DOI: 10.5061/dryad.fn2z34trn
title: School exemptions in the United States

description: Once-eliminated vaccine-preventable childhood diseases, such as measles,
 are resurging across the United States. Understanding the spatio-temporal
 trends in vaccine exemptions is crucial to targeting public health
 intervention to increase vaccine uptake and anticipating vulnerable
 populations as cases surge. However, prior available data on childhood
 disease vaccination is either on too rough a spatial scale for this
 spatially-heterogeneous issue, or is only available for small geographic
 regions, making general conclusions infeasible. Here, we have collated
 school vaccine exemption data across the United States and provide it at
 the county-level for all years available. We demonstrate the fine-scale
 spatial heterogeneity in vaccine exemption levels, and show that many
 counties may fall below the herd immunity threshold. We also show that
 vaccine exemptions increase over time in most states, and non-medical
 exemptions are highly prevalent where allowed. Our dataset also highlights
 the need for greater data sharing and standardized reporting across the
 United States. 
description: We collected data from all US states where school vaccine
 exemption information was freely available from the Department of Health
 website in any format. We were able to locate that data in 24
 states. Within these states, the number of years available varied
 relatively widely, between 19 years in California and a single year in 6
 states. The most represented year in our dataset was 2017 (corresponding
 to school year 2017-2018).  Because the dataset was compiled in June-July
 2019, we note that it is possible that additional data for recent years
 may not be available, or that data may have become available in additional
 states not included in our dataset.  The data format
 varied widely between states, and exemptions were reported either as a
 number of exemptions or as a percentage of the enrolled students. We have
 elected to use number of students rather than percentages, and have
 transformed data as needed. For most states included in our dataset, the
 data are provided at the county level. <br> In several states
 (Arizona, Colorado, Illinois, Maine, Michigan, South Dakota, Tennessee,
 Vermont, Oregon, and Washington), the data was provided at the school
 level, which we aggregated to the county. Additional data processing was
 necessary in some cases. In Virginia, data was provided by school name,
 but county or city information was not included. We used a list of public
 and private schools to match school names with their respective county
 using fuzzy matching (with the `fuzzywuzzy` Python package) with an 80\%
 matching requirement. Our algorithm was unable to find a suitable match
 for between 3.8\% and 6.8\% of schools (depending on year), and these
 schools were not included in the final counts at the county level.
 Similarly, in Idaho, data at the school level included city information
 but county was not provided. We first matched city and county names,
 before aggregating the exemption data at the county level. Finally in New
 York state, exemptions were provided as percentages at the school level
 but enrollment information was not included. We obtained enrollment for
 public and private schools separately from the New York State Education
 Department, and used the school unique code to calculate exemption number
 from enrollment and exemption percentages. We then aggregated these
 numbers at the county level.  States reported data for
 exemptions based on varying definitions, so we selected data records based
 on data availability to make the data comparable cross states. We aimed to
 achieve parsimonious definitions of total medical exemptions, total
 non-medical exemptions, and total exemptions, which includes both types of
 exemptions. We define medical exemptions as reported total medical
 exemptions. In Florida, permanent medical exemptions were reported
 separately from temporary medical exemptions, so permanent medical
 exemptions was chosen to represent total medical exemptions. To define
 total non-medical exemptions, we considered the state law regarding
 non-medical exemptions and the data availability. If the state reported
 total aggregated non-medical exemptions, that was selected as total
 non-medical exemptions. If the state reported only religious exemptions
 and only allows religious exemptions, that was selected as total
 non-medical exemptions. If the state reported only religious exemptions,
 but also allows philosophical exemptions, that was considered missing
 data. If the state allows philosophical exemptions and only reports
 philosophical exemptions, that was selected as total non-medical
 exemptions, as the state may not differentiate religious from
 philosophical. If the state allows philosophical exemptions and reports
 both religious and philosophical exemptions separately, these values were
 summed for total non-medical exemptions. To define total exemptions, if
 the state reported a total exemptions value, this value was used. If the
 state did not report a total exemptions value, but reported values for
 total medical exemptions and total non-medical exemptions, as defined
 above, these were summed for total exemptions. If the state was missing
 either medical or non-medical exemptions, but reported the total number of
 students with completed vaccinations, the total exemptions was the
 difference between the number of students enrolled and the number of
 students completed.  We also considered
 disease-specific exemptions reports. If a state reported the number of
 exemptions for a vaccine specific to a given infection, that value was
 used. If the state did not report exemptions, but did provide the total
 number complete for that disease, the difference between the enrolled
 students and the completed students was used. For pertussis-specific
 vaccination, we used DTaP exemptions where available, and TDaP exemptions
 where DTaP was not available. For measles-specific vaccination, if
 separate reports were available for measles, mumps, and rubella, the value
 for measles was used. If measles was not available, then the mumps or
 rubella exemptions were used, if available. The data in
 the figures is only data reported for kindergartens in states where
 kindergarten-specific data was available, or K-12 data in states where
 kindergarten-specific data was not reported. States reported age groups
 heterogeneously, and data by other age groups is available in the data
 file.
description: This dataset contains: 1) a master file of cleaned and joined
 data. This dataset contains the year, state, county FIPS code, and
 pertinent age group for each record. Each county-year combination that is
 available has entries for total enrolled, total medical exemptions, total
 non-medical exemption, religious exemptions, philosophical exemptions,
 pertussis exemptions, measles exemptions, varicella exemptions, and flu
 exemptions.  2) the raw and uncleaned files that were
 used to produce the master file. There is a file for each state-year
 combination available. The columns included are: Year:
 year that data is reported for State: name of
 state County: name of county
 School_district: name of school district City:
 name of city Number_reporting: number of establishments
 within the given reporting area (e.g., number of schools contributing data
 within a given county or district) School: name of
 school, where data is at the school level
 Public/private: whether data is reported by public schools only,
 private schools only, or both Age: what age groups the
 data is reported for (CC: childcare/preschool, KG: kindergarten, FG: first
 grade, MS: middle school/6th/7th grade, K12: kindergarten-high
 school/mixed grades) Total_enrolled: total number of
 students for the given reporting area (e.g., school, district, or
 county) Total_completed: total number of students that
 are up-to-date/compliant for all vaccines required by a particular
 reporting area (e.g., county or state) Total_exempt:
 total number of students exempt for 1+ vaccines for under any type of
 exemption within the given reporting area ME_total: all
 medical exemptions for the given reporting area (e.g., both permanent and
 temporary) PME_total: all permanent medical exemptions
 for the given reporting area TME_total: all temporary
 medical exemptions for the given reporting area
 PBE_total: total number of students with any type of personal
 belief exemption for 1+ vaccine within the given reporting area (e.g., no
 distinction between philosophical or religious belief
 exemptions) PBE_total-philosophy: total number of
 students with a philosophical exemption for 1+ vaccine within the given
 reporting area PBE_total-religion: total number of
 students with a religious belief exemption for 1+ vaccine within the given
 reporting area **PBE_total does not
 necessarily equal (PBE_total-philosophy + PBE_total-religion). Some states
 report additional exemptions (e.g., McKinney-Vento exemption for children
 experiencing homelessness) and reasons for non-compliance (conditional
 school entrance), while others do not. For states that do not report these
 other exceptions, it is unclear what the true total number of exemptions
 is and so the PBE_total column is left empty. TDaP:
 completion of all recommended TDaP doses TDaP_exempt:
 exemptions for TDaP vaccine Var: completion of all
 recommended varicalla doses Var_exempt: exemptions for
 varicella vaccine HepB: completion of all recommended
 HepB doses HepB_exempt: exemptions for HepB
 vaccine HepA: completion of all recommended HepA
 doses HepA_exempt: exemptions for HepA
 vaccine MMR: completion of all recommended MMR
 doses Mumps_exempt: exemptions for mumps
 vaccine Rubella_exempt: exemptions for rubella
 vaccine Measles2: completion of all recommended measles
 vaccine doses Measles2_exempt: exemptions for measles
 vaccine Polio(IPV): completion of all recommended IPV
 doses Polio(IPV)_exempt: exemptions for polio
 vaccine DTaP: completion of all recommended DTaP
 doses DTaP_exempt: exemptions for DTaP
 vaccine HIB1: completion of all recommended HIB1
 doses HIB1_exempt: exemptions for HIB1
 vaccine MCV4: completion of all recommended MCV4
 doses MCV4_exempt: exemptions for MCV4
 vaccine PCV13: completion of all recommended PCV13
 doses PCV13_exempt: exemptions for PCV13
 vaccine Influenza: completion of all recommended
 influenza vaccine doses Influenza_exempt: exemptions
 for influenza vaccine No_record: the number of students
 for which the institution was not able to acquire/report their
 immunization record States report different data in
 different formats.  The code used to produce the
 figures included in the manuscript as well as the full cleaned and raw
 datasets are available on Github at
 https://github.com/bansallab/exemptions-landscape. The code runs in Python
 3.6.