Michele Nguyen

Michele Nguyen
Nanyang Technological University | ntu · Lee Kong Chian School of Medicine (LKCSoM)

Doctor of Philosophy

About

30
Publications
14,739
Reads
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1,649
Citations
Introduction
My research focuses on sustainability and health analytics. In particular, I use spatiotemporal statistical modelling and extreme value modelling to inform planning and resource allocation.
Additional affiliations
December 2022 - December 2024
Nanyang Technological University
Position
  • Lecturer
October 2019 - November 2022
Nanyang Technological University
Position
  • Instructor
October 2019 - November 2022
Nanyang Technological University
Position
  • Research Fellow
Education
September 2013 - September 2017
Independent Researcher
Independent Researcher
Field of study
  • Statistics
October 2012 - October 2013
University of Oxford
Field of study
  • Applied Statistics
October 2009 - October 2012
Independent Researcher
Independent Researcher
Field of study
  • Mathematics with Statistics

Publications

Publications (30)
Article
Full-text available
Extreme events such as natural and economic disasters leave lasting impacts on society and motivate the analysis of extremes from data. While classical statistical tools based on Gaussian distributions focus on average behaviour and can lead to persistent biases when estimating extremes, extreme value theory (EVT) provides the mathematical foundati...
Article
Full-text available
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. In this study, national da...
Article
Full-text available
Coastal land can be lost at rapid rates due to relative sea-level rise (RSLR) resulting from local land subsidence. However, the comparative severity of local land subsidence is unknown due to high spatial variabilities and difficulties reconciling observations across localities. Here we provide self-consistent, high spatial resolution relative loc...
Preprint
Full-text available
Extreme events such as natural and economic disasters leave lasting impacts on society and motivate the analysis of extremes from data. While classical statistical tools based on Gaussian distributions focus on average behaviour and can lead to persistent biases when estimating extremes, extreme value theory (EVT) provides the mathematical foundati...
Article
Full-text available
This is a contributing paper to the UN Office for Disaster Risk Reduction Global Assessment Report 2022. Also downloadable at: https://hdl.handle.net/10356/153502 ------------------ The goal of Disaster Risk Management (DRM) is to ensure that society continues to function, thrive, and recover quickly despite shocks arising from natural or human ac...
Article
Full-text available
Understanding the temporal dynamics of mosquito populations underlying vector-borne disease transmission is key to optimizing control strategies. Many questions remain surrounding the drivers of these dynamics and how they vary between species—questions rarely answerable from individual entomological studies (that typically focus on a single locati...
Article
Full-text available
Although previous evidence suggests that the infection fatality rate from COVID-19 varies by age and sex, and that transmission intensity varies geographically within countries, no study has yet explored the age-sex-space distribution of excess mortality associated with the COVID pandemic. By applying the principles of small-area estimation to exis...
Preprint
Full-text available
Coastal land is being lost worldwide at an alarming rate due to relative sea-level rise (RSLR) resulting from vertical land motion (VLM). This problem is understudied at a global scale, due to high spatial variability and difficulties reconciling VLM between regions. Here we provide self-consistent, high spatial resolution VLM observations derived...
Article
Full-text available
Probabilistic loss assessments from natural hazards require the quantification of structural vulnerability. Building damage data can be used to estimate fragility curves to obtain realistic descriptions of the relationship between a hazard intensity measure and the probability of exceeding certain damage grades. Fragility curves based on the lognor...
Preprint
Full-text available
Although previous evidence suggests that the infection fatality rate from COVID-19 varies by age and sex, and that transmission intensity varies geographically within countries, no study has yet explored the age-sex-space distribution of excess mortality associated with the COVID pandemic. By applying the principles of small-area estimation to exis...
Article
Full-text available
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. However...
Preprint
Full-text available
Understanding the temporal dynamics (including the start, duration and end) of malaria transmission is key to optimising various control strategies, enabling interventions to be deployed at times when they can have the most impact. This temporal profile of malaria risk is intimately related to the dynamics of the mosquito populations underlying tra...
Article
Full-text available
Background: Anti-malarial drugs play a critical role in reducing malaria morbidity and mortality, but their role is mediated by their effectiveness. Effectiveness is defined as the probability that an anti-malarial drug will successfully treat an individual infected with malaria parasites under routine health care delivery system. Anti-malarial dr...
Article
Full-text available
Background: Many malaria-endemic areas experience seasonal fluctuations in case incidence as Anopheles mosquito and Plasmodium parasite life cycles respond to changing environmental conditions. Identifying location-specific seasonality characteristics is useful for planning interventions. While most existing maps of malaria seasonality use fixed t...
Article
Full-text available
Individual malaria infections can carry multiple strains of Plasmodium falciparum with varying levels of relatedness. Yet, how local epidemiology affects the properties of such mixed infections remains unclear. Here, we develop an enhanced method for strain deconvolution from genome sequencing data, which estimates the number of strains, their prop...
Article
Full-text available
Background: Since 2000, the scale-up of malaria control interventions has substantially reduced morbidity and mortality caused by the disease globally, fuelling bold aims for disease elimination. In tandem with increased availability of geospatially resolved data, malaria control programmes increasingly use high-resolution maps to characterise spa...
Article
Full-text available
Background: Plasmodium vivax exacts a significant toll on health worldwide, yet few efforts to date have quantified the extent and temporal trends of its global distribution. Given the challenges associated with the proper diagnosis and treatment of P vivax, national malaria programmes-particularly those pursuing malaria elimination strategies-req...
Preprint
Many malaria-endemic areas experience seasonal fluctuations in case incidence as Anopheles mosquito and Plasmodium parasite life cycles respond to changing environmental conditions. While most existing maps of malaria seasonality use fixed thresholds of rainfall, temperature, and/or vegetation indices to identify suitable transmission months, we de...
Preprint
Full-text available
Maps of infection risk are a vital tool for the elimination of malaria. Routine surveillance data of malaria case counts, often aggregated over administrative regions, is becoming more widely available and can better measure low malaria risk than prevalence surveys. However, aggregation of case counts over large, heterogeneous areas means that thes...
Article
Full-text available
BACKGROUND: Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used...
Article
Full-text available
Background: The Malaria Atlas Project (MAP) has worked to assemble and maintain a global open-access database of spatial malariometric data for over a decade. This data spans various formats and topics, including: geo-located surveys of malaria parasite rate; global administrative boundary shapefiles; and global and regional rasters representing t...
Preprint
Full-text available
Individuals infected with the Plasmodium falciparum malaria parasite can carry multiple strains with varying levels of relatedness. Yet, how parameters of local epidemiology and the biology of transmission affect the rate and relatedness of such mixed infections remains unclear. Here, we develop an enhanced method for strain deconvolution from geno...
Article
Full-text available
While short-range dependence is widely assumed in the literature for its simplicity, long-range dependence is a feature that has been observed in data from finance, hydrology, geophysics and economics. In this paper, we extend a L\'evy-driven spatio-temporal Ornstein-Uhlenbeck process by randomly varying its rate parameter to model both short-range...
Preprint
While short-range dependence is widely assumed in the literature for its simplicity, long-range dependence is a feature that has been observed in data from finance, hydrology, geophysics and economics. In this paper, we extend a L\'evy-driven spatio-temporal Ornstein-Uhlenbeck process by randomly varying its rate parameter to model both short-range...
Article
Full-text available
We compare two ways of constructing confidence intervals for the moments-matching parameter estimates of a Gaussian spatio-temporal Ornstein-Uhlenbeck process. It was found that those obtained via pairwise likelihood approximations had lower coverages and were more prone to the curse of dimensionality as opposed to those from a parametric bootstrap...
Article
Spatial heteroskedasticity has been observed in many spatial data applications such as air pollution and vegetation. We propose a model, the volatility modulated moving average, to account for changing variances across space. This stochastic process is driven by Gaussian noise and involves a stochastic volatility field. It is conditionally non-stat...
Preprint
Spatial heteroskedasticity refers to stochastically changing variances and covariances in space. Such features have been observed in, for example, air pollution and vegetation data. We study how volatility modulated moving averages can model this by developing theory, simulation and statistical inference methods. For illustration, we also apply our...
Article
Tempo-spatial modelling is an increasingly popular topic in Statistics. Our paper contributes to this line of research by developing the theory, simulation and inference methods for the tempo-spatial Ornstein-Uhlenbeck (TSOU) process. We derive important theoretical properties of TSOU processes, construct suitable simulation algorithms and develop...

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