title: Concurrent partnerships and the spread of HIV.
abstract: OBJECTIVE
  To examine how concurrent partnerships amplify the rate of HIV spread, using methods that can be supported by feasible data collection.
  
  
  METHODS
  A fully stochastic simulation is used to represent a population of individuals, the sexual partnerships that they form and dissolve over time, and the spread of an infectious disease. Sequential monogamy is compared with various levels of concurrency, holding all other features of the infection process constant. Effective summary measures of concurrency are developed that can be estimated on the basis of simple local network data.
  
  
  RESULTS
  Concurrent partnerships exponentially increase the number of infected individuals and the growth rate of the epidemic during its initial phase. For example, when one-half of the partnerships in a population are concurrent, the size of the epidemic after 5 years is 10 times as large as under sequential monogamy. The primary cause of this amplification is the growth in the number of people connected in the network at any point in time: the size of the largest "component'. Concurrency increases the size of this component, and the result is that the infectious agent is no longer trapped in a monogamous partnership after transmission occurs, but can spread immediately beyond this partnership to infect others. The summary measure of concurrency developed here does a good job in predicting the size of the amplification effect, and may therefore be a useful and practical tool for evaluation and intervention at the beginning of an epidemic.
  
  
  CONCLUSIONS
  Concurrent partnerships may be as important as multiple partners or cofactor infections in amplifying the spread of HIV. The public health implications are that data must be collected properly to measure the levels of concurrency in a population, and that messages promoting one partner at a time are as important as messages promoting fewer partners.
authors.affiliation: Department of Sociology, Pennsylvania State University, University Park, USA.
authors.forename: M
authors.initials: M
authors.lastname: Morris
authors.forename: M
authors.initials: M
authors.lastname: Kretzschmar
mesh_terms: D003198:Computer Simulation; D005260:Female; D015658:HIV Infections / Q000635:transmission*; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D012725:Sexual Behavior