The NSAPH Subcollection, part of the Climate-Health CAFÉ Dataverse, features data contributions from the National Studies on Air Pollution and Health (NSAPH) group based at the Harvard T.H. Chan School of Public Health.

This subcollection is focused on providing datasets related to air pollution, climate change, and public health. These datasets result from NSAPH's work in studying the environmental impacts on health outcomes and regulatory policy.

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The NSAPH Subcollection is open for reuse of the general public, but contributions are restricted to NSAPH collaborators. Instructions for NSAPH collaborators that want to upload datasets are offered in the CAFÉ Dataverse upload instructions.

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1,071 to 1,080 of 1,094 Results
PA_outside.tab
Dec 8, 2022 - Replication Data for: Investigating Use of Low-Cost Sensors to Increase Accuracy and Equity of Real-Time Air Quality Information
Tabular Data - 2.8 MB - 44 Variables, 12851 Observations - UNF:6:xR+XaZ3qdLwX5mmz1q6AKw==
Locations and IDs of outdoor PurpleAir LCS
Real_deciles_updated_1-24-2022.rds
Dec 8, 2022 - Replication Data for: Investigating Use of Low-Cost Sensors to Increase Accuracy and Equity of Real-Time Air Quality Information
Gzip Archive - 62.6 MB - MD5: b4541732492bd4e3d1962481cd42f1b9
Vector of deciles of daily PM2.5 (from the Di et al. estimates), used for empirical LCS measurement error sampling
Census data interpolated by year and zip code
Jun 27, 2022
Sabath, Ben, 2022, "Census data interpolated by year and zip code", https://doi.org/10.7910/DVN/9V5WCM, Harvard Dataverse, V1
Demographic values crosswalked from zcta to zip codes, with missing values replaced by a moving average model for each ZCTA. Data was available for the year 2000, and from 2011-2016. All other years were interpolated. Git repository: https://github.com/NSAPH/National-Causal-Analysis/tree/master/Confounders/census
census_interpolated_zips.csv
Jun 27, 2022 - Census data interpolated by year and zip code
Comma Separated Values - 140.6 MB - MD5: 9c50d2abfbcb337b4f220e36a062bbe6
Replication Data for: Combining aggregate and individual-level data to estimate individual-level associations between air pollution and COVID-19 mortality in the United States
Feb 14, 2022
Woodward, Sophie, 2022, "Replication Data for: Combining aggregate and individual-level data to estimate individual-level associations between air pollution and COVID-19 mortality in the United States", https://doi.org/10.7910/DVN/3ZU0AS, Harvard Dataverse, V1, UNF:6:D8W7/RcF4rlkKWjYBggFeQ== [fileUNF]
This is the data repository for publicly available data to reproduce analyses in Woodward, S., Wu, X., Hou, Z., Mork, D., Braun, D., Dominici, F., 2022. Combining aggregate and individual-level data to estimate individual-level associations between air pollution and COVID-19 mortality in the United States. For code, please visit https://github.com/...
census2018.tab
Feb 14, 2022 - Replication Data for: Combining aggregate and individual-level data to estimate individual-level associations between air pollution and COVID-19 mortality in the United States
Tabular Data - 21.6 MB - 24 Variables, 74001 Observations - UNF:6:g0+chDrn/3LDh2B0Y9y+ow==
census-tract level demographics, including population
census_tract_pm25_2018.tab
Feb 14, 2022 - Replication Data for: Combining aggregate and individual-level data to estimate individual-level associations between air pollution and COVID-19 mortality in the United States
Tabular Data - 2.3 MB - 3 Variables, 72538 Observations - UNF:6:wzapA1RYn0R1o35XHTQysw==
Census-tract level PM2.5 estimates. We thank Randall Martin and the members of the Atmospheric Composition Analysis Group at Dalhousie University for providing access to their open-source datasets. Their data (V4.NA.02.MAPLE) that we used can be found here: https://sites.wustl.edu/acag/datasets/surface-pm2-5/. Citation: van Donkelaar, A., R. V. Mar...
county_no2_ozone.tab
Feb 14, 2022 - Replication Data for: Combining aggregate and individual-level data to estimate individual-level associations between air pollution and COVID-19 mortality in the United States
Tabular Data - 104.4 KB - 4 Variables, 3082 Observations - UNF:6:JRO0TFYZOj2Ow9im043PKQ==
the county-level NO2 and O3 exposure data averaged across the period 2000-2016, averaged across grid cells within a zip code and then averaging across zip codes within a county. See Q. Di, H. Amini, L. Shi, I. Kloog, R. Silvern, J. Kelly, M. B. Sabath, C. Choirat,P. Koutrakis, A. Lyapustin,et al., Assessing no2 concentration and model uncertainty w...
fit12.Rdata
Feb 14, 2022 - Replication Data for: Combining aggregate and individual-level data to estimate individual-level associations between air pollution and COVID-19 mortality in the United States
R Data - 17.1 MB - MD5: 3d69104d6eec9c632662820883892dc8
Stanfit object for additional analysis 2: main analysis with data up to June 18, 2020
fit1.Rdata
Feb 14, 2022 - Replication Data for: Combining aggregate and individual-level data to estimate individual-level associations between air pollution and COVID-19 mortality in the United States
R Data - 16.3 MB - MD5: 5c2f85e19510626f10d76581729d8ceb
Stanfit object for sensitivity analysis 1
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