Tuberculosis (TB) is an important and widespread disease of wildlife, livestock and humans world-wide, but long-term empirical datasets describing this condition are rare. A population of meerkats (Suricata suricatta) in South Africa's Kalahari Desert have been diagnosed with Mycobacterium suricattae, a novel strain of TB, causing fatal disease in this group-living species. This study aimed to find characteristics associated with clinical TB in meerkats. These characteristics could subsequently be used to identify 'at-risk' animals within a population, and target these individuals for control measures. We conducted a retrospective study based on a unique, long-term life-history dataset of over 2000 individually identified animals covering a 14-year period after the first confirmatory diagnosis of TB in this population in 2001. Individual- and group-level risk factors were analysed using time-dependent Cox regression to examine their potential influence on the time to development of end-stage TB. Cases of disease involved 144 individuals in 27 of 73 social groups, across 12 of 14 years (an incidence rate of 3·78 cases/100 study years). At the individual level, increasing age had the greatest effect on risk of disease with a hazard ratio of 4·70 (95% CI: 1·92-11·53, P < 0·01) for meerkats aged 24-48 months, and a hazard ratio of 9·36 (3·34-26·25, P < 0·001) for animals aged over 48 months (both age categories compared with animals aged below 24 months). Previous group history of TB increased the hazard by a factor of 4·29 (2·00-9·17, P < 0·01), and an interaction was found between this variable and age. At a group level, immigrations of new group members in the previous year increased hazard by a factor of 3·00 (1·23-7·34, P = 0·016). There was weaker evidence of an environmental effect with a hazard ratio for a low rainfall (<200 mm) year of 2·28 (0·91-5·72, P = 0·079). Our findings identify potential individual characteristics on which to base targeted control measures such as vaccination. Additional data on the dynamics of the infection status of individuals and how this changes over time would complement these findings by enhancing understanding of disease progression and transmission, and thus the implications of potential management measures.