The association between socioeconomic status and pandemic influenza: Systematic review and meta-analysis

Influenza-Associated Outcomes and Healthcare Utilization by Race and Ethnicity in the USA: a Retrospective Cohort Study Using the National Inpatient Sample Database

BACKGROUND

The influenza virus continues to be a public health concern every season. We aimed to evaluate influenza-associated outcomes and healthcare utilization by race and ethnicity.

METHODS

We conducted a retrospective cohort study using the National Inpatient Sample across 2019 and 2020. Influenza pneumonia was selected as the principal diagnosis. Outcomes included mortality, use of respiratory support ventilation, length of stay, and total hospitalization charge. Regression models were adjusted for age, gender, Charlson Comorbidity Index, hospitals' region, bed size, teaching status, insurance status, and median income.

RESULTS

We identified 73,098 individuals hospitalized with influenza pneumonia; 39,807 and 33,291 were admitted in 2019 and 2020, respectively. The sample included 49,829 (68%) White, 11,356 (15.5%) Black, 7526 (10%) Hispanic, 1860 (2.5%) Asian/Pacific, and 617 (0.84%) Native American patients. In-hospital mortality rates and respiratory support (non-invasive ventilation and invasive mechanical ventilation) in 2019 and 2020 were not significantly different across all the races. In 2019 and 2020, the adjusted odds ratios of in-patient mortality were not significantly different. Asians had higher odds of receiving NIV in 2019 but not in 2020 compared to White patients (adjusted odds ratio (aOR) 1.67, p value 0.04). The adjusted odds ratios for receiving IMV were not significantly different between the races in 2019 and 2020.

CONCLUSIONS

This study contributes valuable insight into influenza-associated outcomes and healthcare utilization patterns among diverse racial and ethnic groups. Disparities in healthcare utilization were observed among younger (< 65 years) individuals of Black and Hispanic ethnicity.

Universal health care delivery mitigates socioeconomic-related risk for adverse outcomes in hospitalised patients: Lessons from the COVID-19 pandemic in Australia

BACKGROUND

Internationally, socioeconomic disadvantage is related to severe outcomes of COVID-19. We investigated the impact of socioeconomic disadvantage on infection rates, hospitalisation, and in-hospital outcomes for COVID-19 with standardised medical care.

METHODS

This retrospective cross-sectional study included SARS-CoV-2 PCR-confirmed patients ≥18 years, admitted to a major public hospital between January 2020 and December 2021. Severe COVID-19 outcomes were defined by a composite outcome of in-hospital death or other critical complications. A generalised linear regression model of demographic features, co-existing conditions, and socioeconomic status was used to determine the risks of the composite outcome.

RESULTS

Of 797,343 individuals ≥18 years in the health district, 50,906 (6.4%) were PCR-positive, and 1,962 were hospitalised. Compared with the whole health district population, infected individuals were younger (median [interquartile range] age 35 [25-48] years vs 42 [31-58] years) and from areas with the greatest socioeconomic disadvantage (34.4% vs 20%; both p < 0.0001). Hospitalised patients were older, with more females compared to the PCR-positive group (46 years [33-61], 53.5%, respectively; p < 0.001), and 51.2% were from postcodes with greatest socioeconomic disadvantage (p < 0.0001). The composite outcome occurred in 11.5%, with an in-hospital mortality of 3.8%. Higher risk of the composite outcome was observed in males (OR 1.72, 95% CI [1.26-2.42], p < 0.001), patients aged ≥ 65 years (OR 6.96, [3.3-14.6], p < 0.001), those with ≥ 4 comorbidities (OR 2.67, [1.54-4.63], p < 0.001), and unvaccinated patients (OR 1.57, [1.05-2.38], p < 0.05). The risk of composite outcome did not increase with socioeconomic disadvantage (OR 0.97, [0.68, 1.42], p = 0.64).

CONCLUSION

In the absence of capacity restraints, socioeconomic disadvantage was not associated with severe in-hospital outcomes in a well-resourced care environment despite increased rates of infection and hospitalisation. This highlights the impact of universally accessible, standardised, protocolised, high-quality in-hospital care in reducing the risk of adverse in-hospital outcomes in socioeconomically disadvantaged patients.

Wastewater-Based Surveillance of Respiratory Syncytial Virus Reveals a Temporal Disconnect in Disease Trajectory across an Active International Land Border

Conventional metrics for tracking infectious diseases, including case and outbreak data and syndromic surveillance, can be resource-intensive, misleading, and comparatively slow with prolonged data collection, analysis and authentication. This study examined the 2022-2023 Respiratory Syncytial Virus (RSV) season in a contiguous metropolitan area connected by an active international land border, affording an opportunity for comparison of the respiratory virus season spanning two independent public health jurisdictions. Time-lagged cross correlation and qualitative examination of the wastewater signals showed that the peak of the Detroit (MI, USA) RSV season predated the peak in Windsor (ON, Canada) by approximately 5 weeks. A strong positive relationship was observed between RSV N-gene concentrations in wastewater and hospitalization rates in Windsor-Essex (Kendall's τ = 0.539, p ≤ 0.001, Spearman's ρ = 0.713, p ≤ 0.001) as well as Detroit (Kendall's τ = 0.739, p ≤ 0.001, Spearman's ρ = 0.888, p ≤ 0.001). This study demonstrated that wastewater surveillance can reveal regional differences in infection dynamics between communities and can provide an independent measure of the prevalence of RSV, an underreported disease. These findings support the use of wastewater surveillance as a cost-effective tool in monitoring of RSV to enhance existing surveillance systems and to better inform public health disease mitigation strategies.

A systematic review and meta-analysis on the association between PM2.5 exposure and increased influenza risk

Introduction

This systematic review and meta-analysis investigate the relationship between PM2.5 exposure and increased influenza risk (e.g., increased hospital admissions, confirmed influenza cases), synthesizing previous findings related to pollutant effects and exposure durations.

Methods

We searched PubMed, Web of Science, and Scopus for relevant studies up to 1 January 2010, following Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) guidelines for selection and analysis.

Results

Our review included 16 studies and found that a 10 μg/m3 increase in daily PM2.5 levels was associated with an increase of 1.5% rise in influenza risk (95% CI: 0.08%, 2.2%), with significant variations across different temperatures and lag times post-exposure. The analysis revealed heightened risks, with the most significant increases observed under extreme temperature conditions. Specifically, colder conditions were associated with a 14.2% increase in risk (RR = 14.2%, 95% CI: 3.5%, 24.9%), while warmer conditions showed the highest increase, with a 29.4% rise in risk (RR = 29.4%, 95% CI: 7.8%, 50.9%). Additionally, adults aged 18-64 were notably affected (RR = 4%, 95% CI: 2.9%, 5.1%).

Discussion

These results highlight PM2.5's potential to impair immune responses, increasing flu susceptibility. Despite clear evidence of PM2.5's impact on flu risk, gaps remain concerning exposure timing and climate effects. Future research should broaden to diverse regions and populations to deepen understanding and inform public health strategies.

Associations of Parental Education With Children's Infectious Diseases and Their Mediating Factors: The Japan Environment and Children's Study (JECS)

BACKGROUND

Parents' educational background is presumed to influence the incidence of vaccine-preventable diseases in children through their decisions about vaccinations and other family lifestyle choices. Regarding voluntary vaccination, a household's economic situation may also be associated with non-vaccination. Therefore, this study investigated the association between parental education and vaccine-preventable diseases (varicella, mumps, influenza [flu], pertussis, measles, and rubella) in children, which currently remains elusive.

METHODS

We used datasets from the Japan Environment and Children's Study, which included 104,062 fetal records; our study population comprised 80,930 children up to the age of 3 years. The associations between parental educational background and children's infectious diseases were examined using binomial logistic regression analysis. The mediating effects of household income, vaccination, and smoking were examined using a path analysis.

RESULTS

For varicella, mumps, and influenza covered by voluntary vaccination, a higher education level of the father was associated with a lower incidence of infection. The association between mothers' education and children's infection was limited. There were both income-mediated and non-income-mediated pathways between parental education and voluntary vaccination. For pertussis, measles, and rubella, which are covered by routine vaccines, there was no association between parental education and the child's infection.

CONCLUSION

An association between parental education and childhood infections was observed. Providing financial support for vaccination and communicating the benefits of vaccination in a way that parents at all levels of education can understand may help reduce the incidence of infectious diseases among children.

Spatial-temporal evolution patterns of influenza incidence in plateau regions from 2009 to 2023

Objectives

This study used (Geographic Information System) GIS technology to analyze the spatiotemporal distribution of influenza incidence in Qinghai from 2009 to 2023, based on influenza surveillance data.

Methods

This study first accessed the influenza data sets of Qinghai Province from 2009 to 2023 through the Chinese Infectious Disease Surveillance System. Subsequently, trend charts of influenza incidence in each city and prefecture were employed to illustrate the trends of influenza incidence during the period from 2009 to 2023. To explore the risks of influenza incidence in different counties and districts, methods including spatial autocorrelation, cluster analysis, hotspot analysis, Gravity center shift model, and standard deviation ellipse were utilized.

Results

The study showed that the incidence of influenza showed significant fluctuations, with marked spikes in 2019 and 2023. Spatial autocorrelation analysis revealed significant positive autocorrelation in 2015, 2017-2019, and 2022-2023 (Moran's I > 0 and p < 0.05). Local spatial autocorrelation analysis identified clustering patterns in different regions, with high - high clustering in eastern Qinghai and low - low clustering in the west. Hot - spot analysis indicated that the counties with a high incidence of influenza in Qinghai were mainly located in the lower - altitude east. Standard deviation ellipse analysis showed that in 2021, the spread of influenza was the most extensive, almost covering eastern and parts of western Qinghai. From 2021 to 2022, the spread range shrank and expanded again in 2023. The gravity center of influenza moved southeastward year by year from Gangcha County in 2018 to Gonghe County in 2023. The spread of influenza was found to be expanding eastward, with the epidemic center shifted over time.

Conclusion

The prominent spatiotemporal heterogeneity of influenza incidence in Qinghai Province indicates the need to develop differentiated and precise influenza prevention and control strategies in different regions to address the changing trends of influenza epidemics.

The Global Polycrisis and Health Inequalities

In the current era of multiple, overlapping global crises, it is essential to consider the political economy of health within the broader framework of global interconnectedness. In this article, we employ the polycrisis concept to understand the impacts of the multifaceted, concurrent, and synergistic contemporary global crises on global health and health inequalities. A polycrisis occurs when crises in multiple diverse global systems become causally entangled, compounding their effects. Despite its potential relevance and analytical insights, the polycrisis concept has rarely been applied in public health research. This article fills that gap, and through reviewing the impacts of past economic, environmental, health, and political crises, we argue that the polycrisis is creating a complex web of challenges that are likely to amplify existing and future health inequalities. We conclude by discussing strategies to mitigate these impacts and suggest pathways for research to ensure that the future is not inevitably unequal.

Differences in influenza testing and treatment in micropolitan versus metropolitan areas in the U.S. using medicare claims data from 2010 to 2016

BACKGROUND

To improve understanding of influenza and rurality, we investigated differences in influenza testing and anti-viral treatment rates between micropolitan (muSAs) and metropolitan statistical areas (MSAs) using national medical claims data over multiple influenza seasons.

METHODS

Using billing data from the Centers for Medicare and Medicaid Services for those aged 65 years and older, we estimated weekly rates of ordered rapid influenza diagnostic tests (RIDT) and antivirals (AV) among Medicare enrollees by core-based statistical areas (CBSAs) during 2010-2016. We used Negative Binomial generalized mixed models to estimate adjusted rate ratios (aRR) between MSAs and muSAs, adjusting for clustering by CBSA plus explanatory variables. We ran models for all weeks and only high influenza activity weeks.

RESULTS

For all weeks, the unadjusted rate of RIDTs was 1.97 per 10,000 people in MSAs compared with 2.69 in muSAs (Rate ratio (RR) = 0.73, 95% Confidence Interval (CI): 0.73-0.74) and of AVs was 1.85 in MSAs compared with 1.40 in muSAs (RR = 1.32, CI: 1.31-1.32). From the multivariate model, aRR for RIDTs was 0.82 (0.73-0.94) and for AVs was 1.12 (1.04-1.22) in MSAs versus muSAs. For high influenza activity weeks, aRR for RIDTs was 0.82 (0.73-0.92) and for AVs was 1.15 (1.06-1.24). All models found influenza testing rates higher in muSAs and treatment rates higher in MSAs.

CONCLUSIONS

Our study found lower testing and higher treatment in U.S. metropolitan versus micropolitan areas from 2010 to 2016 for those aged 65 years and older in our population. Identifying differences in influenza rates by rurality may improve public health response. Further research into the relationship of rurality and health disparities is needed.

Estimating the burden of RSV- and influenza-associated hospitalizations, ICU admissions, and deaths across age and socioeconomic groups in New York State, 2005-2019

Background

Multiple prophylactic products are now available to protect against respiratory syncytial virus (RSV) in different age groups. Assessing the pre-intervention burden of RSV infections across various severity levels and risk groups is crucial, as it provides a baseline for evaluating the impact of these products.

Methods

We obtained monthly time series data on hospitalizations, intensive care unit (ICU) admissions, and deaths by age group, ZIP code, and cause for New York state from 2005 to 2019. Socioeconomic status (SES) of the ZIP codes was classified using supervised principal component analysis (PCA). We estimated the incidence of hospitalizations, ICU admissions, and deaths attributable to RSV and to influenza using hierarchical Bayesian regression models. Additionally, we assessed severity, defined by ICU admission and mortality risks, as well as recording fraction (i.e., percent of estimated virus-associated hospitalizations recorded as being due to the specific virus), stratified by age, SES, and over time.

Results

The estimated annual incidence of RSV-associated hospitalizations and ICU admissions were highest in infants under 1 in the low SES group (2,240 [95% credible interval (CrI): 2,200-2,290] hospitalizations and 330 [95% CrI: 320-350] ICU admissions per 100,000 person-years). The incidence of RSV-associated deaths was highest among adults ≥85 years old (61 [95% CrI: 49-74] per 100,000 person-years). In contrast to RSV, the burden of influenza was greatest in age groups ≥65 years. The risk of ICU admission varied by patients' age and SES, and the mortality risk increased dramatically with age for both pathogens (RSV: 11.9% [95% CrI: 9.6-14.3%], influenza: 14.4% [95% CrI: 13.1-15.6%] among ≥85 year age group). Incidence varied by epidemic year and season, and we observed an increasing recording fraction of RSV among all age groups over the study period.

Conclusions

RSV and influenza contribute significantly to the burden of hospitalizations, ICU admissions, and deaths, particularly among infants and older adults. Although the recording fraction of RSV increased over the study period, it remains lower, particularly for adults. Our findings reveal a disparity in hospitalization burden by SES, particularly among younger age groups.

A Narrative Review of Key Risk Factors for Severe Illness Following SARS-CoV-2, Influenza Virus, and Respiratory Syncytial Virus Infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza, and respiratory syncytial virus (RSV) are highly infectious respiratory viruses that affect people of all ages and are typically associated with mild symptoms and few complications in immunocompetent individuals. However, the risk of severe outcomes (e.g., hospitalization and death) following infection with these respiratory viruses is higher in certain populations, including older adults and individuals of certain race/ethnic and sociodemographic groups. Additionally, immunocompromising conditions and pre-existing comorbidities, including underlying cardiovascular (e.g., congestive heart failure) and respiratory diseases (e.g., chronic obstructive pulmonary disease), diabetes, chronic kidney disease, and obesity, are key factors that predispose individuals to SARS-CoV-2-, influenza-, and RSV-related severe outcomes. Increased risk for severe outcomes associated with advancing age and comorbidities is compounded by residence in long-term care facilities due to the enhanced spread of respiratory infections in congregate living environments. In this narrative review, risk factors associated with severe outcomes following infection with SARS-CoV-2, influenza, and RSV in adult populations are explored. Additionally, distinct clinical outcomes based on underlying comorbidities following infection are discussed in the context of high-risk populations. Factors unique to each virus that underpin distinct risk profiles are described and suggest the potential for tailored surveillance and healthcare approaches to target and ultimately mitigate SARS-CoV-2-, influenza-, and RSV-associated disease burden in vulnerable populations. Mutual risk factors for severe outcomes are also highlighted; these similarities indicate that cohesive risk reduction strategies may also be feasible, particularly since vaccines are available for each of these respiratory viruses. Ultimately, a more thorough understanding of the risk factors that predispose individuals to develop SARS-CoV-2-, influenza-, and RSV-related severe outcomes may improve risk reduction strategies, inform healthcare policy, and contribute to the expansion and refinement of existing surveillance approaches to ultimately mitigate disease burden in vulnerable populations.

Individual and community socioeconomic status and receipt of influenza vaccines among adult primary care patients in a large academic health system: 2017-2019

Introduction

Influenza causes significant mortality and morbidity in the U.S., yet less than half of adults receive influenza vaccination. We use census-tract level social vulnerability index (SVI) to examine community- and individual-level characteristics of influenza vaccine coverage among primary care patients at an academic health system in Los Angeles, CA.

Methods

We used electronic medical records (EMR) data of 247,773 primary care patients for 2017-18 and 2018-19 influenza seasons. We geocoded patients' addresses to identify their SVI and merged them with EMR data. We specified mixed-effects logistic regression models estimating the association between patient's vaccine receipt and SVI, adjusting for sociodemographics, Charlson Comorbidity Index, and health insurance.

Results

Vaccination coverage was higher during the 2018-19 influenza season (34%) compared to the 2017-18 season (23%). In adjusted analyses, higher SVI, lower individual socioeconomic status and racial and ethnic minority status were independently associated with lower odds of vaccination. Patients on Medicaid had lower odds of vaccine receipt (adjusted Odds Ratio [aOR] = 0.77 for <65, aOR = 0.30 for 65+) than patients on commercial health insurance. Asian Non-Hispanic patients had higher odds than White Non-Hispanic patients (aOR = 2.39 for <65, aOR = 1.91 for 65+), while Black Non-Hispanic patients had lower odds (aOR = 0.49 for <65, aOR = 0.59 for 65+).

Conclusions

Community and individual socioeconomic status and race and ethnicity were associated with influenza vaccination. Health systems can use SVI to identify communities at increased risk of influenza mortality and morbidity, and engage with community partners to develop communication strategies and invest in interventions to increase vaccine accessibility in under-resourced neighborhoods.

COVID-19-induced changes in the workplace, psychosocial work environment and employee well-being: a longitudinal study

BACKGROUND

In many workplaces, the coronavirus disease 2019 pandemic changed work arrangements, but there is scarce longitudinal evidence on whether psychosocial work environment and employee well-being were affected.

AIMS

To examine the psychosocial work environment and employee well-being before, during and after the pandemic in relation to pandemic-induced changes (working from home, change to other tasks and team reorganization).

METHODS

Survey data from a cohort of 20 944 public sector employees in Finland were collected before (2016-2018), during (2020) and after the pandemic (2022). Multilevel linear and logistic regression was used to examine group differences between the before-during and during-after periods of the pandemic.

RESULTS

Working from home was associated with a small but favourable change in worktime control, organizational justice and social capital (scale 1-5) during the pandemic and after the pandemic (marginal mean difference ranging from 0.02 to 0.09 with 95% confidence intervals [CIs] from 0.01 to 0.10). There was a post-pandemic increase in work time control, even among participants with a transfer into other tasks (0.11, 95% CI 0.07, 0.14) or team reorganization (0.06, 95% CI 0.02, 0.10). The decline in self-rated work ability (scale 0-10) before and during the pandemic was greater in those transferred into other tasks (-0.10, 95% CI -0.13, -0.06) than in those not (-0.05, 95% CI -0.06, -0.04).

CONCLUSIONS

Working from home during the pandemic was accompanied by small favourable changes in the psychosocial work environment during the pandemic, whereas transition to different tasks was associated with a decline in self-rated work ability.

Impact of socioeconomic status on cardiac arrest outcomes during COVID-19 pandemic

Introduction

The coronavirus disease 19 (COVID-19) pandemic has affected healthcare services, potentially leading to inequitable outcomes based on patients' socioeconomic status (SES). This study aimed to evaluate the impact of COVID-19 on out-of-hospital cardiac arrest (OHCA) outcomes by examining disparities across SES levels.

Methods

The study analyzed non-traumatic OHCA cases registered in the Korean Out-of-Hospital Cardiac Arrest Registry from 2010 to 2021, encompassing 238,668 patients aged 18 years and older. SES was assessed at both the individual (Medicaid vs non-Medicaid) and area levels using a deprivation index. Outcomes included any return of spontaneous circulation, survival to admission, survival to discharge, and favorable neurological recovery. Logistic regression and generalized additive models (GAMs) were used for analysis.

Results

OHCA outcomes-including survival to admission, survival to discharge, and favorable neurological recovery-improved over the years, peaking in 2019 before subsequently declining. Logistic regression showed that the lowest SES area was associated with lower rates of ROSC (adjusted odds rations [aOR] 0.82, 95 % confidence interval [CI] 0.75-0.88) and survival to admission (aOR 0.56, 95%CI 0.49-0.64) and discharge (aOR 0.78, 95%CI 0.61-0.98) during the pandemic. GAM analysis revealed that lower SES groups (deprivation index levels 4 and 5) experienced higher-than-expected survival to admission and discharge rates, as well as favorable neurological recovery. Although outcomes in the deprivation index level 1 group (5.5 % in 2021) remained superior, indicating poor outcomes for the lowest SES area group (3.43 % in 2021), the disparity decreased following the pandemic.

Conclusion

Lower levels of SES are a significant risk factor for unfavorable neurological recovery in OHCA, independent of the COVID-19 pandemic. However, SES-related disparities in the outcomes decreased post-pandemic. Despite the overall negative impact of COVID-19, certain lower SES groups showed improved survival rates, likely due to differences in the EMS response and healthcare burden across regions.

Social health gradient and risk factors among patients hospitalized for COVID-19 and pre-pandemic respiratory infections. A linked national individual case-control study in Belgium

Introduction

The literature establishes a clear social gradient in health for transmissible respiratory diseases. However, this gradient's extent remains largely unexplored in the context of COVID-19, and it is uncertain whether the pandemic has exacerbated this gradient. The study aims to compare the socio-economic profiles and comorbidities during the COVID-19 pandemic with a control population affected by viral pneumonia/respiratory disease in 2019.

Methods

This case-control study analyzed linked data from all patients hospitalized for COVID-19 in 2020 (n = 22,087) and for respiratory diseases in 2019 (n = 7,586). Socio-economic data from the social security database were linked to clinical data from the hospital registry. We analyzed the socio-demographic and clinical factors associated with COVID-19 hospitalization (control group, wave 1, and wave 2) using multinomial regressions and logistic regression models and the length of stay during hospitalization using binomial negative regressions.

Results

A social health gradient was observed in both the COVID-19 and control groups, with a significant increase across waves for COVID-19 (p-trend < 0.0001). Men, people over the age of 45, those with comorbidities, high population density, lower income, lower socio-economic status, and people living in Brussels capital were at higher risk of COVID-19 hospitalization and longer length of stay compared to the control group. Except for sub-Saharan Africans, all patients of foreign nationality had a significantly increased risk of hospitalization (p < 0.001), but a shorter length of stay compared to Belgians.

Conclusion

The socio-health gradient for COVID-19 followed the same pattern as that observed in pre-pandemic respiratory diseases, intensifying in the second wave and among the most deprived groups. This study emphasizes the importance of collecting social data alongside clinical data for a better understanding of social health inequalities and for tailoring health prevention policies.

Generalized contact matrices allow integrating socioeconomic variables into epidemic models

Variables related to socioeconomic status (SES), including income, ethnicity, and education, shape contact structures and affect the spread of infectious diseases. However, these factors are often overlooked in epidemic models, which typically stratify social contacts by age and interaction contexts. Here, we introduce and study generalized contact matrices that stratify contacts across multiple dimensions. We demonstrate a lower-bound theorem proving that disregarding additional dimensions, besides age and context, might lead to an underestimation of the basic reproductive number. By using SES variables in both synthetic and empirical data, we illustrate how generalized contact matrices enhance epidemic models, capturing variations in behaviors such as heterogeneous levels of adherence to nonpharmaceutical interventions among demographic groups. Moreover, we highlight the importance of integrating SES traits into epidemic models, as neglecting them might lead to substantial misrepresentation of epidemic outcomes and dynamics. Our research contributes to the efforts aiming at incorporating socioeconomic and other dimensions into epidemic modeling.

Forecasting severe respiratory disease hospitalizations using machine learning algorithms

BACKGROUND

Forecasting models predicting trends in hospitalization rates have the potential to inform hospital management during seasonal epidemics of respiratory diseases and the associated surges caused by acute hospital admissions. Hospital bed requirements for elective surgery could be better planned if it were possible to foresee upcoming peaks in severe respiratory illness admissions. Forecasting models can also guide the use of intervention strategies to decrease the spread of respiratory pathogens and thus prevent local health system overload. In this study, we explore the capability of forecasting models to predict the number of hospital admissions in Auckland, New Zealand, within a three-week time horizon. Furthermore, we evaluate probabilistic forecasts and the impact on model performance when integrating laboratory data describing the circulation of respiratory viruses.

METHODS

The dataset used for this exploration results from active hospital surveillance, in which the World Health Organization Severe Acute Respiratory Infection (SARI) case definition was consistently used. This research nurse-led surveillance has been implemented in two public hospitals in Auckland and provides a systematic laboratory testing of SARI patients for nine respiratory viruses, including influenza, respiratory syncytial virus, and rhinovirus. The forecasting strategies used comprise automatic machine learning, one of the most recent generative pre-trained transformers, and established artificial neural network algorithms capable of univariate and multivariate forecasting.

RESULTS

We found that machine learning models compute more accurate forecasts in comparison to naïve seasonal models. Furthermore, we analyzed the impact of reducing the temporal resolution of forecasts, which decreased the model error of point forecasts and made probabilistic forecasting more reliable. An additional analysis that used the laboratory data revealed strong season-to-season variations in the incidence of respiratory viruses and how this correlates with total hospitalization cases. These variations could explain why it was not possible to improve forecasts by integrating this data.

CONCLUSIONS

Active SARI surveillance and consistent data collection over time enable these data to be used to predict hospital bed utilization. These findings show the potential of machine learning as support for informing systems for proactive hospital management.

Spatial-temporal evolution patterns of influenza incidence in Xinjiang Prefecture from 2014 to 2023 based on GIS

Using GIS technology, this study investigated the spatiotemporal distribution pattern of influenza incidence in Xinjiang from 2014 to 2023 based on influenza surveillance data. The study revealed a noticeable fluctuation trend in influenza incidence rates in Xinjiang, particularly notable spikes observed in 2019 and 2023. The results of the 3-year moving average showed a significant long-term upward trend in influenza incidence rates, confirmed by Theil-Sen method (MAD = 2.202, p < 0.01). Global spatial autocorrelation analysis indicated significant positive spatial autocorrelation in influenza incidence rates from 2016 and from 2018 to 2023 (Moran's I > 0, P < 0.05). Local spatial autocorrelation analysis further revealed clustering patterns in different regions, with high-high clustering and low-high clustering predominating in northern Xinjiang, and low-low clustering predominating in southern Xinjiang. Hotspot analysis indicated a progressive rise in the number of influenza incidence hotspots, primarily concentrated in northern Xinjiang, particularly in Urumqi, Ili Kazakh Autonomous Prefecture, and Hotan Prefecture. Standard deviation ellipse analysis and the trajectory of influenza incidence gravity center migration showed that the transmission range of influenza in Xinjiang has been expanding, with the epidemic center gradually moving northward. The spatiotemporal heterogeneity of influenza incidence in Xinjiang highlights the need for differentiated and precise influenza prevention and control strategies in different regions to address the changing trends in influenza prevalence.

Wastewater Surveillance to Confirm Differences in Influenza A Infection between Michigan, USA, and Ontario, Canada, September 2022-March 2023

Wastewater surveillance is an effective way to track the prevalence of infectious agents within a community and, potentially, the spread of pathogens between jurisdictions. We conducted a retrospective wastewater surveillance study of the 2022-23 influenza season in 2 communities, Detroit, Michigan, USA, and Windsor-Essex, Ontario, Canada, that form North America's largest cross-border conurbation. We observed a positive relationship between influenza-related hospitalizations and the influenza A virus (IAV) wastewater signal in Windsor-Essex (ρ = 0.785; p<0.001) and an association between influenza-related hospitalizations in Michigan and the IAV wastewater signal for Detroit (ρ = 0.769; p<0.001). Time-lagged cross correlation and qualitative examination of wastewater signal in the monitored sewersheds showed the peak of the IAV season in Detroit was delayed behind Windsor-Essex by 3 weeks. Wastewater surveillance for IAV reflects regional differences in infection dynamics which may be influenced by many factors, including the timing of vaccine administration between jurisdictions.

Did the 1918 influenza pandemic cause a 1920 baby boom? Demographic evidence from neutral Europe

In 1919-20, the European countries that were neutral in the First World War saw a small baby bust followed by a small baby boom. The sparse literature on this topic attributes the 1919 bust to individuals postponing conceptions during the peak of the 1918-20 influenza pandemic and the 1920 boom to recuperation of those conceptions. Using data from six large neutral countries of Europe, we present novel evidence contradicting that narrative. In fact, the subnational populations and maternal birth cohorts whose fertility was initially hit hardest by the pandemic were still experiencing below-average fertility in 1920. Demographic evidence, economic evidence, and a review of post-pandemic fertility trends outside Europe suggest that the 1920 baby boom in neutral Europe was caused by the end of the First World War, not by the end of the pandemic.

Associations of hospital-treated infections with subsequent dementia: nationwide 30-year analysis

Infections, which can prompt neuroinflammation, may be a risk factor for dementia1-5. More information is needed concerning associations across different infections and different dementias, and from longitudinal studies with long follow-ups. This New Zealand-based population register study tested whether infections antedate dementia across three decades. We identified individuals born between 1929 and 1968 and followed them from 1989 to 2019 (n = 1,742,406, baseline age = 21-60 years). Infection diagnoses were ascertained from public hospital records. Dementia diagnoses were ascertained from public hospital, mortality and pharmaceutical records. Relative to individuals without an infection, those with an infection were at increased risk of dementia (hazard ratio 2.93, 95% confidence interval 2.68-3.20). Associations were evident for dementia diagnoses made up to 25-30 years after infection diagnoses. Associations held after accounting for preexisting physical diseases, mental disorders and socioeconomic deprivation. Associations were evident for viral, bacterial, parasitic and other infections, and for Alzheimer's disease and other dementias, including vascular dementia. Preventing infections might reduce the burden of neurodegenerative conditions.

The COVID-19 vaccination campaign in Switzerland and its impact on disease spread

We analyse infectious disease case surveillance data to estimate COVID-19 spread and gain an understanding of the impact of introducing vaccines to counter the disease in Switzerland. The data used in this work is extensive and detailed and includes information on weekly number of cases and vaccination rates by age and region. Our approach takes into account waning immunity. The statistical analysis allows us to determine the effects of choosing alternative vaccination strategies. Our results indicate greater uptake of vaccine would have led to fewer cases with a particularly large effect on undervaccinated regions. An alternative distribution scheme not targeting specific age groups also leads to fewer cases overall but could lead to more cases among the elderly (a potentially vulnerable population) during the early stage of prophylaxis rollout.

Importance of social inequalities to contact patterns, vaccine uptake, and epidemic dynamics

Individuals' socio-demographic and economic characteristics crucially shape the spread of an epidemic by largely determining the exposure level to the virus and the severity of the disease for those who got infected. While the complex interplay between individual characteristics and epidemic dynamics is widely recognised, traditional mathematical models often overlook these factors. In this study, we examine two important aspects of human behaviour relevant to epidemics: contact patterns and vaccination uptake. Using data collected during the COVID-19 pandemic in Hungary, we first identify the dimensions along which individuals exhibit the greatest variation in their contact patterns and vaccination uptake. We find that generally higher socio-economic groups of the population have a higher number of contacts and a higher vaccination uptake with respect to disadvantaged groups. Subsequently, we propose a data-driven epidemiological model that incorporates these behavioural differences. Finally, we apply our model to analyse the fourth wave of COVID-19 in Hungary, providing valuable insights into real-world scenarios. By bridging the gap between individual characteristics and epidemic spread, our research contributes to a more comprehensive understanding of disease dynamics and informs effective public health strategies.

Factors affecting the number of influenza patients before and during COVID-19 pandemic, Thailand

This study was aimed to explore the association between potential factors including public health and social measures and the number of influenza patients in Thailand between 2014-2021. Secondary data from relevant agencies were collected. Generalized Estimating Equation (GEE) and regression coefficient (β) were performed at a significance level of 0.05. We found factors associated with number of influenza patients during the time prior to COVID-19 pandemic were monthly income per household (Adjusted β = -0.02; 95% CI: -0.03, -0.01), population density (Adjusted β = 1.00; 95% CI: 0.82, 1.18), rainy season (Adjusted β = 137.15; 95% CI: 86.17, 188.13) and winter time (Adjusted β = 56.46; 95% CI: 3.21, 109.71). During the time of COVID-19 pandemic, population density (Adjusted β = 0.20; 95% CI: 0.15, 0.26), rainy season (Adjusted β = -164.23; 95% CI: -229.93, -98.52), winter time (Adjusted β = 61.06; 95% CI: 0.71, 121.41), public health control measures (prohibition of entering to into an area with high number of COVID-19 infections (Adjusted β = -169.34; 95% CI: -233.52, -105.16), and restriction of travelling also reduced the number of influenza patients (Adjusted β = -66.88; 95% CI: -125.15, -8.62) were associated with number of influenza patients. This study commends strategies in monitoring influenza patients to focus on the areas with low income, high population density, and in specific seasons. Public health and social measures which can be implemented are prohibition of entering to risk-areas (lock down), and restriction of travelling across provinces which their effectiveness in reducing influenza infections.

Lessons learned from COVID-19: improving breast cancer care post-pandemic from the patient perspective

BACKGROUND

Since the onset of the pandemic, breast cancer (BC) services have been disrupted in most countries. The purpose of this qualitative study is to explore the unmet needs, patient-priorities, and recommendations for improving BC healthcare post-pandemic for women with BC and to understand how they may vary based on social determinants of health (SDH), in particular socio-economic status (SES).

METHODS

Thirty-seven women, who were purposively sampled based on SDH and previously interviewed about the impact of COVID-19 on BC, were invited to take part in follow-up semi-structured qualitative interviews in early 2023. The interviews explored their perspectives of BC care since the easing of COVID-19 government restrictions, including unmet needs, patient-priorities, and recommendations specific to BC care. Thematic analysis was conducted to synthesize each topic narratively with corresponding sub-themes. Additionally, variation by SDH was analyzed within each sub-theme.

RESULTS

Twenty-eight women (mean age = 61.7 years, standard deviation (SD) = 12.3) participated in interviews (response rate = 76%). Thirty-nine percent (n = 11) of women were categorized as high-SES, while 61% (n = 17) of women were categorized as low-SES. Women expressed unmet needs in their BC care including routine care and mental and physical well-being care, as well as a lack of financial support to access BC care. Patient priorities included the following: developing cohesion between different aspects of BC care; communication with and between healthcare professionals; and patient empowerment within BC care. Recommendations moving forward post-pandemic included improving the transition from active to post-treatment, enhancing support resources, and implementing telemedicine where appropriate. Overall, women of low-SES experienced more severe unmet needs, which in turn resulted in varied patient priorities and recommendations.

CONCLUSION

As health systems are recovering from the COVID-19 pandemic, the emphasis should be on restoring access to BC care and improving the quality of BC care, with a particular consideration given to those women from low-SES, to reduce health inequalities post-pandemic.

Pharmacy-Based Influenza Vaccination: A Study of Patient Acceptance in Romania

Background

This study explores patient acceptance of influenza vaccination administered by pharmacists in Romania during the 2023 season, considering it a novel strategy to address gaps in knowledge. Pharmacy-based vaccination deviates from traditional methods, providing high-risk patients with full reimbursement and others with 50% reimbursement, allowing a choice between family doctors and pharmacies for vaccine administration.

Material and Method

The survey includes 15 questions covering socio-demographic data, health information, vaccination preferences, and perceptions of pharmacy-based vaccinations.

Results

Respondents showed a positive inclination toward pharmacy-based vaccination, with 68% expressing favorable sentiments, but an awareness gap exists, as only 36% were aware of pharmacy-based vaccination availability.

Conclusion

Challenges include a lack of patient awareness and understanding of benefits, emphasizing the need for structured pharmacist-patient dialogues. Legal changes, a defined funding mechanism, and collaboration are crucial for successful implementation. The study provides valuable insights into patient perceptions, contributing to discussions on optimizing influenza vaccination coverage in Romania and beyond and recognizing pharmacies' potential in achieving broader vaccination goals.

COVID-19 inequalities in England: a mathematical modelling study of transmission risk and clinical vulnerability by socioeconomic status

BACKGROUND

The COVID-19 pandemic resulted in major inequalities in infection and disease burden between areas of varying socioeconomic deprivation in many countries, including England. Areas of higher deprivation tend to have a different population structure-generally younger-which can increase viral transmission due to higher contact rates in school-going children and working-age adults. Higher deprivation is also associated with a higher presence of chronic comorbidities, which were convincingly demonstrated to be risk factors for severe COVID-19 disease. These two major factors need to be combined to better understand and quantify their relative importance in the observed COVID-19 inequalities.

METHODS

We used UK Census data on health status and demography stratified by decile of the Index of Multiple Deprivation (IMD), which is a measure of socioeconomic deprivation. We calculated epidemiological impact using an age-stratified COVID-19 transmission model, which incorporated different contact patterns and clinical health profiles by decile. To separate the contribution of each factor, we considered a scenario where the clinical health profile of all deciles was at the level of the least deprived. We also considered the effectiveness of school closures and vaccination of over 65-year-olds in each decile.

RESULTS

In the modelled epidemics in urban areas, the most deprived decile experienced 9% more infections, 13% more clinical cases, and a 97% larger peak clinical size than the least deprived; we found similar inequalities in rural areas. Twenty-one per cent of clinical cases and 16% of deaths in England observed under the model assumptions would not occur if all deciles experienced the clinical health profile of the least deprived decile. We found that more deaths were prevented in more affluent areas during school closures and vaccination rollouts.

CONCLUSIONS

This study demonstrates that both clinical and demographic factors synergise to generate health inequalities in COVID-19, that improving the clinical health profile of populations would increase health equity, and that some interventions can increase health inequalities.

Socioeconomic inequalities in cardiovascular disease: a causal perspective

Socioeconomic inequalities in cardiovascular disease (CVD) persist in high-income countries despite marked overall declines in CVD-related morbidity and mortality. After decades of research, the field has struggled to unequivocally answer a crucial question: is the association between low socioeconomic position (SEP) and the development of CVD causal? We review relevant evidence from various study designs and disciplinary perspectives. Traditional observational, family-based and Mendelian randomization studies support the widely accepted view that low SEP causally influences CVD. However, results from quasi-experimental and experimental studies are both limited and equivocal. While more experimental and quasi-experimental studies are needed to aid causal understanding and inform policy, high-quality descriptive studies are also required to document inequalities, investigate their contextual dependence and consider SEP throughout the lifespan; no simple hierarchy of evidence exists for an exposure as complex as SEP. The COVID-19 pandemic illustrates the context-dependent nature of CVD inequalities, with the generation of potentially new causal pathways linking SEP and CVD. The linked goals of understanding the causal nature of SEP and CVD associations, their contextual dependence, and their remediation by policy interventions necessitate a detailed understanding of society, its change over time and the phenotypes of CVD. Interdisciplinary research is therefore key to advancing both causal understanding and policy translation.

Heterogeneity of influenza infection at precise scale in Yinchuan, Northwest China, 2012-2022: evidence from Joinpoint regression and spatiotemporal analysis

Identifying high-risk regions and turning points of influenza with a precise spatiotemporal scale may provide effective prevention strategies. In this study, epidemiological characteristics and spatiotemporal clustering analysis at the township level were performed. A descriptive study and a Joinpoint regression analysis were used to explore the epidemiological characteristics and the time trend of influenza. Spatiotemporal autocorrelation and clustering analyses were carried out to explore the spatiotemporal distribution characteristics and aggregation. Furthermore, the hotspot regions were analyzed by spatiotemporal scan analysis. A total of 4025 influenza cases were reported in Yinchuan showing an overall increasing trend. The tendency of influenza in Yinchuan consisted of three stages: increased from 2012 to the first peak in 2019 (32.62/100,000) with a slight decrease in 2016; during 2019 and 2020, the trend was downwards; then it increased sharply again and reached another peak in 2022. The Joinpoint regression analysis found that there were three turning points from January 2012 to December 2022, namely January 2020, April 2020, and February 2022. The children under ten displayed an upward trend and were statistically significant. The trend surface analysis indicated that there was a shifting trend from northern to central and southern. A significant positive spatial auto-correlation was observed at the township level and four high-incidence clusters of influenza were detected. These results suggested that children under 10 years old deserve more attention and the spatiotemporal distribution of high-risk regions of influenza in Yinchuan varies every year at the township level. Thus, more monitoring and resource allocation should be prone to the four high-incidence clusters, which may benefit the public health authorities to carry out the vaccination and health promotion timely.

What can we learn from historical pandemics? A systematic review of the literature

What are the insights from historical pandemics for policymaking today? We carry out a systematic review of the literature on the impact of pandemics that occurred since the Industrial Revolution and prior to Covid-19. Our literature searches were conducted between June 2020 and September 2023, with the final review encompassing 169 research papers selected for their relevance to understanding either the demographic or economic impact of pandemics. We include literature from across disciplines to maximise our knowledge base, finding many relevant articles in journals which would not normally be on the radar of social scientists. Our review identifies two gaps in the literature: (1) the need to study pandemics and their effects more collectively rather than looking at them in isolation; and (2) the need for more study of pandemics besides 1918 Spanish Influenza, especially milder pandemic episodes. These gaps are a consequence of academics working in silos, failing to draw on the skills and knowledge offered by other disciplines. Synthesising existing knowledge on pandemics in one place provides a basis upon which to identify the lessons in preparing for future catastrophic disease events.

Socioeconomic mortality differences during the Great Influenza in Spain

Despite being one of the deadliest viruses in history, there is limited information on the socioeconomic factors that affected mortality rates during the Great Influenza Pandemic. In this study, we use occupation-province level data to investigate the relationship between influenza excess mortality rates and occupation-related status in Spain. We obtain three main results. Firstly, individuals in low-income occupations experienced the highest excess mortality, pointing to a notable income gradient. Secondly, professions that involved more social interaction were associated with a higher excess of mortality, regardless of income. Finally, we observe a substantial rural mortality penalty, even after controlling for income-related occupational groups. Based on this evidence, it seems that the high number of deaths was caused by not self-isolating. Some individuals did not quarantine themselves because they could not afford to miss work. In rural areas, home confinement was likely more limited because their inhabitants did not have immediate access to information about the pandemic or fully understand its impact due to their limited experience handling influenza outbreaks.

Dynamics of viral disease outbreaks: A hundred years (1918/19-2019/20) in retrospect - Loses, lessons and emerging issues

Infectious diseases continue to be the leading cause of morbidity and mortality, and a formidable obstacle to the development and well-being of people worldwide. Viruses account for more than half of infectious disease outbreaks that have plagued the world. The past century (1918/19-2019/20) has witnessed some of the worst viral disease outbreaks the world has recorded, with overwhelming impact especially in low- and middle-income countries (LMIC). The frequency of viral disease outbreak appears to be increasing. Generally, although infectious diseases have afflicted the world for centuries and humankind has had opportunities to examine the nature of their emergence and mode of spread, almost every new outbreak poses a formidable challenge to humankind, beating the existing pandemic preparedness systems, if any, and causing significant losses. These underscore inadequacy in our understanding of the dynamics and preparedness against viral disease outbreaks that lead to epidemics and pandemics. Despite these challenges, the past 100 years of increasing frequencies of viral disease outbreaks have engendered significant improvements in response to epidemics and pandemics, and offered lessons to inform preparedness. Hence, the increasing frequency of emergence of viral outbreaks and the challenges these outbreaks pose to humankind, call for the continued search for effective ways to tackle viral disease outbreaks in real time. Through a PRISMA-based approach, this systematic review examines the outbreak of viral diseases in retrospect to decipher the outbreak patterns, losses inflicted on humanity and highlights lessons these offer for meaningful preparation against future viral disease outbreaks and pandemics.

Spatial distribution and driving factors of the associations between temperature and influenza-like illness in the United States: a time-stratified case-crossover study

BACKGROUND

Several previous studies investigated the associations between temperature and influenza in a single city or region without a national picture. The attributable risk of influenza due to temperature and the corresponding driving factors were unclear. This study aimed to evaluate the spatial distribution characteristics of attributable risk of Influenza-like illness (ILI) caused by adverse temperatures and explore the related driving factors in the United States.

METHODS

ILI, meteorological factors, and PM_2.5 of 48 states in the United States were collected during 2011-2019. The time-stratified case-crossover design with a distributed lag non-linear model was carried out to evaluate the association between temperature and ILI at the state level. The multivariate meta-analysis was performed to obtain the combined effects at the national level. The attributable fraction (AF) was calculated to assess the ILI burden ascribed to adverse temperatures. The ordinary least square model (OLS), spatial lag model (SLM), and spatial error model (SEM) were utilized to identify driving factors.

RESULTS

A total of 7,716,115 ILI cases were included in this study. Overall, the temperature was negatively associated with ILI risk, and lower temperature gave rise to a higher risk of ILI. AF ascribed to adverse temperatures differed across states, from 49.44% (95% eCI: 36.47% ~ 58.68%) in Montana to 6.51% (95% eCI: -6.49% ~ 16.46%) in Wisconsin. At the national level, 29.08% (95% eCI: 27.60% ~ 30.24%) of ILI was attributable to cold. Per 10,000 dollars increase in per-capita income was associated with the increment in AF (OLS: β = -6.110, P = 0.021; SLM: β = -5.496, P = 0.022; SEM: β = -6.150, P = 0.022).

CONCLUSION

The cold could enhance the risk of ILI and result in a considerable proportion of ILI disease burden. The ILI burden attributed to cold varied across states and was higher in those states with lower economic status. Targeted prevention programs should be considered to lower the burden of influenza.

COVID-19 pandemic and socio-environmental inequality: A narrative review

Background and Aims

The COVID-19 pandemic has provided preliminary evidence of the existence of health, social, and environmental inequalities. This inequality encompasses inadequate access to safe water, clean air, and wastewater management, as well as limited socioeconomic and educational opportunities. These issues have not received sufficient attention during the pandemic. The purpose of this narrative review is to provide a comprehensive summary and analysis of the existing literature on a specific topic, ultimately leading to a conclusion based on the evidence presented.

Methods

The search methodology for this study involved conducting comprehensive searches of scientific databases, including PubMed, ScienceDirect, LILACS, and Google Scholar, from 2019 to 2023. The study focused on a specific theme and its relevant aspects related to global environmental health and society. Keywords such as COVID-19, inequities, and environmental health were used for searching. Additionally, the Boolean operator "AND" was used to combine these descriptors.

Results

Unequal exposure to air pollution has been reported in Africa, as well as in large parts of Asia and Latin America, according to the data that has been obtained. The pandemic has also resulted in a surge in healthcare waste generation, exacerbating the environmental impact of solid waste. Furthermore, there is evidence indicating significant disparities in the severe lack of access to sanitation services between developing nations and low-income regions. The issues related to water availability, accessibility, and quality are subject to debate. It has been reported that SARS-CoV-2 is present not only in untreated/raw water, but also in water bodies that act as reservoirs. Moreover, insufficient education, poverty, and low household income have been identified as the most significant risk factors for COVID-19 infection and mortality.

Conclusion

It is evident that addressing socio-environmental inequality and striving to narrow the gap by prioritizing vulnerable populations are imperative.

Reinfections and Cross-Protection in the 1918/19 Influenza Pandemic: Revisiting a Survey Among Male and Female Factory Workers

Objectives: The COVID-19 pandemic highlights questions regarding reinfections and immunity resulting from vaccination and/or previous illness. Studies addressing related questions for historical pandemics are limited. Methods: We revisit an unnoticed archival source on the 1918/19 influenza pandemic. We analysed individual responses to a medical survey completed by an entire factory workforce in Western Switzerland in 1919. Results: Among the total of n = 820 factory workers, 50.2% reported influenza-related illness during the pandemic, the majority of whom reported severe illness. Among male workers 47.4% reported an illness vs. 58.5% of female workers, although this might be explained by varied age distribution for each sex (median age was 31 years old for men, vs. 22 years old for females). Among those who reported illness, 15.3% reported reinfections. Reinfection rates increased across the three pandemic waves. The majority of subsequent infections were reported to be as severe as the first infection, if not more. Illness during the first wave, in the summer of 1918, was associated with a 35.9% (95%CI, 15.7-51.1) protective effect against reinfections during later waves. Conclusion: Our study draws attention to a forgotten constant between multi-wave pandemics triggered by respiratory viruses: Reinfection and cross-protection have been and continue to be a key topic for health authorities and physicians in pandemics, becoming increasingly important as the number of waves increases.

Wildfire-related PM2.5 and health economic loss of mortality in Brazil

BACKGROUND

Wildfire imposes a high mortality burden on Brazil. However, there is a limited assessment of the health economic losses attributable to wildfire-related fine particulate matter (PM_2.5).

METHODS

We collected daily time-series data on all-cause, cardiovascular, and respiratory mortality from 510 immediate regions in Brazil during 2000-2016. The chemical transport model GEOS-Chem driven with Global Fire Emissions Database (GFED), in combination with ground monitored data and machine learning was used to estimate wildfire-related PM_2.5 data at a resolution of 0.25° × 0.25°. A time-series design was applied in each immediate region to assess the association between economic losses due to mortality and wildfire-related PM_2.5 and the estimates were pooled at the national level using a random-effect meta-analysis. We used a meta-regression model to explore the modification effect of GDP and its sectors (agriculture, industry, and service) on economic losses.

RESULTS

During 2000-2016, a total of US$81.08 billion economic losses (US$5.07 billion per year) due to mortality were attributable to wildfire-related PM_2.5 in Brazil, accounting for 0.68% of economic losses and equivalent to approximately 0.14% of Brazil's GDP. The attributable fraction (AF) of economic losses due to wildfire-related PM_2.5 was positively associated with the proportion of GDP from agriculture, while negatively associated with the proportion of GDP from service.

CONCLUSION

Substantial economic losses due to mortality were associated with wildfires, which could be influenced by the agriculture and services share of GDP per capita. Our estimates of the economic losses of mortality could be used to determine optimal levels of investment and resources to mitigate the adverse health impacts of wildfires.

Psychology Meets Biology in COVID-19: What We Know and Why It Matters for Public Health

Psychosocial factors are related to immune, viral, and vaccination outcomes. Yet, this knowledge has been poorly represented in public health initiatives during the COVID-19 pandemic. This review provides an overview of biopsychosocial links relevant to COVID-19 outcomes by describing seminal evidence about these associations known prepandemic as well as contemporary research conducted during the pandemic. This focuses on the negative impact of the pandemic on psychosocial health and how this in turn has likely consequences for critically relevant viral and vaccination outcomes. We end by looking forward, highlighting the potential of psychosocial interventions that could be leveraged to support all people in navigating a postpandemic world and how a biopsychosocial approach to health could be incorporated into public health responses to future pandemics.

Social and demographic patterns of influenza vaccination coverage in Norway, influenza seasons 2014/15 to 2020/21

AIMS

To examine influenza vaccination coverage among risk groups (RG) and health care workers (HCW), and study social and demographic patterns of vaccination coverage over time.

METHODS

Vaccination coverage was estimated by self-report in a nationally representative telephone survey among 14919 individuals aged 18-79 years over seven influenza seasons from 2014/15 to 2020/21. We explored whether belonging to an influenza RG (being >=65 years of age and/or having >=1 medical risk factor), being a HCW or educational attainment was associated with vaccination status using logistic regression.

RESULTS

Vaccination coverage increased from 27 % to 66 % among individuals 65-79 years, from 13 % to 33 % among individuals 18-64 years with >=1 risk factor, and from 9 % to 51 % among HCWs during the study period. Being older, having a risk factor or being a HCW were significantly associated with higher coverage in all multivariable logistic regression analyses. Higher education was also consistently associated with higher coverage, but the difference did not reach significance in all influenza seasons. Educational attainment was not significantly associated with coverage while coverage was at its lowest (2014/15-2017/18), but as coverage increased, so did the differences. Individuals with intermediate or lower education were less likely to report vaccination than those with higher education in season 2018/19, OR = 0.61 (95 % CI 0.46-0.80) and OR = 0.58 (95 % CI 0.41-0.83), respectively, and in season 2019/20, OR = 0.69 (95 % CI 0.55-0.88) and OR = 0.71 (95 % CI 0.53-0.95), respectively. When the vaccine was funded in the COVID-19 pandemic winter of 2020/21, educational differences diminished again and were no longer significant.

CONCLUSIONS

We observed widening educational differences in influenza vaccination coverage as coverage increased from 2014/15 to 2019/20. When influenza vaccination was funded in 2020/21, differences in coverage by educational attainment diminished. These findings indicate that economic barriers influence influenza vaccination decisions among risk groups in Norway.

Individual and household risk factors for COVID-19 infection among household members of COVID-19 patients in home-based care in western Uganda, 2020

OBJECTIVE

To investigate factors associated with COVID-19 among household members of patients in home-based care (HBC) in western Uganda.

METHODS

We conducted a case-control and cohort study. Cases were reverse transcriptase-polymerase chain reaction-confirmed SARS-CoV-2 diagnosed 1-30 November 2020 among persons in HBC in Kasese or Kabarole districts. We compared 78 case-households (≥1 secondary case) with 59 control-households (no secondary cases). The cohort included all case-household members. Data were captured by in-person questionnaire. We used bivariate regression to calculate odds and risk ratios.

RESULTS

Case-households were larger than control-households (mean 5.8 vs 4.3 members, P<0.0001). Having ≥1 household member per room (adjusted odds ratio (aOR)=4.5, 95% CI 2.0-9.9), symptom development (aOR=2.3, 95% CI 1.1-5.0), or interaction with primary case-patient (aOR=4.6, 95% CI 1.4-14.7) increased odds of case-household status. Households assessed for suitability for HBC reduced odds of case-household status (aOR=0.4, 95% CI=0.2-0.8). Interacting with a primary case-patient increased the risk of individual infection among household members (adjusted risk ratio=1.7, 95% CI 1.1-2.8).

CONCLUSION

Household and individual factors influence secondary infection risk in HBC. Decisions about HBC should be made with these in mind.

Aetiological and prognostic roles of frailty, multimorbidity and socioeconomic characteristics in the development of SARS-CoV-2 health outcomes: protocol for systematic reviews of population-based studies

INTRODUCTION

There is growing evidence that the impact of COVID-19 crisis may be stronger for individuals with multimorbidity, frailty and lower socioeconomic status. Existing reviews focus on few, mainly short-term effects of COVID-19 illness and patients with single chronic disease. Information is also largely missing for population representative samples.Applying population-based approach, the systematic reviews will have two objectives: (1) to evaluate the aetiological roles of frailty, multimorbidity and socioeconomic status on SARS-CoV-2 infection probability, hospitalisation, intensive care unit (ICU) admission, mechanical ventilation and COVID-19 related mortality among general population and (2) to investigate the prognostic roles of frailty, multimorbidity and socioeconomic characteristics on the risk of hospitalisation, ICU admission, mechanical ventilation, COVID-19 mortality, functioning, quality of life, disability, mental health and work absence.

METHODS AND ANALYSIS

For this ongoing work, four databases were searched: PubMed, Embase, WHO COVID-19 Global literature on coronavirus disease and PsycINFO, for the period between January 2020 and April 7 2021. Peer-reviewed published literature in English and all types of population-based studies will be considered. Studies using standard tools to assess multimorbidity such as disease count, comorbidity indices or disease combinations will be retained, as well as studies with standard scales and scores for frailty or measurement of a socioeconomic gradient. Initial search included 10 139 articles, 411 for full-text reading. Results will be summarised by risk factor, objective and outcome. The feasibility of meta-analysis will be determined by the findings and will aim to better understand uncertainties of the results. Quality of studies will be assessed using standardised scales.

ETHICS AND DISSEMINATION

The study will be based on published evidence, and it is exempt from the ethical approval. This work is part of the Population Health Information Research Infrastructure (PHIRI) project. Dissemination of the results will imply conference presentation, submission for scientific publication and PHIRI project report.

PROSPERO REGISTRATION NUMBER

CRD42021249444.

Trained Immunity as a Prospective Tool against Emerging Respiratory Pathogens

Although parental vaccines offer long-term protection against homologous strains, they rely exclusively on adaptive immune memory to produce neutralizing antibodies that are ineffective against emerging viral variants. Growing evidence highlights the multifaceted functions of trained immunity to elicit a rapid and enhanced innate response against unrelated stimuli or pathogens to subsequent triggers. This review discusses the protective role of trained immunity against respiratory pathogens and the experimental models essential for evaluating novel inducers of trained immunity. The review further elaborates on the potential of trained immunity to leverage protection against pathogens via the molecular patterns of antigens by pathogen recognition receptors (PPRs) on innate immune cells. The review also focuses on integrating trained innate memory with adaptive memory to shape next-generation vaccines by coupling each one's unique characteristics.

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.

Assessment of Serum Zinc and Selenium Levels in Children with COVID-19

Objective Zinc and selenium levels are being investigated with increasing frequency in adult patients with coronavirus disease 2019 (COVID-19). However, levels of zinc and selenium in children with COVID-19 have not been adequately studied to date.

Methods This prospective, observational study was conducted on 146 pediatric patients diagnosed with COVID-19 and 49 healthy controls between 2020 and 2021. Normal serum zinc reference values were 0.60 to 1.20 µg/mL for children 0 to 10 years old and 0.66 to 1.10 µg/mL for children ≥11 years old. The normal range for serum selenium concentration was considered between 70 and 150 µg/L. Deficiencies were defined for values below the reference range.

Results Zinc and selenium levels were significantly lower in the COVID-19 (+) group compared with the controls (zinc: 0.7 ± 0.2 vs 0.9 ± 0.2 µg/mL, p < 0.001; selenium: 57.1 ± 9.1 vs 66.5 ± 11.4 µg/L, p < 0.01, respectively). Also, zinc and selenium levels were found to be statistically significantly lower in the hospitalized group compared with the outpatient group (zinc: 0.6 ± 0.2 vs 0.8 ± 0.2 µg/mL, p < 0.001; selenium: 52.1 ± 9.6 vs 58.8 ± 8.3 µg/L, p < 0.001). In the receiver operating characteristic curve analysis, selenium levels with a cutoff value of 55.50 µg/L, with 75% sensitivity and 70% specificity, and zinc levels with a cutoff value of 0.7 µg/mL, with 56% sensitivity and 53% specificity, predicted hospitalization.

Conclusion Our data showed that serum zinc and selenium levels were significantly lower in patients with COVID-19 compared with healthy control group. Also, zinc and selenium levels were found to be lower in the hospitalized group compared with the outpatient COVID-19 group.

Neuropsychiatric outcomes in offspring after fetal exposure to maternal influenza infection during pregnancy: A systematic review

Increasing evidence suggests that influenza infection in pregnancy may disrupt fetal neurodevelopment. The impact of maternal influenza infection on offspring neuropsychiatric health has not been comprehensively reviewed. We systematically reviewed comparative studies evaluating associations between maternal influenza infection and neuropsychiatric health outcomes in offspring. We searched MEDLINE, EMBASE, CINAHL, and Web of Science for articles published until January 7, 2022. Included were English studies evaluating neuropsychiatric outcomes in offspring aged > 6 months born to women with and without influenza during pregnancy, defined as clinical or laboratory-confirmed influenza illness, or being pregnant during pandemics/epidemics. Of 12,010 records screened, 42 studies were included. Heterogeneity in study design, exposures, and outcome definitions precluded meta-analyses. Four of 14 studies assessing schizophrenia reported adjusted ratio estimates from 0.5 to 8.2; most 95% CIs contained the null value; study quality was high in three of four. Two studies reported an increased risk of schizophrenia with influenza exposure any time during pregnancy (adjusted incidence rate ratio 8.2, 95% CI: 1.4-48.8; adjusted odds ratio 1.3, 95% CI: 1.2-1.5); another reported a reduced risk with first-trimester exposure (adjusted risk ratio 0.5, 95% CI: 0.3-0.9). Seven studies of autism spectrum disorder reported adjusted ratio estimates from 0.9 to 4.0; all 95% CIs included the null value; study quality was high in four. No conclusions could be drawn about the association between exposure to maternal influenza and neuropsychiatric outcomes due to the limited quantity and quality of available research. Large observational studies with long-term follow-up are required to investigate these associations.

Vitamin D Deficiency and Comorbidities as Risk Factors of COVID-19 Infection: A Systematic Review and Meta-analysis

OBJECTIVES

Extensive evidence links low vitamin D status and comorbidities with coronavirus disease 2019 (COVID-19) outcomes, but the results of published studies are contradictory. Therefore, we investigated the association of lower levels of vitamin D and comorbidities with the risk of COVID-19 infection.

METHODS

We searched MEDLINE (via PubMed), Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov for articles published until August 20, 2021. Sixteen eligible studies were identified (386 631 patients, of whom 181 114 were male). We included observational cohort and case-control studies that evaluated serum levels of vitamin D in COVID-19-positive and COVID-19-negative patients. Mean differences (MDs) with 95% confidence intervals (CIs) were calculated.

RESULTS

Significantly lower vitamin D levels were found in COVID-19-positive patients (MD, -1.70; 95% CI, -2.74 to -0.66; p=0.001), but with variation by study design (case-control: -4.04; 95% CI, -5.98 to -2.10; p<0.001; cohort: -0.39; 95% CI, -1.62 to 0.84; p=0.538). This relationship was more prominent in female patients (MD, -2.18; 95% CI, -4.08 to -0.28; p=0.024) than in male patients (MD, -1.74; 95% CI, -3.79 to 0.31; p=0.096). Male patients showed higher odds of having low vitamin D levels (odds ratio [OR], 2.09; 95% CI, 1.38 to 3.17; p<0.001) than female patients (OR, 1.17; 95% CI, 0.74 to 1.86; p=0.477). Comorbidities showed inconsistent, but generally non-significant, associations with COVID-19 infection.

CONCLUSIONS

Low serum vitamin-D levels were significantly associated with the risk of COVID-19 infection. This relationship was stronger in female than in male COVID-19 patients. Limited evidence was found for the relationships between comorbidities and COVID-19 infection, warranting large population-based studies to clarify these associations.

Addressing the socioeconomic divide in computational modeling for infectious diseases

The COVID-19 pandemic has highlighted how structural social inequities fundamentally shape disease dynamics. Here, the authors provide a set of practical and methodological recommendations to address socioeconomic vulnerabilities in epidemic models.

Identification of Barriers Limiting the Use of Preventive Vaccinations against Influenza among the Elderly Population: A Cross-Sectional Analysis

Older adults are at a high risk of experiencing severe complications of influenza. Receiving a vaccination is a beneficial strategy to prevent the disease and reduce the severity of influenza illnesses. This cross-sectional questionnaire-based study aimed to evaluate the influence of sociodemographic, clinical, and mental parameters as well as other potential risk factors on refusal to vaccinate against influenza among the elderly population in Poland. Furthermore, due to the prevailing COVID-19 pandemic, we put efforts into finding any statistical correlations between the fear of COVID-19 infection in patients and their attitudes toward receiving an influenza vaccination. The study was conducted in November−December 2020 in Poland on a representative nationwide sample of 500 individuals aged > 60. Of the respondents, 62 (12.4%) and 51 (10.2%) underwent influenza vaccination in 2019 and 2020, respectively. Out of ten different factors analyzed in this study, three were significantly associated with attitudes towards influenza vaccination. Participants with net income below the national average of PLN 3000 (OR = 2.37, CI 95% [1.26−4.47]), compared to those earning more than PLN 3000, had significantly higher odds of having a negative attitude towards influenza vaccination. Furthermore, respondents with <174 cm height (OR = 2.56, CI 95% [1.51−4.33]) and those with strong fear of COVID-19 infection (OR = 1.65, CI95% [1.02−2.66]) were also more likely to refrain from influenza vaccination. We believe the identification of factors limiting the willingness to receive influenza vaccination is an effective way to help clinicians focus their efforts on educating the groups of patients with the highest odds of refusing to receive the vaccine. Moreover, it may aid the design and enforcement of national solutions or the implementation of novel legislative measures and preventive programs, increasing public confidence and promoting vaccination, especially among groups at high risk of developing this disease.

Surveillance of COVID-19 outbreaks in prisons in the US South: The role of economic distress in the communities surrounding prison facilities

Introduction:

The US South is the epicenter of the epidemic of mass incarceration. Prisons have experienced substantial challenges in preventing COVID-19. Incarcerated individuals and prison staff are at a high risk for infection due to minimal available preventive measures. Prisons are not closed systems and many staff come from communities in close proximity to the facility. Characteristics of the communities immediately surrounding prisons are an overlooked but critical factor to better understand the role prisons play in pandemics.

Methods:

We used facility-level COVID-19 data from the COVID Prison Project to identify the number of unique outbreaks between May 2019 and May 2020. We used a county-level composite indicator of economic distress (DCI score) to identify the environment surrounding each prison (2015–2019). We modeled the number of outbreaks to DCI scores using negative binomial regression, adjusting for race/ethnicity (African American and Latino/Hispanic), age (65 and older), and rurality level.

Results:

Our sample included 570 prisons in 368 counties across 13 Southern states. We found that score was positively and significantly associated with prison COVID-19 outbreaks (aRR, 1.012; p < 0.0001), and rurality was potentially a stronger surrogate measure of economic distress (aRR, 1.35; p, 0.02). Economic stability is a key precursor to physical health. Poorer communities have been disproportionately impacted by the pandemic, and we found that prisons located in these communities were more susceptible to recurring outbreaks. Prison-based disease prevention interventions should consider the impact that the outside world has on the health of incarcerated individuals.

Factors associated with vaccine intention in adults living in England who either did not want or had not yet decided to be vaccinated against COVID-19

Early studies showed that 28-36% of UK adults were unsure or unwilling to be vaccinated against COVID-19. We wanted to identify which socio-demographic, socio-economic, personal health and psychological factors were associated with COVID-19 vaccine intentions (CVI) in adults living in England who did not want, yet to consider, or not sure whether to vaccinate. In October/November 2020, prior to vaccine availability, we surveyed adults stratified by gender, region, and deprivation, with additional purposive sampling of those aged 50 and over and those from an ethnic minority. Two hundred and ten did not want; 407 had yet to consider; and 1,043 were not sure whether to be vaccinated. Factors positively associated with CVI were: favorable vaccine views, trust in institutions associated with vaccine approval, vaccine subjective norms, anticipated regret of not having a vaccine, perceived vaccine benefits, perceived safety knowledge sufficiency, and a history of having an influenza vaccine. Factors negatively associated were: anti-lockdown views, and being a health or social care worker. Whilst showing significant relationships with CVI when analyzed in isolation, neighborhood deprivation and ethnicity did show an independent relationship to intention when all study measures were controlled for. Our findings suggest vaccine promotion focusing on the anticipated regret of not having a vaccine, the benefits of a mass COVID-19 immunization program, and the safety of a vaccine whilst ensuring or engendering trust in those bodies that brand a campaign may be most supportive of COVID-19 vaccine uptake.