Stigum H, Falck W, Magnus P
Department of Epidemiology, National Institute of Public Health, Oslo, Norway.
Math Biosci. 1994 Mar;120(1):1-23. doi: 10.1016/0025-5564(94)90036-1.
A set of differential equations are used to model the spread of sexually transmitted diseases (STDs) in a one-sex population that includes a core group of highly sexually active subjects. The effects of partner mixing between groups and migration to and from the core on the equilibrium number of infected are shown for gonorrhea, chlamydia, and HIV. The STDs are described by the transmission probability per sexual contact and the duration of infectiousness. Partner change and intercourse frequencies are estimated from sexual survey data on heterosexual behavior. The core group is small (3% of the total population) with a partner change frequency 15 times and an intercourse frequency 2 times that of the remaining population. The degree of partner mixing and migration between the two groups can be varied. The number of sexual contacts in the three types of partnerships (core-core, "mixed," remaining population-remaining population) is also modeled. The mixed partnerships are assumed to be casual and to have a low frequency of intercourse. The model is fairly simple, and the emphasis is on qualitative rather that predictive results. The effects of partner mixing are found to be strikingly different for gonorrhea, chlamydia, and HIV. With increasing partner mixing between groups, gonorrhea shows a small increase and then a decrease in the total number of infected, whereas chlamydial infection shows a strong increase. For HIV infection the effect depends on the transmission probability; when it is 0.001 per sexual contact, the number of infected with HIV is almost unaffected by the partner mixing, and when the transmission probability is 0.002 per sexual contact, there is a strong increase in the number of HIV infected with increasing partner mixing. The effects of migration are also different for each disease. With increasing migration between groups, gonorrhea is almost unaffected in the total number of infected, whereas chlamydial infection shows a strong increase. For HIV the effect again depends on the transmission probability; when it is 0.001 per sexual contact, the number of infected with HIV shows a strong decrease, and when the transmission probability is 0.002 per sexual contact the number of HIV infected reaches its maximum for medium strong migration. A sensitivity analysis shows that for all three diseases the basic reproductive ratios (R0) and the total number of infected are sensitive to duration of infectiousness. In addition, for gonorrhea and chlamydia, RO is sensitive to the partner change rates in the core, whereas for HIV, RO is sensitive to the frequency of intercourse in the core.(ABSTRACT TRUNCATED AT 400 WORDS)
一组微分方程被用于模拟性传播疾病(STD)在单性别群体中的传播情况,该群体包括一群性活动高度活跃的核心人群。针对淋病、衣原体感染和艾滋病病毒(HIV),展示了不同群体间性伴侣混合以及核心人群的进出迁移对感染平衡数量的影响。性传播疾病通过每次性接触的传播概率和传染期来描述。性伴侣更换频率和性交频率是根据异性性行为的性调查数据估算得出的。核心群体规模较小(占总人口的3%),其性伴侣更换频率是其余人群的15倍,性交频率是其余人群的2倍。两组之间的性伴侣混合程度和迁移程度可以有所变化。还对三种类型性伴侣关系(核心人群 - 核心人群、“混合”、其余人群 - 其余人群)中的性接触次数进行了建模。假设混合性伴侣关系是偶然的,且性交频率较低。该模型相当简单,重点在于定性而非预测结果。研究发现,淋病、衣原体感染和HIV在性伴侣混合方面的影响显著不同。随着群体间性伴侣混合程度的增加,淋病的总感染人数先略有增加然后减少,而衣原体感染人数则大幅增加。对于HIV感染,其影响取决于传播概率;当每次性接触的传播概率为0.001时,HIV感染人数几乎不受性伴侣混合的影响,而当每次性接触的传播概率为0.002时,随着性伴侣混合程度的增加,HIV感染人数大幅上升。每种疾病在迁移方面的影响也有所不同。随着群体间迁移的增加,淋病的总感染人数几乎不受影响,而衣原体感染人数大幅增加。对于HIV,其影响同样取决于传播概率;当每次性接触的传播概率为0.001时,HIV感染人数大幅下降,而当每次性接触的传播概率为0.002时,在中等强度迁移情况下,HIV感染人数达到最大值。敏感性分析表明,对于所有三种疾病,基本繁殖数(R0)和总感染人数对传染期敏感。此外,对于淋病和衣原体感染,R0对核心人群中的性伴侣更换率敏感,而对于HIV,R0对核心人群中的性交频率敏感。(摘要截取自400字)