Autonomous Targeting of Infectious Superspreaders Using Engineered Transmissible Therapies

Metzger, Vincent T.; Lloyd-Smith, James O.; Weinberger, Leor S.

To test whether a TIP against HIV could autonomously target high-risk groups, and effectively reduce HIV prevalence, we build upon an established epidemiological model of HIV/AIDS transmission in sub-Saharan Africa that includes four classes of sexual risk behavior based on field data [12] . We develop a datadriven, three-scale model ( Figure 1 ) that translates molecular-level characteristics of the TIP to predict patient-level HIV viral load and ultimately predict HIV/AIDS incidence and prevalence at the population scale. At the single-cell level, the model considers the dynamics of competition between TIP genomic mRNA and HIV genomic mRNA for packaging components [23] . These molecular-level effects of the TIP are translated to viral loads using an established in vivo model of HIV dynamics [24] that includes TIP dynamics [19] . Measured relationships between viral load and transmission [25] are used to estimate TIP and HIV transmission rates between individuals, and the rate of disease progression is estimated based on field data of HIV viral load [26] (see Text S1).