Evidence map›Paper›PMID 37582109›Full record

ArticlePloS one2023

Two complementary approaches to estimate an excess of mortality: The case of Switzerland 2022.

Isabella Locatelli, Valentin Rousson

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In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

2 authors.

Isabella LocatelliCenter for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland.ORCID 0000-0003-0870-1461
Valentin RoussonCenter for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveDuring the COVID-19 pandemic, excess mortality has generally been estimated comparing overall mortality in a given year with either past mortality levels or past mortality trends, with different results. Our objective was to illustrate and compare the two approaches using mortality data for Switzerland in 2022, the third year of the COVID-19 pandemic.

methodsUsing data from the Swiss Federal Statistical Office, standardized mortality rates and life expectancies in 2022 were compared with those of the last pre-pandemic year 2019 (first approach), as well as with those that would be expected if the pre-pandemic downward trend in mortality had continued during the pandemic (second approach). The pre-pandemic trend was estimated via a Poisson log-linear model on age-specific mortality over the period 2010-19.

resultsUsing the first approach, we estimated in Switzerland in 2022 an excess mortality of 2.6% (95%CI: 1.0%-4.1%) for men and 2.5% (95%CI: 1.0%-4.0%) for women, while the excess mortality rose to 8.4% (95%CI: 6.9%-9.9%) for men and 6.0% (95%CI: 4.6%-7.5%) for women using the second approach. Age classes over 80 were the main responsible for the excess mortality in 2022 for both sexes using the first approach, although a significant excess mortality was also found in most age classes above 30 using the second approach. Life expectancy in 2022 has been reduced by 2.7 months for men and 2.4 months for women according to the first approach, whereas it was reduced by respectively 8.8 and 6.0 months according to the second approach.

conclusionsThe excess mortality and loss of life expectancy in Switzerland in 2022 are around three times greater if the pre-pandemic trend is taken into account than if we simply compare 2022 with 2019. These two different approaches, one being more speculative and the other more factual, can also be applied simultaneously and provide complementary results. In Switzerland, such a dual-approach strategy has shown that the pre-pandemic downward trend in mortality is currently halted, while pre-pandemic mortality levels have largely been recovered by 2022.

Indexed as

COVID-19PandemicsFemaleHumansLife ExpectancyLinear ModelsMaleMortalitySwitzerland

Identifiers

PMID37582109
PMCPMC10426989

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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.