TB risk model regression output used in CEA of HrTS among US migrants

Note: the R object will be made publicly available upon acceptance of the manuscript. The draft description of this repository is as follows:

In this repository, we report the R object of a regression output that was used as part of the analysis in the study: Cost-effectiveness of screening with transcriptional signatures for incipient TB among U.S. migrants. The aim of this study was to assess the potential health impact and cost-effectiveness of HrTS for post-arrival TB infection screening among new migrants in the United States.

From Appendix 1 in the online supplement:
Among all the migrants who entered the U.S. in 2019, we included migrants whose annual TB risks could be estimated from the fitted TB risk model reported in a prior study of TB incidence rates in the non-US-born residents of the United States (Hill et al.) [1]. In this study, the authors constructed generalized additive regression models to estimate TB incidence rates as a function of birth country, entry year, age at entry, and number of years since entry to the United States. They trained the model with individual-level data from the National Tuberculosis Surveillance System (NTSS) on TB cases among non-US-born individual between 2000-2016, and population data from the American Community Survey (ACS) and 2000 U.S. Census. This original study was funded by the U.S. Centers for Disease Control and Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention Epidemiologic and Economic Modeling Agreement (#5NU38PS004644). The regression output was made available to the authors of this current project as an .rdata object. The R object is available in this repository.

Reference:
[1] A. N. Hill, T. Cohen, J. A. Salomon, and N. A. Menzies, “High-resolution estimates of tuberculosis incidence among non-U.S.-born persons residing in the United States, 2000–2016,” Epidemics, vol. 33, p. 100419, Dec. 2020, doi: 10.1016/j.epidem.2020.100419.