Evidence map›Paper›PMID 34383083›Full record

ArticleBundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz2021

[Regional monitoring of infections by means of standardized case fatality rates using the example of SARS-CoV-2 in Bavaria].

Kirsi Manz, Ulrich Mansmann

Abstract read
In one paragraph

Article in Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz, 2021. 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. Observational
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.

Kirsi ManzInstitut für Medizinische Informationsverarbeitung, Biometrie und Epidemiologie (IBE), Ludwig-Maximilians-Universität München, Marchioninistr. 15, 81377, München, Deutschland. manz@ibe.med.uni-muenchen.de.
Ulrich MansmannInstitut für Medizinische Informationsverarbeitung, Biometrie und Epidemiologie (IBE), Ludwig-Maximilians-Universität München, Marchioninistr. 15, 81377, München, Deutschland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMaps of the temporal evolution of the regional distribution of a health-related measure enable public health-relevant assessments of health outcomes.

objectivesThe paper introduces the concept of standardized case fatality rate (sCFR). It describes the ratio of the regional variation in mortality to the regional variation in the documented infection process. The regional sCFR values are presented in maps and the time-varying regional heterogeneity observed in them is interpreted. MATERIALS AND

methodsThe regional sCFR is the quotient of the regional standardized mortality and case rate. It is estimated using a bivariate model. The sCFR values presented in maps are based on SARS-CoV‑2 reporting data from Bavaria since the beginning of April 2020 until the end of March 2021. Four quarters (Q2/20, Q3/20, Q4/20, and Q1/21) are considered.

resultsIn the quarters considered, the naïve CFR values in Bavaria are 5.0%, 0.5%, 2.5%, and 2.8%. In Q2/20, regional sCFR values are irregularly distributed across the state. This heterogeneity weakens in the second wave of the epidemic. In Q1/21, only isolated regions with elevated sCFR (> 1.25) appear in southern Bavaria. Clusters of regions with sCFR > 1.25 form in northern Bavaria, with Oberallgäu being the region with the lowest sCFR (0.39, 95% credibility interval: 0.25-0.55).

conclusionsIn Bavaria, heterogeneous regional SARS-CoV-2-specific sCFR values are shown to change over time. They estimate the relative risk of dying from or with COVID-19 as a documented case. Strong small-scale variability in sCFR suggests a preference for regional over higher-level measures to manage the incidence of infection.

Indexed as

COVID-19GermanyHumansIncidenceRiskSARS-CoV-2Bayesian hierarchical modelsGeographical epidemiologyIndirect standardizationStandardized incidence rateStandardized mortality rate

Identifiers

PMID34383083
PMCPMC8358915

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.