Socio-economic status and COVID-19-related cases and fatalities

Environmental health, COVID-19, and the syndemic: internal medicine facing the challenge

Internists are experts in complexity, and the COVID-19 pandemic is disclosing complex and unexpected interactions between communicable and non-communicable diseases, environmental factors, and socio-economic disparities. The medicine of complexity cannot be limited to facing comorbidities and to the clinical management of multifaceted diseases. Evidence indicates how climate change, pollution, demographic unbalance, and inequalities can affect the spreading and outcomes of COVID-19 in vulnerable communities. These elements cannot be neglected, and a wide view of public health aspects by a "one-health" approach is strongly and urgently recommended. According to World Health Organization, 35% of infectious diseases involving the lower respiratory tract depend on environmental factors, and infections from SARS-Cov-2 is not an exception. Furthermore, environmental pollution generates a large burden of non-communicable diseases and disabilities, increasing the individual vulnerability to COVID-19 and the chance for the resilience of large communities worldwide. In this field, the awareness of internists must increase, as privileged healthcare providers. They need to gain a comprehensive knowledge of elements characterizing COVID-19 as part of a syndemic. This is the case when pandemic events hit vulnerable populations suffering from the increasing burden of chronic diseases, disabilities, and social and economic inequalities. Mastering the interplay of such events requires a change in overall strategy, to adequately manage not only the SARS-CoV-2 infection but also the growing burden of non-communicable diseases by a "one health" approach. In this context, experts in internal medicine have the knowledge and skills to drive this change.

COVID-19 mortality and deprivation: pandemic, syndemic, and endemic health inequalities

COVID-19 has exacerbated endemic health inequalities resulting in a syndemic pandemic of higher mortality and morbidity rates among the most socially disadvantaged. We did a scoping review to identify and synthesise published evidence on geographical inequalities in COVID-19 mortality rates globally. We included peer-reviewed studies, from any country, written in English that showed any area-level (eg, neighbourhood, town, city, municipality, or region) inequalities in mortality by socioeconomic deprivation (ie, measured via indices of multiple deprivation: the percentage of people living in poverty or proxy factors including the Gini coefficient, employment rates, or housing tenure). 95 papers from five WHO global regions were included in the final synthesis. A large majority of the studies (n=86) found that COVID-19 mortality rates were higher in areas of socioeconomic disadvantage than in affluent areas. The subsequent discussion reflects on how the unequal nature of the pandemic has resulted from a syndemic of COVID-19 and endemic inequalities in chronic disease burden.

How Cumulative Statistics Can Mislead: The Temporal Dynamism of Sex Disparities in COVID-19 Mortality in New York State

Overall, men have died from COVID-19 at slightly higher rates than women. But cumulative estimates of mortality by sex may be misleading. We analyze New York State COVID-19 mortality by sex between March 2020 and August 2021, demonstrating that 72.7% of the total difference in the number of COVID-19 deaths between women and men was accrued in the first seven weeks of the pandemic. Thus, while the initial surge in COVID-19 mortality was characterized by stark sex disparities, this article shows that disparities were greatly attenuated in subsequent phases of the pandemic. Investigating changes over time could help illuminate how contextual factors contributed to the development of apparent sex disparities in COVID-19 outcomes.

Revisiting the COVID-19 fatality rate and altitude association through a comprehensive analysis

The emergence of COVID-19 virus has led to a pandemic with staggering morbidity and mortality. There is evidence showing that pre-existing conditions and environmental factors are associated with worse COVID-19 outcomes. Among these conditions, altitude is of particular interest. Altitude has been shown to influence the morbidity and mortality of multiple chronic pathologies such as cardiovascular disease, chronic obstructive pulmonary disease and lung cancer. COVID-19 fatality rate has been associated with as altitude as well, but findings are disputed. Therefore, we revisit this assessment with a comprehensive analysis of the relationship between COVID-19 fatality rates and altitude for the Mountain region of the United States while considering the effect of additional comorbidities and sociodemographic factors. A Generalized Additive Model (GAM) approach using one year of county data adjusted by population density was performed to evaluate associations within states and for the whole region. Our analysis revealed a consistent effect where COVID-19 case-fatality rate is decreased with higher altitude, even when controlling for pre-existing conditions and certain demographic variables. In summary, the work presented provides evidence that suggests that the protective effects of high altitude are likely to be influenced by physiologic factors but demographic trends that are associated with life at high altitude must also be considered.

Compliance with COVID-19 preventive measures among chronic disease patients in Wolaita and Dawuro zones, Southern Ethiopia: A proportional odds model

Introduction

So far, shreds of evidence have shown that COVID-19 related hospitalization, serious outcomes, and mortality were high among individuals with chronic medical conditions. However, strict compliance with basic public health measures such as hand washing with soap, social distancing, and wearing masks has been recommended and proven effective in preventing transmission of the infection. Therefore, this study aimed to determine the level of compliance with COVID-19 preventive measures and identify its predictors among patients with common chronic diseases in public hospitals of Southern Ethiopia by applying the proportional odds model.

Methods

A facility-based cross-sectional study was employed in public hospitals of Southern Ethiopia between February and March 2021. Using a systematic random sampling technique, 419 patients with common chronic diseases were recruited. Data were collected using an Open Data Kit and then submitted to the online server. The proportional odds model was employed, and the level of significance was declared at a p-value of less than 0.05.

Results

This study revealed that 55.2% (95%CI: 50.4%-59.9%) of the study participants had low compliance levels with COVID-19 preventive measures. The final proportional odds model identified that perceived susceptibility (AOR: 0.91, 95%CI: 0.84, 0.97), cues to action (AOR: 0.89, 95%CI: 0.85, 0.94), having access to drinking water piped into the dwelling (AOR: 0.52, 95%CI: 0.32, 0.84), having no access to any internet (AOR: 0.62, 95%CI: 0.42, 0.92), having no functional refrigerator (AOR: 2.17, 95%CI: 1.26, 3.74), and having poor knowledge (AOR: 1.42, 95%CI: 1.02, 1.98) were the independent predictors of low compliance level with COVID-19 preventive measures.

Conclusion

In the study area, more than half of the participants had low compliance levels with COVID-19 preventive measures. Thus, the identified factors should be considered when designing, planning, and implementing new interventional strategies, so as to improve the participants’ compliance level.

The association of obesity-related traits on COVID-19 severity and hospitalization is affected by socio-economic status: a multivariable Mendelian randomization study

BACKGROUND

Due to its large impact on human health, socio-economic status (SES) could at least partially influence the established association between obesity and coronavirus disease 2019 (COVID-19) severity. To estimate the independent effect of body size and SES on the clinical manifestations of COVID-19, we conducted a Mendelian randomization (MR) study.

METHODS

Applying two-sample MR approaches, we evaluated the effects of body mass index (BMI, n = 322 154), waist circumference (WC, n = 234 069), hip circumference (n = 213 019) and waist-hip ratio (n = 210 088) with respect to three COVID-19 outcomes: severe respiratory COVID-19 (cases = 8779, controls = 1 000 875), hospitalized COVID-19 (cases = 17 992, controls = 1 810 493) and COVID-19 infection (cases = 87 870, controls = 2 210 804). Applying a multivariable MR (MVMR) approach, we estimated the effect of these anthropometric traits on COVID-19 outcomes accounting for the effect of SES assessed as household income (n = 286 301).

RESULTS

BMI and WC were associated with severe respiratory COVID-19 [BMI: odds ratio (OR) = 1.51, CI = 1.24-1.84, P = 3.01e-05; WC: OR = 1.48, 95% CI = 1.15-1.91, P = 0.0019] and hospitalized COVID-19 (BMI: OR = 1.50, 95% CI = 1.32-1.72, P = 8.83e-10; WC: OR = 1.41, 95% CI = 1.20-1.67, P = 3.72e-05). Conversely, income was associated with lower odds of severe respiratory (OR = 0.70, 95% CI = 0.53-0.93, P = 0.015) and hospitalized COVID-19 (OR = 0.78, 95% CI = 0.66-0.92, P = 0.003). MVMR analyses showed that the effect of these obesity-related traits on increasing the odds of COVID-19 negative outcomes becomes null when accounting for income. Conversely, the association of income with lower odds of COVID-19 negative outcomes is not affected when including the anthropometric traits in the multivariable model.

CONCLUSION

Our findings indicate that SES contributes to the effect of obesity-related traits on COVID-19 severity and hospitalization.

Views from the trenches: California family physicians' challenges and resilience factors while providing patient care during the initial wave of COVID-19

This study examined challenges and factors promoting resilience among 20 California family physicians (FPs) during the first six months of the COVID-19 pandemic. A subset of academic, community, and resident FPs who responded to an online survey also participated in a semi-structured interview that explored concerns, moral distress, burnout, resource needs, support systems, coping strategies, and motivation to continue caring for patients. Thematic analysis was used to identify common themes in participant interviews. Interviewees demonstrated adaptability, resilience, and grit (i.e., commitment to completing a valued goal in the face of setbacks and adversity) despite challenges disrupting patient care, fears for family and self, and frustration due to the politicization of the pandemic. Factors promoting well-being and perseverance included professional and personal support, strong coping skills, and focusing on the meaning derived from practicing medicine. A service orientation that permeates family medicine philosophy and values motivated practitioners to continue to provide patient care while dealing with overwhelming personal and structural challenges. FPs drew strength from their internal coping skills, core family medicine values, and external support, notwithstanding demoralizing effects of mixed messages and politicization of the pandemic. FPs demonstrated resilience and grit in the face of challenges created by the COVID-19 pandemic. Ensuring adequate resources to promote a physically and psychologically healthy workforce while increasing access to care for all patients is crucial to prepare for the next healthcare crisis.

The COVID-19 pandemic as a catalyst for innovation: a regulatory framework to assess fit-for-purpose innovative approaches in clinical research

The COVID-19 pandemic has had a devastating impact on individuals and multiple aspects of our society including healthcare and clinical research. The silver lining is that the pandemic also served as a catalyst for wider adoption of innovative approaches in clinical research, notably the use of mobile or remote services, and digital technologies. Regulators, clinical study investigators, clinical study participants, sponsors, and other stakeholders collaborated to adopt measures that ensured safe participation in clinical studies whilst maintaining study integrity. In this article, we propose a regulatory framework for assessing fit-for-purpose innovative approaches in clinical research based on Roche/Genentech's experience during the COVID-19 pandemic with the aim to inform and encourage broader implementation of patient-centric and sustainable innovation in clinical research. Our goal is to contribute to ongoing discussions on introducing innovative approaches in clinical trials and eventually the development of globally harmonised guidelines.

Exploring Socioeconomic Status as a Global Determinant of COVID-19 Prevalence, Using Exploratory Data Analytic and Supervised Machine Learning Techniques: Algorithm Development and Validation Study

BACKGROUND

The COVID-19 pandemic represents the most unprecedented global challenge in recent times. As the global community attempts to manage the pandemic in the long term, it is pivotal to understand what factors drive prevalence rates and to predict the future trajectory of the virus.

OBJECTIVE

This study had 2 objectives. First, it tested the statistical relationship between socioeconomic status and COVID-19 prevalence. Second, it used machine learning techniques to predict cumulative COVID-19 cases in a multicountry sample of 182 countries. Taken together, these objectives will shed light on socioeconomic status as a global risk factor of the COVID-19 pandemic.

METHODS

This research used exploratory data analysis and supervised machine learning methods. Exploratory analysis included variable distribution, variable correlations, and outlier detection. Following this, the following 3 supervised regression techniques were applied: linear regression, random forest, and adaptive boosting (AdaBoost). Results were evaluated using k-fold cross-validation and subsequently compared to analyze algorithmic suitability. The analysis involved 2 models. First, the algorithms were trained to predict 2021 COVID-19 prevalence using only 2020 reported case data. Following this, socioeconomic indicators were added as features and the algorithms were trained again. The Human Development Index (HDI) metrics of life expectancy, mean years of schooling, expected years of schooling, and gross national income were used to approximate socioeconomic status.

RESULTS

All variables correlated positively with the 2021 COVID-19 prevalence, with R2 values ranging from 0.55 to 0.85. Using socioeconomic indicators, COVID-19 prevalence was predicted with a reasonable degree of accuracy. Using 2020 reported case rates as a lone predictor to predict 2021 prevalence rates, the average predictive accuracy of the algorithms was low (R2=0.543). When socioeconomic indicators were added alongside 2020 prevalence rates as features, the average predictive performance improved considerably (R2=0.721) and all error statistics decreased. Thus, adding socioeconomic indicators alongside 2020 reported case data optimized the prediction of COVID-19 prevalence to a considerable degree. Linear regression was the strongest learner with R2=0.693 on the first model and R2=0.763 on the second model, followed by random forest (0.481 and 0.722) and AdaBoost (0.454 and 0.679). Following this, the second model was retrained using a selection of additional COVID-19 risk factors (population density, median age, and vaccination uptake) instead of the HDI metrics. However, average accuracy dropped to 0.649, which highlights the value of socioeconomic status as a predictor of COVID-19 cases in the chosen sample.

CONCLUSIONS

The results show that socioeconomic status is an important variable to consider in future epidemiological modeling, and highlights the reality of the COVID-19 pandemic as a social phenomenon and a health care phenomenon. This paper also puts forward new considerations about the application of statistical and machine learning techniques to understand and combat the COVID-19 pandemic.

Socio-economic determinants of SARS-CoV-2 infection: Results from a population-based cross-sectional serosurvey in Geneva, Switzerland

Background

SARS-CoV-2 infection and its health consequences have disproportionally affected disadvantaged socio-economic groups globally. This study aimed to analyze the association between socio-economic conditions and having developed antibodies for-SARS-CoV-2 in a population-based sample in the canton of Geneva, Switzerland.

Methods

Data was obtained from a population-based serosurvey of adults in Geneva and their household members, between November and December, 2020, toward the end of the second pandemic wave in the canton. Participants were tested for antibodies for-SARS-CoV-2. Socio-economic conditions representing different dimensions were self-reported. Mixed effects logistic regressions were conducted for each predictor to test its association with seropositive status as the main outcome.

Results

Two thousand eight hundred and eighty-nine adults completed the study questionnaire and were included in the final analysis. Retired participants and those living in suburban areas had lower odds of a seropositive result when compared to employed participants (OR: 0.42, 95% CI: 0.20-0.87) and those living in urban areas (OR: 0.67, 95% CI: 0.46-0.97), respectively. People facing financial hardship for less than a year had higher odds of a seropositive result compared to those who had never faced them (OR: 2.23, 95% CI: 1.01-4.95). Educational level, occupational position, and household income were not associated with being seropositive, nor were ethnicity or country of birth.

Discussion

While conventional measures of socio-economic position did not seem to be related to the risk of being infected in this sample, this study sheds lights on the importance of examining the broader social determinants of health when evaluating the differential impact of the pandemic within the population.

Community distress as a predictor of early hernia recurrence for older adults undergoing ventral hernia repair (VHR)

Background

Social cohesion and neighborhood support have been linked to improved health in a variety of fields, but is not well-studied among the elderly population. This is particularly evident in surgical populations. Therefore, this study sought to assess the potential role of community distress in predicting early hernia recurrence among older adults.

Methods

The Abdominal Core Health Quality Collaborative (ACHQC) was used to identify patients aged 65 or older undergoing elective ventral hernia repair with zip code data available. Patients were linked to the Distressed Communities Index (DCI), which is a national database that assigns a score of 0–100 to each zip code based on 7 measures of neighborhood prosperity. Quintiles were used to compare groups: prosperous (0–20), comfortable (21–40), mid-tier (41–60), at-risk (61–80), and distressed (81–100). Distressed (0–20), at-risk (21–40), mid-tier (41–60), comfortable (61–80), and prosperous (81–100). Time to recurrence for neighborhood distress quintiles was examined using a Cox proportional hazards model.

Results

In total, 9819 patients were included in the study, including 3056 (31.1%) prosperous, 2307 (23.5%) comfortable, 1795 (18.2%) mid-tier, 1390 (14.2%) at-risk, and 1271 (12.9%) distressed. Distressed communities had lower mean age and greater proportion of racial minorities (p < 0.001). Open repairs were significantly more common among the distressed group (66.7%), as were all comorbidities (p < 0.001). Recurrence-free survival was shorter for distressed communities compared to prosperous after adjusting for baseline characteristics (HR 1.3, 95% CI 1.07–1.67, p = 0.01). Mean time to recurrence was lowest for patients living in distressed communities, indicating the worst recurrence rates, while mean time to recurrence was greatest for those in prosperous zip codes (p < 0.001).

Conclusion

Older VHR patients presenting from distressed zip codes, as identified by the Distressed Communities Index, experience hernia recurrence significantly sooner as compared to patients from prosperous zip codes. This study may provide evidence of the role of neighborhood and environmental factors in caring for older patients following VHR.

Graphical abstract

Syndemic aspects between COVID-19 pandemic and social inequalities

Although the coronavirus disease 2019 (COVID-19) pandemic has reached all over the world population, it has demonstrated a heterogeneous impact on different populations. The most vulnerable communities which coexist daily with the social inequalities like low access to hygiene and personal protection products, crowded residences, and higher levels of chronic diseases have a higher risk of contact and the spread of infection, beyond unfavorable clinical outcomes. The elevation of the risk of infection exposure can be related to gender due to the presence of a larger contingent of women in essential services, as well as frontline and cleaning professionals who regardless of gender have the greatest exposure to the virus. Such exposures can contribute to the development of fear of contaminating themselves or their family members associated also with the work stress, both of which are related to the emergence of mental disturbances in these populations. Furthermore, conditions of unsanitary living and low socioeconomic status, populations at war, pre-existing social barriers, and ethnicity have contributed to more impact of the pandemic both in the exposure to the virus and access to health services, COVID-19 management, and management of other pathologies. At the same time, factors such as the closing of non-essential services, the loss of jobs, and the increase in household spending aggravated the social vulnerabilities and impacted the family economy. Lastly, the COVID-19 pandemic contributed still more to the impact on women's health since it propitiated a favorable environment for increasing domestic violence rates, through the segregation of women from social life, and increasing the time of the victims with their aggressors.

Does Influenza Vaccination Reduce the Risk of Contracting COVID-19?

The concurrent timing of the COVID-19 pandemic and the seasonal occurrence of influenza, makes it especially important to analyze the possible effect of the influenza vaccine on the risk of contracting COVID-19, or in reducing the complications caused by both diseases, especially in vulnerable populations. There is very little scientific information on the possible protective role of the influenza vaccine against the risk of contracting COVID-19, particularly in groups at high-risk of influenza complications. Reducing the risk of contracting COVID-19 in high-risk patients (those with a higher risk of infection, complications, and death) is essential to improve public well-being and to reduce hospital pressure and the collapse of primary health centers. Apart from overlapping in time, COVID-19 and flu share common aspects of transmission, so that measures to protect against flu might be effective in reducing the risk of contracting COVID-19. In this study, we conclude that the risk of contracting COVID-19 is reduced if patients are vaccinated against flu, but the reduction is small (0.22%) and therefore not clinically important. When this reduction is analysed based on the risk factor suffered by the patient, statistically significant differences have been obtained for patients with cardiovascular problems, diabetics, chronic lung and chronic kidney disease; in all four cases the reduction in the risk of contagion does not reach 1%. It is worth highlighting the behaviour that is completely different from the rest of the data for institutionalized patients. The data for these patients does not suggest a reduction in the risk of contagion for patients vaccinated against the flu, but rather the opposite, a significant increase of 6%. Socioeconomic conditions, as measured by the MEDEA deprivation index, explain increases in the risk of contracting COVID-19, and awareness campaigns should be increased to boost vaccination programs.

Movement under state and non-state authorities during COVID-19: Evidence from Lebanon

COVID-19 has presented governing authorities with challenging decisions that have required them to consider the tradeoffs between movement restriction and economic activity. We propose that non-state armed groups may make different decisions than state governments in response to these challenges. Drawing upon the case of Hezbollah in Lebanon, we investigate whether movement levels differed between areas with Hezbollah private governance in comparison to other areas of Lebanon. Using Google COVID-19 mobility data and a difference in differences model, we show that following the first COVID-related death in Lebanon, movement in districts with private Hezbollah governance decreased significantly less than in other districts. We present a number of potential reasons for this disparity, arguing that the most probable explanation is the relatively high level of economic assistance that Hezbollah provided to people living in areas under Hezbollah's authority, which led to comparatively lesser rates of movement decline.

In-hospital severe COVID-19 in a philanthropic tertiary hospital setting: is asthma a concern? A retrospective study

BACKGROUND

The frequency of coronavirus disease 2019 (COVID-19) cases among asthmatics has been reported to be reduced. However, the findings regarding the association between asthma and the risk of severe COVID-19 have been divergent.

OBJECTIVE

To investigate whether asthma is associated with a reduced risk of development of severe COVID-19.

DESIGN AND SETTING

Retrospective analysis on COVID-19 surveillance databases at two tertiary-level hospitals in São Paulo, Brazil.

METHODS

The medical records of patients hospitalized due to COVID-19 between March and August 2020 were reviewed in accordance with the clinical, laboratorial, radiological and epidemiological criteria for COVID-19, and for comorbidities.

RESULTS

Among the adult patients included (> 18 years of age) there were 52 asthmatics and 1,318 non-asthmatics. Their median ages and interquartile ranges (IQR) were, respectively, 54 (41-69) and 60 (44-72) years. At least one comorbidity was seen in 73% of asthmatics and 56% of the non-asthmatics. Among the asthmatics, most presented mild asthma (92%) and the prevalence of chronic obstructive pulmonary disease (COPD) was high (27%). The asthmatics presented an unadjusted odds ratio (OR) for severe COVID-19 of 0.89 (95% confidence interval, CI 0.5-1.56); and OR 0.88 (95% CI 0.5 -1.68) after multivariable adjustment. Age > 60 years, male sex, hypertension, diabetes, cancer and homelessness were covariates associated with increased odds for severe COVID-19. Kaplan-Meier estimated survival over hospitalization of up to 30 days did not differ between the groups (log-rank P = 0.09).

CONCLUSIONS

The association between asthma and decreased risk of severe COVID-19 or increased survival was statistically non-significant.

Identifying the High-Risk Population for COVID-19 Transmission in Hong Kong Leveraging Explainable Machine Learning

The worldwide spread of COVID-19 has caused significant damage to people’s health and economics. Many works have leveraged machine learning models to facilitate the control and treatment of COVID-19. However, most of them focus on clinical medicine and few on understanding the spatial dynamics of the high-risk population for transmission of COVID-19 in real-world settings. This study aims to investigate the association between population features and COVID-19 transmission risk in Hong Kong, which can help guide the allocation of medical resources and the implementation of preventative measures to control the spread of the pandemic. First, we built machine learning models to predict the number of COVID-19 cases based on the population features of different tertiary planning units (TPUs). Then, we analyzed the distribution of cases and the prediction results to find specific characteristics of TPUs leading to large-scale outbreaks of COVID-19. We further evaluated the importance and influence of various population features on the prediction results using SHAP values to identify indicators for high-risk populations for COVID-19 transmission. The evaluation of COVID-19 cases and the TPU dataset in Hong Kong shows the effectiveness of the proposed methods. The top three most important indicators are identified as people in accommodation and food services, low income, and high population density.

A multiscale integrated analysis of the COVID-19 restrictions: The energy metabolism of UK and the related socio-economic changes

The COVID-19 pandemic and the related lockdown restrictions have imposed a wide range of impacts that need to be analysed based on the specific characteristics of countries. By comparing socio-economic and energy data for the four quarters of 2020 to the same period of 2019, the MuSIASEM approach is used, for the first time, to investigate the energy metabolism of UK during a period of economic downturn. Results show that the commercial and the public administration activities have been able to achieve energy efficiency increases, and the residential sector has accounted for energy-related economies of scale. The industrial and the other activity sectors, on the contrary, have raised the energy intensity of production. Comparted to time series data, scenarios, and modelling exercises, the MuSIASEM approach integrates a wide range of intensive and extensive variables across different scales of analysis and investigate how specific socio-economic and energy structures have reacted to the COVID-19 crisis. The methodology can be easily replicated for other case studies and results can support the design of recovery and sustainable transition strategies.

COVID-19 Post-Exposure Evaluation (COPE) Study: Assessing the Role of Socio-Economic Factors in Household SARS-CoV-2 Transmission within Campania Region (Southern Italy)

Campania is the sixth poorest region of Italy, and it is the region with the highest income inequality. The secondary attack rates of SARS-CoV-2 among households are found to be substantially heterogeneous among published studies and are influenced by socio-economic factors. We conducted a retrospective study to describe the role of socio-economic factors in the household transmission of SARS-CoV-2 among patients living in Campania Region and referring to "Federico II" Hospital. We interviewed 413 subjects followed-up for COVID-19 between the 8 March 2020 and the 24 May 2021 with the aim to collect demographic, clinical, economic, and social data regarding their household and the index cases. The variables associated with SARS-CoV-2 attack rate higher than 50% among households were higher age (p = 0.023) and higher Charlson Comorbidity Index of the index case (p = 0.023) and, for household characteristics, higher number of families per house (p = 0.02), location of the houses in Naples' suburbs (Chi² = 5.3, p = 0.02) and in Caserta City area (Chi² = 4, p = 0.04), and renting the house compared to owning it (Chi² = 5.83, p = 0.01). This study confirms the finding described by other authors that household transmission of SARS-CoV-2 is correlated with the income inequality of the analyzed geographical area as well as with the indicators of health and economic wealth of the families, and this correlation also applies to the Campania Region.

Achieving the Sustainable Development Goals in the post-pandemic era

The COVID-19 pandemic continues to pose substantial challenges to achieving the Sustainable Development Goals (SDGs). Exploring systematic SDG strategies is urgently needed to aid recovery from the pandemic and reinvigorate global SDG actions. Based on available data and comprehensive analysis of the literature, this paper highlights ongoing challenges facing the SDGs, identifies the effects of COVID-19 on SDG progress, and proposes a systematic framework for promoting the achievement of SDGs in the post-pandemic era. Progress towards attaining the SDGs was already lagging behind even before the onset of the COVID-19 pandemic. Inequitable distribution of food-energy-water resources and environmental crises clearly threaten SDG implementation. Evidently, there are gaps between the vision for SDG realization and actual capacity that constrain national efforts. The turbulent geopolitical environment, spatial inequities, and trade-offs limit the effectiveness of SDG implementation. The global public health crisis and socio-economic downturn under COVID-19 have further impeded progress toward attaining the SDGs. Not only has the pandemic delayed SDG advancement in general, but it has also amplified spatial imbalances in achieving progress, undermined connectivity, and accentuated anti-globalization sentiment under lockdowns and geopolitical conflicts. Nevertheless, positive developments in technology and improvement in environmental conditions have also occurred. In reflecting on the overall situation globally, it is recommended that post-pandemic SDG actions adopt a "Classification-Coordination-Collaboration" framework. Classification facilitates both identification of the current development status and the urgency of SDG achievement aligned with national conditions. Coordination promotes domestic/international and inter-departmental synergy for short-term recovery as well as long-term development. Cooperation is key to strengthening economic exchanges, promoting technological innovation, and building a global culture of sustainable development that is essential if the endeavor of achieving the SDGs is to be successful. Systematic actions are urgently needed to get the SDG process back on track.

Impact of COVID-19-Related Lockdown Measures on Economic and Social Outcomes in Lithuania

The current world crisis caused by the COVID-19 pandemic has transformed into an economic crisis, becoming a problem and a challenge not only for individual national economies but also for the world economy as a whole. The first global lockdown, which started in mid-March of 2020 and lasted for three months in Lithuania, affected the movement and behavior of the population, and had an impact on the economy. This research presents results on the impact of lockdown measures on the economy using nonparametric methods in combination with parametric ones. The impact on unemployment and salary inequality was estimated. To assess the impact of lockdown on the labor market, the analysis of the dynamics of the unemployment rate was performed using the results of the cluster analysis. The Lithuanian data were analyzed in the context of other countries, where the dynamics of the spread of the virus were similar. The salary inequality was measured by the Gini coefficient and analyzed using change point analysis, functional data analysis and linear regression. The study found that the greatest impact of the closure restrictions on socio-economic indicators was recorded in 2020, with a lower impact in 2021. The proposed multi-step approach could be applied to other countries and to various types of shocks and interventions, not only the COVID-19 crisis, in order to avoid adverse economic and social outcomes.

Driving, Social Distancing, Protective, and Coping Behaviors of Older Adults Before and During COVID-19

A thorough understanding of individual characteristics of older adults during the COVID-19 pandemic is critical for managing the ongoing pandemic course and planning for the future pandemics. Here, we explore the impact of the COVID-19 pandemic on driving, social distancing, protective, and coping behaviors of older adults. This study reports data on participants aged above 65 whose driving behaviors are being monitored using Global Positioning System (GPS) devices. Participants completed a COVID-19 survey in May 2020. We found that older adults decreased their number of days driving, number of trips per day, as well as average driving speed, and had fewer speeding incidents following COVID-19 onset. We also show that female and African American older adults engaged in more positive coping and cleaning behaviors, and had greater decreases in the number of days driving during the pandemic. The findings highlight the importance of considering older adults' individual characteristics for an equitable response to the COVID-19 pandemic.

Estimating the time-varying reproduction number for COVID-19 in South Africa during the first four waves using multiple measures of incidence for public and private sectors across four waves

Objectives

We aimed to quantify transmission trends in South Africa during the first four waves of the COVID-19 pandemic using estimates of the time-varying reproduction number (R) and to compare the robustness of R estimates based on three different data sources and using data from public and private sector service providers.

Methods

We estimated R from March 2020 through April 2022, nationally and by province, based on time series of rt-PCR-confirmed cases, hospitalizations, and hospital-associated deaths, using a method which models daily incidence as a weighted sum of past incidence. We also estimated R separately using public and private sector data.

Results

Nationally, the maximum case-based R following the introduction of lockdown measures was 1.55 (CI: 1.43-1.66), 1.56 (CI: 1.47-1.64), 1.46 (CI: 1.38-1.53) and 3.33 (CI: 2.84-3.97) during the first (Wuhan-Hu), second (Beta), third (Delta), and fourth (Omicron) waves respectively. Estimates based on the three data sources (cases, hospitalisations, deaths) were generally similar during the first three waves but case-based estimates were higher during the fourth wave. Public and private sector R estimates were generally similar except during the initial lockdowns and in case-based estimates during the fourth wave.

Discussion

Agreement between R estimates using different data sources during the first three waves suggests that data from any of these sources could be used in the early stages of a future pandemic. High R estimates for Omicron relative to earlier waves is interesting given a high level of exposure pre-Omicron. The agreement between public and private sector R estimates highlights the fact that clients of the public and private sectors did not experience two separate epidemics, except perhaps to a limited extent during the strictest lockdowns in the first wave.

Urban-Rural Differences in Health Care Utilization and COVID-19 Outcomes in Patients With Type 2 Diabetes

Introduction

Two studies in Pennsylvania aimed to determine whether community type and community socioeconomic deprivation (CSD) 1) modified associations between type 2 diabetes (hereinafter, diabetes) and COVID-19 hospitalization outcomes, and 2) influenced health care utilization among individuals with diabetes during the COVID-19 pandemic.

Methods

The hospitalization study evaluated a retrospective cohort of patients hospitalized with COVID-19 through 2020 for COVID-19 outcomes: death, intensive care unit (ICU) admission, mechanical ventilation, elevated D-dimer, and elevated troponin level. We used adjusted logistic regression models, adding interaction terms to evaluate effect modification by community type (township, borough, or city census tract) and CSD. The utilization study included patients with diabetes and a clinical encounter between 2017 and 2020. Autoregressive integrated moving average time-series models evaluated changes in weekly rates of emergency department and outpatient visits, hemoglobin A_1c (HbA_1c) laboratory tests, and antihyperglycemic medication orders from 2018 to 2020.

Results

In the hospitalization study, of 2,751 patients hospitalized for COVID-19, 1,020 had diabetes, which was associated with ICU admission and elevated troponin. Associations did not differ by community type or CSD. In the utilization study, among 93,401 patients with diabetes, utilization measures decreased in March 2020. Utilization increased in July, and then began to stabilize or decline through the end of 2020. Changes in HbA_1c tests and medication order trends during the pandemic differed by community type and CSD.

Conclusion

Diabetes was associated with selected outcomes among individuals hospitalized for COVID-19, but these did not differ by community features. Utilization trajectories among individuals with diabetes during the pandemic were influenced by community type and CSD and could be used to identify individuals at risk of gaps in diabetes care.

Health-Related Quality of Life of Moroccan COVID-19 Survivors: A Case-Control Study

Background: Research on COVID-19 has mostly focused on transmission, mortality and morbidity associated with the virus. However, less attention has been given to its impact on health-related quality of life (HRQoL) of patients with COVID-19. Therefore, this study aimed to determine the demographic and clinical risk factors associated with COVID-19 and evaluate its impact on the HRQoL of COVID-19 survivors. Methods: A case-control study was carried out between September 2021 and March 2022 on 1105 participants. A total of 354 were COVID-19 survivors and 751 were the control group. The HRQoL was assessed using both EQ-5D-5L and SF-6D generic instruments. Results: The average age of all participants was 56.17 ± 15.46. Older age, urban area, tobacco use, presence of chronic diseases especially type 1 diabetes, kidney and cardiovascular diseases were significantly associated with COVID-19. The COVID-19 survivors had significantly lower HRQoL (EQ-VAS = 50.89) compared to the control group (EQ-VAS = 63.36) (p-value < 0.0001). Pain/ discomfort and anxiety/depression were the most negatively affected by COVID-19 (p-value < 0.0001). Conclusions: The findings from this study could help healthcare professionals and policy makers to better understand the HRQoL sequelae among the COVID-19 survivors and contribute to develop tailored interventions.

COVID-19 disease and autoimmune disorders: A mutual pathway

Coronavirus disease 2019 (COVID-19) is a real challenge for humanity with high morbidity and mortality. Despite being primarily a respiratory illness, COVID-19 can affect nearly every human body tissue, causing many diseases. After viral infection, the immune system can recognize the viral antigens presented by the immune cells. This immune response is usually controlled and terminated once the infection is aborted. Nevertheless, in some patients, the immune reaction becomes out of control with the development of autoimmune diseases. Several human tissue antigens showed a strong response with antibodies directed against many severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteins, such as SARS-CoV-2 S, N, and autoimmune target proteins. The immunogenic effects of SARS-CoV-2 are due to the sizeable viral RNA molecules with interrupted transcription increasing the pool of epitopes with increased chances of molecular mimicry and interaction with the host immune system, the overlap between some viral and human peptides, the viral induced-tissue damage, and the robust and complex binding between sACE-2 and SARS-CoV-2 S protein. Consequently, COVID-19 and its vaccine may trigger the development of many autoimmune diseases in a predisposed patient. This review discusses the mutual relation between COVID-19 and autoimmune diseases, their interactive effects on each other, the role of the COVID-19 vaccine in triggering autoimmune diseases, the factors affecting the severity of COVID-19 in patients suffering from autoimmune diseases, and the different ways to minimize the risk of COVID-19 in patients with autoimmune diseases.

Asseri A, Binyamin SS, Al-Rabia MW. Enhanced Gravitational Search Optimization with Hybrid Deep Learning Model for COVID-19 Diagnosis on Epidemiology Data

Effective screening provides efficient and quick diagnoses of COVID-19 and could alleviate related problems in the health care system. A prediction model that combines multiple features to assess contamination risks was established in the hope of supporting healthcare workers worldwide in triaging patients, particularly in situations with limited health care resources. Furthermore, a lack of diagnosis kits and asymptomatic cases can lead to missed or delayed diagnoses, exposing visitors, medical staff, and patients to 2019-nCoV contamination. Non-clinical techniques including data mining, expert systems, machine learning, and other artificial intelligence technologies have a crucial role to play in containment and diagnosis in the COVID-19 outbreak. This study developed Enhanced Gravitational Search Optimization with a Hybrid Deep Learning Model (EGSO-HDLM) for COVID-19 diagnoses using epidemiology data. The major aim of designing the EGSO-HDLM model was the identification and classification of COVID-19 using epidemiology data. In order to examine the epidemiology data, the EGSO-HDLM model employed a hybrid convolutional neural network with a gated recurrent unit based fusion (HCNN-GRUF) model. In addition, the hyperparameter optimization of the HCNN-GRUF model was improved by the use of the EGSO algorithm, which was derived by including the concepts of cat map and the traditional GSO algorithm. The design of the EGSO algorithm helps in reducing the ergodic problem, avoiding premature convergence, and enhancing algorithm efficiency. To demonstrate the better performance of the EGSO-HDLM model, experimental validation on a benchmark dataset was performed. The simulation results ensured the enhanced performance of the EGSO-HDLM model over recent approaches.

Epidemiologic Profile of Severe Acute Respiratory Infection in Brazil During the COVID-19 Pandemic: An Epidemiological Study

Background

The COVID-19 is a significant public health issue, and monitoring confirmed cases and deaths is an essential epidemiologic tool. We evaluated the features in Brazilian hospitalized patients due to severe acute respiratory infection (SARI) during the COVID-19 pandemic in Brazil. We grouped the patients into the following categories: Influenza virus infection (G1), other respiratory viruses' infection (G2), other known etiologic agents (G3), SARS-CoV-2 infection (patients with COVID-19, G4), and undefined etiological agent (G5).

Methods

We performed an epidemiological study using data from DataSUS (https://opendatasus.saude.gov.br/) from December 2019 to October 2021. The dataset included Brazilian hospitalized patients due to SARI. We considered the clinical evolution of the patients with SARI during the COVID-19 pandemic according to the SARI patient groups as the outcome. We performed the multivariate statistical analysis using logistic regression, and we adopted an Alpha error of 0.05.

Results

A total of 2,740,272 patients were hospitalized due to SARI in Brazil, being the São Paulo state responsible for most of the cases [802,367 (29.3%)]. Most of the patients were male (1,495,416; 54.6%), aged between 25 and 60 years (1,269,398; 46.3%), and were White (1,105,123; 49.8%). A total of 1,577,279 (68.3%) patients recovered from SARI, whereas 701,607 (30.4%) died due to SARI, and 30,551 (1.3%) did not have their deaths related to SARI. A major part of the patients was grouped in G4 (1,817,098; 66.3%) and G5 (896,207; 32.7%). The other groups account for &lt;1% of our sample [G1: 3,474 (0.1%), G2: 16,627 (0.6%), and G3: 6,866 (0.3%)]. The deaths related to SARI were more frequent in G4 (574,887; 34.7%); however, the deaths not related to SARI were more frequent among the patients categorized into the G3 (1,339; 21.3%) and G5 (25,829; 4.1%). In the multivariate analysis, the main predictors to classify the patients in the G5 when compared with G4 or G1-G4 were female sex, younger age, Black race, low educational level, rural place of residence, and the use of antiviral to treat the clinical signs. Furthermore, several features predict the risk of death by SARI, such as older age, race (Black, Indigenous, and multiracial background), low educational level, residence in a flu outbreak region, need for intensive care unit, and need for mechanical ventilatory support.

Conclusions

The possible COVID-19 underreporting (G5) might be associated with an enhanced mortality rate, more evident in distinct social groups. In addition, the patients' features are unequal between the patients' groups and can be used to determine the risk of possible COVID-19 underreporting in our population. Patients with a higher risk of death had a different epidemiological profile when compared with patients who recovered from SARI, like older age, Black, Indigenous, and multiracial background races, low educational level, residence in a flu outbreak region, need for intensive care unit and need for mechanical ventilatory support.

Medical avoidance among marginalized groups: the impact of the COVID-19 pandemic

Medical avoidance is common among U.S. adults, and may be emphasized among members of marginalized communities due to discrimination concerns. In the current study, we investigated whether this disparity in avoidance was maintained or exacerbated during the onset of the COVID-19 pandemic. We assessed the likelihood of avoiding medical care due to general-, discrimination-, and COVID-19-related concerns in an online sample (N = 471). As hypothesized, marginalized groups (i.e., non-White race, Latinx/e ethnicity, non-heterosexual sexual orientation, high BMI) endorsed more general- and discrimination-related medical avoidance than majoritized groups. However, marginalized groups were equally likely to seek COVID-19 treatment as majoritized groups. Implications for reducing medical avoidance among marginalized groups are discussed.

Association between area-level material deprivation and incidence of hospitalization among children with SARS-CoV-2 in Montreal

Background

Although sociodemographic factors have been linked with SARS-CoV-2 infection and hospitalizations in adults, there are little data on the association between sociodemographic characteristics and SARS-CoV-2-related hospitalization in children. The objective of this study was to determine the association between area-level material deprivation and incidence of hospitalization with SARS-CoV-2 among children.

Methods

We conducted a retrospective cohort study of all children (0 to 17 years of age) with a PCR-confirmed SARS-CoV-2 infection March 1, 2020 through May 31, 2021 at a tertiary-care paediatric hospital, in Montreal, Canada. Data were collected through chart review and included age, sex, and postal code, allowing linkage to dissemination area-level material deprivation, measured with the Pampalon Material Deprivation Index (PMDI) quintiles. We examined the association between PMDI quintiles and hospitalization using Poisson regression.

Results

During the study period, 964 children had a positive PCR-confirmed SARS-CoV-2 test and 124 were hospitalized. Children living in the most deprived quintile of PMDI represented 40.7% of hospitalizations. Incidence rate ratio of hospitalization for this group compared to the most privileged quintile was 2.42 (95%CI: 1.33; 4.41).

Conclusion

Children living in the most materially deprived areas had more than twice the rate of hospitalizations for COVID-19 than children living in most privileged areas. Special efforts should be deployed to protect children who live in disadvantaged areas, especially pending vaccination of younger children.

L’association entre la défavorisation matérielle par quartier et l’incidence d’hospitalisation chez les enfants infectés par le SRAS-CoV-2 à Montréal

Historique

Même si les facteurs sociodémographiques sont liés à l’infection par le SRAS-CoV-2 et aux hospitalisations chez les adultes, peu de données portent sur l’association entre ces caractéristiques et les hospitalisations attribuables au SRAS-CoV-2 chez les enfants. La présente étude visait à déterminer l’association entre la défavorisation matérielle par quartier et l’incidence d’hospitalisations à cause du SRAS-CoV-2 chez les enfants.

Méthodologie

Les chercheurs ont réalisé une étude de cohorte rétrospective de tous les enfants (de 0 à 17 ans) atteints d’une infection par le SRAS-CoV-2 confirmée par un test d’amplification en chaîne par polymérase après transcription inverse (PCR) entre le 1^er mars et le 31 mai 2021 dans un hôpital pédiatrique de soins tertiaires de Montréal, au Canada. Ils ont colligé les données par examen des dossiers et ont inclus l’âge, le sexe et les codes postaux, afin de pouvoir lier la défavorisation matérielle à l’échelle de l’aire de diffusion, mesurée au moyen des quintiles de l’indice de défavorisation matérielle de Pampalon. Ils ont examiné l’association entre les quintiles de cet indice et les hospitalisations à l’aide de la régression de Poisson.

Résultats

Pendant la période de l’étude, 964 enfants ont reçu un résultat positif au SRAS-CoV-2 confirmé par un test PCR, et 124 d’entre eux ont été hospitalisés. Au total, 40,7 % des enfants hospitalisés habitaient dans le quintile le plus défavorisé d’après l’indice de défavorisation matérielle de Pampalon. Le rapport du taux d’incidence des hospitalisations dans ce groupe était de 2,42 (intervalle de confiance à 95 % : 1,33; 4,41) par rapport au quintile le plus privilégié.

Conclusion

Plus du double des enfants qui habitaient dans les quartiers les plus défavorisés sur le plan matériel étaient hospitalisés à cause de la COVID-19 par rapport à ceux qui habitaient dans les quartiers les plus privilégiés. Il faudrait déployer des efforts particuliers pour protéger les enfants qui habitent dans des quartiers défavorisés, particulièrement dans l’attente de la vaccination des plus jeunes.

Demographic Predictors of Mothers' Willingness to Vaccinate Young Children Against COVID-19, Get Tested and Isolate: A Cross-Sectional Survey Before and During the Greater Sydney Lockdown 2021, Australia

Background and Objectives

Having a COVID-19 vaccination, getting tested, and self-isolating if symptomatic are some of the most important mitigation strategies for preventing the spread of COVID-19. This study aimed to investigate whether demographic factors are associated with mothers' willingness to vaccinate their 4-year-old children against COVID-19 if a suitable vaccine becomes available or to get tested and self-isolate if they themselves have COVID-19 symptoms and whether the willingness could be influenced by the Greater Sydney lockdown 2021.

Methods

A cross-sectional telephone survey was conducted between 24th February and 26th October 2021. Questions from the NSW Adult Population Health Survey and from previously published studies were used to assess family demographics, mothers' willingness to vaccinate their young children, and willingness to get tested and self-isolate if symptomatic. The survey involved 604 mothers of children aged 4 years who participated in an existing trial in Sydney, Australia.

Results

Mothers were more willing to vaccinate their children when the child's father had a tertiary education or higher, with an adjusted odds ratio (AOR) of 2.60 (95% CI 1.67–4.04). Mothers who were older than 30 years or who completed the survey during the lockdown were more willing to get tested if symptomatic, with AOR 2.50 (95% CI 1.17–5.36) and AOR 3.36 (95% CI 1.41–8.02), respectively. Mothers who were married or had de-facto partners were more willing to self-isolate if symptomatic [AOR 17.15 (95% CI 3.56–82.65)].

Conclusion

Fathers' educational level, mothers' age, and marital status were associated with mothers' willingness to vaccinate their young children if a suitable vaccine were available, to get tested, and self-isolate if symptomatic respectively. The promotion of mitigation strategies for tackling the COVID-19 pandemic needs to take into account specific family demographics.

COVID-19 double jeopardy: the overwhelming impact of the social determinants of health

Background

The COVID-19 pandemic has strained healthcare systems by creating a tragic imbalance between needs and resources. Governments and healthcare organizations have adapted to this pronounced scarcity by applying allocation guidelines to facilitate life-or-death decision-making, reduce bias, and save as many lives as possible. However, we argue that in societies beset by longstanding inequities, these approaches fall short as mortality patterns for historically discriminated against communities have been disturbingly higher than in the general population.

Methods

We review attack and fatality rates; survey allocation protocols designed to deal with the extreme scarcity characteristic of the earliest phases of the pandemic; and highlight the larger ethical perspectives (Utilitarianism, non-Utilitarian Rawlsian justice) that might justify such allocation practices.

Results

The COVID-19 pandemic has dramatically amplified the dire effects of disparities with respect to the social determinants of health. Patients in historically marginalized groups not only have significantly poorer health prospects but also lower prospects of accessing high quality medical care and benefitting from it even when available. Thus, mortality among minority groups has ranged from 1.9 to 2.4 times greater than the rest of the population. Standard allocation schemas, that prioritize those most likely to benefit, perpetuate and may even exacerbate preexisting systemic injustices.

Conclusions

To be better prepared for the inevitable next pandemic, we must urgently begin the monumental project of addressing and reforming the structural inequities in US society that account for the strikingly disparate mortality rates we have witnessed over the course of the current pandemic.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12939-022-01629-0.

Dramatic increases in knowledge, attitudes and practices of COVID-19 observed among low-income households in the Philippines: A repeated cross-sectional study in 2020

Background

The COVID-19 pandemic has severely impacted populations globally, and knowledge, attitudes and practices (KAPs) surrounding the virus have necessarily evolved. This study was conducted in partnership with International Care Ministries (ICM), a Philippine-based non-governmental organization that runs the “Transform” poverty alleviation program. The main objective of this study was to describe the changes in COVID-19 KAPs among households experiencing extreme poverty in the Philippines over an 8-month period.

Methods

A KAP questionnaire was integrated into the household survey collected as part of ICM’s regular monitoring and evaluation of “Transform”. Data collection for the first survey was conducted between February 20 and March 13, 2020, and the second survey was conducted between November 12 and December 12, 2020. Frequencies and proportions were calculated to describe the respondents’ responses and the Kruskal-Wallis test was used to assess if there were significant differences in KAP identification between the two time points.

Results

We observed a distinct increase across all KAP domains. Over 90% of study participants were able to correctly identify COVID-19 transmission modes and preventive measures, and an even higher percentage reported adopting these measures. However, the intention to seek care from public hospitals for COVID-19 symptoms dropped from 43.6% to 28.4%, while reports of self-treatment using stored medicines or antibiotics increased. Trust in community members and local health authorities was correlated with higher knowledge and practice scores.

Conclusions

Our study results reflect the extraordinary speed of information dissemination and behaviour change globally over the course of the pandemic, but they also highlight the changes in KAP that show the additional challenges faced by populations experiencing poverty in the Philippines. Prioritization of reducing inequities in the implementation and adoption of the evolving public health measures will be integral as the pandemic continues.

Severe Acute Respiratory Syndrome Coronavirus 2 Antibody Seroprevalence in Decedents Undergoing Forensic Postmortem Examination: Feasibility for Real-Time Pandemic Surveillance

Background

Population-based seroprevalence studies offer comprehensive characterization of coronavirus disease 2019 (COVID-19) spread, but barriers exist and marginalized populations may not be captured. We assessed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody seroprevalence among decedents in Maryland over 6 months in 2020.

Methods

Data were collected on decedents undergoing forensic postmortem examination in Maryland from 24 May through 30 November 2020 from whom a blood specimen could be collected. Those with available blood specimens were tested with the CoronaCHEK lateral flow antibody assay. We assessed monthly seroprevalence compared to the statewide estimated number of cases and proportion of positive test results (testing positivity). We used Poisson regression with robust variance to estimate adjusted prevalence ratios (aPRs) with 95% confidence intervals (CIs) for associations of demographic characteristics, homelessness, and manner of death with SARS-CoV-2 antibodies.

Results

Among 1906 decedents, 305 (16%) were positive for SARS-CoV-2 antibodies. Monthly seroprevalence increased from 11% to 22% over time and was consistently higher than state-level estimates of testing positivity. Hispanic ethnicity was associated with 2- to 3.2-fold higher seropositivity (P < .05) irrespective of sex. Deaths due to motor vehicle crash were associated with 62% increased seropositivity (aPR, 1.62 [95% CI, 1.15-2.28]) vs natural manner of death. Though seroprevalence was lower in decedents of illicit drug overdose vs nonoverdose in early months, this shifted, and seroprevalence was comparable by November 2020.

Conclusions

Decedents undergoing forensic postmortem examination, especially those dying due to motor vehicle trauma, may be a sentinel population for COVID-19 spread in the general population and merits exploration in other states/regions.

A joint hierarchical model for the number of cases and deaths due to COVID-19 across the boroughs of Montreal

As of July 2021, Montreal is the epicentre of the COVID-19 pandemic in Canada with highest number of deaths. We aim to investigate the spatial distribution of the number of cases and deaths due to COVID-19 across the boroughs of Montreal. To this end, we propose that the cumulative numbers of cases and deaths in the 33 boroughs of Montreal are modelled through a bivariate hierarchical Bayesian model using Poisson distributions. The Poisson means are decomposed in the log scale as the sums of fixed effects and latent effects. The areal median age, the educational level, and the number of beds in long-term care homes are included in the fixed effects. To explore the correlation between cases and deaths inside and across areas, three different bivariate models are considered for the latent effects, namely an independent one, a conditional autoregressive model, and one that allows for both spatially structured and unstructured sources of variability. As the inclusion of spatial effects change some of the fixed effects, we extend the Spatial+ approach to a Bayesian areal set up to investigate the presence of spatial confounding. We find that the model which includes independent latent effects across boroughs performs the best among the ones considered, there appears to be spatial confounding with the diploma and median age variables, and the correlation between the cases and deaths across and within boroughs is always negative.

Behavioral factors associated with SARS-CoV-2 infection in Japan

Background

The relative burden of COVID‐19 has been less severe in Japan. One reason for this may be the uniquely strict restrictions imposed upon bars/restaurants. To assess if this approach was appropriately targeting high‐risk individuals, we examined behavioral factors associated with SARS‐CoV‐2 infection in the community.

Methods

This multicenter case–control study involved individuals receiving SARS‐CoV‐2 testing in June–August 2021. Behavioral exposures in the past 2 weeks were collected via questionnaire. SARS‐CoV‐2 PCR‐positive individuals were cases, while PCR‐negative individuals were controls.

Results

The analysis included 778 individuals (266 [34.2%] positives; median age [interquartile range] 33 [27–43] years). Attending three or more social gatherings was associated with SARS‐CoV‐2 infection (adjusted odds ratio [aOR] 2.00 [95% CI 1.31–3.05]). Attending gatherings with alcohol (aOR 2.29 [1.53–3.42]), at bars/restaurants (aOR 1.55 [1.04–2.30]), outdoors/at parks (aOR 2.87 [1.01–8.13]), at night (aOR 2.07 [1.40–3.04]), five or more people (aOR 1.81 [1.00–3.30]), 2 hours or longer (aOR 1.76 [1.14–2.71]), not wearing a mask during gatherings (aOR 4.18 [2.29–7.64]), and cloth mask use (aOR 1.77 [1.11–2.83]) were associated with infection. Going to karaoke (aOR 2.53 [1.25–5.09]) and to a gym (aOR 1.87 [1.11–3.16]) were also associated with infection. Factors not associated with infection included visiting a cafe with others, ordering takeout, using food delivery services, eating out by oneself, and work/school/travel‐related exposures including teleworking.

Conclusions

We identified multiple behavioral factors associated with SARS‐CoV‐2 infection, many of which were in line with the policy/risk communication implemented in Japan. Rapid assessment of risk factors can inform decision making.

Social Capital as Protection Against the Mental Health Impact of the COVID-19 Pandemic

The corona pandemic has a huge impact on the mental wellbeing of the Dutch population. Based on a large-scale panel survey (N = 22,696) on the social impact of COVID-19, this article firstly examines which social groups are most susceptible to the mental health consequences of the pandemic. Secondly, we examine whether social capital provides protection against this impact. We find that the mental health impact of COVID-19 is considerable and that it increased over the course of 2020. Women, young people, respondents with low incomes and/or poor self-perceived health, experience relatively more fear and stress due to the pandemic. We do not find a difference between respondents with or without a migration background. Social capital (received support, trust in people and in institutions) has the expected effect: the more support and trust, the less fear and stress. There is a mediation effect. Older people, respondents with high incomes and/or good health experience less fear and stress, partly because they have more social capital. This is different for females. They would experience even more fear and stress, compared to men, were it not for the fact that they have more social capital. Hence we conclude that social capital indeed provides some protection against the negative mental health consequences of COVID-19.

The association between area deprivation and COVID-19 incidence: a municipality-level spatio-temporal study in Belgium, 2020–2021

Background

In Belgium, current research on socio-economic inequalities in the coronavirus disease 2019 (COVID-19) crisis has mainly focused on excess mortality and data from the first epidemiological wave. The current study adds onto this by examining the association between COVID-19 incidence and area deprivation during the first five wave and interwave periods, thus adding a temporal gradient to the analyses.

Methods

We use all confirmed COVID-19 cases between March 2020 and June 2021 in Belgium, aggregated at the municipality-level. These data were collected by the national laboratory-based COVID-19 surveillance system. A level of area deprivation was assigned to each Belgian municipality using data of three socio-economic variables: the share of unemployed persons in the active population, the share of households without a car and the share of low-educated persons. The spatio-temporal association between COVID-19 incidence and area deprivation was assessed by performing multivariate negative-binomial regression analyses and computing population attributable fractions.

Results

A significant association between COVID-19 incidence and area deprivation was found over the entire study period, with the incidence in the most deprived areas predicted to be 24% higher than in the least deprived areas. This effect was dependent on the period during the COVID-19 crisis. The largest socio-economic inequalities in COVID-19 infections could be observed during wave 2 and wave 3, with a clear disadvantage for deprived areas.

Conclusion

Our results provide new insights into spatio-temporal patterns of socio-economic inequalities in COVID-19 incidence in Belgium. They reveal the existence of inequalities and a shift of these patterns over time.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13690-022-00856-9.

Impact of environmental and individual factors on COVID-19 mortality in children and adolescents in Mexico: An observational study

Background

During the Covid-19 pandemic, children and adolescents faced poverty, potentially dying from preventable causes, or missing out essential vaccines. The aim of this study was to assess potential environmental and individual factors associated to COVID-19 mortality in children and adolescents in Mexico.

Methods

This cross-sectional study analysed the official data of 131,001 children under 10 years of age and adolescents between 10 and 19 years of age with COVID-19 disease, in Mexico. Participants were diagnosticated between March 2020 and June 13, 2021. The environmental variables such as malnutrition, vaccination coverage and social lag index were evaluated at the state level. Multilevel models were fitted to evaluate the association between environmental and individual factors and COVID-19 mortality.

Findings

A total of 773 (0.6%) children and adolescents died due to COVID-19. Younger age (OR = 0.878, 95%CI: 0.869-0.888), diabetes (OR = 3.898, 95%CI: 2.596-5.851), immunosuppression (OR = 5.410, 95%CI: 4.088-7.158), obesity (OR = 1.876, 95%CI: 1.397-2.521), hypertension (OR = 1.906, 95%CI: 1.239-2.932), cardiovascular disease (OR = 2.288, 95%CI: 1.482-3.531), and chronic kidney disease (OR = 13.250, 95%CI: 9.066-19.350) were associated with mortality. COVID-19 mortality was directly associated with social lag index and malnutrition (OR_{very high} = 2.939, 95%CI: 1.111-7.775, and OR = 1.390, 95%CI: 1.073-1.802, respectively), and inversely associated with population density (OR = 0.374, 95%CI: 0.204-0.688). Finally, children and adolescents living in areas with a higher percentage of people with incomplete education (OR = 1.045, 95%CI: 1.011-1.081), of children of school age of 6–14 years who do not attend school (OR = 1.266, 95%CI: 1.032-1.554), and of illiterate population aged 15 and over (OR = 1.086, 95%CI: 0.999-1.179) were associated with a higher risk of COVID-19 mortality.

Interpretation

Malnutrition, social lag index and population density are key factors to understand COVID-19 mortality in children and adolescents. Also, age and pre-existing comorbidities were also associated with worse COVID-19 prognosis.

Funding

No funding was secured for this study.

Vaccine Hesitancy

Purpose of Review

Recent Findings

Summary

COVID-19 Health Disparities and Adverse Social Determinants of Health

Racial and ethnic disparities in healthcare and health outcomes are longstanding. The real-time emergence of COVID-19 disparities has heightened the public and scientific discourse about structural inequities contributing to the greater risk of morbidity and mortality among racial and ethnic minority populations and other underserved groups. A key aspect of assuring health equity is addressing social determinants that lead to adverse health outcomes among minoritized groups. This article presents an exploratory social determinants of health (SDOH) conceptual framework for understanding racial and ethnic COVID-19 disparities, including factors related to health and healthcare, socioeconomics, and environmental determinants. The model also illustrates the backdrop of structural racism and discrimination, which directly affect health and COVID-19 exposure risk, and thus transmission, infection, and death. We also describe a special SDOH collection in the PhenX Toolkit (consensus measures for Phenotypes and eXposures), which includes established measures to promote standardization of assessment and the use of common data elements in research contexts. The use of common constructs, measures, and data elements are important for data integration, understanding the causes of health disparities, and evaluating interventions to reduce them. Substandard SDOH are among the primary drivers of health disparities-and scientific approaches to address these key concerns require identification and leveled alignment with the root causes. The overarching goal of this discussion is to broaden the consideration of mechanisms by which populations with health disparities face additional SARS-CoV-2 exposure risks, and to encourage research to develop interventions to reduce SDOH-associated disparities in COVID-19 and other conditions and behaviors.

Occupation and Educational Attainment Characteristics Associated With COVID-19 Mortality by Race and Ethnicity in California

IMPORTANCE

Racial and ethnic inequities in COVID-19 mortality may be driven by occupation and education, but limited evidence has assessed these mechanisms.

OBJECTIVE

To estimate whether occupational characteristics or educational attainment explained the associations between race and ethnicity and COVID-19 mortality.

DESIGN, SETTING, AND PARTICIPANTS

This population-based retrospective cohort study of Californians aged 18 to 65 years linked COVID-19 deaths to population estimates within strata defined by race and ethnicity, gender, age, nativity in the US, region of residence, education, and occupation. Analysis was conducted from September 2020 to February 2022.

EXPOSURES

Education and occupational characteristics associated with COVID-19 exposure (essential sector, telework option, wages).

MAIN OUTCOMES AND MEASURES

All confirmed COVID-19 deaths in California through February 12, 2021. The study estimated what COVID-19 mortality would have been if each racial and ethnic group had (1) the COVID-19 mortality risk associated with the education and occupation distribution of White people and (2) the COVID-19 mortality risk associated with the lowest-risk educational and occupational positions.

RESULTS

Of 25 235 092 participants (mean [SD] age, 40 [14] years; 12 730 395 [50%] men), 14 783 died of COVID-19, 8 125 565 (32%) had a Bachelor's degree or higher, 13 345 829 (53%) worked in essential sectors, 11 783 017 (47%) could not telework, and 12 812 095 (51%) had annual wages under $51 700. COVID-19 mortality ranged from 15 deaths per 100 000 for White women and Asian women to 139 deaths per 100 000 for Latinx men. Accounting for differences in age, nativity, and region of residence, if all races and ethnicities had the COVID-19 mortality associated with the occupational characteristics of White people (sector, telework, wages), COVID-19 mortality would be reduced by 10% (95% CI, 6% to 14%) for Latinx men, but increased by 5% (95% CI, -8% to 17%) for Black men. If all working-age Californians had the COVID-19 mortality associated with the lowest-risk educational and occupational position (Bachelor's degree, nonessential, telework, and highest wage quintile), there would have been 43% fewer COVID-19 deaths among working-age adults (8441 fewer deaths; 95% CI, 32%-54%), with the largest absolute risk reductions for Latinx men (3755 deaths averted; 95% CI, 3304-4255 deaths) and Latinx women (2329 deaths averted; 95% CI, 2038-2621 deaths).

CONCLUSIONS AND RELEVANCE

In this population-based cohort study of working-age California adults, occupational disadvantage was associated with excess COVID-19 mortality for Latinx men. For all racial and ethnic groups, excess risk associated with low-education, essential, on-site, and low-wage jobs accounted for a substantial fraction of COVID-19 mortality.

The Impact of COVID-19 Pandemic on Halting Sustainable Development in the Colca y Volcanes de Andagua UNESCO Global Geopark in Peru—Prospects and Future

Events, such as the COVID-19 pandemic, that rapidly impact global communication and travel have significant consequences for the tourism industry, which is one of the pillars of global development. We assess the impacts of the COVID-19 crisis on the Colca y Volcanes de Andagua UNESCO Global Geopark in Peru. The Colca y Volcanes de Andagua Geopark was established immediately prior to the pandemic in October 2019. The instability of the government in Peru during the pandemic and the difficult living conditions in the high Andes, such as the lack of drinking water, cleaning agents, medical care, and the high levels of poverty, particularly in the geopark region, has contributed to the significantly high COVID-19 infection rates. In addition, detrimental impacts faced by the local community are a direct result of a reduction in travellers to the area due to legislative restrictions, which have had negative consequences on the local tourism industry. There is an urgent need for the recovery of the local tourism industry to prevent the permanent closure of tourism facilities and to minimise poverty rates.

Social media use and vaccine hesitancy in the European Union

Vaccine hesitancy can hinder the successful roll-out of vaccines. This paper examines COVID-19 vaccine hesitancy in the European Union, drawing from a large-scale cross-national survey covering all 27 EU Member States, carried out between February and March 2021 (n = 29,755). We study the determinants of vaccine hesitancy, focusing on the role of social media use. In multivariate regression models, we find statistically significant (p < 0.05) impacts on vaccine hesitancy of heavy use of social media and using social media as a main source of news. However, the effect of social media and the drivers of vaccine hesitancy vary depending on the reason for hesitancy. Most notably, hesitancy due to health concerns is mainly driven by physical health status and less by social media use, while views that COVID-19 risks are exaggerated (or that COVID-19 does not exist) are more common among men, people in good health, and those using social media as their main source of news.

Implications of the ongoing coronavirus disease 2019 pandemic for primary care

The coronavirus disease 2019 pandemic has caused widespread global disruption. In this article, the authors put forward lessons from the pandemic for primary care. Among these are primary healthcare requires substantial investment; big data should be carefully regulated and used to strengthen primary care; primary care physicians can support media to provide impartial, objective information; protecting the health of vulnerable populations is important; and infectious diseases are still relevant today. Travel and tourism significantly impact health and primary care. Pandemics may be more common in the future due to climate change, increased human population and habitat loss, among other reasons. We should apply the lessons learned from the current pandemic to better prepare for future pandemics.

SARS-CoV-2 infection among educational staff in Berlin, Germany, June to December 2020

BackgroundSARS-CoV-2 infections in preschool and school settings potentially bear occupational risks to educational staff.AimWe aimed to assess the prevalence of SARS-CoV-2 infection in teachers and preschool educators and at identifying factors associated with infection.MethodsWe analysed cross-sectional data derived from 17,448 voluntary, PCR-based screening tests of asymptomatic educational staff in Berlin, Germany, between June and December 2020 using descriptive statistics and a logistic regression model.ResultsParticipants were largely female (73.0%), and median age was 41 years (range: 18-78). Overall, SARS-CoV-2 infection proportion was 1.2% (95% CI: 1.0-1.4). Proportion of positive tests in educational staff largely followed community incidence until the start of the second pandemic wave, when an unsteady plateau was reached. Then, the proportion of positive tests in a (concurrent) population survey was 0.9% (95% CI: 0.6-1.4), 1.2% (95% CI: 0.8-1.8) in teachers and 2.6% (95% CI: 1.6-4.0) in preschool educators. Compared with teachers, increased odds of infection were conferred by being a preschool educator (adjusted odds ratio (aOR): 1.6; 95% CI: 1.3-2.0) and by contact with a SARS-CoV-2 infected individual outside of work (aOR: 3.0; 95% CI: 1.5-5.5). In a step-wise backward selection, the best set of associated factors with SARS-CoV-2 infection involved age, occupation, and calendar week.ConclusionsThese results indicate that preschool educators bear increased odds of SARS-CoV-2 infection compared with teachers. At the same time, the private environment appeared to be a relevant source of SARS-CoV-2 infection for educational staff in 2020.

Disparities in COVID-19 health outcomes among different sub-immigrant groups in the US - a study based on the spatial Durbin model

Immigrants may be more vulnerable to coronavirus disease 2019 (COVID-19) than other sub-population groups due to their relatively low socioeconomic status. However, no quantitative studies have examined the relationships between immigrants and COVID-19 health outcomes (confirmed cases and related deaths). We first examined the relationship between total immigrants and COVID-19 health outcomes with spatial Durbin models after controlling for demographic, biophysical and socioeconomic variables. We then repeated the same analysis within multiple subimmigrant groups divided by those with original nativity to examine the differential associations with health outcomes. The result showed that the proportion of all immigrants is negatively associated with the number of confirmed cases and related deaths. At the continent and sub-continent level, we consistently found negative relationships between the number of confirmed cases and the proportion of all sub-immigrant groups. However, we observed mixed associations between the proportion of sub-immigrant groups and the number of deaths. Those counties having a higher prevalence of immigrants from Africa [Eastern Africa: â€"18.6, 95% confidence interval (CI): â€"38.3~â€"2.9; Northern Africa: â€"146.5, 95% CI: â€"285.5~â€"20.1; Middle Africa: â€"622.6, 95% CI: â€"801.4~â€" 464.5] and the Americas (Northern America: â€"90.5, 95% CI: â€" 106.1~â€"73.8; Latin America: â€"6.8, 95% CI: â€"8.1~â€"5.2) mostly had a lower number of deaths, whereas those counties having a higher prevalence of immigrants from Asia (Eastern Asia: 21.0, 95% CI: 7.7~36.2; Western Asia: 42.5, 95% CI: 16.9~68.8; South- Central Asia: 26.6, 95% CI: 15.5~36.9) showed a higher number of deaths. Our results partially support that some immigrants, especially those from Asia, are more vulnerable to COVID-19 than other sub-population groups.

Exploring the attitudes, concerns, and knowledge regarding COVID-19 vaccine by the parents of children with rheumatic disease: Cross-sectional online survey

BACKGROUND

Vaccination programs are effective strategies in preventing infectious diseases and controlling epidemics. Vaccination against SARS-CoV-2 in children has not yet been approved globally, and it is unclear what attitude families will take when it is approved in children. We aimed to investigate the underlying causes of vaccine acceptance, hesitation, and refusal, as well as concerns about the acceptability of the COVID-19 vaccine by parents of children with rheumatic diseases.

METHODS

Parents of children followed up with a diagnosis of rheumatic disease in the pediatric rheumatology outpatient clinic of a university hospital were included in the study. We applied a closed web-based online survey conducted cross-sectionally and sent to the participants via mobile smartphones.

RESULTS

For fathers, mothers, and their children, acceptance rates for a COVID-19 vaccine were 64.2%, 57.7%, and 41.8%, respectively. In the multivariate analysis, factors affecting parents' acceptance of vaccines for their children were as follows: "Receiving antirheumatic medications regularly (AOR 5.40, 95% CI 1.10-26.33, p = 0.03), the previous history of getting special recommended vaccines (AOR 4.12, 95% CI 1.12-27.85, p = 0.03), relying on vaccines for ending pandemic (AOR 8.84, 95% CI 2.80-27.85, p = 0.001), complying with the pandemic measures entirely (AOR 5.24, 95% CI 1.46-18.74, p = 0.01)". The two most common reasons for vaccine rejection were fear of the side effects of the vaccine and its possible interaction with rheumatic drugs used by children.

CONCLUSION

According to our survey, parents were more likely to accept a COVID-19 vaccine for themselves than their children. The success of COVID-19 vaccination programs sources highly on people's willingness to accept the vaccine. It is crucial to vaccinate children for achieving herd immunity and in terms of avoiding vaccine hesitancy. Larger data examining the causes of concerns in parents of both healthy children and children with chronic diseases should be delineated.