What Really Is a Concentrated HIV Epidemic and What Does It Mean for West and Central Africa? Insights From Mathematical Modeling

被引:36
作者
Boily, Marie-Claude [1 ]
Pickles, Michael [1 ]
Alary, Michel [2 ]
Baral, Stefan [3 ]
Blanchard, James [4 ]
Moses, Stephen [4 ]
Vickerman, Peter [5 ]
Mishra, Sharmistha [1 ,6 ]
机构
[1] Univ London Imperial Coll Sci Technol & Med, Dept Infect Dis Epidemiol, London W2 1PG, England
[2] Univ Laval, Ctr Rech, CHU Quebec, Dept Med Sociale & Prevent, Laval, PQ, Canada
[3] Johns Hopkins Sch Publ Hlth, Ctr Publ Hlth & Human Rights, Dept Epidemiol, Baltimore, MD USA
[4] Univ Manitoba, Dept Community Hlth Sci, Ctr Global Publ Hlth, Winnipeg, MB R3T 2N2, Canada
[5] Univ Bristol, Sch Social & Community Med, Bristol, Avon, England
[6] Univ Toronto, St Michaels Hosp, Dept Med, Div Infect Dis,Li Ka Shing Knowledge Inst, Toronto, ON M5B 1W8, Canada
基金
加拿大健康研究院;
关键词
concentrated epidemic; West and Central Africa; mathematical modeling; sex work; epidemic driver; SIMPLEX-VIRUS TYPE-2; FEMALE SEX WORKERS; TRANSACTIONAL SEX; INFECTION; ACQUISITION; PREVENTION; MEN; INTERVENTIONS; TRANSMISSION; POPULATIONS;
D O I
10.1097/QAI.0000000000000437
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Background: HIV epidemics have traditionally been classified as "concentrated" among key populations if overall HIV prevalence was below 1% and as "generalized" otherwise. We aimed to objectively determine the utility of this classification by determining how high overall HIV prevalence can reach in epidemics driven by unprotected sex work (SW) and how estimates of the contribution of SW to HIV transmission changes over time in these epidemics. Methods: We developed a deterministic model of HIV transmission specific to West and Central Africa to simulate 1000 synthetic HIV epidemics, where SW is the sole behavioral driver that sustains HIV in the population (ie, truly concentrated epidemics), and it is based on a systematic extraction of model parameters specific to West and Central Africa. We determined the range of plausible HIV prevalence in the total population over time and calculated the population attributable fraction (PAF) of SW over different time periods. Results: In 1988 and 2008, HIV prevalence across the 1000 synthetic concentrated HIV epidemics ranged (5th-95th percentile) between 0.1%-4.2% and 0.1%-2.8%, respectively. The maximum HIV prevalence peaked at 12%. The PAF of SW measured from 2008 over 1 year was <5%-18% compared with 16%-59% over 20 years in these SW-driven epidemics. Conclusions: Even high HIV-prevalence epidemics can be driven by unprotected SW and therefore concentrated. Overall, HIV prevalence and the short-term PAF are poor makers of underlying transmission dynamics and underestimate the role of SW in HIV epidemics and thus should not be used alone to inform HIV programs.
引用
收藏
页码:S74 / S82
页数:9
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