Zhengbin Zhang

Accurately characterizing the spatial distribution of diseases is essential for understanding etiology and guiding targeted public health interventions. This study develops an analytical framework integrating disease mapping and spatial scan statistics to identify and validate the spatial clustering patterns of diseases. The framework follows an “exploration–validation–refinement” workflow, combining qualitative visualization with quantitative spatial analysis. Choropleth maps intuitively depict the overall distribution of diseases, providing a basis for identifying potential high-risk areas; the flexible scan statistics (FleXScan) method detects statistically significant clusters; and dot cartograms further reveal internal heterogeneity within the most likely clusters by controlling for population density. This study validated the framework using both synthetic data and real measles case data. The results indicate that the framework substantially improves the accuracy and reliability of cluster detection, facilitates the localization of local high-risk cores, and provides actionable insights for precision disease control.

Background: Tuberculosis (TB) is recognized as a serious public health concern in many developing countries. As the new main force and inheritors of national health construction, college students bear important social responsibilities and missions of practicing TB prevention and control, volunteer mobilization, and health concept dissemination. Improving college students' health literacy is crucial to preventing and treating infectious diseases. This study aims to assess college students' knowledge, attitudes, and practices (KAP) about TB prevention and treatment in Wuhan, China.Methods: A descriptive cross-sectional study survey among college students was conducted from May to June 2022 at 22 colleges using the judgment sampling method in Wuhan. KAP regarding TB was recorded and assessed using an online questionnaire platform. The status quo of KAP regarding TB prevention and treatment was statistically described, and the formation of students' TB prevention and treatment behavior was analyzed using single-factor and multifactor logistic regression.Results: A total of 15,290 college students completed the questionnaire, and 15,272 valid questionnaires were collected. The total awareness rate of knowledge, attitudes, and practices of TB prevention and treatment was 79.69%. Among them, the awareness rate of key knowledge was 79.28%, and the passing rate was 92.46%. The holding rate of correct attitudes was 89.69%, and the passing rate was 90.56%. The formation rate of correct behaviors was 72.11%, and the passing rate was 96.62%. A single-factor analysis showed that gender, grade, parents' education level, contact history of TB patients, and passing rate of key knowledge were statistically different in the formation of prevention and treatment behaviors. Multivariate logistic regression analysis showed that for females (odds ratio [OR] = 1.86, 95% CI [1.50, 2.30], p < 0.01), students with father's educational background of primary school (OR = 2.94, 95%CI [1.62, 5.33], p < 0.01), junior school and equivalent (OR = 2.94, 95%CI [1.62, 5.33], p < 0.01), high school and equivalent (OR = 3.05, 95%CI [1.70, 5.46], p < 0.01), and diploma or undergraduate (OR = 3.24, 95% CI [1.73, 6.09], p < 0.01); no history of TB (OR = 3.32, 95% CI [1.49, 7.41], p < 0.01); a passing key knowledge score (OR = 9.91, 95% CI [8.11, 12.11], p < 0.01); and a passing attitude score (OR = 7.35, 95% CI [6.01, 8.99], p < 0.01) were likely to form TB prevention and treatment behaviors.Conclusion: School health promotion should not only focus on improving students' personal knowledge and skills of TB prevention and treatment but also emphasize the level of family participation, strengthen the comprehensive mobilization action of schools, formulate policies to support health action, create a supportive social environment, and radiate the health education effect of students to the whole society.

The equity of medical services is crucial for the quality of life of a population and the sustainable development of cities. Current research on optimizing the maximal equity of medical facilities has the following limitations: (1) In the accessibility calculation models for multiple transportation modes, the impact of factors such as public transport transfers and travel distance on the choice of transportation mode is often overlooked. (2) Existing spatial equity indicators are mostly derived from the overall study area, failing to fully consider the differences in population distribution and development gaps within different development zones inside the region. This study proposes a novel Incorporating Multiple Transportation Two-Step Floating Catchment Area (IMT-2SFCA) and a Hierarchical Theil-based Maximal Accessibility Equality model (HT-MAE) to optimize the equity of access to tuberculosis medical institutions in Wuhan. The findings reveal that, compared to single-mode transportation accessibility models, the multimodal accessibility model integrates the characteristics of four transportation modes, providing a more realistic reflection of residents’ access to medical services. The optimization results show a significant improvement in the equity of access to medical services across Wuhan and among different economic development zones, although the equity indicators in non-central urban areas have declined. The results of this study provide a theoretical basis and practical insights for alleviating the inequality of access to medical services across different urban layers.

Background: Investigating the molecular epidemiological characteristics of multidrug-resistant tuberculosis (MDR-TB) in China’s moderate-burden regions, such as Wuhan, is crucial for understanding and controlling disease transmission.Materials and methods: This study analyzed MDR-TB isolates from pulmonary tuberculosis cases registered at Wuhan Pulmonary Hospital in 2017. Whole genome sequencing (WGS) was used to identify resistance-conferring mutations, examine their associations with specific Mycobacterium tuberculosis lineages or sublineages, and assess clustering profiles.Results: Among the 149 analyzed strains, the most prevalent mutations associated with resistance to 11 anti-tuberculosis drugs were identified as follows: rpoB Ser450Leu (59.73%, rifampicin), katG Ser315Thr (62.42%, isoniazid), embB Met306Val (42.86%, ethambutol), rpsL Lys43Arg (68.13%, streptomycin), pncA Trp68Arg (10.53%, pyrazinamide), gyrA Asp94Gly (22.50%, fluoroquinolones), and rrs 1401A > G (50.00–100.00%, second-line injectable aminoglycosides). Additional mutations were detected in fabG1 c-15C > T (42.86%, ethionamide) and thyX c-16C > T (21.43%, p-aminosalicylic acid). Notably, rare mutations absent from the WHO mutation catalog, such as ahpC c-52C > T and rpsL Lys43Thr, were also observed. The mutation frequency of embB Met306Ile was significantly higher in Lineage 4 (L4) strains than in Lineage 2 (L2) strains (p = 0.0150), while the rpsL Lys43Arg mutation frequency was lower in L4 compared to L2 (p = 0.0333). A total of 31 MDR MTB Mycobacterium tuberculosis isolates formed clusters, resulting in a clustering rate of 20.81% and a recent transmission rate of 11.41%. The clustering rates between L4 and L2 strains were not significantly different (χ² = 0.0017, p > 0.05).Conclusion: The genetic diversity of MDR-TB in Wuhan demonstrates unique characteristics, with evidence of localized transmission. These findings highlight the urgent need to strengthen measures to detect early cases of MDR-TB and control transmission of MDR-TB in the region.