Social-behavioral insights in understanding tuberculosis transmission pattern during the COVID-19 pandemic period in Kuala Lumpur, Malaysia: The MyTBNet study protocol.

Many countries have reported increase of TB incidence during the COVID-19 pandemic period, which demands dire attention as it may threaten global effort to end TB transmission. Services, are among many others, were disrupted by the COVID-19 pandemic during the years 2020 and 2021; but its impact on the TB transmission is not well understood. This retrospective population-based molecular and epidemiological cohort study aims to determine the pattern of TB transmission in Kuala Lumpur (an area with high population density, moderate TB burden and high rates of COVID-19 cases) for the cohort of Pulmonary TB (PTB) cases notified from 2020 until 2021 and factors associated with clustering or clear epidemiologic linkage. This study will be carried out from 2022 until 2024. The study will utilise comparative phylogenetic analysis to determine the degree of relatedness between different isolates, based on the genomes similarities, and overlay this with epidemiological, clinical and social network data to enhance understanding of the social-behavioural dynamics of TB transmission. Mycobacterium tuberculosis complex (MTBC) cultures will be genotyped using Mycobacterial Interspersed Repetitive Unit Variable Number Tandem Repeats (MIRU-VNTR) and whole-genome sequence (WGS) for MTBC cluster isolates. Epidemiologic and genomic data will be overlaid on a social network constructed by means of interviews with patients, by using Social Network Analysis questionnaire, to determine the origins and transmission dynamics of the outbreak. The finding of this study would aid in the identification of TB transmission events, facilitating active case finding, TB screening, TB contact tracing, and the mapping of social contacts during critical period. This will contribute to building an effective preventive and preparedness strategy to interrupt TB transmission in Malaysia, tailored to the characteristics of the local population.