Table 5 Continued Year Population Structure Intervention Method Partnership Formation Outcome of Validity Interest Strength: Sensitivity 3 sexual activity group, gender; Prefixed intervention Partial Partnerships formed from analysis, uses the model to from the survey: differential the two higher risk groups see whether behavior existed HIV status: 5 different disease HIV condom use rate, equations, with are classified as casual; stages susceptible, acute infection, given the observational partnership turnover parameters, Others are regular. 20095 Heterosexual prevalence. latent infection, pre-AIDS and rate. Not testing new estimated from Zimbabwe full-blown AIDS. The mixing pattern is intervention strategies data Limitation: Not considering either random or the duration of relationship assortative. and concurrency Marital status, age group, sexual Widows prefer Predicted case Strength: Locally activity group (sex worker, casual or random; averted (the appropriate, unique target Reducing the number of ODEs numerical sex or spousal sex); widows date within their percentage fewer population. Targeted sexual partnerships solution using age groups VS. Older cases in the intervention 200915 Heterosexual HIV status: susceptible, primary, involving widows. Runge-Kutta male widows prefer intervention Manicaland, incubating, pre-AIDS, full-blown algorithm; Limitation: No sensitivity younger women compared compared to Zimbabwe AIDS. analysis, data only available to non-widows baseline) for three years follow-up Sex-role preference (only top, only ODEs analytical Strength: Considered bottom or versatile), money vaccine effectiveness 200916 Homosexual HAART; Vaccine Disassortative HIV prevalence boy(male sex workers); analysis; Shanghai, Limitation: Did not consider China HIV status: susceptible and the impact of different HIV infective stages Assortative, proportionate By ethnic groups: Africans, Strength: Model could apply and disassortative are all Caribbean (countries with high to different countries considered as mixing HIV prevalence HIV prevalence) and general patterns. Partnerships are under different Limitation: Only considered Dutch people; By gender. 6 201013 Heterosexual HAART ODE numerical formed as the main mixing pattern immigrants and local people subpopulations in total. Amsterdam, solutions partnership (steady and simulation in the mixing, neglect the Netherlands long-term) and secondary HIV status: susceptible, acute, other common partnership (casual or chronic, and pre-AIDS. characteristics such as age, concurrent steady partnership).
Table 5 Continued Year Population Structure Intervention Method Partnership Formation Outcome of Interest Validity 20095 Heterosexual Zimbabwe 3 sexual activity group, gender; HIV status: 5 different disease stages susceptible, acute infection, latent infection, pre-AIDS and full-blown AIDS. Prefixed intervention from the survey: condom use rate, partnership turnover rate. Not testing new intervention strategies Partial differential equations, with parameters, estimated from data Partnerships formed from the two higher risk groups are classified as casual; Others are regular. The mixing pattern is either random or assortative. HIV Strength: Sensitivity analysis, uses the model to see whether behavior existed given the observational prevalence. Limitation: Not considering the duration of relationship and concurrency 200915 Heterosexual Manicaland, Zimbabwe Marital status, age group, sexual activity group (sex worker, casual sex or spousal sex); HIV status: susceptible, primary, incubating, pre-AIDS, full-blown AIDS. Reducing the number of sexual partnerships involving widows. ODEs numerical solution using Runge-Kutta algorithm; Widows prefer or random; widows date within their age groups VS. Older male widows prefer younger women compared to non-widows Predicted case averted (the percentage fewer cases in the intervention compared to baseline) Strength: Locally appropriate, unique target population. Targeted intervention Limitation: No sensitivity analysis, data only available for three years follow-up 200916 Homosexual Shanghai, China Sex-role preference (only top, only bottom or versatile), money boy(male sex workers); HIV status: susceptible and infective HAART; Vaccine ODEs analytical analysis; Disassortative HIV prevalence Strength: Considered vaccine effectiveness Limitation: Did not consider the impact of different HIV stages 201013 Heterosexual Amsterdam, Netherlands By ethnic groups: Africans, Caribbean (countries with high HIV prevalence) and general Dutch people; By gender. 6 subpopulations in total. HIV status: susceptible, acute, chronic, and pre-AIDS. HAART ODE numerical solutions Assortative, proportionate and disassortative are all considered as mixing patterns. Partnerships are formed as the main partnership (steady and long-term) and secondary partnership (casual or concurrent steady partnership). HIV prevalence under different mixing pattern simulation Strength: Model could apply to different countries Limitation: Only considered immigrants and local people in the mixing, neglect the other common characteristics such as age,