Evidence map›Paper›PMID 30794677›Full record

ArticlePloS one2019

Positive predictive value of the German notification system for infectious diseases: Surveillance data from eight local health departments, Berlin, 2012.

Benjamin Blümel, Michaela Diercke, Daniel Sagebiel, Andreas Gilsdorf

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. 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
0.4field-weighted citation impact, top 30% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  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 at 1 institution in 2 countries.

Benjamin BlümelPostgraduate Training for Applied Epidemiology (PAE, German FETP), Department of Infectious Disease Epidemiology, Robert Koch Institute, Berlin, Germany.ORCID 0000-0002-3227-4941
Michaela DierckeDepartment of Infectious Disease Epidemiology, Robert Koch Institute, Berlin, Germany.ORCID 0000-0002-4678-1813
Daniel SagebielBerlin State Office for Health and Social Affairs, Berlin, Germany.
Andreas GilsdorfDepartment of Infectious Disease Epidemiology, Robert Koch Institute, Berlin, Germany.
Robert Koch Institute · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The German Infection Protection Act requires notifying certain cases of infectious diseases to local health departments (LHD) in Germany. LHDs transmit notifications meeting case definitions to the national health authority, where the proportion of discarded notifications is not known. The proportion of discarded cases at the level of LHDs can be expressed as the positive predictive value (PPV) of the notification system. The PPV can be used to assess the efficiency of the system. We quantified the proportion of discarded notifications to calculate the PPV of the German notification system at the level of LHDs using electronic notification data from Berlin LHDs from 2012. We also analysed reasons for discarding notifications by reviewing notification forms. Data was available from eight LHDs (67%) receiving 10,113 notifications in 2012. Overall PPV was 89% (minimum-maximum = 77-97% across LHDs) and ranging from 30% (Hepatitis B) to 99% (Rotavirus). Of 166 individual investigation forms 84% were on hepatitis B or C cases, most of them discarded because of previously diagnosed chronic disease. LHDs investigate many notifications that do not lead to public health action and useful surveillance data leading to inefficient use of resources. Adaptation of case definitions or the legal framework concerning notifications may increase the efficiency of the notification system and lead to better use of data from notified cases.

Indexed as

Communicable DiseasesBerlinChronic DiseaseDisease NotificationGermanyHepatitis BHumansLocal GovernmentPublic Health Administration

Identifiers

PMID30794677
PMCPMC6386491
OpenAlexW2916321816

What OpenQuestion holds

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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.