Background:
Increases in rates of early syphilis (200%) and gonorrhea (25%) from 2005 to 2006 in San Mateo County (SMC) are among the highest in the Bay Area. Social networks have been shown to facilitate sexually transmitted disease (STD) transmission. Elicitation of social, non-sexual acquaintances and meeting places may improve partner yields and may have favorable acceptability based on racial/ethnic and acculturation variables.

Objective:
To identify social networks and venues for syphilis and gonorrhea index patients through cluster interviewing, evaluate partner yields, and acceptability of this approach.

Method:
All newly reported cases of gonorrhea and syphilis have been given an enhanced interview (since August 2006) and a cluster interview (since October 2007). In the enhanced interview, patients are asked to identify sexual partners, venues and risk behaviors. In the cluster interview, patients are asked to identify high-risk, non-sexual acquaintances. Basic demographics and network attributes are described, and all individuals and venues with viable addresses are geocoded.

Result:
To date, 54 cases of early syphilis and 356 cases of gonorrhea have been reported. Preliminary results show that enhanced cluster interviewing identified 44 partners, 1 social network of 7 persons, and 1 new venue (crack house). The meeting venue and social network were located in census tracts with the highest rates of STDs in SMC. Approximately 25% of the cases and
43% of the partners were of Hispanic ethnicity. Additional identified partners, social networks and meeting venues identified through cluster interviewing will be mapped.

Conclusion:
Preliminary results suggest that enhanced and cluster interviewing have functionality and acceptability in a California County with a large number of STDs in Hispanics.

Implications:
Health Departments should consider cluster interviewing in addition to traditional sex partner elicitation in high morbidity areas. Given limited STD program resources, this method is effective in identifying, treating and preventing unidentified cases.