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Clin Infect Dis. 2019 Jun 18;69(1):159-166. doi: 10.1093/cid/ciy938.

The Importance of Heterogeneity to the Epidemiology of Tuberculosis.

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School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
Health Economic and Decision Science, University of Sheffield, United Kingdom.
Liverpool School of Tropical Medicine, United Kingdom.
CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Portugal.
Department of Global Health and Development, London School of Hygiene and Tropical Medicine, United Kingdom.
Tuberculosis Centre, London School of Hygiene and Tropical Medicine, United Kingdom.
Infectious Disease Epidemiology Department, London School of Hygiene and Tropical Medicine, United Kingdom.
Australian Institute of Tropical Health and Medicine, James Cook University, Townsville, Queensland.
Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, Massachusetts.
Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, United Kingdom.
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.


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.


case detection; epidemiology; heterogeneity; interventions; tuberculosis

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