Characteristics of commercial determinants of health research on corporate activities: A scoping review

INTRODUCTION

Business practices have influenced human health for centuries, yet an overarching concept to study these activities across nations, time periods, and industries (called 'the commercial determinants of health' (CDH)) has emerged only recently. The purpose of this review was to assess the descriptive characteristics of CDH research and to identify remaining research gaps.

METHODS

We systematically searched four databases (Scopus, OVID Medline, Ovid Embase, and Ovid Global Health) on Sept 13, 2022 for literature using CDH terms that described corporate activities that have the potential to influence population health and/or health equity (n = 116). We evaluated the following characteristics of the literature: methods employed, industries studied, regions investigated, funders, reported conflicts of interest, and publication in open-access formats.

RESULTS

The characteristics of the articles included that many were conceptual (50/116 articles; 43%) or used qualitative methods (37; 32%). Only eight articles (7%) used quantitative or mixed methods. The articles most often discussed corporate activities in relation to the food and beverage (51/116; 44%), tobacco (20; 17%), and alcohol industries (19; 16%), with limited research on activities occurring in other industries. Most articles (42/58 articles reporting a regional focus; 72%) focused on corporate activities occurring in high-income regions of the world.

CONCLUSIONS

Our findings indicate that literature that has used CDH terms and described corporate practices that influence human health has primarily focused on three major industries in higher-income regions of the world. Qualitative methods were the most common empirical method for investigating these activities. CDH-focused investigations of corporate practices conducted by less-studied industries (e.g., social media) and in lower-income regions are recommended. Longitudinal quantitative studies assessing the associations between corporate practices and a range of health outcomes is also a necessary next step for this field.

Exploring equity in global health collaborations: a qualitative study of donor and recipient power dynamics in Liberia

IntroductionGlobal health collaborations between individuals from high-resource and low-resource settings are complex and often built on hierarchical structures and power differentials that are difficult to change. There have been many calls and frameworks developed to facilitate more equity within these collaborations, yet little is known about the lived experiences of global health donors and recipients working within such collaborations and how those experiences can facilitate more equitable collaboration. Liberia, a postconflict, post-Ebola country, provides an ideal setting to study lived experiences of global health collaborations.MethodsOur qualitative analysis used key informant interviews representing the perspectives of those working on behalf of the Liberian government, Liberian academics, foreign donors and non-governmental organisations and implementing partners. Thematic analysis guided this analysis to explore topics such as financial control, accountability and decision making.ResultsThe first phase of the analysis mapped the existing patterns of priority setting. Priority-setting power was most strongly held by those with financial control (donors), and implementation plans tended to be built on metrics that aim to meet donor expectations. The second phase of the analysis explored the interplay between underlying factors that we identified in our data associated with driving collaborative inequity: history of prior of engagement, level of transparency and patterns of accountability.ConclusionsOur findings highlight that global health collaborations in Liberia are structured to hinder equitable partnerships. The power structure tied to financial ownership offers little space for recipients to have an equitable role in collaborations, which maintains dependence on external aid and ensures that weak systems remain weak. While our study is limited to Liberia, we anticipate that these dynamics are common elsewhere and reinforce the importance of intentional efforts to ensure equitable decision making and power structures in similar settings worldwide.

Sexual orientation disclosure and depression among Thai gay, bisexual, and other men who have sex with men: The roles of social support and intimate partner violence

BACKGROUND

Among gay, bisexual, and other men who have sex with men (GBM), sexual orientation disclosure to social groups can act as a significant risk for depression. The primary goal of this research is to understand the association between disclosure and depression, the association of social support and intimate partner violence (IPV) experiences, depression, and disclosure.

METHODS

This project uses a secondary dataset of Thailand from a larger cross-sectional study distributed in the Greater Mekong Sub-Region. This study utilized web-based answers from 1468 Thai GBM respondents between the ages of 15-24 years.

RESULTS

Prevalence of depression was over 50%. Across the social groups of interest, those who disclosed to everyone had the lowest depression prevalence. This association was statistically significant for all groups (p<0.050) except for "Family members" (p = 0.052). There was a statistically significant association illustrated between full disclosure to social groups and increased social support. Most respondents (43.9%) had low social support, and additionally this group had the highest level of depression, compared to those with high social support. There was a statistically significant association for lowered depression outcomes and increased social support. IPV experiences that occurred within the last six months had a statistically significant relationship with depression (p = 0.002). There was a notable association between those with experiences of being a victim of IPV, alone and in conjunction with experience of being a perpetrator of IPV, which was associated with increased odds of depression. However, the type of IPV experiences an individual had did not differ based on disclosure status.

DISCUSSION

This study provides strengthened evidence of the impact that differences in supportive networks can have on mental health outcomes. In addition, they provided a wider consideration for how people may have different IPV experiences, either as a perpetrator, victim, or both, and how those shapes health outcomes of depression. GBM communities still face adversity and challenges that affect their long-term health outcomes, even if they do live in what is considered an accepting country.

Reproducibility of biophysical in silico neuron states and spikes from event-based partial histories

Biophysically detailed simulations of neuronal activity often rely on solving large systems of differential equations; in some models, these systems have tens of thousands of states per cell. Numerically solving these equations is computationally intensive and requires making assumptions about the initial cell states. Additional realism from incorporating more biological detail is achieved at the cost of increasingly more states, more computational resources, and more modeling assumptions. We show that for both a point and morphologically-detailed cell model, the presence and timing of future action potentials is probabilistically well-characterized by the relative timings of a moderate number of recent events alone. Knowledge of initial conditions or full synaptic input history is not required. While model time constants, etc. impact the specifics, we demonstrate that for both individual spikes and sustained cellular activity, the uncertainty in spike response decreases as the number of known input events increases, to the point of approximate determinism. Further, we show cellular model states are reconstructable from ongoing synaptic events, despite unknown initial conditions. We propose that a strictly event-based modeling framework is capable of representing the complexity of cellular dynamics of the differential-equations models with significantly less per-cell state variables, thus offering a pathway toward utilizing modern data-driven modeling to scale up to larger network models while preserving individual cellular biophysics.

An AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model

Over the last century, outbreaks and pandemics have occurred with disturbing regularity, necessitating advance preparation and large-scale, coordinated response. Here, we developed a machine learning predictive model of disease severity and length of hospitalization for COVID-19, which can be utilized as a platform for future unknown viral outbreaks. We combined untargeted metabolomics on plasma data obtained from COVID-19 patients (n = 111) during hospitalization and healthy controls (n = 342), clinical and comorbidity data (n = 508) to build this patient triage platform, which consists of three parts: (i) the clinical decision tree, which amongst other biomarkers showed that patients with increased eosinophils have worse disease prognosis and can serve as a new potential biomarker with high accuracy (AUC = 0.974), (ii) the estimation of patient hospitalization length with ± 5 days error (R2 = 0.9765) and (iii) the prediction of the disease severity and the need of patient transfer to the intensive care unit. We report a significant decrease in serotonin levels in patients who needed positive airway pressure oxygen and/or were intubated. Furthermore, 5-hydroxy tryptophan, allantoin, and glucuronic acid metabolites were increased in COVID-19 patients and collectively they can serve as biomarkers to predict disease progression. The ability to quickly identify which patients will develop life-threatening illness would allow the efficient allocation of medical resources and implementation of the most effective medical interventions. We would advocate that the same approach could be utilized in future viral outbreaks to help hospitals triage patients more effectively and improve patient outcomes while optimizing healthcare resources.

Routine saliva testing for SARS-CoV-2 in children: Methods for partnering with community childcare centers

While considerable attention was placed on SARS-CoV-2 testing and surveillance programs in the K-12 setting, younger age groups in childcare centers were largely overlooked. Childcare facilities are vital to communities, allowing parents/guardians to remain at work and providing safe environments for both children and staff. Therefore, early in the COVID-19 pandemic (October 2020), we established a PCR-based COVID-19 surveillance program in childcare facilities, testing children and staff with the goal of collecting actionable public health data and aiding communities in the progressive resumption of standard operations and ways of life. In this study we describe the development of a weekly saliva testing program and provide early results from our experience implementing this in childcare centers. We enrolled children (aged 6 months to 7 years) and staff at seven childcare facilities and trained participants in saliva collection using video chat technology. Weekly surveys were sent out to assess exposures, symptoms, and vaccination status changes. Participants submitted weekly saliva samples at school. Samples were transported to a partnering clinical laboratory or RT-PCR testing using SalivaDirect and results were uploaded to each participant's online patient portal within 24 h. SARS-CoV-2 screening and routine testing programs have focused less on the childcare population, resulting in knowledge gaps in this critical age group, especially as many are still ineligible for vaccination. SalivaDirect testing for SARS-CoV-2 provides a feasible method of asymptomatic screening and symptomatic testing for children and childcare center staff. Given the relative aversion to nasal swabs in younger age groups, an at-home saliva collection method provides an attractive alternative, especially as a routine surveillance tool. Results can be shared rapidly electronically through participants' private medical chart portals, and video chat technology allows for discussion and instruction between investigators and participants. This study fosters a cooperative partnership with participating childcare centers, parents/guardians, and staff with the goal of mitigating COVID-19 transmission in childcare centers. Age-related challenges in saliva collection can be overcome by working with parents/guardians to conceptualize new collection strategies and by offering parents/guardians continued virtual guidance and support.

Plasmodium infection is associated with cross-reactive antibodies to carbohydrate epitopes on the SARS-CoV-2 Spike protein

Sero-surveillance can monitor and project disease burden and risk. However, SARS-CoV-2 antibody test results can produce false positive results, limiting their efficacy as a sero-surveillance tool. False positive SARS-CoV-2 antibody results are associated with malaria exposure, and understanding this association is essential to interpret sero-surveillance results from malaria-endemic countries. Here, pre-pandemic samples from eight malaria endemic and non-endemic countries and four continents were tested by ELISA to measure SARS-CoV-2 Spike S1 subunit reactivity. Individuals with acute malaria infection generated substantial SARS-CoV-2 reactivity. Cross-reactivity was not associated with reactivity to other human coronaviruses or other SARS-CoV-2 proteins, as measured by peptide and protein arrays. ELISAs with deglycosylated and desialated Spike S1 subunits revealed that cross-reactive antibodies target sialic acid on N-linked glycans of the Spike protein. The functional activity of cross-reactive antibodies measured by neutralization assays showed that cross-reactive antibodies did not neutralize SARS-CoV-2 in vitro. Since routine use of glycosylated or sialated assays could result in false positive SARS-CoV-2 antibody results in malaria endemic regions, which could overestimate exposure and population-level immunity, we explored methods to increase specificity by reducing cross-reactivity. Overestimating population-level exposure to SARS-CoV-2 could lead to underestimates of risk of continued COVID-19 transmission in sub-Saharan Africa.

Association between primary or booster COVID-19 mRNA vaccination and Omicron lineage BA.1 SARS-CoV-2 infection in people with a prior SARS-CoV-2 infection: A test-negative case-control analysis

BACKGROUND

The benefit of primary and booster vaccination in people who experienced a prior Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection remains unclear. The objective of this study was to estimate the effectiveness of primary (two-dose series) and booster (third dose) mRNA vaccination against Omicron (lineage BA.1) infection among people with a prior documented infection.

METHODS AND FINDINGS

We conducted a test-negative case-control study of reverse transcription PCRs (RT-PCRs) analyzed with the TaqPath (Thermo Fisher Scientific) assay and recorded in the Yale New Haven Health system from November 1, 2021, to April 30, 2022. Overall, 11,307 cases (positive TaqPath analyzed RT-PCRs with S-gene target failure [SGTF]) and 130,041 controls (negative TaqPath analyzed RT-PCRs) were included (median age: cases: 35 years, controls: 39 years). Among cases and controls, 5.9% and 8.1% had a documented prior infection (positive SARS-CoV-2 test record ≥90 days prior to the included test), respectively. We estimated the effectiveness of primary and booster vaccination relative to SGTF-defined Omicron (lineage BA.1) variant infection using a logistic regression adjusted for date of test, age, sex, race/ethnicity, insurance, comorbidities, social venerability index, municipality, and healthcare utilization. The effectiveness of primary vaccination 14 to 149 days after the second dose was 41.0% (95% confidence interval (CI): 14.1% to 59.4%, p 0.006) and 27.1% (95% CI: 18.7% to 34.6%, p < 0.001) for people with and without a documented prior infection, respectively. The effectiveness of booster vaccination (≥14 days after booster dose) was 47.1% (95% CI: 22.4% to 63.9%, p 0.001) and 54.1% (95% CI: 49.2% to 58.4%, p < 0.001) in people with and without a documented prior infection, respectively. To test whether booster vaccination reduced the risk of infection beyond that of the primary series, we compared the odds of infection among boosted (≥14 days after booster dose) and booster-eligible people (≥150 days after second dose). The odds ratio (OR) comparing boosted and booster-eligible people with a documented prior infection was 0.79 (95% CI: 0.54 to 1.16, p 0.222), whereas the OR comparing boosted and booster-eligible people without a documented prior infection was 0.54 (95% CI: 0.49 to 0.59, p < 0.001). This study's limitations include the risk of residual confounding, the use of data from a single system, and the reliance on TaqPath analyzed RT-PCR results.

CONCLUSIONS

In this study, we observed that primary vaccination provided significant but limited protection against Omicron (lineage BA.1) infection among people with and without a documented prior infection. While booster vaccination was associated with additional protection against Omicron BA.1 infection in people without a documented prior infection, it was not found to be associated with additional protection among people with a documented prior infection. These findings support primary vaccination in people regardless of documented prior infection status but suggest that infection history may impact the relative benefit of booster doses.