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Weeberb J. Requia

Bio: Weeberb J. Requia is an academic researcher from Fundação Getúlio Vargas. The author has contributed to research in topics: Medicine & Air pollution. The author has an hindex of 15, co-authored 59 publications receiving 734 citations. Previous affiliations of Weeberb J. Requia include University of Brasília & Harvard University.

Papers published on a yearly basis

Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors provide a comprehensive review of the effects of EVs adoption on air quality, greenhouse gas emissions, and human health, and identify research gaps and recommend future research areas for the adoption of EVs and their benefits to society.

150 citations

Journal ArticleDOI
TL;DR: The results showed statistical significance in the test of moderators for all pollutants, suggesting that the modifier variables influence the average cardiorespiratory disease risk and may explain the varying effects of air pollution.
Abstract: Background. Little is known about the health risks of air pollution and cardiorespiratory diseases, globally, across regions and populations, which may differ because of external factors.Objectives. We systematically reviewed the evidence on the association between air pollution and cardiorespiratory diseases (hospital admissions and mortality), including variability by energy, transportation, socioeconomic status, and air quality.Search Methods. We conducted a literature search (PubMed and Web of Science) for studies published between 2006 and May 11, 2016.Selection Criteria. We included studies if they met all of the following criteria: (1) considered at least 1 of these air pollutants: carbon monoxide, sulfur dioxide, nitrogen dioxide, ozone, or particulate matter (PM2.5 or PM10); (2) reported risk for hospital admissions, mortality, or both; (3) presented individual results for respiratory diseases, cardiovascular diseases, or both; (4) considered the age groups younger than 5 years, older than 65 yea...

129 citations

Journal ArticleDOI
TL;DR: This study can be useful for the environmental health community to more accurately estimate the health impacts of O3 over space and time, especially in health studies at intra-urban scale.
Abstract: In this paper, we integrated multiple types of predictor variables and three types of machine learners (neural network, random forest, and gradient boosting) into a geographically weighted ensemble model to estimate the daily maximum 8 h O3 with high resolution over both space (at 1 km × 1 km grid cells covering the contiguous United States) and time (daily estimates between 2000 and 2016) We further quantify monthly model uncertainty for our 1 km × 1 km gridded domain The results demonstrate high overall model performance with an average cross-validated R2 (coefficient of determination) against observations of 090 and 086 for annual averages Overall, the model performance of the three machine learning algorithms was quite similar The overall model performance from the ensemble model outperformed those from any single algorithm The East North Central region of the United States had the highest R2, 093, and performance was weakest for the western mountainous regions (R2 of 086) and New England (R2 of 087) For the cross validation by season, our model had the best performance during summer with an R2 of 088 This study can be useful for the environmental health community to more accurately estimate the health impacts of O3 over space and time, especially in health studies at an intra-urban scale

94 citations

Journal ArticleDOI
TL;DR: Long-term exposure to air pollutants poses a significant risk to cardiovascular and respiratory health among the elderly population in the United States, with the greatest increase in the association per unit of exposure occurring at lower concentrations.
Abstract: Background: Studies examining the nonfatal health outcomes of exposure to air pollution have been limited by the number of pollutants studied and focus on short-term exposures. Methods: We examined...

66 citations

Journal ArticleDOI
TL;DR: In this article, the authors constructed two national U.S. population-based cohorts of those aged ≥65 from the Medicare Chronic Conditions Warehouse (2000-2018), combined with high-resolution air pollution datasets, to investigate the association of long-term exposure to ambient fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) with dementia and AD incidence, respectively.
Abstract: Air pollution may increase risk of Alzheimer’s disease and related dementias (ADRD) in the U.S., but the extent of this relationship is unclear. Here, we constructed two national U.S. population-based cohorts of those aged ≥65 from the Medicare Chronic Conditions Warehouse (2000–2018), combined with high-resolution air pollution datasets, to investigate the association of long-term exposure to ambient fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) with dementia and AD incidence, respectively. We identified ~2.0 million incident dementia cases (N = 12,233,371; dementia cohort) and ~0.8 million incident AD cases (N = 12,456,447; AD cohort). Per interquartile range (IQR) increase in the 5-year average PM2.5 (3.2 µg/m3), NO2 (11.6 ppb), and warm-season O3 (5.3 ppb) over the past 5 years prior to diagnosis, the hazard ratios (HRs) were 1.060 (95% confidence interval [CI]: 1.054, 1.066), 1.019 (95% CI: 1.012, 1.026), and 0.990 (95% CI: 0.987, 0.993) for incident dementias, and 1.078 (95% CI: 1.070, 1.086), 1.031 (95% CI: 1.023, 1.039), and 0.982 (95%CI: 0.977, 0.986) for incident AD, respectively, for the three pollutants. For both outcomes, concentration-response relationships for PM2.5 and NO2 were approximately linear. Our study suggests that exposures to PM2.5 and NO2 are associated with incidence of dementia and AD. Air pollution has been linked to neurodegenerative disease. Here the authors carried out a population-based cohort study to investigate the association between long-term exposure to PM2.5, NO2, and warm-season O3 on dementia and Alzheimer’s disease incidence in the United States.

62 citations


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01 Jan 2020
TL;DR: Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future.
Abstract: Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

4,408 citations

Journal ArticleDOI
01 Dec 1878

1,091 citations

Journal ArticleDOI
TL;DR: In this article, the authors presented the hydrogen-based energy system as four corners (stages) of a square shaped integrated whole to demonstrate the interconnection and interdependency of these main stages.

1,090 citations

Book
01 Jan 2003

911 citations

Journal ArticleDOI
TL;DR: The severe limitation of people movements following the PL and the subsequent TL determined a significant reduction of pollutants concentration mainly due to vehicular traffic and led to an appreciable drop in SO2 only in the city of Milan while it remained unchanged in the adjacent areas.

453 citations