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Children with chronic medical conditions are at higher risk of invasive pneumococcal disease (IPD), but little is known about the effectiveness of the primary course of pneumococcal conjugate vaccine (PCV) in these children.
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.
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.
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.
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.
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.
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.
The need for coronavirus 2019 (COVID-19) vaccination in different age groups and populations is a subject of great uncertainty and an ongoing global debate. Critical knowledge gaps regarding COVID-19 vaccination include the duration of protection offered by different priming and booster vaccination regimens in different populations, including homologous or heterologous schedules.
Previous Australian studies have shown that delayed vaccination with each of the three primary doses of diphtheria-tetanus-pertussis-containing vaccines (DTP) is up to 50 % in certain subpopulations. We estimated the excess burden of pertussis that might have been prevented if (i) all primary doses and (ii) each dose was given on time.