Genetic diversity of Mycobacterium tuberculosis using 24-locus MIRU-VNTR typing and Spoligotyping in Upper Myanmar

Introduction: MIRU-VNTR typing and Spoligotyping are the useful molecular tools for TB epidemiology study. Information regarding genetic diversity and tuberculosis (TB) transmission in Upper Myanmar only is scares. Methodology: We determined the genetic diversity of Mycobacterium tuberculosis (Mtb) and TB transmission from Upper Myanmar TB Reference Laboratory, Mandalay Region, including Mandalay (72), Shan (22), Magway (15), Sagaing (13), Nay Pyi Taw (8), Kachin (7), Chin (2) and Kayah (1). One hundred and forty Mtb isolates were genotyped using 24-locus MIRU-VNTR typing and spoligotyping. Lineage classification and TB transmission analysis were performed. Results: 24-locus MIRU-VNTR typing identified 135 unique profiles and two clusters compared to 35 spoligotyping profiles which contained 12 clusters and 23 unique isolates, Beijing (n=100, 71.4%) was found to be prominent lineage by combine two methods. The expected proportion attributable to recent transmission based on clustering rate was 2.1%. One cluster case was more likely to be in MDR patient. Conclusions: Our findings showed Beijing genotypes were dominant in Upper Myanmar. The usage and analysis of 24-locus MIRU-VNTR typing might prove useful for our broader understanding of TB outbreaks and epidemiology than spoligotyping. The genotypic pattern of this combined method suggests that the lower transmission rate may be due to a higher possibility of reactivation cases in Upper Myanmar

Mobile Health App for Tuberculosis Screening and Compliance to Undergo Chest X-ray Examination Among Presumptive Cases Detected by the App in Myanmar: Usability Study

BackgroundIn Myanmar, the use of a mobile app for tuberculosis (TB) screening and its operational effect on seeking TB health care have not been evaluated yet. ObjectiveThis study aims to report the usability of a simple mobile app to screen TB and comply with chest X-ray (CXR) examination of presumptive cases detected by the app. MethodsA new “TB-screen” app was developed from a Google Sheet based on a previously published algorithm. The app calculates a TB risk propensity score from an individual’s sociodemographic characteristics and TB clinical history and suggests whether the individual should undergo a CXR. The screening program was launched in urban slum areas soon after the COVID-19 outbreak subsided. A standard questionnaire was used to assess the app’s usability rated by presumptive cases. Compliance to undergo CXR was confirmed by scanning the referral quick response (QR) code via the app. ResultsRaters were 453 presumptive cases detected by the app. The mean usability rating score was 4.1 out of 5. Compliance to undergo CXR examination was 71.1% (n=322). Active TB case detection among CXR compliances was 7.5% (n=24). One standard deviation (SD) increase in the app usability score was significantly associated with a 59% increase in the odds to comply with CXR (β=.464) after adjusting for other variables (P<.001). ConclusionsThis simple mobile app got a high usability score rated by 453 users. The mobile app usability score successfully predicted compliance to undergo CXR examination. Eventually, 24 (7.5%) of 322 users who were suspected of having TB by the mobile app were detected as active TB cases by CXR. The system should be upscaled for a large trial

Mobile Health App for Tuberculosis Screening and Compliance to Undergo Chest X-ray Examination Among Presumptive Cases Detected by the App in Myanmar: Usability Study (Preprint)

BACKGROUND In Myanmar, the use of a mobile app for tuberculosis (TB) screening and its operational effect on seeking TB health care have not been evaluated yet. OBJECTIVE This study aims to report the usability of a simple mobile app to screen TB and comply with chest X-ray (CXR) examination of presumptive cases detected by the app. METHODS A new “TB-screen” app was developed from a Google Sheet based on a previously published algorithm. The app calculates a TB risk propensity score from an individual’s sociodemographic characteristics and TB clinical history and suggests whether the individual should undergo a CXR. The screening program was launched in urban slum areas soon after the COVID-19 outbreak subsided. A standard questionnaire was used to assess the app’s usability rated by presumptive cases. Compliance to undergo CXR was confirmed by scanning the referral quick response (QR) code via the app. RESULTS Raters were 453 presumptive cases detected by the app. The mean usability rating score was 4.1 out of 5. Compliance to undergo CXR examination was 71.1% (n=322). Active TB case detection among CXR compliances was 7.5% (n=24). One standard deviation (SD) increase in the app usability score was significantly associated with a 59% increase in the odds to comply with CXR (&lt;i&gt;β&lt;/i&gt;=.464) after adjusting for other variables (&lt;i&gt;P&lt;/i&gt;&amp;lt;.001). CONCLUSIONS This simple mobile app got a high usability score rated by 453 users. The mobile app usability score successfully predicted compliance to undergo CXR examination. Eventually, 24 (7.5%) of 322 users who were suspected of having TB by the mobile app were detected as active TB cases by CXR. The system should be upscaled for a large trial. </sec

Mobile Health App for Tuberculosis Screening and Compliance to Undergo Chest X-ray Examination Among Presumptive Cases Detected by the App in Myanmar: Usability Study

Background In Myanmar, the use of a mobile app for tuberculosis (TB) screening and its operational effect on seeking TB health care have not been evaluated yet. Objective This study aims to report the usability of a simple mobile app to screen TB and comply with chest X-ray (CXR) examination of presumptive cases detected by the app. Methods A new “TB-screen” app was developed from a Google Sheet based on a previously published algorithm. The app calculates a TB risk propensity score from an individual’s sociodemographic characteristics and TB clinical history and suggests whether the individual should undergo a CXR. The screening program was launched in urban slum areas soon after the COVID-19 outbreak subsided. A standard questionnaire was used to assess the app’s usability rated by presumptive cases. Compliance to undergo CXR was confirmed by scanning the referral quick response (QR) code via the app. Results Raters were 453 presumptive cases detected by the app. The mean usability rating score was 4.1 out of 5. Compliance to undergo CXR examination was 71.1% (n=322). Active TB case detection among CXR compliances was 7.5% (n=24). One standard deviation (SD) increase in the app usability score was significantly associated with a 59% increase in the odds to comply with CXR (β=.464) after adjusting for other variables (P&lt;.001). Conclusions This simple mobile app got a high usability score rated by 453 users. The mobile app usability score successfully predicted compliance to undergo CXR examination. Eventually, 24 (7.5%) of 322 users who were suspected of having TB by the mobile app were detected as active TB cases by CXR. The system should be upscaled for a large trial. </jats:sec

Genetic diversity of Mycobacterium tuberculosis using 24-locus MIRU-VNTR typing and Spoligotyping in Upper Myanmar

Introduction: MIRU-VNTR typing and Spoligotyping are the useful molecular tools for TB epidemiology study. Information regarding genetic diversity and tuberculosis (TB) transmission in Upper Myanmar only is scares.&#x0D; Methodology: We determined the genetic diversity of Mycobacterium tuberculosis (Mtb) and TB transmission from Upper Myanmar TB Reference Laboratory, Mandalay Region, including Mandalay (72), Shan (22), Magway (15), Sagaing (13), Nay Pyi Taw (8), Kachin (7), Chin (2) and Kayah (1). One hundred and forty Mtb isolates were genotyped using 24-locus MIRU-VNTR typing and spoligotyping. Lineage classification and TB transmission analysis were performed.&#x0D; Results: 24-locus MIRU-VNTR typing identified 135 unique profiles and two clusters compared to 35 spoligotyping profiles which contained 12 clusters and 23 unique isolates, Beijing (n=100, 71.4%) was found to be prominent lineage by combine two methods. The expected proportion attributable to recent transmission based on clustering rate was 2.1%. One cluster case was more likely to be in MDR patient.&#x0D; Conclusions: Our findings showed Beijing genotypes were dominant in Upper Myanmar. The usage and analysis of 24-locus MIRU-VNTR typing might prove useful for our broader understanding of TB outbreaks and epidemiology than spoligotyping. The genotypic pattern of this combined method suggests that the lower transmission rate may be due to a higher possibility of reactivation cases in Upper Myanmar.</jats:p