Effect of maternal vitamin D supplementation on nasal pneumococcal acquisition, carriage dynamics and carriage density in infants in Dhaka, Bangladesh

Background Invasive pneumococcal disease is a major cause of infant morbidity and death worldwide. Vitamin D promotes anti-pneumococcal immune responses in vitro, but whether improvements in infant vitamin D status modify risks of nasal pneumococcal acquisition in early life is not known. Methods This is a secondary analysis of data collected in a trial cohort in Dhaka, Bangladesh. Acute respiratory infection (ARI) surveillance was conducted from 0 to 6 months of age among 1060 infants of women randomized to one of four pre/post-partum vitamin D dose combinations or placebo. Nasal swab samples were collected based on standardized ARI criteria, and pneumococcal DNA quantified by qPCR. Hazards ratios of pneumococcal acquisition and carriage dynamics were estimated using interval-censored survival and multi-state modelling. Results Pneumococcal carriage was detected at least once in 90% of infants by 6 months of age; overall, 69% of swabs were positive (2616/3792). There were no differences between any vitamin D group and placebo in the hazards of pneumococcal acquisition, carriage dynamics, or carriage density (p > 0.05 for all comparisons). Conclusion Despite in vitro data suggesting that vitamin D promoted immune responses against pneumococcus, improvements in postnatal vitamin D status did not reduce the rate, alter age of onset, or change dynamics of nasal pneumococcal colonization in early infancy. Trial registration Registered in ClinicalTrials.gov with the registration number of NCT02388516 and first posted on March 17, 2015.

A model for reconstructing trends and distribution in age at first sex from multiple household surveys with reporting biases

Age at first sex (AFS) is a key indicator for monitoring sexual behaviour risk for HIV and sexually transmitted diseases. Reporting of AFS data, however, suffer social-desirability and recall biases which obscure AFS trends and inferences constructed from it. We illustrated examples of the biases using data from multiple nationally-representative Demographic and Health Surveys household surveys conducted between 1992 and 2019 in Ethiopia (4 surveys), Guinea (4 surveys), Senegal (8 surveys), and Zambia (8 surveys). Based on this, we proposed a time-to-event, interval censored model for the AFS that uses overlapping reports by the same birth cohort in successive surveys to adjust reporting biases. The three-parameter log-skew-logistic distribution described the asymmetric and nonmonotonic hazard exhibited by empirical AFS data. In cross-validation analysis, incorporating a term for AFS reporting bias as a function of age improved model predictions for the trend of AFS over birth cohorts. The interquartile range for the AFS was 16 years to 23 years for Ethiopian and Senegalese women and 15 years to 20 years for Guinean and Zambian men. Median AFS increased by around one to 1.5 years between the 1960 and 1989 birth cohorts for all four datasets. Younger male respondents tended to report a younger AFS while female respondents tended to report an older AFS than when asked in later surveys. Above age 30, both male and female respondents tended to report older AFS compared to when surveyed in their late twenties. Simulations validated that the model recovers the trend in AFS over birth cohorts in the presence of reporting biases. At least three surveys are needed to obtain reliable trend estimate for a 20-years trend. Mis-specified reference age at which reporting is assumed unbiased did not affect the trend estimate but resulted in biased estimates for the median AFS in the most recent birth cohorts.

Regression analysis of multivariate interval-censored failure time data with informative censoring

Regression analysis of multivariate interval-censored failure time data has been discussed by many authors1-6. For most of the existing methods, however, one limitation is that they only apply to the situation where the censoring is non-informative or the failure time of interest is independent of the censoring mechanism. It is apparent that this may not be true sometimes and as pointed out by some authors, the analysis that does not take the dependent censoring into account could lead to biased or misleading results7,8. In this study, we consider regression analysis of multivariate interval-censored data arising from the additive hazards model and propose an estimating equation-based approach that allows for the informative censoring. The method can be easily implemented and the asymptotic properties of the proposed estimator of regression parameters are established. Also we perform a simulation study for the evaluation of the proposed method and it suggests that the method works well for practical situations. Finally, the proposed approach is applied to a set of real data.