Evidence map›Paper›PMID 32527379›Full record

ReviewDeutsches Arzteblatt international2020

Epidemiological Measures in the Context of the COVID-19 Pandemic.

Emilio Gianicolo, Nicola Riccetti, Maria Blettner, André Karch

Abstract readReview
PubMed Publisher
In one paragraph

Review in Deutsches Arzteblatt international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. [SARS-CoV-2, influenza and norovirus infection : A direct epidemiologic comparison].Medizinische Klinik, Intensivmedizin und Notfallmedizin · 2022
    Article
  8. Article
  9. [Epidemiological approaches to address key research questions on COVID-19-an overview].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2021
    Review
  10. Health Sufficiency Indicators for Pandemic Monitoring.International journal of environmental research and public health · 2021
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Standardized Mortality Ratios.Deutsches Arzteblatt international · 2020
    Article
  18. In Reply.Deutsches Arzteblatt international · 2020
    Article
  19. Article
  20. Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany)) · 2020
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Emilio GianicoloInstitute for Medical Biostatistics, Epidemiology, and Informatics (IMBEI), Mainz University Medical Center; Institute for Clinical Physiology, National Research Center, Lecce, Italy; Institute for Epidemiology and Social Medicine, University of Münster.
Nicola Riccetti
Maria Blettner
André Karch

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe various epidemiological indicators used to communicate the impact of COVID-19 have different strengths and limitations.

methodsWe conducted a selective literature review to identify the indicators used and to derive appropriate definitions. We calculated crude and age-adjusted indicators for selected countries.

resultsThe proportion of deaths (case fatality proportion [CFP]; number of deaths/ total number of cases) is commonly used to estimate the severity of a disease. If the CFP is used for purposes of comparison, the existence of heterogeneity in the detection and registration of cases and deaths has to be taken into account. In the early phase of an epidemic, when case numbers rise rapidly, the CFP suffers from bias. For these reasons, variants have been proposed: the "confirmed CFP" (number of deaths/total number of confirmed cases), and the "delay-adjusted CFP," which considers the delay between infection with the disease and death from the disease. The indicator mortality (number of deaths/total population) has at first sight the advantage of being based on a defined denominator, the total population. During the outbreak of a disease, however, the cumulative deaths rise while the total population remains stable. The phase of the epidemic therefore has to be considered when using this indicator. In this context, R0 and R(t) are important indicators. R0 estimates the maximum rate of spread of a disease in a population, while R(t) describes the dynamics of the epidemic at a given time. Age-adjusted analysis of the CFP shows that the differences between countries decrease but do not dis - appear completely. If the test strategies depend on age or symptom severity, however, the bias cannot be entirely eliminated.

conclusionVarious indicators of the impact of the COVID-19 epidemic at population level are used in daily communication. Considering the relevance of the pandemic and the importance of relevant communications, however, the strengths and the limitations of each parameter must be considered carefully.

Indexed as

PandemicsCoronavirus InfectionsCOVID-19HumansPneumonia, Viral

Identifiers

What OpenQuestion holds

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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.