Alternative model specifications.

<p>The above compares modeled results from several alternative models by time period (A) and specification (B). (A) Extends the primary specification from 2017–2023 to include the early period of Xpert MTB/RIF implementation from 2014–2016. Across both panels, points reflect the naively estima...

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Bibliographic Details
Main Author:	Sarah E. Baum (3270183) (author)
Other Authors:	Daniele M. Pelissari (18621328) (author), Fernanda Dockhorn Costa (20469415) (author), Luiza O. Harada (20469418) (author), Mauro Sanchez (287788) (author), Patricia Bartholomay (328739) (author), Ted Cohen (118302) (author), Marcia C. Castro (7377455) (author), Nicolas A. Menzies (8677533) (author)
Published:	2024
Subjects:	Medicine Neuroscience Biotechnology Cancer Hematology Infectious Diseases Virology Computational Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified rapid diagnostic tests observed xpert mtb na &# 239 employed statistical corrections 28 &# 8211 2017 &# 8211 2 &# 8211 previously treated cases used model output resistance &# 8212 alternative model specifications recover unbiased estimates increased testing coverage resistance among new rdt data collected derive timely estimates drug susceptibility testing representative prevalence surveys estimated prevalence ranging routine tb diagnosis patients receiving rdts brazil </ p tb drug resistance new cases rdt testing timely information level data resistance levels recommended rdt tb incidence modeled estimates untested individuals time period results using resistant tuberculosis requires accurate past decade overall cohort methodological development infrequent nationally impute results expanded availability core drugs approach provides 2023 case 000 patients
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Alternative model specifications.

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