery (RECOVER) developed and organized the Long COVID Computational Challenge (L3C), a community challenge aimed at incentivizing the broader scientific community to develop interpretable and accurate methods for identifying patients at risk of developing Long COVID. From August 2022 to December 2022, participants developed Long COVID risk prediction algorithms using the National COVID Cohort Collaborative (N3C) data enclave, a harmonized data repository from over 75 healthcare institutions from across the United States (U.S.). FindingsOver the course of the challenge, 74 teams designed and built 35 Long COVID prediction models using the N3C data enclave. The top 10 teams all scored above a 0.80 Area Under the Receiver Operator Curve (AUROC) with the highest scoring model achieving a mean AUROC of 0.895. Included in the top submission was a visualization dashboard that built timelines for each patient, updating the risk of a patient developing Long COVID in response to clinical events. InterpretationAs a result of L3C, federal reviewers identified multiple machine learning models that can be used to identify patients at risk for developing Long COVID. Many of the teams used approaches in their submissions which can be applied to future clinical prediction questions. FundingResearch reported in this RADx® Rad publication was supported by the National Institutes of Health. Timothy Bergquist, Johanna Loomba, and Emily Pfaff were supported by Axle Subcontract: NCATS-STSS-P00438.

Improving possible serious bacterial infection (PSBI) management in young infants when referral is not feasible: lessons from embedded implementation research in Ethiopia and Kenya

BackgroundSepsis is a leading cause of neonatal mortality, despite the availability of effective treatment of possible serious bacterial illness (PSBI), including when referral to a hospital is not feasible. Gaps in access and delivery worsened during COVID-19. We conducted embedded implementation research in Ethiopia and Kenya aimed at mitigating the impact of COVID-19 and addressing various implementation challenges to improve PSBI management.MethodsThe implementation research projects were implemented at the subnational level in Ethiopia and Kenya between November 2020-June 2022 (Ethiopia) and December 2020-August 2022 (Kenya). Guided by the implementation research frameworks, both projects conducted mixed formative quantitative and exploratory research from April to May 2021, followed by summative evaluations conducted between June and July 2022. Frameworks encompassed Consolidated Framework for Implementation Research (CFIR), Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM), as well as health systems framework that incorporates cascades of care and World Health Organization Health Systems Building Blocks. Results were synthesized across the projects through document review and sharing cross-project measures and strategies through a project community of practice.ResultsDespite differences in settings across the projects, cross-cutting facilitators included community health worker program and support, and existence of guidelines for PSBI management at primary care levels. Barriers included community attitudes towards seeking care for sick newborns, COVID-19 risks and fear, and lack of health care worker competence. Country-specific contextual barriers included supply chain issues, civil conflict (Ethiopia), and labor strikes (Kenya). Strategies chosen to mitigate barriers and support implementation and sustainability in both settings included leveraging community health workers to address resistance to care-seeking, health workers’ training, COVID-19 infection prevention measures, stakeholder engagement, and advocacy to integrate PSBI management into existing programs, policies, and training. Other strategies addressing emerging project-specific barriers, included improving follow-up through a community health desk and PSBI mobile app (Kenya) and supply chain strengthening (Ethiopia). Both projects improved PSBI management coverage, increased adoption and uptake, and informed national policy changes supporting potential for sustainability.ConclusionsPragmatic embedded implementation research effectively supports the identification of barriers and mapping to strategies designed to increase effective coverage of PSBI management when referral is not feasible during the COVID-19 pandemic. Despite differences in context, cross-cutting strategies identified could inform broader scale-up in the region, including during future health system shocks.

Missense variant rs75603675 within TMPRSS2 gene is associated with the increased risk of severe form of COVID-19

Host genetics among other factors play an important role in COVID-19 disease severity. TMPRSS2, a serine protease, facilitates the priming of the SARS-CoV-2 spike protein, which is essential for the virus to enter the host cell. Several studies had targeted the TMPRSS2 polymorphisms with respect to SARS-CoV-2 infection and COVID-19 disease severity. Initially, the Whole Exome Sequencing (WES) of 7 healthy individuals and 22 COVID-19 patients with different degrees of disease severity was conducted to find the mutational landscape in different genes. A total of 26 single nucleotide polymorphisms (SNPs) were identified of which six were within the exons of TMPRSS2 (four synonymous and two nonsynonymous variants) while the rest of the 20 SNPs were recognized within the flanking intronic regions of TMPRSS2 gene. The nonsynonymous SNPs, rs75603675 and rs12329760, were further evaluated for association with disease severity in a larger sample size of 120 individuals by PCR followed by Sanger sequencing. Neither allelic nor genotypic distributions of rs12329760 were significantly associated with COVID-19 disease severity. However, individuals harboring the A allele of rs75603675 was found to have higher risk of severe COVID-19 compared to the C allele [OR (95%CI): 1.95 (1.11–3.39), p = 0.019]. Also, the genotype A/A [OR (95%CI): 5.13 (1.00–26.38), p = 0.033] of rs75603675 was associated with increased risk of severe COVID-19 under the recessive genetic inheritance model. Although the impact of COVID-19 pandemic has waned due to vaccination and public health measures, continued research on the association of COVID-19 disease severity and infection susceptibility with host genetics is required to shed valuable insights on the future long-term health effects of COVID-19 and impact of new variants on different populations and enable implication of proper informed healthcare strategies during future public health crises.

Incidence and risk of post-COVID-19 thromboembolic disease and the impact of aspirin prescription; nationwide observational cohort at the US Department of Veteran Affairs.

COVID-19 triggers prothrombotic and proinflammatory changes, with thrombotic disease prevalent in up to 30% SARS-CoV-2 infected patients. Early work suggests that aspirin could prevent COVID-19 related thromboembolic disorders in some studies but not others. This study leverages data from the largest integrated healthcare system in the United States to better understand this association. Our objective was to evaluate the incidence and risk of COVID-19 associated acute thromboembolic disorders and the potential impact of aspirin. This retrospective, observational study utilized national electronic health record data from the Veterans Health Administration. 334,374 Veterans who tested positive for COVID-19 from March 2, 2020, to June 13, 2022, were included, 81,830 of whom had preexisting aspirin prescription prior to their COVID-19 diagnosis. Patients with and without aspirin prescriptions were matched and the odds of post-COVID acute thromboembolic disorders were assessed. 10.1% of Veterans had a documented thromboembolic disorder within 12 months following their COVID-19 diagnosis. Those with specific comorbidities were at greatest risk. Preexisting aspirin prescription was associated with a significant decrease risk of post-COVID-19 thromboembolic disorders, including pulmonary embolism (OR [95% CI]: 0.69 [0.65, 0.74]) and deep vein thrombosis (OR [95% CI]: 0.76 [0.69, 0.83], but an increased risk of acute arterial diseases, including ischemic stroke (OR [95% CI]: 1.54 [1.46, 1.60]) and acute ischemic heart disease (1.33 [1.26, 1.39]). Findings demonstrated that preexisting aspirin prescription prior to COVID-19 diagnosis was associated with significantly decreased risk of venous thromboembolism and pulmonary embolism but increased risk of acute arterial disease. The risk of arterial disease may be associated with increased COVID-19 prothrombotic effects superimposed on preexisting chronic cardiovascular disease for which aspirin was already prescribed. Prospective clinical trials may help to further assess the efficacy of aspirin use prior to COVID-19 diagnosis for the prevention of post-COVID-19 thromboembolic disorders.

Poor stress resilience in adolescence predicts higher risk of severe COVID-19 and other respiratory infections: A prospective cohort study of 1.4 million Swedish men

ObjectivesTo investigate the associations between stress resilience in late adolescence and later risk of severe COVID-19 and other lower respiratory infections. A secondary aim was to examine potential confounding between low cardiorespiratory fitness (CRF) and stress resilience in relation to respiratory infection. MethodsWe conducted a registry-based cohort study of 1.4 million Swedish men, undergoing military conscription between 1968 and 2005. All were assessed by a psychologist for stress resilience, receiving a score between 1 and 9. The outcomes were hospitalization or death due to COVID-19 from March 2020 to September 2021 and hospitalization due to bacterial or viral pneumonia from conscription until January 2020. A secondary aim was to examine potential confounding between low cardiorespiratory fitness (CRF) and stress resilience in relation to respiratory infection. ResultsPoor stress resilience in late adolescence is associated with later risk of severe lower respiratory infections. Using a high resilience score as the reference, the hazard ratio (95 % CI) for death due to COVID-19 for the lowest scores was 1.49 (1.01–2.18) adjusted for CRF and other confounders. The corresponding adjusted hazard ratios for hospitalization due to bacterial pneumonia were 2.28 (2.03–2.57) and for viral pneumonia 1.92 (1.33–2.79). No significant interaction was seen between stress resilience and CRF in the analysis. ConclusionsPoor stress resilience is a prospective factor for severe COVID-19 as well as for bacterial and viral respiratory pneumonia endpoints, independent of CRF. These findings imply an effect of late adolescent stress resilience on the immune system later in life.

Understanding the influence of meaningfulness on memorable tourism experience (MTE) to invoke revisit intention in tourists with moderating effect of the perceived risk of COVID-19

ABSTRACT This study aims to explore meaningfulness and examine its impact on memorable tourism experience (MTE) and the subsequent effect on the revisit intention. The study also investigates the moderating effect of the perceived risk of COVID-19 on the relationship between MTE and revisit intention. The data were collected from tourists travelling to central India destinations through a survey. Partial least squares structural equation modeling (PLS-SEM) was used to analyze the collected data of 549 tourists. It is also found that MTE directly and positively influences revisit intention in tourists. The result also shows that meaningfulness indirectly affects revisit intention of tourists when the relationship is mediated via MTE. Perceived risk of COVID-19 negatively moderates the relationship between MTE and revisit intention. All these results help destination managers and tourism practitioners make more informed decisions to improve the experience of tourists further and make travel destinations more sustainable.

Risk of Urinary Tract Infection and Bacteremia in Infants Infected With COVID-19.

Our objective was to evaluate the risk of urinary tract infection (UTI) and bacteremia in infants 1 year or less of age infected with COVID-19. This was a retrospective study from TriNetX database in the United States. This study was from March 11, 2020, to May 11, 2023, during the COVID-19 pandemic. Patients were included if they were infants, 1 year or less, had a fever, and had a COVID-19 polymerase chain reaction test 1 week before or after presentation to the emergency department (ED) or hospital. We compared outcomes of bacteremia and a UTI in those with COVID-19 and those without COVID-19. Propensity matching was done to account for the confounders of age, gender, race, immune disorders, genitourinary abnormalities, preterm birth, and circumcision. Infants who were positive for COVID-19 were at a reduced risk of UTI and bacteremia. There was a significant decreased risk of having a UTI if one had COVID-19 (1.0%) versus those without COVID-19 (2.3%) (risk ratio = 0.37, 95% confidence interval = 0.37-0.50, P < 0.001). For bacteremia, there was also a decreased risk if the infant had COVID-19 (0.4%), versus those without COVID-19 (0.5%) (risk ratio = 0.74, 95% confidence interval = 0.56-0.97, P = 0.03). Infants with fever found to have COVID-19 had lower risks of UTI and bacteremia.

COVID-19 worry and smoking processes among Hispanic persons in the United States

Hispanic persons in the United States (US) experienced a disproportionate proportion of adverse health consequences during the pandemic and are a well-established tobacco disparities population. The tendency to worry is one individual difference cognitive-affective construct that is important to smoking behavior and stress-related experiences during the COVID-19 pandemic. However, there is limited understanding of COVID-19 worry in terms of smoking processes among Hispanic persons who smoke during the pandemic. The present investigation examined if COVID-19 worry during the pandemic (February 2021-July 2021) was associated with several processes linked to the maintenance and relapse of smoking among Hispanic persons who smoke. Participants included 337 Hispanic persons who smoke (≥5 cigarettes per day; Mage = 35.5 years old, 37.3% identified as female). Results indicated that in adjusted models covarying for the effects of sex, age, highest level of education, nativity, average number of cigarettes smoked per day, hazardous drinking, drug use problems, and depression, COVID-19 worry was related to increased risk of cigarette dependence, perceived barriers for quitting smoking, and more severe problems when trying to quit. These data are the first to identify an association between heightened COVID-19 worry and risk processes related to the maintenance and relapse of smoking among the Hispanic population in the US.