Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
6 authors.
Jie K HuDepartment of Statistics, The Ohio State University College of Arts and Sciences, Cockins Hall, 1958 Neil Ave, Columbus, OH, USA.ORCID 0000-0002-7987-8419
Ana TrišovićComputer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology, 32 Vassar St., Cambridge, MA, USA.ORCID 0000-0003-1991-0533
Ankita BakshiEsri, 380 New York Street, Redlands, CA, USA.
Danielle BraunDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, USA.ORCID 0000-0002-5177-8598
Francesca DominiciDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, USA.ORCID 0000-0002-9382-0141
Joan A CaseyDepartment of Environmental and Occupational Health Sciences, University of Washington School of Public Health, 3980 15th Avenue Northeast, Seattle, WA, USA.ORCID 0000-0002-9809-4695
Funding
Translational Research Support CoreP30ES000002 · NIEHS · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI JAIME ELIZABETH HART · 1985 to 2026
$44.6M
XENOBIOTIC BIOTRANSFORMATION AND DISPOSITIONP30ES007033 · NIEHS · UNIVERSITY OF WASHINGTON · PI Sheela Sathyanarayana · 1995 to 2026
$42.5M
Training Program in Environmental EpidemiologyT32ES007069 · NIEHS · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI LADEN, FRANCINE · 1985 to 2024
$13.9M
Containerizing tasks to ensure robust AI/ML data curation pipelines to estimate environmental disparities in the rural southR01MD016054 · NIMHD · YALE UNIVERSITY · PI Michelle L Bell, Nicole Deziel · 2022 to 2026
$4.3M
National Cohort Studies of Alzheimer's Disease, Related Dementias and Air PollutionR01AG066793 · NIA · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI ZANOBETTI, ANTONELLA · 2020 to 2025
$4.2M
Environmental Health Disparities in an Older PopulationR01MD012769 · NIMHD · YALE UNIVERSITY · PI BELL, MICHELLE L · 2017 to 2021
$3.9M
Relationship Between Multiple Environmental Exposures and CVD Incidence and Survival: Vulnerability and SusceptibilityR01ES028033 · NIEHS · HARVARD SCHOOL OF PUBLIC HEALTH · PI DOMINICI, FRANCESCA, LADEN, FRANCINE · 2018 to 2022
$3.5M
Integrating Air Pollution Prediction Models: Uncertainty Quantification and Propagation in Health StudiesR01ES030616 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI DOMINICI, FRANCESCA, KIOUMOURTZOGLOU, MARIANTHI-ANNA · 2020 to 2024
$3.1M
(R01 Transfer) Characterizing the link between multiple environmental exposures and Parkinsons disease exacerbationR01ES034373 · NIEHS · RUTGERS BIOMEDICAL AND HEALTH SCIENCES · PI Danielle Braun, Antonella Zanobetti · 2022 to 2026
$2.9M
Susceptibility and adverse health outcomes related to climate-sensitive events among older Medicare beneficiaries with Alzheimer and DementiaRF1AG080948 · NIA · YALE UNIVERSITY · PI BELL, MICHELLE L, BENMARHNIA, TARIK · 2023 to 2023
$2.6M
Evidence to improve heat warning effectiveness in reducing morbidity and mortality.R01ES029950 · NIEHS · BROWN UNIVERSITY · PI WELLENIUS, GREGORY A · 2019 to 2022
$2.5M
Causal Inference with Interference for Evaluating Air Quality PoliciesR01ES026217 · NIEHS · UNIVERSITY OF TEXAS AT AUSTIN · PI ZIGLER, CORWIN MATTHEW · 2016 to 2021
Climate change drives three heat-related hazards: extreme heat (EH), wildfire burn zones (WFBZs), and wildfire smoke (WFS). Using daily census tract-level data from 2006 to 2020, we investigated when, where, and whom these hazards coexposed in 11 Western US states. Among 18,106 tracts, at least one hazard occurred an average of 32 days (581,867 tract-days) annually. EH-WFS coexposure increased over the study period and was the most frequent coexposure (annual average of 38,218 tract-days). EH-WFS-affected regions varied year to year. WFBZ-involved coexposures were spatially confined and did not increase over time. On average, the most tract-days of EH-WFBZ-WFS coexposure took place in California, Arizona, and Oregon. Among census tracts most exposed to EH-WFBZ-WFS, populations disproportionately consisted of people of older age, with disabilities, and living in poverty. American Indian and Alaska Native individuals disproportionately faced all coexposures. As climate change accelerates, tracking coexposure to multiple hazards can help target resources to protect health.
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.
Coexposure to extreme heat, wildfire burn zones, and wildfire smoke in the Western US from 2006 to 2020. · full record | OpenQuestion