DOI: 10.5061/dryad.rbnzs7hfx
title: Data and code for: Local infectious disease experience influences vaccine refusal rates: a natural experiment

description: Vaccination has been critical to the decline in infectious disease
 prevalence in recent centuries. Nonetheless, vaccine refusal has increased
 in recent years, with complacency associated with reductions in disease
 prevalence highlighted as an important contributor. We exploit a natural
 experiment in Glasgow at the beginning of the 20th century to investigate
 whether prior local experience of an infectious disease matters for
 vaccination decisions. Our study is based on smallpox surveillance data
 and administrative records of parental refusal to vaccinate their infants.
 We analyse variation between administrative units of Glasgow in cases and
 deaths from smallpox during two epidemics over the period 1900–1904, and
 vaccine refusal following its legalisation in Scotland in 1907 after a
 long period of compulsory vaccination. We find that lower local disease
 incidence and mortality during the epidemics were associated with higher
 rates of subsequent vaccine refusal. This finding indicates that
 complacency influenced vaccination decisions in periods of higher
 infectious disease risk, responding to local prior experience of the
 relevant disease, and has not emerged solely in the context of the
 generally low levels of infectious disease risk of recent decades. These
 results suggest that vaccine delivery strategies may benefit from
 information on local variation in incidence.
description: <strong>Overview of the record</strong>
 This record provides the main analysis dataset for the following
 paper: Angelopoulos K, Stewart G, Mancy
 R. 2022 Local infectious disease experience influences vaccine refusal
 rates: a natural experiment. Proc. R. Soc. B 20221986. https://doi.org/10.1098/rspb.2022.1986 It also serves as a portal for the remaining code and datasets used in the paper. Specifically, the upload consists of: The main analysis dataset, hosted directly in DataDryad as an Excel spreadsheet. This is the final dataset used to conduct the statistical analysis reported in the paper. 'Related Works: Software': a link to the R code used for the data transformations and analysis, and hosted on Zenodo. Note that this also includes a copy of the main dataset and the shapefiles in (3) below. 'Related Works: Dataset': a link to the shapefiles used to generate maps and other spatial manipulations required for the manuscript, and hosted on Zenodo Each Related Work contains its own README files and/or appropriate documentation. The following is a description of the methods for constructing the main dataset (1).   <strong>Main dataset construction and processing</strong> COV_Main_Dataset.xlsx contains data relating to smallpox and conscientious object to smallpox vaccination (COV), alongside socioeconomic variables, at municipal ward and registration district level for Glasgow 1900-1913. It contains the following worksheets:  Data dictionary: provides descriptions of variables and explains abbreviations used.  Ward_All: provides variables at municipal ward level, for all 25 wards that existed in Glasgow in 1900.  W_Drop_Blyt_Exch: provides variables at municipal ward level, excluding two atypical central wards, Blythswood and Exchange.  RD_All: provides variables at registration district level, for all 20 registration districts, or parts of these registration districts that cover the area of the 25 municipal wards that existed in 1900.  RD_Drop_Blyt: provides variables at registration district level, excluding Blythswood where the maternity hospital was situated and where data are atypical. To construct this dataset, data were first manually transcribed into Excel, primarily from Medical Officer of Health reports and census reports. They were then processed in R as described in the manuscript (code and further documentation are available in 'Related Works: Software', a repository that also includes the raw dataset as transcribed). The file provided here is the final dataset used for the statistical analysis reported in the paper.
description: <strong>Usage
 notes</strong> The main analysis
 dataset: provided as an Excel spreadsheet that can be opened with Excel or
 open-source alternative such as OpenOffice.
 'Related Works: Software': a link to the R code. This
 can be opened using R, R Studio or similar code editors, and run in R.
 This repository also contains Excel files and CSV files, as well as
 shapefiles. These can all be opened/imported into R using the code
 provided. Excel and CSV files can also be opened in Excel or open-source
 alternative such as OpenOffice. Shapefiles can be opened in R, or other
 GIS software such as the open-source software package QGIS.
 'Related Works: Dataset': a link to a collection of
 shapefiles. Shapefiles can be opened in R, or other GIS software such as
 the open-source software package QGIS. 
 <strong>How to cite </strong> 
 Reuse of the <em>main analysis dataset</em> and/or
 other information included in the <em>R code repository</em>:
 please cite the paper and this DataDryad record.
 Reuse of the <em>shapefile(s)</em> only: please cite
 the paper and the shapefiles collection. 
 Citation for paper Angelopoulos K, Stewart G, Mancy
 R. 2022 Local infectious disease experience influences vaccine refusal
 rates: a natural experiment. Proc. R. Soc. B 20221986. https://doi.org/10.1098/rspb.2022.1986 Citation for this DataDryad Record Angelopoulos, Konstantinos; Mancy, Rebecca; Stewart, Gillian (2023), Data and code for Angelopoulos, Stewart and Mancy (2023) "Local infectious disease experience influences vaccine refusal rates: a natural experiment", Proceedings of the Royal Society B: Biological Sciences., Dryad, Dataset, https://doi.org/10.5061/dryad.rbnzs7hfx Citation for shapefiles collection Mancy, Rebecca. (2023). Shapefiles of administrative boundaries, Subway and main rivers in Glasgow, UK, around 1910 (1.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7550897