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Exploring the Association between Misinformation Endorsement, Opinions on the Government Response, Risk Perception, and COVID-19 Vaccine Hesitancy in the US, Canada, and Italy
Get PDFThe COVID-19 pandemic has highlighted the adverse consequences created by an infodemic, specifically bringing attention to compliance with public health guidance and vaccine uptake. COVID-19 vaccine hesitancy is a complex construct that is related to health beliefs, misinformation exposure, and perceptions of governmental institutions. This study draws on theoretical models and current data on the COVID-19 infodemic to explore the association between the perceived risk of COVID-19, level of misinformation endorsement, and opinions about the government response on vaccine uptake. We surveyed a sample of 2697 respondents from the US, Canada, and Italy using a mobile platform between 21–28 May 2021. Using multivariate regression, we found that country of residence, risk perception of contracting and spreading COVID-19, perception of government response and transparency, and misinformation endorsement were associated with the odds of vaccine hesitancy. Higher perceived risk was associated with lower odds of hesitancy, while lower perceptions of government response and higher misinformation endorsement were associated with higher hesitancy
Relationship between the Bolsa Família national cash transfer programme and suicide incidence in Brazil: A quasi-experimental study
Get PDFSocioeconomic factors have been consistently associated with suicide, and economic recessions are linked to rising suicide rates. However, evidence on the impact of socioeconomic interventions to reduce suicide rates is limited. This study investigates the association of the world’s largest conditional cash transfer programme with suicide rates in a cohort of half of the Brazilian population.
Methods and findings
We used data from the 100 Million Brazilian Cohort, covering a 12-year period (2004 to 2015). It comprises socioeconomic and demographic information on 114,008,317 individuals, linked to the “Bolsa Família” programme (BFP) payroll database, and nationwide death registration data. BFP was implemented by the Brazilian government in 2004. We estimated the association of BFP using inverse probability of treatment weighting, estimating the weights for BFP beneficiaries (weight = 1) and nonbeneficiaries by the inverse probability of receiving treatment (weight = E(ps)/(1-E(ps))). We used an average treatment effect on the treated (ATT) estimator and fitted Poisson models to estimate the incidence rate ratios (IRRs) for suicide associated with BFP experience. At the cohort baseline, BFP beneficiaries were younger (median age 27.4 versus 35.4), had higher unemployment rates (56% versus 32%), a lower level of education, resided in rural areas, and experienced worse household conditions. There were 36,742 suicide cases among the 76,532,158 individuals aged 10 years, or older, followed for 489,500,000 person-years at risk. Suicide rates among beneficiaries and nonbeneficiaries were 5.4 (95% CI = 5.32, 5.47, p < 0.001) and 10.7 (95% CI = 10.51, 10.87, p < 0.001) per 100,000 individuals, respectively. BFP beneficiaries had a lower suicide rate than nonbeneficiaries (IRR = 0.44, 95% CI = 0.42, 0.45, p < 0.001). This association was stronger among women (IRR = 0.36, 95% CI = 0.33, 0.38, p < 0.001), and individuals aged between 25 and 59 (IRR = 0.41, 95% CI = 0.40, 0.43, p < 0.001). Study limitations include a lack of control for previous mental disorders and access to means of suicide, and the possible under-registration of suicide cases due to stigma
Incidence of nonvalvular atrial fibrillation and oral anticoagulant prescribing in England, 2009 to 2019: A cohort study
Get PDFAtrial fibrillation (AF) is an important risk factor for ischaemic stroke, and AF incidence is expected to increase. Guidelines recommend using oral anticoagulants (OACs) to prevent the development of stroke. However, studies have reported the frequent underuse of OACs in AF patients. The objective of this study is to describe nonvalvular atrial fibrillation (NVAF) incidence in England and assess the clinical and socioeconomic factors associated with the underprescribing of OACs.
Methods and findings
We conducted a population-based retrospective cohort study using the UK Clinical Practice Research Datalink (CPRD) database to identify patients with NVAF aged ≥18 years and registered in English general practices between 2009 and 2019. Annual incidence rate of NVAF by age, deprivation quintile, and region was estimated. OAC prescribing status was explored for patients at risk for stroke and classified into the following: OAC, aspirin only, or no treatment. We used a multivariable multinomial logistic regression model to estimate relative risk ratios (RRRs) and 95% confidence intervals (CIs) of the factors associated with OAC or aspirin-only prescribing compared to no treatment in patients with NVAF who are recommended to take OAC. The multivariable regression was adjusted for age, sex, comorbidities, socioeconomic status, baseline treatment, frailty, bleeding risk factors, and takes into account clustering by general practice. Between 2009 and 2019, 12,517,191 patients met the criteria for being at risk of developing NVAF. After a median follow-up of 4.6 years, 192,265 patients had an incident NVAF contributing a total of 647,876 person-years (PYR) of follow-up. The overall age-adjusted incidence of NVAF per 10,000 PYR increased from 20.8 (95% CI: 20.4; 21.1) in 2009 to 25.5 (25.1; 25.9) in 2019. Higher incidence rates were observed for older ages and males. Among NVAF patients eligible for anticoagulation, OAC prescribing rose from 59.8% (95% CI: 59.0; 60.6) in 2009 to 83.2% (95% CI: 83.0; 83.4) in 2019. Several conditions were associated with lower risk of OAC prescribing: dementia [RRR 0.52 (0.47; 0.59)], liver disease 0.58 (0.50; 0.67), malignancy 0.74 (0.72; 0.77), and history of falls 0.82 (0.78; 0.85). Compared to white ethnicity, patients from black and other ethnic minorities were less likely to receive OAC; 0.78 (0.65; 0.94) and 0.76 (0.64; 0.91), respectively. Patients living in the most deprived areas were less likely to receive OAC 0.85 (0.79; 0.91) than patients living in the least deprived areas. Practices located in the East of England were associated with higher risk of prescribing aspirin only over no treatment than practices in London (RRR 1.22; 95% CI 1.02 to 1.45). The main limitation of this study is that these findings depends on accurate recording of conditions by health professionals and the inevitable residual confounding due to lack of data on certain factors that could be associated with under-prescribing of OACs
Accuracy of rapid point-of-care antigen-based diagnostics for SARS-CoV-2: An updated systematic review and meta-analysis with meta-regression analyzing influencing factors
Get PDFComprehensive information about the accuracy of antigen rapid diagnostic tests (Ag-RDTs) for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is essential to guide public health decision makers in choosing the best tests and testing policies. In August 2021, we published a systematic review and meta-analysis about the accuracy of Ag-RDTs. We now update this work and analyze the factors influencing test sensitivity in further detail.
Methods and findings
We registered the review on PROSPERO (registration number: CRD42020225140). We systematically searched preprint and peer-reviewed databases for publications evaluating the accuracy of Ag-RDTs for SARS-CoV-2 until August 31, 2021. Descriptive analyses of all studies were performed, and when more than 4 studies were available, a random-effects meta-analysis was used to estimate pooled sensitivity and specificity with reverse transcription polymerase chain reaction (RT-PCR) testing as a reference. To evaluate factors influencing test sensitivity, we performed 3 different analyses using multivariable mixed-effects meta-regression models. We included 194 studies with 221,878 Ag-RDTs performed. Overall, the pooled estimates of Ag-RDT sensitivity and specificity were 72.0% (95% confidence interval [CI] 69.8 to 74.2) and 98.9% (95% CI 98.6 to 99.1). When manufacturer instructions were followed, sensitivity increased to 76.3% (95% CI 73.7 to 78.7). Sensitivity was markedly better on samples with lower RT-PCR cycle threshold (Ct) values (97.9% [95% CI 96.9 to 98.9] and 90.6% [95% CI 88.3 to 93.0] for Ct-values <20 and <25, compared to 54.4% [95% CI 47.3 to 61.5] and 18.7% [95% CI 13.9 to 23.4] for Ct-values ≥25 and ≥30) and was estimated to increase by 2.9 percentage points (95% CI 1.7 to 4.0) for every unit decrease in mean Ct-value when adjusting for testing procedure and patients’ symptom status. Concordantly, we found the mean Ct-value to be lower for true positive (22.2 [95% CI 21.5 to 22.8]) compared to false negative (30.4 [95% CI 29.7 to 31.1]) results. Testing in the first week from symptom onset resulted in substantially higher sensitivity (81.9% [95% CI 77.7 to 85.5]) compared to testing after 1 week (51.8%, 95% CI 41.5 to 61.9). Similarly, sensitivity was higher in symptomatic (76.2% [95% CI 73.3 to 78.9]) compared to asymptomatic (56.8% [95% CI 50.9 to 62.4]) persons. However, both effects were mainly driven by the Ct-value of the sample. With regards to sample type, highest sensitivity was found for nasopharyngeal (NP) and combined NP/oropharyngeal samples (70.8% [95% CI 68.3 to 73.2]), as well as in anterior nasal/mid-turbinate samples (77.3% [95% CI 73.0 to 81.0]). Our analysis was limited by the included studies’ heterogeneity in viral load assessment and sample origination
Soil carbon sequestration through regenerative agriculture in the U.S. state of Vermont
Get PDFThis study investigates the extent to which land use and management transitions on Vermont’s farmland could sequester atmospheric carbon in the soil. We weigh the sequestration potential of several types of regenerative agricultural practices against both business as usual and afforestation scenarios using the Rothamsted Carbon Model. We split the study area into 13 Ecoregions for a finer spatial scale of analysis, with key climate, soil, and land use data specified for each. Empirical soil laboratory data are used to initialize the model to mirror current conditions under each of three agricultural land uses (crops, hay, and pasture) in each Ecoregion. We consult experts as well as the literature to parameterize the anticipated effects of alternative agricultural management practices on soil carbon inputs. In the simulation runs, we find that all non-business-as-usual scenarios sequester carbon over time, with a higher rate of sequestration in the decades immediately after a land use or management change. Among the regenerative agriculture scenarios, conversion to rotational grazing offers the highest soil carbon sequestration potential, at 1,269 kt, or 5.3% above current stocks after ten years. Of all scenarios, afforestation of farmland to non-harvested forest stores the most soil carbon, increasing stocks by 6.5% after ten years, and continuing to sequester at a high rate many decades into the future. We discuss tradeoffs and policy implications, especially in the context of the 2020 Vermont Global Warming Solutions Act, and suggest that payments for ecosystem services for farmers sequestering carbon may have strategic value
Not what the doctor ordered: Prioritizing transdisciplinary science on climate, environment and health in the Latin American and Caribbean region
Get PDFThe Latin American and Caribbean (LAC) region is highly diverse and unequal [1]. It is also host to extreme weather events and changing climate patterns increasingly impacting infrastructure, livelihoods, food security, and peoples’ health and wellbeing. Understanding the interactions between climate, environment and health to develop evidenced-based solutions is therefore crucial for improving health outcomes. However, and despite growing concerns [2], critical gaps in data and scientific capacities remain, impeding effective policy and decision making.
Indeed, resources are lacking, and/or are improperly assigned and invested, to address the impact of climate events and environmental degradation on health in the LAC region. Although several of the 33 countries have progressed in developing national-level climate change and health vulnerability assessments and adaptation plans, these continue to have “limited influence on the allocation of human and financial resources” [3]. That is, even when the assessments highlight the need for greater capacity to respond to the challenges at the intersection of climate, environment and health, governments may not be allocating funds for the production and use of evidence for decision making. We argue here in favor of prioritizing a transdisciplinary approach to science, focused on solutions-oriented research, to create the tools and collect the data we need.
In August 2021, more than 150 researchers and government officials from 35 states met to identify research and capacity building priorities at the Climate, Environment and Health Latin America and Caribbean scoping workshop [4] organized by the Inter-American Institute for Global Change Research (IAI), the U.S. Global Change Research Program (USGCRP), and the Belmont Forum. The event was held in conjunction with the Americas Group on Earth Observations, AmeriGEO Week 2021. Among the most important concerns that emerged in the discussions were: a) Data are produced and collected in the region, but they may not be granular enough, or datasets may have limited interoperability, such that diverse data from different sectors remain siloed or not useful; b) Transdisciplinary research frameworks supporting the integration of knowledge from different academic disciplines and non-academic ways of knowing are essential for improved databases and tools/interventions to support decision making; c) Effective communities of practice informing policy and decision making require the participation of non-governmental stakeholders, including from civil society and the private sector
RNA folding using quantum computers
Get PDFThe 3-dimensional fold of an RNA molecule is largely determined by patterns of intramolecular hydrogen bonds between bases. Predicting the base pairing network from the sequence, also referred to as RNA secondary structure prediction or RNA folding, is a nondeterministic polynomial-time (NP)-complete computational problem. The structure of the molecule is strongly predictive of its functions and biochemical properties, and therefore the ability to accurately predict the structure is a crucial tool for biochemists. Many methods have been proposed to efficiently sample possible secondary structure patterns. Classic approaches employ dynamic programming, and recent studies have explored approaches inspired by evolutionary and machine learning algorithms. This work demonstrates leveraging quantum computing hardware to predict the secondary structure of RNA. A Hamiltonian written in the form of a Binary Quadratic Model (BQM) is derived to drive the system toward maximizing the number of consecutive base pairs while jointly maximizing the average length of the stems. A Quantum Annealer (QA) is compared to a Replica Exchange Monte Carlo (REMC) algorithm programmed with the same objective function, with the QA being shown to be highly competitive at rapidly identifying low energy solutions. The method proposed in this study was compared to three algorithms from literature and, despite its simplicity, was found to be competitive on a test set containing known structures with pseudoknots
Tumor suppressor PALB2 maintains redox and mitochondrial homeostasis in the brain and cooperates with ATG7/autophagy to suppress neurodegeneration
Get PDFThe PALB2 tumor suppressor plays key roles in DNA repair and has been implicated in redox homeostasis. Autophagy maintains mitochondrial quality, mitigates oxidative stress and suppresses neurodegeneration. Here we show that Palb2 deletion in the mouse brain leads to mild motor deficits and that co-deletion of Palb2 with the essential autophagy gene Atg7 accelerates and exacerbates neurodegeneration induced by ATG7 loss. Palb2 deletion leads to elevated DNA damage, oxidative stress and mitochondrial markers, especially in Purkinje cells, and co-deletion of Palb2 and Atg7 results in accelerated Purkinje cell loss. Further analyses suggest that the accelerated Purkinje cell loss and severe neurodegeneration in the double deletion mice are due to excessive oxidative stress and mitochondrial dysfunction, rather than DNA damage, and partially dependent on p53 activity. Our studies uncover a role of PALB2 in mitochondrial homeostasis and a cooperation between PALB2 and ATG7/autophagy in maintaining redox and mitochondrial homeostasis essential for neuronal survival.
Author summary
PALB2 is a tumor suppressor in which inherited mutations increase the risk of breast, ovarian, pancreatic, and other cancers. It plays a critical role in DNA repair and promotes antioxidant gene expression. ATG7 is an essential factor for autophagy, an intracellular waste disposal and nutrient recycling process. Loss of autophagy function leads to accumulation of toxic wastes and damaged mitochondria, leading to oxidative stress and other problems in the cell. As neurons in the brain are particularly sensitive to oxidative stress and waste accumulation, loss of ATG7 or autophagy in the brain causes death of neurons and neurodegeneration. In this study, we found that loss of PALB2 in the brain led to oxidative stress accompanied by increased amount of functionally impaired mitochondria, and that combined loss of PALB2 and ATG7 caused accelerated and more severe neurodegeneration than did ATG7 loss alone. We further found that the exacerbated phenotype was mainly caused by excessive oxidative stress, rather than increased DNA damage. Our studies establish a new function of PALB2, i.e., mitochondrial regulation, provide additional insights into the function of ATG7 in the brain, and further underscore the role of oxidative stress in neuronal death and neurodegeneration
Abnormal global alternative RNA splicing in COVID-19 patients
Get PDFViral infections can alter host transcriptomes by manipulating host splicing machinery. Despite intensive transcriptomic studies on SARS-CoV-2, a systematic analysis of alternative splicing (AS) in severe COVID-19 patients remains largely elusive. Here we integrated proteomic and transcriptomic sequencing data to study AS changes in COVID-19 patients. We discovered that RNA splicing is among the major down-regulated proteomic signatures in COVID-19 patients. The transcriptome analysis showed that SARS-CoV-2 infection induces widespread dysregulation of transcript usage and expression, affecting blood coagulation, neutrophil activation, and cytokine production. Notably, CD74 and LRRFIP1 had increased skipping of an exon in COVID-19 patients that disrupts a functional domain, which correlated with reduced antiviral immunity. Furthermore, the dysregulation of transcripts was strongly correlated with clinical severity of COVID-19, and splice-variants may contribute to unexpected therapeutic activity. In summary, our data highlight that a better understanding of the AS landscape may aid in COVID-19 diagnosis and therapy.
Author summary
Despite intensive studies on the transcriptional signatures of COVID-19 patients, how SARS-CoV-2 affects AS landscape and the contribution of AS to the pathogenesis of COVID-19 remain largely elusive. By profiling the lung transcriptome and lung proteome of nine patients who died of COVID-19 during the first wave of the pandemic in Wuhan, China, we obtained molecular insights into the AS of cellular transcripts upon SARS-CoV-2 infection. Interestingly, SARS-CoV-2 proteins directly engage host spliceosome to dysregulate essential steps of mature mRNA production and result in widespread dysregulation of cellular function. Taken together, our findings shed light on COVID-19 molecular mechanism and offer potential therapeutic targets for severe COVID-19 disease
Funders: The missing link in equitable global health research?
Get PDFGlobal health research is mired by inequities, some of which are linked to current approaches to research funding. The role of funders and donors in achieving greater equity in global health research needs to be clearly defined. Imbalances of power and resources between high income countries (HICs) and low- and middle-income countries (LMICs) is such that many funding approaches do not centre the role of LMIC researchers in shaping global health research priorities and agenda. Relative to need, there is also disparity in financial investment by LMIC governments in health research. These imbalances put at a disadvantage LMIC health professionals and researchers who are at forefront of global health practice. Whilst many LMICs do not have the means (due to geopolitical, historical, and economic reasons) for direct investment, if those with means were to invest more of their own funds in health research, it may help LMICs become more self-sufficient and shift some of the power imbalances. Funders and donors in HICs should address inequities in their approach to research funding and proactively identify mechanisms that assure greater equity–including via direct funding to LMIC researchers and direct funding to build local LMIC-based, led, and run knowledge infrastructures. To collectively shape a new approach to global health research funding, it is essential that funders and donors are part of the conversation. This article provides a way to bring funders and donors into the conversation on equity in global health research