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During winter months of temperate regions, concurrent epidemics of multiple respiratory pathogens can occur, causing periods of increased clinical burden. Case time series, which are predominantly used to monitor infection levels, can exhibit substantial noise and day-of-the-week effects, limiting the visual interpretation of trends in raw data.
In the austral summer of 2021-2022, Australia experienced an unprecedented Japanese encephalitis virus (JEV) outbreak, with detections over 3000 km south of previous occurrences. Given the limited knowledge of JEV transmission ecology in Australia, we developed geospatial models of transmission risk to support the public health response. We created time-varying habitat suitability models for suspected mosquito vectors and ardeid hosts using month-scaled occurrence and covariate data from 2000-2023.
Since the emergence of SARS-CoV-2 in 2019 through to mid-2021, much of the Australian population lived in a COVID-19-free environment. This followed the broadly successful implementation of a strong suppression strategy, including international border closures. With the availability of COVID-19 vaccines in early 2021, the national government sought to transition from a state of minimal incidence and strong suppression activities to one of high vaccine coverage and reduced restrictions but with still-manageable transmission.
Despite the large body of research on missing value distributions and imputation, there is comparatively little literature with a focus on how to make it easy to handle, explore, and impute missing values in data. This paper addresses this gap. The new methodology builds upon tidy data principles, with the goal of integrating missing value handling as a key part of data analysis workflows.
The ACEFA NHMRC Centre of Research Excellence aims to support the timely, effective response to epidemic diseases in Australia through real-time data analytics, modelling, and forecasting.
Japanese Encephalitis virus is a mosquito-borne virus that is typically only found in south-east Asia.
Following widespread exposure to Omicron variants, SARS-CoV-2 has transitioned to endemic circulation. Populations now have diverse infection and vaccination histories, resulting in heterogeneous immune landscapes. Careful consideration of the value of ongoing vaccination is required through the post-Omicron phase of COVID-19 management to minimise disease burden.
Contact tracing is an important public health measure used to reduce transmission of infectious diseases. Contact tracers typically conduct telephone interviews with cases to identify contacts and direct them to quarantine, with the aim of preventing onward transmission. However, in situations where caseloads exceed the capacity of the public health system, timely interviews may not be feasible for all cases. Here we present a modelling framework for assessing the impact of different case interview prioritisation strategies on disease transmission.
Disease surveillance data was critical in supporting public health decisions throughout the coronavirus disease 2019 (COVID-19) pandemic. At the same time, the unprecedented circumstances of the pandemic revealed many shortcomings of surveillance systems for viral respiratory pathogens. Strengthening of surveillance systems was identified as a priority for the recently established Australian Centre for Disease Control, which represents a critical opportunity to review pre-pandemic and pandemic surveillance practices, and to decide on future priorities, during both pandemic and inter-pandemic periods.
Children are more vulnerable than adults to climate-related health threats, but reviews examining how climate change affects human health have been mainly descriptive and lack an assessment of the magnitude of health effects children face. This is the first systematic review and meta-analysis that identifies which climate-health relationships pose the greatest threats to children.