Evidence map›Paper›PMID 39534734›Full record

ArticleJournal of Appalachian health2024

Using Public Funeral and Obituary Listings to Identify Spikes in Excess Mortality in One Appalachian County.

Allen Archer, Melissa White, Megan Quinn, Randy Wykoff

Abstract read
In one paragraph

Article in Journal of Appalachian health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Allen ArcherEast Tennessee State University.
Melissa WhiteEast Tennessee State University.
Megan QuinnEast Tennessee State University.
Randy WykoffEast Tennessee State University.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Delays (10-22 months) in availability of official state and county-level mortality data could have significant public health consequences. The COVID-19 pandemic illuminated the need for health officials to access timely death data to identify unexpected increases in mortality in their communities. Purpose: The purpose of this study is to determine if funeral home listings and/or newspaper obituaries could help identify excess mortality on the local level, prior to the availability of official death records. Methods: To calculate excess mortality, four years (2017-2020) of data were collected from three sources: the state health department, online funeral home listings, and newspaper obituaries, all from Washington County, Tennessee. Simple linear regression was used to predict number of expected deaths by month for 2020 using 2017, 2018, and 2019 reported deaths, by data source. The percent difference of actual 2020 deaths from the expected deaths was then calculated by month and compared for each data source. Results: Official COVID-19 state-reported death data accounted for only 50% of excess mortality estimated in 2020. Nearly 100 excess deaths occurred before the first reported death due to COVID-19. Trends in the percent difference between actual and expected funeral home listings and newspaper obituaries followed similar patterns as percent differences in actual v. expected state-reported mortality data. Implications: Had funeral home listings and newspaper obituaries been used to identify excess mortality, health officials would have seen increases in mortality nearly five months prior to the first identified COVID-19 death. These publicly available tools could prove valuable to local health officials as an "early warning" sign of excess mortality.

Indexed as

AppalachiaCOVID-19excess mortalityfuneralobituaryTennessee

Identifiers

PMID39534734
PMCPMC11869939

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.