Search
Australian states and territories used test-trace-isolate-quarantine (TTIQ) systems extensively in their response to the COVID-19 pandemic in 2020-2021. We report on an analysis of Australian case data to estimate the impact of test-trace-isolate-quarantine systems on SARS-CoV-2 transmission.
Understanding how emerging infectious diseases spread within and between countries is essential to contain future pandemics. Spread to new areas requires connectivity between one or more sources and a suitable local environment, but how these two factors interact at different stages of disease emergence remains largely unknown.
Long-standing health inequalities in Australian society that were exposed by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic were described as "fault lines" in a recent call to action by a consortium of philanthropic organizations. With asthma a major contributor to childhood disease burden, studies of its spatial epidemiology can provide valuable insights into the emergence of health inequalities early in life.
Monitoring how the incidence of influenza infections changes over time is important for quantifying the transmission dynamics and clinical severity of influenza. Infection incidence is difficult to measure directly, and hence, other quantities which are more amenable to surveillance are used to monitor trends in infection levels, with the implicit assumption that they correlate with infection incidence.
Access to medical treatment for fever is essential to prevent morbidity and mortality in individuals and to prevent transmission of communicable febrile illness in communities. Quantification of the rates at which treatment is accessed is critical for health system planning and a prerequisite for disease burden estimates.
Studies have shown that stunting and wasting indicators are strongly correlated among children, with the potential of concurrently affecting their physical and cognitive development. However, the identification of subpopulations of children with varying risks of stunting and wasting could be valuable for targeted intervention.
Despite significant decline in the past two decades, malaria is still a major public health concern in Tanzania; with over 93% of the population still at risk. Community knowledge, attitudes and practices, and beliefs are key in enhancing uptake and utilization of malaria control interventions, but there is a lack of information on their contribution to effective control of the disease.
Geostatistical analysis of health data is increasingly used to model spatial variation in malaria prevalence, burden, and other metrics. Traditional inference methods for geostatistical modelling are notoriously computationally intensive, motivating the development of newer, approximate methods for geostatistical analysis or, more broadly, computational modelling of spatial processes.
Since 2004, malaria transmission on Bioko Island has declined significantly as a result of the scaling-up of control interventions. The aim of eliminating malaria from the Island remains elusive, however, underscoring the need to adapt control to the local context. Understanding the factors driving the risk of malaria infection is critical to inform optimal suits of interventions in this adaptive approach.
A random effects meta-analysis was used to estimate the pooled prevalence of HIV infection within minority indigenous populations of the South-East Asia (SEAR) and Western Pacific Regions (WPR). Sub-group analyses were conducted, and the sources of heterogeneity explored through meta-regression. The majority of studies were undertaken in high HIV risk subpopulations.