Figure 1.
Outline of FGS-HIV transmission model.
The flow between epidemiological classes for the transmission dynamics of FGS and HIV. Individuals enter the system at age 15, and exit at age 50. ,
,
, and
denote, respectively, the number of women uninfected by HIV and FGS, infected with FGS, infected with HIV, and infected with both HIV and FGS.
and
denote, respectively, the number of men uninfected and infected with HIV.
Table 1.
Estimates of the parameters used in our dynamic HIV-FGS model (Figure 1).
Figure 2.
Comparison of model predictions to Zimbabwe antenatal clinic data for non-urban areas [17].
The solid line represents the yearly HIV prevalence as estimated by our model from baseline epidemiological parameters (dotted lines are the 2.5th and 97.5th percentile values). Empirical HIV prevalence is shown as stars (error bars are the 95% confidence intervals). The model was validated from antenatal clinic data not originally used for model parameterization.
Table 2.
Model fit to data.
Figure 3.
Cost-effectiveness of school-age intervention for the base case analysis.
The number of HIV cases averted (A,B), the cost per HIV cases averted (C,D), and the net savings (E,F) were computed for different efficacies of mass praziquantel administration in reducing FGS (B,D,F) and the mitigated risk of HIV infection per sexual act (A,C,E).
Figure 4.
Partial rank correlation coefficients (PRCCs).
A parameter was considered to be important in affecting the effectiveness of mass drug administration with praziquantel for impact on HIV transmission if |PRCC|>0.4. Specifically, probability of acquiring FGS from adult infection and the annual number of sex acts in low risk partnerships were the most important parameters for the first scenario (A), and the coefficient by which FGS enhances HIV transmission rate per sex act and the annual number of sex acts in low-risk partnerships were the most important parameters for the second scenario (B).