Evidence map›Paper›PMID 28465304›Full record

ArticleBMJ open2017

Invasive meningococcal disease in the Veneto region of Italy: a capture-recapture analysis for assessing the effectiveness of an integrated surveillance system.

Tatjana Baldovin, Roberta Lazzari, Silvia Cocchio, Patrizia Furlan, Chiara Bertoncello, Mario Saia, Francesca Russo, Vincenzo Baldo

Abstract read
In one paragraph

Article in BMJ open, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. [Journal of preventive medicine and hygiene · 2021
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. [Health Technology Assessment of meningococcal B vaccine (TrumenbaJournal of preventive medicine and hygiene · 2019
    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

8 authors.

Tatjana BaldovinDepartment of Cardiac, Thoracic and Vascular Sciences, Hygiene and Public Health Unit, University of Padua, Padua, Italy.
Roberta LazzariDepartment of Cardiac, Thoracic and Vascular Sciences, Hygiene and Public Health Unit, University of Padua, Padua, Italy.
Silvia CocchioDepartment of Cardiac, Thoracic and Vascular Sciences, Hygiene and Public Health Unit, University of Padua, Padua, Italy.
Patrizia FurlanDepartment of Cardiac, Thoracic and Vascular Sciences, Hygiene and Public Health Unit, University of Padua, Padua, Italy.
Chiara BertoncelloDepartment of Cardiac, Thoracic and Vascular Sciences, Hygiene and Public Health Unit, University of Padua, Padua, Italy.
Mario SaiaArea Sanità e Sociale, Veneto Regional Authority, Venice, Italy.
Francesca RussoService of Hygiene Promotion and Development and Public Health, Veneto Region, Venice, Italy.
Vincenzo BaldoDepartment of Cardiac, Thoracic and Vascular Sciences, Hygiene and Public Health Unit, University of Padua, Padua, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEpidemiology of

methodsAnalysis was performed from 2007 to 2014 on data recorded in different systems: Mandatory Notification System, National Surveillance of Invasive Bacterial Diseases System and Laboratories Surveillance System (LSS), which were pooled into a combined surveillance system (CSS) and hospital discharge records (HDRs). A capture-recapture method was used and completeness of each source estimated. Number of cases with IMD by source of information and year, incidence of IMD by age group, case fatality rate (CFR) and distribution of meningococcal serogroups by year were also analysed.

resultsCombining the four data systems enabled the identification of 179 confirmed cases with IMD, achieving an overall sensitivity of 94.7% (95% CI: 90.8% to 98.8%), while it was 76.7% (95% CI: 73.6% to 80.1%) for CSS and 77.2% (95% CI: 74.1% to 80.6%) for HDRs. Typing of isolates was done in 80% of cases, and 95.2% of the typed cases were provided by LSS. Serogroup B was confirmed in 50.3% of cases. The estimated IMD notification rate (cases with IMD diagnosed and reported to the surveillance systems) was 0.48/100 000 population, and incidence peaked at 6.2/100 000 in children aged <1 year old (60.9% due to MenB), and increased slightly in the age group between 15 and 19 years (1.1/100 000). A CFR of 14% was recorded (8.7% in paediatric age).

conclusionsQuality of surveillance systems relies on case ascertainment based on serological characterisation of the circulating strains by microbiology laboratories. All available sources should be routinely combined to improve the epidemiology of IMD and the information used by public health departments to conduct timely preventive measures.

Indexed as

Public Health SurveillanceAdolescentChildChild, PreschoolData CollectionEpidemiological MonitoringFemaleHealth SurveysHumansIncidenceInfantItalyMaleMeningococcal InfectionsMeningococcal VaccinesNeisseria meningitidisMeningococcal Vaccineslaboratory surveillance datameningococcal diseasesensitivitysurveillance systems

Identifiers

PMID28465304
PMCPMC5623379

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Registered trials

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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.