Rethinking the population attributable fraction for infectious diseases
Authors: Sharmistha Mishra, Stefan D Baral
Journal: The Lancet Infectious Diseases (2019)

The population attributable fraction (PAF) is commonly used in public health to signal the contribution, or importance, of a risk factor to a health outcome. The PAF poses the counterfactual:1Levin ML The occurrence of lung cancer in man.Acta Unio Int Contra Cancrum. 1953; 9: 531-541PubMed Google Scholar what would happen if the considered risk factor was entirely absent from the population? In The Lancet Infectious Diseases, Katharine Looker and colleagues2Looker KJ Welton NJ Sabin KM et al.Global and regional estimates of the contribution of herpes simplex virus type 2 infection to HIV incidence: a population attributable fraction analysis using published epidemiological data.Lancet Infect Dis. 2019; (published online Nov 18)https://doi.org/10.1016/S1473-3099(19)30470-0Summary Full Text Full Text PDF PubMed Scopus (48) Google Scholar estimated that globally, in 2016, 29·6% (95% uncertainty interval 22·9–37·1) of new HIV infections acquired via sexual transmission were attributable to herpes simplex virus type 2 (HSV-2) infection. To examine the public health relevance of these findings, a key limitation of the classic PAF must first be considered, as noted by Looker and colleagues.2Looker KJ Welton NJ Sabin KM et al.Global and regional estimates of the contribution of herpes simplex virus type 2 infection to HIV incidence: a population attributable fraction analysis using published epidemiological data.Lancet Infect Dis. 2019; (published online Nov 18)https://doi.org/10.1016/S1473-3099(19)30470-0Summary Full Text Full Text PDF PubMed Scopus (48) Google Scholar To estimate the classic PAF from observational data, the relative risk of a given exposure for the health outcome is multiplied by the prevalence of the risk factor in the entire population (appendix).3Hanley JA A heuristic approach to the formulas for population attributable fraction.J Epidemiol Community Health. 2001; 55: 508-514Crossref PubMed Scopus (195) Google Scholar, 4Rothman KJ Greenland S Lash TL Modern epidemiology.2nd edn. Lippincott Williams and Wilkins, Philadelphia2008Google Scholar Thus, a small relative risk of a high-prevalence risk factor can drive the classic PAF, the public health implication being to prioritise resources to eliminate a small risk among many. For example, in a setting in which 30% of all individuals have risk factors associated with a small relative risk of HIV acquisition (eg, sex without condom with few partners) and 2% have risk factors associated with a large relative risk of HIV acquisition (eg, transactional sex without condom with many partners), the classic PAF would suggest programmes prioritise the larger subset of the population. However, such an approach runs counter to the propagation of infectious diseases, especially HIV and other sexually transmitted infections, as risk factors among the relatively few can sustain even generalised epidemics of these infections.5Yorke JA Hethcote HW Nold A Dynamics and control of the transmission of gonorrhea.Sex Transm Dis. 1978; 5: 51-56Crossref PubMed Scopus (316) Google Scholar, 6Wasserheit JN Aral SO The dynamic topology of sexually transmitted disease epidemics: implications for prevention strategies.J Infect Dis. 1996; 174: S201-S213Crossref PubMed Google Scholar This disconnect derives from the fact that the classic PAF does not consider onward transmission: it is a static measure restricted to acquisition risks and ignores what happens within a sexual or drug-injection network after acquisition. When a risk factor, such as HSV-2 infection, increases susceptibility to HIV infection in one person, it might start a chain of HIV transmission events at the population level—ie, an HSV-2 infection in one person could indirectly, over time, lead to several HIV infections even among individuals without HSV-2. Therefore, the classic PAF probably underestimates the number of HIV infections in the total population that stem directly and indirectly from HSV-2 infection. This bias is largest when HSV-2 leads to HIV acquisition in a small subset of the population with disproportionately higher risks of onward HIV transmission (eg, individuals engaged in sex work whose HIV prevention and treatment needs have not been met) and when a static measure is used to predict long-term effects.7Mishra S Pickles M Blanchard JF Moses S Boily MC Distinguishing sources of HIV transmission from the distribution of newly acquired HIV infections: why is it important for HIV prevention planning?.Sex Transm Infect. 2014; 90: 19-25Crossref PubMed Scopus (24) Google Scholar For example, Looker and colleagues2Looker KJ Welton NJ Sabin KM et al.Global and regional estimates of the contribution of herpes simplex virus type 2 infection to HIV incidence: a population attributable fraction analysis using published epidemiological data.Lancet Infect Dis. 2019; (published online Nov 18)https://doi.org/10.1016/S1473-3099(19)30470-0Summary Full Text Full Text PDF PubMed Scopus (48) Google Scholar found that the contribution of HSV-2 infection to HIV acquisition within key risk populations (female sex workers and men who have sex with men) was lower than the contribution in the general population. But key populations are part of the wider sexual network, and in the long term, the downstream effects on HIV prevention of suppressing or preventing HSV-2 infection in such populations are likely to be larger than those of HSV-2 suppression or prevention in the wider population. To address the limitations of the classic PAF, the transmission PAF (tPAF) can be estimated with mathematical models of onward transmission.7Mishra S Pickles M Blanchard JF Moses S Boily MC Distinguishing sources of HIV transmission from the distribution of newly acquired HIV infections: why is it important for HIV prevention planning?.Sex Transm Infect. 2014; 90: 19-25Crossref PubMed Scopus (24) Google Scholar, 8Mishra S Boily MC Schwartz S et al.Data and methods to characterize the role of sex work and to inform sex work programs in generalized HIV epidemics: evidence to challenge assumptions.Ann Epidemiol. 2016; 26: 557-569Crossref PubMed Scopus (28) Google Scholar As with the classic PAF, the tPAF generated from a transmission model is informed by observed relative risks, but it differentiates risks of onward transmission by simulating the sexual network. With a transmission model, the counterfactual can be simulated explicitly and projections of cumulative incidence with and without the risk factor can be compared (appendix). Consequently, the tPAF of a given risk factor can be interpreted—under the epidemic conditions of the modelled system—as the maximum fraction of infections that could be averted if that risk factor was absent or partially removed.1Levin ML The occurrence of lung cancer in man.Acta Unio Int Contra Cancrum. 1953; 9: 531-541PubMed Google Scholar, 9Morgenstern H Bursic ES A method for using epidemiologic data to estimate the potential impact of an intervention on the health status of a target population.J Community Health. 1982; 7: 292-309Crossref PubMed Scopus (113) Google Scholar Using the tPAF to prioritise resources on the basis of potential long-term gains would have substantial policy and programmatic implications, including more specific strategies focused on comprehensively addressing the needs of the few to prevent infections among the many.7Mishra S Pickles M Blanchard JF Moses S Boily MC Distinguishing sources of HIV transmission from the distribution of newly acquired HIV infections: why is it important for HIV prevention planning?.Sex Transm Infect. 2014; 90: 19-25Crossref PubMed Scopus (24) Google Scholar Ultimately, the findings from Looker and colleagues' study might underestimate the potential, population-level effects on HIV prevention of eliminating HSV-2. The magnitude of the underestimation will depend on the subset of the population prioritised for HSV-2 interventions and the time frame considered for anticipated effects. We declare no competing interests. Download .pdf (.18 MB) Help with pdf files Supplementary appendix Global and regional estimates of the contribution of herpes simplex virus type 2 infection to HIV incidence: a population attributable fraction analysis using published epidemiological dataA large burden of HIV is likely to be attributable to HSV-2 infection, even if the effect of HSV-2 infection on HIV had been imperfectly measured in studies providing adjusted RR estimates, potentially because of residual confounding. The contribution is likely to be greatest in areas where HSV-2 is highly prevalent, particularly Africa. New preventive interventions against HSV-2 infection could not only improve the quality of life of millions of people by reducing the prevalence of herpetic genital ulcer disease, but could also have an additional, indirect effect on HIV transmission. Full-Text PDF Open Access