John Snow and Causal Inference

Vikram Dayal () and Anand Murugesan ()
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Vikram Dayal: Institute of Economic Growth
Anand Murugesan: Central European University

Chapter Chapter 1 in Demystifying Causal Inference, 2023, pp 1-17 from Springer

Abstract: Abstract In the early months of 2020, the world was caught off guard as the COVID-19 pandemic spread rapidly. Epidemiologists and medical experts scrambled to understand its cause and mode of transmission. The pressing question was: what was driving the outbreaks, and how was the virus transmitted? Initially, health policy officials advised the public to focus on handwashing and avoid close contact. They assumed that the contagion spread through physical proximity and contact, much like the common cold. However, thanks to the accumulation of knowledge, advanced statistical methods, and technological advancements, experts swiftly identified the true vector of transmission: airborne aerosols carrying the coronavirus. Within a matter of weeks, wearing face masks became mandatory worldwide, reflecting the importance of rapidly identifying the cause for effective policy responses.

Keywords: Causal reasoning; John Snow; Broad Street pump; Difference-in-differences; Quasi-experimental design; Instrumental variables; Causal graphs (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-99-3905-3_1

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DOI: 10.1007/978-981-99-3905-3_1

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