Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2018 Mar;24(3):573-575.
doi: 10.3201/eid2403.171613.

Statistical Method to Detect Tuberculosis Outbreaks among Endemic Clusters in a Low-Incidence Setting

Sandy P Althomsons, Andrew N Hill, Alexia V Harrist, Anne Marie France, Krista M Powell, James E Posey, Lauren S Cowan, Thomas R Navin

Statistical Method to Detect Tuberculosis Outbreaks among Endemic Clusters in a Low-Incidence Setting

Sandy P Althomsons et al. Emerg Infect Dis. 2018 Mar.

Abstract

We previously reported use of genotype surveillance data to predict outbreaks among incident tuberculosis clusters. We propose a method to detect possible outbreaks among endemic tuberculosis clusters. We detected 15 possible outbreaks, of which 10 had epidemiologic data or whole-genome sequencing results. Eight outbreaks were corroborated.

Keywords: United States; bacteria; endemic clusters; genotype; low-incidence setting; molecular epidemiology; outbreaks; respiratory infections; statistical method; tuberculosis and other mycobacteria.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Epidemiologic curve showing a prevalent (endemic) outbreak of tuberculosis, by case counts per 3-month period, United States, 2009–2016. Q, quarter.
Figure 2
Figure 2
Whole-genome sequencing results for a prevalent (endemic) cluster detected as a possible tuberculosis outbreak, United States, 2009–2016. Values indicate number of SNPs. Shown is a closely related (<2 SNPs) group of 11 isolates (lower section of phylogenetic tree). Isolates reported during a 3-year window of unexpected growth are indicated in gray. One isolate reported 1 quarter before and 1 isolate reported 1 quarter after the 3-year window of unexpected growth detection are indicated in white. An additional 2 isolates were 3 SNPs from this closely related group, 1 during (gray) and 1 outside (white) the unexpected growth window. MRCA, most recent common ancestor; SNP, single-nucleotide polymorphism.
See this image and copyright information in PMC

References

    1. Althomsons SP, Kammerer JS, Shang N, Navin TR. Using routinely reported tuberculosis genotyping and surveillance data to predict tuberculosis outbreaks. PLoS One. 2012;7:e48754. 10.1371/journal.pone.0048754 - DOI - PMC - PubMed
    1. van Soolingen D, Jajou R, Mulder A, de Neeling H. Whole genome sequencing as the ultimate tool to diagnose tuberculosis. Int J Mycobacteriol. 2016;5(Suppl 1):S60–1. 10.1016/j.ijmyco.2016.10.036 - DOI - PubMed
    1. Guthrie JL, Gardy JL. A brief primer on genomic epidemiology: lessons learned from Mycobacterium tuberculosis. Ann N Y Acad Sci. 2017;1388:59–77. 10.1111/nyas.13273 - DOI - PubMed
    1. Centers for Disease Control and Prevention. Reported tuberculosis in the United States, 2016. Atlanta: US Department of Health and Human Services, CDC; 2017 [cited 2017 Dec 18]. http://www.cdc.gov/tb/statistics/reports/2016/default.htm
    1. Walker TM, Ip CL, Harrell RH, Evans JT, Kapatai G, Dedicoat MJ, et al. Whole-genome sequencing to delineate Mycobacterium tuberculosis outbreaks: a retrospective observational study. Lancet Infect Dis. 2013;13:137–46. 10.1016/S1473-3099(12)70277-3 - DOI - PMC - PubMed

Publication types

LinkOut - more resources