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1.
Biometrics ; 79(3): 2220-2231, 2023 09.
Artigo em Inglês | MEDLINE | ID: mdl-35996756

RESUMO

Many spatial phenomena exhibit interference, where exposures at one location may affect the response at other locations. Because interference violates the stable unit treatment value assumption, standard methods for causal inference do not apply. We propose a new causal framework to recover direct and spill-over effects in the presence of spatial interference, taking into account that exposures at nearby locations are more influential than exposures at locations further apart. Under the no unmeasured confounding assumption, we show that a generalized propensity score is sufficient to remove all measured confounding. To reduce dimensionality issues, we propose a Bayesian spline-based regression model accounting for a sufficient set of variables for the generalized propensity score. A simulation study demonstrates the accuracy and coverage properties. We apply the method to estimate the causal effect of wildland fires on air pollution in the Western United States over 2005-2018.


Assuntos
Poluição do Ar , Estados Unidos , Pontuação de Propensão , Teorema de Bayes , Causalidade , Simulação por Computador
2.
Geohealth ; 3(12): 443-457, 2019 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-32159029

RESUMO

Smoke Sense is a citizen science project with investigative, educational, and action-oriented objectives at the intersection of wildland fire smoke and public health. Participants engage with a smartphone application to explore current and forecast visualizations of air quality, learn about how to protect health from wildfire smoke, and record their smoke experiences, health symptoms, and behaviors taken to reduce their exposures to smoke. Through participation in the project, individuals engage in observing changes in their environment and recording changes in their health, thus facilitating progression on awareness of health effects of air pollution and adoption of desired health-promoting behaviors. Participants can also view what others are reporting. Data from the pilot season (1 August 2017 to 7 January 2018; 5,598 downloads) suggest that there is a clear demand for personally relevant data during wildfire episodes motivated by recognition of environmental hazard and the personal concern for health. However, while participants shared clear perceptions of the environmental hazard and health risks in general, they did not consistently recognize their own personal health risk. The engagement in health protective behavior was driven in response to symptoms rather than as preventive courses of action. We also observed clear differences in the adoption likelihood of various health protective behaviors attributed to barriers and perceived benefits of these actions. As users experience a greater number and severity of symptoms, the perceived benefits of taking health protective actions exceeded the costs associated with the barriers and thus increased adoption of those actions. Based on pilot season data, we summarize key insights which may improve current health risk communications in nudging individuals toward health protective behavior; there is a need to increase personal awareness of risk and compelling evidence that health protective behaviors are beneficial.

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