Skip to content
The Kids Research Institute Australia logo
Donate

No results yet

Search

Research

Spatial distribution of rotavirus immunization coverage in Ethiopia: a geospatial analysis using the Bayesian approach

Rotavirus causes substantial morbidity and mortality every year, particularly among under-five children. Despite Rotavirus immunization preventing severe diarrheal disease in children, the vaccination coverage remains inadequate in many African countries including Ethiopia.

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

Viral haemorrhagic fevers and malaria co-infections among febrile patients seeking health care in Tanzania

In recent years there have been reports of viral haemorrhagic fever (VHF) epidemics in sub-Saharan Africa where malaria is endemic. VHF and malaria have overlapping clinical presentations making differential diagnosis a challenge.

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.

Research

A Maximum Entropy Model of the Distribution of Dengue Serotype in Mexico

Pathogen strain diversity is an important driver of the trajectory of epidemics. The role of bioclimatic factors on the spatial distribution of dengue virus serotypes has, however, not been previously studied. Hence, we developed municipality-scale environmental suitability maps for the four dengue virus serotypes using maximum entropy modeling.

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

Comodity forecasting

Project description This project support the development of 10-year global forecasts of nets, insecticides, diagnostics, and treatments for malaria

Research

Risk factors associated with post-tuberculosis sequelae: a systematic review and meta-analysis

Post-tuberculosis (TB) sequelae present a significant challenge in the management of TB survivors, often leading to persistent health issues even after successful treatment. Identifying risk factors associated with post-TB sequelae is important for improving outcomes and quality of life of TB survivors. This systematic review and meta-analysis aims to identify risk factors associated with long-term physical sequelae among TB survivors.

Research

Individual variation in vaccine immune response can produce bimodal distributions of protection

The ability for vaccines to protect against infectious diseases varies among individuals, but computational models employed to inform policy typically do not account for this variation. Here we examine this issue: we implement a model of vaccine efficacy developed in the context of SARS-CoV-2 in order to evaluate the general implications of modelling correlates of protection on the individual level.