Publications by authors named "Oscar Esparcia-Rodriguez"

Background: In June, 2021, WHO published the most complete catalogue to date of resistance-conferring mutations in Mycobacterium tuberculosis. Here, we aimed to assess the performance of genome-based antimicrobial resistance prediction using the catalogue and its potential for improving diagnostics in a real low-burden setting.

Methods: In this retrospective population-based genomic study M tuberculosis isolates were collected from 25 clinical laboratories in the low-burden setting of the Valencia Region, Spain.

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Transmission is a driver of tuberculosis (TB) epidemics in high-burden regions, with assumed negligible impact in low-burden areas. However, we still lack a full characterization of transmission dynamics in settings with similar and different burdens. Genomic epidemiology can greatly help to quantify transmission, but the lack of whole genome sequencing population-based studies has hampered its application.

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Objective: Patients with Inflammatory Bowel Disease (IBD) are at increased risk of hepatitis B virus (HBV) infection as well as a lower response to vaccination. This study aimed to analyze the immune response after vaccination against HBV in patients diagnosed with IBD and its associated factors.

Methods: A retrospective observational study was conducted on patients with IBD treated at the vaccination clinic for at-risk patients at the during the period 2011-2018.

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Objective: Ocular infections caused by human adenovirus are highly contagious and can cause outbreaks, especially in nursing homes. In this work, we describe the epidemiological and analytical research as well as the control measures carried out for a conjunctivitis outbreak.

Methods: Descriptive epidemiological study.

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Background: Whole genome sequencing provides better delineation of transmission clusters in Mycobacterium tuberculosis than traditional methods. However, its ability to reveal individual transmission links within clusters is limited. Here, we used a 2-step approach based on Bayesian transmission reconstruction to (1) identify likely index and missing cases, (2) determine risk factors associated with transmitters, and (3) estimate when transmission happened.

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