Estimation of time of HIV seroconversion using a modified CD4 depletion model

Area of Science:

• Epidemiology
• Biostatistics
• Immunology

Background:

• Estimating time since HIV seroconversion is vital for understanding HIV progression and treatment.
• Previous CD4 cell depletion models overlooked population heterogeneity in CD4 trajectories.
• Accurate seroconversion time estimation is essential for public health interventions and cohort analysis.

Purpose of the Study:

• To estimate the time from HIV seroconversion to HIV diagnosis date.
• To develop a methodology that accounts for heterogeneity in CD4 cell count trajectories.
• To analyze a population-based cohort of people living with HIV (PLWH) in British Columbia, Canada.

Main Methods:

• Utilized linked administrative and clinical data from the British Columbia STOP HIV/AIDS cohort.
• Employed non-linear mixed effects models for longitudinal CD4 cell count data, modeling time with an exponential decay function.
• Stratified models by age and HIV stage at diagnosis, incorporating viral load and assuming a normal CD4 range of 500-1500 cells/mm³.

Main Results:

• Analyzed data from 1,253 people living with HIV (PLWH).
• Observed faster CD4 decline in individuals aged ≥50 years at diagnosis in Stages 1 and 2 of infection.
• Determined a median infection duration of 6.9 years from seroconversion to HIV diagnosis.

Conclusions:

• Presented a novel methodology for estimating HIV seroconversion time that incorporates individual CD4 trajectory heterogeneity.
• The method relies on routinely collected HIV-related data, enhancing its applicability.
• This approach can be extended to estimate other crucial HIV epidemic measures.