Skip to content
The Kids Research Institute Australia logo
Donate

No results yet

Search

Research

Built Environments and Child Health: A Policy Review’, Life Course Centre Working Paper Series, 2021-22

Childhood obesity is one of the most serious public health challenges of the 21st century and is affected not only by individual choice but also by societal and environmental influences. Childhood obesity is higher in children living in regional and remote compared with major cities, in one-parent families and for those with a disability.

Research

Projected health impact of post-discharge malaria chemoprevention among children with severe malarial anaemia in Africa

Children recovering from severe malarial anaemia (SMA) remain at high risk of readmission and death after discharge from hospital. However, a recent trial found that post-discharge malaria chemoprevention (PDMC) with dihydroartemisinin-piperaquine reduces this risk. We developed a mathematical model describing the daily incidence of uncomplicated and severe malaria requiring readmission among 0-5-year old children after hospitalised SMA.

Research

WALLABY Pilot Survey: H i gas kinematics of galaxy pairs in cluster environment

We examine the H i gas kinematics of galaxy pairs in two clusters and a group using Australian Square Kilometre Array Pathfinder (ASKAP) WALLABY pilot survey observations. We compare the H i properties of galaxy pair candidates in the Hydra I and Norma clusters, and the NGC 4636 group, with those of non-paired control galaxies selected in the same fields.

Research

Geospatial modelling for malaria risk stratification and intervention targeting for low-endemic countries

Ewan Punam Susan Tasmin Cameron Amratia Rumisha Symons BSc PhD PhD PhD (Biostatistics) Director of Malaria Risk Stratification Honorary Research

Research

Reconstructing the early global dynamics of under-ascertained COVID-19 cases and infections

Asymptomatic or subclinical SARS-CoV-2 infections are often unreported, which means that confirmed case counts may not accurately reflect underlying epidemic dynamics. Understanding the level of ascertainment (the ratio of confirmed symptomatic cases to the true number of symptomatic individuals) and undetected epidemic progression is crucial to informing COVID-19 response planning, including the introduction and relaxation of control measures.

Research

Mapping the endemicity and seasonality of clinical malaria for intervention targeting in Haiti using routine case data

Towards the goal of malaria elimination on Hispaniola, the National Malaria Control Program of Haiti and its international partner organisations are conducting a campaign of interventions targeted to high-risk communities prioritised through evidence-based planning. Here we present a key piece of this planning: an up-to-date, fine-scale endemicity map and seasonality profile for Haiti informed by monthly case counts.

Research

Seroprevalence and associated risk factors of chikungunya, dengue, and Zika in eight districts in Tanzania

This study was conducted to determine the seroprevalence and risk factors of chikungunya (CHIKV), dengue (DENV), and Zika (ZIKV) viruses in Tanzania.

Research

WALLABY pre-pilot survey: Two dark clouds in the vicinity of NGC 1395

We present the Australian Square Kilometre Array Pathfinder (ASKAP) WALLABY pre-pilot observations of two 'dark' H i sources (with H i masses of a few times 108 {M}_\odot and no known stellar counterpart) that reside within 363 kpc of NGC 1395, the most massive early-type galaxy in the Eridanus group of galaxies.

Research

Modelling temperature-driven changes in species associations across freshwater communities

Due to global climate change–induced shifts in species distributions, estimating changes in community composition through the use of Species Distribution Models has become a key management tool. Being able to determine how species associations change along environmental gradients is likely to be pivotal in exploring the magnitude of future changes in species’ distributions.

Research

Emulator-based Bayesian optimization for efficient multi-objective calibration of an individual-based model of malaria

Individual-based models have become important tools in the global battle against infectious diseases, yet model complexity can make calibration to biological and epidemiological data challenging. We propose using a Bayesian optimization framework employing Gaussian process or machine learning emulator functions to calibrate a complex malaria transmission simulator.