Development of a prognostic model based on demographic, environmental and lifestyle information for predicting incidences of symptomatic respiratory or gastrointestinal infection in adult office workers

BACKGROUND Occurrence of respiratory tract infection (RTI) or gastrointestinal tract infection (GTI) is known to vary between individuals and may be a confounding factor in the analysis of the results of intervention trials. We aimed at developing a prognostic model for predicting individual incidences of RTI and GTI on the basis of data collected in a hand-hygiene intervention trial among adult office workers, and comprising a prior-to-onset questionnaire on potential infection-risk factors and weekly electronic follow-up reports on occurrence of symptoms of, and on exposures to RTI or GTI. METHODS A mixed-effect negative binomial regression model was used to calculate a predictor-specific incidence rate ratio for each questionnaire variable and for each of the four endpoints, and predicted individual incidences for symptoms of and exposures to RTI and GTI. In the fitting test these were then compared with the observed incidences. RESULTS Out of 1270 eligible employees of six enterprises, 683 volunteered to participate in the trial. Ninety-two additional participants were recruited during the follow-up. Out of the 775 registered participants, 717 returned the questionnaire with data on potential predictor variables and follow-up reports for determination of outcomes. Age and gender were the strongest predictors of both exposure to, and symptoms of RTI or GTI, although no gender difference was seen in the RTI incidence. In addition, regular use of public transport, and history of seasonal influenza vaccination increased the risk of RTI. The individual incidence values predicted by the model showed moderate correlation with those observed in each of the four categories. According to the Cox-Snell multivariate formula the model explained 11.2% of RTI and 3.3% of GTI incidences. Resampling revealed mean and 90% confidence interval values of 10.9 (CI 6.9-14.5)% for RTI and 2.4 (0.6-4.4)% for GTI. CONCLUSION The model created explained a relatively small proportion of the occurrence of RTI or GTI. Unpredictable exposure to disease agents, and individual susceptibility factors are likely to be key determinants of disease emergence. Yet, the model might be useful in prerandomization stratification of study population in RTI intervention trials where the expected difference between trial arms is relatively small. TRIAL REGISTRATION Registered at ClinicalTrials.gov with Identifier NCT00821509 on 12 March 2009.