A Sign of Superspreading in Tuberculosis: Highly Skewed Distribution of Genotypic Cluster Sizes

• Published in: Epidemiology (Cambridge, Mass.) Vol. 24; no. 3; pp. 395 - 400
• Main Authors: Ypma, Rolf J. F., Altes, Hester Korthals, van Soolingen, Dick, Wallinga, Jacco, van Ballegooijen, W. Marijn
• Format: Journal Article
• Language: English
• Published: Philadelphia, PA Lippincott Williams & Wilkins 01-05-2013; Lippincott Williams & Wilkins, Inc
• Subjects: Amplified Fragment Length Polymorphism Analysis; Bacterial diseases; Biological and medical sciences; Cluster Analysis; Contact Tracing; Data transmission; Disease models; Disease transmission; DNA, Bacterial - analysis; Epidemiology; General aspects; Genotype; Human bacterial diseases; Humans; Infectious Disease; Infectious diseases; Medical sciences; Miscellaneous; Models, Statistical; Molecular Typing; Mycobacterium tuberculosis; Mycobacterium tuberculosis - classification; Mycobacterium tuberculosis - genetics; Netherlands - epidemiology; Polymorphism, Restriction Fragment Length; Public health. Hygiene; Public health. Hygiene-occupational medicine; Registries; Simulations; Skewed distribution; Trucks; Tuberculosis; Tuberculosis and atypical mycobacterial infections; Tuberculosis, Pulmonary - epidemiology; Tuberculosis, Pulmonary - microbiology; Tuberculosis, Pulmonary - transmission; Netherlands; Infection; Tuberculosis; Size; Distribution; Bacteriosis; Genotype; Cluster; Mycobacterial infection; Epidemiology; Public health
• ISSN: 1044-3983; 1531-5487
• DOI: 10.1097/EDE.0b013e3182878e19

Background: Molecular typing is a valuable tool for gaining insight into spread of Mycobacterium tuberculosis. Typing allows for clustering of cases whose isolates share an identical genotype, revealing epidemiologic relatedness. Observed distributions of genotypic cluster sizes of tuberculosis (TB) are highly skewed. A possible explanation for this skewness is the concept of "superspreading": a high heterogeneity in the number of secondary cases caused per infectious individual. Superspreading has been previously found for diseases such as severe acute respiratory syndrome and smallpox, where the entire transmission tree is known. So far, no method exists to relate superspreading to the distribution of genotypic cluster sizes. Methods: We quantified heterogeneity in secondary infections per infectious individual by describing this number as a negative binomial distribution. The dispersion parameter k is a measure of superspreading; standard (homogeneous) models use values of k≥1, whereas small values of k imply superspreading. We estimated this negative binomial dispersion parameter for TB in the Netherlands, using the genotypic cluster size distribution for all 8330 cases of culture confirmed, pulmonary TB diagnosed between 1993 and 2007 in the Netherlands. Results: The dispersion parameter k was estimated at 0.10 (95% confidence interval = 0.09—0.12), well in the range of values consistent with superspreading. Simulation studies showed the method reliably estimates the dispersion parameter across a range of scenarios and parameter values. Conclusion: Heterogeneity in the number of secondary cases caused per infectious individual is a plausible explanation for the observed skewness in genotypic cluster size distribution of TB.