ABSTRACT
Intro: Tuberculosis (TB) is an ancient disease in Malaysia and the arrival of COVID-19 has driven TB into an unknown that possibly creates hidden threats to public health. Recently, TB is identified as a socially influenced disease transmitted through people that are easily mobile and dynamically connected. It is critical to develop a data-driven geospatial-based modelling to map tuberculosis (TB) cases in Malaysia for boosting early detection. Method(s): We conducted a retrospective review of TB notified cases in Kuala Lumpur, Malaysia, between the years 2020 and 2021. The data was retrieved from the MyTB database and TB cases trends were examined against the five main series of 2020-2021 Malaysia Movement Control Order (MCO). The examination was extended to the study of social demographic and disease profiles. Locality, sub-locality, and housing type were investigated to measure hotspots in Kuala Lumpur. Finding(s): The number of patients with pulmonary TB (PTB) was high where 51% of them are smear positive and contributed majorly by male dominants. Cases with diabetes tend to be dominated by positive smear PTB that is close to 80%. There is a relatively strong trend that cases diagnosed with diabetes are in the non-smokers group and almost equally distributed between men and women, although the remaining cases are succeeded by men at the rate of 98% as opposed to women. Conclusion(s): The review of Kuala Lumpur TB notification between 2020 and 2021 is presented in this study providing a glance at a retrospective view of TB case notification in the era of the pandemic COVID-19. There are 188 cases per 100,000 population within the area of Kuala Lumpur and several important examinations were conducted to understand the underlying insights of notified TB cases. Several areas have been identified as hotspots according to geospatial modelling to allow targeted TB prevention activities at the community level.Copyright © 2023