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Open Access Research article

Tracking type specific prevalence of human Papillomavirus in cervical pre-cancer: a novel sampling strategy

Edward K Waters1*, John Kaldor1, Andrew J Hamilton2, Anthony MA Smith3, David J Philp1, Basil Donovan1 and David G Regan1

Author Affiliations

1 The Kirby Institute, The University of New South Wales, Sydney, NSW, 2052, Australia

2 Melbourne School of Land and Environment, The University of Melbourne, Dookie College, Dookie, Victoria, Australia

3 Australian Research Centre in Sex, Health and Society, La Trobe University, Melbourne, Victoria, Australia

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BMC Medical Research Methodology 2012, 12:77  doi:10.1186/1471-2288-12-77

Published: 14 June 2012



Surveillance designed to detect changes in the type-specific distribution of HPV in cervical intraepithelial neoplasia grade 3 (CIN-3) is necessary to evaluate the effectiveness of the Australian vaccination programme on cancer causing HPV types. This paper develops a protocol that eliminates the need to calculate required sample size; sample size is difficult to calculate in advance because HPV’s true type-specific prevalence is imperfectly known.


A truncated sequential sampling plan that collects a variable sample size was designed to detect changes in the type-specific distribution of HPV in CIN-3. Computer simulation to evaluate the accuracy of the plan at classifying the prevalence of an HPV type as low (< 5%), moderate (5-15%), or high (> 15%) and the average sample size collected was conducted and used to assess its appropriateness as a surveillance tool.


The plan classified the proportion of CIN-3 lesions positive for an HPV type very accurately, with >90% of simulations correctly classifying a simulated data-set with known prevalence. Misclassifying an HPV type of high prevalence as being of low prevalence, arguably the most serious kind of potential error, occurred < 0.05 times per 100 simulations. A much lower sample size (21–22 versus 40–48) was required to classify samples of high rather than low or moderate prevalence.


Truncated sequential sampling enables the proportion of CIN-3 due to an HPV type to be accurately classified using small sample sizes. Truncated sequential sampling should be used for type-specific HPV surveillance in the vaccination era.