Association Between Vaccination Coverage Disparity and the Dynamics of the COVID-19 Delta and Omicron Waves in the US

Associations between COVID-19 therapies and outcomes in rural and urban America: A multisite, temporal analysis from the Alpha to Omicron SARS-CoV-2 variants

PURPOSE

To investigate the enduring disparities in adverse COVID-19 events between urban and rural communities in the United States, focusing on the effects of SARS-CoV-2 vaccination and therapeutic advances on patient outcomes.

METHODS

Using National COVID Cohort Collaborative (N3C) data from 2021 to 2023, this retrospective cohort study examined COVID-19 hospitalization, inpatient death, and other adverse events. Populations were categorized into urban, urban-adjacent rural (UAR), and nonurban-adjacent rural (NAR). Adjustments included demographics, variant-dominant waves, comorbidities, region, and SARS-CoV-2 treatment and vaccination. Statistical methods included Kaplan-Meier survival estimates, multivariable logistic, and Cox regression.

FINDINGS

The study included 3,018,646 patients, with rural residents constituting 506,204. These rural dwellers were older, had more comorbidities, and were less vaccinated than their urban counterparts. Adjusted analyses revealed higher hospitalization odds in UAR and NAR (aOR 1.07 [1.05-1.08] and 1.06 [1.03-1.08]), greater inpatient death hazard (aHR 1.30 [1.26-1.35] UAR and 1.37 [1.30-1.45] NAR), and greater risk of other adverse events compared to urban dwellers. Delta increased, while Omicron decreased, inpatient adverse events relative to pre-Delta, with rural disparities persisting throughout. Treatment effectiveness and vaccination were similarly protective across all cohorts, but dexamethasone post-ventilation was effective only in urban areas. Nirmatrelvir/ritonavir and molnupiravir better protected rural residents against hospitalization.

CONCLUSIONS

Despite advancements in treatment and vaccinations, disparities in adverse COVID-19 outcomes persist between urban and rural communities. The effectiveness of some therapeutic agents appears to vary based on rurality, suggesting a nuanced relationship between treatment and geographic location while highlighting the need for targeted rural health care strategies.

COVID-Related Discrimination and Health Care Access among a Nationally Representative, Diverse Sample of US Adults

BACKGROUND

In the United States, COVID-related discrimination towards racial and ethnic minority populations is well documented; however, its impact on healthcare access during the pandemic has not been assessed.

METHODS

We used data from our nationally representative, online survey of 5,500 American Indian/Alaska Native (AIAN), Asian, Black, Native Hawaiian/Pacific Islander, Latino, White, and multiracial adults conducted between 12/2020-2/2021 (baseline) and 8/2021-9/2021 (6-month follow-up; 35.1% response rate). At baseline, participants were asked how often they experienced discriminatory behaviors "because they think you might have COVID-19" (modified Everyday Discrimination Scale). Participants were asked if they were unable to get needed health care (e.g., cancer screening), or COVID-19 testing at both time-points. Vaccine willingness was assessed at baseline and uptake at follow-up.

RESULTS

Experiencing COVID-related discrimination was associated with not being able to get health care at baseline (OR = 3.66, 95% CI = 2.91-4.59) and follow-up (OR = 1.86, 95% CI = 1.16-2.97) and not being able to get a COVID-19 test at baseline (OR = 2.11, 95% CI = 1.68-2.65) and follow-up (OR = 4.12, 95% CI = 2.20-7.72). Experiencing discrimination was also associated with being less likely to have received a COVID-19 vaccine (OR = 0.52, 95% CI = 0.30-0.90), despite individuals who experienced discrimination being more willing to vaccinate at baseline (OR = 1.56, 95% CI = 1.10-2.22).

CONCLUSIONS

COVID-related discrimination was associated with an increased likelihood of being unable to get health care across all racial and ethnic populations, although associations were strongest among Asian, AIAN, and Latino adults. Healthcare providers should be aware of the impact of discrimination on healthcare utilization, delays, and health-seeking behaviors, especially among racial and ethnic minorities.

Prediction models for COVID-19 disease outcomes

SARS-CoV-2 has caused over 6.9 million deaths and continues to produce lasting health consequences. COVID-19 manifests broadly from no symptoms to death. In a retrospective cross-sectional study, we developed personalized risk assessment models that predict clinical outcomes for individuals with COVID-19 and inform targeted interventions. We sequenced viruses from SARS-CoV-2-positive nasopharyngeal swab samples between July 2020 and July 2022 from 4450 individuals in Missouri and retrieved associated disease courses, clinical history, and urban-rural classification. We integrated this data to develop machine learning-based predictive models to predict hospitalization, ICU admission, and long COVID.The mean age was 38.3 years (standard deviation = 21.4) with 55.2% (N = 2453) females and 44.8% (N = 1994) males (not reported, N = 4). Our analyses revealed a comprehensive set of predictors for each outcome, encompassing human, environment, and virus genome-wide genetic markers. Immunosuppression, cardiovascular disease, older age, cardiac, gastrointestinal, and constitutional symptoms, rural residence, and specific amino acid substitutions were associated with hospitalization. ICU admission was associated with acute respiratory distress syndrome, ventilation, bacterial co-infection, rural residence, and non-wild type SARS-CoV-2 variants. Finally, long COVID was associated with hospital admission, ventilation, and female sex.Overall, we developed risk assessment models that offer the capability to identify patients with COVID-19 necessitating enhanced monitoring or early interventions. Of importance, we demonstrate the value of including key elements of virus, host, and environmental factors to predict patient outcomes, serving as a valuable platform in the field of personalized medicine with the potential for adaptation to other infectious diseases.

Excess Death Rates by State During the COVID-19 Pandemic: United States, 2020‒2023

Objectives. To estimate state-level excess death rates during 2020 to 2023 and examine differences by region and partisan orientation. Methods. We modeled death and population counts from the Centers for Disease Control and Prevention to estimate excess death rates for the United States, 9 census divisions, and 50 states. We compared excess death rates for states with different partisan orientations, measured by the party of the seated governor and the level of partisan representation in state legislatures. Results. The United States experienced 1 277 697 excess deaths between March 2020 and July 2023. Almost 90% of these deaths were attributed to COVID-19, and 51.5% occurred after vaccines were available. The highest excess death rates first occurred in the Northeast and then shifted to the South and Mountain states. Between weeks ending June 20, 2020, through March 19, 2022, excess death rates were higher in states with Republican governors and greater Republican representation in state legislatures. Conclusions. Excess death rates during the COVID-19 pandemic varied considerably across the US states and were associated with partisan representation in state government, although the influence of confounding variables cannot be excluded. (Am J Public Health. 2024;114(9):882-891. https://doi.org/10.2105/AJPH.2024.307731).

Motivators and mechanisms for an international rural health collaboration

Collaborations are critical to address rural health challenges. We evaluated a new international collaboration between institutions in Georgia, the United States (US), and Scotland, United Kingdom (UK), to address rural health issues and to understand the barriers and facilitators to effective international collaboration efforts. A qualitative approach was used through in-depth interviews and focus groups with educators, researchers, and healthcare providers in the US and Scotland who were involved in the CONVERGE international rural health collaboration. Transcriptions were imported into the NVivo qualitative software program. A reflexive thematic analysis was employed to identify key themes from the collected data. Twelve interviews and two focus groups were conducted virtually with 17 participants. Two primary domains were identified from the thematic analysis: (1) motivators that increase engagement in international collaboration, and (2) mechanisms for, and barriers to, the continuity needed to create meaningful change. Six themes emerged related to commonality of issues, prospect of sharing knowledge, need of sustained funding and institutional support, and selection of human resources. Participants of CONVERGE were more likely to engage when they had a space to share ways to address challenging issues and integrate knowledge and practice. They were motivated by their desire for growth and the institutions they serve and emphasized that infrastructure support is vital for sustainable collaborations.

Tracking the Uneven Outcomes of COVID-19 on Racial and Ethnic Groups: Implications for Health Policy

The socioeconomic shocks of the first COVID-19 pandemic wave disproportionately affected vulnerable groups. But did that trend continue to hold during the Delta and Omicron waves? Leveraging data from the Johns Hopkins Coronavirus Resource Center, this paper examines whether demographic inequalities persisted across the waves of COVID-19 infections. The current study utilizes fixed effects regressions to isolate the marginal relationships between socioeconomic factors with case counts and death counts. Factors include levels of urbanization, age, gender, racial distribution, educational attainment, and household income, along with time- and state-specific COVID-19 restrictions and other time invariant controls captured via fixed effects controls. County-level health outcomes in large metropolitan areas show that despite higher incidence rates in suburban and exurban counties, urban counties still had disproportionately poor outcomes in the latter COVID-19 waves. Policy makers should consider health disparities when developing long-term public health regulatory policies to help shield low-income households from the adverse effects of COVID-19 and future pandemics.

A Study Examining the Impact of County-Level Demographic, Socioeconomic, and Political Affiliation Characteristics on COVID-19 Vaccination Patterns in Indiana

The COVID-19 vaccination campaign resulted in uneven vaccine uptake throughout the United States, particularly in rural areas, areas with socially and economically disadvantaged groups, and populations that exhibited vaccine hesitancy behaviors. This study examines how county-level sociodemographic and political affiliation characteristics differentially affected patterns of COVID-19 vaccinations in the state of Indiana every month in 2021. We linked county-level demographics from the 2016-2020 American Community Survey Five-Year Estimates and the Indiana Elections Results Database with county-level COVID-19 vaccination counts from the Indiana State Department of Health. We then created twelve monthly linear regression models to assess which variables were consistently being selected, based on the Akaike Information Criterion (AIC) and adjusted R-squared values. The vaccination models showed a positive association with proportions of Bachelor's degree-holding residents, of 40-59 year-old residents, proportions of Democratic-voting residents, and a negative association with uninsured and unemployed residents, persons living below the poverty line, residents without access to the Internet, and persons of Other Race. Overall, after April, the variables selected were consistent, with the model's high adjusted R2 values for COVID-19 cumulative vaccinations demonstrating that the county sociodemographic and political affiliation characteristics can explain most of the variation in vaccinations. Linking county-level sociodemographic and political affiliation characteristics with Indiana's COVID-19 vaccinations revealed inherent inequalities in vaccine coverage among different sociodemographic groups. Increased vaccine uptake could be improved in the future through targeted messaging, which provides culturally relevant advertising campaigns for groups less likely to receive a vaccine, and increasing access to vaccines for rural, under-resourced, and underserved populations.

Convergence of HIV and non-communicable disease epidemics: geospatial mapping of the unmet health needs in an HIV hyperendemic community in South Africa

INTRODUCTION

As people living with HIV (PLHIV) are experiencing longer survival, the co-occurrence of HIV and non-communicable diseases has become a public health priority. In response to this emerging challenge, we aimed to characterise the spatial structure of convergence of chronic health conditions in an HIV hyperendemic community in KwaZulu-Natal, South Africa.

METHODS

In this cross-sectional study, we used data from a comprehensive population-based disease survey conducted in KwaZulu-Natal, South Africa, which collected data on HIV, diabetes and hypertension. We implemented a novel health needs scale to categorise participants as: diagnosed and well-controlled (Needs Score 1), diagnosed and suboptimally controlled (Score 2), diagnosed but not engaged in care (Score 3) or undiagnosed and uncontrolled (Score 4). Scores 2-4 were indicative of unmet health needs. We explored the geospatial structure of unmet health needs using different spatial clustering methods.

RESULTS

The analytical sample comprised 18 041 individuals. We observed a similar spatial structure for HIV among those with combined needs Score 2-3 (diagnosed but uncontrolled) and Score 4 (undiagnosed and uncontrolled), with most PLHIV with unmet needs clustered in the southern urban and peri-urban areas. Conversely, a high prevalence of need Scores 2 and 3 for diabetes and hypertension was mostly distributed in the more rural central and northern part of the surveillance area. A high prevalence of need Score 4 for diabetes and hypertension was mostly distributed in the rural southern part of the surveillance area. Multivariate clustering analysis revealed a significant overlap of all three diseases in individuals with undiagnosed and uncontrolled diseases (unmet needs Score 4) in the southern part of the catchment area.

CONCLUSIONS

In an HIV hyperendemic community in South Africa, areas with the highest needs for PLHIV with undiagnosed and uncontrolled disease are also areas with the highest burden of unmet needs for other chronic health conditions, such as diabetes and hypertension. Our study has revealed remarkable differences in the distribution of health needs across the rural to urban continuum even within this relatively small study site. The identification and prioritisation of geographically clustered vulnerable communities with unmet health needs for both HIV and non-communicable diseases provide a basis for policy and implementation strategies to target communities with the highest health needs.

Impact of "Long Covid" on Children: Global and Hong Kong Perspectives

BACKGROUND

The coronavirus disease (COVID-19) pandemic spares no nation or city, and the virus is responsible for the escalating incidence and mortality worldwide.

OBJECTIVE

This article reviews the impact of "Long Covid" on Children.

METHODS

A PubMed search was conducted in December 2021 in Clinical Queries using the key terms "COVID-19" OR "long COVID". The search was restricted to children and adolescent aged < 18 years and English literature.

RESULTS

Many large-scale studies have provided strong scientific evidence as to the detrimental and irreversible sequelae of COVID-19 on the health, psychology, and development of affected children. Many insights into managing this disease can be obtained from comparing the management of influenza. COVID-19 is generally a mild respiratory disease in children. Several syndromes, such as multisystem inflammatory syndrome in children (MIS-C) and COVID toe, are probably not specific to SARS-CoV-2. "Long COVID", or the long-term effects of SARS-CoV-2 infection, or the prolonged isolation and containment strategies on education and psychosocial influences on children associated with the pandemic, are significant.

CONCLUSION

Healthcare providers must be aware of the potential effects of quarantine on children's mental health. More importantly, healthcare providers must appreciate the importance of the decisions and actions made by governments, non-governmental organizations, the community, schools, and parents in reducing the possible effects of this situation. Multifaceted age-specific and developmentally appropriate strategies must be adopted by healthcare authorities to lessen the negative impact of quarantine on the psychological well-being of children.

The evolution of the COVID-19 pandemic through the lens of google searches

Real-time data is essential for policymakers to adapt to a rapidly evolving situation like the COVID-19 pandemic. Using data from 221 countries and territories, we demonstrate the capacity of Google search data to anticipate reported COVID-19 cases and understand how containment policies are associated with changes in socioeconomic indicators. First, search interest in COVID-specific symptoms such as "loss of smell" strongly correlated with cases initially, but the association diminished as COVID-19 evolved; general terms such as "COVID symptoms" remained strongly associated with cases. Moreover, trends in search interest preceded trends in reported cases, particularly in the first year of the pandemic. Second, countries with more restrictive containment policies experienced greater search interest in unemployment and mental health terms after policies were implemented, indicating socio-economic externalities. Higher-income countries experienced a larger increase in searches related to unemployment and a larger reduction in relationship and family planning keywords relative to lower-income countries. The results demonstrate that real-time search interest can be a valuable tool to inform policies across multiple stages of the pandemic.

Comparison of SARS-CoV-2 Vaccination Skepticism, Reasons, and Concerns Between Mass Vaccination Centers and General Practices in Germany 2021

Introduction

The reluctance to be vaccinated against COVID-19 has significantly curbed vaccine uptake. Unlike mass vaccination centers, general practitioners (GPs) might be able to address some of the patients' concerns through their long-term doctor-patient relationship. This study compared vaccination reasons, concerns and skepticism about vaccination, and perceived importance of the vaccine and its hypothetical value between vaccination centers and GP practices.

Methods

A survey was distributed (07/2021-10/2021) among newly vaccinated individuals in ten GP practices (n = 364) and two vaccine centers (n = 474).

Results

Participants in vaccine centers stated more prosocial and benefit-oriented reasons for vaccination, whereas participants in GP practices more often stated the GP's recommendation as the reason. Perceived importance of the vaccine in combating the pandemic was rated higher among individuals at vaccine centers and with higher health awareness and self-efficacy. Participants at both types of sites who preferred a GP for vaccination expressed more vaccination skepticism, which was also related to older age, more health risk concerns related to COVID-19 vaccines, and lower perceived importance of the vaccine.

Conclusion

Our results indicate opportunities for framing future vaccination campaigns that include vaccination centers. Additionally, a rapid GP involvement in future mass vaccinations might be crucial for overcoming attitudinal barriers and achieving higher vaccine uptake.

Geospatial patterns of progress towards UNAIDS '95-95-95' targets and community vulnerability in Zambia: insights from population-based HIV impact assessments

INTRODUCTION

In sub-Saharan Africa, HIV/AIDS remains a leading cause of death. The UNAIDS established the '95-95-95' targets to improve HIV care continuum outcomes. Using geospatial data from the Zambia Population-based HIV Impact Assessment (ZAMPHIA), this study aims to investigate geospatial patterns in the '95-95-95' indicators and individual-level determinants that impede HIV care continuum in vulnerable communities, providing insights into the factors associated with gaps.

METHODS

This study used data from the 2016 ZAMPHIA to investigate the geospatial distribution and individual-level determinants of engagement across the HIV care continuum in Zambia. Gaussian kernel interpolation and optimised hotspot analysis were used to identify geospatial patterns in the HIV care continuum, while geospatial k-means clustering was used to partition areas into clusters. The study also assessed healthcare availability, access and social determinants of healthcare utilisation. Multiple logistic regression models were used to examine the association between selected sociodemographic and behavioural covariates and the three main outcomes of study.

RESULTS

Varied progress towards the '95-95-95' targets were observed in different regions of Zambia. Each '95' displayed a unique geographical pattern, independent of HIV prevalence, resulting in four distinct geographical clusters. Factors associated with gaps in the '95s' include younger age, male sex, and low wealth, with younger individuals having higher odds of not being on antiretroviral therapy and having detectable viral loads.

CONCLUSIONS

Our study revealed significant spatial heterogeneity in the HIV care continuum in Zambia, with different regions exhibiting unique geographical patterns and levels of performance in the '95-95-95' targets, highlighting the need for geospatial tailored interventions to address the specific needs of different subnational regions. These findings underscore the importance of addressing differential regional gaps in HIV diagnosis, enhancing community-level factors and developing innovative strategies to improve local HIV care continuum outcomes.

Explaining the U.S. rural disadvantage in COVID-19 case and death rates during the Delta-Omicron surge: The role of politics, vaccinations, population health, and social determinants

The Delta-Omicron wave of the COVID-19 pandemic (Wave 4) in the United States occurred in Fall of 2021 through Spring of 2022. Although vaccinations were widely available, this was the deadliest period to date in the U.S., and the toll was especially high in rural areas, exacerbating an existing rural mortality penalty. This paper uses county-level multilevel regression models and publicly available data for 47 U.S. states and the District of Columbia. We describe differences in COVID-19 case and mortality rates across the rural-urban continuum during Wave 4 of the COVID-19 pandemic. Using a progressive modeling approach, we evaluate the relative contribution of a range of explanatory factors for the rural disadvantage we observe, including: pre-pandemic population health composition, vaccination rates, political partisanship, socioeconomic composition, access to broadband internet rate, and primary care physicians per capita. Results show that rural counties had higher observed burdens of cases and deaths in Wave 4 compared to more urban counties. The most remote rural counties had Wave 4 COVID-19 mortality rates 52% higher than the most urban counties. Older age composition, worse pre-pandemic population health, lower vaccination rates, higher share of votes cast for Donald Trump in the 2020 Presidential election, and lower socioeconomic composition completely explained the rural disadvantage in reported COVID-19 case rates in Wave 4, and accounting for these factors reversed the observed rural disadvantage in COVID-19 mortality. In models of mortality rate, Trump vote share had the largest effect size, followed by the percentage of the population age 50 or older, the poverty rate, the pre-pandemic mortality rate, the share of residents with a 4-year college degree, and the vaccination rate. These findings add to a growing literature describing the disproportionate toll of the COVID-19 pandemic on rural America, highlighting the combined effect of multiple sources of rural disadvantage.

Using wastewater to overcome health disparities among rural residents

The SARS-CoV-2 pandemic highlighted the need for novel tools to promote health equity. There has been a historical legacy around the location and allocation of public facilities (such as health care) focused on efficiency, which is not attainable in rural, low-density, United States areas. Differences in the spread of the disease and outcomes of infections have been observed between urban and rural populations throughout the COVID-19 pandemic. The purpose of this article was to review rural health disparities related to the SARS-CoV-2 pandemic while using evidence to support wastewater surveillance as a potentially innovative tool to address these disparities more widely. The successful implementation of wastewater surveillance in resource-limited settings in South Africa demonstrates the ability to monitor disease in underserved areas. A better surveillance model of disease detection among rural residents will overcome issues around the interactions of a disease and social determinants of health. Wastewater surveillance can be used to promote health equity, particularly in rural and resource-limited areas, and has the potential to identify future global outbreaks of endemic and pandemic viruses.

Progress Towards UNAIDS's 95-95-95 Targets in Zimbabwe: Sociodemographic Constraints and Geospatial Heterogeneity

The HIV/AIDS epidemic remains critical in sub-Saharan Africa, with UNAIDS establishing "95-95-95" targets to optimize HIV care. Using the Zimbabwe Population-based HIV Impact Assessment (ZIMPHIA) geospatial data, this study aimed to identify patterns in these targets and determinants impacting the HIV care continuum in underserved Zimbabwean communities. Analysis techniques, including Gaussian kernel interpolation, optimized hotspot, and multivariate geospatial k-means clustering, were utilized to establish spatial patterns and cluster regional HIV care continuum needs. Further, we investigated healthcare availability, access, and social determinants and scrutinized the association between socio-demographic and behavioral covariates with HIV care outcomes. Disparities in progress toward the "95-95-95" targets were noted across different regions, with each target demonstrating unique geographic patterns, resulting in four distinct clusters with specific HIV care needs. Key factors associated with gaps in achieving targets included younger age, male sex, employment, and minority or no religious affiliation. Our study uncovers significant spatial heterogeneity in the HIV care continuum in Zimbabwe, with unique regional patterns in "95-95-95" targets. The spatial analysis of the UNAIDS targets presented here could prove instrumental in designing effective control strategies by identifying vulnerable communities that are falling short of these targets and require intensified efforts. Our result provides insights for designing region-specific interventions and enhancing community-level factors, emphasizing the need to address regional gaps and improve HIV care outcomes in vulnerable communities lagging behind.

Mapping Health Disparities in 11 High-Income Nations

Importance

Health care delivery faces a myriad of challenges globally with well-documented health inequities based on geographic location. Yet, researchers and policy makers have a limited understanding of the frequency of geographic health disparities.

Objective

To describe geographic health disparities in 11 high-income countries.

Design, Setting, and Participants

In this survey study, we analyzed results from the 2020 Commonwealth Fund International Health Policy (IHP) Survey-a nationally representative, self-reported, and cross-sectional survey of adults from Australia, Canada, France, Germany, the Netherlands, New Zealand, Norway, Sweden, Switzerland, the UK, and the US. Eligible adults older than age 18 years were included by random sampling. Survey data were compared for the association of area type (rural or urban) with 10 health indicators across 3 domains: health status and socioeconomic risk factors, affordability of care, and access to care. Logistic regression was used to determine the associations between countries with area type for each factor, controlling for individuals' age and sex.

Main Outcomes and Measures

The main outcomes were geographic health disparities as measured by differences in respondents living in urban and rural settings in 10 health indicators across 3 domains.

Results

There were 22 402 survey respondents (12 804 female [57.2%]), with a 14% to 49% response rate depending on the country. Across the 11 countries and 10 health indicators and 3 domains (health status and socioeconomic risk factors, affordability of care, access to care), there were 21 occurrences of geographic health disparities; 13 of those in which rural residence was a protective factor and 8 of those where rural residence was a risk factor. The mean (SD) number of geographic health disparities in the countries was 1.9 (1.7). The US had statistically significant geographic health disparities in 5 of 10 indicators, the most of any country, while Canada, Norway, and the Netherlands had no statistically significant geographic health disparities. The indicators with the most occurrences of geographic health disparities were in the access to care domain.

Conclusions and Relevance

In this survey study of 11 high-income nations, health disparities across 10 indicators were identified. Differences in number of disparities reported by country suggest that health policy and decision makers in the US should look to Canada, Norway, and the Netherlands to improve geographic-based health equity.

Geospatial Patterns of Progress towards UNAIDS "95-95-95" Targets and Community Vulnerability in Zambia

In sub-Saharan Africa, HIV/AIDS remains a leading cause of death. The UNAIDS established the "95-95-95" targets to improve HIV care continuum outcomes. Using geospatial data from the Zambia Population-based HIV Impact Assessment (ZAMPHIA), this study aims to investigate geospatial patterns in the "95-95-95" indicators and individual-level determinants that impede HIV care continuum in vulnerable communities, providing insights into the factors associated with gaps. This study used data from the 2016 ZAMPHIA to investigate the geospatial distribution and individual-level determinants of engagement across the HIV care continuum in Zambia. Gaussian kernel interpolation and optimized hotspot analysis were used to identify geospatial patterns in the HIV care continuum, while geospatial k-means clustering was used to partition areas into clusters. The study also assessed healthcare availability, access, and social determinants of healthcare utilization. Multiple logistic regression models were used to examine the association between selected sociodemographic and behavioral covariates and the three main outcomes of study. Varied progress towards the "95-95-95" targets were observed in different regions of Zambia. Each "95" displayed a unique geographic pattern, independent of HIV prevalence, resulting in four distinct geographic clusters. Factors associated with gaps in the "95s" include younger age, male sex, and low wealth, with younger individuals having higher odds of not being on ART and having detectable viral loads. Our study revealed significant spatial heterogeneity in the HIV care continuum in Zambia, with different regions exhibiting unique geographic patterns and levels of performance in the "95-95-95" targets, highlighting the need for geospatial tailored interventions to address the specific needs of different subnational regions. These findings underscore the importance of addressing differential regional gaps in HIV diagnosis, enhancing community-level factors, and developing innovative strategies to improve local HIV care continuum outcomes.

SARS-CoV-2 Omicron Replacement of Delta as Predominant Variant, Puerto Rico

We reconstructed the SARS-CoV-2 epidemic caused by Omicron variant in Puerto Rico by sampling genomes collected during October 2021-May 2022. Our study revealed that Omicron BA.1 emerged and replaced Delta as the predominant variant in December 2021. Increased transmission rates and a dynamic landscape of Omicron sublineage infections followed.

School closures during COVID-19: an overview of systematic reviews

OBJECTIVES

To assess the benefits and drawbacks of school closures and in-school mitigations during the COVID-19 pandemic.

DESIGN

Overview of systematic reviews (SRs).

SEARCH METHODS

We searched six databases and additional resources on 29 July 2022: MEDLINE, Embase, Google Scholar, Cochrane Library, COVID-END inventory of evidence synthesis, and Epistemonikos.

ELIGIBILITY CRITERIA

We selected SRs written in English that answered at least one of four specific questions concerning the efficacy and drawbacks of school closures. Their primary studies were conducted in primary and secondary schools, including pupils aged 5-18. Interventions included school closures or mitigations (such as mask usage) introduced in schools.

DATA COLLECTION AND ANALYSIS

We used AMSTAR 2 to assess confidence in the included SRs, and GRADE was used to assess certainty of evidence. We performed a narrative synthesis of the results, prioritising higher-quality SRs, those which performed GRADE assessments and those with more unique primary studies. We also assessed the overlap between primary studies included in the SRs.

MAIN OUTCOME MEASURES

Our framework for summarising outcome data was guided by the following questions: (1) What is the impact of school closures on COVID-19 transmission, morbidity or mortality in the community? (2) What is the impact of COVID-19 school closures on mental health (eg, anxiety), physical health (eg, obesity, domestic violence, sleep) and learning/achievement of primary and secondary pupils? (3) What is the impact of mitigations in schools on COVID-19 transmission, morbidity or mortality in the community? and (4) What is the impact of COVID-19 mitigations in schools on mental health, physical health and learning/achievement of primary and secondary pupils?

RESULTS

We identified 578 reports, 26 of which were included. One SR was of high confidence, 0 moderate, 10 low and 15 critically low confidence. We identified 132 unique primary studies on the effects of school closures on transmission/morbidity/mortality, 123 on learning, 164 on mental health, 22 on physical health, 16 on sleep, 7 on domestic violence and 69 on effects of in-school mitigations on transmission/morbidity/mortality.Both school closures and in-school mitigations were associated with reduced COVID-19 transmission, morbidity and mortality in the community. School closures were also associated with reduced learning, increased anxiety and increased obesity in pupils. We found no SRs that assessed potential drawbacks of in-school mitigations on pupils. The certainty of evidence according to GRADE was mostly very low.

CONCLUSIONS

School closures during COVID-19 had both positive and negative impacts. We found a large number of SRs and primary studies. However, confidence in the SRs was mostly low to very low, and the certainty of evidence was also mostly very low. We found no SRs assessing the potential drawbacks of in-school mitigations on children, which could be addressed moving forward. This overview provides evidence that could inform policy makers on school closures during future potential waves of COVID-19.

Convergence of HIV and non-communicable disease epidemics: Geospatial mapping of the unmet health needs in a HIV Hyperendemic South African community

Background

As people living with HIV (PLHIV) are experiencing longer survival, the co-occurrence of HIV and non-communicable diseases has become a public health priority. In response to this emerging challenge, we aimed to characterize the spatial structure of convergence of chronic health conditions in a HIV hyperendemic community in KwaZulu-Natal, South Africa.

Methods

We utilized data from a comprehensive population-based disease survey conducted in KwaZulu-Natal, South Africa, which collected data on HIV, diabetes, and hypertension. We implemented a novel health needs scale to categorize participants as: diagnosed and well-controlled (Needs Score 1), diagnosed and sub-optimally controlled (Score 2), diagnosed but not engaged in care (Score 3), or undiagnosed and uncontrolled (Score 4). Scores 2-4 were indicative of unmet health needs. We explored the geospatial structure of unmet health needs using different spatial clustering methods.

Findings

The analytical sample comprised of 18,041 individuals. We observed a similar spatial structure for HIV among those with a combined needs Score 2-3 (diagnosed but uncontrolled) and Score 4 (undiagnosed and uncontrolled), with most PLHIV with unmet needs clustered in the southern peri-urban area, which was relatively densely populated within the surveillance area. Multivariate clustering analysis revealed a significant overlap of all three diseases in individuals with undiagnosed and uncontrolled diseases (unmet needs Score 4) in the southern part of the catchment area.

Interpretation

In a HIV hyperendemic community in South Africa, areas with the highest needs for PLHIV with undiagnosed and uncontrolled disease are also areas with the highest burden of unmet needs for other chronic health conditions, such as diabetes and hypertension. The identification and prioritization of geographically clustered vulnerable communities with unmet health needs for both HIV and non-communicable diseases provide a basis for policy and implementation strategies to target communities with the highest health needs.

Funding

Research reported in this publication was supported by the Fogarty International Center (R21 TW011687; D43 TW010543), the National Institute of Mental Health, the National Institute of Allergy and Infectious Diseases (K24 HL166024; T32 AI007433) of the National Institutes of Health, and Heart Lung and Blood Institute (K24 HL166024, T32 AI007433). The contents of this manuscript are solely the responsibility of the authors and do not necessarily represent the official views of the funders.

Mindful mindfulness reporting: Media portrayals of scientific evidence for meditation mobile apps

Promoting mental health is a major global challenge. As mindfulness meditation apps can help maintain and restore good mental health, it is important to understand how their efficacy and safety are portrayed in the media. This study systematically evaluates whether evidence from academic research is used to communicate the health effects of two popular mindfulness apps, Calm and Smiling Mind. A scoping review mapped research findings from 16 relevant articles, and a media analysis examined the types of evidence used in news reporting. Analysing 105 news articles revealed that 98% did not use evidence from academic research on app-based meditation to support health claims. Only 28.5% of articles included advice from a health expert, and 9.5% mentioned potential risks and alternative treatments. Stronger evidence-based reporting on the health effects of mindfulness apps is needed to enable people to make more informed decisions for their health and wellbeing.

Geospatial assessment of the convergence of communicable and non-communicable diseases in South Africa

Introduction

Several low-and middle-income countries are undergoing rapid epidemiological transition with a rising burden of non-communicable diseases (NCDs). South Africa (SA) is a country with one of the largest HIV epidemics worldwide and a growing burden of NCDs where the collision of these epidemics poses a major public health challenge.

Methods

Using data from a large nationally representative survey, the South Africa Demographic and Health Survey (SADHS 2016), we conducted a geospatial analysis of several diseases including HIV, tuberculosis (TB), cardiovascular, respiratory, and metabolic diseases to identify areas with a high burden of co-morbidity within the country. We explored the spatial structure of each disease and associations between diseases using different spatial and visual data methodologies. We also assessed the individual level co-occurrence of HIV and the other diseases included in the analysis.

Results

The spatial distribution for HIV prevalence showed that this epidemic is most intense in the eastern region of the country, mostly within the Gauteng, Mpumalanga, and Kwazulu-Natal provinces. In contrast, chronic diseases had their highest prevalence rates the southern region of the country, particularly in the Eastern and Western Cape provinces. Individual-level analyses were consistent with the spatial correlations and found no statistically significant associations between HIV infection and the presence of any NCDs.

Conclusions

We found no evidence of geospatial overlap between the HIV epidemic and NCDs in SA. These results evidence the complex epidemiological landscape of the country, characterized by geographically distinct areas exhibiting different health burdens. The detailed description of the heterogenous prevalence of HIV and NCDs in SA reported in this study could be a useful tool to inform and direct policies to enhance targeted health service delivery according to the local health needs of each community.

The impact of face masks on infants' learning of faces: An eye tracking study

This preregistered study examined how face masks influenced face memory in a North American sample of 6- to 9-month-old infants (N = 58) born during the COVID-19 pandemic. Infants' memory was tested using a standard visual paired comparison (VPC) task. We crossed whether or not the faces were masked during familiarization and test, yielding four trial types (masked-familiarization/masked-test, unmasked-familiarization/masked-test, masked-familiarization/unmasked-test, and unmasked-familiarization/unmasked-test). Infants showed memory for the faces if the faces were unmasked at test, regardless of whether or not the face was masked during familiarization. However, infants did not show robust evidence of memory when test faces were masked, regardless of the familiarization condition. In addition, infants' bias for looking at the upper (eye) region was greater for masked than unmasked faces, although this difference was unrelated to memory performance. In summary, although the presence of face masks does appear to influence infants' processing of and memory for faces, they can form memories of masked faces and recognize those familiar faces even when unmasked.

Expert review of global real-world data on COVID-19 vaccine booster effectiveness and safety during the omicron-dominant phase of the pandemic

INTRODUCTION

COVID-19 vaccines have been highly effective in reducing morbidity and mortality during the pandemic. However, the emergence of the Omicron variant and subvariants as the globally dominant strains have raised doubts about the effectiveness of currently available vaccines and prompted debate about potential future vaccination strategies.

AREAS COVERED

Using the publicly available IVAC VIEW-hub platform, we reviewed 52 studies on vaccine effectiveness (VE) after booster vaccinations. VE were reported for SARS-CoV-2 symptomatic infection, severe disease and death and stratified by vaccine schedule and age. In addition, a non-systematic literature review of safety was performed to identify single or multi-country studies investigating adverse event rates for at least two of the currently available COVID-19 vaccines.

EXPERT OPINION

Booster shots of the current COVID-19 vaccines provide consistently high protection against Omicron-related severe disease and death. Additionally, this protection appears to be conserved for at least 3 months, with a small but significant waning after that. The positive risk-benefit ratio of these vaccines is well established, giving us confidence to administer additional doses as required. Future vaccination strategies will likely include a combination of schedules based on risk profile, as overly frequent boosting may be neither beneficial nor sustainable for the general population.

Impact of healthcare capacity disparities on the COVID-19 vaccination coverage in the United States: A cross-sectional study

Background

The impact of the COVID-19 vaccination campaign in the US has been hampered by a substantial geographical heterogeneity of the vaccination coverage. Several studies have proposed vaccination hesitancy as a key driver of the vaccination uptake disparities. However, the impact of other important structural determinants such as local disparities in healthcare capacity is virtually unknown.

Methods

In this cross-sectional study, we conducted causal inference and geospatial analyses to assess the impact of healthcare capacity on the vaccination coverage disparity in the US. We evaluated the causal relationship between the healthcare system capacity of 2417 US counties and their COVID-19 vaccination rate. We also conducted geospatial analyses using spatial scan statistics to identify areas with low vaccination rates.

Findings

We found a causal effect of the constraints in the healthcare capacity of a county and its low-vaccination uptake. Counties with higher constraints in their healthcare capacity were more probable to have COVID-19 vaccination rates ≤50, with 35% higher constraints in low-vaccinated areas (vaccination rates ≤ 50) compared to high-vaccinated areas (vaccination rates > 50). We also found that COVID-19 vaccination in the US exhibits a distinct spatial structure with defined "vaccination coldspots".

Interpretation

We found that the healthcare capacity of a county is an important determinant of low vaccine uptake. Our study highlights that even in high-income nations, internal disparities in healthcare capacity play an important role in the health outcomes of the nation. Therefore, strengthening the funding and infrastructure of the healthcare system, particularly in rural underserved areas, should be intensified to help vulnerable communities.

Funding

None.

The impact of the COVID-19 pandemic on mortality in people with dementia without COVID-19: a systematic review and meta-analysis

INTRODUCTION

Significant mortality amongst vulnerable populations, such as people living with dementia, might go undetected during pandemic conditions due to refocus of care efforts. There is an urgent need to fully evaluate the pandemic impact on mortality amongst people living with dementia in order to facilitate future healthcare reforms and prevent deaths. The purpose of this study was to determine whether there was any significant difference in mortality amongst people with dementia without COVID-19 during the COVID-19 pandemic compared to previous years.

METHODS

A literature search was conducted in 5 databases. The relative risk ratio and confidence interval was used to estimate the change in mortality rates amongst people with dementia during the COVID-19 pandemic. The I2 value was used to assess heterogeneity, publication bias, and sensitivity analyses were performed.

RESULTS

Pooled analysis of 11 studies showed that mortality amongst people living with dementia was significantly increased during the COVID-19 pandemic for people with dementia without COVID-19. Mortality risk increased by 25% during the time period studied. Subgroup analysis was not performed due the low number of included studies.

CONCLUSIONS

The results of this study suggest that people with dementia had a significant increased mortality during the pandemic even if they did not have COVID-19. People with dementia should participate in efforts that reduce general social spread and pandemic impact on healthcare system such as vaccinations, mask mandates, and testing. These results have clinical implications as preventing direct COVID-19 infection is not enough to adequately protect people living with dementia from increased mortality. Measures to limit social spread of infections and help support patients should also be a focus for clinicians. Further research should focus on the identification of mechanisms and other explanations for increased mortality as well as contributing factors such as living in care homes and differences between countries with various pandemic strategies.