4.4 Article

Modeling the Effect of HIV/AIDS Stigma on HIV Infection Dynamics in Kenya

期刊

BULLETIN OF MATHEMATICAL BIOLOGY
卷 83, 期 5, 页码 -

出版社

SPRINGER
DOI: 10.1007/s11538-021-00891-7

关键词

HIV; Stigma; Kenya; Mathematical model; UN goals

资金

  1. National Science Foundation [NSF-DMS-1343651, DBI-1300426]
  2. U.S. National Science Foundation [NSF-DGE-1414475]
  3. National Institute for Mathematical and Biological Synthesis
  4. University of Tennessee, Knoxville
  5. Fitchburg State University
  6. LMS Scheme 5 grants [51607, 51710]
  7. International Research Initiator Scheme at University of Bath

向作者/读者索取更多资源

Stigma towards people living with HIV/AIDS has hindered global response to the disease, with internalized and enacted stigma being key components. Particularly high in sub-Saharan Africa, stigma has contributed to a surge in cases in countries like Kenya. Efforts to eliminate stigma have improved perceptions over time, but HIV/AIDS remains a significant problem, prompting analysis of different interventions and goals for the future.
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.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.4
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据