From: Bayesian adaptive algorithms for locating HIV mobile testing services
Parameters | Values |
---|---|
Overall population | Simulate from lognormal distribution based on 2010 Lusaka, Zambia census |
Grid dimensions | 6 × 6 |
Level of correlation, percentage of hotspots in grid | Low, 20% (on average) |
Percentage of new infections (times zone population divided by 365 days) | 0.66% |
Percentage of new HIV-negative arrivals (times zone population divided 365 days) | 3.4% |
Days until return to unobserved, uninfected pool | 45 |
Initial observed HIV+/HIV– (priors for TS) | Beta(1, 1) |
Initial observed HIV+/HIV– (priors for ICAR/BYM during learning period) | Beta(1, 1) |
Intercept (priors for ICAR/BYM) | Normal(0, 2.85) |
Priors for ICAR and exchangeable random effects | Inverse-Gamma(3, 2) |
Days of testing | 180 |
Tests per day | 25 |