Nick Golding
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Nick Golding

Infectious Disease Dynamics Unit, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia

Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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30 June 2015 in eLife
Verified
Journal Article
Open access
MKMoritz Ug Kraemer
Moritz Ug Kraemer
MSMarianne E Sinka
Marianne E Sinka
KDKirsten A Duda
Kirsten A Duda
AMAdrian Qn Mylne
Adrian Qn Mylne
FSFreya M Shearer
Freya M Shearer
SHSimon Hay
Simon Hay
Dengue and chikungunya are increasing global public health concerns due to their rapid geographical spread and increasing disease burden. Knowledge of the contemporary distribution of their shared vectors, Aedes aegypti and Aedes albopictus remains incomplete and is complicated by an ongoing range expansion fuelled by increased global trade and travel. Mapping the global distribution of these vectors and the geographical determinants of their ranges is essential for public health planning. Here we compile the largest contemporary database for both species and pair it with relevant environmental variables predicting their global distribution. We show Aedes distributions to be the widest ever recorded; now extensive in all continents, including North America and Europe. These maps will help define the spatial limits of current autochthonous transmission of dengue and chikungunya viruses. It is only with this kind of rigorous entomological baseline that we can hope to project future health impacts of these viruses.

10 June 2019 in Nature Microbiology
Verified
Journal Article
Open access
PDF file
Janey MessinaJaney Messina
Janey Messina
OBOliver J. Brady
Oliver J. Brady
NGNick Golding
Nick Golding
MKMoritz U. G. Kraemer
Moritz U. G. Kraemer
GWG. R. William Wint
G. R. William Wint
SHSimon Hay
Simon Hay
Dengue is a mosquito-borne viral infection that has spread throughout the tropical world over the past 60 years and now affects over half the world’s population. The geographical range of dengue is expected to further expand due to ongoing global phenomena including climate change and urbanization. We applied statistical mapping techniques to the most extensive database of case locations to date to predict global environmental suitability for the virus as of 2015. We then made use of climate, population and socioeconomic projections for the years 2020, 2050 and 2080 to project future changes in virus suitability and human population at risk. This study is the first to consider the spread of Aedes mosquito vectors to project dengue suitability. Our projections provide a key missing piece of evidence for the changing global threat of vector-borne disease and will help decision-makers worldwide to better prepare for and respond to future changes in dengue risk.

4 March 2019 in Nature Microbiology
Verified
Journal Article
Open access
PDF file
MKMoritz U. G. Kraemer
Moritz U. G. Kraemer
RRRobert C. Reiner
Robert C. Reiner
OBOliver J. Brady
Oliver J. Brady
JMJane P. Messina
Jane P. Messina
MGMarius Gilbert
Marius Gilbert
NGNick Golding
Nick Golding
The global population at risk from mosquito-borne diseases—including dengue, yellow fever, chikungunya and Zika—is expanding in concert with changes in the distribution of two key vectors:Aedes aegyptiandAedes albopictus. The distribution of these species is largely driven by both human movement and the presence of suitable climate. Using statistical mapping techniques, we show that human movement patterns explain the spread of both species in Europe and the United States following their introduction. We find that the spread ofAe. aegyptiis characterized by long distance importations, whileAe. albopictushas expanded more along the fringes of its distribution. We describe these processes and predict the future distributions of both species in response to accelerating urbanization, connectivity and climate change. Global surveillance and control efforts that aim to mitigate the spread of chikungunya, dengue, yellow fever and Zika viruses must consider the so far unabated spread of these mosquitos. Our maps and predictions offer an opportunity to strategically target surveillance and control programmes and thereby augment efforts to reduce arbovirus burden in human populations globally.

11 January 2016 in Nature Microbiology
Verified
Journal Article
Open access
PDF file
Direk LimmathurotsakulDirek Limmathurotsakul
Direk Limmathurotsakul
NGNick Golding
Nick Golding
David DanceDavid Dance
David Dance
JMJane P. Messina
Jane P. Messina
DPDavid M. Pigott
David M. Pigott
SHSimon Hay
Simon Hay
Burkholderia pseudomallei, a highly pathogenic bacterium that causes melioidosis, is commonly found in soil in Southeast Asia and Northern Australia1,2. Melioidosis can be difficult to diagnose due to its diverse clinical manifestations and the inadequacy of conventional bacterial identification methods3. The bacterium is intrinsically resistant to a wide range of antimicrobials, and treatment with ineffective antimicrobials may result in case fatality rates (CFRs) exceeding 70%4,5. The importation of infected animals has, in the past, spread melioidosis to non-endemic areas6,7. The global distribution of B. pseudomallei and the burden of melioidosis, however, remain poorly understood. Here, we map documented human and animal cases and the presence of environmental B. pseudomallei and combine this in a formal modelling framework8–10 to estimate the global burden of melioidosis. We estimate there to be 165,000 (95% credible interval 68,000–412,000) human melioidosis cases per year worldwide, from which 89,000 (36,000–227,000) people die. Our estimates suggest that melioidosis is severely underreported in the 45 countries in which it is known to be endemic and that melioidosis is probably endemic in a further 34 countries that have never reported the disease. The large numbers of estimated cases and fatalities emphasize that the disease warrants renewed attention from public health officials and policy makers.

19 May 2014 in Methods in Ecology and Evolution
Verified
Journal Article
Open access
PDF file
LPLj Pollock
Lj Pollock
RTR Tingley
R Tingley
WMWk Morris
Wk Morris
NGN Golding
N Golding
RORb O'Hara
Rb O'Hara
MMMA McCarthy
MA McCarthy
Summary: A primary goal of ecology is to understand the fundamental processes underlying the geographic distributions of species. Two major strands of ecology – habitat modelling and community ecology – approach this problem differently. Habitat modellers often use species distribution models (SDMs) to quantify the relationship between species’ and their environments without considering potential biotic interactions. Community ecologists, on the other hand, tend to focus on biotic interactions and, in observational studies, use co‐occurrence patterns to identify ecological processes. Here, we describe a joint species distribution model (JSDM) that integrates these distinct observational approaches by incorporating species co‐occurrence data into a SDM. JSDMs estimate distributions of multiple species simultaneously and allow decomposition of species co‐occurrence patterns into components describing shared environmental responses and residual patterns of co‐occurrence. We provide a general description of the model, a tutorial and code for fitting the model in R. We demonstrate this modelling approach using two case studies: frogs and eucalypt trees in Victoria, Australia. Overall, shared environmental correlations were stronger than residual correlations for both frogs and eucalypts, but there were cases of strong residual correlation. Frog species generally had positive residual correlations, possibly due to the fact these species occurred in similar habitats that were not fully described by the environmental variables included in the JSDM. Eucalypt species that interbreed had similar environmental responses but had negative residual co‐occurrence. One explanation is that interbreeding species may not form stable assemblages despite having similar environmental affinities. Environmental and residual correlations estimated from JSDMs can help indicate whether co‐occurrence is driven by shared environmental responses or other ecological or evolutionary process (e.g. biotic interactions), or if important predictor variables are missing. JSDMs take into account the fact that distributions of species might be related to each other and thus overcome a major limitation of modelling species distributions independently.

12 December 2013 in Parasites & Vectors
Verified
Journal Article
Open access
PDF file
OBOliver J Brady
Oliver J Brady
MJMichael A Johansson
Michael A Johansson
CGCarlos A Guerra
Carlos A Guerra
SBSamir Bhatt
Samir Bhatt
NGNick Golding
Nick Golding
SHSimon Hay
Simon Hay
The survival of adult female Aedes mosquitoes is a critical component of their ability to transmit pathogens such as dengue viruses. One of the principal determinants of Aedes survival is temperature, which has been associated with seasonal changes in Aedes populations and limits their geographical distribution. The effects of temperature and other sources of mortality have been studied in the field, often via mark-release-recapture experiments, and under controlled conditions in the laboratory. Survival results differ and reconciling predictions between the two settings has been hindered by variable measurements from different experimental protocols, lack of precision in measuring survival of free-ranging mosquitoes, and uncertainty about the role of age-dependent mortality in the field.