Working Paper: NBER ID: w14823
Authors: Ajay Mahal; Brendan O'Flaherty; David E. Bloom
Abstract: Without well designed empirical studies, mathematical models are an important way to use data on needle infection for inferences about human infection. We develop a model with explicit behavioral foundations to explore an array of policy interventions related to HIV transmission among IDU. In our model, needle exchanges affect the spread of HIV in three ways: more HIV-negative IDUs use new needles instead of old ones; needles are retired after fewer uses; and the proportion of HIV-positive IDUs among users of both old and new needles rises owing to sorting effects. The first and second effects reduce the long-run incidence of HIV, while the third effect works in the opposite direction. We compare the results of our model with those of Kaplan and O'Keefe (1993) that is the foundation of many later models of HIV transmission among IDU.
Keywords: HIV; Needle Exchange Programs; Injecting Drug Users; Mathematical Modeling
JEL Codes: I18; K42
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| NEPs (P26) | Increased use of new needles by HIV-negative IDUs (I12) |
| Increased use of new needles by HIV-negative IDUs (I12) | Reduced long-term HIV incidence (I14) |
| NEPs (P26) | Shorter lifespan of needles due to increased turnover (C41) |
| Shorter lifespan of needles due to increased turnover (C41) | Reduced long-term HIV incidence (I14) |
| Increase in the proportion of HIV-positive IDUs (I12) | Increased HIV transmission (F42) |
| Increased HIV transmission (F42) | Counteract reductions in HIV incidence from NEPs (H53) |