Dataset Information

DatAC: A visual analytics platform to explore climate and air quality indicators associated with the COVID-19 pandemic in Spain.

ABSTRACT: The coronavirus disease 2019 (COVID-19) pandemic has caused an unprecedented global health crisis, with several countries imposing lockdowns to control the coronavirus spread. Important research efforts are focused on evaluating the association of environmental factors with the survival and spread of the virus and different works have been published, with contradictory results in some cases. Data with spatial and temporal information is a key factor to get reliable results and, although there are some data repositories for monitoring the disease both globally and locally, an application that integrates and aggregates data from meteorological and air quality variables with COVID-19 information has not been described so far to the best of our knowledge. Here, we present DatAC (Data Against COVID-19), a data fusion project with an interactive web frontend that integrates COVID-19 and environmental data in Spain. DatAC is provided with powerful data analysis and statistical capabilities that allow users to explore and analyze individual trends and associations among the provided data. Using the application, we have evaluated the impact of the Spanish lockdown on the air quality, observing that NO₂, CO, PM_2.5, PM₁₀ and SO₂ levels decreased drastically in the entire territory, while O₃ levels increased. We observed similar trends in urban and rural areas, although the impact has been more important in the former. Moreover, the application allowed us to analyze correlations among climate factors, such as ambient temperature, and the incidence of COVID-19 in Spain. Our results indicate that temperature is not the driving factor and without effective control actions, outbreaks will appear and warm weather will not substantially limit the growth of the pandemic. DatAC is available at https://covid19.genyo.es.

SUBMITTER: Martorell-Marugan J

PROVIDER: S-EPMC7399783 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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DatAC: A visual analytics platform to explore climate and air quality indicators associated with the COVID-19 pandemic in Spain.

Martorell-Marugán Jordi J Villatoro-García Juan Antonio JA García-Moreno Adrián A López-Domínguez Raúl R Requena Francisco F Merelo Juan Julián JJ Lacasaña Marina M de Dios Luna Juan J Díaz-Mochón Juan J JJ Lorente Jose A JA Carmona-Sáez Pedro P

The Science of the total environment 20200804

The coronavirus disease 2019 (COVID-19) pandemic has caused an unprecedented global health crisis, with several countries imposing lockdowns to control the coronavirus spread. Important research efforts are focused on evaluating the association of environmental factors with the survival and spread of the virus and different works have been published, with contradictory results in some cases. Data with spatial and temporal information is a key factor to get reliable results and, although there ar ...[more]

PMID: 32853931

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Project description:BACKGROUND:Standard methods for obtaining data may delay quality improvement (QI) interventions including for bronchiolitis, a common cause of childhood hospitalization. OBJECTIVE:To describe the use of a dashboard in the context of a multifaceted QI intervention aimed at reducing the use of chest radiographs, bronchodilators, antibiotics, steroids, and viral testing in patients with bronchiolitis. METHODS:This QI initiative took place at Children's Minnesota, a large, not-for-profit children's health care organization. A multidisciplinary bronchiolitis workgroup developed a local clinical guideline and order-set. Delays in obtaining baseline data prompted a pediatric hospitalist and information technology specialist to modify a vendor's dashboard to display data related to bronchiolitis guideline metrics. Patients 2 months to 2 years old with a bronchiolitis emergency department (ED)/inpatient encounter in the period October 1, 2014 to April 30, 2018 were included. The primary outcome was a functioning dashboard; a process measure was the percentage of ED clinician logins. Outcome measures included the percent use of guideline metrics (e.g., bronchodilators) displayed on statistical process control charts (ED vs. inpatient). Balancing measures included length of stay, charge ratios, and hospital revisits. RESULTS:A workgroup (formed October 2015) implemented a bronchiolitis order-set and guideline (February 2016) followed by a bronchiolitis dashboard (August 2016) consolidating disparate data sources loaded within 2 to 4 days of discharge. In total, 35% of ED clinicians logged in. Leaders used the dashboard to target and track interventions such as a bronchodilator order alert. There were improvements in most outcome metrics; however, timing did not suggest direct dashboard impact. ED balancing measures were lower after implementation. CONCLUSION:We described use of a dashboard to support a multifaceted QI initiative for bronchiolitis. Leaders used the dashboard for targeted interventions but the dashboard did not directly impact the observed improvements. Future studies should assess reasons for low individual dashboard use.

Project description:ImportanceFuture changes in climate are likely to adversely affect human health by affecting concentrations of particulate matter sized less than 2.5 μm (PM2.5) and ozone (O3) in many areas. However, the degree to which these outcomes may be mitigated by reducing air pollutant emissions is not well understood.ObjectiveTo model the associations between future changes in climate, air quality, and human health for 2 climate models and under 2 air pollutant emission scenarios.Design, setting, and participantsThis modeling study simulated meteorological conditions over the coterminous continental US during a 1995 to 2005 baseline and over the 21st century (2025-2100) by dynamically downscaling representations of a high warming scenario from the Community Earth System Model (CESM) and the Coupled Model version 3 (CM3) global climate models. Using a chemical transport model, PM2.5 and O3 concentrations were simulated under a 2011 air pollutant emission data set and a 2040 projection. The changes in PM2.5 and O3-attributable deaths associated with climate change among the US census-projected population were estimated for 2030, 2050, 2075, and 2095 for each of 2 emission inventories and climate models. Data were analyzed from June 2018 to June 2020.Main outcomes and measuresThe main outcomes were simulated change in summer season means of the maximum daily 8-hour mean O3, annual mean PM2.5, population-weighted exposure, and the number of avoided or incurred deaths associated with these pollutants. Results are reported for 2030, 2050, 2075, and 2095, compared with 2000, for 2 climate models and 2 air pollutant emissions data sets.ResultsThe projected increased maximum daily temperatures through 2095 were up to 7.6 °C for the CESM model and 11.8 °C for the CM3 model. Under each climate model scenario by 2095, compared with 2000, an estimated additional 21 000 (95% CI, 14 000-28 000) PM2.5-attributable deaths and 4100 (95% CI, 2200-6000) O3-attributable deaths were projected to occur. These projections decreased to an estimated 15 000 (95% CI, 10 000-20 000) PM2.5-attributable deaths and 640 (95% CI, 340-940) O3-attributable deaths when simulated using a future emission inventory that accounted for reduced anthropogenic emissions.Conclusions and relevanceThese findings suggest that reducing future air pollutant emissions could also reduce the climate-driven increase in deaths associated with air pollution by hundreds to thousands.

Dataset Information

DatAC: A visual analytics platform to explore climate and air quality indicators associated with the COVID-19 pandemic in Spain.

Publications

DatAC: A visual analytics platform to explore climate and air quality indicators associated with the COVID-19 pandemic in Spain.

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