spatial analysis of avoidable hospitalizations due to tuberculosis in ribeirao preto, sp, brazil (2006-2012)

Klicks: 316
ID: 231682
2016
Kostenloses PDF
Artikelqualität & Leistungskennzahlen
Gesamtqualität
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
KI-Qualitätsbewertung
Nicht analysiert
Readership in this journal
Emerging

Ranked #71 of 356 articles by views in proceedings - 2016 3rd international conference on information technology, computer, and electrical engineering, icitacee 2016

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 356 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
ABSTRACT OBJECTIVE To describe the spatial distribution of avoidable hospitalizations due to tuberculosis in the municipality of Ribeirao Preto, SP, Brazil, and to identify spatial and space-time clusters for the risk of occurrence of these events. METHODS This is a descriptive, ecological study that considered the hospitalizations records of the Hospital Information System of residents of Ribeirao Preto, SP, Southeastern Brazil, from 2006 to 2012. Only the cases with recorded addresses were considered for the spatial analyses, and they were also geocoded. We resorted to Kernel density estimation to identify the densest areas, local empirical Bayes rate as the method for smoothing the incidence rates of hospital admissions, and scan statistic for identifying clusters of risk. Softwares ArcGis 10.2, TerraView 4.2.2, and SaTScanTM were used in the analysis. RESULTS We identified 169 hospitalizations due to tuberculosis. Most were of men (n = 134; 79.2%), averagely aged 48 years (SD = 16.2). The predominant clinical form was the pulmonary one, which was confirmed through a microscopic examination of expectorated sputum (n = 66; 39.0%). We geocoded 159 cases (94.0%). We observed a non-random spatial distribution of avoidable hospitalizations due to tuberculosis concentrated in the northern and western regions of the municipality. Through the scan statistic, three spatial clusters for risk of hospitalizations due to tuberculosis were identified, one of them in the northern region of the municipality (relative risk [RR] = 3.4; 95%CI 2.7–4,4); the second in the central region, where there is a prison unit (RR = 28.6; 95%CI 22.4–36.6); and the last one in the southern region, and area of protection for hospitalizations (RR = 0.2; 95%CI 0.2–0.3). We did not identify any space-time clusters. CONCLUSIONS The investigation showed priority areas for the control and surveillance of tuberculosis, as well as the profile of the affected population, which shows important aspects to be considered in terms of management and organization of health care services targeting effectiveness in primary health care.
Referenzschlüssel
yamamura2016revistaspatial Verwenden Sie diesen Schlüssel zum automatischen Zitieren im Manuskript bei Verwendung von SciMatic Manuscript Manager oder Thesis Manager
Autoren ;Mellina Yamamura;Isabela Moreira de Freitas;Marcelino Santo Neto;Francisco Chiaravalloti Neto;Marcela Antunes Paschoal Popolin;Luiz Henrique Arroyo;Ludmila Barbosa Bandeira Rodrigues;Juliane Almeida Crispim;Ricardo Alexandre Arcêncio
Zeitschrift proceedings - 2016 3rd international conference on information technology, computer, and electrical engineering, icitacee 2016
Jahr 2016
DOI
10.1590/S1518-8787.2016050006049
URL
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0034-89102016000100215&lng=en&tlng=en
Schlüsselwörter
tuberculose estudos ecológicospublic aspects of medicine hospitalização

Zitationen

Keine Zitationen gefunden. Um eine Zitation hinzuzufügen, kontaktieren Sie den Administrator unter info@scimatic.org

Kommentare

Noch keine Kommentare. Seien Sie der Erste, der diesen Artikel kommentiert.