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Economic burden of multidrug-resistant tuberculosis on patients and households: a global systematic review and meta-analysis

Multidrug-resistant tuberculosis (MDR-TB) is a major health threat worldwide, causing a significant economic burden to patients and their families. Due to the longer duration of treatment and expensive second-line medicine, the economic burden of MDR-TB is assumed to be higher than drug-susceptible TB.

Influenza vaccination in Western Australian children: Exploring the health benefits and cost savings of increased vaccine coverage in children

To assess potential benefits and direct healthcare cost savings with expansion of an existing childhood influenza immunisation program, we developed a dynamic transmission model for the state of Western Australia, evaluating increasing coverage in children < 5 years and routinely immunising school-aged children.

Epidemiology of soil-transmitted helminths using quantitative PCR and risk factors for hookworm and Necator americanus infection in school children in Dak Lak province, Vietnam

Soil-transmitted helminth (STH) infection is driven by a complex interaction of demographic, socioeconomic and behavioural factors, including those related to water, sanitation and hygiene (WASH). Epidemiological studies that measure both infection and potential risk factors associated with infection help to understand the drivers of transmission in a population and therefore can provide information to optimise STH control programmes.

The risk of mother-to-child transmission of hepatitis B virus infection in Ethiopia: A systematic review and meta-analysis

Mother-to-child transmission (MTCT) of hepatitis B virus (HBV) is a predominant route of infection for children in Ethiopia. No study has so far reported a nationwide estimate of the risk of MTCT of HBV. We conducted a meta-analysis of surveys and estimated the pooled risk of MTCT of HBV in the context of human immunodeficiency virus (HIV) infection.

Spatial and Temporal Data Visualisation for Mass Dissemination: Advances in the Era of COVID-19

The COVID-19 pandemic is the first major pandemic of the digital age and has been characterised by unprecedented public consumption of spatial and temporal disease data, which can enable greater transparency and accountability of governments to the public for their public health decisions.

The seasonality of respiratory syncytial virus in Western Australia prior to implementation of SARS-CoV-2 non-pharmaceutical interventions

Respiratory syncytial virus (RSV) seasonality is dependent on the local climate. We assessed the stability of RSV seasonality prior to the SARS-CoV-2 pandemic in Western Australia (WA), a state spanning temperate and tropical regions.

Psychological distress in three Australian communities living with environmental per- and polyfluoroalkyl substances contamination

Environmental chemical contamination is a recognised risk factor for psychological distress, but has been seldom studied in the context of per- and polyfluoroalkyl substances (PFAS) contamination. We examined psychological distress in a cross-sectional study of three Australian communities exposed to PFAS from the historical use of aqueous film-forming foam in firefighting activities, and three comparison communities without environmental contamination.

Non-specific benefit of seasonal influenza vaccine on respiratory syncytial virus-hospitalisations in children: An instrumental variable approach using population-based data

Seasonal influenza vaccine is effective against influenza hospitalisations, but little is known about non-specific effects of the vaccine on other respiratory pathogens with similar seasonal patterns. We aimed to assess the causal impact of seasonal influenza vaccine on laboratory-confirmed hospitalisations for respiratory syncytial virus (RSV) in children using an instrumental variable strategy.

Determining the true incidence of seasonal respiratory syncytial virus-confirmed hospitalizations in preterm and term infants in Western Australia

Respiratory syncytial virus contributes to significant global infant morbidity and mortality. We applied a previously developed statistical prediction model incorporating pre-pandemic RSV testing data and hospital admission data to estimate infant RSV-hospitalizations by birth month and prematurity, focused on infants aged <1 year.

among children with pneumonia using a causal Bayesian network

Pneumonia remains a leading cause of hospitalization and death among young children worldwide, and the diagnostic challenge of differentiating bacterial from non-bacterial pneumonia is the main driver of antibiotic use for treating pneumonia in children. Causal Bayesian networks (BNs) serve as powerful tools for this problem as they provide clear maps of probabilistic relationships between variables and produce results in an explainable way by incorporating both domain expert knowledge and numerical data.