Related Experiment Video
Updated: May 22, 2026

Comprehensive & Cost Effective Laboratory Monitoring of HIV/AIDS: an African Role Model
Published on: October 31, 2010
Measuring concurrency: an empirical study of different methods in a large population-based survey and evaluation of
Judith R Glynn1, Albert Dube, Ndoliwe Kayuni
1Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK. judith.glynn@lshtm.ac.uk
Background:
Recent UNAIDS guidelines recommend measuring concurrency 6 months before the interview date, based on overlapping partnership dates. This has theoretical advantages, but little is known about how well it can be measured in practice.
Methods:
The assumptions underlying the UNAIDS measure were tested using data from a sexual behaviour survey conducted in rural northern Malawi. All resident adults aged 15-59 were eligible. Questions included self-reported concurrency and dates for all marital and nonmarital partnerships in the past 12 months.
Results:
A total of 6796 women and 5253 men were interviewed, 83 and 72% of those eligible, respectively. Since few women reported multiple partners, detailed analysis was restricted to men. Overall 19.2% [95% confidence interval (CI) 18.1-20.2] of men self-reported concurrent relationships in the past year (almost all of those with more than one partner). Using overlapping dates the estimate was 16.7% (15.7-17.7). Excluding partnerships which tied on dates (making overlap uncertain) or restricting the analysis to the three most recent partners gave similar results. The UNAIDS 6-month measure was 12.0% (11.1-12.9), and current concurrency was 11.5% (10.6-12.4). The difference between dates-based and self-reported 12-month measures was much larger for unmarried men: 11.1% (9.7-12.4) self-reported; 7.1% (6.9-8.2) on dates. Polygyny (15% of married men) and the longer duration of relationships stabilized the estimates for married men. Nonmarital partnerships were under-reported, particularly those starting longer ago.
Conclusions:
The difficulties of recall of dates for relationships, and under-reporting of partners lead to underestimation of concurrency using date-based measures. Self-reported concurrency is much easier to measure and appears more complete.
Related Concept Videos
Statistical Methods for Analyzing Epidemiological Data
Data Collection by Observations
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
Comparing the Survival Analysis of Two or More Groups
Study Designs in Epidemiology
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and case-control studies.
Bias in Epidemiological Studies
Longitudinal Research

