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Main Authors: Vega, Sofia L., Nethery, Rachel C.
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2307.09546
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author Vega, Sofia L.
Nethery, Rachel C.
author_facet Vega, Sofia L.
Nethery, Rachel C.
contents Although some pollutants emitted in vehicle exhaust, such as benzene, are known to cause leukemia in adults with high exposure levels, less is known about the relationship between traffic-related air pollution (TRAP) and childhood hematologic cancer. In the 1990s, the US EPA enacted the reformulated gasoline program in select areas of the US, which drastically reduced ambient TRAP in affected areas. This created an ideal quasi-experiment to study the effects of TRAP on childhood hematologic cancers. However, existing methods for quasi-experimental analyses can perform poorly when outcomes are rare and unstable, as with childhood cancer incidence. We develop Bayesian spatio-temporal matrix completion methods to conduct causal inference in quasi-experimental settings with rare outcomes. Selective information sharing across space and time enables stable estimation, and the Bayesian approach facilitates uncertainty quantification. We evaluate the methods through simulations and apply them to estimate the causal effects of TRAP on childhood leukemia and lymphoma.
format Preprint
id arxiv_https___arxiv_org_abs_2307_09546
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Spatio-temporal quasi-experimental methods for rare disease outcomes: The impact of reformulated gasoline on childhood hematologic cancer
Vega, Sofia L.
Nethery, Rachel C.
Applications
Although some pollutants emitted in vehicle exhaust, such as benzene, are known to cause leukemia in adults with high exposure levels, less is known about the relationship between traffic-related air pollution (TRAP) and childhood hematologic cancer. In the 1990s, the US EPA enacted the reformulated gasoline program in select areas of the US, which drastically reduced ambient TRAP in affected areas. This created an ideal quasi-experiment to study the effects of TRAP on childhood hematologic cancers. However, existing methods for quasi-experimental analyses can perform poorly when outcomes are rare and unstable, as with childhood cancer incidence. We develop Bayesian spatio-temporal matrix completion methods to conduct causal inference in quasi-experimental settings with rare outcomes. Selective information sharing across space and time enables stable estimation, and the Bayesian approach facilitates uncertainty quantification. We evaluate the methods through simulations and apply them to estimate the causal effects of TRAP on childhood leukemia and lymphoma.
title Spatio-temporal quasi-experimental methods for rare disease outcomes: The impact of reformulated gasoline on childhood hematologic cancer
topic Applications
url https://arxiv.org/abs/2307.09546