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Dive into the research topics where G. R. William Wint is active.

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Featured researches published by G. R. William Wint.


Nature | 2013

The global distribution and burden of dengue

Samir Bhatt; Peter W. Gething; Oliver J. Brady; Jane P. Messina; Andrew Farlow; Catherine L. Moyes; John M. Drake; John S. Brownstein; Anne G. Hoen; Osman Sankoh; Monica F. Myers; Dylan B. George; Thomas Jaenisch; G. R. William Wint; Cameron P. Simmons; Thomas W. Scott; Jeremy Farrar; Simon I. Hay

Dengue is a systemic viral infection transmitted between humans by Aedes mosquitoes. For some patients, dengue is a life-threatening illness. There are currently no licensed vaccines or specific therapeutics, and substantial vector control efforts have not stopped its rapid emergence and global spread. The contemporary worldwide distribution of the risk of dengue virus infection and its public health burden are poorly known. Here we undertake an exhaustive assembly of known records of dengue occurrence worldwide, and use a formal modelling framework to map the global distribution of dengue risk. We then pair the resulting risk map with detailed longitudinal information from dengue cohort studies and population surfaces to infer the public health burden of dengue in 2010. We predict dengue to be ubiquitous throughout the tropics, with local spatial variations in risk influenced strongly by rainfall, temperature and the degree of urbanization. Using cartographic approaches, we estimate there to be 390 million (95% credible interval 284–528) dengue infections per year, of which 96 million (67–136) manifest apparently (any level of disease severity). This infection total is more than three times the dengue burden estimate of the World Health Organization. Stratification of our estimates by country allows comparison with national dengue reporting, after taking into account the probability of an apparent infection being formally reported. The most notable differences are discussed. These new risk maps and infection estimates provide novel insights into the global, regional and national public health burden imposed by dengue. We anticipate that they will provide a starting point for a wider discussion about the global impact of this disease and will help to guide improvements in disease control strategies using vaccine, drug and vector control methods, and in their economic evaluation.


eLife | 2015

The global distribution of the arbovirus vectors Aedes aegypti and Ae. albopictus

Moritz U. G. Kraemer; Marianne E. Sinka; Kirsten A. Duda; Adrian Mylne; Freya M Shearer; Christopher M. Barker; Chester G. Moore; Roberta Gomes Carvalho; Giovanini Evelim Coelho; Wim Van Bortel; Guy Hendrickx; Francis Schaffner; Iqbal Elyazar; Hwa-Jen Teng; Oliver J. Brady; Jane P. Messina; David M Pigott; Thomas W. Scott; David L. Smith; G. R. William Wint; Nick Golding; Simon I. Hay

Dengue and chikungunya are increasing global public health concerns due to their rapid geographical spread and increasing disease burden. Knowledge of the contemporary distribution of their shared vectors, Aedes aegypti and Aedes albopictus remains incomplete and is complicated by an ongoing range expansion fuelled by increased global trade and travel. Mapping the global distribution of these vectors and the geographical determinants of their ranges is essential for public health planning. Here we compile the largest contemporary database for both species and pair it with relevant environmental variables predicting their global distribution. We show Aedes distributions to be the widest ever recorded; now extensive in all continents, including North America and Europe. These maps will help define the spatial limits of current autochthonous transmission of dengue and chikungunya viruses. It is only with this kind of rigorous entomological baseline that we can hope to project future health impacts of these viruses. DOI: http://dx.doi.org/10.7554/eLife.08347.001


PLOS ONE | 2014

Mapping the global distribution of livestock.

Timothy P. Robinson; G. R. William Wint; Giulia Conchedda; Thomas P. Van Boeckel; Valentina Ercoli; Elisa Palamara; Giuseppina Cinardi; Laura D'Aietti; Simon I. Hay; Marius Gilbert

Livestock contributes directly to the livelihoods and food security of almost a billion people and affects the diet and health of many more. With estimated standing populations of 1.43 billion cattle, 1.87 billion sheep and goats, 0.98 billion pigs, and 19.60 billion chickens, reliable and accessible information on the distribution and abundance of livestock is needed for a many reasons. These include analyses of the social and economic aspects of the livestock sector; the environmental impacts of livestock such as the production and management of waste, greenhouse gas emissions and livestock-related land-use change; and large-scale public health and epidemiological investigations. The Gridded Livestock of the World (GLW) database, produced in 2007, provided modelled livestock densities of the world, adjusted to match official (FAOSTAT) national estimates for the reference year 2005, at a spatial resolution of 3 minutes of arc (about 5×5 km at the equator). Recent methodological improvements have significantly enhanced these distributions: more up-to date and detailed sub-national livestock statistics have been collected; a new, higher resolution set of predictor variables is used; and the analytical procedure has been revised and extended to include a more systematic assessment of model accuracy and the representation of uncertainties associated with the predictions. This paper describes the current approach in detail and presents new global distribution maps at 1 km resolution for cattle, pigs and chickens, and a partial distribution map for ducks. These digital layers are made publically available via the Livestock Geo-Wiki (http://www.livestock.geo-wiki.org), as will be the maps of other livestock types as they are produced.


Scientific Data | 2015

The global compendium of Aedes aegypti and Ae. albopictus occurrence.

Moritz U. G. Kraemer; Marianne E. Sinka; Kirsten A. Duda; Adrian Mylne; Freya M Shearer; Oliver J. Brady; Jane P. Messina; Christopher M. Barker; Chester G. Moore; Roberta Gomes Carvalho; Giovanini Evelim Coelho; Wim Van Bortel; Guy Hendrickx; Francis Schaffner; G. R. William Wint; Iqbal Elyazar; Hwa-Jen Teng; Simon I. Hay

Aedes aegypti and Ae. albopictus are the main vectors transmitting dengue and chikungunya viruses. Despite being pathogens of global public health importance, knowledge of their vectors’ global distribution remains patchy and sparse. A global geographic database of known occurrences of Ae. aegypti and Ae. albopictus between 1960 and 2014 was compiled. Herein we present the database, which comprises occurrence data linked to point or polygon locations, derived from peer-reviewed literature and unpublished studies including national entomological surveys and expert networks. We describe all data collection processes, as well as geo-positioning methods, database management and quality-control procedures. This is the first comprehensive global database of Ae. aegypti and Ae. albopictus occurrence, consisting of 19,930 and 22,137 geo-positioned occurrence records respectively. Both datasets can be used for a variety of mapping and spatial analyses of the vectors and, by inference, the diseases they transmit.


Nature Communications | 2014

Predicting the risk of avian influenza A H7N9 infection in live-poultry markets across Asia

Marius Gilbert; Nick Golding; Hang Zhou; G. R. William Wint; Timothy P. Robinson; Andrew J. Tatem; Shengjie Lai; Sheng Zhou; Hui-Hui Jiang; Danhuai Guo; Zhi Huang; Jane P. Messina; Xiangming Xiao; Catherine Linard; Thomas P. Van Boeckel; Samir Bhatt; Peter W. Gething; Jeremy Farrar; Simon I. Hay; Hongjie Yu

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 sampled. 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.


Transactions of The Royal Society of Tropical Medicine and Hygiene | 2015

The global distribution of Crimean-Congo hemorrhagic fever

Jane P. Messina; David M Pigott; Nick Golding; Kirsten A. Duda; John S. Brownstein; Daniel J. Weiss; Harry S. Gibson; Timothy P. Robinson; Marius Gilbert; G. R. William Wint; Patricia A. Nuttall; Peter W. Gething; Monica F. Myers; Dylan B. George; Simon I. Hay

Background Crimean-Congo hemorrhagic fever (CCHF) is a tick-borne infection caused by a virus (CCHFV) from the Bunyaviridae family. Domestic and wild vertebrates are asymptomatic reservoirs for the virus, putting animal handlers, slaughter-house workers and agricultural labourers at highest risk in endemic areas, with secondary transmission possible through contact with infected blood and other bodily fluids. Human infection is characterized by severe symptoms that often result in death. While it is known that CCHFV transmission is limited to Africa, Asia and Europe, definitive global extents and risk patterns within these limits have not been well described. Methods We used an exhaustive database of human CCHF occurrence records and a niche modeling framework to map the global distribution of risk for human CCHF occurrence. Results A greater proportion of shrub or grass land cover was the most important contributor to our model, which predicts highest levels of risk around the Black Sea, Turkey, and some parts of central Asia. Sub-Saharan Africa shows more focalized areas of risk throughout the Sahel and the Cape region. Conclusions These new risk maps provide a valuable starting point for understanding the zoonotic niche of CCHF, its extent and the risk it poses to humans.


Trends in Microbiology | 2002

Mapping bovine tuberculosis in Great Britain using environmental data

G. R. William Wint; Timothy P. Robinson; David M. Bourn; Peter Durr; Simon I. Hay; Sarah E. Randolph; David J. Rogers

The incidence of bovine tuberculosis (BTB) is increasing in Great Britain, exacerbated by the temporary suspension of herd testing in 2001 for fear of spreading the much more contagious foot and mouth disease. The transmission pathways of BTB remain poorly understood. Current hypotheses suggest the disease is introduced into susceptible herds from a wildlife reservoir (principally the Eurasian Badger) and/or from cattle purchased from infected areas, while the role of climatic factors in transmission has generally been ignored. Here, we show how remotely sensed satellite data, which provide good indicators of a variety of climatic factors, can be used to describe the distribution of BTB in Great Britain in 1997, and suggest how such data could be used to produce BTB risk maps for the future.


Nature Reviews Microbiology | 2015

The many projected futures of dengue

Jane P. Messina; Oliver J. Brady; David M Pigott; Nick Golding; Moritz U. G. Kraemer; Thomas W. Scott; G. R. William Wint; David L. Smith; Simon I. Hay

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.


Lancet Infectious Diseases | 2017

Spread of yellow fever virus outbreak in Angola and the Democratic Republic of the Congo 2015–16: a modelling study

Moritz U. G. Kraemer; Nuno Rodrigues Faria; Robert C Reiner; Nick Golding; Birgit Nikolay; Stephanie Stasse; Michael A. Johansson; Henrik Salje; Ousmane Faye; G. R. William Wint; Matthias Niedrig; Freya M Shearer; Sarah C. Hill; Robin N Thompson; Donal Bisanzio; Nuno Taveira; Heinrich H. Nax; Bary S. R. Pradelski; Elaine O. Nsoesie; Nicholas R Murphy; Isaac I. Bogoch; Kamran Khan; John S. Brownstein; Andrew J. Tatem; Tulio de Oliveira; David L. Smith; Amadou A. Sall; Oliver G. Pybus; Simon I. Hay; Simon Cauchemez

Summary Background Since late 2015, an epidemic of yellow fever has caused more than 7334 suspected cases in Angola and the Democratic Republic of the Congo, including 393 deaths. We sought to understand the spatial spread of this outbreak to optimise the use of the limited available vaccine stock. Methods We jointly analysed datasets describing the epidemic of yellow fever, vector suitability, human demography, and mobility in central Africa to understand and predict the spread of yellow fever virus. We used a standard logistic model to infer the district-specific yellow fever virus infection risk during the course of the epidemic in the region. Findings The early spread of yellow fever virus was characterised by fast exponential growth (doubling time of 5–7 days) and fast spatial expansion (49 districts reported cases after only 3 months) from Luanda, the capital of Angola. Early invasion was positively correlated with high population density (Pearsons r 0·52, 95% CI 0·34–0·66). The further away locations were from Luanda, the later the date of invasion (Pearsons r 0·60, 95% CI 0·52–0·66). In a Cox model, we noted that districts with higher population densities also had higher risks of sustained transmission (the hazard ratio for cases ceasing was 0·74, 95% CI 0·13–0·92 per log-unit increase in the population size of a district). A model that captured human mobility and vector suitability successfully discriminated districts with high risk of invasion from others with a lower risk (area under the curve 0·94, 95% CI 0·92–0·97). If at the start of the epidemic, sufficient vaccines had been available to target 50 out of 313 districts in the area, our model would have correctly identified 27 (84%) of the 32 districts that were eventually affected. Interpretation Our findings show the contributions of ecological and demographic factors to the ongoing spread of the yellow fever outbreak and provide estimates of the areas that could be prioritised for vaccination, although other constraints such as vaccine supply and delivery need to be accounted for before such insights can be translated into policy. Funding Wellcome Trust.


Trends in Parasitology | 2016

Progress and Challenges in Infectious Disease Cartography

Moritz U. G. Kraemer; Simon I. Hay; David M Pigott; David L. Smith; G. R. William Wint; Nick Golding

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 example, 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.

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Simon I. Hay

University of Washington

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Nick Golding

University of Melbourne

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David L. Smith

University of Washington

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David M Pigott

University of Washington

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Timothy P. Robinson

International Livestock Research Institute

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