Platelet function defects in adolescents with heavy menstrual bleeding.

Platelet function defects (PFD) are reported to occur frequently in adult women with heavy menstrual bleeding (HMB). Few studies on adolescent HMB report varying incidence rates (2-44%) for PFD. We reviewed our institutional experience in detecting and managing PFD in adolescent HMB. Postmenarchial girls and adolescents with HMB seen at our institution undergo a comprehensive bleeding disorder work-up by paediatric haematology and paediatric gynaecology providers. Whole blood platelet aggregometry (WBPA) is performed as a second tier test after excluding thrombocytopaenia, coagulation factor deficiencies and Von Willebrand disease (VWD). We retrospectively reviewed the medical records of adolescents with HMB seen between June 2009 and November 2010, as approved by the Institutional Review Board. Patient demographics, clinical features, laboratory results, therapy details and patient outcome information were analysed. Overall, 114 postmenarchial girls and adolescents with HMB were evaluated; 68 patients (59%) had WBPA study performed. Nineteen patients (28%) had at least one aggregation or secretion defect; 12 (18%) had two or more such defects. Treatment included hormonal therapy (13/19; 68%), antifibrinolytic agents (8/19; 42%) and intra-nasal DDAVP (3/19; 16%). Thirteen patients (81%) had improved outcome (median follow-up--15.6 months; range of 1-66 months). In this study, PFD were identified in nearly one-third of girls with HMB, with the majority of these having two or more defects as identified by WBPA. Further prospective studies are needed to better define the prevalence and address appropriate management of HMB and other bleeding complications of PFD in adolescents.

Pathogen spread on coupled networks: effect of host and network properties on transmission thresholds.

Human populations are interconnected through a variety of different networks. The complex interactions of diverse populations of individuals and their interconnected network structures affect the diffusion of processes through the population. For example, the different modes of transmission of HIV and TB mean that they are transmitted along very different contact networks: HIV via sexual contact and TB via respiratory contact. In addition, co-infection with HIV raises the risk of progressing to active TB and reduces the response to TB treatment, potentially causing increasing incidence of TB. Here we extend existing network theory to find the effect of multiple networks and multiple host types on epidemic thresholds. We first analyse how transmission of a pathogen via an additional network affects its epidemic threshold. We then use the theory behind branching processes to study how multiple host types in a population affect its threshold. The formulation we obtain enables modellers to determine how multiple networks and host heterogeneity (i.e. vaccination, behavioural change, mixing patterns, etc.) affect the epidemic threshold. We apply the results to the example of HIV and TB to illustrate how the interactions of the diseases can substantially alter the epidemic threshold of TB.

Respondent driven sampling and community structure in a population of injecting drug users, Bristol, UK.

BACKGROUND: A 2006 respondent driven sampling (RDS) survey of injecting drug users (IDUs) in Bristol, UK, estimated 40 per 100 person years HCV incidence but in 2009 another RDS survey estimated only 10 per 100 person years incidence amongst the same population. Estimated increases in intervention exposure do not fully explain the decrease in risk. We investigate whether the underlying contact network structure and differences in the structure of the RDS trees could have contributed to the apparent change in incidence. METHOD: We analyse the samples for evidence that individuals recruit participants who are like themselves (assortative recruiting). Using an assortativity measure, we develop a Monte Carlo approach to determine whether the RDS data exhibit significantly more assortativity than is expected for that sample. Motivated by these findings, a network model is used to investigate how much assortativity and the structure of the RDS tree impacts sample estimates of prevalence and incidence. RESULTS: The samples suggest there is some assortativity on injecting habits or markers of injecting risk. The 2009 sample has lower assortativity than 2006. Simulations of RDS confirm that assortativity influences the estimated incidence in a population and the structure of RDS samples can result in bias. Our simulations suggest that RDS incidence estimates have considerable variance, making them difficult to use for monitoring trends. CONCLUSIONS: We suggest there was likely to have been a decline in risk between 2006 and 2009 due to increased intervention coverage, but the bias and variance in the estimates prevents accurate estimation of the incidence.

Modelling the performance of isoniazid preventive therapy for reducing tuberculosis in HIV endemic settings: the effects of network structure.

Individuals living with HIV experience a much higher risk of progression from latent M. tuberculosis infection to active tuberculosis (TB) disease relative to individuals with intact immune systems. A several-month daily course of a single drug during latent infection (i.e. isoniazid preventive therapy (IPT)) has proved in clinical trials to substantially reduce an HIV-infected individual's risk of TB disease. As a result of these findings and ongoing studies, the World Health Organization has produced strong guidelines for implementing IPT on a community-wide scale for individuals with HIV at risk of TB disease. To date, there has been limited use of IPT at a community-wide level. In this paper, we present a new co-network model for HIV and TB co-epidemics to address questions about how the population-level impact of community-wide IPT may differ from the individual-level impact of IPT offered to selected individuals. In particular, we examine how the effect of clustering of contacts within high-TB incidence communities may affect the rates of re-infection with TB and how this clustering modifies the expected population-level effects of IPT. We find that populations with clustering of respiratory contacts experience aggregation of TB cases and high numbers of re-infection events. While, encouragingly, the overall population-level effects of community-wide IPT appear to be sustained regardless of network structure, we find that in populations where these contacts are highly clustered, there is dramatic heterogeneity in the impact of IPT: in some sub-regions of these populations, TB is nearly eliminated, while in others, repeated re-infection almost completely undermines the effect of IPT. Our findings imply that as IPT programmes are brought to scale, we should expect local heterogeneity of effectiveness as a result of the complex patterns of disease transmission within communities.