Estimating excess 1-year mortality associated with the COVID-19 pandemic according to underlying conditions and age: a population-based cohort study

Final assessment of the COVID-19 pandemic impact between the different social and economic strata population of the city of Buenos Aires

Background

During the pandemic, epidemiological communications reported an estimation of excess deaths. However, the final calculation requires a detailed analysis. The study aim was to ascertain the number and distribution of COVID-19 fatalities among various socio-economic strata in a large, moderate to low-income city.

Study design

Observational time series analysis in a large city, treated as a natural experiment.

Methods

Analysis of death certificates, demographic data, and health system records of positive RT-PCR COVID-19 tests from 2015 to 2021, categorizing by age, sex, and place of residence. The study measured the pandemic's impact on mortality, including COVID and non-COVID deaths, using corrected Poisson regression models for different demographics and assessing socio-economic status impact via ecological community-level analysis.

Results

Compared to the pre-pandemic period (2015-2019, IRR = 1.00), the sex- and age-adjusted rate of all-cause death increased significantly during the pandemic (2020-2021) IRR = 1.109 [1.054-1.167], p < 0.0001. This was observed in both males (IRR = 1.158 [1.1-1.219], p < 0.0001) and females (IRR = 1.068 [1.016-1.124], p = 0.01). There was no observed effect of the pandemic on the historical trend in the progressive reduction of mortality in people under 35 years of age. The increase in deaths was at the expense of COVID (+11,175 deaths) and cardiovascular causes (IRR = 1.114 [1.020-1.217] p = 0.017). During the pandemic, there was a significant increase in deaths at home (IRR = 1.219 [1197-1.242], p < 0.0001), especially in people dying of cardiovascular causes (IRR = 1.391 [1.360-1.422], p < 0.0001). The increase in the adjusted mortality rate during the pandemic was socially conditioned.

Conclusions

The pandemic not only led to increased COVID-19 mortality but also heightened fatalities from non-COVID causes, reflecting a potential bias in healthcare resource allocation towards SARS-CoV-2 at the expense of chronic pathologies care.

Modelling on COVID-19 control with double and booster-dose vaccination

COVID-19 vaccines have been illustrated to lessen the growth of sickness caused by the virus effectively. In any case, inoculation has consistently been controversial, with differing opinions and viewpoints. This has compelled some individuals to decide against receiving the vaccine. These divergent viewpoints have had a trivial impact on the epidemic's dynamics and the disease's development. In response to vaccinated individuals still falling ill, many countries have implemented booster vaccines to protect further. In this specific investigation, a mathematical model composed of seven compartments is employed to examine the effectiveness of a booster dose in preventing and treating the transmission of COVID-19. The principles of mathematics are employed to analyse and investigate the dynamics of the disease. Using a qualitative prototype analysis, we acquired valuable insights into its effectiveness. One essential aspect is the basic reproduction number, a critical determinant of the disease's spread. This calculation is determined by studying the system's equilibrium and evaluating its stability. Furthermore, we examined the balance from a local and global viewpoint, considering the possibility of bifurcation and the model's reproductive number sensitivity index. Through numerical simulations, we have visually illustrated the analytical findings outlined in this research paper and presented a thorough examination of the efficacy of booster shots as a preventive and therapeutic measure in the spread dynamics of COVID-19.

Associations Between COVID-19, Delirium, and 1-Year Mortality: Exploring Influences on Delirium Incidence in COVID-19 Patients

BACKGROUND

This study investigated the relationship between coronavirus disease 2019 (COVID-19), delirium, and 1-year mortality. Factors associated with delirium in COVID-19 patients were identified, along with the influence of psychotropic medications on delirium.

METHODS

The study used the South Korean National Health Insurance Service database. Adult COVID-19 patients diagnosed between October 2020 and December 2021 were included, with a propensity score-matched control group. Time-dependent Cox regression assessed associations among COVID-19, delirium, and mortality. Logistic regression analyzed the impact of psychotropic medications on delirium incidence.

RESULTS

The study included 832,602 individuals, with 416,301 COVID-19 patients. COVID-19 (hazard ratio [HR], 3.03; 95% confidence interval [CI], 2.92-3.13) and delirium (HR, 2.33; 95% CI, 2.06-2.63) were independent risk factors for 1-year mortality. Comorbidities, insurance type, and residence were also related to mortality. Among COVID-19 patients, antipsychotic use was associated with lower delirium incidence (odds ratio [OR], 0.38; 95% CI, 0.30-0.47), while mood stabilizers (OR, 1.77; 95% CI, 1.40-2.21) and benzodiazepines (OR, 8.62; 95% CI, 7.46-9.97) were linked to higher delirium incidence.

CONCLUSION

COVID-19 and delirium are risk factors for 1-year mortality. Some factors associated with delirium in COVID-19 patients are modifiable and can be targeted in preventive and therapeutic interventions.

Cardiovascular diseases as risk factors of post-COVID syndrome: a systematic review

BACKGROUND

A growing proportion of people experience incomplete recovery months after contracting coronavirus disease 2019 (COVID-19). These COVID-19 survivors develop a condition known as post-COVID syndrome (PCS), where COVID-19 symptoms persist for > 12 weeks after acute infection. Limited studies have investigated PCS risk factors that notably include pre-existing cardiovascular diseases (CVD), which should be examined considering the most recent PCS data. This review aims to identify CVD as a risk factor for PCS development in COVID-19 survivors.

METHODS

Following the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) checklist, systematic literature searches were performed in the PubMed, Scopus, and Web of Science databases from the earliest date available to June 2023. Data from observational studies in English that described the association between CVD and PCS in adults (≥ 18 years old) were included. A minimum of two authors independently performed the screening, study selection, data extraction, data synthesis, and quality assessment (Newcastle-Ottawa Scale). The protocol of this review was registered under PROSPERO (ID: CRD42023440834).

RESULTS

In total, 594 studies were screened after duplicates and non-original articles had been removed. Of the 11 included studies, CVD including hypertension (six studies), heart failure (three studies), and others (two studies) were significantly associated with PCS development with different factors considered. The included studies were of moderate to high methodological quality.

CONCLUSION

Our review highlighted that COVID-19 survivors with pre-existing CVD have a significantly greater risk of developing PCS symptomology than survivors without pre-existing CVD. As heart failure, hypertension and other CVD are associated with a higher risk of developing PCS, comprehensive screening and thorough examinations are essential to minimise the impact of PCS and improve patients' disease progression.

Disparities by Social Determinants of Health: Links Between Long COVID and Cardiovascular Disease

Long COVID has been defined by the World Health Organisation as "continuation or development of new symptoms 3 months after the initial SARS-CoV-2 infection, with these symptoms lasting for at least 2 months with no other explanation." Cardiovascular disease is implicated as a risk factor, concomitant condition, and consequence of long COVID. As well as heterogeneity in definition, presentation, and likely underlying pathophysiology of long COVID, disparities by social determinants of health, extensively studied and described in cardiovascular disease, have been observed in 3 ways. First, underlying long-term conditions, such as cardiovascular disease and its risk factors, are associated with incidence and severity of long COVID, and previously described socioeconomic disparities in these factors are important in exacerbating disparities in long COVID. Second, socioeconomic disparities in management of COVID-19 may themselves lead to distal disparities in long COVID. Third, there are socioeconomic disparities in the way that long COVID is diagnosed, managed, and prevented. Together, factors such as age, sex, deprivation, and ethnicity have far-reaching implications in this new postviral syndrome across its management spectrum. There are similarities and differences compared with disparities for cardiovascular disease. Some of these disparities are in fact, inequalities, that is, rather than simply observed variations, they represent injustices with costs to individuals, communities, and economies. This review of current literature considers opportunities to prevent or at least attenuate these socioeconomic disparities in long COVID and cardiovascular disease, with special challenges for research, clinical practice, public health, and policy in a new disease which is evolving.

A Cross-Sectional Analysis of Bystander Cardiopulmonary Resuscitation (CPR): Behavioural Changes in the COVID-19 Era

Objectives The coronavirus disease 2019 (COVID-19) pandemic has impacted public health systems and individuals' behaviour, with decreasing survival rates among out-of-hospital cardiac arrest (OHCA) patients. Bystander cardiopulmonary resuscitation (CPR) improves OHCA outcomes, which may have been affected by COVID-19. We sought to understand the impacts of COVID-19 on bystanders' willingness to administer CPR in three Canadian provinces. Methods Participants ≥ 18 years of age were surveyed online about their current and recalled pre-pandemic attitudes toward CPR and perceived transmission risk. We compared mean willingness to perform various CPR actions before and during the pandemic using paired t-tests. Differences in willingness across three provinces were assessed using analysis of variance (ANOVA) and Tukey's Honestly Significant Difference (HSD) test. We also conducted Chi-square tests to assess changes in willingness to perform CPR on children and older adults. Results Five hundred thirty-five participants were surveyed from October 1 to November 15, 2021. The mean age was 42.7 years (SD 14.5), and 60.2% were female. Participants reported less willingness to perform chest compressions on strangers during the pandemic compared to their recollections before the pandemic (mean willingness 86.2% vs. 94.3% prior, p<0.001). With personal protective equipment (PPE) available, particularly masks, willingness recovered to 91.3% (p<0.001). Willingness was higher in Nova Scotia (NS) than in British Columbia (BC) or Ontario (ON). Reluctance to assist older adults increased from 6.6% to 12.0% (p=0.020). Conclusions This study highlights changes in CPR willingness during the COVID-19 pandemic, underscoring the importance of PPE and offering insights into public health strategies pertaining to CPR during a pandemic.

Updates in the pathophysiology of COVID-19 infection in male reproductive and sexual health: a literature review

This extensive comprehensive review explores the impact of the Coronavirus disease 2019 (COVID-19) pandemic on men's sexual and reproductive health. We conducted a literature review focusing on the possible pathophysiology by which severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) affects men's sexual and reproductive systems. We reviewed most of the studies that reported the impact of SARS-CoV-2 infection on the Testicular, Epididymal, Prostatic, and Penile tissue. Also, we focused on evaluating the SARS-CoV-2 infection on semen parameters and male reproductive hormones. Finally, we reviewed the COVID-19 vaccine's effect on male reproductive and sexual health. Findings revealed the adverse consequences of SARS-CoV-2 at cellular and organ levels on the male genital tract. However, the reported data are still controversial. The initial data regarding COVID-19 vaccination was promising promoted safety for men's reproductive and sexual health. We conclude this paper by offering recommendations to address these adverse consequences and potentially improve sexual and reproductive health among men in the post-COVID-19 pandemic era.

Demographic and Geographic Characterization of Excess Mortality During the COVID-19 Pandemic in Baltimore City, Maryland, March 2020 to March 2021

Estimates of excess mortality can provide insight into direct and indirect impacts of the coronavirus disease 2019 (COVID-19) pandemic beyond deaths specifically attributed to COVID-19. We analyzed death certificate data from Baltimore City, Maryland, from March 1, 2020, to March 31, 2021, and found that 1,725 individuals (95% confidence interval: 1,495, 1,954) died in excess of what was expected from all-cause mortality trends in 2016-2019; 1,050 (61%) excess deaths were attributed to COVID-19. Observed mortality was 23%-32% higher than expected among individuals aged 50 years and older. Non-White residents of Baltimore City also experienced 2 to 3 times higher rates of excess mortality than White residents (e.g., 37.4 vs. 10.7 excess deaths per 10,000 population among Black residents vs. White residents). There was little to no observed excess mortality among residents of hospice, long-term care, and nursing home facilities, despite accounting for nearly 30% (312/1,050) of recorded COVID-19 deaths. There was significant geographic variation in excess mortality within the city, largely following racial population distributions. These results demonstrate the substantial and unequal impact of the COVID-19 pandemic on Baltimore City residents and the importance of building robust, timely surveillance systems to track disparities and inform targeted strategies to remediate the impact of future epidemics.

Assessing the Disruption Impact on Healthcare Delivery

Health emergency outbreaks such as the COVID-19 pandemic make it challenging for healthcare systems to ration medical resources and patient care. Such disastrous events have been increasing over the past years and are becoming inevitable, necessitating the need for healthcare to be well-prepared and resilient to unpredictable rises in demand. Quantitative and qualitative based decision support systems increase the effectiveness of planning, alleviating uncertainties associated with the crisis. This study aims to understand how the COVID-19 pandemic has affected the performance of healthcare systems in different areas and to address the associated disruption. A cross-sectional online survey was conducted in the Kingdom of Saudi Arabia and the United Arab Emirates among healthcare workers who worked during the pandemic. The pandemic-related disruption and its psychometric properties were assessed using Structural Equations Modeling (SEM) with 5 latent factors: Staff Mental Health, Communication Level, Planning and Readiness, Healthcare Supply Chain, and Telehealth. Responses from highly qualified participants with many years of experience in hospital settings were collected and analyzed. Results show that the model satisfactorily fits the data with a CLI of 0.91 and TLI of 0.88. The model indicates that enhancing supply chain management, planning, telehealth usage, and communication level across the healthcare system can mitigate the disruption. However, the lack of mental health management for healthcare workers can significantly disrupt the quality of delivered care. Staff mental health and healthcare supply chain, respectively, are the highest contributors to varying degrees of disruption in healthcare delivery. This study provides a direction for more research focusing on determinants of healthcare efficiency. It also provides decision-makers insights into the main factors leading to disruptions in healthcare systems, allowing them to shape their outbreak response and better prepare for future health emergencies.

Changes in Patterns of Referral for Inpatient Rehabilitation Cancer Patients Due to COVID-19: A Retrospective Study

ABSTRACT

There is a paucity of literature on the effect of COVID-19 on hospital processes. We hypothesized that COVID-19 was associated with decreased cancer physiatry referrals in 2020. This is a retrospective cohort study of consecutive patients from April to July 2019 and 2020 admitted at an academic quaternary cancer center. The main outcomes were number of hospital admissions, rate, and characteristics of inpatient rehabilitation admissions and change in percentage of physiatry referrals as the primary endpoint. Results showed that in 2019, there were 387 referrals from 10,274 inpatient admissions (3.8%; 95% confidence interval, 2.4-4.2), compared with 337 referrals from 7051 admissions in 2020 (4.8%; 95% confidence interval, 4.3-5.3, P = 0.001). Hematology services referred more patients than neurosurgery in 2020 (20.4% vs. 31.4%; 48.2% vs. 26.5%, P = 0.01). Discharge disposition reflected an increased frequency of return to acute care service in 2020 (10.2% vs. 21.8%, P = 0.03). In conclusion, there was an increase in the rate of physiatry referrals despite a decrease in hospital admissions. There was an increase in referrals by hematology, likely due to emphasis on safe discharge and the populations hospitalized.

The Potential Role of Nitric Oxide as a Therapeutic Agent against SARS-CoV-2 Infection

The global coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become the greatest worldwide public health threat of this century, which may predispose multi-organ failure (especially the lung) and death despite numerous mild and moderate symptoms. Recent studies have unraveled the molecular and clinical characteristics of the infectivity, pathogenicity, and immune evasion of SARS-CoV-2 and thus improved the development of many different therapeutic strategies to combat COVID-19, including treatment and prevention. Previous studies have indicated that nitric oxide (NO) is an antimicrobial and anti-inflammatory molecule with key roles in pulmonary vascular function in the context of viral infections and other pulmonary disease states. This review summarized the recent advances of the pathogenesis of SARS-CoV-2, and accordingly elaborated on the potential application of NO in the management of patients with COVID-19 through antiviral activities and anti-inflammatory properties, which mitigate the propagation of this disease. Although there are some limits of NO in the treatment of COVID-19, it might be a worthy candidate in the multiple stages of COVID-19 prevention or therapy.

COVID-19, the COVID-19 response, and racial injustice: Associations with depressive and anxiety symptoms among US adults from April 2020 to March 2021

Background

People in the United States have faced numerous large and intersecting threats to their mental health since the onset of the coronavirus disease pandemic. This study aimed to understand the unique relationships between these co-occurring threats - including the police killings of unarmed Black people and the fight for racial justice - and how they affect mental health symptoms among various demographic groups.

Methods

Data on population mental health, state-level COVID-19 incidence rates, cases of police-involved killings, and occurrences of racial justice protests were analyzed. The primary outcome was depression or anxiety symptoms. Regression models were used to estimate prospective associations between individual-, household-, and state-level exposures to hypothesized mental health threats and subsequent depression or anxiety symptoms.

Results

Data from 2,085,041 individual participants were included. Most were women (51.2%), and most were white, non-Hispanic (61.2%), with almost half (47.7%) reporting some loss of household income since March 13, 2020. Neither the killing of unarmed Black people by police, nor the above-average occurrence of Black Lives Matter (BLM) protests, were observed to be associated with anxiety or depressive symptoms in the overall population, though the BLM protests were associated with reduced depressive and anxiety symptoms among younger participants. State-level COVID-19 incidence risk was more strongly associated with depressive and anxiety symptoms among women, Black people, older people, and higher income people, compared to men, white people, younger people, and lower income people.

Conclusion

Our findings are relevant for anticipating and addressing the mental health consequences of social injustice and protest movements in the context of COVID-19 pandemic, as well as future pandemics. Promoting population mental health requires addressing underlying social and structural inequities and prioritizing the pursuit of social justice and health equity as a primary mental health intervention.

Risk preferences, preventive behaviour, and the probability of a loss: Empirical evidence from the COVID-19 pandemic

RATIONALE

A theoretical model of optimal choice under risk, in which an individual chooses the level of prevention to avoid a loss, has the ambiguous prediction that a higher risk-taking preference increases the probability of a loss.

OBJECTIVE

To empirically investigate the prediction in the case of COVID-19 with individual-level survey data.

DATA

Survey data from the Understanding America Study (UAS). The UAS Coronavirus Tracking Survey followed 8628 respondents from March 2020 until July 2021 (29 survey waves) and data was gathered on having contracted COVID-19, vaccination, and preventive behaviour. Separate UAS modules gathered data on individuals' risk preferences; twice before and once during the COVID-19 pandemic. UAS also gathered data on pre-pandemic health and socio-economic status. Combining these data, and dropping missing observations, provided longitudinal data for 4335 respondents (96,370 observations) of whom 530 contracted COVID-19.

RESULTS

In support of the theoretical prediction, the empirical findings show that a one-standard deviation higher risk-taking preference is associated with about a one-third higher probability of contracting COVID-19 within two weeks. Furthermore, the findings show that individuals' risk-taking preference is negatively associated with the preventive behaviour of social distancing and not associated with getting vaccinated. There is, however, no support for preventive behaviour being associated with the probability of contracting COVID-19. The exception is for being vaccinated, which is negatively associated with the probability of contracting COVID-19. The findings, therefore, do not support that the positive association of the risk-taking preference with the probability of contracting COVID-19 is mediated through observed preventive behaviour.

CONCLUSIONS

The findings support the importance of individuals' risk-taking behaviour for contracting COVID-19 and, more generally, the importance of loss prevention as a risk management tool for individuals.

Multimorbidity patterns in COVID-19 patients and their relationship with infection severity: MRisk-COVID study

BACKGROUND

Several chronic conditions have been identified as risk factors for severe COVID-19 infection, yet the implications of multimorbidity need to be explored. The objective of this study was to establish multimorbidity clusters from a cohort of COVID-19 patients and assess their relationship with infection severity/mortality.

METHODS

The MRisk-COVID Big Data study included 14 286 COVID-19 patients of the first wave in a Spanish region. The cohort was stratified by age and sex. Multimorbid individuals were subjected to a fuzzy c-means cluster analysis in order to identify multimorbidity clusters within each stratum. Bivariate analyses were performed to assess the relationship between severity/mortality and age, sex, and multimorbidity clusters.

RESULTS

Severe infection was reported in 9.5% (95% CI: 9.0-9.9) of the patients, and death occurred in 3.9% (95% CI: 3.6-4.2). We identified multimorbidity clusters related to severity/mortality in most age groups from 21 to 65 years. In males, the cluster with highest percentage of severity/mortality was Heart-liver-gastrointestinal (81-90 years, 34.1% severity, 29.5% mortality). In females, the clusters with the highest percentage of severity/mortality were Diabetes-cardiovascular (81-95 years, 22.5% severity) and Psychogeriatric (81-95 years, 16.0% mortality).

CONCLUSION

This study characterized several multimorbidity clusters in COVID-19 patients based on sex and age, some of which were found to be associated with higher rates of infection severity/mortality, particularly in younger individuals. Further research is encouraged to ascertain the role of specific multimorbidity patterns on infection prognosis and identify the most vulnerable morbidity profiles in the community.

TRIAL REGISTRATION

NCT04981249. Registered 4 August 2021 (retrospectively registered).

SARS-CoV-2 Infection, Hospitalization, and Mortality in Adults With and Without Cancer

Importance

Patients with cancer are at increased risk of SARS-CoV-2-associated adverse outcomes.

Objective

To determine the associations of tumor type with SARS-CoV-2 infection, hospitalization, intensive care unit (ICU) admission, and death.

Design, Setting, and Participants

This retrospective, population-based cohort study included community-dwelling adults aged at least 18 years in Ontario, Canada, ICES-linked provincial health databases from January 1, 2020, to November 30, 2021. Data were analyzed from December 1, 2021, to November 1, 2022.

Exposures

Cancer diagnosis.

Main Outcomes and Measures

The primary outcome was SARS-CoV-2 infection, and secondary outcomes included all-cause 14-day hospitalization, 21-day ICU admission, and 28-day death following SARS-CoV-2 infection. Cox proportional hazards models were used to obtain adjusted hazard ratios (aHRs) and 95% CIs.

Results

Of 11 732 108 people in the ICES-linked health databases, 279 287 had cancer (57.2% female; mean [SD] age, 65.9 [16.1] years) and 11 452 821 people did not have cancer (45.7% female; mean [SD] age, 65.9 [16.0] years). Overall, 464 574 individuals (4.1%) developed SARS-CoV-2 infection. Individuals with hematologic malignant neoplasms (33 901 individuals) were at increased risk of SARS-CoV-2 infection (aHR, 1.19; 95% CI, 1.13-1.25), 14-day hospitalization (aHR, 1.75; 95% CI, 1.57-1.96), and 28-day mortality (aHR, 2.03; 95% CI, 1.74-2.38) compared with the overall population, while individuals with solid tumors (245 386 individuals) were at lower risk of SARS-CoV-2 infection (aHR, 0.93; 95% CI, 0.91-0.95) but increased risk of 14-day hospitalization (aHR, 1.11; 95% CI, 1.05-1.18) and 28-day mortality (aHR, 1.31; 95% CI, 1.19-1.44). The 28-day mortality rate was high in hospitalized patients with hematologic malignant neoplasms (163 of 321 hospitalized patients [50.7%]) or solid tumors (486 of 1060 hospitalized patients [45.8%]). However, the risk of 21-day ICU admission in patients with hematologic malignant neoplasms (aHR, 1.14; 95% CI, 0.93-1.40) or solid tumors (aHR, 0.93; 95% CI, 0.82-1.05) was not significantly different from that among individuals without cancer. The SARS-CoV-2 infection risk decreased stepwise with increasing numbers of COVID-19 vaccine doses received (1 dose: aHR, 0.63; 95% CI, 0.62-0.63; 2 doses: aHR, 0.16; 95% CI, 0.16-0.16; 3 doses: aHR, 0.05; 95% CI, 0.04-0.06).

Conclusions and Relevance

These findings highlight the importance of prioritization strategies regarding ICU access to reduce the mortality risk in increased-risk populations, such as patients with cancer.

Staying Home, Tweeting Hope: Mixed Methods Study of Twitter Sentiment Geographical Index During US Stay-At-Home Orders

BACKGROUND

Stay-at-home orders were one of the controversial interventions to curb the spread of COVID-19 in the United States. The stay-at-home orders, implemented in 51 states and territories between March 7 and June 30, 2020, impacted the lives of individuals and communities and accelerated the heavy usage of web-based social networking sites. Twitter sentiment analysis can provide valuable insight into public health emergency response measures and allow for better formulation and timing of future public health measures to be released in response to future public health emergencies.

OBJECTIVE

This study evaluated how stay-at-home orders affect Twitter sentiment in the United States. Furthermore, this study aimed to understand the feedback on stay-at-home orders from groups with different circumstances and backgrounds. In addition, we particularly focused on vulnerable groups, including older people groups with underlying medical conditions, small and medium enterprises, and low-income groups.

METHODS

We constructed a multiperiod difference-in-differences regression model based on the Twitter sentiment geographical index quantified from 7.4 billion geo-tagged tweets data to analyze the dynamics of sentiment feedback on stay-at-home orders across the United States. In addition, we used moderated effects analysis to assess differential feedback from vulnerable groups.

RESULTS

We combed through the implementation of stay-at-home orders, Twitter sentiment geographical index, and the number of confirmed cases and deaths in 51 US states and territories. We identified trend changes in public sentiment before and after the stay-at-home orders. Regression results showed that stay-at-home orders generated a positive response, contributing to a recovery in Twitter sentiment. However, vulnerable groups faced greater shocks and hardships during the COVID-19 pandemic. In addition, economic and demographic characteristics had a significant moderating effect.

CONCLUSIONS

This study showed a clear positive shift in public opinion about COVID-19, with this positive impact occurring primarily after stay-at-home orders. However, this positive sentiment is time-limited, with 14 days later allowing people to be more influenced by the status quo and trends, so feedback on the stay-at-home orders is no longer positively significant. In particular, negative sentiment is more likely to be generated in states with a large proportion of vulnerable groups, and the policy plays a limited role. The pandemic hit older people, those with underlying diseases, and small and medium enterprises directly but hurt states with cross-cutting economic situations and more complex demographics over time. Based on large-scale Twitter data, this sociological perspective allows us to monitor the evolution of public opinion more directly, assess the impact of social events on public opinion, and understand the heterogeneity in the face of pandemic shocks.

The role of CT-scan in the diagnosis and prognosis of COVID-19 in a sample of Iraqi patients referred to Al-Diwaniyah Teaching Hospital, Iraq

The respiratory system is the primary target of the SARS-CoV-2 virus, leading to clinical manifestations such as dry cough, fever, and shortness of breath. Other reported manifestations include generalized weakness, dizziness, headache, vomiting, and diarrhea. A chest CT scan is one of the best imaging tools to screen and diagnose COVID-19. This prospective observational study was conducted at Al-Diwaniyah Teaching Hospital in the mid-Euphrates region of Iraq to assess the prognostic role of chest CT examinations in COVID-19 patients between February 2020 and July the 15th, 2020. The study included 100 patients suspected of COVID-19 based on clinical features and microbiological investigations, comprising 72 males and 28 females aged between 30 and 55. All patients were SARS-CoV-2 PCR positive and had no history of chronic lung disease. We categorized patients into two groups based on changes in density and lesion area: patients with changes (n=55) and patients without changes (n=45). Furthermore, we divided all patients into three groups according to treatment requirements and symptom severity: group 1 included patients with severe symptoms who required CPAP and admission to the Respiratory Care Unit, group 2 consisted of patients with moderate symptoms who needed oxygen therapy and hospital admission, and group 3 comprised patients with mild symptoms who were treated as outpatients with medication. Upon correlating the change in density and lesion area with these groups, we observed that most patients with no changes were in group 1, while patients with changes were predominantly seen in group 2. Additionally, the ratio of lesion area in the mediastinal CT window to lung CT was identified as a potential prognostic factor for COVID-19 patients.

Coronial postmortem reports and indirect COVID-19 pandemic-related mortality

AIMS

Widespread disruption of healthcare services and excess mortality not directly attributed to COVID-19 occurred between March and May 2020. We undertook the first UK multicentre study of coroners' autopsies before and during this period using postmortem reports.

METHODS

We reviewed reports of non-forensic coroners' autopsies performed during the first COVID-19 lockdown (23 March to 8 May 2020), and the same period in 2018. Deaths were categorised as natural non-COVID-19, COVID-19-related, non-natural (suicide, drug and alcohol-related, traumatic, other). We provided opinion regarding whether delayed access to medical care or changes in behaviour due to lockdown were a potential factor in deaths.

RESULTS

Seven centres covering nine coronial jurisdictions submitted a total of 1100 coroners' autopsies (498 in 2018, 602 in 2020). In only 54 autopsies was death attributed to COVID-19 (9%). We identified a significant increase in cases where delays in accessing medical care potentially contributed to death (10 in 2018, 44 in 2020). Lockdown was a contributing factor in a proportion of suicides (24%) and drug and alcohol-related deaths (12%).

CONCLUSIONS

Postmortem reports have considerable utility in evaluating excess mortality due to healthcare and wider societal disruption during a pandemic. They provide information at an individual case level that is not available from assessment of death certification data. Detailed evaluation of coroners' autopsy reports, supported by appropriate regulatory oversight, is recommended to mitigate disruption and indirect causes of mortality in future pandemics. Maintaining access to healthcare, including substance misuse and mental health services, is an important consideration.

The total number of patients with any of four major fragility fractures decreased during the first wave of the COVID-19 epidemic in Japan, commencing before the state of emergency declaration, which was not as enforceable as lockdown

Durin g the first wave of the COVID-19 epidemic, the total number of patients with any of the four major fragility fractures, including both inpatients and first-visit outpatients, began to decline shortly before the state of emergency was declared, rather than immediately after it was declared.

PURPOSE

This study aimed to investigate the impact of public health measures in the first wave of the COVID-19 epidemic on the occurrence of major fragility fractures (MFFs).

METHODS

Patients aged 50 years or older who were hospitalized or had an initial visit as an outpatient for an MFF, defined as a proximal femoral fracture (PFF), vertebral fragility fracture (VFF), distal radius fracture (DRF), or a proximal humeral fracture (PHF), were included in this study. Three-phase interrupted time-series analyses were performed to evaluate the impact of the voluntary event cancellation request in late February 2020 and the emergency declaration in early April 2020 on changes in the total number of patients, including inpatients and first-visit outpatients.

RESULTS

A total of 166,560 patients with MFFs were included (92,767 PFFs, 26,158 VFFs, 33,869 DRFs, and 13,766 PHFs). From the end of February, in seven prefectures with high proportions of urbanization, decreasing trends were estimated for level changes and slope changes in the total number of patients with any of the four MFFs (level change: PFF; point estimate; - 13.5 (95% CI; - 43.4, 16.5), VFF; - 15.3 (- 32.2, 1.5), DRF; - 16.1 (- 39.9, 7.6), PHF; - 1.9 (- 13.6, 9.8), slope change: PFF; - 4.8 (- 14.0, 4.4), VFF; - 3.0 (- 8.1, 2.2), DRF; - 0.6 (- 7.9, 6.7), PHF; - 2.4 (- 6.0, 1.2)).

CONCLUSION

The findings suggested that the total number of patients with any of the four MFFs did not begin to decline from early April 2020 after the state of emergency was declared but earlier, in late February 2020.

The effectiveness of COVID deaths to COVID policies: A robust conditional approach

This paper examines the effectiveness of four major COVID-19 social distancing policies, (i) shelter-in-place orders (SIPO), (ii) non-essential business closures, (iii) mandatory quarantine for travelers, and (iv) bans on large gatherings, on both COVID cases and COVID deaths. Results indicate that states are highly ineffective in producing the fraction of the population that does not have COVID-19 or the fraction of the population that does not die from COVID-19. We find that having any form of social distancing policies increases the fraction of the population not considered a positive COVID-19 case by 23.5 percentage points. Results also show that having any of the four major social distancing policies reduces the fraction of the population who has died of COVID-19 by 1.3 percentage points between March 1, 2020 and September 1, 2020; during the first 100 days, effectiveness would improve by 2.1 percentage points. Evidence suggests that there is no effective uniform national COVID-19 social distancing policy. Furthermore, conditional efficiency regressions after 100 days suggest that behavioral noncompliance and premature expiration of social distancing policies both negatively impact effectiveness. Partial regression plots suggest that bans on large gatherings and the closure of non-essential businesses were the two most impactful COVID-19 social distancing policies.

An analytical approach to evaluate the impact of age demographics in a pandemic

The time required to identify and confirm risk factors for new diseases and to design an appropriate treatment strategy is one of the most significant obstacles medical professionals face. Traditionally, this approach entails several clinical studies that may last several years, during which time strict preventative measures must be in place to contain the epidemic and limit the number of fatalities. Analytical tools may be used to direct and accelerate this process. This study introduces a six-state compartmental model to explain and assess the impact of age demographics by designing a dynamic, explainable analytics model of the SARS-CoV-2 coronavirus. An age-stratified mathematical model taking the form of a deterministic system of ordinary differential equations divides the population into different age groups to better understand and assess the impact of age on mortality. It also provides a more accurate and effective interpretation of the disease evolution, specifically in terms of the cumulative numbers of infected cases and deaths. The proposed Kermack-Mckendrick model is incorporated into a non-linear least-squares optimization curve-fitting problem whose optimized parameters are numerically obtained using the Levenberg-Marquard algorithm. The curve-fitting model's efficiency is proved by testing the age-stratified model's performance on three U.S. states: Connecticut, North Dakota, and South Dakota. Our results confirm that splitting the population into different age groups leads to better fitting and forecasting results overall as compared to those achieved by the traditional method, i.e., without age groups. By using comprehensive models that account for age, gender, and ethnicity, regional public health authorities may be able to avoid future epidemics from inflicting more fatalities and establish a public health policy that reduces the burden on the elderly population.

Clinical Profile and Determinants of Mortality in Patients with Interstitial Lung Disease Admitted for COVID-19

BACKGROUND

Concern has risen about the effects of COVID-19 in interstitial lung disease (ILD) patients. The aim of our study was to determine clinical characteristics and prognostic factors of ILD patients admitted for COVID-19.

METHODS

Ancillary analysis of an international, multicenter COVID-19 registry (HOPE: Health Outcome Predictive Evaluation) was performed. The subgroup of ILD patients was selected and compared with the rest of the cohort.

RESULTS

A total of 114 patients with ILDs were evaluated. Mean ± SD age was 72.4 ± 13.6 years, and 65.8% were men. ILD patients were older, had more comorbidities, received more home oxygen therapy and more frequently had respiratory failure upon admission than non-ILD patients (all p < 0.05). In laboratory findings, ILD patients more frequently had elevated LDH, C-reactive protein, and D-dimer levels (all p < 0.05). A multivariate analysis showed that chronic kidney disease and respiratory insufficiency on admission were predictors of ventilatory support, and that older age, kidney disease and elevated LDH were predictors of death.

CONCLUSIONS

Our data show that ILD patients admitted for COVID-19 are older, have more comorbidities, more frequently require ventilatory support and have higher mortality than those without ILDs. Older age, kidney disease and LDH were independent predictors of mortality in this population.

Research-Practice Partnership to Develop and Implement Routine Mental Health Symptom Tracking Tool Among Older Adults During COVID-19

OBJECTIVE

Older adults are disproportionally impacted by the COVID-19 pandemic, causing a mental health crisis in late life, due to physical restrictions (e.g., quarantine), limited access to services, and lower literacy and access to technology. Despite established benefits, systematic screening of mental health needs of older adults in community and routine care settings is limited and presents multiple challenges. Cross-disciplinary collaborations are essential for identification and evaluation of mental health needs and service delivery.

METHODS

Using a research-practice partnership model, we developed and implemented a routine mental health needs identification and tracking tool at a community-based social services organization. Repeated screenings were conducted remotely over 5 months and included depression, anxiety, perceived loneliness, social support, and related domains such as sleep quality, resilience, and trauma symptoms linked to COVID-19. We examined symptomatic distress levels and associations between different domains of functioning.

RESULTS

Our project describes the process of establishing a research-practice partnership during the COVID-19 pandemic. We collected 292 screenings from 124 individuals; clients were mildly to moderately depressed and anxious, reporting large amounts of time alone and moderate levels of loneliness. Those reporting higher depressive symptoms reported higher anxiety symptoms, poorer sleep quality, lower quality of life, lower capacity to adapt to challenging situations, and greater trauma symptoms due to COVID-19.

CONCLUSION

Our routine screening tool can serve as a blueprint for case management agencies and senior centers nationwide, beyond the pressing mental health crisis due to COVID-19, to continue identifying needs as they emerge in the community.

Social Support in Older Transgender and Gender Diverse Communities in the United Kingdom and Australia: A Comparative Study During COVID-19

While the impact of the COVID-19 pandemic on older people has been recognized, there is limited understanding of its impact on older trans and gender diverse people who often have different experiences of care and support than the general population. This article examines older trans and gender diverse people's experience of social support during the COVID-19 pandemic, based on a comparative mixed method survey administered in Australia and the United Kingdom. Using a non-probability sample of 84 participants who were connected to social media and service organizations in the United Kingdom and Australia, we found some commonalities and differences between experiences in these countries. Some participants were isolated, including almost 1 in 5 participants who said that they did not have someone they could call upon in an emergency. However, participants had rich networks of friends, partners, and family members. Religious organizations and the community also played an important role. Friends were reported as the main emergency contacts and as the main people to whom support is provided. This research supports previous findings that friends of trans and gender diverse people play an important role in well-being.

A local government area based Covid-19 vulnerability analysis in Nigeria

Vulnerability to COVID-19 has been widely studied from varying perspectives, but susceptibility at the grassroots has not been adequately considered. The vulnerability of the 774 local government areas (LGAs) in Nigeria to COVID-19 and its predictors were determined using road distances from the two major entry airports in the country to each of the LGAs, socio-economic indices, quality of hygiene, and the level of exposure to mass media. LGA population data were obtained from the National Population Commission of Nigeria, while socio-economic and socio-demographic data were extracted from the 2018 NDHS report. Distances were determined with the aid of an online distance calculator, distantias. The single most important predictor was female non-exposure to mass media. Distances from the COVID-19 epicentres of Lagos and Abuja did not contribute much to the model. Thus, the result highlighted the strategic position of women in the African community and the potential of the mass media in disease control. The suppression of the established effect of distance suggests that vulnerability to COVID-19 in developing countries may not follow the path assumed in developed countries. Thus, the way to contain the disease in developing countries might be the active enlightenment of women.

Future Time Perspective and Psychological Well-Being for Older Canadian Women During the COVID-19 Pandemic

Relevant literature indicates that one's perception of future time is related to their psychological well-being, particularly for older adults. However, more research is needed to understand this relationship in the context of COVID-19. Older adults may be especially vulnerable to the psychological impacts of the pandemic, but findings on their psychological well-being during COVID-19 are mixed. The current study examines relationships between Future Time Perspective (FTP), COVID-19 impact, and Psychological Well-Being, and how these variables change over 8 months during the earlier period of the pandemic. The current study explored these relationships in a sample of older women in Ontario, Canada, at two time points (Mage = 70.39 at T1), who completed online Qualtrics surveys. We used hierarchical linear regressions to test our expectations that COVID-19 impact would be negatively associated with psychological well-being, whereas FTP would be positively associated with psychological well-being, and that FTP would moderate the relationship between COVID-19 impact and psychological well-being. We found partial support for these hypotheses. Our knowledge of the relationship between FTP and psychological well-being would benefit from research that continues to explore different contexts and diverse samples, to enhance understandings of important differences.

The COVID-19 pandemic's true death toll in Iran after two years: an interrupted time series analysis of weekly all-cause mortality data

INTRODUCTION

This study aimed to investigate overall and age group/region/sex-specific excess all-cause mortality from the inception of the COVID-19 pandemic in Iran until February 2022.

METHODS

Weekly all-cause mortality data were obtained for the period March 2015 until February 2022. We conducted interrupted time series analyses, using a generalized least-square regression model to estimate excess mortality after the COVID-19 pandemic. Using this approach, we estimated the expected post-pandemic death counts based on five years of pre-pandemic data and compared the results with observed mortality during the pandemic.

RESULTS

After the COVID-19 pandemic, we observed an immediate increase (1,934 deaths per week, p = 0.01) in weekly all-cause mortality. An estimated 240,390 excess deaths were observed in two years after the pandemic. Within the same period, 136,166 deaths were officially attributed to COVID-19. The excess mortality was greatest among males compared with females (326 versus 264 per 100k), with an increasing trend by age group. There is a clear increased excess mortality in the central and northwestern provinces.

CONCLUSION

We found that the full mortality burden during the outbreak has been much heavier than what is officially reported, with clear differences by sex, age group, and geographical region.

Effects of High Temperature on COVID-19 Deaths in U.S. Counties

The United States of America (USA) was afflicted by extreme heat in the summer of 2021 and some states experienced a record-hot or top-10 hottest summer. Meanwhile, the United States was also one of the countries impacted most by the coronavirus disease 2019 (COVID-19) pandemic. Growing numbers of studies have revealed that meteorological factors such as temperature may influence the number of confirmed COVID-19 cases and deaths. However, the associations between temperature and COVID-19 severity differ in various study areas and periods, especially in periods of high temperatures. Here we choose 119 US counties with large counts of COVID-19 deaths during the summer of 2021 to examine the relationship between COVID-19 deaths and temperature by applying a two-stage epidemiological analytical approach. We also calculate the years of life lost (YLL) owing to COVID-19 and the corresponding values attributable to high temperature exposure. The daily mean temperature is approximately positively correlated with COVID-19 deaths nationwide, with a relative risk of 1.108 (95% confidence interval: 1.046, 1.173) in the 90th percentile of the mean temperature distribution compared with the median temperature. In addition, 0.02 YLL per COVID-19 death attributable to high temperature are estimated at the national level, and distinct spatial variability from -0.10 to 0.08 years is observed in different states. Our results provide new evidence on the relationship between high temperature and COVID-19 deaths, which might help us to understand the underlying modulation of the COVID-19 pandemic by meteorological variables and to develop epidemic policy response strategies.

Direct and indirect mortality impacts of the COVID-19 pandemic in the United States, March 1, 2020 to January 1, 2022

Excess mortality studies provide crucial information regarding the health burden of pandemics and other large-scale events. Here, we use time series approaches to separate the direct contribution of SARS-CoV-2 infection on mortality from the indirect consequences of the pandemic in the United States. We estimate excess deaths occurring above a seasonal baseline from March 1, 2020 to January 1, 2022, stratified by week, state, age, and underlying mortality condition (including COVID-19 and respiratory diseases; Alzheimer's disease; cancer; cerebrovascular diseases; diabetes; heart diseases; and external causes, which include suicides, opioid overdoses, and accidents). Over the study period, we estimate an excess of 1,065,200 (95% Confidence Interval (CI) 909,800-1,218,000) all-cause deaths, of which 80% are reflected in official COVID-19 statistics. State-specific excess death estimates are highly correlated with SARS-CoV-2 serology, lending support to our approach. Mortality from 7 of the 8 studied conditions rose during the pandemic, with the exception of cancer. To separate the direct mortality consequences of SARS-CoV-2 infection from the indirect effects of the pandemic, we fit generalized additive models (GAM) to age- state- and cause-specific weekly excess mortality, using covariates representing direct (COVID-19 intensity) and indirect pandemic effects (hospital intensive care unit (ICU) occupancy and measures of interventions stringency). We find that 84% (95% CI 65-94%) of all-cause excess mortality can be statistically attributed to the direct impact of SARS-CoV-2 infection. We also estimate a large direct contribution of SARS-CoV-2 infection (≥67%) on mortality from diabetes, Alzheimer's, heart diseases, and in all-cause mortality among individuals over 65 years. In contrast, indirect effects predominate in mortality from external causes and all-cause mortality among individuals under 44 years, with periods of stricter interventions associated with greater rises in mortality. Overall, on a national scale, the largest consequences of the COVID-19 pandemic are attributable to the direct impact of SARS-CoV-2 infections; yet, the secondary impacts dominate among younger age groups and in mortality from external causes. Further research on the drivers of indirect mortality is warranted as more detailed mortality data from this pandemic becomes available.

Implications of an HbA1c-based Diabetes Screening on Prevalence and Effect of Dysglycemia in Patients With COVID-19

CONTEXT

In patients with severe acute respiratory syndrome coronavirus type 2 infection, diabetes is associated with poor COVID-19 prognosis. However, case detection strategy is divergent and reported prevalence varies from 5% to 35%.

OBJECTIVE

We examined how far the choice of screening tools affects the detection rate of dysglycemia and in consequence the estimation of diagnosis-associated risk for moderate (mo) or severe (s) COVID-19.

METHODS

Non-intensive care unit inpatients with COVID-19 were screened systematically at admission for diabetes (D) and prediabetes (PreD) by glycated hemoglobin A1c (HbA1c) (A), random blood glucose (B), and known history (C) from November 1, 2020 to March 8, 2021. Dysglycemia rate and effect on COVID-19 outcome were analyzed in 2 screening strategies (ABC vs BC).

RESULTS

A total of 578 of 601 (96.2%) of admitted patients were screened and analyzed. In ABC, prevalence of D and PreD was 38.2% and 37.5%, respectively. D was significantly associated with an increased risk for more severe COVID-19 (adjusted odds ratio [aOR] [moCOVID-19]: 2.27, 95% CI, 1.16-4.46 and aOR [sCOVID-19]: 3.26, 95% CI, 1.56-6.38). Patients with PreD also presented more often with more severe COVID-19 than those with normoglycemia (aOR [moCOVID-19]: 1.76, 95% CI, 1.04-2.97 and aOR [sCOVID-19]: 2.41, 95% CI, 1.37-4.23). Screening with BC failed to identify only 96% of PreD (206/217) and 26.2% of D diagnosis (58/221) and missed associations of dysglycemia and COVID-19 severity.

CONCLUSION

Pandemic conditions may hamper dysglycemia detection rate and in consequence the awareness of individual patient risk for COVID-19 severity. A systematic diabetes screening including HbA1c reduces underdiagnosis of previously unknown or new-onset dysglycemia, and enhances the quality of risk estimation and access of patients at risk to a diabetes-specific intervention.

What motivated residents of Saudi Arabia to receive the COVID-19 vaccine?

Background

Acceptance of vaccination is a multifactorial issue. The unprecedented speed at which the COVID-19 disease spread globally has meant that people have had to face the idea of receiving novel vaccines for a novel disease.

Purpose

Studies conducted earlier in the pandemic had shown high vaccine hesitancy in Saudi Arabia, therefore we wanted to understand the motivating factors for people living in Saudi Arabia with regards to accepting the COVID-19 vaccine, our survey was conducted when the government had already mandated vaccination to enter public spaces. Saudi society is not particularly outspoken and therefore it was of special importance to the authors to explore the motivation behind COVID-19 vaccines.

Methods

This is a cross-sectional survey of 802 participants living in Saudi Arabia. The questionnaire was distributed to staff, visitors, and patients in a hospital in Saudi Arabia and via electronic means to the general population.

Results

A total of 521 (65%) of the respondents were women, and 281 (35%) were men. A total of 710 (88.5%) were Saudi, and 55 (6.9%) were non-Saudi. The majority of participants (496, 65.7%) stated that they registered for the vaccine as soon as it was available, with 185 (24.5%) stating that they registered when they were mandated to do so and 74 (9.8%) registered only when they felt cases were increasing. Most participants (316, 41%) stated that the main reason for taking the vaccine was one of a self-protective nature, followed by indirect vaccination (240, 31.1%), paternalistic reasons (157, 20.4%) and altruistic reasons (58, 7.5%).

Conclusions

With the increased burden on healthcare that is being faced by COVID-19, other resources need to be carefully allocated. This paper may aid the Saudi government in understanding the motivation for the population to take the vaccine and therefore facilitate any future vaccination campaigns to ensure the best utilization of resources.

Human Gut Microbiota and Its Metabolites Impact Immune Responses in COVID-19 and Its Complications

BACKGROUND & AIMS

We investigate interrelationships between gut microbes, metabolites, and cytokines that characterize COVID-19 and its complications, and we validate the results with follow-up, the Japanese 4D (Disease, Drug, Diet, Daily Life) microbiome cohort, and non-Japanese data sets.

METHODS

We performed shotgun metagenomic sequencing and metabolomics on stools and cytokine measurements on plasma from 112 hospitalized patients with SARS-CoV-2 infection and 112 non-COVID-19 control individuals matched by important confounders.

RESULTS

Multiple correlations were found between COVID-19-related microbes (eg, oral microbes and short-chain fatty acid producers) and gut metabolites (eg, branched-chain and aromatic amino acids, short-chain fatty acids, carbohydrates, neurotransmitters, and vitamin B6). Both were also linked to inflammatory cytokine dynamics (eg, interferon γ, interferon λ3, interleukin 6, CXCL-9, and CXCL-10). Such interrelationships were detected highly in severe disease and pneumonia; moderately in the high D-dimer level, kidney dysfunction, and liver dysfunction groups; but rarely in the diarrhea group. We confirmed concordances of altered metabolites (eg, branched-chain amino acids, spermidine, putrescine, and vitamin B6) in COVID-19 with their corresponding microbial functional genes. Results in microbial and metabolomic alterations with severe disease from the cross-sectional data set were partly concordant with those from the follow-up data set. Microbial signatures for COVID-19 were distinct from diabetes, inflammatory bowel disease, and proton-pump inhibitors but overlapping for rheumatoid arthritis. Random forest classifier models using microbiomes can highly predict COVID-19 and severe disease. The microbial signatures for COVID-19 showed moderate concordance between Hong Kong and Japan.

CONCLUSIONS

Multiomics analysis revealed multiple gut microbe-metabolite-cytokine interrelationships in COVID-19 and COVID-19related complications but few in gastrointestinal complications, suggesting microbiota-mediated immune responses distinct between the organ sites. Our results underscore the existence of a gut-lung axis in COVID-19.

Sympathetic Neural Overdrive, Aortic Stiffening, Endothelial Dysfunction, and Impaired Exercise Capacity in Severe COVID-19 Survivors: A Mid-Term Study of Cardiovascular Sequelae

BACKGROUND

COVID-19 has become a dramatic health problem during this century. In addition to high mortality rate, COVID-19 survivors are at increased risk for cardiovascular diseases 1-year after infection. Explanations for these manifestations are still unclear but can involve a constellation of biological alterations. We hypothesized that COVID-19 survivors compared with controls exhibit sympathetic overdrive, vascular dysfunction, cardiac morpho-functional changes, impaired exercise capacity, and increased oxidative stress.

METHODS

Nineteen severe COVID-19 survivors and 19 well-matched controls completed the study. Muscle sympathetic nerve activity (microneurography), brachial artery flow-mediated dilation and blood flow (Doppler-Ultrasound), carotid-femoral pulse wave velocity (Complior), cardiac morpho-functional parameters (echocardiography), peak oxygen uptake (cardiopulmonary exercise testing), and oxidative stress were measured ~3 months after hospital discharge. Complementary experiments were conducted on human umbilical vein endothelial cells cultured with plasma samples from subjects.

RESULTS

Muscle sympathetic nerve activity and carotid-femoral pulse wave velocity were greater and brachial artery flow-mediated dilation, brachial artery blood flow, E/e' ratio, and peak oxygen uptake were lower in COVID-19 survivors than in controls. COVID-19 survivors had lower circulating antioxidant markers compared with controls, but there were no differences in plasma-treated human umbilical vein endothelial cells nitric oxide production and reactive oxygen species bioactivity. Diminished peak oxygen uptake was associated with sympathetic overdrive, vascular dysfunction, and reduced diastolic function in COVID-19 survivors.

CONCLUSIONS

Our study revealed that COVID-19 survivors have sympathetic overactivation, vascular dysfunction, cardiac morpho-functional changes, and reduced exercise capacity. These findings indicate the need for further investigation to determine whether these manifestations are persistent longer-term and their impact on the cardiovascular health of COVID-19 survivors.

Impact of the first wave of the COVID-19 pandemic on non-COVID inpatient care in southern Spain

We assessed the impact of the first wave of COVID-19 pandemic on non-COVID hospital admissions, non-COVID mortality, factors associated with non-COVID mortality, and changes in the profile of non-COVID patients admitted to hospital. We used the Spanish Minimum Basic Data Set with diagnosis grouped according to the Diagnostic Related Groups. A total of 10,594 patients (3% COVID-19; 97% non-COVID) hospitalised during the first wave in 2020 (27-February/07-June) were compared with those hospitalised within the same dates of 2017-2019 (average annual admissions: 14,037). We found a decrease in non-COVID medical (22%) and surgical (33%) hospitalisations and a 25.7% increase in hospital mortality among non-COVID patients during the first pandemic wave compared to pre-pandemic years. During the officially declared sub-period of excess mortality in the area (17-March/20-April, in-hospital non-COVID mortality was even higher (58.7% higher than the pre-pandemic years). Non-COVID patients hospitalised during the first pandemic wave (compared to pre-pandemic years) were older, more frequently men, with longer hospital stay and increased disease severity. Hospitalisation during the first pandemic wave in 2020, compared to hospitalisation during the pre-pandemic years, was an independent risk factor for non-COVID mortality (HR 1.30, 95% CI 1.07-1.57, p = 0.008), reflecting the negative impact of the pandemic on hospitalised patients.

Occupational differences in COVID-19 incidence, severity, and mortality in the United Kingdom: Available data and framework for analyses

There are important differences in the risk of SARS-CoV-2 infection and death depending on occupation. Infections in healthcare workers have received the most attention, and there are clearly increased risks for intensive care unit workers who are caring for COVID-19 patients. However, a number of other occupations may also be at an increased risk, particularly those which involve social care or contact with the public. A large number of data sets are available with the potential to assess occupational risks of COVID-19 incidence, severity, or mortality. We are reviewing these data sets as part of the Partnership for Research in Occupational, Transport, Environmental COVID Transmission (PROTECT) initiative, which is part of the National COVID-19 Core Studies. In this report, we review the data sets available (including the key variables on occupation and potential confounders) for examining occupational differences in SARS-CoV-2 infection and COVID-19 incidence, severity and mortality. We also discuss the possible types of analyses of these data sets and the definitions of (occupational) exposure and outcomes. We conclude that none of these data sets are ideal, and all have various strengths and weaknesses. For example, mortality data suffer from problems of coding of COVID-19 deaths, and the deaths (in England and Wales) that have been referred to the coroner are unavailable. On the other hand, testing data is heavily biased in some periods (particularly the first wave) because some occupations (e.g. healthcare workers) were tested more often than the general population. Random population surveys are, in principle, ideal for estimating population prevalence and incidence, but are also affected by non-response. Thus, any analysis of the risks in a particular occupation or sector (e.g. transport), will require a careful analysis and triangulation of findings across the various available data sets.

Occupational differences in COVID-19 incidence, severity, and mortality in the United Kingdom: Available data and framework for analyses

There are important differences in the risk of SARS-CoV-2 infection and death depending on occupation. Infections in healthcare workers have received the most attention, and there are clearly increased risks for intensive care unit workers who are caring for COVID-19 patients. However, a number of other occupations may also be at an increased risk, particularly those which involve social care or contact with the public. A large number of data sets are available with the potential to assess occupational risks of COVID-19 incidence, severity, or mortality. We are reviewing these data sets as part of the Partnership for Research in Occupational, Transport, Environmental COVID Transmission (PROTECT) initiative, which is part of the National COVID-19 Core Studies. In this report, we review the data sets available (including the key variables on occupation and potential confounders) for examining occupational differences in SARS-CoV-2 infection and COVID-19 incidence, severity and mortality. We also discuss the possible types of analyses of these data sets and the definitions of (occupational) exposure and outcomes. We conclude that none of these data sets are ideal, and all have various strengths and weaknesses. For example, mortality data suffer from problems of coding of COVID-19 deaths, and the deaths (in England and Wales) that have been referred to the coroner are unavailable. On the other hand, testing data is heavily biased in some periods (particularly the first wave) because some occupations (e.g. healthcare workers) were tested more often than the general population. Random population surveys are, in principle, ideal for estimating population prevalence and incidence, but are also affected by non-response. Thus, any analysis of the risks in a particular occupation or sector (e.g. transport), will require a careful analysis and triangulation of findings across the various available data sets.

Assessing the Impact of COVID-19 on the Health of Native Hawaiian/Pacific Islander People in the United States, 2021

OBJECTIVES

Minimal research has assessed COVID-19's unique impact on the Native Hawaiian/Pacific Islander (NH/PI) population-an Indigenous-colonized racial group with social and health disparities that increase their risk for COVID-19 morbidity and mortality. To address this gap, we explored the scope of COVID-19 outcomes, vaccination status, and health in diverse NH/PI communities.

METHODS

NH/PI staff at partner organizations collected survey data from April through November 2021 from 319 community-dwelling NH/PI adults in 5 states with large NH/PI populations: Arkansas, California, Oregon, Utah, and Washington. Data were analyzed with descriptive statistics, Pearson χ2 tests, independent and paired t tests, and linear and logistic regression analyses.

RESULTS

During the COVID-19 pandemic, 30% of survey participants had contracted COVID-19, 16% had a close family member who died of the disease, and 64% reported COVID-19 vaccine uptake. Thirty percent reported fair/poor health, 21% currently smoked cigarettes, and 58% reported obesity. Survey participants reported heightened COVID-19-related psychosocial distress (mean score = 4.9 on 10-point scale), which was more likely when health outcomes (general health, sleep, obesity) were poor or a family member had died of COVID-19. Logistic regression indicated that age, experiencing COVID-19 distress, and past-year use of influenza vaccines were associated with higher odds of COVID-19 vaccine uptake (1.06, 1.18, and 7.58 times, respectively).

CONCLUSIONS

Our empirical findings highlight the acute and understudied negative impact of COVID-19 on NH/PI communities in the United States and suggest new avenues for improving NH/PI community health, vaccination, and recovery from COVID-19.

An agent-based model of COVID-19 pandemic and its variants using fuzzy subsets and real data applied in an island environment

In this paper, we present a model of the spread of the COVID-19 pandemic simulated by a multi-agent system (MAS) based on demographic data and medical knowledge. Demographic data are linked to the distribution of the population according to age and to an index of socioeconomic fragility with regard to the elderly. Medical knowledge are related to two risk factors: age and obesity. The contributions of this approach are as follows. Firstly, the two aggravating risk factors are introduced into the MAS using fuzzy sets. Secondly, the worsening of disease caused by these risk factors is modeled by fuzzy aggregation operators. The appearance of virus variants is also introduced into the simulation through a simplified modeling of their contagiousness. Using real data from inhabitants of an island in the Antilles (Guadeloupe, FWI), we model the rate of the population at risk which could be critical cases, if neither social distancing nor barrier gestures are respected by the entire population. The results show that hospital capacities are exceeded. The results show that hospital capacities are exceeded. The socioeconomic fragility index is used to assess mortality and also shows that the number of deaths can be significant.

Using national electronic health records for pandemic preparedness: validation of a parsimonious model for predicting excess deaths among those with COVID-19-a data-driven retrospective cohort study

OBJECTIVES

To use national, pre- and post-pandemic electronic health records (EHR) to develop and validate a scenario-based model incorporating baseline mortality risk, infection rate (IR) and relative risk (RR) of death for prediction of excess deaths.

DESIGN

An EHR-based, retrospective cohort study.

SETTING

Linked EHR in Clinical Practice Research Datalink (CPRD); and linked EHR and COVID-19 data in England provided in NHS Digital Trusted Research Environment (TRE).

PARTICIPANTS

In the development (CPRD) and validation (TRE) cohorts, we included 3.8 million and 35.1 million individuals aged ≥30 years, respectively.

MAIN OUTCOME MEASURES

One-year all-cause excess deaths related to COVID-19 from March 2020 to March 2021.

RESULTS

From 1 March 2020 to 1 March 2021, there were 127,020 observed excess deaths. Observed RR was 4.34% (95% CI, 4.31-4.38) and IR was 6.27% (95% CI, 6.26-6.28). In the validation cohort, predicted one-year excess deaths were 100,338 compared with the observed 127,020 deaths with a ratio of predicted to observed excess deaths of 0.79.

CONCLUSIONS

We show that a simple, parsimonious model incorporating baseline mortality risk, one-year IR and RR of the pandemic can be used for scenario-based prediction of excess deaths in the early stages of a pandemic. Our analyses show that EHR could inform pandemic planning and surveillance, despite limited use in emergency preparedness to date. Although infection dynamics are important in the prediction of mortality, future models should take greater account of underlying conditions.

Effectiveness of BNT162b2 and CoronaVac vaccinations against SARS-CoV-2 omicron infection in people aged 60 years or above: a case-control study

BACKGROUND

In view of limited evidence that specifically addresses vaccine effectiveness (VE) in the older population, this study aims to evaluate the real-world effectiveness of BNT162b2 and CoronaVac in older adults during the Omicron BA.2 outbreak.

METHODS

This case-control study analyzed data available between January and March 2022 from the electronic health databases in Hong Kong and enrolled individuals aged 60 or above. Each case was matched with up to 10 controls by age, sex, index date and Charlson Comorbidity Index for the four outcomes (COVID-19 infection, COVID-19-related hospitalization, severe complications, and all-cause mortality) independently. Conditional logistic regression was conducted to evaluate VE of BNT162b2 and CoronaVac against COVID-19-related outcomes within 28 days after COVID-19 infection among participants stratified by age groups (60-79, ≥80 years old).

RESULTS

A dose-response relationship between the number of vaccine doses received and protection against severe or fatal disease was observed. Highest VE (95% CI) against COVID-19 infection was observed in individuals aged ≥80 who received three doses of BNT162b2 [75.5% (73.1-77.7%)] or three doses of CoronaVac [53.9% (51.0-56.5%)] compared to those in the younger age group who received three doses of BNT162b2 [51.1% (49.9-52.4%)] or three doses of CoronaVac [2.0% (-0.1-4.1%)]. VE (95% CI) was higher for other outcomes, reaching 91.9% (89.4-93.8%) and 86.7% (84.3-88.8%) against COVID-19-related hospitalization; 85.8% (61.2-94.8%) and 89.8% (72.4-96.3%) against COVID-19-related severe complications; and 96.4% (92.9-98.2%) and 95.0% (92.1-96.8%) against COVID-19-related mortality after three doses of BNT162b2 and CoronaVac in older vaccine recipients, respectively. A similar dose-response relationship was established in younger vaccine recipients and after stratification by sex and Charlson Comorbidity Index.

CONCLUSION

Both BNT162b2 and CoronaVac vaccination were effective in protecting older adults against COVID-19 infection and COVID-19-related severe outcomes amidst the Omicron BA.2 pandemic, and VE increased further with the third dose.

Ageing workers' mental health during COVID-19: a multilevel observational study on the association with the work environment, perceived workplace safety and individual factors

OBJECTIVES

The stress and anxiety associated with the predisposition of ageing workers to severe COVID-19 illness, once occupationally infected, jeopardise their mental health. This study aimed to investigate the association between individual level, work environment exposure factors and perceived workplace safety with a decline in mental health of ageing workers from different industry sectors.

DESIGN

Observational study, prevalence assessment of survey added to longitudinal cohort data.

SETTING

The Survey of Health, Ageing and Retirement in Europe (SHARE) from 27 countries in Europe and Israel participating in the COVID-19 survey (summer 2020) and having prepandemic waves' SHARE data.

PARTICIPANTS

Workers aged 50-70 (n=6449) who attended their workplaces at least partially after the pandemic broke out.

PRIMARY OUTCOME MEASURE

Perceived decline in mental health compared with preoutbreak status.

RESULTS

Multilevel analyses demonstrated that 24.5% (95% CI 23.5% to 25.5%) of ageing workers in Europe experienced mental health decline associated with national-level self-reported COVID-19 burden. Workplace safety perception was the strongest predictor, as each one-point increase in unsafe perception was associated with 60% of mental health decline (OR=1.6, 95% CI 1.47 to 1.74), explaining 30% of increased reported mental health symptoms of ageing workers. Safety perception mediates the mental health outcomes of the work environment, such as workplace contagion risk and work location. Female gender (OR=1.77, 95% CI 1.55 to 2.02), financial difficulties (OR=1.19, 95% CI 1.1 to 1.28), higher vulnerability index (comorbidities, age >60) (OR=1.11, 95% CI 1.05 to 1.18), pre-existing mental problems (OR=1.78, 95% CI 1.55 to 2.04) and increased national burden of COVID-19 (OR=1.01, 95% CI 1.0 to 1.02) were associated with declines in mental health, whereas exclusively working on-site was protective.

CONCLUSION

Vulnerable subgroups for mental health declines among ageing workers were revealed, which warrant their screening and employers' evaluation of workplace conditions of ageing workers to prevent mental health-related implications. Workplace interventions should aim to reduce work environment influences on infection risk and mental distress.

The role of ECMO in COVID-19 acute respiratory failure: Defining risk factors for mortality

BACKGROUND

Veno-venous extracorporeal membrane oxygenation (VV ECMO) utilization increased substantially during the COVID-19 pandemic, but without patient selection criteria.

METHODS

We conducted a retrospective review of all adult patients with COVID-19-associated ARDS placed on VV ECMO at our institution from April 2020 through June 2022.

RESULTS

162 patients were included (n = 95 Pre-Delta; n = 58 Delta; n = 9 Omicron). The frequency of ECMO duration greater than three weeks was variable by pandemic period (17% pre-Delta, 41% Delta, 22% Omicron, p = 0.003). In-hospital mortality was 60.5%. Age ≥50 years (RR 1.28, 95% CI 1.01, 1.62), ≥7 days of respiratory support (1.39, 95% CI 1.05, 1.83) and pre-cannulation renal failure requiring dialysis (RR 1.42, 95% CI 1.13, 1.78) were associated with mortality.

CONCLUSIONS

In this cohort of VV ECMO patients with COVID-19, older age, a longer duration of pre-ECMO respiratory support, and pre-ECMO renal failure all increased the risk of mortality by approximately 30%.

Coronavirus disease 2019 (COVID-19) excess mortality outcomes associated with pandemic effects study (COPES): A systematic review and meta-analysis

Background and aim

With the Coronavirus Disease 2019 (COVID-19) pandemic continuing to impact healthcare systems around the world, healthcare providers are attempting to balance resources devoted to COVID-19 patients while minimizing excess mortality overall (both COVID-19 and non-COVID-19 patients). To this end, we conducted a systematic review (SR) to describe the effect of the COVID-19 pandemic on all-cause excess mortality (COVID-19 and non-COVID-19) during the pandemic timeframe compared to non-pandemic times.

Methods

We searched EMBASE, Cochrane Database of SRs, MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL) and Cochrane Controlled Trials Register (CENTRAL), from inception (1948) to December 31, 2020. We used a two-stage review process to screen/extract data. We assessed risk of bias using Newcastle-Ottawa Scale (NOS). We used Critical Appraisal and Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology.

Results

Of 11,581 citations, 194 studies met eligibility. Of these studies, 31 had mortality comparisons (n = 433,196,345 participants). Compared to pre-pandemic times, during the COVID-19 pandemic, our meta-analysis demonstrated that COVID-19 mortality had an increased risk difference (RD) of 0.06% (95% CI: 0.06-0.06% p < 0.00001). All-cause mortality also increased [relative risk (RR): 1.53, 95% confidence interval (CI): 1.38-1.70, p < 0.00001] alongside non-COVID-19 mortality (RR: 1.18, 1.07-1.30, p < 0.00001). There was "very low" certainty of evidence through GRADE assessment for all outcomes studied, demonstrating the evidence as uncertain.

Interpretation

The COVID-19 pandemic may have caused significant increases in all-cause excess mortality, greater than those accounted for by increases due to COVID-19 mortality alone, although the evidence is uncertain.

Systematic review registration

[https://www.crd.york.ac.uk/prospero/#recordDetails], identifier [CRD42020201256].

Effect of the COVID-19 pandemic on allogeneic stem cell transplantation in Japan

The coronavirus disease 2019 (COVID-19) pandemic affected healthcare quality and access worldwide and may also have negatively affected the frequency and outcomes of allogeneic hematopoietic stem cell transplantation (HSCT). We evaluated the effect of the pandemic on allogeneic HSCT in Japan. Our subjects were patients who received allogeneic HSCT during January 2018-December 2020 in Japan. We assessed differences in yearly number of allogeneic HSCTs and 1-year outcomes in 2020 versus both 2019 and 2018. The total number of patients who received allogeneic HSCT increased from 3621 patients in 2018 and 3708 patients in 2019 to 3865 patients in 2020. Some following changes in allogeneic HSCT methods were observed: patients were older, fewer patients received bone marrow transplantation, fewer patients received transplants from unrelated donors, fewer patients received transplants from matched donors, more patients received reduced-intensity conditioning, and fewer patients received anti-thymocyte globulin in 2020 compared with previous years. HSCT outcomes were not affected, as 1-year overall survival was not significantly different (65.8% in 2020, vs. 66.5% in 2019 and 66.4% in 2018). Our results suggest that we can maintain transplant care during the pandemic by controlling the spread of COVID-19 and modifying HSCT methods.

Ethics of participation and social inclusion of older persons in research: lessons learned from the COVID-19 pandemic in Singapore

The COVID-19 pandemic brought about safe distancing measures that are unprecedented. This article details the impact of the pandemic across research studies involving older persons in Singapore, and assesses the different strategies used to adapt to their needs in the context of evolving public health measures. The pandemic exposed diverse experiences of vulnerability among older persons, pushing for critical reflections on ethics of participation and social inclusion as the new research normal. We emphasize the importance of practicing flexibility: consideration for differentiated approaches to recruitment and data collection that should be proactively embedded in research designs for older persons during the pandemic and beyond.

Machine learning models to predict the maximum severity of COVID-19 based on initial hospitalization record

Background

As the worldwide spread of coronavirus disease 2019 (COVID-19) continues for a long time, early prediction of the maximum severity is required for effective treatment of each patient.

Objective

This study aimed to develop predictive models for the maximum severity of hospitalized COVID-19 patients using artificial intelligence (AI)/machine learning (ML) algorithms.

Methods

The medical records of 2,263 COVID-19 patients admitted to 10 hospitals in Daegu, Korea, from February 18, 2020, to May 19, 2020, were comprehensively reviewed. The maximum severity during hospitalization was divided into four groups according to the severity level: mild, moderate, severe, and critical. The patient's initial hospitalization records were used as predictors. The total dataset was randomly split into a training set and a testing set in a 2:1 ratio, taking into account the four maximum severity groups. Predictive models were developed using the training set and were evaluated using the testing set. Two approaches were performed: using four groups based on original severity levels groups (i.e., 4-group classification) and using two groups after regrouping the four severity level into two (i.e., binary classification). Three variable selection methods including randomForestSRC were performed. As AI/ML algorithms for 4-group classification, GUIDE and proportional odds model were used. For binary classification, we used five AI/ML algorithms, including deep neural network and GUIDE.

Results

Of the four maximum severity groups, the moderate group had the highest percentage (1,115 patients; 49.5%). As factors contributing to exacerbation of maximum severity, there were 25 statistically significant predictors through simple analysis of linear trends. As a result of model development, the following three models based on binary classification showed high predictive performance: (1) Mild vs. Above Moderate, (2) Below Moderate vs. Above Severe, and (3) Below Severe vs. Critical. The performance of these three binary models was evaluated using AUC values 0.883, 0.879, and, 0.887, respectively. Based on results for each of the three predictive models, we developed web-based nomograms for clinical use (http://statgen.snu.ac.kr/software/nomogramDaeguCovid/).

Conclusions

We successfully developed web-based nomograms predicting the maximum severity. These nomograms are expected to help plan an effective treatment for each patient in the clinical field.

Cytomegalovirus Seropositivity in Older Adults Changes the T Cell Repertoire but Does Not Prevent Antibody or Cellular Responses to SARS-CoV-2 Vaccination

Chronic infection with human CMV may contribute to poor vaccine efficacy in older adults. We assessed the effects of CMV serostatus on Ab quantity and quality, as well as cellular memory recall responses, after two and three SARS-CoV-2 mRNA vaccine doses, in older adults in assisted living facilities. CMV serostatus did not affect anti-Spike and anti-receptor-binding domain IgG Ab levels, nor neutralization capacity against wild-type or β variants of SARS-CoV-2 several months after vaccination. CMV seropositivity altered T cell expression of senescence-associated markers and increased effector memory re-expressing CD45RA T cell numbers, as has been previously reported; however, this did not impact Spike-specific CD4+ T cell memory recall responses. CMV-seropositive individuals did not have a higher incidence of COVID-19, although prior infection influenced humoral immunity. Therefore, CMV seropositivity may alter T cell composition but does not impede the durability of humoral protection or cellular memory responses after SARS-CoV-2 mRNA vaccination in older adults.

Parental health beliefs, intention, and strategies about covid-19 vaccine for their children: A cross-sectional analysis from five Arab countries in the Middle East

BACKGROUND

The issue around vaccination of children has brought divergent opinions among the populations across the globe and among the Arab population. There has been a low response rate to the calls for vaccination of children and this is reflective of the sentiments which parents may have towards their children being vaccinated. This study aims to explore the parents' health beliefs, intentions, and strategies towards the COVID-19 vaccine for their children among Arab population.

METHODS

A cross-sectional study using an online survey from October to December 2021, was carried out in five Arab countries in the Middle East. A reliable health belief model (HBM) including five domains: severity, susceptibility, benefits, barriers and cues to action, was adopted. Chi-square, Mann-Whitney test, and multivariable logistic regression were performed for data analysis.

RESULTS

The survey response rate was 58 % (1154/2000). Only 56 % of Arab parents are intended to vaccinate their children against COVID-19. The mean scores of parental health belief are largely driven by their concern over the vaccine's side effect (p = 0.001) followed by its efficacy, safety (p < 0.001), and scheduling difficulty (p = 0.029). However, strategies that were statistically encouraged parents to vaccinate their children included doctor's recommendation, adequate information being provided, and acceptance of the vaccine by public (p < 0.001). Parents with one child were almost three times most likely to vaccinate their children (OR = 2.660, 95 %CI = 1.572-4.504, p < 0.001). Parents' desire to vaccinate their children is also influenced by other factors such as job loss owing to COVID-19 and the presence of a health worker in the family.

CONCLUSION

Intention of Arab parents to vaccinate their children via COVID-19 vaccine is still limited. Thus, it is essential for health care authorities to avail the information which will debunk the erroneous beliefs which some parents have developed towards the vaccination of children against COVID-19.

Risk of Severe COVID-19 Disease and the Pandemic's Impact on Service Utilization Among a Longitudinal Cohort of Persons with HIV-Washington, DC

People with HIV (PWH) have a high burden of medical comorbidities, potentially putting them at increased risk for severe COVID-19. Additionally, during the COVID-19 pandemic, HIV care delivery has been restructured and the impact on HIV outcomes is unknown. The objectives of this study were first, to examine the risk of severe COVID-19 among PWH, using a definition incorporating clinical risk factors, and second, to examine the pandemic's impact on HIV care. We used data from the DC Cohort, a large cohort of people receiving HIV care in Washington, DC. We found that a high proportion of participants across all age groups qualified as increased (58%) or high risk (34%) for severe COVID-19. Between 2019 and 2020, encounters increased (17.7%, increasing to 23.5% of active DC Cohort participants had an encounter) while laboratory utilization decreased (14.4%, decreasing to 11.4% of active DC Cohort participants had an HIV RNA test performed). Implications of our work include the importance of protecting vulnerable people with HIV from acquiring COVID-19 and potentially manifesting severe complications through strategies including vaccination. Additionally, acknowledging that HIV service delivery will likely be changed long-term by the pandemic, adaptation is required to ensure continued progress towards 90-90-90 goals.