Evidence map›Paper›PMID 37466563›Full record

ArticleEpidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil2023

Evaluation of completeness and timeliness of data in the National Information System for Notifiable Diseases for spotted fever in the state of São Paulo, Brazil, 2007-2017.

Daniele Rosa Xavier, Michellin Pereira de Albuquerque, Sílvia Von Tiesenhausen de Sousa-Carmo, Adriano Pinter

Abstract read
In one paragraph

Article in Epidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Health Information Systems: how much progress are we making?Epidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil · 2023
    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.

Daniele Rosa XavierUniversidade de São Paulo, Programa de Pós-Graduação em Saúde Pública, São Paulo, SP, Brazil.ORCID 0000-0003-0398-7667
Michellin Pereira de AlbuquerqueUniversidade de São Paulo, Programa de Pós-Graduação em Saúde Pública, São Paulo, SP, Brazil.ORCID 0000-0003-1676-0488
Sílvia Von Tiesenhausen de Sousa-CarmoSecretaria de Estado da Saúde, Centro de Informações de Vigilância Epidemiológica, São Paulo, SP, Brazil.ORCID 0000-0002-0334-6926
Adriano PinterSuperintendência de Controle de Endemias, São Paulo, SP, Brazil.ORCID 0000-0003-4596-3268

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveto evaluate the completeness and timeliness of notifications of cases of spotted fever (SF) held on the Notifiable Health Conditions Information System (SINAN) in São Paulo State, Brazil, from 2007 to 2017.

methodsthis was a descriptive and ecological study of confirmed human cases of SF regarding completeness and timeliness of ten fields of the notification form (good if ≥ 90% for most variables); time series analysis was performed using the Prais-Winsten technique.

resultswe analyzed 736 records; among essential fields, only "Discharge date" showed poor completeness (68.5%). Timeliness was good for the "Investigation" and "Closure" fields; other time lapses were not adequate.

conclusionin São Paulo state, data completeness was good for most variables, whereas timeliness was not adequate (except for "Closure" and "Investigation"), pointing to the need for health education and communication actions about SF.

Indexed as

Population SurveillanceSpotted Fever Group RickettsiosisBrazilDisease NotificationHumansInformation Systems

Identifiers

PMID37466563
PMCPMC10355991

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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.