DDI2.5 XML CODEBOOK RECORD FOR STUDY NUMBER 855911 Collection of Mortality from Selected Respiratory Illnesses in a Number of Prominent UK Cities, 1895-1956
We utilize the reports compiled by the Medical Officer of Health (MOH) to gather information on mortality from different respiratory diseases, focussing on Influenza, Pneumonia and Bronchitis. We catalogue annual mortality rates for different diseases for Belfast, Birmingham, Cardiff, Glasgow, Liverpool, London, Manchester and Sheffield. The dataset covers the years 1895 to 1956.This research aims to assess the medium-run implications of COVID-19 on income and health inequality, and possible policies that aim to mitigate these effects. The medium run is important because the impacts of COVID-19 on inequality are expected to persist for many years. Understanding how inequality changes over the medium run, and assessing mitigation policies beyond the short term, requires information on the evolution of income and health inequalities several years after an outbreak. To achieve this, we will combine models typically applied to modern datasets with quantitative data from historical periods that, unlike contemporary data, cover extended post-outbreak periods. We will use records from Glasgow since the end of the 19th century, covering a period of intense and volatile economic activity, as well as multiple disease outbreaks. We choose Glasgow because it is a large city demonstrating similar inequalities to those seen today, and because administrative records for Glasgow provide detailed relevant information. Our approach is the following. We will use a modelling framework that has been shown to be effective in capturing income inequality and the effects of recessions on this inequality. We will extend the modelling approach to also include health inequalities and ensure that both income and health inequalities are represented accurately using recent datasets. To set up the model so that it captures the effects of outbreaks on inequalities, we will use historical data from earlier times that include large disease outbreaks. The model will then allow us to examine the effects of different policy interventions for households with different socioeconomic characteristics. We have manually entered the data using MOH reports available at the Wellcome Library (https://wellcomelibrary.org/). Mortality from different causes is recorded as “Death/Million Living”, as reported in the relevant table in the MOH Report. For the years when rates are unavailable, figures have been compiled from the table containing “Total Deaths” and available population figures. Most of the variables of interest are reported consistently over time, but sometimes changes in the internal reporting mean that deaths are shifted between causes (particularly between Pneumonia, Bronchitis, Bronchio-Pneumonia and other respiratory illnesses). Care should be taken, when comparing deaths across time.
2022, DISEASES, Demography population, EPIDEMIOLOGY, HISTORY, Health, vital statistics and censuses, Humanities
2022, DISEASES, Demography population, EPIDEMIOLOGY, HISTORY, Health, vital statistics and censuses, Humanities
We utilize the reports compiled by the Medical Officer of Health (MOH) to gather information on mortality from different respiratory diseases, focussing on Influenza, Pneumonia and Bronchitis. We catalogue annual mortality rates for different diseases for Belfast, Birmingham, Cardiff, Glasgow, Liverpool, London, Manchester and Sheffield. The dataset covers the years 1895 to 1956.This research aims to assess the medium-run implications of COVID-19 on income and health inequality, and possible policies that aim to mitigate these effects. The medium run is important because the impacts of COVID-19 on inequality are expected to persist for many years. Understanding how inequality changes over the medium run, and assessing mitigation policies beyond the short term, requires information on the evolution of income and health inequalities several years after an outbreak. To achieve this, we will combine models typically applied to modern datasets with quantitative data from historical periods that, unlike contemporary data, cover extended post-outbreak periods. We will use records from Glasgow since the end of the 19th century, covering a period of intense and volatile economic activity, as well as multiple disease outbreaks. We choose Glasgow because it is a large city demonstrating similar inequalities to those seen today, and because administrative records for Glasgow provide detailed relevant information. Our approach is the following. We will use a modelling framework that has been shown to be effective in capturing income inequality and the effects of recessions on this inequality. We will extend the modelling approach to also include health inequalities and ensure that both income and health inequalities are represented accurately using recent datasets. To set up the model so that it captures the effects of outbreaks on inequalities, we will use historical data from earlier times that include large disease outbreaks. The model will then allow us to examine the effects of different policy interventions for households with different socioeconomic characteristics. We have manually entered the data using MOH reports available at the Wellcome Library (https://wellcomelibrary.org/). Mortality from different causes is recorded as “Death/Million Living”, as reported in the relevant table in the MOH Report. For the years when rates are unavailable, figures have been compiled from the table containing “Total Deaths” and available population figures. Most of the variables of interest are reported consistently over time, but sometimes changes in the internal reporting mean that deaths are shifted between causes (particularly between Pneumonia, Bronchitis, Bronchio-Pneumonia and other respiratory illnesses). Care should be taken, when comparing deaths across time.