The role that in-person schooling contributes to community incidence of SARS-CoV-2 infections and deaths remains unknown. We conducted an event study evaluating the effect of in-person school on SARS-CoV-2 cases and deaths per 100,000 persons during the 12-weeks following school opening, stratified by US Census region. There was no impact of in-person school opening and COVID-19 deaths. In most regions, COVID-19 incidence rates were not statistically different in counties with in-person versus remote school modes. However, in the South, there was a significant and sustained increase in cases per week among counties that opened for in-person learning versus remote learning, with weekly effects ranging from 7.8 (95% CI: 1.2–14.5) to 18.9 (95% CI: 7.9–29.9) additional cases per 100,000, driven by increases among 0–9 year olds and adults.
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Sep 10, 2021
Ertem, Zeynep; Schechter-Perkins, Elissa; Oster, Emily; Van den Berg, Polly; Epshtein, Isabella; Chaiyakunapruk, Nathorn; Wilson, Fernando; Perenchevich, Elli; Pettey, Warren; Branch-Elliman, Westyn; Nelson, Richard, 2021, "Replication Data for: Impact of School Opening on SARS-CoV-2 Transmission", https://doi.org/10.7910/DVN/1XDSS9, Harvard Dataverse, V1, UNF:6:RizJaTj9UA/b1wm47z0hRg== [fileUNF]
This repository includes files to prepare the data for the paper titled as The Impact of School Opening Model on SARS-CoV-2 Community Incidence and Mortality: A Nationwide Cohort Study by Ertem et al.
Tabular Data - 46.8 MB - 431 Variables, 20165 Observations - UNF:6:LfM6/cAGoE4mP4dZ00Ouxg==
The final data for each county per week with the covariates mentioned in the data dictionary. Note that the covariates from the Burbio Data and CDC Restricted Data are excluded due to data sharing agreements. Please request them for yourself to obtain the full data used for the paper.
Stata Syntax - 1.0 MB - MD5: dd164689585048b3660213fffaa17602
Stata code to produce the analysis and figures in the paper
Tabular Data - 61.8 KB - 5 Variables, 473 Observations - UNF:6:tUc/w8MSDQttn3sLaXuZAA==
This data dictionary explains each field in the final dataset.
Markdown Text - 1.4 KB - MD5: 7ff6638e508daf1507c5ec8c4a38b7ac
General information about this dataset.
Plain Text - 1.3 KB - MD5: 1b620b3e6ce72d748d634110e43eb230
Jupyter Notebook - 12.5 KB - MD5: ffa434781e0eef67ae6940b3a7b09911
These iPython notebook files can be used to construct the data used for this paper from scratch.
Jupyter Notebook - 3.6 KB - MD5: 0e1d1186eedccafb7d06cbeece96bd8b
These iPython notebook files can be used to construct the data used for this paper from scratch.
Jupyter Notebook - 20.0 KB - MD5: 8f713474b870468e498556e87f2db038
These iPython notebook files can be used to construct the data used for this paper from scratch.
Jupyter Notebook - 6.3 KB - MD5: 28a766ccf2d5e5dbc7e9bbf6f1054ae0
These iPython notebook files can be used to construct the data used for this paper from scratch.
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