C. P. Farrington

Estimation of the basic reproduction number for infectious diseases from age-stratified serological survey data

The basic reproduction number of an infection, R0, is the average number of secondary infections generated by a single typical infective individual in a totally susceptible population. It is directly related to the effort required to eliminate infection. We consider statistical methods for estimating R0 from age-stratified serological survey data. The main difficulty is indeterminacy, since the contacts between individuals of different ages are not observed. We show that, given an estimate of the average age-specific hazard of infection, a particular leading left eigenfunction is required to specify R0. We review existing methods of estimation in the light of this indeterminacy. We suggest using data from several infections transmitted via the same route, and we propose that the choice of model be guided by a criterion based on similarity of their contact functions. This approach also allows model uncertainty to be taken into account. If one infection induces no lasting immunity, we show that the only additional assumption required to estimate R0 is that the contact function is symmetric. When matched data on two or more infections transmitted by the same route are available, the methods may be extended to incorporate the effect of individual heterogeneity. The approach can also be applied in partially vaccinated populations and to populations comprising loosely linked communities. The methods are illustrated with data on hepatitis A, mumps, rubella, parvovirus, Haemophilus influenzae type b and measles infection.

Does concurrent prescription of selective serotonin reuptake inhibitors and non-steroidal anti-inflammatory drugs substantially increase the risk of upper gastrointestinal bleeding?

Background:  A 15‐fold increased risk of gastrointestinal bleeding has been reported with concurrent use of selective serotonin reuptake inhibitors and non‐steroidal anti‐inflammatory drugs. Recent guidance cautions against concurrent prescription, particularly in older people.

Use of the self-controlled case series method in vaccine safety studies : review and recommendations for best practice

The self-controlled case-series method was originally developed to investigate potential associations between vaccines and adverse events, and is now commonly used for this purpose. This study reviews applications of the method to vaccine safety investigations in the period 1995-2010. In total, 40 studies were reviewed. The application of the self-controlled case-series method in these studies is critically examined, with particular reference to the definition of observation and risk periods, control of confounders, assumptions and potential biases, methodological and presentation issues, power and sample size, and software. Comparisons with other study designs undertaken in the papers reviewed are also highlighted. Some recommendations are presented, with the emphasis on promoting good practice.

Parvovirus B19 viraemia in Dutch blood donors

Blood, donated by asymptomatic donors, may contain and transmit parvovirus B19. To investigate the dynamics of parvovirus viraemia in asymptomatic blood donors, we studied the amounts of parvovirus DNA in pools of donor plasma, the prevalence of parvovirus antibodies among blood donors in relation to age, and the seasonal and year-to-year variation of the incidence of parvovirus infection in The Netherlands. The incidence of parvovirus infection follows a seasonal cycle and a cycle of several years. Among Dutch blood donors the incidence was estimated to be 0.56% per year. Forty seven out of 100 pools of 5000 plasma donations tested positive for parvovirus DNA. We inferred that the course of viraemia in asymptomatic donors shows a short peak (> 10(9) copies parvovirus DNA/ml), followed by viraemia below 10(6) copies/ml for about 2 weeks.

Matrix models for childhood infections: a Bayesian approach with applications to rubella and mumps.

Mathematical modelling is an established tool for planning and monitoring vaccination programmes. However, the matrices describing contact rates are based on subjective choices, which have a large impact on results. This paper reviews published models and obtains prior model probabilities based on publication frequency and expert opinion. Using serological survey data on rubella and mumps, Bayesian methods of model choice are applied to select the most plausible models. Estimates of the basic reproduction number R0 are derived, taking into account model uncertainty and individual heterogeneity in contact rates. Twenty-two models are documented, for which publication frequency and expert opinion are negatively correlated. Using the expert prior with individual heterogeneity, R0=6.1 [95% credible region (CR) 4.3-9.2] for rubella and R0=19.3 (95% CR 4.0-31.5) for mumps. The posterior modes are insensitive to the prior for rubella but not for mumps. Overall, assortative models with individual heterogeneity are recommended.

Measures of Disassortativeness and their Application to Directly Transmitted Infections

We propose a measure of disassortativeness to summarize contact patterns relevant to the transmission of directly transmitted infections. We discuss the properties of this measure, describe standardization relative to homogeneous mixing, and generalize it to multivariate contact structures. We explore some of its properties and apply our methods to serological surveys of close contact infections and surveys of self-reported social contacts obtained in several European countries.

Interval-censored survival data with informative examination times: parametric models and approximate inference.

We develop parametric methods for analysing interval-censored data when examination and survival times are not independent. The hazard function is modelled by introducing individual frailties related to the frequency of examinations. Model parameters may be obtained by direct maximization of the marginal log-likelihood. We develop a simpler approximate method in which the frailties are estimated by empirical Bayes. The two approaches are equivalent asymptotically as the number of examinations on each individual increases. Simulations suggest that the approximate method is adequate for estimating regression parameters even when the number of examinations on each individual is small. The methods are used to estimate age and period effects on HIV incidence in a cohort of repeat attenders at genito-urinary clinics in London, U.K.

Is it appropriate to use fixed assay cut-offs for estimating seroprevalence?

Population seroprevalence can be estimated from serosurveys by classifying quantitative measurements into positives (past infection/vaccinated) or negatives (susceptible) according to a fixed assay cut-off. The choice of assay cut-offs has a direct impact on seroprevalence estimates. A time-resolved fluorescence immunoassay (TRFIA) was used to test exposure to human parvovirus 4 (HP4). Seroprevalence estimates were obtained after applying the diagnostic assay cut-off under different scenarios using simulations. Alternative methods for estimating assay cut-offs were proposed based on mixture modelling with component distributions for the past infection/vaccinated and susceptible populations. Seroprevalence estimates were compared to those obtained directly from the data using mixture models. Simulation results showed that when there was good distinction between the underlying populations all methods gave seroprevalence estimates close to the true one. For high overlap between the underlying components, the diagnostic assay cut-off generally gave the most biased estimates. However, the mixture model methods also gave biased estimates which were a result of poor model fit. In conclusion, fixed cut-offs often produce biased estimates but they also have advantages compared to other methods such as mixture models. The bias can be reduced by using assay cut-offs estimated specifically for seroprevalence studies.