Kerrie Mengersen
Dados Biográficos
| ID | 1751099 |
|---|---|
| NOME | Kerrie Mengersen |
| PRENOMES | Kerrie |
| SOBRENOME | Mengersen |
| ASSINATURA | MENGERSEN K |
| AFILIAÇÕES | Queensland University of Technology |
| ORCID | 0000-0001-8625-9168 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 19 |
| TOTAL DE CITAÇÕES | 10 |
| TOTAL COMO AUTOR | 19 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2000 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2026 |
| ÍNDICE H | 2 |
Extracting and communicating insights about geographical patterns from spatiotemporal disease models
Spatiotemporal modelling is increasingly employed to understand how geographic patterns of disease vary over time; however, most studies report minimal information, often neglecting uncertainty altogether. This represents a missed opportunity to understand changes in disease risk at a fine granularity and to provide a valuable, actionable evidence base. This study describes generalisable methods for extracting key metrics from the outputs of Baye…
A data-informed multidimensional composite score for stress assessment
Occupations such as the military, emergency responders, and athletes demand acute physical, cognitive and psychosocial effort. Individuals in these roles face task-specific stressors, including extreme heat, sustained mental focus and performance under social pressure, resulting in variable stress responses. Comparing individual stress responses is challenging due to the complex physiological, cognitive, and emotional interactions. This study pre…
Practical guidelines for Indigenous research
This article presents an Indigenous research methodology developed in the context of a case study to better understand data literacy within our local Indigenous Australian community. For too long Indigenous peoples have been the subjects, rather than the producers, of data-focused research. By adopting this approach in our case study, we identified practical guidelines for conducting best-practice Indigenous research in our own local community. R…
Patterns of educational performance among Indigenous students in Australia, 2010–2019
Data reporting in the Australian education system produces deficit-based comparisons of academic achievement between Indigenous and non-Indigenous students. Since 2009, data from the National Assessment Program – Literacy and Numeracy (NAPLAN) have been used by the Australian government to allow it to report on ‘Closing the Gap’ policy. These data are used to justify government-funded initiatives designed to improve educational outcomes for Indig…
Creating area level indices of behaviours impacting cancer in Australia with a Bayesian generalised shared component model
This study develops a model-based index approach called the Generalised Shared Component Model (GSCM) by drawing on the large field of factor models. The proposed fully Bayesian approach accommodates heteroscedastic model error, multiple shared factors and flexible spatial priors. Moreover, unlike previous index approaches, our model provides indices with uncertainty. Focusing on unhealthy behaviors that increase the risk of cancer, the proposed …
Age- and Gender-Specific Differences in the Seasonal Distribution of Diabetes Mortality in Shandong, China
Diabetes mortality in Shandong is higher than the national average in China. This study first explored diabetes mortality variation spatially at the county/district level among adults aged over 30 years in terms of age and gender, specifically by season. Daily diabetes mortality data were collected from 31 mortality surveillance points across Shandong Province in 2014. A geographic information system, spatial kriging interpolation and a spatial c…
Spatial statistical machine learning models to assess the relationship between development vulnerabilities and educational factors in children in Queensland, Australia
This study confirmed that it is important to take into account the spatial nature of data when fitting statistical machine learning models. A new spatial random forest model was introduced and was shown to explain more of the spatial variation and provide a better model fit in the case study of development vulnerabilities among children in Queensland. At small-area population level, increased attendance at preschool was strongly associated with r…
Bayesian spatial survival modelling for dengue fever in Makassar, Indonesia
OBJECTIVE: To understand the spatial pattern of dengue fever (DF) patients' survival and investigated factors influencing DF patients' survival. METHOD: A Bayesian spatial survival method via a conditional autoregressive approach was used to analyze the factors that influence DF patients' survival in 14 sub-districts from January 2015 to May 2017 in Makassar city, Indonesia. Bayesian spatial and a non-spatial model were compared by using deviance…
Bayesian Hierarchical Multidimensional Item Response Modeling of Small Sample, Sparse Data for Personalized Developmental Surveillance
Developmental surveillance tools are used to closely monitor the early development of infants and young children. This study provides a novel implementation of a multidimensional item response model, using Bayesian hierarchical priors, to construct developmental profiles for a small sample of children ( N = 115) with sparse data collected through an online developmental surveillance tool. The surveillance tool records 348 developmental milestones…
Reconstructing Missing and Anomalous Data Collected from High-Frequency In-Situ Sensors in Fresh Waters
In situ sensors that collect high-frequency data are used increasingly to monitor aquatic environments. These sensors are prone to technical errors, resulting in unrecorded observations and/or anomalous values that are subsequently removed and create gaps in time series data. We present a framework based on generalized additive and auto-regressive models to recover these missing data. To mimic sporadically missing (i) single observations and (ii)…
Bayesian Spatial Survival Models for Hospitalisation of Dengue
Spatial models are becoming more popular in time-to-event data analysis. Commonly, the intrinsic conditional autoregressive prior is placed on an area level frailty term to allow for correlation between areas. We considered a range of Bayesian Weibull and Cox semiparametric spatial models to describe a dataset on hospitalisation of dengue. This paper aimed to extend these two models, to evaluate the suitability of these models for estimation and …
Hindsight is 2020 vision
We demonstrate the utility of modelling to interpret community behaviour in the early epidemic stages. Two lessons learnt that are important for the future are: i) countries that imposed strict containment measures early in the epidemic fared better with respect to numbers of reported cases; and ii) broader testing is required early in the epidemic to understand the magnitude of undocumented infections and recover rapidly. We conclude that clear …
Rising floodwaters
The roles of forest and wetland ecosystems in regulating flooding have drawn increasing attention in the contexts of climate change adaptation and disaster risk reduction. However, data on floods are scarce in many of the countries where people are most exposed and vulnerable to their impacts. Here, our separate analyses of village interview surveys(364 villages) and news archives(16 sources)show that floods have major impacts on lives and liveli…
Geographic variation in the intended choice of adjuvant treatments for women diagnosed with screen-detected breast cancer in Queensland
This highlights the need to identify the additional barriers that impact on treatment intentions among women diagnosed with screen-detected breast cancer, particularly for those women living further away from cancer treatment centers
Socio-environmental drivers and suicide in Australia
Proportion of Aboriginal and Torres Strait Islanders, unemployment and temperature appeared to be statistically associated with of suicide incidence across LGAs among all selected variables, especially in recent years. The results indicated that socio-demographic factors played more important roles than meteorological factors in the spatial pattern of suicide incidence
Spatial inequalities in colorectal and breast cancer survival
Small area estimation of sparse disease counts using shared component models-application to birth defect registry data in New South Wales, Australia
Weather Variability, Sunspots, and the Blooms of Cyanobacteria
Socioeconomic status and infant mortality in Australia
Socioeconomic status and infant mortality in Australia
Weather Variability, Sunspots, and the Blooms of Cyanobacteria
Small area estimation of sparse disease counts using shared component models-application to birth defect registry data in New South Wales, Australia
Spatial inequalities in colorectal and breast cancer survival
Socio-environmental drivers and suicide in Australia
Proportion of Aboriginal and Torres Strait Islanders, unemployment and temperature appeared to be statistically associated with of suicide incidence across LGAs among all selected variables, especially in recent years. The results indicated that socio-demographic factors played more important roles than meteorological factors in the spatial pattern of suicide incidence
Geographic variation in the intended choice of adjuvant treatments for women diagnosed with screen-detected breast cancer in Queensland
This highlights the need to identify the additional barriers that impact on treatment intentions among women diagnosed with screen-detected breast cancer, particularly for those women living further away from cancer treatment centers
Rising floodwaters
The roles of forest and wetland ecosystems in regulating flooding have drawn increasing attention in the contexts of climate change adaptation and disaster risk reduction. However, data on floods are scarce in many of the countries where people are most exposed and vulnerable to their impacts. Here, our separate analyses of village interview surveys(364 villages) and news archives(16 sources)show that floods have major impacts on lives and liveli…
Bayesian Spatial Survival Models for Hospitalisation of Dengue
Spatial models are becoming more popular in time-to-event data analysis. Commonly, the intrinsic conditional autoregressive prior is placed on an area level frailty term to allow for correlation between areas. We considered a range of Bayesian Weibull and Cox semiparametric spatial models to describe a dataset on hospitalisation of dengue. This paper aimed to extend these two models, to evaluate the suitability of these models for estimation and …
Hindsight is 2020 vision
We demonstrate the utility of modelling to interpret community behaviour in the early epidemic stages. Two lessons learnt that are important for the future are: i) countries that imposed strict containment measures early in the epidemic fared better with respect to numbers of reported cases; and ii) broader testing is required early in the epidemic to understand the magnitude of undocumented infections and recover rapidly. We conclude that clear …
Bayesian spatial survival modelling for dengue fever in Makassar, Indonesia
OBJECTIVE: To understand the spatial pattern of dengue fever (DF) patients' survival and investigated factors influencing DF patients' survival. METHOD: A Bayesian spatial survival method via a conditional autoregressive approach was used to analyze the factors that influence DF patients' survival in 14 sub-districts from January 2015 to May 2017 in Makassar city, Indonesia. Bayesian spatial and a non-spatial model were compared by using deviance…
Bayesian Hierarchical Multidimensional Item Response Modeling of Small Sample, Sparse Data for Personalized Developmental Surveillance
Developmental surveillance tools are used to closely monitor the early development of infants and young children. This study provides a novel implementation of a multidimensional item response model, using Bayesian hierarchical priors, to construct developmental profiles for a small sample of children ( N = 115) with sparse data collected through an online developmental surveillance tool. The surveillance tool records 348 developmental milestones…
Reconstructing Missing and Anomalous Data Collected from High-Frequency In-Situ Sensors in Fresh Waters
In situ sensors that collect high-frequency data are used increasingly to monitor aquatic environments. These sensors are prone to technical errors, resulting in unrecorded observations and/or anomalous values that are subsequently removed and create gaps in time series data. We present a framework based on generalized additive and auto-regressive models to recover these missing data. To mimic sporadically missing (i) single observations and (ii)…
Age- and Gender-Specific Differences in the Seasonal Distribution of Diabetes Mortality in Shandong, China
Diabetes mortality in Shandong is higher than the national average in China. This study first explored diabetes mortality variation spatially at the county/district level among adults aged over 30 years in terms of age and gender, specifically by season. Daily diabetes mortality data were collected from 31 mortality surveillance points across Shandong Province in 2014. A geographic information system, spatial kriging interpolation and a spatial c…
Spatial statistical machine learning models to assess the relationship between development vulnerabilities and educational factors in children in Queensland, Australia
This study confirmed that it is important to take into account the spatial nature of data when fitting statistical machine learning models. A new spatial random forest model was introduced and was shown to explain more of the spatial variation and provide a better model fit in the case study of development vulnerabilities among children in Queensland. At small-area population level, increased attendance at preschool was strongly associated with r…
Patterns of educational performance among Indigenous students in Australia, 2010–2019
Data reporting in the Australian education system produces deficit-based comparisons of academic achievement between Indigenous and non-Indigenous students. Since 2009, data from the National Assessment Program – Literacy and Numeracy (NAPLAN) have been used by the Australian government to allow it to report on ‘Closing the Gap’ policy. These data are used to justify government-funded initiatives designed to improve educational outcomes for Indig…
Creating area level indices of behaviours impacting cancer in Australia with a Bayesian generalised shared component model
This study develops a model-based index approach called the Generalised Shared Component Model (GSCM) by drawing on the large field of factor models. The proposed fully Bayesian approach accommodates heteroscedastic model error, multiple shared factors and flexible spatial priors. Moreover, unlike previous index approaches, our model provides indices with uncertainty. Focusing on unhealthy behaviors that increase the risk of cancer, the proposed …
Practical guidelines for Indigenous research
This article presents an Indigenous research methodology developed in the context of a case study to better understand data literacy within our local Indigenous Australian community. For too long Indigenous peoples have been the subjects, rather than the producers, of data-focused research. By adopting this approach in our case study, we identified practical guidelines for conducting best-practice Indigenous research in our own local community. R…
Extracting and communicating insights about geographical patterns from spatiotemporal disease models
Spatiotemporal modelling is increasingly employed to understand how geographic patterns of disease vary over time; however, most studies report minimal information, often neglecting uncertainty altogether. This represents a missed opportunity to understand changes in disease risk at a fine granularity and to provide a valuable, actionable evidence base. This study describes generalisable methods for extracting key metrics from the outputs of Baye…
A data-informed multidimensional composite score for stress assessment
Occupations such as the military, emergency responders, and athletes demand acute physical, cognitive and psychosocial effort. Individuals in these roles face task-specific stressors, including extreme heat, sustained mental focus and performance under social pressure, resulting in variable stress responses. Comparing individual stress responses is challenging due to the complex physiological, cognitive, and emotional interactions. This study pre…
Medicine (10 obras) · Geography (8 obras) · Mathematics (8 obras) · Statistics (8 obras) · Population (7 obras) · Bayesian probability (5 obras) · Demography (5 obras) · Demography (5 obras) · Health disparities and outcomes (5 obras) · Computer Science (4 obras)