Comparison of three methods for ascertainment of contact information relevant to respiratory pathogen transmission in encounter networks.
BACKGROUND
Mathematical models of infection that consider targeted interventions are exquisitely dependent on the assumed mixing patterns of the population. We report on a pilot study designed to assess three different methods (one retrospective, two prospective) for obtaining contact data relevant to the determination of these mixing patterns.


METHODS
65 adults were asked to record their social encounters in each location visited during 6 study days using a novel method whereby a change in physical location of the study participant triggered data entry. Using a cross-over design, all participants recorded encounters on 3 days in a paper diary and 3 days using an electronic recording device (PDA). Participants were randomised to first prospective recording method.


RESULTS
Both methods captured more contacts than a pre-study questionnaire, but ascertainment using the paper diary was superior to the PDA (mean difference: 4.52 (95% CI 0.28, 8.77). Paper diaries were found more acceptable to the participants compared with the PDA. Statistical analysis confirms that our results are broadly consistent with those reported from large-scale European based surveys. An association between household size (trend 0.14, 95% CI (0.06, 0.22), P < 0.001) and composition (presence of child 0.37, 95% CI (0.17, 0.56), P < 0.001) and the total number of reported contacts was observed, highlighting the importance of sampling study populations based on household characteristics as well as age. New contacts were still being recorded on the third study day, but compliance had declined, indicating that the optimal number of sample days represents a trade-off between completeness and quality of data for an individual.


CONCLUSIONS
The study's location-based reporting design allows greater scope compared to other methods for examining differences in the characteristics of encounters over a range of environments. Improved parameterisation of dynamic transmission models gained from work of this type will aid in the development of more robust decision support tools to assist health policy makers and planners.
McCaw
James M
JM
Murdoch Childrens Research Institute, University of Melbourne, Parkville, VIC, Australia. jamesm@unimelb.edu.au
Forbes
Kristian
K
Nathan
Paula M
PM
Pattison
Philippa E
PE
Robins
Garry L
GL
Nolan
Terence M
TM
McVernon
Jodie
J
D000328:Adult; D000368:Aged; D016358:Contact Tracing / Q000379:methods*; D018592:Cross-Over Studies; D003625:Data Collection / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010865:Pilot Projects; D011897:Random Allocation; D012141:Respiratory Tract Infections / Q000453:epidemiology* / Q000635:transmission*; D012919:Social Behavior