ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2023
Contribution of Reinfection to Annual Rate of Tuberculosis Infection (ARI) and Incidence of Tuberculosis Disease.
Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 15 citations in OpenAlex.
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- Advancement in diagnostic approaches for latent tuberculosis: distinguishing recent from remote infections.One health outlook · 2025Review
- Distinguishing new from persistent infections at the strain level using longitudinal genotyping data.bioRxiv : the preprint server for biology · 2025Article
- Non-communicable diseases and resistant tuberculosis, a growing burden among people living with HIV in Eastern Kenya.PLOS global public health · 2025Article
- Long-Term Case-Finding of Latent Tuberculosis Infection Among Household Contacts to Support Tuberculosis Elimination Efforts in Indonesia.Materia socio-medica · 2025Article
- Overlooked, dismissed, and downplayed: reversion ofEuropean respiratory review : an official journal of the European Respiratory Society · 2024Review
- What Influence Could the Acceptance of Visitors Cause on the Epidemic Dynamics of a Reinfectious Disease?: A Mathematical Model.Acta biotheoretica · 2024Article
- Impact of Reversion of Mycobacterium tuberculosis Immunoreactivity Tests on the Estimated Annual Risk of Tuberculosis Infection.American journal of epidemiology · 2023Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 2 countries.
Funding
Abstract
backgroundModeling studies have concluded that 60-80% of tuberculosis (TB) infections result from reinfection of previously infected persons. The annual rate of infection (ARI), a standard measure of the risk of TB infection in a community, may not accurately reflect the true risk of infection among previously infected persons. We constructed a model of infection and reinfection with Mycobacterium tuberculosis to explore the predictive accuracy of ARI and its effect on disease incidence.
methodsWe created a deterministic simulation of the progression from TB infection to disease and simulated the prevalence of TB infection at the beginning and end of a theoretical year of infection. We considered 10 disease prevalence scenarios ranging from 100/100 000 to 1000/100 000 in simulations where TB exposure probability was homogeneous across the whole simulated population or heterogeneously stratified into high-risk and low-risk groups. ARI values, rates of progression from infection to disease, and the effect of multiple reinfections were obtained from published studies.
resultsWith homogeneous exposure risk, observed ARI values produced expected numbers of infections. However, when heterogeneous risk was introduced, observed ARI was seen to underestimate true ARI by 25-58%. Of the cases of TB disease that occurred, 36% were among previously infected persons when prevalence was 100/100 000, increasing to 79% of cases when prevalence was 1000/100 000.
conclusionsMeasured ARI underestimates true ARI as a result of heterogeneous population mixing. The true force of infection in a community may be greater than previously appreciated. Hyperendemic communities likely contribute disproportionally to the global TB disease burden.
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