Injection risk Sex risk

1. .000 .325 [34] [8] .000 [2] ProximalPartner ProximalPartner Female Female Sex Risk by Gender .478 [34] ProximalPartner Distal Partner Distal Partner HIV+ .000[23] .124 [15] Female Male Male .183 [27] .048 [15] .000 [23] .542 .202 .323 .305 .234 [37] .049 .025 [1] [205] [1] [205] .230 [37] [3] [3] .183 [27] Female .141[37] Distal Partner Proximal Partner .286 [11] HIV+ .000 [1] Female .082 [37] .397 [11] Female Male .000 [6] .330 .313 .083 [14] Injection Risk by Gender [162] [12] .375 [34] Distal Partner HIV+ .281 [11] .249 [7] Male Male .242 [11] .312 [3] .464 .355 .356 .314 .282 .410 [22] [4] [84] [84] [8] [8] .215 [10] Proximal Partner .156 [2] HIV+ Female .307 [10] Male .070 [2] .312 .248 [27] [2] .213 [27] Distal Partner Male The HIV Transmission Gradient:Relationship-level Estimates of Risk David C. Bell, Isaac D. Montoya Affiliated Systems Corporation, Houston BACKGROUND RESULTS Of critical importance in the transmission of HIV are “gatekeepers,” the HIV-negative partners of persons who are HIV-infected. These are the persons at risk and they are the persons who can eventually spread the disease further. And since the highest infectivity comes in the first months after infection, usually before knowledge of infection, the behavior of these “gatekeepers” while they are HIV- is critical. • There is a gradient of infection potential by which HIV can diffuse from the HIV+ population through “gatekeepers” to the rest of the population. RESEARCH METHODS We collected a representativesample of 267 personsconsisting of 169 quasi-randomlyrecruited index persons and 98 oftheir sex and drug injection partnersfrom high drug use neighborhoods.They described 3254 relationshipsinvolving 1538 persons. HIV Risk Index:Estimating Potential Transmission We use a “pipeline” estimate of HIV risk. By estimating the “HIV carrying capacity” of the joint behaviors between the partners, we can estimate the conditional probability of HIV transmission if the partner were HIV+. risk indexik where i is respondent k is partner j is risk behavior fj is per-act risk cijk is number of 30-day risk behaviors Imputed per-act transmission probabilities: Vaginal sex from male to female without condom 0.001 Vaginal sex from female to male without condom 0.0005 Vaginal sex from male to female with condom 0.000025 Vaginal sex from female to male with condom 0.0000125 Receptive anal sex without a condom 0.02 Insertive anal sex without a condom 0.0087 Receptive anal sex with a condom 0.0008 Insertive anal sex with a condom 0.00035 Shared injection equipment (infected) 0.0067 Shared cooker, cotton, or water 0.000067 The HIV Transmission Gradient • Injection risk • Sex risk NETWORKS AND RANDOM MIXING Networks organize the possibility of disease transmission. In this set of seven interlocking networks, there are three HIV+ persons (in red). They are linked to eight other persons by risk links (also in red). None of the other persons in the networks is at direct risk. We projected HIV transmission by using 30-day risk estimates and projecting them over the next 20 years. Next we examined the effect of network organization by modifying our data. We took all links from a given person and randomly selected a different partner from the list of partners and then projecting transmission over these relationships. Random mixing projection Network-based projection Years CONCLUSIONS • The network organization of sex and injection behaviors reduces transmission by almost 70% over random mixing. • In general, the highest levels of risk we observe are among HIV+ individuals. • There is an HIV transmission gradient that operates to limit the spread of HIV. • In the general population, people are acting approxi-mately as if their sex partners were HIV+. • Among drug injectors (at least cocaine injectors), we find very high levels of risk.