Evidence map›Paper›PMID 37758827›Full record

ArticleScientific reports2023

Public health factors help explain cross country heterogeneity in excess death during the COVID19 pandemic.

Min Woo Sun, David Troxell, Robert Tibshirani

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.1field-weighted citation impact, top 25% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Observational
  2. 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

3 authors at 1 institution in 1 country.

Min Woo Sun *Department of Biomedical Data Science, Stanford University, 450 Serra Mall, Stanford, CA, 94305, USA. minwoos@stanford.edu.
David Troxell *Department of Statistics, Stanford University, 450 Serra Mall, Stanford, CA, 94305, USA.
Robert TibshiraniDepartment of Biomedical Data Science, Stanford University, 450 Serra Mall, Stanford, CA, 94305, USA.
Stanford University · US

Funding

New Statistical Methods for Medical Signals and ImagesR01EB001988 · NIBIB · STANFORD UNIVERSITY · PI JOHNSTONE, IAIN M · 2003 to 2018
$6.1M
NIBIB NIH HHS R01 EB001988
6 · The paper itself

Abstract

The COVID-19 pandemic has taken a devastating toll around the world. Since January 2020, the World Health Organization estimates 14.9 million excess deaths have occurred globally. Despite this grim number quantifying the deadly impact, the underlying factors contributing to COVID-19 deaths at the population level remain unclear. Prior studies indicate that demographic factors like proportion of population older than 65 and population health explain the cross-country difference in COVID-19 deaths. However, there has not been a comprehensive analysis including variables describing government policies and COVID-19 vaccination rate. Furthermore, prior studies focus on COVID-19 death rather than excess death to assess the impact of the pandemic. Through a robust statistical modeling framework, we analyze 80 countries and show that actionable public health efforts beyond just the factors intrinsic to each country are important for explaining the cross-country heterogeneity in excess death.

Indexed as

COVID-19PandemicsCOVID-19 VaccinesGovernmentHumansPublic HealthCOVID-19 Vaccines

Identifiers

PMID37758827
PMCPMC10533501
OpenAlexW4387105844

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.