Performance of a Mathematical Model to Forecast Lives Saved from HIV Treatment Expansion in Resource-Limited Settings

April D. Kimmel, Daniel W. Fitzgerald, Jean W. Pape and Bruce R. Schackman

Medical Decision Making, 2015, vol. 35, issue 2, 230-242

Abstract: Background . International guidelines recommend HIV treatment expansion in resource-limited settings, but funding availability is uncertain. We evaluated the performance of a model that forecasts lives saved through continued HIV treatment expansion in Haiti. Methods . We developed a computer-based, mathematical model of HIV disease and used incidence density analysis of patient-level Haitian data to derive model parameters for HIV disease progression. We assessed the internal validity of model predictions and internally calibrated model inputs when model predictions did not fit the patient-level data. We then derived uncertain model inputs related to diagnosis and linkage to care, pretreatment retention, and enrollment on HIV treatment through an external calibration process that selected input values by comparing model predictions to Haitian population-level data. Model performance was measured by fit to event-free survival (patient level) and number receiving HIV treatment over time (population level). Results . For a cohort of newly HIV-infected individuals with no access to HIV treatment, the model predicts median AIDS-free survival of 9.0 years precalibration and 6.6 years postcalibration v. 5.8 years (95% confidence interval, 5.1–7.0) from the patient-level data. After internal validation and calibration, 16 of 17 event-free survival measures (94%) had a mean percentage deviation between model predictions and the empiric data of

Keywords: HIV/AIDS; antiretroviral therapy; mortality; resource-limited settings; simulation; model performance; calibration; validation (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0272989X14551755 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:35:y:2015:i:2:p:230-242

DOI: 10.1177/0272989X14551755

Access Statistics for this article

More articles in Medical Decision Making
Bibliographic data for series maintained by SAGE Publications ().