Verbal autopsy (VA) has become a widely established approach for characterizing cause of death patterns in settings where individual deaths are not routinely certified as to cause, with a variety of methods being used for both interview and interpretation phases . Most often, VA has been applied for particular times, or over relatively short periods, to obtain point estimates of cause-specific mortality. However, as archives of VA data accumulate over time, possibilities of studying epidemic dynamics using VA approaches emerge. This is of interest in terms of measuring potential newly emerging causes of death , as well as for monitoring the dynamics of epidemiological transition . But it also raises new methodological challenges, for example around consistent interpretation of VA into causes of death over long periods of time and consequently around practitioners' developing perceptions of new situations. More generally, it raises the question of how effectively VA methods are able to detect newly emerging causes of death.
Over the past two decades, southern Africa has experienced a massive and rapidly developing epidemic of HIV infection and associated mortality [[4–6]]. However, large-scale modeled estimates provide a rather imperfect picture of the epidemic, given that most deaths in southern Africa are neither certified nor medically investigated . Localized populations with intensive surveillance, such as member centers of the INDEPTH Network , provide opportunities to look at specific examples in detail [[9–11]], even if this may generate a subsequent debate as to generalizability. A number of studies elsewhere have established the validity of VA methods for attributing deaths to HIV/AIDS, particularly among adults [[12–16]]. Nevertheless, there remain some unresolved issues about how to best handle co-causes of mortality in cases of HIV-related death, and willingness to attribute deaths to HIV, whatever methods are used, may be influenced by nonmedical factors such as social stigmatization [17, 18].
HIV-related deaths are complex to count, since HIV-positive individuals are frequently affected by other diseases as a result of being immunologically compromised, and it can be difficult from VA data, in the absence of HIV serology, to determine the relative significance of AIDS versus other diseases in the processes leading to death. The 10th version of the International Classification of Diseases (ICD-10) uses codes B20 to B24 as underlying causes representing HIV/AIDS in combination with other disease categories (B20 infectious and parasitic diseases, B21 malignant neoplasms, B22 other diseases including wasting, B23 other conditions, and B24 nonspecific AIDS) . However, differentiating probable HIV-related deaths detected by VA into these subcategories may not be easy to achieve, particularly where there is no explicit evidence of HIV positivity.
The ability to interpret any VA interview reliably depends on several factors, including the quality and detail of information on signs and symptoms provided by the informant. In settings where stigma is high around a particular cause of death - as is often the case for HIV - sensitive information may be withheld from the interviewer. Extent of nondisclosure is likely to vary as an epidemic develops, starting from minimal levels when key symptoms are not yet widely known by informants, and when physicians may also not yet be attuned to a particular diagnosis. As a significant epidemic such as HIV/AIDS develops, stigma is likely to rise, together with nondisclosure of relevant details. In a mature epidemic - particularly in the case of HIV as antiretroviral treatments are rolled out - nondisclosure may wane. These patterns may have significant effects on the outcomes of VA interpretation.
The Agincourt Health and Socio-Demographic Surveillance Site in the rural northeast of South Africa has been documenting a geographically-defined population (around 70,000 people in 2005) since 1992, including registering deaths and following those up with VA interviews . The start of this surveillance in 1992 coincided with the early stages of the HIV epidemic (at least in terms of HIV-related mortality) in this area, and hence the accumulated VA data enable a methodological exploration as to how the epidemic evolved. Our primary aim is to characterize the epidemic of HIV-related mortality in this population, comparing both physician-interpreted causes of death and probabilistically modeled causes of death from the same VA interview material. As subsidiary aims, we investigate (1) approaches for handling common co-causes of HIV-related mortality, such as tuberculosis, malnutrition, and chronic gastroenteritis, and (2) variations between different coding physicians' responses to the emerging epidemic. Although this paper deals specifically with an epidemic of HIV-related mortality, findings are discussed in terms of using VA for monitoring long-term dynamics in mortality patterns.