In This Article STI Networks, Patterns, and Control Strategies

  • Introduction

Public Health STI Networks, Patterns, and Control Strategies
by
Ian H. Spicknall, Jeremy A. Grey, Rilene A. Chew Ng, Sevgi O. Aral
  • LAST MODIFIED: 27 June 2018
  • DOI: 10.1093/obo/9780199756797-0188

Introduction

Sexually transmitted diseases are propagated through sexual connections. Networks of sexual connections underlie patterns of infection across time and space. STIs, when untreated, are associated with adverse outcomes such as infertility, HIV-related mortality, congenital syphilis, and ectopic pregnancy, among others. Changes in STI patterns over time and among specific subpopulations can be early indicators of increases in negative health outcomes more broadly. Timely analyses of epidemiologic data can detect groups and locations in need of intervention. These methods of STI control and prevention are multifaceted and have evolved over time. This review examines dominant themes related to STI Networks, STI Patterns, and STI Control Strategies, with a goal to provide readers with tools to become well-informed consumers of novel literature in these areas, and to plan research and intervention activities in the field of STI prevention.

STI Networks

The field of STI networks is broad and dynamic, with literature from diverse domains like sociology, physics, and computer science, as well as more traditional public health–oriented disciplines. The field continues to adapt, expand, and drift—as our computational capabilities have increased, so has activity in network science, applied in a multitude of ways. For the purposes of this review, networks may most simply be thought of as the pipes through which STIs spread. This section first summarizes key works that are helpful in STI network methodology. Second, it highlights some of the more notable STI network data collection studies. Third, it highlights some of the inferences that STI network data combined with mathematical modeling has achieved. It concludes with two smaller discussions, the first examining the emerging area of STI networks based on genetic data, and the second providing an assessment of how missing data affect network analyses.

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