Monitoring Linked Epidemics: The Case of Tuberculosis and HIV

Abstract

BackgroundThe tight epidemiological coupling between HIV and its associated opportunistic infections leads to challenges and opportunities for disease surveillance.Methodology/Principal FindingsWe review efforts of WHO and collaborating agencies to track and fight the TB/HIV co-epidemic, and discuss modeling—via mathematical, statistical, and computational approaches—as a means to identify disease indicators designed to integrate data from linked diseases in order to characterize how co-epidemics change in time and space. We present R TB/HIV, an index comparing changes in TB incidence relative to HIV prevalence, and use it to identify those sub-Saharan African countries with outlier TB/HIV dynamics. R TB/HIV can also be used to predict epidemiological trends, investigate the coherency of reported trends, and cross-check the anticipated impact of public health interventions. Identifying the cause(s) responsible for anomalous R TB/HIV values can reveal information crucial to the management of public health.Conclusions/SignificanceWe frame our suggestions for integrating and analyzing co-epidemic data within the context of global disease monitoring. Used routinely, joint disease indicators such as R TB/HIV could greatly enhance the monitoring and evaluation of public health programs.

Bayesian hierarchical modeling of joint spatiotemporal risk patterns for Human Immunodeficiency Virus (HIV) and Tuberculosis (TB) in Kenya

“…These findings are corroborated in other studies by [31,53]. Looking beyond Kenya, studies by [54] revealed that TB appeared to outpace HIV in Rwanda and Burundi while HIV greatly outpaced TB in Mauritania, Senegal and The Gambia Joint temporal analysis is important when investigating the temporal coherency of epidemiological trends from the same area [54]. In our study, the shared temporal trend presented a steep decrease from 2012 to 2013 then an almost constant risk without any significant variation over time.…”

Prevalence of Candida co-infection in patients with pulmonary tuberculosis

“…It is often described as a HIV, tuberculosis coepidemic. 19 However, testing for HIV infection in tuberculosis patients has not emerged as a routine practice in resource limited and developing countries like India. Only 22 (29.3%) out of 75 patients were tested for HIV and found negative.…”

Bayesian hierarchical modeling of joint spatiotemporal risk patterns for Human Immunodeficiency Virus (HIV) and Tuberculosis (TB) in Kenya

“…Joint temporal analysis is important when investigating the temporal coherency of epidemiological trends from the same area [37]. In our study, the shared temporal trend an almost constant risk with minimal variation over time.…”