I recently joined the project team for a research study on tuberculosis in Amritsar. It was during a field visit that the Assessment Officer Anju Bala mentioned Happy’s case. In the language of the field, she described it as ‘the case of a family where TB came again and again,’ stressing the repetitive nature of the disease.
During our conversation with Happy, a 19-year-old daily wage labourer, it became clear that Tuberculosis (TB) had affected multiple generations in his family: first his grandfather (20-25 years ago), then his father (almost 10 years ago) and his paternal aunt (7-8 years ago), and now him. While the infection did occur within the same family and close contacts, the cases were separated by several years. Individually, each case followed a predictable trajectory that aligned with the programmatic indicators. However, when viewed together, they revealed a pattern not easily understood through a single exposure or a moment of transmission. The focus, thus, shifted from who became ill to how the risk may have accumulated intergenerationally within the same household, years apart.
We revisited the case notes with this lens, and the answers emerged. Not much has changed in the family’s daily life across these years. The family still lived in small, crowded housing with ill-ventilated rooms, and that was true for most houses in the area. Work was manual, physically demanding, and lacked certainty. Food intake depended on these limited earnings and was often inadequate. Healthcare was something they sought only when symptoms persisted and could no longer be ignored.
These patterns, including the delayed care-seeking, unstable work, and living environments that increase the risk to exposure, are the very signals used by field staff to assess the risk of infection, treatment disruption and disease relapse. In Happy’s case, these risk factors were passed down across generations not through bloodlines, but through living conditions that remained unchanged. Seen this way, TB appeared to be more than just a bacterial infection; it became a sum of the vulnerabilities that shape the everyday lives of those like Happy.
Within its current mandate, the health system takes a well-defined clinical route: once TB is diagnosed, it responds with tests, medications, and follow-ups to identify, treat, and cure the cases. Follow-ups and digital tools support adherence and ensure treatment completion, but cases like these are a reminder of how disease risk is shaped outside the treatment window. As a researcher, this case reminded me that some field observations extend beyond what a single programmatic frame can capture.
*The views expressed in this article are solely the personal opinions and reflections of the author(s) and do not necessarily reflect the objectives of the study they are part of.
Author’s Bio:
Sk Sahil
Research Associate
Sk. Sahil is a public health enthusiast with over 5 years of experience in implementing large-scale health programs across multiple disease areas. He currently serves as a Research Associate at the Max Institute of Healthcare Management, Indian School of Business (MIHM-ISB), where he works on implementation research on the efficacy of pill-in-hand adherence monitoring for tuberculosis. His work focuses on contributing to research outputs, supporting evidence generation, supporting data quality assurance processes, driving field-level insights, and coordinating field implementation teams to strengthen program delivery and improve outcomes.