Evidence map›Paper›PMID 37648196›Full record

ArticleEnvironmental research2023

Spatio-temporal interpolation and delineation of extreme heat events in California between 2017 and 2021.

Pedram Fard, Ming Kei Jake Chung, Hossein Estiri, Chirag J Patel

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Environmental research, 2023. 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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

4 authors.

Pedram FardDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Ming Kei Jake ChungDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China; Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Hong Kong, China.
Hossein EstiriDepartment of Medicine, Harvard Medical School, Boston, MA, USA.
Chirag J PatelDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. Electronic address: Chirag_Patel@hms.harvard.edu.

Funding

Data science tools to identify robust exposure-phenotype associations for precision medicineR01ES032470 · NIEHS · HARVARD MEDICAL SCHOOL · PI MANRAI, ARJUN KUMAR, PATEL, CHIRAG J. · 2021 to 2025
$3.5M
The confluence of extreme heat cold on the health and longevity of an Aging Population with Alzheimers and related DementiaRF1AG074372 · NIA · HARVARD MEDICAL SCHOOL · PI DOMINICI, FRANCESCA, ESTIRI, HOSSEIN · 2022 to 2023
$2.6M
NIA NIH HHS RF1 AG074372NIEHS NIH HHS R01 ES032470
6 · The paper itself

Abstract

Robust spatio-temporal delineation of extreme climate events and accurate identification of areas that are impacted by an event is a prerequisite for identifying population-level and health-related risks. In prior research, attributes such as temperature and humidity have often been linearly assigned to the population of the study unit from the closest weather station. This could result in inaccurate event delineation and biased assessment of extreme heat exposure. We have developed a spatio-temporal model to dynamically delineate boundaries for Extreme Heat Events (EHE) across space and over time, using a relative measure of Apparent Temperature (AT). Our surface interpolation approach offers a higher spatio-temporal resolution compared to the standard nearest-station (NS) assignment method. We show that the proposed approach can provide at least 80.8 percent improvement in identification of areas and populations impacted by EHEs. This improvement in average adjusts the misclassification of about one million Californians per day of an extreme event, who would be either unidentified or misidentified under EHEs between 2017 and 2021.

Indexed as

Extreme HeatCaliforniaClimateClimate ChangeTemperatureWeatherApparent temperatureAugmented mappingClimate changeDistance-based interpolationHeat-health impactsSpatio-temporal modeling

Identifiers

PMID37648196
PMCPMC10591937

What OpenQuestion holds

Textmetadata
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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.