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Revealing Environmental Causes of Preterm Births in a Quasi-Experimental Framework

CORDIS · observation · Publication date unknown

preterm births by evaluating environmental policy changes in a quasi-experimental setting. This interdisciplinary project will devise a robust and novel methodology through embedding data science and artificial intelligence within an epidemiology framework to: 1) systematically identify policy changes targeting environmental factors, 2) evaluate their role on preterm birth rates in time and space (quasi-experimental framework), 3) draw causal inferences integrating original and previous evidence on the impact of these environmental factors on preterm births. The Experienced Researcher (ER) will advance his skills in environmental science, public health, epidemiology and informatics through high-calibre external and in-house training from the host institution. TinyTrend will leverage high-quality population-wide administrative health data from Lombardy (Italy), including 1M pregnancies for the 2010-2023 period, and generate a new FAIR dataset of policy changes. For the first time, the ER will combine both data sources in an interrupted time series analysis with control series to gener

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recordType

award

status

SIGNED

region

EU

value

172750.08

unit

EUR