Objectives: This study aimed to estimate the prevalence of loss to follow-up (LTFU) among tuberculosis (TB) patients in Indonesia and to identify associated factors. Methods: This study analyzed data from the 2022 Tuberculosis Information System in Indonesia. A total of 71,665 drug-sensitive TB patients were included in the analysis. Age, sex,employment status, diagnosis type, human immunodeficiency virus (HIV) status, diabetesmellitus, TB type, mode of treatment, treatment standard, referral status, and type of residence.Categorical variables were analyzed using chi-square tests, followed by multivariable logistic regression to identify confounder-adjusted independent predictors of LTFU. Results: The prevalence of LTFU was 18.4%. A higher likelihood of LTFU was observed amongolder adults aged ≥65 years (adjusted-prevalence-odds-ratio [aPOR], 1.862), men (aPOR, 1.187), unemployed individuals (aPOR, 1.136), non-referred patients (aPOR, 1.547), patients with HIV (aPOR, 3.712), and those obtaining TB drugs out of pocket (aPOR, 4.998). The strongest predictorwas receipt of non-standard treatment, which was associated with a markedly increasedlikelihood of LTFU (aPOR, 26.912). In contrast, rural residence demonstrated a protective association (aPOR, 0.610). All associations were statistically significant (p < 0.001). Conclusion This study highlights a substantial burden of LTFU among TB patients in Indonesia,with nearly one in five patients discontinuing treatment. Multiple sociodemographic and clinical factors—particularly non-standard treatment, non-referral status, and HIV co-infection—were strongly associated with LTFU, underscoring gaps in the TB care continuum.These findings emphasize the need for targeted, patient-centered interventions, strengthenedreferral pathways, improved communication, and enhanced care coordination to reduce LTFU in high-risk groups.

Objective To identify the influences of local and regional climate phenomena on dengue transmission in Lahore District of Pakistan, from 2006 to 2014. Methods Time-series models were applied to analyze associations between reported cases of dengue and climatic parameters. The coherence trend of regional climate phenomena (IOD and ENSO) was evaluated with wavelet analysis. Results The minimum temperature 4 months before the dengue outbreak played the most important role in the Lahore District (P = 0.03). A NINO 3.4 index 9 months before the outbreaks exhibited a significant negative effect on dengue transmission (P = 0.02). The IOD exhibited a synchronized pattern with dengue outbreak from 2010 to 2012. The ENSO effect (NINO 3.4 index) might have played a more important role after 2012. Conclusions This study provides preliminary results of climate influences on dengue transmission in the Lahore District of Pakistan. An increasing dengue transmission risk accompanied by frequent climate changes should be noted. Integrating the influences of climate variability into disease prevention strategies should be considered by public health authorities.