The HIV pandemic, especially the devastating epidemics in sub-Saharan Africa (SSA) and the subsequent recent rapid declines in prevalence/incidence in several countries, has raised many questions. Among these are (i) why major HIV epidemics appear to have occurred only in SSA and (ii) to what extent are these marked declines in HIV transmission attributable to sexual behavior changes? Both questions have generated intense debates, often focusing on aspects of sexual behaviour; for example, whether the difference between SSA and the rest of the world can be explained by the higher levels of concurrency, that is having multiple sex partners simultaneously .
Definitive answers to these questions require accurate data on sexual behaviour. However, although impressive amounts of data on sexual behaviour have been collected, they all tend to be self-reported . The sensitive nature of sexual behaviour, and nonrandom social desirability and recall biases, can introduce inaccuracy in these data [3–6]. Several studies have also shown that such data can be unreliable; biomarker studies have shown underreporting of recent unprotected intercourse by women [7,8].
Self-reported data should therefore preferably neither be dependent upon comparing differences in behaviour between populations nor on monitoring changes in behaviour over time to evaluate the impact of behavioural interventions. Nonetheless, such self-reported data are still widely collected and analysed. We believe that there should be more emphasis on developing biomarkers that can reliably detect differences and trends in behaviour patterns. Recently, viral genetic linkage has been used to distinguish transmission within discordant couples from transmission from outside partners. Its finding, that a large fraction of infections acquired from outside the partnership occurred in individuals who reported no extra-marital sex, has provided insight into the ongoing HIV epidemic and how misleading reliance on self-reported data may be .
Yet, as a measure of sexual behaviour in the population, this biomarker is not appropriate. It is complex to carry out and interpret and is restricted to HIV-affected couples. An easier type of biomarker, one that seems never to have been carried out in SSA, is nonpaternity , the percentage of children whose biological father differs from the official or presumed father, usually the husband or regular male partner of the mother.
In addition to providing a direct biomarker of extra-marital sex, nonpaternity can capture not only current behaviour but also past trends. With adequately powered studies, it is possible to derive a time-series of the rate of extra-marital sex from the nonpaternity age-stratified prevalence, and accordingly trends in sexual risk behaviour over decades, including the decades that witnessed the rise of the HIV epidemic. Although nonpaternity probes sexual behaviour only in women, the main challenges in self-reported data relate to women's sexual behaviour . Although multiple mating in human males is believed to be well characterized, the nature of multiple mating in human females is subject to intense debate and conflicting evidence . Nonpaternity studies may provide insights about female sexuality that are of relevance not only for the epidemiology of sexually transmitted infections, but well beyond in fields as far as evolutionary anthropology .
Admittedly, limitations may affect the interpretation of nonpaternity data. Birth control methods and fertility differentials may introduce bias. Nonpaternity could be also due to covert adoptions, misidentified stepchildren or sperm donations [10,13]. There are also complex ethical challenges in the conduct of such studies.
Despite these caveats, some limitations can be overcome, and others may be an issue in some settings but not others. These limitations may not also hinder the ability of nonpaternity studies to provide at least a lower-bound estimate for extra-marital sex, which is in its own of greatest interest. Nonpaternity studies could be conducted as secondary data analyses on already collected samples for other studies or routine data, or ideally could be nested, with appropriate ethical prudence, within broader population-based surveys such as the Demographic and Health Surveys.
In sum, nonpaternity studies can provide a trove of data on sexual behaviour and trends that are not prone to the extensive limitations of self-reported data. The potential for enhancing our knowledge with such data is immense. Not only they can facilitate a better understanding of HIV epidemics and their evolution, but also provide critical data to inform concept and design of interventions. This in turn would help optimize the impact of programmes by better targeting the drivers of HIV transmission.
This publication was made possible by NPRP grant number 5-752-3-177 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.
Conflicts of interest
There are no conflicts of interest.
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