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Vaccine preventable invasive bacterial diseases in Italy: A comparison between the national surveillance system and recorded hospitalizations, 2007-2016.
Vaccine. 2018 Nov 23;:
Authors: Pezzotti P, Bellino S, Riccardo F, Lucaroni F, Cerquetti M, Pantosti A, Rezza G, Stefanelli P
Abstract
BACKGROUND: Vaccine-preventable invasive bacterial diseases (IBDs) caused by Neisseria meningitidis (Nm), Streptococcus pneumoniae (Sp), and Haemophilus influenzae (Hi) have been notified in Italy since 2007 without assessing reporting completeness.
METHODS: Our study compared the number of cases of IBDs identified from the Italian Hospital Discharge Records (HDRs), using specific diagnostic ICD-9-CM codes, with those notified to the National Surveillance System (NSS) from 2007 to 2016. A multinomial logistic regression model was used to impute the aetiology of all discharges with a diagnosis of unspecified bacterial meningitis.
RESULTS: Over a 10-year period, 14,243 hospital discharges with diagnosis of IBD were estimated in Italy (12,671 with specified aetiology and 1,572 with imputed aetiology). Among those, 2,513 (17.6%) were caused by Nm, 10,441 (73.3%) by Sp, and 1289 (9.1%) by Hi. Most invasive meningococcal diseases were coded as meningitis (72.3%), while Hi and Sp were more frequently coded as septicaemia (51.6% and 60.4%, respectively). The highest mean annual incidence rate was found for IBD caused by Sp (1.74 per 100,000), followed by Nm (0.42 per 100,000) and by Hi (0.21 per 100,000). Comparing NSS with HDR data, we found an initially high underreporting of all IBDs, and particularly for Hi. Data from the two systems overlapped in more recent years, due to an improved reporting completeness. The increasing IBD incidence observed in NSS data was not confirmed by HDR data trends, although with pathogen-related differences with Hi cases rising in both data sources, suggesting that is mainly due to an improved disease notification rather than to a true incidence increase.
CONCLUSIONS: Comparing surveillance data with other data sources is useful to better interpret observed trends of notifiable diseases.
PMID: 30478004 [PubMed - as supplied by publisher]
from PubMed via alexandrossfakianakis on Inoreader https://ift.tt/2r7UbEJ
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