ORCID Profile
0000-0002-8028-4079
Current Organisation
University of Oxford
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Public Library of Science (PLoS)
Date: 10-08-2020
Publisher: Springer Science and Business Media LLC
Date: 12-2008
DOI: 10.1038/NATURE07632
Publisher: Springer Science and Business Media LLC
Date: 28-07-2012
Publisher: Springer Science and Business Media LLC
Date: 05-10-2018
Publisher: Springer Science and Business Media LLC
Date: 21-02-2017
Publisher: Springer Science and Business Media LLC
Date: 20-02-2017
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: Oxford University Press (OUP)
Date: 28-01-2016
Publisher: The Royal Society
Date: 19-03-2013
Abstract: The primary aim of this review was to evaluate the state of knowledge of the geographical distribution of all infectious diseases of clinical significance to humans. A systematic review was conducted to enumerate cartographic progress, with respect to the data available for mapping and the methods currently applied. The results helped define the minimum information requirements for mapping infectious disease occurrence, and a quantitative framework for assessing the mapping opportunities for all infectious diseases. This revealed that of 355 infectious diseases identified, 174 (49%) have a strong rationale for mapping and of these only 7 (4%) had been comprehensively mapped. A variety of ambitions, such as the quantification of the global burden of infectious disease, international biosurveillance, assessing the likelihood of infectious disease outbreaks and exploring the propensity for infectious disease evolution and emergence, are limited by these omissions. An overview of the factors hindering progress in disease cartography is provided. It is argued that rapid improvement in the landscape of infectious diseases mapping can be made by embracing non-conventional data sources, automation of geo-positioning and mapping procedures enabled by machine learning and information technology, respectively, in addition to harnessing labour of the volunteer ‘cognitive surplus’ through crowdsourcing.
Publisher: Elsevier BV
Date: 12-2017
Publisher: Springer Science and Business Media LLC
Date: 12-2012
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: Public Library of Science (PLoS)
Date: 07-08-2012
Publisher: Springer Science and Business Media LLC
Date: 04-2013
DOI: 10.1038/NATURE12060
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: Public Library of Science (PLoS)
Date: 22-04-2020
Publisher: Cold Spring Harbor Laboratory
Date: 10-2019
DOI: 10.1101/790097
Abstract: Mosquitoes are important vectors for pathogens of humans and other vertebrate animals. Some aspects of adult mosquito behavior and mosquito ecology play an important role in determining the capacity of vector populations to transmit pathogens. Here, we re-examine factors affecting the transmission of pathogens by mosquitoes using a new approach. Unlike most previous models, this framework considers the behavioral states and state transitions of adult mosquitoes through a sequence of activity bouts. We developed a new framework for in idual-based simulation models called MBITES (Mosquito Bout-based and In idual-based Transmission Ecology Simulator). In MBITES, it is possible to build models that simulate the behavior and ecology of adult mosquitoes in exquisite detail on complex resource landscapes generated by spatial point processes. We also developed an ordinary differential equation model which is the Kolmogorov forward equations for models developed in MBITES under a specific set of simplifying assumptions. While infection of the mosquito and pathogen development are one possible part of a mosquito’s state, that is not the main focus. Using extensive simulation using some models developed in MBITES, we show that vectorial capacity can be understood as an emergent property of simple behavioral algorithms interacting with complex resource landscapes, and that relative density or sparsity of resources and the need to search can have profound consequences for mosquito populations’ capacity to transmit pathogens.
Publisher: Elsevier BV
Date: 10-2015
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: Elsevier BV
Date: 08-2018
Publisher: Proceedings of the National Academy of Sciences
Date: 21-05-2018
Abstract: Malaria control programs rely on chemical insecticides to target mosquito vectors and are potentially threatened by the emergence of insecticide resistance in African vector populations. Insecticide resistance management initiatives require comprehensive quantification of resistance in field populations to the set of insecticides used in vector control. We analyzed patterns of variation and covariation in resistance to these insecticides, using statistical methods that handle the sparse spatiotemporal distribution of the available data. We found relationships across different insecticide types that are consistent across large parts of Africa, allowing prediction of resistance to be improved by incorporating observations across multiple insecticide types. We also found large-scale relationships between phenotypic resistance and patterns of genetic variation, demonstrating the potential utility of genetic markers.
Publisher: Springer Science and Business Media LLC
Date: 10-2015
Publisher: Elsevier
Date: 2012
Publisher: eLife Sciences Publications, Ltd
Date: 29-12-2015
DOI: 10.7554/ELIFE.09672
Abstract: Insecticide-treated nets (ITNs) for malaria control are widespread but coverage remains inadequate. We developed a Bayesian model using data from 102 national surveys, triangulated against delivery data and distribution reports, to generate year-by-year estimates of four ITN coverage indicators. We explored the impact of two potential 'inefficiencies': uneven net distribution among households and rapid rates of net loss from households. We estimated that, in 2013, 21% (17%–26%) of ITNs were over-allocated and this has worsened over time as overall net provision has increased. We estimated that rates of ITN loss from households are more rapid than previously thought, with 50% lost after 23 (20–28) months. We predict that the current estimate of 920 million additional ITNs required to achieve universal coverage would in reality yield a lower level of coverage (77% population access). By improving efficiency, however, the 920 million ITNs could yield population access as high as 95%.
Publisher: Elsevier BV
Date: 11-2017
Publisher: Cold Spring Harbor Laboratory
Date: 06-01-2020
DOI: 10.1101/2020.01.06.895656
Abstract: Mitigating the threat of insecticide resistance in African malaria vector populations requires comprehensive information about where resistance occurs, to what degree, and how this has changed over time. Estimating these trends is complicated by the sparse, heterogeneous distribution of observations of resistance phenotypes in field populations. We use 6423 observations of the prevalence of resistance to the most important vector control insecticides to inform a Bayesian geostatistical ensemble modelling approach, generating fine-scale predictive maps of resistance phenotypes in mosquitoes from the Anopheles gambiae complex across Africa. Our models are informed by a suite of 111 predictor variables describing potential drivers of selection for resistance. Our maps show alarming increases in the prevalence of resistance to pyrethroids and DDT across Sub-Saharan Africa from 2005-2017 as well as substantial spatial variation in resistance trends.
Publisher: Oxford University Press (OUP)
Date: 17-06-2015
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: Public Library of Science (PLoS)
Date: 27-03-2014
Publisher: Springer Science and Business Media LLC
Date: 05-03-2016
Publisher: Public Library of Science (PLoS)
Date: 06-09-2012
Publisher: Springer Science and Business Media LLC
Date: 16-03-2017
Publisher: Public Library of Science (PLoS)
Date: 10-06-2015
Publisher: Springer Science and Business Media LLC
Date: 27-03-2013
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: Public Library of Science (PLoS)
Date: 25-06-2020
Publisher: Elsevier BV
Date: 11-2017
Publisher: BMJ
Date: 04-2017
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Catherine Moyes.