Spatiotemporal clustering of tuberculosis notifications in Nepal during the COVID-19 pandemic and subsequent recovery: A national space-time scan analysis, 2019-2024

Tuberculosis is an ancient bacterial infection that settles in the lungs, spreading through the air when an infected person coughs or speaks. For decades, public health workers have relied on a steady rhythm of reporting: when a doctor diagnoses a case, they tell the authorities, who then track where the disease is appearing and how fast it is moving. This tracking is vital because the disease does not spread evenly; it often gathers in specific neighborhoods or regions, creating pockets of high risk that need extra attention. However, the global pandemic of a different respiratory virus, which began in 2020, threw this rhythm into chaos. Lockdowns, overwhelmed hospitals, and fear of visiting clinics meant that many people with tuberculosis went undiagnosed or untreated for months. As the world began to recover from that crisis, health officials faced a new question: as services returned to normal, where did the cases of tuberculosis reappear, and did they return in the same places they had always been, or had the disruption changed the pattern entirely?

In Nepal, a team of researchers set out to answer this question by looking at the last five years of data, covering the period just before the pandemic, the height of the disruption, and the years of recovery that followed. They gathered reports from every single district in the country, a total of seventy-seven regions, to build a complete picture of how tuberculosis notifications changed over time and space. The researchers treated the data like a map that could be scanned for hotspots, using a method that looks for groups of cases that appear together in a specific place and time more often than chance would allow. They were not just counting total numbers; they were looking for the shape of the outbreak, seeking to see if the disease was clustering in certain areas while fading in others, and whether these clusters shifted as the country moved through the pandemic and into its aftermath.

The results revealed a story of significant change. Over the five-year period studied, the number of tuberculosis cases reported in Nepal rose sharply. By the final year of the study, the rate of reported cases had climbed from ninety-two per one hundred thousand people to one hundred and thirty-nine per one hundred thousand, a fifty-one percent increase. This rise was not a slow, uniform drift across the entire country. Instead, the data showed that the increase happened in distinct waves and specific locations. The researchers identified four major areas where cases gathered together in a way that was statistically unlikely to be random. The largest and most prominent of these clusters covered a group of districts in the central and southern parts of the country, including Kathmandu, Lalitpur, and Bhaktapur, along with several districts in the southern plains. This cluster was active from the middle of the recovery period through the most recent year, suggesting that these areas have become a persistent focus for the disease.

Beyond the central cluster, the analysis found other pockets of high activity scattered across the landscape. Significant groups of cases appeared in the western part of the country, in the eastern plains, and in a specific district known as Rupandehi. These findings indicate that the return of tuberculosis cases after the pandemic was not a simple nationwide rebound but a complex patchwork of local surges. When the researchers looked at the timing of the cases across the whole nation, they saw a clear spike in reports during the last two years of the study period, confirming that the recovery phase brought a substantial increase in diagnosed cases. The data suggests that while the overall number of cases is rising, the disease is concentrating its impact in particular geographic zones rather than spreading evenly.

The study concludes that understanding these patterns requires looking at both time and place simultaneously. The researchers found that the post-pandemic recovery period in Nepal has been marked by a distinct geographic and temporal unevenness in tuberculosis notifications. The identification of these specific clusters suggests that a one-size-fits-all approach to control may no longer be sufficient. Instead, the evidence points toward the need for strategies that are tailored to the specific districts where the disease is gathering. By mapping these clusters, health officials can direct their resources to the areas where they are most needed, ensuring that the recovery from the pandemic does not leave behind the communities where tuberculosis has taken the strongest hold.