ESTIMATION OF SEROPREVALENCE, RAPE, AND HOMELESSNESS IN THE UNITED-STATES USING A SOCIAL NETWORK APPROACH

The authors have developed and tested scale-up methods, based on a sim ple social network theory, to estimate the size of hard-to-count subpo pulations. The authors asked a nationally representative sample of res pondents how many people they knew in a list of 32 subpopulations, inc luding 29 subpopulations of known size and 3 of unknown size. Using th ese responses, the authors produced an effectively unbiased maximum li kelihood estimate of the number of people each respondent knows. These estimates were then used to back-estimate the size of the three popul ations of unknown size. Maximum likelihood values and 95% confidence i ntervals are found for seroprevalence, 800,000 +/- 43,000; for homeles s, 526,000 +/- 35,000; and for women raped in the last 12 months, 194, 000 +/- 21,000. The estimate for seroprevalence agrees strikingly with medical estimates, the homeless estimate is well within the published estimates, and the authors' estimate lies in the middle of the publis hed range for rape victims.