Evidence map›Paper›PMID 34962265›Full record

ArticleBiostatistics (Oxford, England)2023

Integrated causal-predictive machine learning models for tropical cyclone epidemiology.

Rachel C Nethery, Nina Katz-Christy, Marianthi-Anna Kioumourtzoglou, Robbie M Parks, Andrea Schumacher, G Brooke Anderson

Open access · hybridAbstract read
In one paragraph

Article in Biostatistics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 38% of its field
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.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.

  1. Pooled it
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  15. Exposure Assessment for Tropical Cyclone Epidemiology.Current environmental health reports · 2022
    Review
4 · The record

Corrections and comments

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 at 3 institutions in 1 country.

Rachel C NetheryDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Ave, Boston, MA, USA.ORCID 0000-0001-9895-1477
Nina Katz-ChristyDepartment of Statistics, Harvard University, 1 Oxford St, Cambridge, MA, USA.
Marianthi-Anna KioumourtzoglouDepartment of Environmental Health Sciences, Columbia Mailman School of Public Health, 722 W. 168th Street, New York City, NY, USA.
Robbie M ParksDepartment of Environmental Health Sciences, Columbia Mailman School of Public Health, 722 W. 168th Street, New York City, NY, USA.
Andrea SchumacherCooperative Institute for Research in the Atmosphere, Colorado State University, 3925A West Laporte Ave, Fort Collins, CO, USA.
G Brooke AndersonDepartment of Environmental & Radiological Health Sciences, Colorado State University, 122A Environmental Health Building, Fort Collins, CO, USA.
Harvard University · USColorado State University · USCooperative Institute for Research in Environmental Sciences · US

Funding

True Metal fac coreP30ES009089 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI MATTHEW S PERZANOWSKI · 1998 to 2026
$44.7M
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
Disease Outcomes iN Older adults under extreme Heat, AiR pollution and Medication use (DO-NO-HARM)R01AG060232 · NIA · RUTGERS, THE STATE UNIV OF N.J. · PI SETOGUCHI IWATA, SOKO · 2019 to 2023
$3.0M
Improving statistical methods for small area estimates of public health indicators and demographic characteristicsR01HD092580 · NICHD · EMORY UNIVERSITY · PI Lance A Waller · 2018 to 2026
$2.3M
Principal Component Pursuit to Assess Exposure to Environmental Mixtures in Epidemiologic StudiesR01ES028805 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI KIOUMOURTZOGLOU, MARIANTHI-ANNA · 2018 to 2021
$2.2M
Novel Assessments of the Health Impacts of Tropical CyclonesR00ES033742 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI PARKS, ROBBIE M · 2023 to 2025
$911k
Improving Methods for Comparative Effectiveness Research in Cardiovascular CareK02HS017731 · AHRQ · DUKE UNIVERSITY · PI SETOGUCHI IWATA, SOKO · 2008 to 2012
$752k
Investigating Health Effects of Climate-Related Disasters in the United StatesR00ES022631 · NIEHS · COLORADO STATE UNIVERSITY · PI ANDERSON, BROOKE · 2015 to 2017
$731k
Utility of a New Database to Study Drug Safety during PregnancyR21HD055479 · NICHD · BRIGHAM AND WOMEN'S HOSPITAL · PI SETOGUCHI IWATA, SOKO · 2007 to 2008
$474k
Heat Waves, Medication Use, and Adverse Health Outcomes Among Older AdultsR21AG044294 · NIA · DUKE UNIVERSITY · PI LI, WENHONG · 2013 to 2014
$432k
Causal machine learning methods for studying the effects of environmental exposures on childhood cancer using natural experimentsK01ES032458 · NIEHS · HARVARD SCHOOL OF PUBLIC HEALTH · PI NETHERY, RACHEL C · 2021 to 2023
$417k
Novel Assessments of the Health Impacts of Tropical CyclonesK99ES033742 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI PARKS, ROBBIE M · 2022 to 2023
$208k
AHRQ HHS K02 HS017731NIA NIH HHS R01 AG060232NIA NIH HHS R21 AG044294NICHD NIH HHS R01 HD092580NICHD NIH HHS R21 HD055479NIEHS NIH HHS K01 ES032458NIEHS NIH HHS K99 ES033742NIEHS NIH HHS P30 ES009089NIEHS NIH HHS R00 ES022631NIEHS NIH HHS R00 ES033742NIEHS NIH HHS R01 ES028805NIEHS NIH HHS R01 ES030616
6 · The paper itself

Abstract

Strategic preparedness reduces the adverse health impacts of hurricanes and tropical storms, referred to collectively as tropical cyclones (TCs), but its protective impact could be enhanced by a more comprehensive and rigorous characterization of TC epidemiology. To generate the insights and tools necessary for high-precision TC preparedness, we introduce a machine learning approach that standardizes estimation of historic TC health impacts, discovers common patterns and sources of heterogeneity in those health impacts, and enables identification of communities at highest health risk for future TCs. The model integrates (i) a causal inference component to quantify the immediate health impacts of recent historic TCs at high spatial resolution and (ii) a predictive component that captures how TC meteorological features and socioeconomic/demographic characteristics of impacted communities are associated with health impacts. We apply it to a rich data platform containing detailed historic TC exposure information and records of all-cause mortality and cardiovascular- and respiratory-related hospitalization among Medicare recipients. We report a high degree of heterogeneity in the acute health impacts of historic TCs, both within and across TCs, and, on average, substantial TC-attributable increases in respiratory hospitalizations. TC-sustained windspeeds are found to be the primary driver of mortality and respiratory risks.

Indexed as

Cyclonic StormsAgedCausalityHumansMedicareModels, TheoreticalUnited StatesCausal inferenceEnvironmental epidemiologyExtreme weather eventsHurricanesLatent factor modelMatrix completion

Identifiers

PMID34962265
PMCPMC10102905
OpenAlexW3094260149

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.