%0 Journal Article
%T Sampling strategies to measure the prevalence of common recurrent infections in longitudinal studies
%A Wolf-Peter Schmidt
%A Bernd Genser
%A Mauricio L Barreto
%A Thomas Clasen
%A Stephen P Luby
%A Sandy Cairncross
%A Zaid Chalabi
%J Emerging Themes in Epidemiology
%D 2010
%I BioMed Central
%R 10.1186/1742-7622-7-5
%X 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.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.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.The prevalence of common recurrent infections such as diarrhoea and respiratory infections in field studies is commonly estimated using repeated measurements in the same individuals. Many studies have used intensive surveillance, for example by conducting twice-weekly home visits to measure prevalence on every single day over the study period [1,2]. In other studies prevalence was measured at intervals, for example during only four home visits at 4-week intervals [3]. The differences in logistical effort are considerable. A study of 100 households over one year with twice-weekly surveillance visits would require 52 กม 2 กม 100 = 10,400 visits. Conducting only four visits per household in total requires only 4 กม 100 = 400 v
%U http://www.ete-online.com/content/7/1/5