OBJECTIVE: To assess the degree of sexual mixing in a sexually transmitted disease clinic population stratified by country of birth. DESIGN: Prospective linked HIV serosurvey incorporating demographic and sexual risk data gathered by a doctor-administered questionnaire. SETTING: The Department of Genitourinary Medicine at St Thomas' Hospital, London, UK. SUBJECTS: Fifteen thousand eight hundred and seventy-eight heterosexuals who attended between April 1992 and February 1995. MAIN OUTCOME MEASURE: The degree of assortative (like-with-like) mixing, after stratification of the population by country of birth, of index patients, their parents and their sexual partners. RESULTS: Sexual mixing in this population of sexually transmitted disease clinic attenders is highly assortative when the CoB of parents (family origin) of index patients is taken into account. CONCLUSION: Our findings help to explain the low spread of heterosexual HIV infection in the UK to date, and may help future projections, and health targeting of those at risk. This model can be applied to other mixed population.
OBJECTIVE: To assess the degree of sexual mixing in a sexually transmitted disease clinic population stratified by country of birth. DESIGN: Prospective linked HIV serosurvey incorporating demographic and sexual risk data gathered by a doctor-administered questionnaire. SETTING: The Department of Genitourinary Medicine at St Thomas' Hospital, London, UK. SUBJECTS: Fifteen thousand eight hundred and seventy-eight heterosexuals who attended between April 1992 and February 1995. MAIN OUTCOME MEASURE: The degree of assortative (like-with-like) mixing, after stratification of the population by country of birth, of index patients, their parents and their sexual partners. RESULTS: Sexual mixing in this population of sexually transmitted disease clinic attenders is highly assortative when the CoB of parents (family origin) of index patients is taken into account. CONCLUSION: Our findings help to explain the low spread of heterosexual HIV infection in the UK to date, and may help future projections, and health targeting of those at risk. This model can be applied to other mixed population.
Authors: Nina T Harawa; Trista A Bingham; Susan D Cochran; Sander Greenland; William E Cunningham Journal: Am J Public Health Date: 2002-12 Impact factor: 9.308
Authors: Manon Ragonnet-Cronin; Nanette Benbow; Christina Hayford; Kathleen Poortinga; Fangchao Ma; Lisa A Forgione; Zhijuan Sheng; Yunyin W Hu; Lucia V Torian; Joel O Wertheim Journal: AIDS Res Hum Retroviruses Date: 2021-02-08 Impact factor: 1.723
Authors: Alethea W McCormick; Nadia N Abuelezam; Erin R Rhode; Taige Hou; Rochelle P Walensky; Pamela P Pei; Jessica E Becker; Madeline A DiLorenzo; Elena Losina; Kenneth A Freedberg; Marc Lipsitch; George R Seage Journal: PLoS One Date: 2014-05-27 Impact factor: 3.240