Geovisual analytics of historical morbidity and mortality data of Tuberculosis and Diphteria in Zürich in the late 1920s and early 1930s

Tuberculosis and diphtheria are two infectious diseases that continue to be a major global health concern, particularly in developing countries. For instance, in 2023 alone, over one million lives were claimed by tuberculosis alone. Nevertheless, significant improvements have been made compared to the 19th and 20th centuries, when both diseases claimed a much higher death toll. This master’s thesis aims to explore the distribution of tuberculosis and diphtheria cases in the city of Zurich in the late 1920s and early 1930s with a focus on geographical patterns and socioeconomic status. While there have been similar studies on the spread of other diseases, these have focused on other cities and diseases, most notably London for cholera, and more recently, Basel, (the canton of) Berne for the 1918-1920 influenza pandemic and emerging cities of developing countries. This thesis will explore the history of Zurich’s fight against tuberculosis and diphtheria in relation to socioeconomic indicators, while aiming to provide new insights into its course, which could be central to understanding further developments in Zurich's health policy and geography of health. The dataset encompasses single case entries with attributes including registration dates, gender, age, occupation, place of residence, hospital treatment and mortality rates. Utilising these attributes, visualisations and clustering analyses were conducted. The results indicate a stronger socioeconomically underpinned clustering for tuberculosis than for diphtheria. Moreover, the mortality and case numbers in general are higher for tuberculosis. When contextualised within a historical framework, it is evident that the case numbers of both tuberculosis and diphtheria case numbers had declined from their respective peak values in the late 19th century, although tuberculosis remained a major public health problem. Consequently, during the time period under investigation, tuberculosis was identified as the most prevalent chronic disease. Conversely, diphtheria, often referred to as the “strangling angel” of children had already experienced a significant decline in its prevalence and mortality. The investigation revealed that both diseases exhibited clustering behaviour in space. However, during more thorough analyses conducted, age and particularly social class emerged as the only significant influences on tuberculosis mortality, while no significant influences on diphtheria mortality manifested themselves. The absence of statistical significance in the diphtheria data may be attributed to the limited number of fatalities, which rendered the sample size inadequate for conducting a meaningful analysis.

Publication Details

Journal
Zurich Open Repository and Archive (University of Zurich)
Published
2025-04-17
DOI
https://doi.org/10.5167/uzh-278853
Primary Topic
Data-Driven Disease Surveillance
Type
article
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article

Geovisual analytics of historical morbidity and mortality data of Tuberculosis and Diphteria in Zürich in the late 1920s and early 1930s

Zurich Open Repository and Archive (University of Zurich)
Data-Driven Disease Surveillance
article

Geovisual analytics of historical morbidity and mortality data of Tuberculosis and Diphteria in Zürich in the late 1920s and early 1930s

article en

Abstract

Tuberculosis and diphtheria are two infectious diseases that continue to be a major global health concern, particularly in developing countries. For instance, in 2023 alone, over one million lives were claimed by tuberculosis alone. Nevertheless, significant improvements have been made compared to the 19th and 20th centuries, when both diseases claimed a much higher death toll. This master’s thesis aims to explore the distribution of tuberculosis and diphtheria cases in the city of Zurich in the late 1920s and early 1930s with a focus on geographical patterns and socioeconomic status. While there have been similar studies on the spread of other diseases, these have focused on other cities and diseases, most notably London for cholera, and more recently, Basel, (the canton of) Berne for the 1918-1920 influenza pandemic and emerging cities of developing countries. This thesis will explore the history of Zurich’s fight against tuberculosis and diphtheria in relation to socioeconomic indicators, while aiming to provide new insights into its course, which could be central to understanding further developments in Zurich's health policy and geography of health. The dataset encompasses single case entries with attributes including registration dates, gender, age, occupation, place of residence, hospital treatment and mortality rates. Utilising these attributes, visualisations and clustering analyses were conducted. The results indicate a stronger socioeconomically underpinned clustering for tuberculosis than for diphtheria. Moreover, the mortality and case numbers in general are higher for tuberculosis. When contextualised within a historical framework, it is evident that the case numbers of both tuberculosis and diphtheria case numbers had declined from their respective peak values in the late 19th century, although tuberculosis remained a major public health problem. Consequently, during the time period under investigation, tuberculosis was identified as the most prevalent chronic disease. Conversely, diphtheria, often referred to as the “strangling angel” of children had already experienced a significant decline in its prevalence and mortality. The investigation revealed that both diseases exhibited clustering behaviour in space. However, during more thorough analyses conducted, age and particularly social class emerged as the only significant influences on tuberculosis mortality, while no significant influences on diphtheria mortality manifested themselves. The absence of statistical significance in the diphtheria data may be attributed to the limited number of fatalities, which rendered the sample size inadequate for conducting a meaningful analysis.

Zurich Open Repository and Archive (University of Zurich)
Openalex Percentile: Top 46%
Data-Driven Disease Surveillance
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