Assessing the age specificity of infection fatality rates for COVID-19: systematic review, meta-analysis, and public policy implications

Age-related peculiarities of antibody-mediated humoral immune response following SARS-CoV-2 infection

Thousands of articles were published about the COVID-19 disease and hundreds about the immune response. But still little is known about the features of SARS-CoV-2-specific immunity in elderly. The aim of current research was to evaluate the age-related peculiarities of antibody mediated humoral immune response following SARS-CoV-2 infection. Our study presents an intriguing divergence from the classical concept of immunosenescence, where aging has been assumed to cause poor antibody responses, reduced or inefficient vaccination, and overall blunted immune responses in elderly people. Our findings were opposite to some of these expectations; participants aged over 60 expressed elevated titers of anti-SARS-CoV-2 antibodies in comparison to younger adults. Analyzing the data of relative neutralization and avidity of anti-SARS-Cov-2 (S) antibodies we propose that although older adults produce a higher quantity of antibodies, their functional efficiency appears relatively reduced exhibiting lower neutralizing capacity and binding strength per antibody compared to younger adults. We can assume that the immune system of the elderly may require a higher level of antibody production to obtain a comparable level of protection. Our findings highlight the intricate nature of immune responses in convalescent older adults. This has particular relevance to understanding immunity and vaccine responses in different age groups.

Pandemic prevention competencies of long-term care institution workers: A retrospective national survey in Taiwan

BACKGROUND

Long-term care institutions are especially vulnerable in pandemics. Despite Taiwan's proximity to COVID-19's epicenter, the country demonstrated effective pandemic management.

PURPOSE

This study assessed pandemic prevention competencies of Taiwan's long-term care workers, identifying key influencing factors.

METHODS

A cross-sectional survey was conducted, with assessments on competencies via the Emerging Infectious Disease Prevention Competencies Scale.

DISCUSSION

A total of 433 valid responses were obtained. Competencies were rated strong (mean 65.2/81), with predictors including sense of purpose, perceived supervisor support, alignment with institutional culture, job satisfaction, and regular pandemic prevention drills. Findings underscore the role of a supportive environment in fostering pandemic competencies and highlight the importance of strengthening problem-solving capacities to enhance preparedness.

CONCLUSION

Investing in workforce preparedness, leadership engagement, and institutional culture-building is essential for strengthening long-term care resilience to future pandemics worldwide.

The association between healthy walking and COVID-19 symptom severity: A cross-sectional study on the first peak following China's prevention policy change

BACKGROUND

Healthy walking is a moderate aerobic exercise with a step frequency of more than 100 steps per minute. This study aims to assess the impact of Healthy Walking, a novel form of physical activity, on the severity and course of COVID-19 among patients aged from 18 to 65 years old.

METHODS

This cross-sectional study included 1,128 adult participants who completed the questionnaire after recovering from the first wave of COVID-19 infections following China`s modification of its prevention policy. The survey questions included their health status when suffering from COVID-19, basic sociodemographic data, and medical history concerning chronic conditions and lifestyle. A multiple logistic regression model and linear regression model were used to evaluate the dependent variable that reflects the severity of COVID-19 infection.

RESULTS

Among the 1,128 adult participants, the mean age was 39.93 ± 10.18 (IQR: 31.75-48), and 407 (36.08%) were male. Participants who walked up to 300 min per week had a negative association with COVID-19 (OR: 0.562, 95% CI: 0.41-0.863). Receiving three vaccine doses was negatively associated with severe COVID-19 (OR: 0.289, 95% CI:0.092-0.742) compared with receiving only one dose. Females (OR: 1.935, 95% CI:1.475-2.540) had a positive association with severe COVID-19, also a high incidence of co-habitatants was also positively associated (OR: 2.741, 95% CI:1.284-5.881) In the linear model assessing risk factor affecting the course of COVID-19, habitual Healthy Walking ([Formula: see text] =-0.433, [Formula: see text]=0.004) was linked to a reduced disease duration after adjusting all significant risk factors.

CONCLUSIONS

Regular Healthy Walking may help alleviate symptoms and speed up recovery. Therefore, incorporating walking into other physical exercise may reduce COVID-19 symptom severity and speed up COVID-19 recovery.

Paradoxical increase in global COVID-19 deaths with vaccination coverage: World Health Organization estimates (2020-2023)

BackgroundMany reports on the impact of vaccination on COVID-19 pandemic deaths were projections undertaken as the global emergency was unfolding. An increasing number of independent investigators have drawn attention to the subjective nature and inherent biases in mathematical models used for such forecasts that could undermine their accuracy when excess mortality was the metric of choice.ObjectiveCOVID-19 deaths were compared between the pre-vaccines and vaccination eras to observe how vaccination impacted COVID-19 death trajectory worldwide during the pandemic emergency.MethodsCOVID-19 cases, deaths and vaccination rates in World Health Organization (WHO) database till 07 June 2023, Case fatality rate per 1000 for the pre-vaccines period (CFR1), and that over vaccination era (CFR2) were compared for all WHO regions, while tests of correlation between the percentage change in COVID-19 deaths and variables of interest were examined.ResultsCOVID-19 deaths increased with vaccination coverage ranging from 43.3% (Africa) to 1275.0% (Western Pacific). The Western Pacific (1.5%) and Africa (3.8%) regions contributed least to the global cumulative COVID-19 deaths pre-vaccines, while the Americas (49.9%) and Europe (27.6%) had the highest counts. The Americas (39.8%) and Europe (34.1%) accounted for >70% of global COVID-19 deaths despite high vaccination, and the percentage increase in COVID-19 mortality and the percentage of person's ≥65 years were significantly correlated (0.48) in Africa.ConclusionCOVID-19 mortality increased in the vaccination era, especially in regions with higher vaccination coverage.

SARS-CoV-2 dynamics in New York City during March 2020-August 2023

BACKGROUND

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been widespread since 2020 and will likely continue to cause substantial recurring epidemics. However, understanding the underlying infection burden and dynamics, particularly since late 2021 when the Omicron variant emerged, is challenging. Here, we leverage extensive surveillance data available in New York City (NYC) and a comprehensive model-inference system to reconstruct SARS-CoV-2 dynamics therein through August 2023.

METHODS

We fit a metapopulation network SEIRSV (Susceptible-Exposed-Infectious-(re)Susceptible-Vaccination) model to age- and neighborhood-specific data of COVID-19 cases, emergency department visits, and deaths in NYC from the pandemic onset in March 2020 to August 2023. We further validate the model-inference estimates using independent SARS-CoV-2 wastewater viral load data.

RESULTS

The validated model-inference estimates indicate a very high infection burden-the number of infections (i.e., including undetected asymptomatic/mild infections) totaled twice the population size ( > 5 times documented case count) during the first 3.5 years. Estimated virus transmissibility increased around 3-fold, whereas estimated infection-fatality risk (IFR) decreased by >10-fold during this period. The detailed estimates also reveal highly complex variant dynamics and immune landscape, and higher infection risk during winter in NYC over the study period.

CONCLUSIONS

This study provides highly detailed epidemiological estimates and identifies key transmission dynamics and drivers of SARS-CoV-2 during its first 3.5 years of circulation in a large urban center (i.e., NYC). These transmission dynamics and drivers may be relevant to other populations and inform future planning to help mitigate the public health burden of SARS-CoV-2.

Autoantibodies neutralizing type I interferons remain a significant risk factor for critical COVID-19 pneumonia in vaccinated patients

BACKGROUND

Neutralizing autoantibodies against type I interferons were strongly linked to severe COVID-19 in unvaccinated patients; however, this has yet to be evaluated in vaccinated individuals.

OBJECTIVE

To analyze how these autoantibodies influences disease variability in vaccine breakthrough COVID-19 pneumonia patients.

METHODS

Clinical and laboratory data; autoantibodies blocking interferon-α2 and -ω; and humoral response to SARS-CoV-2 vaccine were collected from all vaccinated COVID-19 pneumonia patients admitted from April 2021 to December 2022 at Bellvitge University Hospital, Spain.

RESULTS

458 patients developed COVID-19 pneumonia despite an appropriate antibody response to SARS-CoV-2 vaccination. Autoantibodies neutralizing interferons were significantly more prevalent in patients with critical pneumonia compared to those with milder forms (8.8 % vs. 3.6 %; p = 0.037). Having these autoantibodies was an independent predictor for critical COVID-19 pneumonia (OR 2.88 [95 %CI 1.18-6.98]).

CONCLUSION

Vaccination considerably reduces the severity of COVID-19; however, patients with type I interferon autoantibodies remain at increased risk of severe disease.

[Vaccination and cardiovascular diseases]

Respiratory tract infections with influenza, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and respiratory syncytial (RS) viruses and pneumococci as well as endogenous reactivation of varicella zoster viruses presenting as herpes zoster, are associated with adverse cardiovascular outcomes, such as myocardial infarction or hospitalization for heart failure. Effective prevention of these events, particularly through influenza and pneumococcal vaccination, is well established and cost-effective. Despite guideline recommendations to vaccinate older patients and people at risk, vaccination rates in these population groups remain suboptimal and below average in international comparison. This article sheds light on the association of vaccine preventable diseases with cardiovascular complications and demonstrates the protective effect of the respective vaccinations. Additionally, recommendations on the practical approach to vaccinating high-risk patients are given.

Predicting coronavirus disease 2019 severity using explainable artificial intelligence techniques

Predictive models for determining coronavirus disease 2019 (COVID-19) severity have been established; however, the complexity of the interactions among factors limits the use of conventional statistical methods. This study aimed to establish a simple and accurate predictive model for COVID-19 severity using an explainable machine learning approach. A total of 3,301 patients ≥ 18 years diagnosed with COVID-19 between February 2020 and October 2022 were included. The discovery cohort comprised patients whose disease onset fell before October 1, 2020 (N = 1,023), and the validation cohort comprised the remaining patients (N = 2,278). Pointwise linear and logistic regression models were used to extract 41 features. Reinforcement learning was used to generate a simple model with high predictive accuracy. The primary evaluation was the area under the receiver operating characteristic curve (AUC). The predictive model achieved an AUC of ≥ 0.905 using four features: serum albumin levels, lactate dehydrogenase levels, age, and neutrophil count. The highest AUC value was 0.906 (sensitivity, 0.842; specificity, 0.811) in the discovery cohort and 0.861 (sensitivity, 0.804; specificity, 0.675) in the validation cohort. Simple and well-structured predictive models were established, which may aid in patient management and the selection of therapeutic interventions.

Vaccination strategies for different contact patterns: weighing epidemiological against economic outcomes

The aim of this paper is to shed light on the economic and epidemiological trade-offs that emerge when choosing between different vaccination strategies. For that purpose we employ a setting with three age groups that differ with respect to their fatality rates. The model also accounts for heterogeneity in the transmission rates between and within these age groups. We compare the results for two different contact patterns, in terms of the total number of deceased, the total number of infected, the peak infection rate and the economic gains from different vaccination strategies. We find that fatalities are minimized by first vaccinating the elderly, except when vaccination is slow and the general transmission rate is relatively low. In this case deaths are minimized by first vaccinating the group that is mainly responsible for spreading of the virus. With regard to the other outcome variables it is best to vaccinate the group that drives the pandemic first. A trade-off may therefore emerge between reducing fatalities on the one hand and lowering the number of infected as well as maximizing the economic gains from vaccinations on the other hand.

Plasma proteomic evidence for increased β-amyloid pathology after SARS-CoV-2 infection

Previous studies have suggested that systemic viral infections may increase risks of dementia. Whether this holds true for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus infections is unknown. Determining this is important for anticipating the potential future incidence of dementia. To begin to do this, we measured plasma biomarkers linked to Alzheimer's disease pathology in the UK Biobank before and after serology-confirmed SARS-CoV-2 infections. SARS-CoV-2 infection was associated with biomarkers associated with β-amyloid pathology: reduced plasma Aβ42:Aβ40 ratio and, in more vulnerable participants, lower plasma Aβ42 and higher plasma pTau-181. The plasma biomarker changes were greater in participants who had been hospitalized with COVID-19 or had reported hypertension previously. We showed that the changes in biomarkers were linked to brain structural imaging patterns associated with Alzheimer's disease, lower cognitive test scores and poorer overall health evaluations. Our data from this post hoc case-control matched study thus provide observational biomarker evidence that SARS-CoV-2 infection can be associated with greater brain β-amyloid pathology in older adults. While these results do not establish causality, they suggest that SARS-CoV-2 (and possibly other systemic inflammatory diseases) may increase the risk of future Alzheimer's disease.

Role and benefits of infectious diseases specialists in the COVID-19 pandemic: Multilevel analysis of care provision in German hospitals using data from the Lean European Open Survey on SARS-CoV-2 infected patients (LEOSS) cohort

PURPOSE

This study investigates the care provision and the role of infectious disease (ID) specialists during the coronavirus disease-2019 (COVID-19) pandemic.

METHODS

A survey was conducted at German study sites participating in the Lean European Open Survey on SARS-CoV-2 infected patients (LEOSS). Hospitals certified by the German Society of Infectious diseases (DGI) were identified as ID centers. We compared care provision and the involvement of ID specialists between ID and non-ID hospitals. Then we applied a multivariable regression model to analyse how clinical ID care influenced the mortality of COVID-19 patients in the LEOSS cohort.

RESULTS

Of the 40 participating hospitals in the study, 35% (14/40) were identified as ID centers. Among those, clinical ID care structures were more commonly established, and ID specialists were always involved in pandemic management and the care of COVID-19 patients. Overall, 68% (27/40) of the hospitals involved ID specialists in the crisis management team, 78% (31/40) in normal inpatient care, and 80% (28/35) in intensive care. Multivariable analysis revealed that COVID-19 patients in ID centers had a lower mortality risk compared to those in non-ID centers (odds ratio: 0.61 (95% CI 0.40-0.93), p = 0.021).

CONCLUSION

ID specialists played a crucial role in pandemic management and inpatient care.

Association between physical activity practice and sleep quality of older people in social isolation during the COVID-19 pandemic and Health Guidelines and future studies for the post-COVID period: a systematic review

PURPOSE

Physical activity (PA) is considered an alternative to mitigate the negative impacts of the COVID-19 pandemic on the sleep of older adults. The objective was to verify the association between physical activity and the sleep quality of older people in social isolation during the COVID-19 pandemic, to analyze the Health Guidelines, and suggest future studies for the post-COVID period.

METHODS

This systematic review followed PRISMA recommendations, and the protocol was registered in PROSPERO (CRD 42023406471). The search for articles occurred in April 2024 in the databases PubMed, Web of Science, SCOPUS, and gray literature. Data were extracted and checked in a Microsoft Excel® spreadsheet. The quality assessment was performed using tools from the National Institutes of Health.

RESULTS

In total, 1582 studies were found in the databases, of which nine were included in the analyses. Four studies reported a negative association of reduced levels of PA during the pandemic with sleep quality, while one study showed a positive association of PA with sleep quality. Four studies demonstrated no association.

CONCLUSIONS

PA was associated with the sleep quality of older adults during the COVID-19 pandemic and reduced levels of PA during this period demonstrated a negative association with sleep quality. Practice of PA is recommended for this post-COVID scenario, as a measure to reduce social isolation and its negative effects and improve the quality of sleep in older adults.

A Hierarchical Bayesian Model for Estimating Age-Specific COVID-19 Infection Fatality Rates in Developing Countries

The COVID-19 infection fatality rate (IFR) is the proportion of individuals infected with SARS-CoV-2 who subsequently die. As COVID-19 disproportionately affects older individuals, age-specific IFR estimates are imperative to facilitate comparisons of the impact of COVID-19 between locations and prioritize distribution of scarce resources. However, there lacks a coherent method to synthesize available data to create estimates of IFR and seroprevalence that vary continuously with age and adequately reflect uncertainties inherent in the underlying data. In this article, we introduce a novel Bayesian hierarchical model to estimate IFR as a continuous function of age that acknowledges heterogeneity in population age structure across locations and accounts for uncertainty in the estimates due to seroprevalence sampling variability and the imperfect serology test assays. Our approach simultaneously models test assay characteristics, serology, and death data, where the serology and death data are often available only for binned age groups. Information is shared across locations through hierarchical modeling to improve estimation of the parameters with limited data. Modeling data from 26 developing country locations during the first year of the COVID-19 pandemic, we found seroprevalence did not change dramatically with age, and the IFR at age 60 was above the high-income country estimate for most locations.

Global COVID-19 vaccine hesitancy among elderly: A systematic review

Background & Objectives

Elderly infected with COVID-19 has high mortality risk, and the protection from COVID-19 vaccine is limited by vaccine hesitancy. The information of vaccine hesitancy in elderly is incomplete and fragmented. In this study, we attempt to examine the level of vaccine hesitancy in elderly and the related factors in global perspectives.

Methods

A systematic review was conducted to include observational studies of COVID-19 vaccine hesitancy in elderly from January 2020 to September 2021. Search strategies covering COVID-19 vaccine, vaccine hesitancy and elderly in four databases of PUBMED, MEDLINE, EMBASE and COCHRANE LIBRARY were adopted. Studies reporting COVID-19 vaccine hesitancy prevalence in elderly were included. A meta-analysis of the vaccine hesitancy prevalence was performed. The primary outcome is the vaccine hesitancy prevalence in elderly population globally. The secondary outcomes are the factors of COVID-19 vaccine hesitancy among elderly.

Results

Initial 479 articles were included for screening, with 54 studies included for meta-analysis of COVID-19 vaccine hesitancy in elderly and 6 studies included for qualitative analysis of factors for vaccine hesitancy. The overall prevalence of vaccine hesitancy was 27.7 % (95 % C.I: 23.8-31.6 %). The prevalence was significantly higher in Asia than in Europe (35.3 % VS 17.9 %, p < 0.05). The vaccine hesitancy was significantly higher before the launch of the vaccine than after (30.3 % VS 18.7 %, p < 0.05). Important factors of vaccine hesitancy in elderly identified were low income, low education, perception of COVID-19 being more contagious, more vaccine side effects and lower vaccine efficacy.

Conclusions

COVID-19 vaccine hesitancy is an important problem in elderly, with geographical variation. Tailored policy and strategies targeting the hesitancy factors were required to promote COVID-19 vaccine to elderly.

Predictors of Change in Vaccination Decisions Among the Vaccine Hesitant: Examining the Roles of Age and Intolerance of Uncertainty

BACKGROUND

Vaccine hesitancy and resistance pose significant threats to controlling pandemics and preventing infectious diseases. In a group of individuals unvaccinated against the disease caused by the SARS-CoV-2 coronavirus (COVID-19), we investigated how age, intolerance of uncertainty (IU), and their interaction affected the likelihood of having changed one's vaccination decision a year later. We hypothesized that higher IU would increase the likelihood of becoming vaccinated, particularly among individuals of younger age. We predicted that this effect would remain significant, even after controlling for delay discounting and trust in science.

PURPOSE

The goal of this research was to understand the factors influencing changes in vaccination decisions among the vaccine hesitant.

METHODS

In a larger longitudinal study, ~7,500 participants from Prolific.co completed demographic and vaccination status questions, a delay discounting task, and the Intolerance of Uncertainty Scale in June-August 2021. Approximately 3,200 participants completed a follow-up survey in July-August 2022, answering questions about vaccination status, reasons for vaccination decision, and trust in science. We analyzed data from 251 participants who initially had no intention of getting vaccinated and completed the follow-up survey; 38% reported becoming vaccinated in the intervening year.

RESULTS

Data were analyzed using multilevel logistic regression. Over and above other factors related to vaccination decisions (delay discounting, trust in science), younger participants were more likely to change their decision and become vaccinated a year later, especially if they had higher IU, confirming our predictions. Primary reasons for becoming vaccinated were necessity and seeking protection against the virus.

CONCLUSIONS

These findings highlight the complex interplay between age, uncertainty, and vaccination decisions, and inform health policies by suggesting the need for tailoring interventions to specific concerns in different age groups.

A modeling framework for the analysis of the SARS-CoV2 transmission dynamics

Despite the progress in medical data collection the actual burden of SARS-CoV-2 remains unknown due to under-ascertainment of cases. This was apparent in the acute phase of the pandemic and the use of reported deaths has been pointed out as a more reliable source of information, likely less prone to under-reporting. Since daily deaths occur from past infections weighted by their probability of death, one may infer the total number of infections accounting for their age distribution, using the data on reported deaths. We adopt this framework and assume that the dynamics generating the total number of infections can be described by a continuous time transmission model expressed through a system of nonlinear ordinary differential equations where the transmission rate is modeled as a diffusion process allowing to reveal both the effect of control strategies and the changes in individuals behavior. We develop this flexible Bayesian tool in Stan and study 3 pairs of European countries, estimating the time-varying reproduction number (R t $$ {R}_t $$ ) as well as the true cumulative number of infected individuals. As we estimate the true number of infections we offer a more accurate estimate ofR t $$ {R}_t $$ . We also provide an estimate of the daily reporting ratio and discuss the effects of changes in mobility and testing on the inferred quantities.

Will COVID-19 become mild, like a cold?

Several recent studies conclude that an increase in the pathogenicity of SARS-CoV-2 cannot be ruled out. However, it should be noted that SARS-CoV-2 is a 'direct' respiratory virus - meaning it is usually spread by the respiratory route but does not routinely pass through the lymphatics like measles and smallpox. Providing its tropism does not change, it will be unique if its pathogenicity does not decrease until it becomes similar to common cold viruses. Ewald noted in the 1980s that respiratory viruses may evolve mildness because their spread benefits from the mobility of their hosts. This review examines factors that usually lower respiratory viruses' severity, including heat sensitivity (which limits replication in the warmer lungs) and changes to the virus's surface proteins. Other factors may, however, increase pathogenicity, such as replication in the lymphatic system and spreading via solid surfaces or faecal matter. Furthermore, human activities and political events could increase the harmfulness of SARS-CoV-2, including the following: large-scale testing, especially when the results are delayed; transmission in settings where people are close together and not free to move around; poor hygiene facilities; and social, political, or cultural influences that encourage sick individuals to remain active, including crises such as wars. If we can avoid these eventualities, SARS-CoV-2 is likely to evolve to be milder, although the timescale is uncertain. Observations of influenza-like pandemics suggest it may take around two decades for COVID-19 to become as mild as seasonal colds.

Impact of cross-reactivity and herd immunity on SARS-CoV-2 pandemic severity

Public health systems reported low mortality from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in East Asia, in low-income countries, and for children during the first year of the SARS-CoV-2 pandemic. These reports led commentators to suggest that cross-reactive immunity from prior exposure to other pathogens reduced fatality risk. Resolution of initial infection waves also contributed to speculation that herd immunity prevented further waves prior to vaccination. Serology instead implied that immunity was too limited to achieve herd immunity and that there was little impact from cross-reactive protection. Paediatric deaths exceeded those from influenza, with higher age-specific fatality risk in lower-income nations and similar fatality risk in East Asia compared with demographically similar regions. Neither pre-outbreak exposure to related pathogens nor immunity induced by initial infection waves are necessarily a reliable response to future pathogen outbreaks. Preparedness for future pathogen outbreaks should instead focus on strategies such as voluntary behavioural changes, nonpharmaceutical interventions, and vaccination.

FIB-4 score as a predictor of COVID-19-related severity in hospitalized patients

AIM

to determine the impact of liver fibrosis on the prognosis of COVID and liver injury associated with the infection.

METHODS

retrospective multicenter study including 575 patients requiring admission for COVID-19 between January and June 2020. Fibrosis index-4 (FIB-4) was calculated within six months prior to infection and at six months post-infection.

RESULTS

baseline FIB-4 was elevated in patients who died (1.91 ± 0.95 vs 1.43 ± 0.85; p < 0.001). In addition, 17.1 % (32/187) of patients with baseline FIB-4 < 1.45 died vs 52.9 % (9/17) with FIB-4 > 3.25 (p < 0.001). In the adjusted multivariate analysis, baseline FIB-4 (OR 1.61 [95 % CI: 1.19-2.18]; p = 0.002) was independently associated with mortality. Parameters associated with liver injury, including aspartate aminotransferase (AST) (28 ± 10 vs 45 ± 56 IU/l; p < 0.001) and alanine aminotransferase (ALT) (20 ± 12 vs 38 ± 48 IU/l; p < 0.001) were significantly higher at admission compared to baseline. Furthermore, FIB-4 increased from baseline to the time of admission (1.53 ± 0.88 vs 2.55 ± 1.91; p < 0.001), and up to 6.9 % (10/145) of patients with FIB-4 < 1.45 on admission died vs 47.5 % if FIB-4 > 3.25 (58/122) (p < 0.001). In the adjusted multivariate analysis, FIB-4 on admission (OR 1.14 [95 % CI: 1.03-1.27]; p = 0.015) was independently associated with mortality. In addition, AST (42 ± 38 vs 22 ± 17 IU/l; p < 0.001) and ALT (40 ± 50 vs 20 ± 19 IU/l; p < 0.001) were significantly reduced at six months after the resolution of infection. Accordingly, FIB-4 decreased significantly (2.12 ± 1.25 vs 1.32 ± 0.57; p < 0.001) six months after the infection.

CONCLUSION

increased FIB-4, either at baseline or at the time of admission, was associated with severity and mortality related to respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, the liver damage expressed by elevated transaminases and FIB-4 levels was reversible in most of patients.

COVID-19 in Pediatric Populations

The COVID-19 pandemic reshaped the landscape of respiratory viral illnesses, causing common viruses to fade as SARS-CoV-2 took precedence. By 2023, more than 96% of the children in the United States were estimated to have been infected with SARS-CoV-2, with certain genetic predispositions and underlying health conditions posing risk factors for severe disease in children. Children, in general though, exhibit immunity advantages, protecting against aspects of the SARS-CoV-2 infection known to drive increased severity in older adults. Post-COVID-19 complications such as multisystem inflammatory syndrome in children and long COVID have emerged, underscoring the importance of vaccination. Here, we highlight the risks of severe pediatric COVID-19, age-specific immunoprotection, comparisons of SARS-CoV-2 with other respiratory viruses, and factors contributing to post-COVID-19 complications in children.

Examining the effects of voluntary avoidance behaviour and policy-mediated behaviour change on the dynamics of SARS-CoV-2: A mathematical model

Background

Throughout the SARS-CoV-2 pandemic, policymakers have had to navigate between recommending voluntary behaviour change and policy-driven behaviour change to mitigate the impact of the virus. While individuals will voluntarily engage in self-protective behaviour when there is an increasing infectious disease risk, the extent to which this occurs and its impact on an epidemic is not known.

Methods

This paper describes a deterministic disease transmission model exploring the impact of individual avoidance behaviour and policy-mediated avoidance behaviour on epidemic outcomes during the second wave of SARS-CoV-2 infections in Ontario, Canada (September 1, 2020 to February 28, 2021). The model incorporates an information feedback function based on empirically derived behaviour data describing the degree to which avoidance behaviour changed in response to the number of new daily cases COVID-19.

Results

Voluntary avoidance behaviour alone was estimated to reduce the final attack rate by 23.1%, the total number of hospitalizations by 26.2%, and cumulative deaths by 27.5% over 6 months compared to a counterfactual scenario in which there were no interventions or avoidance behaviour. A provincial shutdown order issued on December 26, 2020 was estimated to reduce the final attack rate by 66.7%, the total number of hospitalizations by 66.8%, and the total number of deaths by 67.2% compared to the counterfactual scenario.

Conclusion

Given the dynamics of SARS-CoV-2 in a pre-vaccine era, individual avoidance behaviour in the absence of government action would have resulted in a moderate reduction in disease however, it would not have been sufficient to entirely mitigate transmission and the associated risk to the population in Ontario. Government action during the second wave of the COVID-19 pandemic in Ontario reduced infections, protected hospital capacity, and saved lives.

The Medical Complexity of Newly Admitted Long-Term Care Residents Before and During the COVID-19 Pandemic in Ontario, British Columbia, and Alberta: A Serial Cross-Sectional Study

The COVID-19 pandemic had profound effects on the long-term care (LTC) setting worldwide, including changes in admission practices. We aimed to describe the characteristics and medical complexity of newly admitted LTC residents before (March 1, 2019 to February 29, 2020) and during (March 1, 2020 to March 31, 2021) the COVID-19 pandemic via a population-based serial cross-sectional study in Ontario, Alberta, and British Columbia, Canada. With data from the Minimum Data Set 2.0 we characterize the medical complexity of newly admitted LTC residents via the Geriatric 5Ms framework (mind, mobility, medication, multicomplexity, matters most) through descriptive statistics (counts, percentages), stratified by pandemic wave, month, and province. We included 45 756 residents admitted in the year prior to and 35 744 during the first year of the pandemic. We found an increased proportion of residents with depression, requiring extensive assistance with activities of daily living, hip fractures, antipsychotic use, expected to live <6 months, with pneumonia, low social engagement, and admitted from acute care. Our study confirms an increase in medical complexity of residents admitted to LTC during the pandemic and can be used to plan services and interventions and as a baseline for continued monitoring in changes in population characteristics over time.

More severe comorbidities, advanced age, and incomplete vaccination increase the risk of COVID-19 mortality

Numerous studies have stated that comorbidities are risk factors for coronavirus disease 2019 (COVID-19) mortality, but few have considered the severity or stage of these comorbidities. The aim of this study was to determine the association between the severity of comorbidity, age, and number of COVID-19 vaccinations with COVID-19 mortality. This case-control study was conducted from July 2021 until December 2022 at the Dr. Soetomo General Academic Hospital, Surabaya, Indonesia. The patients were divided into non-survived patients (case group) and survived patients (control group). The inclusion criteria for cases were adult patients hospitalized with confirmed COVID-19, based on reverse transcriptase-polymerase chain reaction (RT-PCR) testing of nasopharyngeal swabs. Using total sampling, 1,046 confirmed COVID-19 patients, which consisted of 450 (43%) non-survived patients and 596 (57%) survived patients, were included. The most common comorbidity was diabetes mellitus (DM) (82.7%), chronic kidney disease (CKD) (43%), hypertension (25.7%), and obesity (23.6%). Our multivariate analysis indicated that older age (aOR: 1.03; 95%CI: 1.02-1.04, p<0.001), male sex (aOR: 1.29; 95%CI: 1.11- 2.00, p=0.007), severe COVID-19 at first admission (aOR: 3.13; 95%CI: 2.08-4.73, p<0.001), having pneumonia (aOR: 1.99; 95%CI: 1.21-3.33, p=0.005), poorly controlled DM with HbA1c≥9% (aOR: 2.90; 95%CI: 1.72-4.89, p<0.001), severe obesity with body mass index (BMI)≥30 (OR: 2.90; 95%CI: 1.72-4.89, p<0.001), hypertension stage 2 (aOR: 1.99; 95%CI: 1.12-3.53, p=0.019) or stage 3 (aOR: 6.59; 95%CI: 2.39-18.17, p<0.001), CKD stage 3 (aOR: 2.50; 95%CI: 1.36-4.59, p=0.003), stage 4 (aOR: 5.47; 95%CI: 2.18-13.69, p<0.001) or stage 5 (aOR: 1.71; 95%CI: 1.04-2.81, p=0.036), and having chronic lung disease (aOR: 3.08; 95%CI: 1.22-7.77, p=0.017) significantly increased the risk of COVID-19 mortality. In contrast, COVID-19 vaccination reduced the risk of COVID-19-associated death. This study highlights that more severe comorbidities, advanced age, and incomplete vaccination were associated with COVID-19 mortality.

Comparison of fatalities due to COVID-19 and other nonexternal causes during the first five pandemic waves : Results from multiple cause of death statistics in Bavaria

BACKGROUND

Older age is a risk factor for a fatal course of SARS-CoV‑2 infection, possibly due to comorbidities whose exact role in this context, however, is not yet well understood. In this paper, the characteristics and comorbidities of persons who had died of COVID-19 in Bavaria by July 2022 are shown and compared with the characteristics of other fatalities during the pandemic.

METHODS

Based on data from multiple cause of death statistics, odds ratios for dying from COVID-19 (compared to dying from other nonexternal causes of death) were calculated by using logistic regression models, stratified by age, sex, and pandemic waves.

RESULTS

In Bavaria, a total of 24,479 persons (6.5% of all deaths) officially died from COVID-19 between March 2020 and July 2022. In addition to increasing age and male sex, preexisting diseases and comorbidities such as obesity, degenerative diseases of the nervous system, dementia, renal insufficiency, chronic lower respiratory diseases, and diabetes mellitus were significantly associated with COVID-19-related deaths. Dementia was mainly associated with increased COVID-19 mortality during the first and second waves, while obesity was strongly associated during the fourth wave.

DISCUSSION

The frequency of specific comorbidities in COVID-19 deaths varied over the course of the pandemic. This suggests that wave-specific results also need to be interpreted against the background of circulating virus variants, changing immunisation levels, and nonpharmaceutical interventions in place at the time.

SARS-CoV-2 dynamics in New York City during March 2020-August 2023

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been widespread since 2020 and will likely continue to cause substantial recurring epidemics. However, understanding the underlying infection burden (i.e., including undetected asymptomatic/mild infections) and dynamics, particularly since late 2021 when the Omicron variant emerged, is challenging due to the potential for asymptomatic and repeat SARS-CoV-2 infection, changes in testing practices, and changes in disease reporting. Here, we leverage extensive surveillance data available in New York City (NYC) and a comprehensive model-inference system to reconstruct SARS-CoV-2 dynamics therein from the pandemic onset in March 2020 to August 2023, and further validate the estimates using independent wastewater surveillance data. The validated model-inference estimates indicate a very high infection burden totaling twice the population size (>5 times documented case count) but decreasing infection-fatality risk (a >10-fold reduction) during the first 3.5 years. The detailed estimates also reveal highly complex variant dynamics and immune landscape, changing virus transmissibility, and higher infection risk during winter in NYC over this time period. These transmission dynamics and drivers, albeit based on data in NYC, may be relevant to other populations and inform future planning to help mitigate the public health burden of SARS-CoV-2.

Sarcopenia, sarcopenic obesity and the clinical outcome of the older inpatients with COVID-19 infection: a prospective observational study

OBJECTIVE

We aimed to investigate the impact of sarcopenia and sarcopenic obesity (SO) on the clinical outcome in older patients with COVID-19 infection and chronic disease.

METHODS

We prospectively collected data from patients admitted to Huadong Hospital for COVID-19 infection between November 1, 2022, and January 31, 2023. These patients were included from a previously established comprehensive geriatric assessment (CGA) cohort. We collected information on their pre-admission condition regarding sarcopenia, SO, and malnutrition, as well as their medical treatment. The primary endpoint was the incidence of intubation, while secondary endpoints included in-hospital mortality rates. We then utilized Kaplan-Meier (K-M) survival curves and the log-rank tests to compare the clinical outcomes related to intubation or death, assessing the impact of sarcopenia and SO on patient clinical outcomes.

RESULTS

A total of 113 patients (age 89.6 ± 7.0 years) were included in the study. Among them, 51 patients had sarcopenia and 39 had SO prior to hospitalization. Intubation was required for 6 patients without sarcopenia (9.7%) and for 18 sarcopenia patients (35.3%), with 16 of these being SO patients (41%). Mortality occurred in 2 patients without sarcopenia (3.3%) and in 13 sarcopenia patients (25.5%), of which 11 were SO patients (28%). Upon further analysis, patients with SO exhibited significantly elevated risks for both intubation (Hazard Ratio [HR] 7.43, 95% Confidence Interval [CI] 1.26-43.90, P < 0.001) and mortality (HR 6.54, 95% CI 1.09-39.38, P < 0.001) after adjusting for confounding factors.

CONCLUSIONS

The prevalence of sarcopenia or SO was high among senior inpatients, and both conditions were found to have a significant negative impact on the clinical outcomes of COVID-19 infection. Therefore, it is essential to regularly assess and intervene in these conditions at the earliest stage possible.

Understanding COVID-19-Related Behaviors, Worries, and Attitudes among Chinese: Roles of Personality and Severity

During the COVID-19 pandemic, people exhibited various forms of adjustments. This study examines how situational factors (i.e., the severity of COVID-19) and individual differences (i.e., the HEXACO traits) affect one's COVID-19-related responses regarding behaviors (i.e., mask-wearing and hoarding), worries (i.e., worrying about infecting and spreading COVID-19), and attitudes (i.e., discrimination and empathy toward people infecting COVID-19) in China. With a sample of 927 participants, our results show that the severity of COVID-19 was predictive of all the responses, and its predictive value was more pronounced relative to personality traits. Concerning the association between personality traits and responses, Honesty-Humility and Conscientiousness were predictive of one's behaviors, Emotionality was predictive of one's worries, and almost all the HEXACO traits were associated with one's attitudes toward people infected with COVID-19. This study sheds some light on understanding how situations and individual differences shape one's responses in a time of emergency.

Rapid initiation of nasal saline irrigation to reduce severity in high-risk COVID+ outpatients

OBJECTIVE

To determine whether initiating saline nasal irrigation after COVID-19 diagnosis reduces hospitalization and death in high-risk outpatients compared with observational controls, and if irrigant composition impacts severity.

METHODS

Participants 55 and older were enrolled within 24 hours of a + PCR COVID-19 test between September 24 and December 21, 2020. Among 826 screened, 79 participants were enrolled and randomly assigned to add 2.5 mL povidone-iodine 10% or 2.5 mL sodium bicarbonate to 240 mL of isotonic nasal irrigation twice daily for 14 days. The primary outcome was hospitalization or death from COVID-19 within 28 days of enrollment by daily self-report confirmed with phone calls and hospital records, compared to the CDC Surveillance Dataset covering the same time. Secondary outcomes compared symptom resolution by irrigant additive.

RESULTS

Seventy-nine high-risk participants were enrolled (mean [SD] age, 64 [8] years; 36 [46%] women; 71% Non-Hispanic White), with mean BMI 30.3. Analyzed by intention-to-treat, by day 28, COVID-19 symptoms resulted in one ED visit and no hospitalizations in 42 irrigating with alkalinization, one hospitalization of 37 in the povidone-iodine group, (1.27%) and no deaths. Of nearly three million CDC cases, 9.47% were known to be hospitalized, with an additional 1.5% mortality in those without hospitalization data. Age, sex, and percentage with pre-existing conditions did not significantly differ by exact binomial test from the CDC dataset, while reported race and hospitalization rate did. The total risk of hospitalization or death (11%) was 8.57 times that of enrolled nasal irrigation participants (SE = 2.74; P = .006). Sixty-two participants completed daily surveys (78%), averaging 1.8 irrigations/day. Eleven reported irrigation-related complaints and four discontinued use. Symptom resolution was more likely for those reporting twice daily irrigation (X2 = 8.728, P = .0031) regardless of additive.

CONCLUSION

SARS-CoV-2+ participants initiating nasal irrigation were over 8 times less likely to be hospitalized than the national rate.

Modelling the unexpected dynamics of COVID-19 in Manaus, Brazil

In late March 2020, SARS-CoV-2 arrived in Manaus, Brazil, and rapidly developed into a large-scale epidemic that collapsed the local health system and resulted in extreme death rates. Several key studies reported that ∼76% of residents of Manaus were infected (attack rate AR≃76%) by October 2020, suggesting protective herd immunity had been reached. Despite this, an unexpected second wave of COVID-19 struck again in November and proved to be larger than the first, creating a catastrophe for the unprepared population. It has been suggested that this could be possible if the second wave was driven by reinfections. However, it is widely reported that reinfections were at a low rate (before the emergence of Omicron), and reinfections tend to be mild. Here, we use novel methods to model the epidemic from mortality data without considering reinfection-caused deaths and evaluate the impact of interventions to explain why the second wave appeared. The method fits a "flexible" reproductive number R 0 ( t ) that changes over the epidemic, and it is demonstrated that the method can successfully reconstruct R 0 ( t ) from simulated data. For Manaus, the method finds AR≃34% by October 2020 for the first wave, which is far less than required for herd immunity yet in-line with seroprevalence estimates. The work is complemented by a two-strain model. Using genomic data, the model estimates transmissibility of the new P.1 virus lineage as 1.9 times higher than that of the non-P.1. Moreover, an age class model variant that considers the high mortality rates of older adults show very similar results. These models thus provide a reasonable explanation for the two-wave dynamics in Manaus without the need to rely on large reinfection rates, which until now have only been found in negligible to moderate numbers in recent surveillance efforts.

Estimating geographic variation of infection fatality ratios during epidemics

Objectives

We aim to estimate geographic variability in total numbers of infections and infection fatality ratios (IFR; the number of deaths caused by an infection per 1,000 infected people) when the availability and quality of data on disease burden are limited during an epidemic.

Methods

We develop a noncentral hypergeometric framework that accounts for differential probabilities of positive tests and reflects the fact that symptomatic people are more likely to seek testing. We demonstrate the robustness, accuracy, and precision of this framework, and apply it to the United States (U.S.) COVID-19 pandemic to estimate county-level SARS-CoV-2 IFRs.

Results

The estimators for the numbers of infections and IFRs showed high accuracy and precision; for instance, when applied to simulated validation data sets, across counties, Pearson correlation coefficients between estimator means and true values were 0.996 and 0.928, respectively, and they showed strong robustness to model misspecification. Applying the county-level estimators to the real, unsimulated COVID-19 data spanning April 1, 2020 to September 30, 2020 from across the U.S., we found that IFRs varied from 0 to 44.69, with a standard deviation of 3.55 and a median of 2.14.

Conclusions

The proposed estimation framework can be used to identify geographic variation in IFRs across settings.

Clinical outcomes in patients with diabetes and stress hyperglycemia that developed SARS-CoV-2 infection

INTRODUCTION

Diabetes and stress hyperglycemia have been related with poorer clinical outcomes in patients infected by SARS-CoV-2 and at risk for severe disease.

OBJECTIVE

To evaluate clinical outcomes in three groups of patients (with diabetes, without diabetes and with stress hyperglycemia) with SARS-CoV-2 infection.

MATERIALS AND METHODS

A retrospective cohort study was conducted in Cali (Colombia). We included patients 18 years old or older with a diagnosis of SARS-CoV-2 infection, managed in the emergency room, hospitalization, or intensive care unit between March 2020 and December 2021. Immunocompromised patients and pregnant women were excluded. Patients were classified into three groups: without diabetes, with diabetes, and with stress hyperglycemia. A comparison between the groups was performed.

RESULTS

A total of 945 patients were included (59.6% without diabetes, 27% with diabetes, and 13.4% with stress hyperglycemia). Fifty-five-point three percent required intensive care unit management, with a higher need in patients with stress hyperglycemia (89.8%) and diabetes (67.1%), with no difference between these groups (p = 0.249). We identified a higher probability of death in the group with stress hyperglycemia versus the one without diabetes (adjusted OR = 8.12; 95% CI: 5.12-12.88; p < 0.01). Frequency of acute respiratory distress syndrome, need for invasive mechanical ventilation, use of vasopressors and inotropes, need for de novo renal replacement therapy, and mortality was higher in patients with metabolic alterations (diabetes and stress hyperglycemia).

CONCLUSIONS

Diabetes and stress hyperglycemia were associated with worse clinical outcomes and mortality in patients with COVID-19. These patients should be identified early and considered them high risk at the COVID-19 diagnosis to mitigate adverse outcomes.

Estimation of standardized real-time fatality rate for ongoing epidemics

BACKGROUND

The fatality rate is a crucial metric for guiding public health policies during an ongoing epidemic. For COVID-19, the age structure of the confirmed cases changes over time, bringing a substantial impact on the real-time estimation of fatality. A 'spurious decrease' in fatality rate can be caused by a shift in confirmed cases towards younger ages even if the fatalities remain unchanged across different ages.

METHODS

To address this issue, we propose a standardized real-time fatality rate estimator. A simulation study is conducted to evaluate the performance of the estimator. The proposed method is applied for real-time fatality rate estimation of COVID-19 in Germany from March 2020 to May 2022.

FINDINGS

The simulation results suggest that the proposed estimator can provide an accurate trend of disease fatality in all cases, while the existing estimator may convey a misleading signal of the actual situation when the changes in temporal age distribution take place. The application to Germany data shows that there was an increment in the fatality rate at the implementation of the 'live with COVID' strategy.

CONCLUSIONS

As many countries have chosen to coexist with the coronavirus, frequent examination of the fatality rate is of paramount importance.

Categorisation of continuous covariates for stratified randomisation: How should we adjust?

To obtain valid inference following stratified randomisation, treatment effects should be estimated with adjustment for stratification variables. Stratification sometimes requires categorisation of a continuous prognostic variable (eg, age), which raises the question: should adjustment be based on randomisation categories or underlying continuous values? In practice, adjustment for randomisation categories is more common. We reviewed trials published in general medical journals and found none of the 32 trials that stratified randomisation based on a continuous variable adjusted for continuous values in the primary analysis. Using data simulation, this article evaluates the performance of different adjustment strategies for continuous and binary outcomes where the covariate-outcome relationship (via the link function) was either linear or non-linear. Given the utility of covariate adjustment for addressing missing data, we also considered settings with complete or missing outcome data. Analysis methods included linear or logistic regression with no adjustment for the stratification variable, adjustment for randomisation categories, or adjustment for continuous values assuming a linear covariate-outcome relationship or allowing for non-linearity using fractional polynomials or restricted cubic splines. Unadjusted analysis performed poorly throughout. Adjustment approaches that misspecified the underlying covariate-outcome relationship were less powerful and, alarmingly, biased in settings where the stratification variable predicted missing outcome data. Adjustment for randomisation categories tends to involve the highest degree of misspecification, and so should be avoided in practice. To guard against misspecification, we recommend use of flexible approaches such as fractional polynomials and restricted cubic splines when adjusting for continuous stratification variables in randomised trials.

Inference under superspreading: Determinants of SARS-CoV-2 transmission in Germany

Superspreading, under-reporting, reporting delay, and confounding complicate statistical inference on determinants of disease transmission. A model that accounts for these factors within a Bayesian framework is estimated using German Covid-19 surveillance data. Compartments based on date of symptom onset, location, and age group allow to identify age-specific changes in transmission, adjusting for weather, reported prevalence, and testing and tracing. Several factors were associated with a reduction in transmission: public awareness rising, information on local prevalence, testing and tracing, high temperature, stay-at-home orders, and restaurant closures. However, substantial uncertainty remains for other interventions including school closures and mandatory face coverings. The challenge of disentangling the effects of different determinants is discussed and examined through a simulation study. On a broader perspective, the study illustrates the potential of surveillance data with demographic information and date of symptom onset to improve inference in the presence of under-reporting and reporting delay.

Diagnostics for Public Health - Infectious Disease Surveillance and Control

AbstractAccurate diagnostics are critical in public health to ensure successful disease tracking, prevention, and control. Many of the same characteristics are desirable for diagnostic procedures in both medicine and public health: for example, low cost, high speed, low invasiveness, ease of use and interpretation, day-to-day consistency, and high accuracy. This review lays out five principles that are salient when the goal of diagnosis is to improve the overall health of a population rather than that of a particular patient, and it applies them in two important use cases: pandemic infectious disease and antimicrobial resistance.

Consumption of Meats and Fish in Poland during the COVID-19 Lockdown Period

The COVID-19 pandemic and related restrictions have significantly impacted the quality of life of society in many countries in various aspects. The purpose of this study was to examine how the COVID-19 pandemic affected the consumption of meat and fish in society in Poland as well as the factors that determined these changes. The cross-sectional study was conducted using an original online questionnaire between 8th and 18th of April 2020. The subjects were selected randomly. The target population were adults living in Poland. The inclusion criterion for the study was the age of at least 18 years and consent to selfless participation in the study. Communication via social media such as Facebook or Instagram was used to enroll more participants from different socio-demographic subgroups. The questionnaire was divided into two parts-the first part contained questions about sex, age, body mass, body height, residence, level of education, and occupation, and the second part consisted of specific questions about the consumption frequency of different kinds of meat during the COVID-19 lockdown period (in comparison to the time before the pandemic). A total of 3888 people took part in the study including 84.54% women, with an average age of 30.17 ± 9.22 years. The frequency of poultry consumption increased, while for pork, beef, ham and other meat products as well as fish and seafood it declined. The factors that influenced the change in dietary patterns during the lockdown related to the COVID-19 pandemic included age, body mass index, gender, place of residence, and type of work performed. However, no relationship was found between the change in meat and fish consumption during the pandemic and the level of education and form of employment during the pandemic.

Association of socioeconomic disadvantage and ethnicity with perinatal neonatal, and infant mortality in Slovakia

BACKGROUND

Infant mortality rates are reliable indices of the child and general population health status and health care delivery. The most critical factors affecting infant mortality are socioeconomic status and ethnicity. The aim of this study was to assess the association between socioeconomic disadvantage, ethnicity, and perinatal, neonatal, and infant mortality in Slovakia before and during the COVID-19 pandemic.

METHODS

The associations between socioeconomic disadvantage (educational level, long-term unemployment rate), ethnicity (the proportion of the Roma population) and mortality (perinatal, neonatal, and infant) in the period 2017-2022 were explored, using linear regression models.

RESULTS

The higher proportion of people with only elementary education and long-term unemployed, as well as the higher proportion of the Roma population, increases mortality rates. The proportion of the Roma population had the most significant impact on mortality in the selected period between 2017 and 2022, especially during the COVID-19 pandemic (2020-2022).

CONCLUSIONS

Life in segregated Roma settlements is connected with the accumulation of socioeconomic disadvantage. Persistent inequities between Roma and the majority population in Slovakia exposed by mortality rates in children point to the vulnerabilities and exposures which should be adequately addressed by health and social policies.

Attitudes towards COVID-19 vaccination: A cross sectional study in the Federal Capital Territory, Nigeria

Vaccine acceptance is complex and context-specific, varying across time, place and perceived behavioural nature of the community involved. A high vaccine acceptance rate is important to achieve herd immunity, however, vaccine hesitancy is a possible barrier to this. This study aimed to assess attitudes towards COVID-19 vaccination and associated factors. A cross-sectional survey was undertaken to investigate the attitudes of Federal Capital Territory residents towards COVID-19 vaccine uptake in Nigeria. Data were collected using questionnaires which were administered to respondents physically and online through random and snowball sampling strategies respectively. Data received were then analysed using Statistical Package for Social Sciences (SPSS). A total of 1767 responses were received with males representing 57.8% of the sample. More than half (54.9%) of the respondents were between the ages of 18-30 years. A third (35.4%) of the study participants indicated that a vaccine was not necessary for COVID-19, and 56.5% indicated willingness to accept COVID-19 vaccination. The majority of the sample (56.9%) indicated that the government decision-making was in their best interest, whilst close to two-thirds of the respondents (61%) were of the view that COVID-19 vaccination should not be made compulsory. Older respondents as represented by those over 60 years were more likely to accept COVID-19 vaccination (p = 0.039). This study however revealed negative attitudes towards COVID-19 vaccination, indicating the urgent need for government, policymakers, and other stakeholders to prioritise the development of strategies that can appropriately address vaccine hesitancy in the study setting. Contextual interventions indicated include strategic public enlightenment campaigns targeting populations with less favourable dispositions towards being vaccinated.

Cytokine expression and mortality risk among COVID-19 hospitalized patients over 60 years of age in a referral hospital in Cartagena, Colombia

Background

Cytokine dysregulation in COVID-19 patients aged over 60 has been associated to adverse outcomes. While serum levels have been studied, cellular expression, particularly in Afro-Colombians, remains understudied. This research aims to describe cytokine expression in peripheral blood leukocytes and its association with adverse outcomes in COVID-19 patients aged over 60 at Cartagena's referral hospital.

Methods

A cohort study was conducted, encompassing severe and critical cases of COVID-19 between November 2021 and February 2022. At baseline, the cellular expression level of cytokines IL-2, IL-4, IL-6, IL-10, TNF-α and IFN-γ was assessed using flow cytometry. Additionally, various biochemical, hematological, and coagulation markers were evaluated. The main outcome was time to death.

Results

Among the 50 enrolled participants, the median age was 76.5 years, 60% were male, 60% were admitted to the ICU, and 42% died. Lactate dehydrogenase and hemoglobin were the only markers that differed between fatal and surviving cases. Regarding cytokines, the level of IL-6 expression was associated with an increased risk of death. Specifically, a one percent increase in the expression was associated with a 7.3% increase in the risk of death. Stratifying the analysis by death and ICU admission, the median expression level remained high in fatal cases who were admitted to the ICU.

Conclusions

Our findings revealed a significant association between high cellular expression levels of IL-6 and an increased risk of mortality. These results provide valuable scientific insights that could inform the prioritization of case management, providing especially advantageous for the vulnerable Afro-Colombian group.

COVID-19 surveillance report for Sudan, 2020 to 2021

Background

Following the World Health Organization declaration, COVID-19 was first appearance in Sudan was in March 2020. Cases were reported to the Sudan Federal Ministry of Heath through the surveillance system from different sources. This study used surveillance data from 2020 to 2021 to describe the epidemiologic patterns of COVID-19 occurrence in Sudan and provide insight for better preparedness and response.

Methods

Through a retrospective descriptive study, COVID19 cases records obtained from the national surveillance line-list in Surveillance and Information Directorate in Federal Ministry of Health. The analysis of data was done with SPSS version 21. Descriptive analysis done by frequencies and percentages, and further analysis through performing multivariate logistic regression.

Results

Out of 48,545 suspected cases tested for COVID-19 using RT-PCR, 27,453 (56.5%) tested positive with case fatality ratio of 6.5%. Higher death rate among elderly (78% > 60-year-old) and males (70.1%). From the reported cases, 53.8% showed no symptoms, while the common symptoms among symptomatic patients were; fever (26.4%), cough (19.1%), shortness of breath (16.8%) with small proportion (4.5%) reported loss of smell and taste. Specific states, Khartoum, Gezira and Red Sea showed highest prevalence. The disease peaked four times during 2020-2021, with a proposed alert threshold of 200-250 cases per week acting as an explosion point nationwide.

Conclusions

The high case fatality rate in the country requires further analysis, as well as the high proportion of asymptomatic infection. This will be ensured by improving the quality and completeness of surveillance data. A proposed threshold of 200-250 cases per week should be an alert to augment the measures of controlling the pandemic over the country, including providing enough supplies to decrease mortality.

Flatten the curve. On a new covid-19 (hit) severity

BACKGROUND

During the health crisis of the COVID-19 pandemic, the adagium was to 'flatten the curve'. We investigate how well countries succeeded in this aim by constructing an appropriate severity measure. It is able to distinguish between countries that, e.g., experienced identical overall (excess) mortality rates or attained equal case load peaks over a certain period of time. Concretely, this implies that an identical total number of infections or deaths over a certain period is considered relatively worse if there is a higher and/or more peaks. More classical measures (like the total number or the maximum of cases/deaths) neglect this and are therefore inappropriate to assess the resilience of a health care system nor pandemic policy ex post performance.

METHODS & RESULTS

We applied our new (hit) severity to a set of 32 countries, and found that the flattening didn't go equally well. The difference in severity is large, with Norway being consistently the least severely hit by the pandemic (using deaths as indicator) during the whole observation period, while Hungary comes out as eventually being hit the hardest in our sample.

CONCLUSIONS

Having constructed a (hit) severity measure that enables to differentiate between countries' performances in a sound way, further research should now relate these observed differences to the pre-pandemic health care status and the sanitary measures or restrictions imposed during the pandemic; in order to reveal what measures help the most in what type of health care system and society.

Bayesian workflow for time-varying transmission in stratified compartmental infectious disease transmission models

Compartmental models that describe infectious disease transmission across subpopulations are central for assessing the impact of non-pharmaceutical interventions, behavioral changes and seasonal effects on the spread of respiratory infections. We present a Bayesian workflow for such models, including four features: (1) an adjustment for incomplete case ascertainment, (2) an adequate sampling distribution of laboratory-confirmed cases, (3) a flexible, time-varying transmission rate, and (4) a stratification by age group. Within the workflow, we benchmarked the performance of various implementations of two of these features (2 and 3). For the second feature, we used SARS-CoV-2 data from the canton of Geneva (Switzerland) and found that a quasi-Poisson distribution is the most suitable sampling distribution for describing the overdispersion in the observed laboratory-confirmed cases. For the third feature, we implemented three methods: Brownian motion, B-splines, and approximate Gaussian processes (aGP). We compared their performance in terms of the number of effective samples per second, and the error and sharpness in estimating the time-varying transmission rate over a selection of ordinary differential equation solvers and tuning parameters, using simulated seroprevalence and laboratory-confirmed case data. Even though all methods could recover the time-varying dynamics in the transmission rate accurately, we found that B-splines perform up to four and ten times faster than Brownian motion and aGPs, respectively. We validated the B-spline model with simulated age-stratified data. We applied this model to 2020 laboratory-confirmed SARS-CoV-2 cases and two seroprevalence studies from the canton of Geneva. This resulted in detailed estimates of the transmission rate over time and the case ascertainment. Our results illustrate the potential of the presented workflow including stratified transmission to estimate age-specific epidemiological parameters. The workflow is freely available in the R package HETTMO, and can be easily adapted and applied to other infectious diseases.

Vaccination strategies impact the probability of outbreak extinction: A case study of COVID-19 transmission

Mass vaccination has proven to be an effective control measure for mitigating the transmission of infectious diseases. Throughout history, various vaccination strategies have been employed to control infections and terminate outbreaks. In this study, we utilized the transmission of COVID-19 as a case study and constructed a stochastic age-structured compartmental model to investigate the effectiveness of different vaccination strategies. Our analysis focused on estimating the outbreak extinction probability under different vaccination scenarios in both homogeneous and heterogeneous populations. Notably, we found that population heterogeneity can enhance the likelihood of outbreak extinction at varying levels of vaccine coverage. Prioritizing vaccinations for individuals with higher infection risk was found to maximize outbreak extinction probability and reduce overall infections, while allocating vaccines to those with higher mortality risk has been proven more effective in reducing deaths. Moreover, our study highlighted the significance of booster doses as the vaccine effectiveness wanes over time, showing that they can significantly enhance the extinction probability and mitigate disease transmission.

Prevalence of Neutralizing Autoantibodies Against Type I Interferon in a Multicenter Cohort of Severe or Critical COVID-19 Cases in Shanghai

OBJECTIVE

We sought to explore the prevalence of type I interferon-neutralizing antibodies in a Chinese cohort and its clinical implications during the Omicron variant wave of SARS-CoV-2.

METHODS

Type I interferon (IFN) autoantibodies possessing neutralizing capabilities were identified using luciferase assays. The capacity of the autoantibodies for in vitro interference with antiviral activity of IFN was assessed by using a SARS-CoV-2 replicon system. An analysis of the demographic and clinical profiles of patients exhibiting neutralizing antibodies was also conducted.

RESULTS

In this cohort, 11.8% of severe/critical cases exhibited the existence of type I IFN-neutralizing antibodies, specifically targeting IFN-α2, IFN-ω, or both, with an elderly male patient tendency. Notably, these antibodies exerted a pronounced inhibitory effect on the antiviral activity of IFN against SARS-CoV-2 under controlled in vitro conditions. Furthermore, a noteworthy correlation was discerned between the presence of these neutralizing antibodies and critical clinical parameters, including C-reactive protein (CRP) levels, D-dimer levels, and lymphocyte counts.

CONCLUSION

The presence of type I IFN-neutralizing antibodies is a pervasive risk factor for severe/critical COVID-19 in the Chinese population.

Physical Activity, Sleeping Problems, Weight, Feelings of Social Isolation, and Quality of Life of Older Adults After Coronavirus Infection: A Longitudinal Cohort Study

BACKGROUND

There is debate as to whether a coronavirus infection (SARS-CoV-2) affects older adults' physical activity, sleeping problems, weight, feelings of social isolation, and quality of life (QoL). We investigated differences in these outcomes between older adults with and without coronavirus infection over 180 days following infection.

METHODS

We included 6789 older adults (65+) from the Lifelines COVID-19 cohort study who provided data between April 2020 and June 2021. Older adults (65+) with and without coronavirus infection were matched on sex, age, education, living situation, body mass index, smoking status, vulnerable health, time of infection, and precoronavirus health outcome. Weighted linear mixed models, adjusted for strictness of governmental policy measures, were used to compare health outcomes after infection between groups.

RESULTS

In total, 309 participants were tested positive for coronavirus. Eight days after infection, older adults with a coronavirus infection engaged in less physical activity, had more sleeping problems, weighed less, felt more socially isolated, and had a lower QoL than those without an infection. Differences in weight, feelings of social isolation, and QoL were absent after 90 days. However, differences in physical activity were still present at 90 days following infection and sleeping problems were present at 180 days.

CONCLUSION

Our findings found negative associations of coronavirus infection with all the examined outcomes, which for physical activity persisted for 90 days and sleeping problems for 180 days. Magnitudes of estimated effects on physical activity and sleeping problems remain uncertain.

Does Western or Chinese Zodiac Sign Predict COVID Infections and Death?

INTRODUCTION

Humans have been fascinated by and studying the sky since the beginning of time. Beliefs in Chinese and Western astrology persist in modern society and have gained increasing interest in light of the COVID-19 pandemic. Zodiac signs are typified by certain qualities, for example, obsessive-compulsive traits in Libras and Virgos or the highly social traits in Leos and Geminis. We investigate whether the various characteristics or personalities purported of assigned birth signs may alter the predisposition to COVID-19 infections or mortality.

METHODS

This is a retrospective, single-center cohort study of 2545 adult patients with confirmed COVID-19 infection presenting to the emergency room over a 14-month period (September 2020 to November 2021). COVID-19 infectivity was determined based on polymerase chain reaction (PCR) testing. Western and Chinese Zodiac signs were designated using date of birth. Both Zodiac signs were evaluated for risk of infection and death.

RESULTS

Mortality rates across the zodiac and astrology signs showed no statistical difference using the 12-sample test for equality of proportions. Coincidentally, the mean age for the deceased was 74.5 years, and it was 53.9 years for those alive, resulting in a difference of 20.6 years. A two-sample t-test confirms that the observed difference of 20.6 years of age between the two groups is statistically significant with a p-value <0.05. The coefficient of the predictor age is statistically significant. The odds ratio estimate of age is 1.06, with the corresponding 95% confidence interval (CI) being (1.048, 1.073). This means that the odds of dying increase by 6% for every additional year.

DISCUSSION

Astrology once held a significant impact on beliefs in medicine and continues in Chinese and Ayurvedic medicine. Our study utilized local data to determine if COVID-19 infection rates and mortality might have a relationship to astrological designations of Chinese and Western zodiac signs. Data analysis demonstrated that there was no statistical significance found between Western and Chinese Zodiac signs and mortality or infections. Similar to many previous studies, age can be a risk factor for mortality.

Excess Mortality Stratified by Age and Sex for Croatia and Croatian Counties during the 2020-2021 COVID-19 Pandemic

Excess mortality is often used to estimate the effect of a certain crisis on the population. It is defined as the number of deaths during a crisis exceeding the expected number based on historical trends. Here, we calculated excess mortality due to the COVID-19 pandemic for Croatia in the 2020-2021 period. The excess was calculated on the national and county level for different age and sex categories. In addition to the absolute number, the excess mortality was also expressed as a ratio of excess deaths to the predicted baseline and excess mortality rate. We showed that using both measures is necessary to avoid incorrect conclusions. The estimated excess mortality on the national level was 14,963, corresponding to an excess percentage of 14.3%. With respect to sex, there was a higher excess mortality rate for men compared to women. An exponential relationship was observed between age and the excess mortality rate.These trends wee representative of most counties as well, with large variations in the magnitude of the effect. However, there were also exceptions to the general rule. The reasons for these deviations were discussed in terms of between-county differences in demographic structure, population density and special events that took place during the pandemic.

Developmental Impacts of Epigenetics and Metabolism in COVID-19

Developmental biology is intricately regulated by epigenetics and metabolism but the mechanisms are not completely understood. The situation becomes even more complicated during diseases where all three phenomena are dysregulated. A salient example is COVID-19, where the death toll exceeded 6.96 million in 4 years, while the virus continues to mutate into different variants and infect people. Early evidence during the pandemic showed that the host's immune and inflammatory responses to COVID-19 (like the cytokine storm) impacted the host's metabolism, causing damage to the host's organs and overall physiology. The involvement of angiotensin-converting enzyme 2 (ACE2), the pivotal host receptor for the SARS-CoV-2 virus, was identified and linked to epigenetic abnormalities along with other contributing factors. Recently, studies have revealed stronger connections between epigenetics and metabolism in COVID-19 that impact development and accelerate aging. Patients manifest systemic toxicity, immune dysfunction and multi-organ failure. Single-cell multiomics and other state-of-the-art high-throughput studies are only just beginning to demonstrate the extent of dysregulation and damage. As epigenetics and metabolism directly impact development, there is a crucial need for research implementing cutting-edge technology, next-generation sequencing, bioinformatics analysis, the identification of biomarkers and clinical trials to help with prevention and therapeutic interventions against similar threats in the future.

Sociodemographic characteristics and COVID-19 testing rates: spatiotemporal patterns and impact of test accessibility in Sweden

BACKGROUND

Diagnostic testing is essential for disease surveillance and test-trace-isolate efforts. We aimed to investigate if residential area sociodemographic characteristics and test accessibility were associated with Coronavirus Disease 2019 (COVID-19) testing rates.

METHODS

We included 426 224 patient-initiated COVID-19 polymerase chain reaction tests from Uppsala County in Sweden from 24 June 2020 to 9 February 2022. Using Poisson regression analyses, we investigated if postal code area Care Need Index (CNI; median 1.0, IQR 0.8-1.4), a composite measure of sociodemographic factors used in Sweden to allocate primary healthcare resources, was associated with COVID-19 daily testing rates after adjustments for community transmission. We assessed if the distance to testing station influenced testing, and performed a difference-in-difference-analysis of a new testing station targeting a disadvantaged neighbourhood.

RESULTS

We observed that CNI, i.e. primary healthcare need, was negatively associated with COVID-19 testing rates in inhabitants 5-69 years. More pronounced differences were noted across younger age groups and in Uppsala City, with test rate ratios in children (5-14 years) ranging from 0.56 (95% CI 0.47-0.67) to 0.87 (95% CI 0.80-0.93) across three pandemic waves. Longer distance to the nearest testing station was linked to lower testing rates, e.g. every additional 10 km was associated with a 10-18% decrease in inhabitants 15-29 years in Uppsala County. The opening of the targeted testing station was associated with increased testing, including twice as high testing rates in individuals aged 70-105, supporting an intervention effect.

CONCLUSIONS

Ensuring accessible testing across all residential areas constitutes a promising tool to decrease inequalities in testing.

Higher COVID-19 pneumonia risk associated with anti-IFN-α than with anti-IFN-ω auto-Abs in children

We found that 19 (10.4%) of 183 unvaccinated children hospitalized for COVID-19 pneumonia had autoantibodies (auto-Abs) neutralizing type I IFNs (IFN-α2 in 10 patients: IFN-α2 only in three, IFN-α2 plus IFN-ω in five, and IFN-α2, IFN-ω plus IFN-β in two; IFN-ω only in nine patients). Seven children (3.8%) had Abs neutralizing at least 10 ng/ml of one IFN, whereas the other 12 (6.6%) had Abs neutralizing only 100 pg/ml. The auto-Abs neutralized both unglycosylated and glycosylated IFNs. We also detected auto-Abs neutralizing 100 pg/ml IFN-α2 in 4 of 2,267 uninfected children (0.2%) and auto-Abs neutralizing IFN-ω in 45 children (2%). The odds ratios (ORs) for life-threatening COVID-19 pneumonia were, therefore, higher for auto-Abs neutralizing IFN-α2 only (OR [95% CI] = 67.6 [5.7-9,196.6]) than for auto-Abs neutralizing IFN-ω only (OR [95% CI] = 2.6 [1.2-5.3]). ORs were also higher for auto-Abs neutralizing high concentrations (OR [95% CI] = 12.9 [4.6-35.9]) than for those neutralizing low concentrations (OR [95% CI] = 5.5 [3.1-9.6]) of IFN-ω and/or IFN-α2.