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Sampling strategies to measure the prevalence of common recurrent infections in longitudinal studies.

Schmidt, W.P.; Genser, B.; Barreto, M.L.; Clasen, T.; Luby, S.P.; Cairncross, S.; Chalabi, Z.;
Emerg Themes Epidemiol, 2010; 7(1):5
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pub_id
20678239
pubmedid
20678239
ISI
reference_type
author
Schmidt, W.P.; Genser, B.; Barreto, M.L.; Clasen, T.; Luby, S.P.; Cairncross, S.; Chalabi, Z.;
title
Sampling strategies to measure the prevalence of common recurrent infections in longitudinal studies.
secondary_title
Emerg Themes Epidemiol
ISBNISSN
1742-7622
volume
7
number
1
pages
5
year
2010
abstract
ABSTRACT: BACKGROUND: Measuring recurrent infections such as diarrhoea or respiratory infections in epidemiological studies is a methodological challenge. Problems in measuring the incidence of recurrent infections include the episode definition, recall error, and the logistics of close follow up. Longitudinal prevalence (LP), the proportion-of-time-ill estimated by repeated prevalence measurements, is an alternative measure to incidence of recurrent infections. In contrast to incidence which usually requires continuous sampling, LP can be measured at intervals. This study explored how many more participants are needed for infrequent sampling to achieve the same study power as frequent sampling. METHODS: We developed a set of four empirical simulation models representing low and high risk settings with short or long episode durations. The model was used to evaluate different sampling strategies with different assumptions on recall period and recall error. RESULTS: The model identified three major factors that influence sampling strategies: (1) the clustering of episodes in individuals; (2) the duration of episodes; (3) the positive correlation between an individual's disease incidence and episode duration. Intermittent sampling (e.g. 12 times per year) often requires only a slightly larger sample size compared to continuous sampling, especially in cluster-randomized trials. The collection of period prevalence data can lead to highly biased effect estimates if the exposure variable is associated with episode duration. To maximize study power, recall periods of 3 to 7 days may be preferable over shorter periods, even if this leads to inaccuracy in the prevalence estimates. CONCLUSION: Choosing the optimal approach to measure recurrent infections in epidemiological studies depends on the setting, the study objectives, study design and budget constraints. Sampling at intervals can contribute to making epidemiological studies and trials more efficient, valid and cost-effective.
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secondary_author
place_published
publisher
number_of_volumes
tertiary_author
tertiary_title
edition
date
type_of_work
subsidiary_author
alternate_title
call_number
accession_number
custom_1
WOS_NOT_FOUND_BY_DOI
custom_2
Unknown
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custom_4
10.1186/1742-7622-7-5
custom_5
DOAJ
custom_6
10
label
2016-10-18
notes
Journal Article
url
author_address
Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, UK. Wolf-Peter.Schmidt@lshtm.ac.uk.
library
1742-7622-7-5 10.1186/1742-7622-7-5 20678239 PMC2922204
date_accepted
date_online
created
2010-08-19 12:04:34
modified
2016-07-08 00:00:00
library

<ArticleId IdType="pii">1742-7622-7-5</ArticleId>
<ArticleId IdType="doi">10.1186/1742-7622-7-5</ArticleId>
<ArticleId IdType="pubmed">20678239</ArticleId>
<ArticleId IdType="pmc">PMC2922204</ArticleId>