Sexual mixing patterns in the spread of gonococcal and chlamydial infections.

Division of STD Prevention, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA.
American Journal of Public Health (Impact Factor: 4.23). 07/1999; 89(6):825-33. DOI: 10.2105/AJPH.89.6.825
Source: PubMed

ABSTRACT This study sought to define, among sexually transmitted disease (STD) clinic attendees, (1) patterns of sex partner selection, (2) relative risks for gonococcal or chlamydial infection associated with each mixing pattern, and (3) selected links and potential and actual bridge populations.
Mixing matrices were computed based on characteristics of the study participants and their partners. Risk of infection was determined in study participants with various types of partners, and odds ratios were used to estimate relative risk of infection for discordant vs concordant partnerships.
Partnerships discordant in terms of race/ethnicity, age, education, and number of partners were associated with significant risk for gonorrhea and chlamydial infection. In low-prevalence subpopulations, within-subpopulation mixing was associated with chlamydial infection, and direct links with high-prevalence subpopulations were associated with gonorrhea.
Mixing patterns influence the risk of specific infections, and they should be included in risk assessments for individuals and in the design of screening, health education, and partner notification strategies for populations.

  • [Show abstract] [Hide abstract]
    ABSTRACT: Fundamental to the identification of the architecture and organization of complex systems is the detection of modules, also called communities or clusters, through the use of graph partition methods. In this paper, we extend one of the most popular graph partition methods, modularity, to jointly preserve the structure of multiple networks using the multi-view technique. Under the assumption that the same modular structure is shared by all network realizations, we show that the multi-view approach is robust against scaling, noise and outliers. In addition, it can overcome some resolution limitations of the traditional modularity-based method. We demonstrate the performance of the combined modularity-multiview method in simulations and experimental data from a 191-subject functional brain network.
    2013 Asilomar Conference on Signals, Systems and Computers; 11/2013
  • [Show abstract] [Hide abstract]
    ABSTRACT: Incorporation of 'social' variables into epidemiological models remains a challenge. Too much detail and models cease to be useful; too little and the very notion of infection - a highly social process in human populations - may be considered with little reference to the social. The French sociologist Émile Durkheim proposed that the scientific study of society required identification and study of 'social currents'. Such 'currents' are what we might today describe as 'emergent properties', specifiable variables appertaining to individuals and groups, which represent the perspectives of social actors as they experience the environment in which they live their lives. Here we review the ways in which one particular emergent property, hope, relevant to a range of epidemiological situations, might be used in epidemiological modelling of infectious diseases in human populations. We also indicate how such an approach might be extended to include a range of other potential emergent properties to represent complex social and economic processes bearing on infectious disease transmission.
    Global Public Health 02/2015; DOI:10.1080/17441692.2015.1007155 · 0.92 Impact Factor
  • Source


1 Download
Available from