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Far from MCAR: obtaining population-level estimates of HIV viral suppression

Far from MCAR: obtaining population-level estimates of HIV viral suppression

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dc.contributor.author Laura B. Balzer
dc.contributor.author James Ayieko
dc.contributor.author Dalsone Kwarisiima
dc.contributor.author Gabriel Chamie
dc.contributor.author Edwin D. Charlebois
dc.contributor.author Joshua Schwab
dc.contributor.author Mark J. van der Laan
dc.contributor.author Moses R. Kamya
dc.contributor.author Diane V. Havlir
dc.contributor.author Maya L. Petersen
dc.date.accessioned 2021-01-11T13:51:39Z
dc.date.available 2021-01-11T13:51:39Z
dc.date.issued 2019
dc.identifier.uri https://combine.alvar.ug/handle/1/49411
dc.description.abstract ABSTRACT Background Population-level estimates of disease prevalence and control are needed to assess the effectiveness of prevention and treatment strategies. However, available data are often subject to differential missingness. Consider population-level HIV viral suppression: proportion of all HIV-positive persons who are suppressing viral replication. Individuals with measured HIV status, and, among HIV-positive individuals, those with measured viral suppression are likely to differ from those without such measurements. Methods We discuss three sets of assumptions sufficient to identify population-level suppression over time in the intervention arm of the SEARCH Study (NCT01864603), a community randomized trial in rural Kenya and Uganda (2013-2017). Using data on nearly 100,000 participants, we compare estimates from an unadjusted approach assuming data are missing-completely-at-random (MCAR); stratification on age group, sex, and community; and, targeted maximum likelihood estimation (TMLE) with Super Learner to adjust for baseline and time-updated predictors of measurement. Results Despite high annual coverage of testing, estimates of population-level viral suppression varied by identification assumption. Unadjusted estimates were most optimistic: 50% of HIV-positive persons suppressed at baseline, 80% at Year 1, 85% at Year 2, and 85% at Year 3. Stratification on baseline predictors yielded slightly lower estimates, and full adjustment reduced estimates further: 42% of HIV-positive persons suppressed at baseline, 71% at Year 1, 76% at Year 2, and 79% at Year 3. Conclusions Estimation of population-level disease burden and treatment coverage require appropriate adjustment for missingness. Even in “Big Data” settings, estimates relying on the MCAR assumption or baseline stratification should be interpreted with caution.
dc.publisher Cold Spring Harbor Laboratory
dc.title Far from MCAR: obtaining population-level estimates of HIV viral suppression
dc.type Preprint
dc.identifier.doi 10.1101/19012781
dc.identifier.mag 3000030162
dc.identifier.lens 009-468-142-503-908
dc.identifier.spage 19012781
dc.subject.lens-fields Demography
dc.subject.lens-fields Randomized controlled trial
dc.subject.lens-fields Prevalence
dc.subject.lens-fields Disease burden
dc.subject.lens-fields Human immunodeficiency virus (HIV)
dc.subject.lens-fields Viral suppression
dc.subject.lens-fields Population level
dc.subject.lens-fields Maximum likelihood
dc.subject.lens-fields Medicine
dc.subject.lens-fields Missing data


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