The authors are aware of this potential confounder, and develop a measure of admixture based on 11 SNPs to include as a covariate in their regression. However, this measure is kind of weak, which I imagine in the sticking point for the skeptics in the Times article. If you have access to the supplemental information, take a look at it--several of these 11 SNPs are in the same gene, which means they're not independent, and several don't even have big frequency differences between African and European samples (if you're trying to judge via SNPs whether someone is more African or European, those SNPs better have a big frequency difference between Africa and Europe). This is probably not a precise measure of ancestry. In fact, the Duffy null allele they claim as associated is a better predictor of ancestry than any of these SNPs.
So it's quite possible that the authors have simply shown a correlation between level of African ancestry and susceptibility to HIV (which could be due to any number of sociological, demographic, or genetic factors), rather than an association between Duffy null and susceptibility to HIV. Here's a relatively simple test of this possibility: genotype rs1426654 (the nonsynonymous SNP in SLC24A5) in their sample and perform exactly the same test as performed with Duffy. The motivation for this is that this SNP shares the property of Duffy null of being highly informative about ancestry, while being in a gene that presumably plays no role in HIV infection. If you get an association there, it seriously calls the Duffy result into question; if not, you feel a bit more comfortable.
This is why mapping human variation is so important. Note that the genetic variation itself might not even be responsible for greater susceptibility to HIV in a causal sense; if circumcision does have a role in reducing the spread of HIV then cultural practices which correlate with genetic variation can also produce spurious correlations. As an illustrative example in South Africa there is a correlation between HIV infection rates and decreased Khoisan ancestry. I say this because the Zulus have higher infection rates than the Xhosa, and the latter have a great deal more Khoisan ancestry than the former. The differences have been attributed to the fact that the Xhosa practice circumcision and the Zulu do not, so the differences in genes is just coincidental.
And circumcision also correlates with a variety of other cultural practices that impact on HIV transmission. This confounded the earlier studies claiming circumcision prevents HIV. Notably, where circumcised men are Muslim and others are not, they also practise polygamy, ritual cleaning, abstention at the menses, etc. Tribal circumcision as a rite of passage and the idea that an uncircumcised youth is "not a man" may affect the age of onsent of intercourse. Interestingly, the promoters of circumcision have only begun to acknowledge those confounders now they have the (non-blinded, non-placebo controlled) randomised controlled tests (on paid volunteers, of whom many more dropped out, their HIV status unknown, than were known to be infected) which they consider "conclusive". With HIV rates higher among the circumcised men of six countries (Cameroon, Ghana, Lesotho, Malawi, Rwanda, Tanzania) than the non-circumcised, according to the National Health and Demographic Surveys, that claim is still open to debate.
Early on in the AIDS epidemic, I read a paper by French researcher in Africa who found that a particular antigen marker was greatly over-represented in his AIDS patients. (I think by a factor of 5 over the general population of that country.) He also noted that the antigen marker was more frequent in African populations than among Europeans. The study was at least thirty years ago, and I am unable to google up any references to it, but it does point the way to doing this kind of research. If you are looking for "susceptibility genes" and wish to avoid the problem of false positives, first do the search in populations which are as culturally and racially homogeneous as possible. If you find anything, you can later compare gene frequencies between populations--if this is what interests you.