After a brief dip in Tuberculosis (TB) incidence and mortality driven by Covid-19 pandemic, Mycobacterium tuberculosis (Mtb) emerged yet again as one of the leading cause of deaths in humans across globe. The rise of Multi Drug Resistant TB (MDR-TB) exacerbates the success of “end TB strategy”. Thus, the statistics of TB clearly highlight the requirement for stepping up efforts for comprehensive health initiatives and concerted action plan to combat TB. Two-pronged approach could be by, on one hand, hitting the pathogen Mtb at its adaptability by gleaning into its mechanisms of adaptation and on the other, by reinforcing the host immune onslaught and pressures against Mtb. With two research stories, one involving mathematics and statistics for TB and other against TB, this article accentuates the merit of integrating mathematics and statistics with the biology of host as well as pathogen for performing data-backed theoretical investigations to not only further mechanistic insights but also suggest potential novel targets against TB.
Mathematics and Statistics of, for and against Tuberculosis
