An updated method to estimate factors associated with tuberculosis transmission using whole genome sequencing and other additional metadata
Shapiro, A. N.; Huang, C.; Brooks, M. B.; Malatesta, S.; Lecca, L.; Becerra, M. C.; Calderon, R. I.; Contreras, C.; Jimenez, J.; Yataco, R.; Zhang, Z.; Murray, M. B.; White, L.; Jenkins, H.
Show abstract
BackgroundUnderstanding tuberculosis (TB) transmission dynamics is necessary to interrupt disease spread. We developed a model to estimate adjusted odds ratios (ORs) for factors associated with genetic relatedness, as proxy for transmission. MethodsWe build upon an existing iterative model that modifies genetically linked tuberculosis case data to better represent true transmission links. We incorporate bootstrapped logistic regression to calculate adjusted ORs with confidence intervals that account for correlation from individuals present across multiple transmission pairs. We assess model performance with simulation studies and apply the method to cohort data from Lima, Peru. ResultsIterative algorithm estimates resembled those from logistic regression but had larger confidence intervals, reflecting the data correlation adjustment. Transmission pairs where at least one member was >34 years had decreased transmission odds. Pairs with at least one incarcerated or male member had increased adjusted transmission odds. ConclusionsWe produce adjusted ORs accounting for the correlation of pairwise genetic relatedness data. These ORs are an accurate proxy for the association between covariates and transmission and further our understanding of factors associated with tuberculosis transmission.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Long-term effects of mass screening for latent and active tuberculosis in the Marshall Islands 94%
- Quantifying Within-Household Tuberculosis Transmission: A Systematic Review and a Prospective Cohort Study 93%
- Estimating the Relative Probability of Direct Transmission between Infectious Disease Patients 93%
Similar papers in this journal
- Revisiting the Natural History of Pulmonary Tuberculosis: a Bayesian Estimation of Natural Recovery and Mortality rates 95%
- Exhaled Mycobacterium tuberculosis predicts incident infection in household contacts 94%
- Effects of the COVID-19 pandemic on TB outcomes in the United States: a Bayesian analysis 93%
Similar papers in this journal
- Potential Utility of C-reactive Protein for Tuberculosis Risk Stratification among Patients with Non-Meningitic Symptoms at HIV Diagnosis in Low- and Middle-Income Countries 91%
- Programmatic diagnostic accuracy and clinical utility of Xpert MTB/XDR in patients with rifampicin-resistant tuberculosis in Georgia 91%
- Evaluating strategies to combat a major syphilis outbreak in Australia among Aboriginal and Torres Strait Islander peoples in remote and regional Australia through mathematical modelling 90%
Similar papers in this journal
- Network Analysis of Pairwise Relative Tuberculosis Transmission Probabilities in Lima, Peru 92%
- Comparative evaluation of methodologies for estimating the effectiveness of non-pharmaceutical interventions in the context of COVID-19: a simulation study 92%
- The impact of delayed switch to second-line antiretroviral therapy on mortality, depending on failure time definition and CD4 count at failure 92%
Similar papers in this journal
- Using genetic data to identify transmission risk factors: statistical assessment and application to tuberculosis transmission 94%
- EpiFusion: Joint inference of the effective reproduction number by integrating phylodynamic and epidemiological modelling with particle filtering 92%
- Estimating the epidemic reproduction number from temporally aggregated incidence data: a statistical modelling approach and software tool 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.