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Research

Treatment Outcomes among Pregnant Patients with Multidrug-Resistant Tuberculosis: A Systematic Review and Meta-analysis

The management of multidrug-resistant tuberculosis (MDR-TB) during pregnancy is challenging, yet no systematic synthesis of evidence has accurately measured treatment outcomes.

Research

The Centres for Disease Control light trap and the human decoy trap compared to the human landing catch for measuring Anopheles biting in rural Tanzania

Vector mosquito biting intensity is an important measure to understand malaria transmission. Human landing catch (HLC) is an effective but labour-intensive, expensive, and potentially hazardous entomological surveillance tool. The Centres for Disease Control light trap (CDC-LT) and the human decoy trap (HDT) are exposure-free alternatives.

Research

Using open data and open-source software to develop spatial indicators of urban design and transport features for achieving healthy and sustainable cities

Benchmarking and monitoring of urban design and transport features is crucial to achieving local and international health and sustainability goals. However, most urban indicator frameworks use coarse spatial scales that either only allow between-city comparisons, or require expensive, technical, local spatial analyses for within-city comparisons.

Research

Breastfeeding in a COVID-19 world

The coronavirus disease 2019 (COVID-19) pandemic has changed the birthing and postnatal experience of women. This review highlights how policy changes have affected pregnant and breastfeeding women, the evidence for continued breastfeeding and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines, and how the pandemic's unexpected consequences have affected these women's wellbeing.

Research

Creating healthy and sustainable cities: what gets measured, gets done

Citation: Giles-Corti B, Moudon AV, Lowe M, Adlakha D, et al.. Creating healthy and sustainable cities: what gets measured, gets done. Lancet Global

Research

Consensus guidelines for antifungal stewardship, surveillance and infection prevention, 2021

Invasive fungal diseases (IFD) are serious infections associated with high mortality, particularly in immunocompromised patients. The prescribing of antifungal agents to prevent and treat IFD is associated with substantial economic burden on the health system, high rates of adverse drug reactions, significant drug-drug interactions and the emergence of antifungal resistance.

Research

Does a major change to a COVID-19 vaccine program alter vaccine intention? A qualitative investigation

On 8th April 2021, the Australian Technical Advisory Group on Immunisation (ATAGI) made the Pfizer-BioNtech (Comirnaty) vaccine the “preferred” vaccine for adults in Australia aged < 50 years due to a risk of thrombosis with thrombocytopenia syndrome (TTS) following AstraZeneca vaccination. We sought to understand whether this impacted COVID-19 vaccine intentions.

Research

Caregiver Psychological Distress Predicts Temperament and Social-Emotional Outcomes in Infants with Autism Traits

Child temperament and caregiver psychological distress have been independently associated with social-emotional difficulties among individuals with autism. However, the interrelationship among these risk factors has rarely been investigated.

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.