The Role of Viral Introductions in Sustaining Community-Based HIV Epidemics in Rural Uganda: Evidence from Spatial Clustering, Phylogenetics, and Egocentric Transmission Models
Figure 2
Spatial clustering of HIV-seropositive persons within households (0 km) and in geographic windows of 250 m up to 10 km (the first window is 10–250 m, and windows are centered every 50 m starting at 125 m).
Spatial clustering analyses show whether HIV prevalence or incidence is elevated within certain distances of other HIV-seropositive persons. We define the spatial clustering of HIV-seropositive individuals as τ(d1,d2), the relative probability that an HIV-seropositive person resides within a distance window, d1 to d2, from another HIV-seropositive person compared to the probability that any individual is HIV seropositive in the entire study population. Where spatial clustering exists, values of τ(d1,d2) exceed one. Shaded areas show the 95% bootstrapped confidence intervals for spatial clustering estimates. (A) The spatial clustering between HIV-seropositive persons (prevalent or incident cases with other prevalent or incident cases; red). (B) The spatial clustering of HIV-seroincident cases with ART-naïve HIV-seroprevalent persons (yellow). (C) The spatial clustering of HIV-seroincident cases with other HIV-seroincident cases (blue). (D) A blowup of the area where significant extra-household spatial clustering (<500 m) was identified among all HIV-seropositive persons (marked with black box in [A–C]). Data are shown only up to 10 km (no significant spatial clustering was observed beyond this distance).