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Despite impacting mankind since ancient times, tuberculosis (TB) persists as the leading cause of death from an infectious disease. TB can remain latent and further research is required to understand activation risk and the risks vs. the benefits of treating latent infection. Drug resistance poses an escalating threat to treating active disease and achieving cure.
Drug-resistant tuberculosis (DR-TB) remains a major public health challenge in China, with varying treatment outcomes across different regions. Understanding the spatial distribution of DR-TB treatment outcomes is crucial for targeted interventions to improve treatment success in high-burden areas such as Hunan Province. This study aimed to map the spatial distribution of DR-TB treatment outcomes at a local level and identify sociodemographic and environmental factors associated with poor treatment outcomes in Hunan Province, China.
This systematic review aimed to summarise existing literature on the impacts of armed conflicts on tuberculosis burden and treatment outcomes.
Drug-resistant tuberculosis (DR-TB) is a major public health threat in Hunan Province, with an increasing clinical burden in recent years. This study aimed to identify socio-demographic and clinical factors associated with DR-TB in Hunan province, China.
Contact investigations with drug-susceptible tuberculosis (DS-TB) patients have demonstrated a high prevalence of tuberculosis infection (TBI). However, the prevalence of TBI among individuals in close contact with drug-resistant tuberculosis (DR-TB) patients is poorly understood. This systematic review and meta-analysis aimed to determine the prevalence of TBI among household and non-household contacts of DR-TB patients.
o map subnational and local prevalence of drug-resistant tuberculosis (DR-TB) across Africa. We assembled a geolocated dataset from 173 sources across 31 African countries, comprising drug susceptibility test results and covariate data from publicly available databases. We used Bayesian model-based geostatistical framework with multivariate Bayesian logistic regression model to estimate DR-TB prevalence at lower administrative levels.
Health system and environmental factors play a significant role in achieving the World Health Organization End Tuberculosis (TB) targets. However, quantitative measures are scarce or non-existent at a global level. We aimed to measure the progress made towards meeting the global End TB milestones from 2015 to 2020 and identify health system and environmental factors contributing to the success.
To achieve targets set within the 2030 Sustainable Development Agenda and the 2021–2030 Neglected Tropical Diseases (NTD) Roadmap, the World Health Organization identify the need for improved data analytics to inform NTD control programs.
Malaria incidence (MI) has significantly declined in Nepal, and this study aimed to investigate the spatiotemporal distribution and drivers of MI at the ward level. Data for malaria cases were obtained from the National Surveillance System from 2013 to 2021. Data for covariates, including annual mean temperature, annual mean precipitation, and distance to the nearest city, were obtained from publicly available sources. A Bayesian spatial model was used to identify factors associated with the spatial distribution of MI.
No studies have yet examined high-resolution shifts in the spatial patterns of human movement in Australia throughout 2020 and 2021, a period coincident with the repeated enactment and removal of varied governmental restrictions aimed at reducing community transmission of SARS-CoV-2. We compared overlapping timeseries of COVID-19 pandemic-related restrictions, epidemiological data on cases and vaccination rates, and high-resolution human movement data to characterize population-level responses to the pandemic in Australian cities.