Sarah T Cherng1, Sourya Shrestha1, Sue Reynolds1, Andrew N Hill1, Suzanne M Marks1, Jane Kelly1, David W Dowdy1. 1. Sarah T. Cherng, Sourya Shrestha, and David W. Dowdy are with the Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD. Sue Reynolds, Andrew N. Hill, and Suzanne M. Marks are with the Division of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, GA. Jane Kelly is with the Georgia Department of Public Health, Atlanta.
Abstract
OBJECTIVES: To illustrate the magnitude of between-state heterogeneities in tuberculosis (TB) incidence among US populations at high risk for TB that may help guide state-specific strategies for TB elimination. METHODS: We used data from the National Tuberculosis Surveillance System and other public sources from 2011 to 2015 to calculate TB incidence in every US state among people who were non-US-born, had diabetes, or were HIV-positive, homeless, or incarcerated. We then estimated the proportion of TB cases that reflected the difference between each state's reported risk factor-specific TB incidence and the lowest incidence achieved among 4 states (California, Florida, New York, Texas). We reported these differences for the 4 states and also calculated and aggregated across all 50 states to quantify the total percentage of TB cases nationally that reflected between-state differences in risk factor-specific TB incidence. RESULTS: On average, 24% of recent TB incidence among high-risk US populations reflected heterogeneity at the state level. The populations that accounted for the greatest percentage of heterogeneity-reflective cases were non-US-born individuals (51%) and patients with diabetes (24%). CONCLUSIONS: State-level differences in TB incidence among key populations provide clues for targeting state-level interventions.
OBJECTIVES: To illustrate the magnitude of between-state heterogeneities in tuberculosis (TB) incidence among US populations at high risk for TB that may help guide state-specific strategies for TB elimination. METHODS: We used data from the National Tuberculosis Surveillance System and other public sources from 2011 to 2015 to calculate TB incidence in every US state among people who were non-US-born, had diabetes, or were HIV-positive, homeless, or incarcerated. We then estimated the proportion of TB cases that reflected the difference between each state's reported risk factor-specific TB incidence and the lowest incidence achieved among 4 states (California, Florida, New York, Texas). We reported these differences for the 4 states and also calculated and aggregated across all 50 states to quantify the total percentage of TB cases nationally that reflected between-state differences in risk factor-specific TB incidence. RESULTS: On average, 24% of recent TB incidence among high-risk US populations reflected heterogeneity at the state level. The populations that accounted for the greatest percentage of heterogeneity-reflective cases were non-US-born individuals (51%) and patients with diabetes (24%). CONCLUSIONS: State-level differences in TB incidence among key populations provide clues for targeting state-level interventions.
Authors: K G Castro; S M Marks; M P Chen; A N Hill; J E Becerra; R Miramontes; C A Winston; T R Navin; R H Pratt; K H Young; P A LoBue Journal: Int J Tuberc Lung Dis Date: 2016-07 Impact factor: 2.373
Authors: Suzanne M Marks; David W Dowdy; Nicolas A Menzies; Priya B Shete; Joshua A Salomon; Andrea Parriott; Sourya Shrestha; Jennifer Flood; Andrew N Hill Journal: Public Health Rep Date: 2020 Jul/Aug Impact factor: 2.792
Authors: Sourya Shrestha; Sarah Cherng; Andrew N Hill; Sue Reynolds; Jennifer Flood; Pennan M Barry; Adam Readhead; Margaret Oxtoby; Michael Lauzardo; Tom Privett; Suzanne M Marks; David W Dowdy Journal: Am J Epidemiol Date: 2019-09-01 Impact factor: 4.897