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Broadstreet COVID-19 Data Project

BroadStreet - United States COVID-19 Executive Orders Dataset

In April 2020, BroadStreet and The COVID-19 Data Project partnered with Temple University's Center for Public Health Law Research (CPHLR) to look longitudinally at executive orders, health directives, proclamations, and policies related to COVID-19. We have refined CPHLR's process, enabling the collection of city, state, and US territory orders which are then reduced to quantitative and qualitative data to allow for simple access and analysis.

The most data release occurred on July 31st, 2022. This data release has two versions: orders from A-C that have been standardized (“Clean Data”), and orders from D-W locations that haven’t been standardized (“Raw Data”).

Part I: Raw Data

Structure

The data is in wide format. It is stored in a csv file with the following 23 column fields.

Content

field_name description value
iden_num The identification number of the location using FIPS codes
geo_type Whether the order applies to a city/state/territory
name The text name of the city/state/territory
order_num The name of the Executive Order or Proclamation
amend If the order is an amendment to a previous order 0=no, 1=yes
start_d The date that the order goes into effect MM/DD/YYYY; with leading zeros (02/17/2009); 0=no date
end_d The date that the order will no longer be in effect MM/DD/YYYY; with leading zeros (02/17/2009; 0=no date
initial_emgcy If the order is the initial state of emergency declaration 0=no, 1=yes
cont_emgcy If the order has been released in response to COVID-19 pandemic 0=no, 1=yes
reopen If the order contains measures related to re-opening 0=no, 1=yes
stay_home If the order contains measures related to stay at home directives 0=no, 1=yes
curfew If the order contains measures related to mandated or suggested curfew 0=no, 1=yes
mask_req If the order contains measures related to mask/face-covering requirements 0=no, 1=yes
gather_ban If the order contains measures related to gathering ban 0=no, 1=yes
social_dist If the order contains measures related to social distancing 0=no, 1=yes
bsns If the order contains measures related to the operation of businesses 0=no, 1=yes
restaurant If the order contains measures related to the operation of restaurants 0=no, 1=yes
school If the order contains measures related to the operation of schools 0=no, 1=yes
med_proc If the order contains measures related to medical procedures 0=no, 1=yes
travel If the order contains measures related to travel restrictions 0=no, 1=yes
correc_fac If the order contains measures related to correctional facilities 0=no, 1=yes
vaccine If the order contains measures related to the COVID-19 vaccine 0=no, 1=yes
notes Notes about the Order or Proclamation

Methodology

On a weekly basis, new releases of Executive Orders are pulled from The Council of State Governments and public health department websites before being converted, read, and coded for a quality assurance process by the Policy Track team. Each order is reviewed and compared with the current COVID-19 statutes, regulations, emergency declarations, and mitigation policies dating back to January 20, 2020, as it is the day prior to the first confirmed case of COVID-19 by the Centers for Disease Control and Prevention.

The original format of the documents is either HTML or PDF. Once the documents have been converted into the Google Doc format, the direct links are incorporated to the shared spreadsheet for the data entry teams to access. Both conversion methods generate spelling and formatting inconsistencies which must be corrected manually. Manual correction may include "auto spell check," image removal, border removal, and/or hand-typing documents in full. The scope topics and descriptions have been created by Policy Track leaders based on CPHLR's "protocol notes." Data entry following the CPHLR protocols includes the analysis and mark-up of the documents and the entering of binary variables pertaining to the inclusion of "in-scope" content. The marked-up document provides the Track leaders and the Quality Assurance (QA) team members with important information and creates a track record of the logged binary variables. The individuals place a 0 (zero) in cells to signify a document does not contain content about the given scope topics; a 1 (one) is placed in cells to signify a document does contain content about the given scope topics. Any ambiguous information in the documents is noted and a detailed review is conducted by the QA team to determine if the content is applicable to the scope topics.

State and territory orders are gathered weekly and typically included in our data one week after they were released. New city and county and federal orders are gathered monthly and currently included in our data when the quantity of released state and territory orders is low. All city and county orders are stored on a spreadsheet for reference as new orders are identified.

Part II: Clean Data

In May 2022, Policy Track interns established a protocol to standardize the naming convention of collected orders. This is to identify duplicate orders and link the dataset to the machine-readable files. In addition, a new scope of ‘Governing Body’ is added. It was noted that different entities were responsible for writing the order: the options are Executive Authority and Public Health Department.

Structure

The data is in wide format. It is stored in a csv file with the following 25 column fields.

Content

field_name description value
iden_num The identification number of the location using FIPS codes
geo_type Whether the order applies to a city/state/territory
name The text name of the city/state/territory
order_num The name of the Executive Order or Proclamation
broadstreet_num The assigned BroadStreet name of the order
gov_body The entity that wrote the order
amend If the order is an amendment to a previous order 0=no, 1=yes
start_d The date that the order goes into effect MM/DD/YYYY; with leading zeros (02/17/2009); 0=no date
end_d The date that the order will no longer be in effect MM/DD/YYYY; with leading zeros (02/17/2009; 0=no date
initial_emgcy If the order is the initial state of emergency declaration 0=no, 1=yes
cont_emgcy If the order has been released in response to COVID-19 pandemic 0=no, 1=yes
reopen If the order contains measures related to re-opening 0=no, 1=yes
stay_home If the order contains measures related to stay at home directives 0=no, 1=yes
curfew If the order contains measures related to mandated or suggested curfew 0=no, 1=yes
mask_req If the order contains measures related to mask/face-covering requirements 0=no, 1=yes
gather_ban If the order contains measures related to gathering ban 0=no, 1=yes
social_dist If the order contains measures related to social distancing 0=no, 1=yes
bsns If the order contains measures related to the operation of businesses 0=no, 1=yes
restaurant If the order contains measures related to the operation of restaurants 0=no, 1=yes
school If the order contains measures related to the operation of schools 0=no, 1=yes
med_proc If the order contains measures related to medical procedures 0=no, 1=yes
travel If the order contains measures related to travel restrictions 0=no, 1=yes
correc_fac If the order contains measures related to correctional facilities 0=no, 1=yes
vaccine If the order contains measures related to the COVID-19 vaccine 0=no, 1=yes
notes Notes about the Order or Proclamation

About Us

The Covid-19 Data Project began in March 2020 to satisfy the driving need for accessible data tracking the spread of the coronavirus across the United States. Over 120 interns and volunteers were recruited via the BroadStreet website, and through institutional reference for interested undergraduate or graduate students. The project quickly grew as the virus spread, leading to a large data set involving historical and present data collection, input, and analysis.

Suggested Citation

When using data images, downloaded data, or shared document formats, please attribute BroadStreet as well as the original source, when applicable. For examples and more information, review this article which answers the question "How do I cite BroadStreet?"

Contributors

Isaiah Banta, Robert Birds, Samin Charepoo, Alessandro Malave, Allison Muir, MHA. A full list of the Broadstreet Covid-19 Data Project volunteers can be found at https://covid19dataproject.org/team-2/

Questions / Feedback

Email the primary contributors at: hello@broadstreet.io