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Professor Nick Golding

Honorary Research Fellow

Nick Golding

Head, Infectious Disease Ecology & Modelling and Honorary Research Fellow

BSc DPhil

nick.golding@thekids.org.au

Professor Nick Golding is an infectious disease modeller with a focus on globally-important pathogens. His work combines mathematical and statistical modelling, ecology, and public health. Since completing a PhD on modelling mosquito-borne diseases at the University of Oxford, he has collaborated with epidemiologists from around the world developing models and maps of the risk posed by some of the world’s most important and neglected diseases – including malaria, Dengue fever, Chikungunya, and Ebola.

After moving to the University of Melbourne in 2016, Professor Golding has worked closely with ecologists both on modelling methods and on urgent health issues like Melbourne’s Buruli ulcer outbreak – where risk to humans depends on the ecology of mosquitos and possums. In 2020 Professor Golding joined the Malaria Atlas Project at The Kids Research Institute Australia as Director of Malaria Ecology. He is a member of the Australian national modelling team, advising national and state governments on their response to COVID-19 throughout the pandemic.

Projects

Geospatial analysis of Japanese Encephalitis virus (JEV) transmission risk

Japanese Encephalitis virus is a mosquito-borne virus that is typically only found in south-east Asia.

The Vector Atlas

The Vector Atlas aims to update and create vector species maps and spatial products that improve disease prediction, mitigation and preparedness.

Finding new, safer and targeted therapies for paediatric brain cancer that amplify responses to radiation therapy

Radiation therapy is an essential component of brain cancer treatment. However, the high doses currently required are extremely damaging to the growing brains and bodies of children.

Developing and characterising juvenile models of aggressive paediatric brain cancers for the evaluation of novel immunotherapies.

While profound treatment responses have been realised using immunotherapy for some cancer types, this is yet to be seen for paediatric brain cancer patients.

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. 

Measuring how a disease outbreak could spread in WA

Modelling to support Australia's COVID-19 response

Published research

Opportunities to strengthen respiratory virus surveillance systems in Australia: lessons learned from the COVID-19 response

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.

Mapping the distribution of Nipah virus infections: a geospatial modelling analysis

Nipah virus is a zoonotic paramyxovirus responsible for disease outbreaks with high fatality rates in south and southeast Asia. However, knowledge of the potential geographical extent and risk patterns of the virus is poor. We aimed to establish an integrated spatiotemporal and phylogenetic database of Nipah virus infections in humans and animals across south and southeast Asia. 

Spatio-temporal spread of artemisinin resistance in Southeast Asia

Current malaria elimination targets must withstand a colossal challenge-resistance to the current gold standard antimalarial drug, namely artemisinin derivatives. If artemisinin resistance significantly expands to Africa or India, cases and malaria-related deaths are set to increase substantially.

Estimating the impact of test–trace–isolate–quarantine systems on SARS-CoV-2 transmission in Australia

Australian states and territories used test-trace-isolate-quarantine (TTIQ) systems extensively in their response to the COVID-19 pandemic in 2020-2021. We report on an analysis of Australian case data to estimate the impact of test-trace-isolate-quarantine systems on SARS-CoV-2 transmission. 

The global distribution and the risk prediction of relapsing fever group Borrelia: a data review with modelling analysis

The recent discovery of emerging relapsing fever group Borrelia (RFGB) species, such as Borrelia miyamotoi, poses a growing threat to public health. However, the global distribution and associated risk burden of these species remain uncertain. We aimed to map the diversity, distribution, and potential infection risk of RFGB. 

Estimating measures to reduce the transmission of SARS-CoV-2 in Australia to guide a ‘National Plan’ to reopening

The availability of COVID-19 vaccines promised a reduction in the severity of disease and relief from the strict public health and social measures (PHSMs) imposed in many countries to limit spread and burden of COVID-19. We were asked to define vaccine coverage thresholds for Australia's transition to easing restrictions and reopening international borders. 

Introduction of Aedes aegypti mosquitoes carrying wAlbB Wolbachia sharply decreases dengue incidence in disease hotspots

Partial replacement of resident Aedes aegypti mosquitoes with introduced mosquitoes carrying certain strains of inherited Wolbachia symbionts can result in transmission blocking of dengue and other viruses of public health importance. Wolbachia strain wAlbB is an effective transmission blocker and stable at high temperatures, making it particularly suitable for hot tropical climates.

Comparison of new computational methods for spatial modelling of malaria

Geostatistical analysis of health data is increasingly used to model spatial variation in malaria prevalence, burden, and other metrics. Traditional inference methods for geostatistical modelling are notoriously computationally intensive, motivating the development of newer, approximate methods for geostatistical analysis or, more broadly, computational modelling of spatial processes.

COVID-19 vaccine coverage targets to inform reopening plans in a low incidence setting

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.

Statistical modeling based on structured surveys of Australian native possum excreta harboring Mycobacterium ulcerans predicts Buruli ulcer occurrence in humans

Buruli ulcer (BU) is a neglected tropical disease caused by infection of subcutaneous tissue with Mycobacterium ulcerans. BU is commonly reported across rural regions of Central and West Africa but has been increasing dramatically in temperate southeast Australia around the major metropolitan city of Melbourne, with most disease transmission occurring in the summer months.

A modelling approach to estimate the transmissibility of SARS-CoV 2 during periods of high, low, and zero case incidence

Against a backdrop ofwidespread global transmission, a number of countries have successfully brought large outbreaks of COVID-19 under control and maintained near-elimination status. A key element of epidemic response is the tracking of disease transmissibility in near real-time. During major out-breaks, the effective reproduction number can be estimated froma time-series of case, hospitalisation or death counts. In low or zero incidence settings, knowing the potential for the virus to spread is a response priority.

A fractional land use change model for ecological applications

By mapping land use under projections of socio-economic change, ecological changes can be predicted to inform conservation decision-making. We present a land use model that enables the fine-scale mapping of land use change under future scenarios. Its predictions can be used as input to virtually all existing spatially-explicit ecological models.

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.

Education and Qualifications
  • BSc (Hons) – Liverpool John Moores University
  • DPhil – University of Oxford