Clinton J McDaniel
Biographic Data
| ID | 9993695 |
|---|---|
| NAME | Clinton J McDaniel |
| GIVEN NAMES | Clinton J |
| FAMILY NAME | McDaniel |
| SIGNATURE | MCDANIEL C J |
| AFFILIATIONS | Centers for Disease Control and Prevention |
| ORCID | 0000-0001-7725-6758 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
Mutation of Mycobacterium tuberculosis and Implications for Using Whole-Genome Sequencing for Investigating Recent Tuberculosis Transmission
Tuberculosis (TB) control programs use whole-genome sequencing (WGS) of Mycobacterium tuberculosis ( Mtb ) for detecting and investigating TB case clusters. Existence of few genomic differences between Mtb isolates might indicate TB cases are the result of recent transmission. However, the variable and sometimes long duration of latent infection, combined with uncertainty in the Mtb mutation rate during latency, can complicate interpretation of W…
Logically Inferred Tuberculosis Transmission (Litt)
Understanding tuberculosis (TB) transmission chains can help public health staff target their resources to prevent further transmission, but currently there are few tools to automate this process. We have developed the Logically Inferred Tuberculosis Transmission (LITT) algorithm to systematize the integration and analysis of whole-genome sequencing, clinical, and epidemiological data. Based on the work typically performed by hand during a cluste…
Estimating and Evaluating Tuberculosis Incidence Rates Among People Experiencing Homelessness, United States, 2007–2016
OBJECTIVES: Persons experiencing homelessness (PEH) are disproportionately affected by tuberculosis (TB). We estimate area-specific rates of TB among PEH and characterize the extent to which available data support recent transmission as an explanation of high TB incidence. METHODS: We estimated TB incidence among PEH using National Tuberculosis Surveillance System data and population estimates for the US Department of Housing and Urban Developmen…
No prominent works on this page.
Logically Inferred Tuberculosis Transmission (Litt)
Understanding tuberculosis (TB) transmission chains can help public health staff target their resources to prevent further transmission, but currently there are few tools to automate this process. We have developed the Logically Inferred Tuberculosis Transmission (LITT) algorithm to systematize the integration and analysis of whole-genome sequencing, clinical, and epidemiological data. Based on the work typically performed by hand during a cluste…
Estimating and Evaluating Tuberculosis Incidence Rates Among People Experiencing Homelessness, United States, 2007–2016
OBJECTIVES: Persons experiencing homelessness (PEH) are disproportionately affected by tuberculosis (TB). We estimate area-specific rates of TB among PEH and characterize the extent to which available data support recent transmission as an explanation of high TB incidence. METHODS: We estimated TB incidence among PEH using National Tuberculosis Surveillance System data and population estimates for the US Department of Housing and Urban Developmen…
Mutation of Mycobacterium tuberculosis and Implications for Using Whole-Genome Sequencing for Investigating Recent Tuberculosis Transmission
Tuberculosis (TB) control programs use whole-genome sequencing (WGS) of Mycobacterium tuberculosis ( Mtb ) for detecting and investigating TB case clusters. Existence of few genomic differences between Mtb isolates might indicate TB cases are the result of recent transmission. However, the variable and sometimes long duration of latent infection, combined with uncertainty in the Mtb mutation rate during latency, can complicate interpretation of W…
Medicine (3 works) · Tuberculosis (3 works) · Tuberculosis Research and Epidemiology (3 works) · Computer Science (2 works) · Algorithm (1 works) · Biology (1 works) · Computational biology (1 works) · COVID-19 diagnosis using AI (1 works) · Data integration (1 works) · Data mining (1 works)