In October my master’s student had her work on modeling HIV interventions in China published in the journal AIDS, with me as second author. You can read the abstract at the journal website, but sadly the article is pay-walled so its full joys are not available to the casual reader. This article is a sophisticated and complex mathematical model of HIV, which incorporates three disease stages, testing and treatment separately. It is based on a model published by Long et al in the Annals of Internal Medicine in 2010, but builds on this model by including the effects of methadone maintenance treatment, and doesn’t include an injecting drug use quality of life weight. It also adds new risk groups to the model: Long et al considered only men who have sex with men (MSM), injecting drug users (IDU) and the general population, but we added commercial sex workers (CSW) and their clients, who we refer to as “high risk men.” Thus our mathematical model can consider the role of both injecting drug users and sex workers as bridging populations between high-risk groups and the general population, an important consideration in China.
The HIV epidemic in China is currently a concentrated epidemic, primarily among IDUs in five provinces, and amongst MSM. The danger of concentrated epidemics is that they give the disease a foothold in a country, and a poor or delayed response may cause the epidemic to jump to the rest of the population – there is some suggestion this may have happened in Russia, for example. The Chinese authorities, recognizing this risk, began expanding methadone maintenance treatment (MMT) in the early 2000s, but it still only covers 5% of the estimated 2,500,000 IDUs in China. Our goal in this paper was to compare the effectiveness of three key interventions to prevent the spread of this disease: expanded voluntary counseling and testing (VCT); expanded antiretroviral treatment (ART); and expanded harm reduction (MMT and needle/syringe programs); and combinations of these interventions. VCT was assumed to reduce risk behavior and expand the pool of individuals who can enter treatment per year; ART was assumed to reduce infectiousness; and harm reduction to reduce risk behavior. Costs were assigned to all of the programs based on available Chinese data, and different scenarios considered (such as testing everyone once a year, or high-risk groups more frequently than everyone else).
The results showed that all the interventions considered are cost-effective relative to doing nothing; that some of the interventions saved more money than they cost; and that the most cost-effective intervention was expanding access to ART. Harm reduction was very close to ART in cost-effectiveness, and would probably be more cost-effective if we incorporated its non-HIV-related effects (reduced mortality and crime). The Chinese government stands to reap a long-term benefit from implementing some of these programs now, through the 3.4 million HIV cases averted if the interventions are successful (there are a lot of “ifs” in that sentence).This is the first paper I’m aware of that compares ART and harm reduction head on for cost-effectiveness, though subsequently some Australians showed in the same journal that needle/syringe programs (NSP) in Australia are highly cost-effective as an anti-HIV intervention. This is also the most comprehensive model of HIV in China to date, and the first to conduct cost-effectiveness analysis in that setting. I think it might be the first paper to consider the detailed structure of risk groups in a concentrated epidemic, as well. There are obvious limitations to the conclusions that one can draw from a mathematical model, and some additional limitations on this model that are specific to China: the data on costs was a bit weak (especially for MMT) and of course there are questions about how feasible some of the interventions would be. We also didn’t consider restricting the interventions to the key affected provinces, which would have made them much cheaper, and we didn’t consider ART or VCT interventions targeted only at the high-risk groups, which would also have been cheaper. For example, legalizing sex work and setting strict licensing laws might enable universal, quarterly HIV testing and lead to the eradication of HIV from this group within 10 years, but we didn’t include this scenario in the model because a) legalization is not going to happen, b) enforcement of licensing laws is highly unlikely to be effective in the current context in China, and c) data on the size and behavior of the CSW population is probably the weakest part of our model, so findings would be unreliable. Despite the general and specific limitations of this kind of modeling in this setting, I think the results are a strong starting point for informing China’s HIV policy. China seems to have a very practical approach towards this kind of issue, so I expect that we’ll see these kinds of policies implemented in the near future. My next goal is to explore the mathematical dynamics of these kinds of models with the aim of answering some of the controversial questions about whether behavioral change is a necessary or effective part of a modern HIV response, and the exact conditions under which we can hope to eliminate or eradicate HIV. Things are looking very hopeful for the future of HIV, i.e. it’s going to be eliminated or contained in most countries within our lifetime even without development of a vaccine, and that’s excellent, but there is still debate about how fast that will happen and the most cost-effective ways of getting there: hopefully the dynamic properties of these models can give some insight into that debate. This article is a big professional achievement for me in another way. It’s extremely rare for master’s students to publish in a journal as prestigious as AIDS (impact factor over 6!), and my student’s achievement is a reflection of her amazing talent at both mathematics and English, and a year of intense work on her part, but I like to think it also is a reflection of my abilities as a supervisor. There were lots of points where we could have let things slide on the assumption that master’s students don’t publish in AIDS; but we didn’t, and she did. I like to think the final product reflects well on both of us, so read it if you get the chance!