Abstract
Although less well-recognized than for other infectious diseases, heterogeneity is a defining feature of tuberculosis (TB) epidemiology. To advance toward TB elimination, this heterogeneity must be better understood and addressed. Drivers of heterogeneity in TB epidemiology act at the level of the infectious host, organism, susceptible host, environment, and distal determinants. These effects may be amplified by social mixing patterns, while the variable latent period between infection and disease may mask heterogeneity in transmission. Reliance on notified cases may lead to misidentification of the most affected groups, as case detection is often poorest where prevalence is highest. Assuming that average rates apply across diverse groups and ignoring the effects of cohort selection may result in misunderstanding of the epidemic and the anticipated effects of control measures. Given this substantial heterogeneity, interventions targeting high-risk groups based on location, social determinants, or comorbidities could improve efficiency, but raise ethical and equity considerations.
Highlights
There are many reasons to suspect that TB epidemics are highly heterogeneous, such as the prominence of highly localised or household transmission, the wide geographical variation in disease burden within and between countries and the many individual-level factors strongly associated with risk of disease
All TB modelling studies must judge which aspects of heterogeneity are sufficiently important to include given the question posed and the local context, and which should not be incorporated for parsimony
Targeting of interventions is an appropriate consideration in designing intervention strategies, evidence to support specific targeted approaches is sometimes weak or contradictory
Summary
Estimates of the global burden of tuberculosis (TB) suggest gradual decline, this aggregate. HIV is the strongest individual-level risk factor and a major driver of the TB epidemic in many parts of Africa, while the rising global prevalence of non-communicable diseases (e.g. diabetes) may hinder our ability to achieve control targets by impairing host immunity at the population level.[17] History of exposure and disease are important, as people who are latently infected likely have partial protection against reinfection with the pathogen,[18] whereas previously treated persons are likely to be at substantially increased risk for recurrent disease.[19] This latter increase in risk may reflect repeated exposure, incomplete treatment, or underlying immunological vulnerability.[20]
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