Ewan Cameron
Director of Malaria Risk Stratification
BSc PhD
With over a decade of international research experience spanning the fields of astronomy, statistics, machine learning and epidemiology, Dr Ewan Cameron returned to Australia in February 2020 as an Associate Professor at Curtin University and Honorary Research Associate at The Kids Research Institute Australia.
Within the Malaria Atlas Project, he leads a team responsible for the innovation of novel approaches to probabilistic disease mapping, with a focus on bespoke model development for sub-national risk stratification.
The outputs of this research support the work of the World Health Organisation (in particular with respect to the “High Burden, High Impact” project: ” a country-led response to reignite the pace of progress in the global malaria fight”), the Clinton Health Access Initiative, and the national malaria control programs of multiple endemic countries.
Projects
The STAMP RSV Program
STAMP-RSV is guided by a community reference group with lived experiences of RSV. The goal is to translate research findings into effective and efficient RSV control policies to reduce the health and economic burden of RSV.
July 2024
Modelling the COVID pandemic with the Geographical COVID-19 Model (GEO-COV)
Researchers have developed a new model for simulating covid-19 outbreaks in Western Australia.
Geospatial modelling for malaria risk stratification and intervention targeting for low-endemic countries
Geospatial modelling for malaria risk stratification and intervention targeting for high burden high impact countries
DETECT Schools
The DETECT-Schools Study was launched in May 2020 as a partnership between the WA Government Departments of Education and Health with The Kids Research Institute Australia.
July 2021
Published research
Fine-scale maps of malaria incidence to inform risk stratification in Laos
Malaria risk maps are crucial for controlling and eliminating malaria by identifying areas of varying transmission risk. In the Greater Mekong Subregion, these maps guide interventions and resource allocation. This article focuses on analysing changes in malaria transmission and developing fine-scale risk maps using five years of routine surveillance data in Laos (2017-2021). The study employed data from 1160 geolocated health facilities in Laos, along with high-resolution environmental data.
Geospatial joint modeling of vector and parasite serology to microstratify malaria transmission
The World Health Organization identifies a strong surveillance system for malaria and its mosquito vector as an essential pillar of the malaria elimination agenda. Anopheles salivary antibodies are emerging biomarkers of exposure to mosquito bites that potentially overcome sensitivity and logistical constraints of traditional entomological surveys.
A situational assessment of treatments received for childhood diarrhea in the Federal Republic of Nigeria
We assess progress towards improved case management of childhood diarrhea in Nigeria over a period of targeted health systems reform from 2013 to 2018. Individual and community data from three Demographic and Health Survey rounds are leveraged in a geospatial model designed for stratified estimation by venue of treatment seeking and State.
Trends in treatment-seeking for fever in children under five years old in 151 countries from 1990 to 2020
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.
A health inequality analysis of childhood asthma prevalence in urban Australia
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.
Statistical modelling under differential privacy constraints: a case study in fine-scale geographical analysis with Australian Bureau of Statistics TableBuilder data
Consistent with the principles of differential privacy protection, the Australian Bureau of Statistics artificially perturbs all count data from the Australian Census prior to its release to researchers through the TableBuilder platform. This perturbation involves the addition of random noise to every non-zero cell count followed by the suppression of small values to zero.
Impacts on Human Movement in Australian Cities Related to the COVID-19 Pandemic
No studies have yet examined high-resolution shifts in the spatial patterns of human movement in Australia throughout 2020 and 2021, a period coincident with the repeated enactment and removal of varied governmental restrictions aimed at reducing community transmission of SARS-CoV-2. We compared overlapping timeseries of COVID-19 pandemic-related restrictions, epidemiological data on cases and vaccination rates, and high-resolution human movement data to characterize population-level responses to the pandemic in Australian cities.
Childhood-onset type 1 diabetes in Western Australia: An update on incidence and temporal trends from 2001 to 2022
To determine the incidence and incidence trends over 2001-2022 of childhood-onset type 1 diabetes (T1D) in Western Australia and assess the impact of the COVID-19 pandemic.
Evaluating COVID-19-Related Disruptions to Effective Malaria Case Management in 2020–2021 and Its Potential Effects on Malaria Burden in Sub-Saharan Africa
The COVID-19 pandemic has led to far-reaching disruptions to health systems, including preventative and curative services for malaria. The aim of this study was to estimate the magnitude of disruptions in malaria case management in sub-Saharan Africa and their impact on malaria burden during the COVID-19 pandemic. We used survey data collected by the World Health Organization, in which individual country stakeholders reported on the extent of disruptions to malaria diagnosis and treatment.
Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions
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.
Spatiotemporal mapping of malaria incidence in Sudan using routine surveillance data
Malaria is a serious threat to global health, with over 95 % of the cases reported in 2020 by the World Health Organization in African countries, including Sudan. Sudan is a low-income country with a limited healthcare system and a substantial burden of malaria.
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.
A simulation study of disaggregation regression for spatial disease mapping
Disaggregation regression has become an important tool in spatial disease mapping for making fine-scale predictions of disease risk from aggregated response data.
Mapping malaria by sharing spatial information between incidence and prevalence data sets
As malaria incidence decreases and more countries move towards elimination, maps of malaria risk in low-prevalence areas are increasingly needed. For low-burden areas, disaggregation regression models have been developed to estimate risk at high spatial resolution from routine surveillance reports aggregated by administrative unit polygons.
Maps and metrics of insecticide-treated net access, use, and nets-per-capita in Africa from 2000-2020
Insecticide-treated nets (ITNs) are one of the most widespread and impactful malaria interventions in Africa, yet a spatially-resolved time series of ITN coverage has never been published. Using data from multiple sources, we generate high-resolution maps of ITN access, use, and nets-per-capita annually from 2000 to 2020 across the 40 highest-burden African countries.
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.
Indirect effects of the COVID-19 pandemic on malaria intervention coverage, morbidity, and mortality in Africa: a geospatial modelling analysis
Substantial progress has been made in reducing the burden of malaria in Africa since 2000, but those gains could be jeopardised if the COVID-19 pandemic affects the availability of key malaria control interventions. The aim of this study was to evaluate plausible effects on malaria incidence and mortality under different levels of disruption to malaria control.