Search
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.
Influenza and COVID-19 infections during pregnancy may have serious adverse consequences for women as well as their infants. However, uptake of influenza and COVID-19 vaccines during pregnancy remains suboptimal. This study aims to assess the effectiveness of a multi-component nudge intervention to improve influenza and COVID-19 vaccine uptake among pregnant women.
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.
Tuberculosis (TB) is the leading infectious cause of death globally. Several preventive measures are employed to prevent TB, yet there is a paucity of evidence on the effectiveness of these interventions. Therefore, this study aimed to identify the most effective interventions for reducing TB incidence.
Vaccination in pregnancy is the best strategy to reduce complications from influenza or pertussis infection in infants who are too young to be protected directly from vaccination. Pregnant women are also at risk of influenza complications preventable through antenatal vaccination. Both vaccines are funded under the National Immunisation Program for pregnant women in Australia, but coverage is not routinely reported nationally.
The global population has been severely affected by the coronavirus disease 2019 (COVID-19) pandemic, however, with older age identified as a risk factor, children have been underprioritized. This article discusses the factors contributing to the less severe response observed in children following infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), including, differing viral entry receptor expression and immune responses.
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.
COVID-19 is a new multi-organ disease causing considerable worldwide morbidity and mortality. While many recognized pathophysiological mechanisms are involved, their exact causal relationships remain opaque. Better understanding is needed for predicting their progression, targeting therapeutic approaches, and improving patient outcomes. While many mathematical causal models describe COVID-19 epidemiology, none have described its pathophysiology.
Group A Streptococcus causes a wide range of diseases from relatively mild infections including pharyngitis to more severe illnesses such as invasive diseases and rheumatic heart disease (RHD). Our aim is to estimate the cost-effectiveness of a hypothetical Strep A vaccine on multiple disease manifestations at the global-level.
The impact of pneumococcal conjugate vaccines (PCVs) on pneumonia in children is well-documented but data on 23-valent pneumococcal polysaccharide vaccine (PPV23) are lacking. Between 2001 and 2011, Indigenous children in Western Australia (WA) were recommended to receive PPV23 at 18-24 months of age following 3 doses of 7-valent PCV. We evaluated the incremental effectiveness of PPV23 against pneumonia hospitalisation.