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Another Use for Rapid Home H.I.V. Test: Screening Sexual Partners
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- see below for published study and commentary full text/pdfs
NY Times By DONALD G. McNEIL Jr.
Published: October 5, 2012
The first rapid home-testing kit for H.I.V. has just gone on sale for $40, marketed as a way for people to find out privately if they have the virus that causes AIDS.
Some experts said the OraQuick test's $40 price would prevent many people from using it to screen partners.
But some experts and advocates say that another use, unadvertised, for the OraQuick test - to screen potential sexual partners - may become equally popular and even help slow an epidemic stuck at 50,000 new infections each year in the United States.
There are reasons to think that screening might make a difference. Studies have found that a significant minority of people who are H.I.V.-positive either lie about their status or keep it secret, infecting unsuspecting partners.
And though the manufacturer, OraSure Technologies, is not promoting the use of the test for screening, 70 percent of the 4,000 men and women in the company's clinical trials said they would either definitely or very likely use it that way. Some even suggested that the company sell boxes of two so couples could be tested together.
The only study of the practice - a small one involving 27 gay men who frequently had sex with virtual strangers without using condoms - found that it probably prevented some infections. The study was published online in August by the journal AIDS and Behavior.
"If it becomes a community norm, people may start testing their partners," said Alex Carballo-Dieguez, the lead author of the study, who is a psychology professor at Columbia University and the associate director of the H.I.V. Center for Clinical and Behavioral Studies at the New York State Psychiatric Institute. "On sex sites now, men advertise themselves as 'drug-and-disease-free.' They could start saying 'D-and-D-free, and willing to prove it.' "
Other AIDS experts had doubts. Some thought $40 was too much for people who need to screen multiple partners. Others said that men and women who are not comfortable demanding that their partners wear condoms would be unable to insist on a test.
And some, including Anthony S. Fauci, the country's best-known AIDS doctor, worried that a negative test could lead partners to forgo condoms, removing the barrier to both H.I.V. and other diseases like gonorrhea.
The OraQuick test is imperfect. It is nearly 100 percent accurate when it indicates that someone is not infected and, in fact, is not. But it is only about 93 percent accurate when it says that someone is not infected and the person actually does have the virus, though the body is not yet producing the antibodies that the test detects.
The men in Dr. Carballo-Dieguez's study were given 16 tests each and followed for three months. None of them had unprotected sex with anyone who tested positive.
Of the 101 partners they tested, 10 were positive. In six cases, it was how the partner first learned he was infected. (Ten percent is a very high success rate for H.I.V. testing, experts said.)
Twenty-three other partners refused testing. Two, after being asked, admitted knowing they were infected.
Seven men got angry, and one stomped on the kit. One man walked out saying he wanted to be alone and broke off contact.
Asking usually did not ruin the moment's intimacy, the men said. Some pairs did the tests together, swabbing each other's gums. Some passed the 20-minute wait talking, playing video games or in foreplay. One 47-year-old man found the wait helpful, telling the researchers, "It gives you that extra 20 minutes to decide, 'O.K., if this comes back negative, am I really ready to bareback?' " - slang for having sex without a condom.
Dr. Carballo-Dieguez said people's decision about whether to screen would depend on various factors, including the test's price and how comfortable they were with its imperfect accuracy.
OraSure appears ambivalent about partner screening. AIDS experts said the company might fear lawsuits by people infected by partners who got false negatives - a possibility it declined to comment on. In an interview, its president, Douglas A. Michel, said, "We're supportive, as long as it's between consenting adults."
But he also said the label would warn that the test "should not be used to make decisions that might put the user at risk of contracting H.I.V."
Asked about the price of the test, he said market research indicated that most users would buy it once or twice a year, so $40 was "appropriate."
The technology is similar to that in home pregnancy kits, which sell for as little as $4 each.
Larry Kramer, the longtime AIDS activist, called screening "a potentially cool idea, but it depends on how the partner/date/trick/stranger takes it."
If a test had been around 30 years ago, he added, "there would have been a lot more people alive today."
Hunteur Vreeland, a professional party organizer who arranges "gay porn harbor cruises" and "underwear erotic parties" at Paddles, a dungeon-themed club in New York, said he would even consider selling home tests at his events. He now offers free H.I.V. testing at them in conjunction with the Men's Sexual Health Project of Bellevue Hospital Center.
"Knowledge is never a bad thing," he said. He added that if a potential partner unexpectedly pulled out a test kit, he would probably leave.
Then he reconsidered.
"But if the dude was hot, and maybe I was on the cusp of getting tested anyway - well, then, maybe I'd be, 'All right, I'll take it.' "
Justin Goforth, the director of medical adherence for Whitman-Walker Health, a clinic in Washington with many AIDS patients, said he doubted that screening would help his clientele.
"It's expensive," he said. "People who can afford it already have strategies for avoiding infection. It won't help women whose men refuse to use condoms, because he'll refuse to take the test, too. And the same for young black men - they usually get infected by older men, and the power dynamic is not in their favor."
Steven Petrow, the author of "Complete Gay & Lesbian Manners," argued against screening.
"Nobody should take this test and 20 minutes later go have unprotected sex," he said. "The art of talking to a partner is the primary thing. You have to respect each other and tell the truth."
But numerous studies have shown that many sexual partners do not.
In a large 2007 survey led by Dr. Robert Klitzman, also of Columbia University and the New York State Psychiatric Institute, nearly 20 percent of infected gay men admitted to having had unprotected sex with at least one partner without revealing their status.
Men made many excuses, saying they believed that they were not infectious or felt it was the partner's duty to ask.
An equally large 2003 study led by Dr. Daniel H. Ciccarone of the University of California, San Francisco, found that about 9 percent of H.I.V.-positive heterosexual men and women and about 14 percent of infected gay or bisexual men had recently had unprotected sex with someone they either knew was uninfected or were unsure about, without revealing their own infection.
The authors estimated that in the six months their study covered, 17,000 infected gay men across the country and almost 5,000 infected heterosexual men and women had sex without telling the truth.
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Use of a Rapid HIV Home Test to Screen Sexual Partners: An Evaluation of its Possible Use and Relative Risk
Ana Ventuneac1 , Alex Carballo-Dieguez1, Cheng-Shiun Leu1, 2, Bruce Levin1, 2, Jose Bauermeister3, Emily Woodman-Maynard4 and Rebecca Giguere1
(1) HIV Center for Clinical and Behavioral Studies, New York State Psychiatric Institute, Columbia University, Unit 15, 1051 Riverside Drive, New York, NY 10032, USA
(2) Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA
(3) Health Behavior and Health Education, School of Public Health, University of Michigan, Ann Arbor, MI, USA
(4) Clinical Psychology, Fordham University, New York, USA
Abstract
We estimated the HIV risk reduction that could be attained by using a rapid HIV home test (HT) to screen sexual partners versus using condoms in different proportions of anal intercourse (AI) occasions among men who have sex with men (MSM). Special attention was paid to the role of the window period during which infected cases go undetected. Our results show that if MSM engage in anal intercourse [AI] without condoms following a non-reactive HT result, they have lower chances of becoming infected by someone still in the window period than by following heuristics and using condoms inconsistently. For MSM who do not use condoms, use of HT as a screening device may be a useful risk reduction strategy. This advantage increases with higher HIV population prevalence. With higher HIV incidence, this strategy will not provide any advantage if condoms are used in as little as one out of four occasions.
Introduction
Evidence from recent studies on the sexual behavior of men who have sex with men (MSM) substantiates the assertion that some of the men who will not or cannot use condoms consistently are actively seeking and engaging in strategies to lower the risk of HIV transmission (Eaton et al. 2007; Elford et al. 2007; George et al. 2006; Golden et al. 2008; Halkitis et al. 2005; Mao et al. 2006; Parsons et al. 2005; Pinkerton 2008; Poppen et al. 2005; Truong et al. 2006; Xia et al. 2006). Serosorting, defined as "the practice of preferentially choosing sex partners, or deciding not to use condoms with selected partners, based on their disclosed, concordant HIV status" (Golden et al. 2008, p. 212), has increased in popularity among HIV-negative MSM. However, recent studies have demonstrated that this practice is not effective and may actually increase men's risk of HIV transmission (Eaton et al. 2007; Golden et al. 2008; Pinkerton 2008). This may occur if, for example, assumptions about one's own status are inaccurate (Eaton et al. 2007; Golden et al. 2008; Pinkerton 2008), as may be the case if one is tested for HIV infrequently. A recent study found that testing intervals were wide for the majority of MSM occurring 14 months, on average, after the last test (Eaton et al. 2007); knowledge of one's own HIV status may be inaccurate if such a large interval is the norm and the individual engages in frequent HIV risk behavior.
Other studies have documented a widespread lack of accurate knowledge about one's own HIV status. MacKellar et al. (2005), using data collected from MSM, ages 15-29, at 263 randomly sampled venues in six US cities between 1994 and 2000, found that the majority of MSM who tested positive were unaware of their infection. Estimates indicate that, compared to people who are aware of their infection, those who are unaware of their status engage in greater sexual risk behaviors (Marks et al. 2005), and contribute to new infections disproportionately (Marks et al. 2006).
Various efforts are underway to increase the number of individuals who are regularly tested for the virus in the US (Branson et al. 2006), including making a rapid HIV test available for over-the-counter (OTC) use (Huff 2005; Spielberg et al. 2004; Walensky and Paltiel 2006; Wright and Katz 2006). In November of 2005, the FDA started to consider licensing the OraQuick® ADVANCE Rapid HIV-1/2 Antibody Test, produced by OraSure Technologies Inc., for OTC sale (Richmond 2005; Wright and Katz 2006). This test is already approved by the FDA for use in testing facilities (Branson 2000) and, if approved for OTC sale, could be self-administered in the privacy of one's own home using an oral fluid sample.
Despite the potential of a rapid HIV home test (HT) to reach individuals who might be reluctant to test themselves in a clinical setting, there is concern that it could be used to screen partners prior to sexual intercourse (Walensky and Paltiel 2006; Goldstein 2005; Harris 2005). All antibody-based tests have a window period during which an infected individual tests negative (Fiebig et al. 2003); the home test is no exception. Most worrisome, this is a period of acute HIV infection during which a newly infected individual may be most contagious (Ahlgren et al. 1990; Jacquez et al. 1994; Pilcher et al. 2005; Rapatski et al. 2005; Wawer et al. 2005). If individuals decide to have sex without condoms after receiving a false non-reactive HT result, they might unknowingly put themselves at risk for infection.
Our study objective was to estimate the risk of HIV infection run by MSM if they use HT to screen potential sexual partners as compared to the risk run if they use condoms inconsistently. We used epidemiological and behavioral data from MSM to address the following research question: Given that antibodies are not likely to be detected during the 3-month window period of primary or acute HIV infection, a high-infectivity stage during which the rate of transmission is thought to be highest as compared to the subsequent asymptomatic stage of infection, and considering that partners are likely to get a false-negative result during this period, would lack of condom use following a non-reactive HT result increase an individual's risk of HIV infection when compared to inconsistent condom use without HT use?
Discussion
Our mathematical modeling involved calculating the relative risk of using HT to screen sexual partners versus inconsistent condom use. The probability of HIV infection was calculated based on the following factors: HIV prevalence and incidence estimates; infectiousness; HT and condom use-effectiveness (HT-use was constant in our equation); condom breakage and slippage; HT sensitivity estimates; condom use if HT result is reactive; and number of partners and AI occasions. A key strength of our analyses is that the number of partners and number of AI occasions used in our calculations were not set arbitrarily; rather, they were estimated based on data collected in a prior study of HIV-uninfected MSM who are at high risk of HIV infection due to inconsistent or no condom use. Our calculations indicate that, as HIV prevalence increases in the population, there is advantage in using HT to screen partners versus low levels of condom use. However, the advantage dissipates with higher HIV incidence.
Our findings are in line with the work of Varghese et al. (2002) who estimated that, among MSM, engaging in sexual intercourse with a partner who tested negative reduced the relative risk of HIV infection as compared to sexual intercourse with untested partners. Based on their calculations for MSM, they noted that "[e]nsuring that a partner is HIV-negative can be one of the most effective strategies for prevention of HIV infection" (p. 42). However, the findings point to the importance of infectiousness during the acute stage (Eaton et al. 2007; Pinkerton 2008) in determining risk, particularly for populations with high HIV incidence. If MSM engage in AI without condoms following a non-reactive HT result, they would have lower chances of becoming infected by someone still in the window period of infection than by using condoms in as much as five out of ten sexual occasions. HT as a sexual partner screening device may be a useful risk reduction strategy for MSM who do not use condoms. This advantage increases with higher prevalence in the population. However, with higher incidence in the population, this strategy will not provide any advantage to men over and above condom use, if condoms are used in as little as one out of four occasions.
This study has some limitations. First, we did not include in our calculations other factors that could potentially impact the probability of HIV infection, such as the presence of sexually transmitted infections or circumcision status. Assumptions could be made for other parameters of interest (e.g., type of partner and thereby number of AI occasions). For example, reasonable assumptions could be made about the distribution of the number of AI occasions by partner-type, in that many more occasions may take place with a few "steady" partners and only a few occasions with "other" partners, such as one-night stands (Pinkerton and Abramson 1993). Thus realistic patterns of sexual behavior with long-term versus short-term partners could be factored in. For example, Pinkerton and Abramson (1993) found that a substantial risk reduction can be made if condom-use is consistent with all one-night stands in high prevalence populations.
In addition, our approach was intentionally chosen to be conservative in order to provide an upper bound for the risk. We assumed that acutely infected partners would not be detected by HT (i.e., HT would return a non-reactive result) and condoms will definitely not be used. In practice, other factors may decrease the risk of transmission: MSM may choose not to have sex after all, condoms may be used even with a non-reactive HT result, the kit may return a reactive result before the end of the 3-month acute stage, etc. Lastly, we assumed constant HT-use with all partners. More realistic estimates could be made by varying HT-use consistency. Future research examining differing condom and HT use patterns would be useful.
Despite these limitations, our results provide important insights about the potential benefits of using HT to screen partners for low condom-users. Although consistent condom use can substantially reduce the probability of HIV infection, many individuals choose not to use condoms for various reasons (Carballo-Dieguez and Bauermeister 2004; Bauermeister et al. 2009), and consistent condom use seems to be an unattainable ideal for some MSM. As technological developments become available, the question of how people will use them becomes very important. In this study, we have provided evidence that there is likely to be some advantage to employing a soon-to-be made available technology for individuals who choose to forego condom use in risky circumstances. Without careful study, individuals at the forefront of the battle with HIV may promote various strategies that are not at all beneficial and may in fact be harmful, as studies on Nonoxynol-9 have shown (Carballo-Dieguez et al. 2007; Gayle 2000; Gross et al. 1998; Phillips and Zacharopoulos 1998; Stephenson 2000).
Alternative strategies to reduce the risk of HIV infection need to be studied to know how reasonable and effective a method may be for individuals who choose not to use condoms. Recent studies have begun to examine serosorting and its impact on HIV transmission more carefully (Eaton et al. 2007; Golden et al. 2008; Pinkerton 2008). In the case of HT-use to screen partners, a great deal of work and attention is necessary, particularly for projecting use-effectiveness of HT (varying levels of use) and with different combinations of both HT and condom use to mimic more realistic circumstances. Similarly, considering sexual behavior by partner type would allow better informed strategies about when and who to screen. Of particular concern would be individuals who "migrate" from using condoms consistently to relying on HT-use, as Foss et al. (2003) have explored in their work on shifts in condom use after the introduction of microbicides.
There are clearly a number of issues that affect potential users differently (How? Where? When? With whom?). As Varghese et al. (2002) have noted, all sex acts have some level of risk for HIV, and prevention efforts could benefit from estimates of the magnitude of risk reduction derived from various choices, in order to be able to provide more accurate information on sexual decisions that can effectively reduce individuals' risk. Our inquiry maintained the exploration in the realm of the hypothetical rather than taking it a step further to conduct a systematic exploration on possible uses of HT with various types of partners and actual experimentation of HT-use with partners. This should be the next step in integrating biomedical and behavioral research to inform HIV prevention programs (Rosengarten et al. 2008).
Acknowledgments We would like to thank the reviewer of this manuscript for providing invaluable recommendations for the mathematical model used in this study. We would also like to thank Christopher S. Murrill and Lucia V. Torian at the New York City Department of Health and Mental Hygiene, and Denis Nash at Columbia University's Mailman School of Public Health for providing estimates of HIV incidence among MSM. The study, Internet Use and HIV Risk among Men in New York City (Frontiers in Prevention), was supported by a grant from NIMH (R01 MH69333, Principal Investigator: Alex Carballo-Dieguez, Ph.D.). This research was also supported by a center grant from the National Institute of Mental Health to the HIV Center for Clinical and Behavioral Studies at NY State Psychiatric Institute and Columbia University (P30-MH43520; Principal Investigator: Anke A. Ehrhardt, Ph.D.). The content is solely the responsibility of the authors and does not necessarily represent the official views of NIMH or the NIH.
Methods excerpted
We computed probabilities of becoming HIV infected based on various assumptions about model parameters to identify the point at which HT use to screen partners presents an increase in risk, particularly since antibodies are not likely to be detected by HT during the first 3 months of infection, relative to the protection provided by different levels of condom use (proportion of anal intercourse [AI] occasions that are protected with a condom). Similar models have been used to estimate infection risks based on different patterns of sexual behavior (Pinkerton and Abramson 1993) and combinations of condom and microbicide use (Foss et al. 2003), as well as to model the effect of HAART on infectiousness (Blower et al. 2000; Law et al. 2001). The model is static, in that it provides probabilities over a fixed period of time and assumes fixed infectivity, prevalence and incidence rates. Although we recognize the importance of calculating the risk of ever being infected over a lifespan, as suggested by Pinkerton and Abramson (1993), in this model we consider a 1 year span for the sake of clarity. We assume statistical independence among the parameters (i.e., risk of HIV transmission is the same irrespective of the sexual occasion, whether it is the first or hundredth with an infected person; becoming infected from one partner is independent from becoming infected from other partners; Pinkerton and Abramson 1993; Foss et al. 2003). Parameter estimates were identified through data resulting from Frontiers in Prevention (FIP), a study conducted in New York City with MSM who reported using condoms inconsistently or not at all (see Carballo-Dieguez et al. 2006; and Ventuneac et al. 2009 for a description of the study and sample), and a literature search using MEDLINE with the search terms "HIV incidence" and "HIV prevalence," and narrowing results to "MSM" and "NYC epidemiology" (national studies were reviewed for NYC data) from 1998 to July of 2008. We also contacted the New York City Department of Health and Mental Hygiene for data on inconsistent condom users.
We defined the parameters used in the equations and how we obtained their estimates as follows. Let ∏ be the probability that a sexual partner is HIV infected. We varied ∏ to be 8.4, 12.1, 14, 18, and 20%, based on HIV prevalence estimates among MSM in NYC ranging from 8.4 to 18% (Catania et al. 2001; Centers for Disease Control and Prevention 2001, 2005; Koblin et al. 2000; Manning et al. 2000; McQuillan et al. 2006; Torian et al. 2002; Valleroy et al. 2000). Let σ be the probability that a sexual partner is in the acute infection stage. We used estimates of HIV incidence in NYC of 2.5% (2,500 per 100,000 person-years of follow up [p-y]; Nash et al. 2005), 5.5% (5,500/100,000 p-y; preliminarily estimated among MSM who used condoms inconsistently from the National HIV Behavioral Surveillance data; personal communication with Christopher S. Murrill at New York City Department of Health, December 15, 2005), and 7.6% (7,600/100,000 p-y; Centers for Disease Control and Prevention 2001) and divided these by 4∏ (which we varied as stated above) to reflect that the acute stage lasts typically 3 months (Ahlgren et al. 1990; Jacquez et al. 1994; Pilcher et al. 2005; Rapatski et al. 2005; Wawer et al. 2005). Let α be the probability of infection per contact (sex occasion) during the primary/acute infection, and let ß be the probability of infection during the chronic asymptomatic stage. In our model, we estimated α and ß to be .024 and .002 respectively, based on estimates of infectivity per contact in gay men previously used by Rapatski et al. (2005). Their stage ratios are similar to stage ratios of estimates found by Wawer et al. (2005; actual stage infectivities for vaginal intercourse were lower).
Results
Table 1 lists the probabilities of HIV infection for HT-use to screen sexual partners versus varying levels of condom use by various HIV prevalence and incidence estimates, while factoring in infectiousness. The results of our calculations show that the effectiveness of HT-use as a strategy in reducing one's risk of becoming HIV infected largely depends on prevalence and incidence of HIV in the population. The relative advantage of HT-use as a risk reduction strategy in comparison to no condom use is greater with higher prevalence. With lower prevalence (8.4%) and factoring in incidence of 2.5%, the probability of infection is ~8% lower under the HT condition versus no condom use (.103 vs. .180, respectively). The difference doubles (17.6%) with a prevalence of 20% (.128 for HT vs. .304 for no condom use, with 2.5% incidence factored in). This is mainly attributable to a device's ability to accurately detect antibodies to HIV after antibody seroconversion (Busch et al. 2003).
When condom use is inconsistent, HT-use provides some advantage (i.e., lower risk of HIV infection); however, underlying HIV prevalence and incidence rates determine the point at which such advantage is present. Under the 8.4% prevalence and 2.5% incidence condition, the point at which there is greater risk of becoming infected occurs for HT-use when condoms are used on half of occasions, meaning men would have lower chances of becoming HIV infected, if they used condoms on half or more of AI occasions than if they used HT to screen their partners before AI. HT-use would be advantageous to men who use condoms on less than half of AI occasions they engage in. With prevalence of 20%, increased risk occurs for HT-use only when condoms are used on 68% or more of occasions. In other words, the advantage of HT-use increases with higher prevalence in the population.
However, the relative advantage of HT-use compared to inconsistent condom use as a risk reduction strategy decreases with higher incidence in the population. This is attributable to the "window period" with its high infectiousness (Ahlgren et al. 1990; Jacquez et al. 1994; Pilcher et al. 2005; Rapatski et al. 2005; Wawer et al. 2005). In our calculations, the relative advantage of HT is lowest with high incidence and low prevalence populations, but still present over no condom use. With 7.6% incidence and 8.4% prevalence, there is a 5.4% lower probability of HIV infection for the HT condition versus no condom use. With 20% prevalence, the difference is 14%. The point at which there is greater risk of becoming infected under the HT-use condition occurs when condoms are used on a quarter of occasions for populations with high HIV incidence, highlighting the effectiveness of condom use in preventing HIV.
Although our calculations illustrate that, depending on HIV prevalence and incidence, HT-use could be beneficial for MSM who engage in unprotected AI, it is important to point out that we assumed consistent use of HT. This point must be stressed because realistic estimates need to be made about possible factors that can impact consistent HT-use with partners, including cost, availability, convenience, and partner characteristics. Further insights could be gained by calculating probabilities for different levels of HT-use.
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Commentary
Use of a Rapid HIV Home Test to Screen Sexual Partners: A Commentary on Ventuneac, Carballo-Dieguez, Leu et al. 2009
Cheng-Shiun Leu1, 2 , Ana Ventuneac3, Bruce Levin1, 2 and Alex Carballo-Dieguez1
(1) HIV Center for Clinical and Behavioral Studies, New York State Psychiatric Institute and Columbia University, 1051 Riverside Drive, Unit 15, New York, NY 10032, USA
(2) Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, USA
(3) Center for HIV Educational Studies and Training (CHEST), Hunter College of the City University of New York (CUNY), New York, USA
Abstract
Previously, we estimated the HIV risk reduction that men who have sex with men could attain using a rapid HIV home test to screen sexual partners versus using condoms inconsistently. Here, we clarify the assumptions of our published formulas. Using models that more closely resemble our study population, our results show a difference from that presented in the original article in the magnitude of the relative advantage (i.e., lower risk of HIV infection) for HIV home test use versus inconsistent condom use. We present a general formula that can accommodate different types of partnerships in estimating risk of HIV infection.
Resumen
Calculamos previamente la reduccion en riesgo de transmision de VIH que los hombres que tienen sexo con hombres podrian obtener usando un test rApido de VIH en la casa para selccionar parejas sexuales en vez de usar condones irregularmente. Aqui aclaramos las presuposiciones de las formulas publicadas. Usando modelos que se asemejan mejor a nuestra poblacion clave, nuestros resultados demuestran una diferencia con los presentados en el articulo original en cuanto a la magnitud de la ventaja relativa (es decir, menor riesgo de infeccion con VIH) en caso del uso del test de VIH en la casa comparado con el uso irregular de condones. Presentamos una formula general que puede utilizarse con differentes tipos de parejas al calcular el riesgo de infeccion con VIH.
In our article, "Use of a Rapid HIV Home Test to Screen Sexual Partners: An evaluation of Its Possible Use and Relative Risk" by Ventuneac, Carballo-Dieguez, Leu et al. published in AIDS Behavior [1], we provided formulas for calculating the probability of HIV transmission to facilitate a comparison of the public health risks and benefits of use of a rapid HIV home test to screen sexual partners among men who have sex with men (MSM). The formulas express the transmission probability as a function of an assumed number of partners per year and number of occasions of anal intercourse per partner per year, among other parameters, and build on the model used by Pinkerton and Abramson [2]. The two key parameters-m, the number of distinct partners per year, and n, the number of anal intercourse occasions per partner per year-require careful attention to assumptions related to partnerships types when they are estimated from samples of respondents asked about their sex behavior over a preceding period of less than 1 year. Indeed, the reported values of m and n from our own sample of men asked about their behavior for the preceding 2 months may not accurately reflect the actual behavior of our study population because the assumptions we tacitly used when estimating m and n were mutually inconsistent. The purpose of this commentary is to clarify these assumptions for the correct use of the published formulas and to present an even more general formula that can accommodate different types of partner relationships.
The expression we gave for the probability of HIV transmission if home test (HT) screening is used to screen partners iswhereas, if HT is not used to screen partners, the probability of HIV transmission is
see pdf attached
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In the above formulas, ∏ is the probability that a sexual partner is HIV infected; σ is the conditional probability that a sexual partner is in the acute infection stage given that the partner is infected; α is the probability of infection per contact (anal sex occasion) during the primary/acute infection; ß is the probability of infection during the chronic asymptomatic stage; μHT is the condom use effectiveness if HT is used (defined as the probability that an individual is protected by condom use with a positive partner in the non-acute stage, per contact after HT use, assuming that HT use is consistent with all partners); μc is the condom use effectiveness if HT is not used; and, as stated above, m is the number of partners per year and n is the number of occasions per partner per year.
In our discussion the quantity n was assumed to be the same for all partners and chosen at a value intended to represent a typical characteristic of the study population. To determine m and n, we used data from the Frontiers in prevention (FIP) study [3, 4], conducted in New York city with MSM who reported using condoms inconsistently or not at all. Among MSM who reported being HIV-negative, the median number of partners per respondent in the 2 months preceding their interview was seven and the corresponding median total number of anal intercourse occasions per respondent was ten. From these observations we annualized the observed median number of partners, setting m = 7 x 6 = 42. We also annualized the number of occasions per partner per month, 10/7 = 1.43, setting n = 1.43 x 12 = 17. Though the annualization of both quantities might seem reasonable on its face, the resulting scenario, m = 42, n = 17, while certainly representing a highly sexually active population, no doubt overestimated the actual risk behavior of the FIP study population.
To see why, consider two extreme cases. Let case 1 represent a "one-night stand" model, where each respondent would have different partners each and every month. Thus if men reported having seven partners in a 2 month period, the model assumption implies there would be a total of m = 7 x 6 = 42 distinct partners per year. In that case, if men reported having anal intercourse on ten occasions in the 2 month period, the assumption implies that they would have only these ten occasions with those seven partners but no more with those same partners, so the number of occasions per distinct partner per year would be n = 10/7 = 1.43. Equivalently, one could reason that there would be 10 x 6 = 60 occasions in total for the year deriving from 42 partners, so that n = 60/42 = 1.43.
At the other extreme, let case 2 represent a "multiple long-term buddy" model with m stable partnerships for the entire year. With reports of seven partners for the 2 month reporting period, the model assumption now implies there would only ever be those seven distinct partners, i.e., m = 7. But then we must assume each of those partners will continue providing occasions over the entire year, so there will be (10/7) x 6 or n = 60/7 = 8.57 occasions per partner per year. Equivalently, one could reason directly that there would be 60 occasions in total for the year provided by the same seven partners, so n = 60/7 = 8.57.
Notice that in either model, we should have assumed only 60 total occasions per year rather than 42 x 17 = 714 total occasions per year, which represents a much riskier scenario. In general, actual populations could be expected to behave somewhere in between the one-night stand model and the multiple long-term buddy model. If one knows or is willing to assume the total number of occasions over the entire year for each partner, irrespective of how long the partnership lasts, a more general formula can be used to estimate the risk. Let n i denote the number of occasions for partner i = 1, m. Thenif HT is used to screen partners, and
see attached pdf
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if HT is not used to screen partners. These expressions will lie in between the simpler expressions given above where, in general, one should determine the total number of occasions per respondent per year, say N, and then set n = N/m, where, m should be determined carefully according to partnership type.
Table 1 below compares the probability of HIV transmission under the three scenarios just presented. The results show a difference in the magnitude of the relative advantage (i.e., lower risk of HIV infection) under the HT condition versus inconsistent condom use between the probabilities of becoming HIV infected originally presented (Case 0) and the two cases that more closely resemble the FIP study population (Cases 1 and 2). With lower prevalence (8.4%) and factoring in incidence of 2.5%, for example, the probability of infection was reported to be about 8% lower under the HT condition versus no condom use (0.103 vs. 0.180, respectively). Under the assumptions presented for the two cases, the probability of infection is only .7% lower under the HT condition versus no condom use (Case 1: 0.011 vs. 0.018, respectively; Case 2: 0.010 vs. 0.017, respectively). With HIV prevalence of 20% and incidence of 2.5% for the two cases, the probability of infection is 1.9% lower under the HT condition versus no condom use. The relative advantage of HT use as a strategy in reducing one's risk of becoming HIV infected as compared to inconsistent condom use depends heavily on the total number of occasions per respondent per year (N = mn), but only weakly on the particular values of m and n with fixed product. To a lesser extent, the relative advantage depends on the prevalence of HIV in the population, as reported previously, but less so on the incidence rate of HIV.
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