Heterogeneity in regional notification patterns and its impact on aggregate national case notification data: the example of measles in Italy
Author(s)
Williams, JR
Manfredi, P
Butler, AR
degli Atti, MC
Salmaso, S
Type
Journal Article
Abstract
Background: A monthly time series of measles case notifications exists for Italy from 1949
onwards, although its usefulness is seriously undermined by extensive under-reporting which varies
strikingly between regions, giving rise to the possibility of significant distortions in epidemic
patterns seen in aggregated national data.
Results: A corrected national time series is calculated using an algorithm based upon the
approximate equality between births and measles cases; under-reporting estimates are presented
for each Italian region, and poor levels of reporting in Southern Italy are confirmed.
Conclusion: Although an order of magnitude larger, despite great heterogeneity between regions
in under-reporting and in epidemic patterns, the shape of the corrected national time series
remains close to that of the aggregated uncorrected data. This suggests such aggregate data may
be quite robust to great heterogeneity in reporting and epidemic patterns at the regional level. The
corrected data set maintains an epidemic pattern distinct from that of England and Wales.
onwards, although its usefulness is seriously undermined by extensive under-reporting which varies
strikingly between regions, giving rise to the possibility of significant distortions in epidemic
patterns seen in aggregated national data.
Results: A corrected national time series is calculated using an algorithm based upon the
approximate equality between births and measles cases; under-reporting estimates are presented
for each Italian region, and poor levels of reporting in Southern Italy are confirmed.
Conclusion: Although an order of magnitude larger, despite great heterogeneity between regions
in under-reporting and in epidemic patterns, the shape of the corrected national time series
remains close to that of the aggregated uncorrected data. This suggests such aggregate data may
be quite robust to great heterogeneity in reporting and epidemic patterns at the regional level. The
corrected data set maintains an epidemic pattern distinct from that of England and Wales.
Date Issued
2003-07-18
Date Acceptance
2003-07-18
Citation
BMC Public Health, 2003, 3 (1)
ISSN
1471-2458
Publisher
BioMed Central
Journal / Book Title
BMC Public Health
Volume
3
Issue
1
Copyright Statement
© 2003 Williams et al; licensee BioMed Central Ltd. This article is published under license to BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL.
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000184744500001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Life Sciences & Biomedicine
Public, Environmental & Occupational Health
PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH, SCI
ENGLAND
WALES
EPIDEMIOLOGY
SURVEILLANCE
VACCINATION
Algorithms
Bias (Epidemiology)
Birth Rate
Demography
Disease Notification
Geography
Humans
Immunization Programs
Italy
Life Tables
Measles
Models, Statistical
Time Factors
1117 Public Health And Health Services
Public Health
Publication Status
Published
Article Number
ARTN 23