While COVID-19 is a global pandemic, different countries have experienced different morbidity and mortality patterns. We employ retrospective and prospective space–time permutation analysis on COVID-19 positive records across different municipalities in Sweden from March 2020 to February 2021, using data provided by the Swedish Public Health Agency. To the best of our knowledge, this is the first study analyzing nationwide COVID-19 space–time clustering in Sweden, on a season-to-season basis. Our results show that different municipalities within Sweden experienced varying extents of season-dependent COVID-19 clustering in both the spatial and temporal dimensions. The reasons for the observed differences could be related to the differences in the earlier exposures to the virus, the strictness of the social restrictions, testing capabilities and preparedness. By profiling COVID-19 space–time clusters before the introduction of vaccines, this study contributes to public health efforts aimed at containing the virus by providing plausible evidence in evaluating which epidemiologic interventions in the different regions could have worked and what could have not worked.

Background: Tuberculosis (TB) remains a significant public health challenge in Uganda. As countries strive toward the End TB targets – a 90% reduction in TB deaths and an 80% reduction in TB incidence by 2030, timely data-driven insights are critical for guiding effective responses, particularly in the post-COVID-19 context. Methods: This study analysed district-level TB case notification data from January 2020 to February 2025, sourced from the National Tuberculosis and Leprosy Programme (NTLP). We applied temporal trend analysis, spatial autocorrelation, hotspot and emerging hotspot detection, and forest-based space-time forecasting to assess past patterns and project incidence through February 2026. Results: TB notifications increased sharply from 29,640 cases in 2020 to 72,768 in 2024, with case notification rates rising from 71.3 to 158.5 per 100,000 population. Spatial analysis revealed persistent clustering in northeastern Uganda (notably Moroto and Nakapiripirit), districts bordering Lake Victoria (e.g., Mukono, Buikwe, Buvuma), and emerging clusters in oil-rich Lake Albert regions. Cold spots were consistently identified in eastern and southwestern Uganda. Forecasts suggest a continued high burden in these same areas. Conclusion: By identifying stable, emerging and projected TB clusters, this study offers actionable insights to guide targeted interventions, optimize surveillance, and inform strategic planning. These findings provide a data-driven pathway toward accelerating Uganda’s progress toward its End TB commitments. Clinical trial: Not applicable.