Abstract:
Stigma toward people living with HIV/AIDS (PLWHA) has impeded the response
to the disease across the world. Widespread stigma leads to poor adherence of preventative measures while also causing PLWHA to avoid testing and care, delaying
important treatment. Stigma is clearly a hugely complex construct. However, it can
be broken down into components which include internalized stigma (how people with
the trait feel about themselves) and enacted stigma (how a community reacts to an
individual with the trait). Levels of HIV/AIDS-related stigma are particularly high in
sub-Saharan Africa, which contributed to a surge in cases in Kenya during the late
twentieth century. Since the early twenty-first century, the United Nations and governments around the world have worked to eliminate stigma from society and resulting
public health education campaigns have improved the perception of PLWHA over
time, but HIV/AIDS remains a significant problem, particularly in Kenya. We take a
data-driven approach to create a time-dependent stigma function that captures both the level of internalized and enacted stigma in the population. We embed this within
a compartmental model for HIV dynamics. Since 2000, the population in Kenya has
been growing almost exponentially and so we rescale our model system to create a
coupled system for HIV prevalence and fraction of individuals that are infected that
seek treatment. This allows us to estimate model parameters from published data. We
use the model to explore a range of scenarios in which either internalized or enacted
stigma levels vary from those predicted by the data. This analysis allows us to understand the potential impact of different public health interventions on key HIV metrics
such as prevalence and disease-related death and to see how close Kenya will get to
achieving UN goals for these HIV and stigma metrics by 2030.
