Skip to content
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Menu
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Menu
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
Validation and calibration of a computer simulation model of pediatric HIV infection
PLoS ONE, Volume 8, No. 12, Article e83389, Year 2013
Notification
URL copied to clipboard!
Description
Background: Computer simulation models can project long-term patient outcomes and inform health policy. We internally validated and then calibrated a model of HIV disease in children before initiation of antiretroviral therapy to provide a framework against which to compare the impact of pediatric HIV treatment strategies. Methods: We developed a patient-level (Monte Carlo) model of HIV progression among untreated children <5 years of age, using the Cost-Effectiveness of Preventing AIDS Complications model framework: the CEPAC-Pediatric model. We populated the model with data on opportunistic infection and mortality risks from the International Epidemiologic Database to Evaluate AIDS (IeDEA), with mean CD4% at birth (42%) and mean CD4% decline (1.4%/ month) from the Women and Infants' Transmission Study (WITS). We internally validated the model by varying WITS-derived CD4% data, comparing the corresponding model-generated survival curves to empirical survival curves from IeDEA, and identifying best-fitting parameter sets as those with a root-mean square error (RMSE) <0.01. We then calibrated the model to other African settings by systematically varying immunologic and HIV mortality-related input parameters. Model-generated survival curves for children aged 0-60 months were compared, again using RMSE, to UNAIDS data from >1,300 untreated, HIV-infected African children. Results: In internal validation analyses, model-generated survival curves fit IeDEA data well; modeled and observed survival at 16 months of age were 91.2% and 91.1%, respectively. RMSE varied widely with variations in CD4% parameters; the best fitting parameter set (RMSE = 0.00423) resulted when CD4% was 45% at birth and declined by 6%/month (ages 0-3 months) and 0.3%/month (ages >3 months). In calibration analyses, increases in IeDEA-derived mortality risks were necessary to fit UNAIDS survival data. Conclusions: The CEPAC-Pediatric model performed well in internal validation analyses. Increases in modeled mortality risks required to match UNAIDS data highlight the importance of pre-enrollment mortality in many pediatric cohort studies. © 2013 Ciaranello et al.
Authors & Co-Authors
Ciaranello, Andrea L.
United States, Boston
Massachusetts General Hospital
United States, Boston
Brigham and Women's Hospital
Morris, Bethany L.
United States, Boston
Massachusetts General Hospital
Walensky, Rochelle P.
United States, Boston
Massachusetts General Hospital
United States, Boston
Brigham and Women's Hospital
United States, Cambridge
Harvard University
Weinstein, Milton C.
United States, Boston
Harvard T.h. Chan School of Public Health
Ayaya, Samuel Omulando
Kenya, Eldoret
Moi University
Doherty, Kathleen E.
United States, Boston
Massachusetts General Hospital
Leroy, Valeriane
France, Paris
Inserm
Hou, Taige
United States, Boston
Massachusetts General Hospital
Desmonde, Sophie
France, Paris
Inserm
Lu, Zhigang
United States, Boston
Massachusetts General Hospital
Noubary, Farzad
United States, Boston
Massachusetts General Hospital
Patel, Kunjal
United States, Boston
Harvard T.h. Chan School of Public Health
Ramirez-Avila, Lynn
United States, Boston
Massachusetts General Hospital
United States, Boston
Boston Children's Hospital
United States, Los Angeles
University of California, Los Angeles
Losina, Elena
United States, Boston
Massachusetts General Hospital
United States, Boston
Brigham and Women's Hospital
United States, Cambridge
Harvard University
United States, Boston
School of Public Health
Seage, George R.
United States, Boston
Harvard T.h. Chan School of Public Health
Freedberg, Kenneth A.
United States, Boston
Massachusetts General Hospital
United States, Cambridge
Harvard University
United States, Boston
Harvard T.h. Chan School of Public Health
United States, Boston
School of Public Health
Statistics
Citations: 16
Authors: 16
Affiliations: 9
Identifiers
Doi:
10.1371/journal.pone.0083389
e-ISSN:
19326203
Research Areas
Health System And Policy
Infectious Diseases
Maternal And Child Health
Study Design
Cohort Study
Participants Gender
Female