The role of social transfers in mitigating families with children from the economic impact of the COVID‐19 pandemic

In this study, we investigated the household income of families with children. Our specific interest was the earned income losses during the COVID‐19 pandemic, and how social transfers have mitigated those losses. We assessed the monthly income levels by comparing the information on the year prior to pandemic to income levels during COVID‐19 pandemic. We found that the pandemic affected all studied subgroups of families with children, with the most negative economic influence in May 2020. In addition, our results indicate that in Finland the social transfers protected fairly well against the negative economic impacts of the pandemic among families with children, especially among vulnerable families (those with lowest income level prior COVID‐19, with low parental education, single‐parent families and families with non‐Finnish‐born parents). The information gained from this analysis can be useful in economic recovery during and after COVID‐19 pandemic, and when preparing for future challenges. [ FROM AUTHOR] Copyright of International Journal of Social Welfare is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Population-Based Model of the Fraction of Incidental COVID-19 Hospitalizations during the Omicron BA.1 Wave in the United States

1. Background: Some reports have suggested that as many as one-half of all hospital inpatients identified as COVID-19-positive during the Omicron BA.1 variant-driven wave were incidental cases admitted primarily for reasons other than their viral infections. To date, however, there are no prospective longitudinal studies of a representative panel of hospitals based on pre-established criteria for determining whether a patient was, in fact, admitted as a result of the disease. 2. Materials and Methods: To fill this gap, we developed a formula to estimate the fraction of incidental COVID-19 hospitalizations that relies on measurable, population-based parameters. We applied our approach to a longitudinal panel of 164 counties throughout the United States, covering a 4-week interval ending in the first week of January 2022. 3. Results: Within this panel, we estimated that COVID-19 incidence was rising exponentially at a rate of 9.34% per day (95% CI, 8.93–9.87). Assuming that only one-quarter of all Omicron BA.1 infections had been reported by public authorities, we further estimated the aggregate prevalence of active SARS-CoV-2 infection during the first week of January to be 3.45%. During the same week, among 250 high-COVID-volume hospitals within our 164-county panel, an estimated one in four inpatients was COVID-positive. Based upon these estimates, we computed that 10.6% of such COVID-19-positive hospitalized patients were incidental infections. Across individual counties, the median fraction of incidental COVID-19 hospitalizations was 9.5%, with an interquartile range of 6.7 to 12.7%. 4. Conclusion: Incidental COVID-19 infections appear to have been a nontrivial fraction of all COVID-19-positive hospitalized patients during the Omicron BA.1 wave. In the aggregate, however, the burden of patients admitted for complications of their viral infections was far greater. [ FROM AUTHOR] Copyright of COVID is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Association of multiple-sclerosis-related mortality with COVID-19 and other common infections: a multiple causes of death analysis.

BACKGROUND AND PURPOSE: People with multiple sclerosis (MS) suffer from higher infection-related mortality compared to the general population; however, sparse data are available on the increased risk of death associated with coronavirus disease 2019 (COVID-19) and other common types of infections. METHODS: All mortality records and multiple-cause-of-death data in 2010-2021 of residents in the Veneto region (northeastern Italy) were extracted. Mention of specific infections was compared between death certificates reporting MS or not. Odds ratios (OR) with 95% confidence intervals (95% CI) were estimated by conditional logistic regression matching by age, sex and calendar year. The bimonthly averages of MS-related deaths in 2010-2019 were compared with those registered during the pandemic (2020-2021). RESULTS: Of 580,015 deaths through 2010-2021, MS was mentioned in 850 cases (0.15%), 59.3% women. Influenza and pneumonia were reported in 18.4% of MS-related compared to 11.0% non-MS-related deaths (OR 2.72, 95% CI 2.28-3.25). The odds of mention of urinary tract infections was significantly greater in MS-related deaths of men (OR 8.16, 95% CI 5.23-12.7) than women (OR 3.03, 95% CI 1.82-5.02). Aspiration pneumonia, pressure ulcers/skin infections and sepsis were also significantly associated with MS-related deaths. Reporting of COVID-19 as a cause of death did not significantly differ between deaths with and without mention of MS (approximately 11% of both). However, compared to 2010-2019, peaks in MS-related deaths were observed during the pandemic waves. CONCLUSIONS: Infections continue to play a significant role in MS-related deaths, underlying the need to improve prevention and management strategies.

Social deprivation and SARS-CoV-2 testing: a population-based analysis in a highly contrasted southern France region.

Background: Testing was the cornerstone of the COVID-19 epidemic response in most countries until vaccination became available for the general population. Social inequalities generally affect access to healthcare and health behaviors, and COVID-19 was rapidly shown to impact deprived population more drastically. In support of the regional health agency in Provence-Alpes-Côte d'Azur (PACA) in South-Eastern France, we analyzed the relationship between testing rate and socio-demographic characteristics of the population, to identify gaps in testing coverage and improve targeting of response strategies. Methods: We conducted an ecological analysis of SARS-CoV-2/COVID-19 testing rate in the PACA region, based on data aggregated at the finest spatial resolution available in France (IRIS) and by periods defined by public health implemented measures and major epidemiological changes. Using general census data, population density, and specific deprivation indices, we used principal component analysis followed by hierarchical clustering to define profiles describing local socio-demographic characteristics. We analyzed the association between these profiles and testing rates in a generalized additive multilevel model, adjusting for access to healthcare, presence of a retirement home, and the age profile of the population. Results: We identified 6 socio-demographic profiles across the 2,306 analyzed IRIS spatial units: privileged, remote, intermediate, downtown, deprived, and very deprived (ordered by increasing social deprivation index). Profiles also ranged from rural (remote) to high density urban areas (downtown, very deprived). From July 2020 to December 2021, we analyzed SARS-CoV-2/COVID-19 testing rate over 10 periods. Testing rates fluctuated strongly but were highest in privileged and downtown areas, and lowest in very deprived ones. The lowest adjusted testing rate ratios (aTRR) between privileged (reference) and other profiles occurred after implementation of a mandatory healthpass for many leisure activities in July 2021. Periods of contextual testing near Christmas displayed the largest aTRR, especially during the last periods of 2021 after the end of free convenience testing for unvaccinated individuals. Conclusion: We characterized in-depth local heterogeneity and temporal trends in testing rates and identified areas and circumstances associated with low testing rates, which the regional health agency targeted specifically for the deployment of health mediation activities.

Estonian National Mental Health Study: Design and methods for a registry-linked longitudinal survey.

OBJECTIVES: The Estonian National Mental Health Study (EMHS) was conducted in 2021-2022 to provide population-wide data on mental health in the context of COVID-19 pandemic. The main objective of this paper is to describe the rationale, design, and methods of the EMHS and to evaluate the survey response. METHODS: Regionally representative stratified random sample of 20,000 persons aged 15 years and older was drawn from the Estonian Population Register for the study. Persons aged 18 years and older at the time of the sampling were enrolled into three survey waves where they were invited to complete an online or postal questionnaire about mental well-being and disorders, and behavioral, cognitive, and other risk factors. Persons younger than 18 years of age were invited to fill an anonymous online questionnaire starting from wave 2. To complement and validate survey data, data on socio-demographic, health-related, and environmental variables were collected from six national administrative databases and registries. Additionally, a subsample was enrolled into a validation study using ecological momentary assessment. RESULTS: In total, 5636 adults participated in the survey wave 1, 3751 in wave 2, and 4744 in wave 3. Adjusted response rates were 30.6%, 21.1%, and 27.6%, respectively. Women and older age groups were more likely to respond. Throughout the three survey waves, a considerable share of adult respondents screened positive for depression (27.6%, 25.1%, and 25.6% in waves 1, 2, and 3, respectively). Women and young adults aged 18 to 29 years had the highest prevalence of depression symptoms. CONCLUSIONS: The registry-linked longitudinal EMHS dataset comprises a rich and trustworthy data source to allow in-depth analysis of mental health outcomes and their correlates among the Estonian population. The study serves as an evidence base for planning mental health policies and prevention measures for possible future crises.

Epidemiological characteristics of the three waves of COVID-19 epidemic in Taiwan during April 2022 to March 2023.

BACKGROUND: Taiwan experienced a relatively low incidence of COVID-19 before 2022. However, from April 2022 to March 2023, the country was struck by a nationwide outbreak that occurred in three waves. Despite the considerable magnitude of the epidemic, the epidemiological characteristics of this outbreak have yet to be clearly understood. METHODS: This was a nationwide, population-based, retrospective cohort study. We recruited patients who had been confirmed as domestically-acquired COVID-19 patients from April 17, 2022, to March 19, 2023. The three epidemic waves were analyzed in terms of numbers of cases, cumulative incidence, numbers of COVID-19-related deaths, mortality, gender, age, residence, SARS-CoV-2 variant sub-lineages, and reinfection status. RESULTS: The numbers of COVID-19 patients (cumulative incidence per million population) were 4,819,625 (207,165.3) in the first wave, 3,587,558 (154,206.5) in the second wave, and 1,746,698 (75,079.5) in the third wave, showing a progressive decline. The numbers of COVID-19-related deaths and mortalities also decreased throughout the three waves. The coverage of vaccination was observed to increase over time. CONCLUSION: During the three waves of COVID-19 epidemic, the numbers of cases and deaths gradually declined, while the vaccine coverage increased. It may be appropriate to consider easing restrictions and returning to normality. However, continued monitoring of the epidemiological situation and tracking the emergence of new variants are crucial to prevent the possibility of another epidemic.

Healthcare utilization and adverse outcomes stratified by sex, age and long-term care residency using the Alberta COVID-19 Analytics and Research Database (ACARD): a population-based descriptive study.

BACKGROUND: Understanding the epidemiology of Coronavirus Disease of 2019 (COVID-19) in a local context is valuable for both future pandemic preparedness and potential increases in COVID-19 case volume, particularly due to variant strains. METHODS: Our work allowed us to complete a population-based study on patients who tested positive for COVID-19 in Alberta from March 1, 2020 to December 15, 2021. We completed a multi-centre, retrospective population-based descriptive study using secondary data sources in Alberta, Canada. We identified all adult patients (≥ 18 years of age) tested and subsequently positive for COVID-19 (including only the first incident case of COVID-19) on a laboratory test. We determined positive COVID-19 tests, gender, age, comorbidities, residency in a long-term care (LTC) facility, time to hospitalization, length of stay (LOS) in hospital, and mortality. Patients were followed for 60 days from a COVID-19 positive test. RESULTS: Between March 1, 2020 and December 15, 2021, 255,037 adults were identified with COVID-19 in Alberta. Most confirmed cases occurred among those less than 60 years of age (84.3%); however, most deaths (89.3%) occurred among those older than 60 years. Overall hospitalization rate among those who tested positive was 5.9%. Being a resident of LTC was associated with substantial mortality of 24.6% within 60 days of a positive COVID-19 test. The most common comorbidity among those with COVID-19 was depression. Across all patients 17.3% of males and 18.6% of females had an unplanned ambulatory visit subsequent to their positive COVID-19 test. CONCLUSIONS: COVID-19 is associated with extensive healthcare utilization. Residents of LTC were substantially impacted during the COVID-19 pandemic with high associated mortality. Further work should be done to better understand the economic burden associated with related healthcare utilization following a COVID-19 infection to inform healthcare system resource allocation, planning, and forecasting.

Association between Covid-19 vaccination and incidence of type 1 diabetes in China: Evidence from 14.14 million registered residents between 2007 and 2021.

AIMS: Reports have suggested that COVID-19 vaccination may cause Type 1 diabetes (T1D), particularly fulminant T1D (FT1D). This study aimed to investigate the incidence of T1D in a general population of China, where>90% of the people have received three injections of inactivated SARS-Cov-2 vaccines in 2021. METHODS: A population-based registry of T1D was performed using data from the Beijing Municipal Health Commission Information Center. Annual incidence rates were calculated by age group and gender, and annual percentage changes were assessed using Joinpoint regression. RESULTS: The study included 14.14 million registered residents, and 7,697 people with newly diagnosed T1D were identified from 2007 to 2021. T1D incidence increased from 2.77 in 2007 to 3.84 per 100,000 persons in 2021. However, T1D incidence was stable from 2019 to 2021, and the incidence rate did not increase when people were vaccinated in January-December 2021. The incidence of FT1D did not increase from 2015 to 2021. CONCLUSIONS: The findings suggest that COVID-19 vaccination did not increase the onset of T1D or have a significant impact on T1D pathogenesis, at least not on a large scale.

A longitudinal study of mental health in at-risk adolescents before and during the COVID-19 pandemic.

Although cross-sectional studies have shown that the COVID-19 pandemic has negatively affected the mental health of adolescents, the effect of the pandemic on adolescents with pre-pandemic symptoms is unclear. We, therefore, tested the hypothesis that adolescents had increased emotional and behavioral problems during the lockdowns imposed during the pandemic.This study included three measurements in a prospective cohort of 1022 adolescents who were oversampled based on their high risk of developing psychopathology. Before the pandemic, we assessed depressive, anxiety, stress, oppositional defiant problems, psychotic experiences and suicidality, using the Youth Self-Report; 445 and 333 of these 1,022 adolescents subsequently completed the online questionnaire in the first lockdown (in April 2020) and in the second lockdown (in January 2021), respectively. Multilevel random intercept regression models were used to determine the change in psychiatric symptoms, including an interaction term to assess whether these changes differed based on the severity of symptoms prior to the pandemic. Throughout the pandemic, the majority of the participating adolescents reported having emotional and behavioral symptoms that were within the normal range. Moreover, the mean symptom scores for all six outcomes decreased significantly among adolescents with high clinical severity prior to the pandemic.In contrast to our original hypothesis, the effects of the COVID-19 pandemic may not necessarily be detrimental, at least among a specific subgroup of adolescents with pre-existing mental health problems. Moreover, our finding that most adolescents in this at-risk sample did not report experiencing clinically relevant symptoms during the pandemic reflects their resilience during the pandemic.

Large Diffusion of Severe Acute Respiratory Syndrome Coronavirus 2 After the Successive Epidemiological Waves, Including Omicron, in Guinea and Cameroon: Implications for Vaccine Strategies.

Background: We aimed to estimate the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence among the general population in Conakry, Guinea and Yaounde, Cameroon after the coronavirus disease 2019 Omicron wave. Methods: We conducted population-based, age-stratified seroprevalence surveys in Conakry and Yaounde (May and June 2022). We collected demographic and epidemiologic information and dried blood spot samples that were tested for SARS-CoV-2 immunoglobulin G (IgG) antibodies using recombinant nucleocapsid and spike proteins with Luminex technology. Results: Samples were obtained from 1386 and 1425 participants in Guinea and Cameroon, respectively. The overall age-standardized SARS-CoV-2 IgG seroprevalence against spike and nucleocapsid proteins was 71.57% (95% confidence interval [CI], 67.48%-75.33%) in Guinea and 74.71% (95% CI, 71.99%-77.25%) in Cameroon. Seroprevalence increased significantly with age categories. Female participants were more likely than male participants to be seropositive. The seroprevalence in unvaccinated participants was 69.6% (95% CI, 65.5%-73.41%) in Guinea and 74.8% (95% CI, 72.04%-77.38%) in Cameroon. In multivariate analysis, only age, sex, and education were independently associated with seropositivity. Conclusions: These findings show a high community transmission after the different epidemiological waves including Omicron, especially among people aged >40 years. In addition, our results suggest that the spread of SARS-CoV-2 has been underestimated as a significant proportion of the population has already contracted the virus and that vaccine strategies should focus on vulnerable populations.

Sex-Based Differences in Severe Outcomes, Including Cardiovascular Hospitalization, in Adults With COVID-19 in Ontario, Canada.

Background: While men have experienced higher risks of SARS-CoV-2 infection compared to women, an analysis of sex differences by age in severe outcomes during the acute phase of infection is lacking. Objectives: The purpose of this study was to assess heterogeneity in severe outcome risks by age and sex by conducting a retrospective cohort study of community-dwelling adults in Ontario who tested positive for SARS-CoV-2 infection during the first 3 waves. Methods: Adjusted odds ratios were estimated using multilevel multivariable logistic regression models including an interaction term for age and sex. The primary outcome was a composite of severe outcomes (hospitalization for a cardiovascular (CV) event, intensive care unit admission, mechanical ventilation, or death) within 30 days. Results: Among 30,736, 199,132, and 186,131 adults who tested positive during the first 3 waves, 1,908 (6.2%), 5,437 (2.7%), and 5,653 (3.0%) experienced a severe outcome within 30 days. For all outcomes, the sex-specific risk depended on age (all P for interaction <0.05). Men with SARS-CoV-2 infection experienced a higher risk of outcomes than infected women of the same age, except for the risk of all-cause hospitalization being higher for young women than men (ages 18-45 years) during waves 2 and 3. The sex disparity in CV hospitalization across all ages either persisted or increased with each subsequent wave. Conclusions: To mitigate risks in subsequent waves, it is helpful to further understand the factors that contribute to the generally higher risks faced by men across all ages, and the persistent or increasing sex disparity in the risk of CV hospitalization.

Does misclassification of former tobacco smokers explain the 'smoker's paradox' in the risk of COVID-19? Insights from the Stockholm Public Health Cohort.

BACKGROUND: The association between tobacco smoking and the risk of COVID-19 and its adverse outcomes is controversial, as studies reported contrasting findings. Bias due to misclassification of the exposure in the analyses of current versus non-current smoking could be a possible explanation because former smokers may have higher background risks of the disease due to co-morbidity. The aim of the study was to investigate the extent of this potential bias by separating non-, former, and current smokers when assessing the risk or prognosis of diseases. METHODS: We analysed data from 43,400 participants in the Stockholm Public Health Cohort, Sweden, with information on smoking obtained prior to the pandemic. We estimated the risk of COVID-19, hospital admissions and death for (a) former and current smokers relative to non-smokers, (b) current smokers relative to non-current smokers, that is, including former smokers; adjusting for potential confounders (aRR). RESULTS: The aRR of a COVID-19 diagnosis was elevated for former smokers compared with non-smokers (1.07; 95% confidence interval (CI) =1.00-1.15); including hospital admission with any COVID-19 diagnosis (aRR= 1.23; 95% CI = 1.03-1.48); or with COVID-19 as the main diagnosis (aRR=1.23, 95% CI= 1.01-1.49); and death within 30 days with COVID-19 as the main or a contributory cause (aRR=1.40; 95% CI=1.00-1.95). Current smoking was negatively associated with risk of COVID-19 (aRR=0.79; 95% CI=0.68-0.91). CONCLUSIONS: Separating non-smokers from former smokers when assessing the disease risk or prognosis is essential to avoid bias. However, the negative association between current smoking and the risk of COVID-19 could not be entirely explained by misclassification.

Developing a comorbidity score in cancer patients using healthcare utilization databases during the COVID-19 pandemic: An experience from Italy.

BACKGROUND: A strong relationship has been observed between comorbidities and the risk of severe/fatal COVID-19 manifestations, but no score is available to evaluate their association in cancer patients. To make up for this lacuna, we aimed to develop a comorbidity score for cancer patients, based on the Lombardy Region healthcare databases. METHODS: We used hospital discharge records to identify patients with a new diagnosis of solid cancer between February and December 2019; 61 comorbidities were retrieved within 2 years before cancer diagnosis. This cohort was split into training and validation sets. In the training set, we used a LASSO-logistic model to identify comorbidities associated with the risk of developing a severe/fatal form of COVID-19 during the first pandemic wave (March-May 2020). We used a logistic model to estimate comorbidity score weights and then we divided the score into five classes (<=-1, 0, 1, 2-4, >=5). In the validation set, we assessed score performance by areas under the receiver operating characteristic curve (AUC) and calibration plots. We repeated the process on second pandemic wave (October-December 2020) data. RESULTS: We identified 55,425 patients with an incident solid cancer. We selected 21 comorbidities as independent predictors. The first four score classes showed similar probability of experiencing the outcome (0.2% to 0.5%), while the last showed a probability equal to 5.8%. The score performed well in both the first and second pandemic waves: AUC 0.85 and 0.82, respectively. Our results were robust for major cancer sites too (i.e., colorectal, lung, female breast, and prostate). CONCLUSIONS: We developed a high performance comorbidity score for cancer patients and COVID-19. Being based on administrative databases, this score will be useful for adjusting for comorbidity confounding in epidemiological studies on COVID-19 and cancer impact.

Disparities in COVID-19 Hospitalization at the Intersection of Race and Ethnicity and Income.

BACKGROUND: Existing studies have elucidated racial and ethnic disparities in COVID-19 hospitalizations, but few have examined disparities at the intersection of race and ethnicity and income. METHODS: We used a population-based probability survey of non-institutionalized adults in Michigan with a polymerase chain reaction-positive SARS-CoV-2 test before November 16, 2020. We categorized respondents by race and ethnicity and annual household income: low-income (< $50,000) Non-Hispanic (NH) Black, high-income (≥ $50,000) NH Black, low-income Hispanic, high-income Hispanic, low-income NH White, and high-income NH White. We used modified Poisson regression models, adjusting for sex, age group, survey mode, and sample wave, to estimate COVID-19 hospitalization prevalence ratios by race and ethnicity and income. RESULTS: Over half of the analytic sample (n = 1593) was female (54.9%) and age 45 or older (52.5%), with 14.5% hospitalized for COVID-19. Hospitalization was most prevalent among low-income (32.9%) and high-income (31.2%) Non-Hispanic (NH) Black adults, followed by low-income NH White (15.3%), low-income Hispanic (12.9%), high-income NH White (9.6%), and high-income Hispanic adults (8.8%). In adjusted models, NH Black adults, regardless of income (low-income prevalence ratio [PR]: 1.86, 95% CI: 1.36-2.54; high-income PR: 1.57, 95% CI: 1.07-2.31), and low-income NH White adults (PR: 1.52, 95% CI: 1.12-2.07), had higher prevalence of hospitalization compared to high-income NH White adults. We observed no significant difference in the prevalence of hospitalization among Hispanic adults relative to high-income NH White adults. CONCLUSIONS: We observed disparities in COVID-19 hospitalization at the intersection of race and ethnicity and income for NH Black adults and low-income NH White adults relative to high-income NH White adults, but not for Hispanic adults.

Whole-population trends in pathology-confirmed cancer incidence in Northern Ireland, Scotland and Wales during the SARS-CoV-2 pandemic: A retrospective observational study.

INTRODUCTION: The COVID-19 epidemic interrupted normal cancer diagnosis procedures. Population-based cancer registries report incidence at least 18 months after it happens. Our goal was to make more timely estimates by using pathologically confirmed cancers (PDC) as a proxy for incidence. We compared the 2020 and 2021 PDC with the 2019 pre-pandemic baseline in Scotland, Wales, and Northern Ireland (NI). METHODS: Numbers of female breast (ICD-10 C50), lung (C33-34), colorectal (C18-20), gynaecological (C51-58), prostate (C61), head and neck (C00-C14, C30-32), upper gastro-intestinal (C15-16), urological (C64-68), malignant melanoma (C43), and non-melanoma skin (NMSC) (C44) cancers were counted. Multiple pairwise comparisons generated incidence rate ratios (IRR). RESULTS: Data were accessible within 5 months of the pathological diagnosis date. Between 2019 and 2020, the number of pathologically confirmed malignancies (excluding NMSC) decreased by 7315 (14.1 %). Scotland experienced early monthly declines of up to 64 % (colorectal cancers, April 2020 versus April 2019). Wales experienced the greatest overall change in 2020, but Northern Ireland experienced the quickest recovery. The pandemic's effects varied by cancer type, with no significant change in lung cancer diagnoses in Wales in 2020 (IRR 0.97 (95 % CI 0.90-1.05)), followed by an increase in 2021 (IRR 1.11 (1.03-1.20). CONCLUSION: PDC are useful in reporting cancer incidence quicker than cancer registrations. Temporal and geographical differences between participating countries mirrored differences in responses to the COVID-19 pandemic, indicating face validity and the potential for quick cancer diagnosis assessment. To verify their sensitivity and specificity against the gold standard of cancer registrations, however, additional research is required.

Poor health status before the COVID-19 pandemic is associated with unfavourable changes in health-related lifestyle.

AIMS: The effects of COVID-19 containment measures on health-related lifestyle have been both favourable and unfavourable for health. Factors predisposing to unfavourable changes are still poorly known. In this short communication, we aimed to examine which socioeconomic and health-related factors predicted unfavourable lifestyle changes based on data from the same individuals before (2017) the pandemic and during the second wave (2020) of the pandemic in Finland. METHODS: This individual-level follow-up study was based on a nationally representative, two-stage stratified cluster sample of Finnish adults from the FinHealth 2017 Study, conducted in Spring 2017, and its follow-up survey, conducted in Autumn 2020. A total of 3834 men and women aged 25-69 years at baseline had information of selected lifestyle factors (vegetable consumption, leisure-time physical activity, sleeping problems and nightmares) available at both time points. Odds ratios and 95% confidence intervals for unfavourable lifestyle changes (yes/no) according to socioeconomic and health-related factors were calculated using logistic regression models taking into account the sampling design and non-response. RESULTS: We found that those having poor health (i.e. psychological distress, poor self-rated health or chronic diseases) or disadvantaged socioeconomic background before the pandemic were prone to unfavourable lifestyle changes during the follow-up. CONCLUSIONS: Observed unfavourable lifestyle changes in vulnerable population groups may accelerate health inequalities. Targeted health promotion actions are needed to prevent this unfavourable development.

COVID-19 Morbidity Among Individuals with Autistic Spectrum Disorder: A Matched Controlled Population-Based Study.

In this study we aimed to assess whether individuals with ASD are prone to higher infection rates, or to severe COVID-19 illness. Individuals with ASD and age- and gender-matched controlled counterparts (total n = 32,812) were assessed for COVID-19 infection rates and hospitalizations. Results indicated higher infection rates among individuals with ASD, with the largest effect among individuals aged 40-60 (OR = 2.05, 95%CI 1.33-3.15, p < .001), as well as higher odds for hospitalizations, evident primarily in men (OR = 2.40, 95%CI 1.14-5.02, p = 0.02) but not women. Medical and environmental risk factors may associate ASD with higher infection and morbidity rates. Healthcare policy providers should consider proactive steps to protect this population from the associated risks.

Factors Impacting Readiness to Perform Secondary Population-Based Triage During the Second Wave of COVID-19 in Victoria, Australia: Pilot Study.

OBJECTIVE: Pandemics generate such a significant demand for care that traditional triage methods can become saturated. Secondary population-based triage (S-PBT) overcomes this limitation. Although the coronavirus disease (COVID-19) pandemic forced S-PBT into operation internationally during the first year of the pandemic, Australian doctors were spared this responsibility. However, the second wave of COVID-19 provides an opportunity to explore the lived experience of preparing for S-PBT within the Australian context.The aim of this study is to explore the lived experience of preparing to operationalize S-PBT to allocate critical care resources during Australia's second wave of COVID-19 in 2020. METHODS: Intensivists and emergency physicians working during the second Victorian COVID-19 surge were recruited by purposive non-random sampling. Semi-structured interviews were hosted remotely, recorded, transcribed, and coded to facilitate a qualitative phenomenological analysis. RESULTS: Six interviews were conducted with an equal mix of intensivists and emergency doctors. Preliminary findings from a thematic analysis revealed 4 themes: (1) threat of resources running; (2) informed decision requiring information; (3) making decisions as we always do; and (4) a great burden to carry. CONCLUSION: This is the first description of this novel phenomenon within Australia and, in doing so, it identified a lack of preparedness to operationalize S-PBT during the second wave of COVID-19 in Australia.

The prevalence of SARS-CoV-2 infection and long COVID in U.S. adults during the BA.4/BA.5 surge, June-July 2022.

Due to changes in SARS-CoV-2 testing practices, passive case-based surveillance may be an increasingly unreliable indicator for monitoring the burden of SARS-CoV-2, especially during surges. We conducted a cross-sectional survey of a population-representative sample of 3042 U.S. adults between June 30 and July 2, 2022, during the Omicron BA.4/BA.5 surge. Respondents were asked about SARS-CoV-2 testing and outcomes, COVID-like symptoms, contact with cases, and experience with prolonged COVID-19 symptoms following prior infection. We estimated the weighted age and sex-standardized SARS-CoV-2 prevalence, during the 14-day period preceding the interview. We estimated age and gender adjusted prevalence ratios (aPR) for current SARS-CoV-2 infection using a log-binomial regression model. An estimated 17.3% (95% CI 14.9, 19.8) of respondents had SARS-CoV-2 infection during the two-week study period-equating to 44 million cases as compared to 1.8 million per the CDC during the same time period. SARS-CoV-2 prevalence was higher among those 18-24 years old (aPR 2.2, 95% CI 1.8, 2.7) and among non-Hispanic Black (aPR 1.7, 95% CI 1.4,2.2) and Hispanic adults (aPR 2.4, 95% CI 2.0, 2.9). SARS-CoV-2 prevalence was also higher among those with lower income (aPR 1.9, 95% CI 1.5, 2.3), lower education (aPR 3.7 95% CI 3.0,4.7), and those with comorbidities (aPR 1.6, 95% CI 1.4, 2.0). An estimated 21.5% (95% CI 18.2, 24.7) of respondents with a SARS-CoV-2 infection >4 weeks prior reported long COVID symptoms. The inequitable distribution of SARS-CoV-2 prevalence during the BA.4/BA.5 surge will likely drive inequities in the future burden of long COVID.

Risk of Herpes Zoster in Patients with Pulmonary Tuberculosis-A Population-Based Cohort Study.

BACKGROUND: Pulmonary tuberculosis (TB), a global health problem, is typically caused by the bacterium Mycobacterium tuberculosis. Herpes zoster (HZ) is caused by the reactivation of the varicella-zoster virus (VZV). The reactivation of VZV can be caused by stress. We investigated whether pulmonary TB increases the risk of HZ development. METHODS: This study used data that sampled a population of 2 million people in 2000 from the National Health Insurance Research Database. This cohort study observed Taiwanese patients aged 20-100 years with pulmonary TB from 2000 to 2017 (tracked to 2018). Pulmonary TB was defined as having two or more outpatient diagnoses or at least one admission record. To address potential bias caused by confounding factors, the control cohort and pulmonary TB cohort were matched 1:1 by age, gender, index year, and comorbidities. Patients with HZ before the index date were excluded. RESULTS: A total of 30,805 patients were in the pulmonary TB and control cohorts. The incidence rate of HZ in pulmonary TB and control cohorts were 12.00 and 9.66 per 1000 person-years, respectively. The risk of HZ in the pulmonary TB cohort (adjusted hazard ratios = 1.23; 95% confidence interval = 1.16-1.30) was significantly higher than that of in control cohort. Among patients without comorbidities, the patients with TB were 1.28-fold more likely to have HZ than those without TB. CONCLUSION: Patients with TB should be well treated to avoid the potential risk of HZ occurrence. Although we identified the association between pulmonary TB and HZ, further studies are needed to confirm the result.