Demographic characterization and spatial cluster analysis of human Salmonella 1, 4, [5], 12:i:- infections in Portugal: A 10 year study. Issue 2 (March 2018)

• Record Type: Journal Article
• Authors: Seixas, R.; Nunes, T.; Machado, J.; Tavares, L.; Owen, S.P.; Bernardo, F.; Oliveira, M.
• Is Part Of: Journal of infection and public health. Volume 11:Issue 2(2018)
• Page Start: 178
• Page End: 182
• Publication Date: 2018-03
• Subjects: Cluster analysis -- Geographical information system (GIS) -- Portugal -- Public health -- Salmonella 1, 4, [5], 12:i:-; Communicable diseases -- Periodicals; Public health -- Periodicals; Epidemiology -- Periodicals; Nosocomial infections -- Prevention -- Periodicals; Medical microbiology -- Periodicals; 614.4
• DOI: 10.1016/j.jiph.2017.06.002
• Languages: English
• ISSNs: 1876-0341

Abstract

Abstract: Salmonella 1, 4, [5], 12:i:- is presently considered one of the major serovars responsible for human salmonellosis worldwide. Due to its recent emergence, studies assessing the demographic characterization and spatial epidemiology of salmonellosis 1, 4, [5], 12:i:- at local- or country-level are lacking. In this study, a analysis was conducted over a 10 year period, from 2000 to the first quarter of 2011 at the Portuguese National Laboratory in Portugal mainland, with a total of 215 Salmonella 1, 4, [5], 12:i:- serotyped isolates obtained from human infections by a passive surveillance system. Data regarding source, year and month of sampling, gender, age, district and municipality of the patients were registered. Descriptive statistical analysis and a spatial scan statistic combined with a geographic information system were employed to characterize the epidemiology and identify spatial clusters. Results showed that most districts have reports of Salmonella 1, 4, [5], 12:i:-, with a higher number of cases at the Portuguese coastland, including districts like Porto (n = 60, 27.9%), Lisboa (n = 29, 13.5%) and Aveiro (n = 28, 13.0%). An increased incidence was observed in the period from 2004 to 2011 and most infections occurred during May and October. Spatial analysis revealed 4 clusters of higher than expected infection rates. Three were located in the north of Portugal, including two at the coastland (Cluster 1 [RR = 3.58, p ≤ 0.001] and 4 [RR = 10.42 p ≤ 0.230]), and one at the countryside (Cluster 3 [RR = 17.76, p ≤ 0.001]). A larger cluster was detected involving the center and south of Portugal (Cluster 2 [RR = 4.85, p ≤ 0.001]). The present study was elaborated with data provided by a passive surveillance system, which may originate an underestimation of disease burden. However, this is the first report describing the incidence and the distribution of areas with higher risk of infection in Portugal, revealing that Salmonella 1, 4, [5], 12:i:- displayed a significant geographic clustering and these areas should be further evaluated to identify risk factors in order to establish prevention programs.