ORCID Profile
0000-0001-8916-5570
Current Organisations
Curtin University
,
Telethon Kids Institute
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In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Biostatistics | Evolutionary biology | Evolutionary biology not elsewhere classified | Environmental Science and Management | Ecological Applications | Conservation and Biodiversity | Landscape Ecology | Epidemiology | Population ecology | Evolutionary ecology | Community Ecology |
Expanding Knowledge in the Environmental Sciences | Expanding Knowledge in the Biological Sciences | Disease Distribution and Transmission (incl. Surveillance and Response) | Flora, Fauna and Biodiversity at Regional or Larger Scales | Forest and Woodlands Flora, Fauna and Biodiversity
Publisher: Oxford University Press (OUP)
Date: 04-07-2015
Publisher: The Open Journal
Date: 12-08-2019
DOI: 10.21105/JOSS.01601
Publisher: Elsevier BV
Date: 03-2017
Publisher: Elsevier BV
Date: 2022
Publisher: Oxford University Press (OUP)
Date: 15-06-2015
DOI: 10.1111/BIJ.12567
Publisher: Wiley
Date: 20-10-2021
DOI: 10.1111/GCB.15888
Abstract: 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. This is particularly important in connectivity‐limited ecosystems, such as freshwater ecosystems, where increased human translocation is creating species associations over previously unseen environmental gradients. Here, we use a large‐scale presence–absence dataset of freshwater fish from lakes across the Fennoscandian region in a Joint Species Distribution Model, to measure the effect of temperature on species associations. We identified a trend of negative associations between species tolerant of cold waters and those tolerant of warmer waters, as well as positive associations between several more warm‐tolerant species, with these associations often shifting depending on local temperatures. Our results confirm that freshwater ecosystems can expect to see a large‐scale shift towards communities dominated by more warm‐tolerant species. While there remains much work to be done to predict exactly where and when local extinctions may take place, the model implemented provides a starting‐point for the exploration of climate‐driven community trends. This approach is especially informative in regards to determining which species associations are most central in shaping future community composition, and which areas are most vulnerable to local extinctions.
Publisher: Wiley
Date: 08-11-2021
Publisher: Public Library of Science (PLoS)
Date: 05-08-2016
DOI: 10.1371/JOURNAL.PNTD.0004915
Abstract: Infection by the simian malaria parasite, Plasmodium knowlesi, can lead to severe and fatal disease in humans, and is the most common cause of malaria in parts of Malaysia. Despite being a serious public health concern, the geographical distribution of P. knowlesi malaria risk is poorly understood because the parasite is often misidentified as one of the human malarias. Human cases have been confirmed in at least nine Southeast Asian countries, many of which are making progress towards eliminating the human malarias. Understanding the geographical distribution of P. knowlesi is important for identifying areas where malaria transmission will continue after the human malarias have been eliminated. A total of 439 records of P. knowlesi infections in humans, macaque reservoir and vector species were collated. To predict spatial variation in disease risk, a model was fitted using records from countries where the infection data coverage is high. Predictions were then made throughout Southeast Asia, including regions where infection data are sparse. The resulting map predicts areas of high risk for P. knowlesi infection in a number of countries that are forecast to be malaria-free by 2025 (Malaysia, Cambodia, Thailand and Vietnam) as well as countries projected to be eliminating malaria (Myanmar, Laos, Indonesia and the Philippines). We have produced the first map of P. knowlesi malaria risk, at a fine-scale resolution, to identify priority areas for surveillance based on regions with sparse data and high estimated risk. Our map provides an initial evidence base to better understand the spatial distribution of this disease and its potential wider contribution to malaria incidence. Considering malaria elimination goals, areas for prioritised surveillance are identified.
Publisher: Springer Science and Business Media LLC
Date: 26-02-2021
DOI: 10.1038/S41598-021-84198-6
Abstract: Understanding human movement patterns at local, national and international scales is critical in a range of fields, including transportation, logistics and epidemiology. Data on human movement is increasingly available, and when combined with statistical models, enables predictions of movement patterns across broad regions. Movement characteristics, however, strongly depend on the scale and type of movement captured for a given study. The models that have so far been proposed for human movement are best suited to specific spatial scales and types of movement. Selecting both the scale of data collection, and the appropriate model for the data remains a key challenge in predicting human movements. We used two different data sources on human movement in Australia, at different spatial scales, to train a range of statistical movement models and evaluate their ability to predict movement patterns for each data type and scale. Whilst the five commonly-used movement models we evaluated varied markedly between datasets in their predictive ability, we show that an ensemble modelling approach that combines the predictions of these models consistently outperformed all in idual models against hold-out data.
Publisher: Public Library of Science (PLoS)
Date: 05-08-2013
Publisher: WHO Press
Date: 09-06-2017
Publisher: Public Library of Science (PLoS)
Date: 29-07-2015
Publisher: Wiley
Date: 22-07-2020
DOI: 10.1111/AEC.12898
Publisher: eLife Sciences Publications, Ltd
Date: 21-12-2022
Publisher: Wiley
Date: 2010
DOI: 10.1002/WEA.444
Publisher: F1000 Research Ltd
Date: 15-12-2017
DOI: 10.12688/WELLCOMEOPENRES.12483.2
Abstract: Background : In 2011, the World Health Organization recognized podoconiosis as one of the neglected tropical diseases. Nonetheless, the magnitude of podoconiosis and the geographical distribution of the disease is poorly understood. Based on a nationwide mapping survey and geostatistical modelling, we predict the prevalence of podoconiosis and estimate the number of cases across Ethiopia. Methods : We used nationwide data collected in Ethiopia between 2008 and 2013. Data were available for 141,238 in iduals from 1,442 communities in 775 districts from all nine regional states and two city administrations. We developed a geostatistical model of podoconiosis prevalence among adults (in iduals aged 15 years or above), by combining environmental factors. The number of people with podoconiosis was then estimated using a gridded map of adult population density for 2015. Results : Podoconiosis is endemic in 345 districts in Ethiopia: 144 in Oromia, 128 in Southern Nations, Nationalities and People’s [SNNP], 64 in Amhara, 4 in Benishangul Gumuz, 4 in Tigray and 1 in Somali Regional State. Nationally, our estimates suggest that 1,537,963 adults (95% confidence intervals, 290,923-4,577,031 adults) were living with podoconiosis in 2015. Three regions (SNNP, Oromia and Amhara) contributed 99% of the cases. The highest proportion of in iduals with podoconiosis resided in the SNNP (39%), while 32% and 29% of people with podoconiosis resided in Oromia and Amhara Regional States, respectively. Tigray and Benishangul Gumuz Regional States bore lower burdens, and in the remaining regions, podoconiosis was almost non-existent. Conclusions : The estimates of podoconiosis cases presented here based upon the combination of currently available epidemiological data and a robust modelling approach clearly show that podoconiosis is highly endemic in Ethiopia. Given the presence of low cost prevention, and morbidity management and disability prevention services, it is our collective responsibility to scale-up interventions rapidly.
Publisher: Springer Science and Business Media LLC
Date: 10-06-2019
DOI: 10.1038/S41564-019-0476-8
Abstract: 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.
Publisher: F1000 Research Ltd
Date: 04-09-2017
DOI: 10.12688/WELLCOMEOPENRES.12483.1
Abstract: Background: In 2011, the World Health Organization recognized podoconiosis as one of the neglected tropical diseases. Nonetheless, the number of people with podoconiosis and the geographical distribution of the disease is poorly understood. Based on a nationwide mapping survey and geostatistical modelling, we predict the prevalence of podoconiosis and estimate the number of cases across Ethiopia. Methods: We used nationwide data collected in Ethiopia between 2008 and 2013. Data were available for 141,238 in iduals from 1,442 villages in 775 districts from all nine regional states and two city administrations. We developed a geostatistical model of podoconiosis prevalence among adults (in iduals aged 15 years or above), by combining environmental factors. The number of people with podoconiosis was then estimated using a gridded map of adult population density for 2015. Results: Podoconiosis is endemic in 345 districts in Ethiopia: 144 in Oromia, 128 in Southern Nations, Nationalities and People’s [SNNP], 64 in Amhara, 4 in Benishangul Gumuz, 4 in Tigray and 1 in Somali Regional State. Nationally, our estimates suggest that 1,537,963 adults (95% confidence intervals, 290,923-4,577,031 adults) were living with podoconiosis in 2015. Three regions (SNNP, Oromia and Amhara) contributed 99% of the cases. The highest proportion of in iduals with podoconiosis resided in the SNNP (39%), while 32% and 29% of people with podoconiosis resided in Oromia and Amhara Regional States, respectively. Tigray and Benishangul Gumuz Regional States bore lower burdens, and in the remaining regions, podoconiosis was almost non-existent. Discussion: The estimates of podoconiosis cases presented here based upon the combination of currently available epidemiological data and a robust modelling approach clearly show that podoconiosis is highly endemic in Ethiopia. Given the presence of low cost prevention, and morbidity management and disability prevention services, it is our collective responsibility to scale-up interventions rapidly.
Publisher: eLife Sciences Publications, Ltd
Date: 13-08-2020
DOI: 10.7554/ELIFE.58785
Abstract: As of 1 May 2020, there had been 6808 confirmed cases of COVID-19 in Australia. Of these, 98 had died from the disease. The epidemic had been in decline since mid-March, with 308 cases confirmed nationally since 14 April. This suggests that the collective actions of the Australian public and government authorities in response to COVID-19 were sufficiently early and assiduous to avert a public health crisis – for now. Analysing factors that contribute to in idual country experiences of COVID-19, such as the intensity and timing of public health interventions, will assist in the next stage of response planning globally. We describe how the epidemic and public health response unfolded in Australia up to 13 April. We estimate that the effective reproduction number was likely below one in each Australian state since mid-March and forecast that clinical demand would remain below capacity thresholds over the forecast period (from mid-to-late April).
Publisher: eLife Sciences Publications, Ltd
Date: 19-04-2016
DOI: 10.7554/ELIFE.15272
Abstract: Zika virus was discovered in Uganda in 1947 and is transmitted by Aedes mosquitoes, which also act as vectors for dengue and chikungunya viruses throughout much of the tropical world. In 2007, an outbreak in the Federated States of Micronesia sparked public health concern. In 2013, the virus began to spread across other parts of Oceania and in 2015, a large outbreak in Latin America began in Brazil. Possible associations with microcephaly and Guillain-Barré syndrome observed in this outbreak have raised concerns about continued global spread of Zika virus, prompting its declaration as a Public Health Emergency of International Concern by the World Health Organization. We conducted species distribution modelling to map environmental suitability for Zika. We show a large portion of tropical and sub-tropical regions globally have suitable environmental conditions with over 2.17 billion people inhabiting these areas.
Publisher: Springer Science and Business Media LLC
Date: 30-04-2015
Publisher: Ubiquity Press, Ltd.
Date: 10-2021
DOI: 10.5334/JORS.249
Publisher: Springer Science and Business Media LLC
Date: 02-03-2015
DOI: 10.1038/NRMICRO3430
Abstract: Dengue is a vector-borne disease that causes a substantial public health burden within its expanding range. Several modelling studies have attempted to predict the future global distribution of dengue. However, the resulting projections are difficult to compare and are sometimes contradictory because the models differ in their approach, in the quality of the disease data that they use and in the choice of variables that drive disease distribution. In this Review, we compare the main approaches that have been used to model the future global distribution of dengue and propose a set of minimum criteria for future projections that, by analogy, are applicable to other vector-borne diseases.
Publisher: Cold Spring Harbor Laboratory
Date: 06-08-2022
DOI: 10.1101/2022.08.04.22278391
Abstract: As of January 2021, Australia had effectively controlled local transmission of COVID-19 despite a steady influx of imported cases and several local, but contained, outbreaks in 2020. Throughout 2020, state and territory public health responses were informed by weekly situational reports that included an ensemble forecast for each jurisdiction. We present here an analysis of one forecasting model included in this ensemble across the variety of scenarios experienced by each jurisdiction from May to October 2020. We examine how successfully the forecasts characterised future case incidence, subject to variations in data timeliness and completeness, showcase how we adapted these forecasts to support decisions of public health priority in rapidly-evolving situations, evaluate the impact of key model features on forecast skill, and demonstrate how to assess forecast skill in real-time before the ground truth is known. Conditioning the model on the most recent, but incomplete, data improved the forecast skill, emphasising the importance of developing strong quantitative models of surveillance system characteristics, such as ascertainment delay distributions. Forecast skill was highest when there were at least 10 reported cases per day, the circumstances in which authorities were most in need of forecasts to aid in planning and response.
Publisher: Elsevier BV
Date: 12-2019
Publisher: Cold Spring Harbor Laboratory
Date: 29-11-2021
DOI: 10.1101/2021.11.28.21264509
Abstract: Against a backdrop of widespread 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 outbreaks, the reproduction rate can be estimated from a 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. Absence of case data means that this potential cannot be estimated directly. We present a semi-mechanistic modelling framework that draws on time-series of both behavioural data and case data (when disease activity is present) to estimate the transmissibility of SARS-CoV-2 from periods of high to low – or zero – case incidence, with a coherent transition in interpretation across the changing epidemiological situations. Of note, during periods of epidemic activity, our analysis recovers the effective reproduction number, while during periods of low – or zero – case incidence, it provides an estimate of transmission risk. This enables tracking and planning of progress towards the control of large outbreaks, maintenance of virus suppression, and monitoring the risk posed by re-introduction of the virus. We demonstrate the value of our methods by reporting on their use throughout 2020 in Australia, where they have become a central component of the national COVID-19 response.
Publisher: Wiley
Date: 05-2014
Publisher: Oxford University Press (OUP)
Date: 27-03-2015
Publisher: Cold Spring Harbor Laboratory
Date: 17-08-2019
DOI: 10.1101/738310
Abstract: Approximately 150 triatomine species are known to be infected with the Chagas parasite, Trypanosoma cruzi , but they differ in the risk they pose to human populations. The largest risk comes from species that have a domestic life cycle and these species have been targeted by indoor residual spraying c aigns, which have been successful in many locations. It is now important to consider residual transmission that may be linked to persistent populations of dominant vectors, or to secondary or minor vectors. The aim of this project was to define the geographical distributions of the community of triatomine species in Latin America. Presence-only data with over 12, 000 observations of triatomine vectors were extracted from a public database and target-group background data were generated to account for s ling bias in the presence data. Geostatistical regression was then applied to estimate species distributions and fine-scale distribution maps were generated for thirty triatomine vector species. The results for Panstrongylus geniculatus, P. megistus, Triatoma barberi, T. brasiliensis , and T. pseudomaculata are presented in detail and the model validation results for each of the 30 species are presented in full. The predictive maps for all species are made publicly available so that they can be used to assess the communities of vectors present within different regions of the endemic zone. The maps are presented alongside key indicators for the capacity of each species to transmit T. cruzi to humans. These indicators include infection prevalence, evidence for human blood meals, and colonisation or invasion of homes. A summary of these indicators shows that the majority of the 30 species mapped by this study have the potential to transmit T. cruzi to humans. The Pan American Health Organisation’s Strategy and Plan of Action for Chagas Disease Prevention, Control and Care highlights the importance of eliminating those triatomine vector species that colonise homes, and has had great success in many locations. Since indoor residual spraying c aigns have targeted these species, their importance relative to other vectors has diminished and their geographical distributions may also have changed. It is now vital to consider the full community of vector species, including previously dominant vectors as well as secondary or minor vector species, in order to target residual transmission to humans. Our aim was to define the geographical distributions of the most commonly reported triatomine species in Latin America. We extracted reports of triatomine vector species observed at specific locations from a public database and we used a geostatistical model to generate fine-scale predictive maps for thirty triatomine vector species. We present these maps alongside a summary of key indicators related to the capacity of each species to transmit the Chagas parasite to humans. We show that most of the 30 species that we have mapped pose a potential threat to human populations.
Publisher: Springer Science and Business Media LLC
Date: 08-04-2019
DOI: 10.1038/S41564-019-0440-7
Abstract: This Article was mistakenly not made Open Access when originally published this has now been amended, and information about the Creative Commons Attribution 4.0 International License has been added into the ‘Additional information’ section.
Publisher: Cold Spring Harbor Laboratory
Date: 09-12-2020
DOI: 10.1101/2020.12.08.415992
Abstract: Land use change leads to shifts in species ranges and declines in bio ersity across the world. By mapping likely future land use under projections of socio-economic change, these ecological changes can be predicted to inform conservation decision-making. We present a land use modelling approach that enables ecologists to map changes in land use under various socio-economic scenarios at fine spatial resolutions. Its predictions can be used as a direct input to virtually all existing spatially-explicit ecological models. The most commonly used land use modelling approaches provide binary predictions of land use. However, continuous representations of land use have been shown to improve ecological models. Our approach maps the fractional cover of land use within each grid cell, providing higher information content than discrete classes at the same spatial resolution. When parametrized using data from 1990, the method accurately reproduced land use patterns observed in the Amazon from 1990 until 2018. Predictions were accurate in terms of the fractional amounts allocated across the landscape and the correct identification of areas with declines and increases in different land uses. A small case study showcases the successful application of our model to reproduce patterns of agricultural expansion and habitat decline. The model source code is provided as an open-source R package, making this new, open method available to ecologists to bridge the gap between socio-economic, land use and bio ersity modelling.
Publisher: Public Library of Science (PLoS)
Date: 11-01-2018
Publisher: Wiley
Date: 20-05-0002
Publisher: Springer Science and Business Media LLC
Date: 14-07-2015
Publisher: Wiley
Date: 18-09-2018
Publisher: Springer Science and Business Media LLC
Date: 22-10-2020
DOI: 10.1186/S12916-020-01790-9
Abstract: Asymptomatic or subclinical SARS-CoV-2 infections are often unreported, which means that confirmed case counts may not accurately reflect underlying epidemic dynamics. Understanding the level of ascertainment (the ratio of confirmed symptomatic cases to the true number of symptomatic in iduals) and undetected epidemic progression is crucial to informing COVID-19 response planning, including the introduction and relaxation of control measures. Estimating case ascertainment over time allows for accurate estimates of specific outcomes such as seroprevalence, which is essential for planning control measures. Using reported data on COVID-19 cases and fatalities globally, we estimated the proportion of symptomatic cases (i.e. any person with any of fever ≥ 37.5 °C, cough, shortness of breath, sudden onset of anosmia, ageusia or dysgeusia illness) that were reported in 210 countries and territories, given those countries had experienced more than ten deaths. We used published estimates of the baseline case fatality ratio (CFR), which was adjusted for delays and under-ascertainment, then calculated the ratio of this baseline CFR to an estimated local delay-adjusted CFR to estimate the level of under-ascertainment in a particular location. We then fit a Bayesian Gaussian process model to estimate the temporal pattern of under-ascertainment. Based on reported cases and deaths, we estimated that, during March 2020, the median percentage of symptomatic cases detected across the 84 countries which experienced more than ten deaths ranged from 2.4% (Bangladesh) to 100% (Chile). Across the ten countries with the highest number of total confirmed cases as of 6 July 2020, we estimated that the peak number of symptomatic cases ranged from 1.4 times (Chile) to 18 times (France) larger than reported. Comparing our model with national and regional seroprevalence data where available, we find that our estimates are consistent with observed values. Finally, we estimated seroprevalence for each country. As of 7 June, our seroprevalence estimates range from 0% (many countries) to 13% (95% CrI 5.6–24%) (Belgium). We found substantial under-ascertainment of symptomatic cases, particularly at the peak of the first wave of the SARS-CoV-2 pandemic, in many countries. Reported case counts will therefore likely underestimate the rate of outbreak growth initially and underestimate the decline in the later stages of an epidemic. Although there was considerable under-reporting in many locations, our estimates were consistent with emerging serological data, suggesting that the proportion of each country’s population infected with SARS-CoV-2 worldwide is generally low.
Publisher: Springer Science and Business Media LLC
Date: 16-03-2017
Publisher: Elsevier BV
Date: 03-2018
Publisher: eLife Sciences Publications, Ltd
Date: 27-06-2014
DOI: 10.7554/ELIFE.02851
Abstract: The leishmaniases are vector-borne diseases that have a broad global distribution throughout much of the Americas, Africa, and Asia. Despite representing a significant public health burden, our understanding of the global distribution of the leishmaniases remains vague, reliant upon expert opinion and limited to poor spatial resolution. A global assessment of the consensus of evidence for leishmaniasis was performed at a sub-national level by aggregating information from a variety of sources. A database of records of cutaneous and visceral leishmaniasis occurrence was compiled from published literature, online reports, strain archives, and GenBank accessions. These, with a suite of biologically relevant environmental covariates, were used in a boosted regression tree modelling framework to generate global environmental risk maps for the leishmaniases. These high-resolution evidence-based maps can help direct future surveillance activities, identify areas to target for disease control and inform future burden estimation efforts.
Publisher: Wiley
Date: 03-11-2019
Publisher: Springer Science and Business Media LLC
Date: 21-03-2019
DOI: 10.1038/S41564-019-0429-2
Abstract: In the version of this Article originally published, the affiliation for author Catherine Linard was incorrectly stated as ‘ 6 Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK’. The correct affiliation is ‘ 9 Spatial Epidemiology Lab (SpELL), Universite Libre de Bruxelles, Brussels, Belgium’. The affiliation for author Hongjie Yu was also incorrectly stated as ‘ 11 Department of Statistics, Harvard University, Cambridge, MA, USA’. The correct affiliation is ‘ 15 School of Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China’. This has now been amended in all versions of the Article.
Publisher: Springer Science and Business Media LLC
Date: 2014
Publisher: Springer Science and Business Media LLC
Date: 08-02-2021
DOI: 10.1038/S41598-021-82474-Z
Abstract: Climate change threatens bio ersity directly by influencing biophysical variables that drive species’ geographic distributions and indirectly through socio-economic changes that influence land use patterns, driven by global consumption, production and climate. To date, no detailed analyses have been produced that assess the relative importance of, or interaction between, these direct and indirect climate change impacts on bio ersity at large scales. Here, we apply a new integrated modelling framework to quantify the relative influence of biophysical and socio-economically mediated impacts on avian species in Vietnam and Australia and we find that socio-economically mediated impacts on suitable ranges are largely outweighed by biophysical impacts. However, by translating economic futures and shocks into spatially explicit predictions of bio ersity change, we now have the power to analyse in a consistent way outcomes for nature and people of any change to policy, regulation, trading conditions or consumption trend at any scale from sub-national to global.
Publisher: Springer Science and Business Media LLC
Date: 11-04-2017
Abstract: Chagas is a potentially fatal chronic disease affecting large numbers of people across the Americas and exported throughout the world through human population movement. It is caused by the Trypanosoma cruzi parasite, which is transmitted by triatomine vectors to humans and a wide range of alternative host species. The database described here was compiled to allow the risk of vectorial transmission to humans to be mapped using geospatial models. The database collates all available records, published since 2003, for prevalence and occurrence of infection in humans, vectors and alternative hosts, and links each record to a defined time and location. A total of 16,802 records of infection have been extracted from the published literature and unpublished sources. The resulting database can be used to improve our understanding of the geographic variation in vector infection prevalence and to estimate the risk of vectorial transmission of T. cruzi to humans.
Publisher: eLife Sciences Publications, Ltd
Date: 20-01-2023
DOI: 10.7554/ELIFE.78089
Abstract: Against a backdrop of widespread 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 outbreaks, the effective reproduction number can be estimated from a 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. Absence of case data means that this potential cannot be estimated directly. We present a semi-mechanistic modelling framework that draws on time-series of both behavioural data and case data (when disease activity is present) to estimate the transmissibility of SARS-CoV-2 from periods of high to low – or zero – case incidence, with a coherent transition in interpretation across the changing epidemiological situations. Of note, during periods of epidemic activity, our analysis recovers the effective reproduction number, while during periods of low – or zero – case incidence, it provides an estimate of transmission risk. This enables tracking and planning of progress towards the control of large outbreaks, maintenance of virus suppression, and monitoring the risk posed by re-introduction of the virus. We demonstrate the value of our methods by reporting on their use throughout 2020 in Australia, where they have become a central component of the national COVID-19 response.
Publisher: Elsevier BV
Date: 11-2017
Publisher: Public Library of Science (PLoS)
Date: 10-08-2020
Publisher: Springer Science and Business Media LLC
Date: 18-08-2015
Abstract: Measures of clinical incidence are necessary to help estimate the burden of a disease. Incidence is a metric not commonly measured in malariology because the longitudinal surveys required are costly and labour intensive. This database is an effort to collate published incidence records obtained using active case detection for Plasmodium falciparum and Plasmodium vivax malaria. The literature search methods, data abstraction procedures and data processing procedures are described here. A total of 1,680 spatio-temporally unique incidence records were collected for the database: 1,187 for P. falciparum and 493 for P. vivax . These data were gathered to model the relationship between clinical incidence and prevalence of infection and can be used for a variety of modelling exercises including the assessment of change in disease burden in relation to age and control interventions. The subset of data that have been used for such modelling exercises are described and identified.
Publisher: eLife Sciences Publications, Ltd
Date: 14-04-2023
DOI: 10.7554/ELIFE.84983
Abstract: 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. Previous research has shown that Australian native possums are reservoirs of M. ulcerans and that they shed the bacteria in their fecal material (excreta). Field surveys show that locales where possums harbor M. ulcerans overlap with human cases of BU, raising the possibility of using possum excreta surveys to predict the risk of disease occurrence in humans. We thus established a highly structured 12 month possum excreta surveillance program across an area of 350 km 2 in the Mornington Peninsula area 70 km south of Melbourne, Australia. The primary objective of our study was to assess using statistical modeling if M. ulcerans surveillance of possum excreta provided useful information for predicting future human BU case locations. Over two s ling c aigns in summer and winter, we collected 2,282 possum excreta specimens of which 11% were PCR positive for M. ulcerans -specific DNA. Using the spatial scanning statistical tool SaTScan , we observed non-random, co-correlated clustering of both M. ulcerans positive possum excreta and human BU cases. We next trained a statistical model with the Mornington Peninsula excreta survey data to predict the future likelihood of human BU cases occurring in the region. By observing where human BU cases subsequently occurred, we show that the excreta model performance was superior to a null model trained using the previous year’s human BU case incidence data (AUC 0.66 vs 0.55). We then used data unseen by the excreta-informed model from a new survey of 661 possum excreta specimens in Geelong, a geographically separate BU endemic area to the southwest of Melbourne, to prospectively predict the location of human BU cases in that region. As for the Mornington Peninsula, the excreta-based BU prediction model outperformed the null model (AUC 0.75 vs 0.50) and pinpointed specific locations in Geelong where interventions could be deployed to interrupt disease spread. This study highlights the One Health nature of BU by confirming a quantitative relationship between possum excreta shedding of M. ulcerans and humans developing BU. The excreta survey-informed modeling we have described will be a powerful tool for the efficient targeting of public health responses to stop BU. This research was supported by the National Health and Medical Research Council of Australia and the Victorian Government Department of Health (GNT1152807 and GNT1196396).
Publisher: Springer Science and Business Media LLC
Date: 23-10-2014
Abstract: Ebola is a zoonotic filovirus that has the potential to cause outbreaks of variable magnitude in human populations. This database collates our existing knowledge of all known human outbreaks of Ebola for the first time by extracting details of their suspected zoonotic origin and subsequent human-to-human spread from a range of published and non-published sources. In total, 22 unique Ebola outbreaks were identified, composed of 117 unique geographic transmission clusters. Details of the index case and geographic spread of secondary and imported cases were recorded as well as summaries of patient numbers and case fatality rates. A brief text summary describing suspected routes and means of spread for each outbreak was also included. While we cannot yet include the ongoing Guinea and DRC outbreaks until they are over, these data and compiled maps can be used to gain an improved understanding of the initial spread of past Ebola outbreaks and help evaluate surveillance and control guidelines for limiting the spread of future epidemics.
Publisher: eLife Sciences Publications, Ltd
Date: 14-07-2016
DOI: 10.7554/ELIFE.16412
Abstract: As the outbreak of Ebola virus disease (EVD) in West Africa is now contained, attention is turning from control to future outbreak prediction and prevention. Building on a previously published zoonotic niche map ( xref ref-type="bibr" rid="bib27" Pigott et al., 2014 /xref ), this study incorporates new human and animal occurrence data and expands upon the way in which potential bat EVD reservoir species are incorporated. This update demonstrates the potential for incorporating and updating data used to generate the predicted suitability map. A new data portal for sharing such maps is discussed. This output represents the most up-to-date estimate of the extent of EVD zoonotic risk in Africa. These maps can assist in strengthening surveillance and response capacity to contain viral haemorrhagic fevers.
Publisher: Elsevier BV
Date: 12-2017
Publisher: Springer Science and Business Media LLC
Date: 04-03-2019
DOI: 10.1038/S41564-019-0376-Y
Abstract: 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 aegypti and Aedes 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 of Ae. aegypti is characterized by long distance importations, while Ae. albopictus has 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.
Publisher: Springer Science and Business Media LLC
Date: 17-06-2014
DOI: 10.1038/NCOMMS5116
Abstract: Two epidemic waves of an avian influenza A (H7N9) virus have so far affected China. Most human cases have been attributable to poultry exposure at live-poultry markets, where most positive isolates were s led. The potential geographic extent of potential re-emerging epidemics is unknown, as are the factors associated with it. Using newly assembled data sets of the locations of 8,943 live-poultry markets in China and maps of environmental correlates, we develop a statistical model that accurately predicts the risk of H7N9 market infection across Asia. Local density of live-poultry markets is the most important predictor of H7N9 infection risk in markets, underscoring their key role in the spatial epidemiology of H7N9, alongside other poultry, land cover and anthropogenic predictor variables. Identification of areas in Asia with high suitability for H7N9 infection enhances our capacity to target biosurveillance and control, helping to restrict the spread of this important disease.
Publisher: eLife Sciences Publications, Ltd
Date: 08-09-2014
DOI: 10.7554/ELIFE.04395
Abstract: Ebola virus disease (EVD) is a complex zoonosis that is highly virulent in humans. The largest recorded outbreak of EVD is ongoing in West Africa, outside of its previously reported and predicted niche. We assembled location data on all recorded zoonotic transmission to humans and Ebola virus infection in bats and primates (1976–2014). Using species distribution models, these occurrence data were paired with environmental covariates to predict a zoonotic transmission niche covering 22 countries across Central and West Africa. Vegetation, elevation, temperature, evapotranspiration, and suspected reservoir bat distributions define this relationship. At-risk areas are inhabited by 22 million people however, the rarity of human outbreaks emphasises the very low probability of transmission to humans. Increasing population sizes and international connectivity by air since the first detection of EVD in 1976 suggest that the dynamics of human-to-human secondary transmission in contemporary outbreaks will be very different to those of the past.
Publisher: Elsevier BV
Date: 03-2018
Publisher: Hindawi Limited
Date: 17-12-2014
DOI: 10.1111/TBED.12310
Abstract: West Nile virus (WNV) is a mosquito borne arbovirus that circulates within avian reservoirs. WNV can spill over into humans and Equidae that are dead-end hosts for WNV but suffer fever, acute morbidity and sometimes death. Outbreaks of WNV are common across Africa and Eastern Europe, and there have also been sporadic outbreaks in Spain and the Camargue Regional Park in France, but never in Great Britain (GB). These areas all fall along a major bird migration route. In this study, we analyse a scenario in which WNV is circulating in the Camargue or in other wetland areas in France and we estimate the risk of northward migrating passerine birds stopping in a WNV hotspot, becoming infected and carrying active infection to GB. If the disease were circulating in the Camargue during a single migratory season, the probability that one or more migrating birds becomes infected and lands in GB whilst still infected is 0.881 with 0.384 birds arriving in areas of suitable vector habitat. However, if WNV became established in the Grand Brière National Park or La Brenne Regional Park wetland areas further to the north, the model predicts that at least one infected bird will continue to GB. Thus, GB is at risk of WNV introduction from the Camargue, but the risk is considerably greater if WNV were to circulate further north than its previous focus in France, but this is highly sensitive to the force of infection in the infected area. However, the risk of establishment and infection of humans in GB is dependent upon a number of additional factors, in particular the vector and epidemiological situation in GB.
Publisher: Springer Science and Business Media LLC
Date: 12-2013
Publisher: Elsevier BV
Date: 10-2009
DOI: 10.1016/J.RVSC.2009.03.015
Abstract: The relative resistance of Manx Loaghtan, Shetland and Southdown sheep to naturally acquired gastrointestinal nematode infection was assessed over a ten week period. Thirty shearling ewes, ten from each of the three breeds, were co-grazed on an infective pasture. The animals were initially treated with an anthelmintic to minimise previous nematode infection, and faecal s les were collected from in idual animals every two weeks. Southdown sheep had significantly higher faecal egg counts (FEC) than Shetland by week 6, and than Manx Loaghtan by week 10. After ten weeks there was an 86-fold difference in FEC between Shetland and Southdown sheep, and a 14-fold difference between Manx Loaghtan and Southdown sheep. These preliminary results suggest that primitive Shetland and Manx Loaghtan sheep may have greater resistance to gastrointestinal parasites, a trait that could be of value to the UK livestock industry.
Publisher: Cold Spring Harbor Laboratory
Date: 08-07-2020
DOI: 10.1101/2020.07.07.20148460
Abstract: Asymptomatic or subclinical SARS-CoV-2 infections are often unreported, which means that confirmed case counts may not accurately reflect underlying epidemic dynamics. Understanding the level of ascertainment (the ratio of confirmed symptomatic cases to the true number of symptomatic in iduals) and undetected epidemic progression is crucial to informing COVID-19 response planning, including the introduction and relaxation of control measures. Estimating case ascertainment over time allows for accurate estimates of specific outcomes such as seroprevalence, which is essential for planning control measures. Using reported data on COVID-19 cases and fatalities globally, we estimated the proportion of symptomatic cases (i.e. any person with any of fever = 37.5°C, cough, shortness of breath, sudden onset of anosmia, ageusia or dysgeusia illness) that were reported in 210 countries and territories, given those countries had experienced more than ten deaths. We used published estimates of the baseline case fatality ratio (CFR), which was adjusted for delays and under-ascertainment, then calculated the ratio of this baseline CFR to an estimated local delay-adjusted CFR to estimate the level of under-ascertainment in a particular location. We then fit a Bayesian Gaussian process model to estimate the temporal pattern of under-ascertainment. Based on reported cases and deaths, we estimated that, during March 2020, the median percentage of symptomatic cases detected across the 84 countries which experienced more than ten deaths ranged from 2.4% (Bangladesh) to 100% (Chile). Across the ten countries with the highest number of total confirmed cases as of 6th July 2020, we estimated that the peak number of symptomatic cases ranged from 1.4 times (Chile) to 18 times (France) larger than reported. Comparing our model with national and regional seroprevalence data where available, we find that our estimates are consistent with observed values. Finally, we estimated seroprevalence for each country. As of the 7th June, our seroprevalence estimates range from 0% (many countries) to 13% (95% CrI: 5.6% – 24%) (Belgium). We found substantial under-ascertainment of symptomatic cases, particularly at the peak of the first wave of the SARS-CoV-2 pandemic, in many countries. Reported case counts will therefore likely underestimate the rate of outbreak growth initially and underestimate the decline in the later stages of an epidemic. Although there was considerable under-reporting in many locations, our estimates were consistent with emerging serological data, suggesting that the proportion of each country’s population infected with SARS-CoV-2 worldwide is generally low. Wellcome Trust, Bill & Melinda Gates Foundation, DFID, NIHR, GCRF, ARC.
Publisher: Wiley
Date: 05-01-2016
Publisher: Springer Science and Business Media LLC
Date: 09-02-2012
Publisher: Springer Science and Business Media LLC
Date: 11-10-2014
Publisher: Springer Science and Business Media LLC
Date: 28-04-2016
Publisher: European Centre for Disease Control and Prevention (ECDC)
Date: 19-05-2016
DOI: 10.2807/1560-7917.ES.2016.21.20.30234
Abstract: Chikungunya fever is an acute febrile illness caused by the chikungunya virus (CHIKV), which is transmitted to humans by Aedes mosquitoes. Although chikungunya fever is rarely fatal, patients can experience debilitating symptoms that last from months to years. Here we comprehensively assess the global distribution of chikungunya and produce high-resolution maps, using an established modelling framework that combines a comprehensive occurrence database with bespoke environmental correlates, including up-to-date Aedes distribution maps. This enables estimation of the current total population-at-risk of CHIKV transmission and identification of areas where the virus may spread to in the future. We identified 94 countries with good evidence for current CHIKV presence and a set of countries in the New and Old World with potential for future CHIKV establishment, demonstrated by high environmental suitability for transmission and in some cases previous sporadic reports. Aedes aegypti presence was identified as one of the major contributing factors to CHIKV transmission but significant geographical heterogeneity exists. We estimated 1.3 billion people are living in areas at-risk of CHIKV transmission. These maps provide a baseline for identifying areas where prevention and control efforts should be prioritised and can be used to guide estimation of the global burden of CHIKV.
Publisher: eLife Sciences Publications, Ltd
Date: 20-03-2023
Publisher: Springer Science and Business Media LLC
Date: 30-09-2014
Abstract: The leishmaniases are neglected tropical diseases of significant public health importance. However, information on their global occurrence is disparate and sparse. This database represents an attempt to collate reported leishmaniasis occurrences from 1960 to 2012. Methodology for the collection of data from the literature, abstraction of case locations and data processing procedures are described here. In addition, strain archives and online data resources were accessed. A total of 12,563 spatially and temporally unique occurrences of both cutaneous and visceral leishmaniasis comprise the database, ranging in geographic scale from villages to states. These data can be used for a variety of mapping and spatial analyses covering multiple resolutions.
Publisher: Springer Science and Business Media LLC
Date: 10-2015
Publisher: Springer Science and Business Media LLC
Date: 07-05-2015
Publisher: Elsevier BV
Date: 2020
DOI: 10.1016/J.TREE.2019.08.006
Abstract: With the expansion in the quantity and types of bio ersity data being collected, there is a need to find ways to combine these different sources to provide cohesive summaries of species' potential and realized distributions in space and time. Recently, model-based data integration has emerged as a means to achieve this by combining datasets in ways that retain the strengths of each. We describe a flexible approach to data integration using point process models, which provide a convenient way to translate across ecological currencies. We highlight recent ex les of large-scale ecological models based on data integration and outline the conceptual and technical challenges and opportunities that arise.
Publisher: Springer Science and Business Media LLC
Date: 15-04-2014
Publisher: eLife Sciences Publications, Ltd
Date: 30-06-2015
DOI: 10.7554/ELIFE.08347
Abstract: 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.
Publisher: eLife Sciences Publications, Ltd
Date: 16-06-2015
Publisher: Elsevier BV
Date: 11-2017
Publisher: eLife Sciences Publications, Ltd
Date: 28-08-2014
Publisher: Oxford University Press (OUP)
Date: 17-06-2015
Publisher: Wiley
Date: 30-08-2021
Abstract: Light‐level geolocators are popular bio‐logging tools, with advantageous sizes, longevity and affordability. Biologists tracking seabirds often presume geolocator spatial accuracies between 186 and 202 km from previously innovative, yet taxonomically, spatially and computationally limited, studies. Using recently developed methods, we investigated whether assumed uncertainty norms held across a larger‐scale, multispecies study. We field‐tested geolocator spatial accuracy by synchronously deploying these with GPS loggers on scores of seabirds across five species and 11 Mediterranean Sea, east Atlantic and south Pacific breeding colonies. We first interpolated geolocations using the geolocation package FLightR without prior knowledge of GPS tracked routes. We likewise applied another package, probGLS , additionally testing whether sea‐surface temperatures could improve route accuracy. Geolocator spatial accuracy was lower than the ~200 km often assumed. probGL S produced the best accuracy (mean ± SD = 304 ± 413 km, n = 185 deployments) with 84.5% of GPS‐derived latitudes and 88.8% of longitudes falling within resulting uncertainty estimates. FLightR produced lower spatial accuracy (408 ± 473 km, n = 171 deployments) with 38.6% of GPS‐derived latitudes and 23.7% of longitudes within package‐specific uncertainty estimates. Expected inter‐twilight period (from GPS position and date) was the strongest predictor of accuracy, with increasingly equatorial solar profiles (i.e. closer temporally to equinoxes and/or spatially to the Equator) inducing more error. In iduals, species and geolocator model also significantly affected accuracy, while the impact of distance travelled between successive twilights depended on the geolocation package. Geolocation accuracy is not uniform among seabird species and can be considerably lower than assumed. In idual idiosyncrasies and spatiotemporal dynamics (i.e. shallower inter‐twilight shifts by date and latitude) mean that practitioners should exercise greater caution in interpreting geolocator data and avoid universal uncertainty estimates. We provide a function capable of estimating relative accuracy of positions based on geolocator‐observed inter‐twilight period.
Publisher: Springer Science and Business Media LLC
Date: 12-2013
Publisher: Public Library of Science (PLoS)
Date: 11-10-2017
Publisher: Public Library of Science (PLoS)
Date: 27-03-2014
Publisher: Wiley
Date: 15-10-2020
Publisher: Springer Science and Business Media LLC
Date: 05-03-2016
Publisher: Springer Science and Business Media LLC
Date: 26-03-2019
DOI: 10.1038/S41598-019-41192-3
Abstract: Human mobility is an important driver of geographic spread of infectious pathogens. Detailed information about human movements during outbreaks are, however, difficult to obtain and may not be available during future epidemics. The Ebola virus disease (EVD) outbreak in West Africa between 2014–16 demonstrated how quickly pathogens can spread to large urban centers following one cross-species transmission event. Here we describe a flexible transmission model to test the utility of generalised human movement models in estimating EVD cases and spatial spread over the course of the outbreak. A transmission model that includes a general model of human mobility significantly improves prediction of EVD’s incidence compared to models without this component. Human movement plays an important role not only to ignite the epidemic in locations previously disease free, but over the course of the entire epidemic. We also demonstrate important differences between countries in population mixing and the improved prediction attributable to movement metrics. Given their relative rareness, locally derived mobility data are unlikely to exist in advance of future epidemics or pandemics. Our findings show that transmission patterns derived from general human movement models can improve forecasts of spatio-temporal transmission patterns in places where local mobility data is unavailable.
Publisher: Public Library of Science (PLoS)
Date: 10-06-2015
Publisher: Elsevier BV
Date: 2016
Abstract: Quantitatively mapping the spatial distributions of infectious diseases is key to both investigating their epidemiology and identifying populations at risk of infection. Important advances in data quality and methodologies have allowed for better investigation of disease risk and its association with environmental factors. However, incorporating dynamic human behavioural processes in disease mapping remains challenging. For ex le, connectivity among human populations, a key driver of pathogen dispersal, has increased sharply over the past century, along with the availability of data derived from mobile phones and other dynamic data sources. Future work must be targeted towards the rapid updating and dissemination of appropriately designed disease maps to guide the public health community in reducing the global burden of infectious disease.
Start Date: 05-2018
End Date: 12-2022
Amount: $365,058.00
Funder: Australian Research Council
View Funded ActivityStart Date: 05-2019
End Date: 12-2023
Amount: $437,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 07-2023
End Date: 07-2026
Amount: $590,000.00
Funder: Australian Research Council
View Funded Activity