Predicting the risk of avian influenza A H7N9 infection in live-poultry markets across Asia
TL;DR: Using newly assembled data sets of the locations of 8,943 live-poultry markets in China and maps of environmental correlates, a statistical model is developed that accurately predicts the risk of H7N9 market infection across Asia.
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 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.
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TL;DR: This study demonstrates how data collected by mobile phone network operators can cost-effectively provide accurate and detailed maps of population distribution over national scales and any time period while guaranteeing phone users’ privacy.
Abstract: During the past few decades, technologies such as remote sensing, geographical information systems, and global positioning systems have transformed the way the distribution of human population is studied and modeled in space and time. However, the mapping of populations remains constrained by the logistics of censuses and surveys. Consequently, spatially detailed changes across scales of days, weeks, or months, or even year to year, are difficult to assess and limit the application of human population maps in situations in which timely information is required, such as disasters, conflicts, or epidemics. Mobile phones (MPs) now have an extremely high penetration rate across the globe, and analyzing the spatiotemporal distribution of MP calls geolocated to the tower level may overcome many limitations of census-based approaches, provided that the use of MP data is properly assessed and calibrated. Using datasets of more than 1 billion MP call records from Portugal and France, we show how spatially and temporarily explicit estimations of population densities can be produced at national scales, and how these estimates compare with outputs produced using alternative human population mapping methods. We also demonstrate how maps of human population changes can be produced over multiple timescales while preserving the anonymity of MP users. With similar data being collected every day by MP network providers across the world, the prospect of being able to map contemporary and changing human population distributions over relatively short intervals exists, paving the way for new applications and a near real-time understanding of patterns and processes in human geography.
732 citations
Cites background from "Predicting the risk of avian influe..."
...sets are sampled from geographically distinct regions (56), allowed for a quantitative assessment of the extrapolation capacity of the model (57, 58)....
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TL;DR: The estimates suggest that melioidosis is severely underreported in the 45 countries in which it is known to be endemic and that it is probably endemic in a further 34 countries that have never reported the disease.
Abstract: Burkholderia pseudomallei, a highly pathogenic bacterium that causes melioidosis, is commonly found in soil in Southeast Asia and Northern Australia1,2. Melioidosis can be difficult to diagnose due to its diverse clinical manifestations and the inadequacy of conventional bacterial identification methods3. The bacterium is intrinsically resistant to a wide range of antimicrobials, and treatment with ineffective antimicrobials may result in case fatality rates (CFRs) exceeding 70%4,5. The importation of infected animals has, in the past, spread melioidosis to non-endemic areas6,7. The global distribution of B. pseudomallei and burden of melioidosis, however, remain poorly understood. Here, we map documented human and animal cases, and the presence of environmental B. pseudomallei, and combine this in a formal modelling framework8-10 to estimate the global burden of melioidosis. We estimate there to be 165,000 (95% credible interval 68,000-412,000) human melioidosis cases per year worldwide, of which 89,000 (36,000-227,000) die. Our estimates suggest that melioidosis is severely underreported in the 45 countries in which it is known to be endemic and that melioidosis is likely endemic in a further 34 countries which have never reported the disease. The large numbers of estimated cases and fatalities emphasise that the disease warrants renewed attention from public health officials and policy makers.
653 citations
TL;DR: A map that quantifies travel time to cities for 2015 at a spatial resolution of approximately one by one kilometre is developed and validated and it is demonstrated how access to urban centres stratifies the economic, educational, and health status of humanity.
Abstract: The economic and man-made resources that sustain human wellbeing are not distributed evenly across the world, but are instead heavily concentrated in cities. Poor access to opportunities and services offered by urban centres (a function of distance, transport infrastructure, and the spatial distribution of cities) is a major barrier to improved livelihoods and overall development. Advancing accessibility worldwide underpins the equity agenda of 'leaving no one behind' established by the Sustainable Development Goals of the United Nations. This has renewed international efforts to accurately measure accessibility and generate a metric that can inform the design and implementation of development policies. The only previous attempt to reliably map accessibility worldwide, which was published nearly a decade ago, predated the baseline for the Sustainable Development Goals and excluded the recent expansion in infrastructure networks, particularly in lower-resource settings. In parallel, new data sources provided by Open Street Map and Google now capture transportation networks with unprecedented detail and precision. Here we develop and validate a map that quantifies travel time to cities for 2015 at a spatial resolution of approximately one by one kilometre by integrating ten global-scale surfaces that characterize factors affecting human movement rates and 13,840 high-density urban centres within an established geospatial-modelling framework. Our results highlight disparities in accessibility relative to wealth as 50.9% of individuals living in low-income settings (concentrated in sub-Saharan Africa) reside within an hour of a city compared to 90.7% of individuals in high-income settings. By further triangulating this map against socioeconomic datasets, we demonstrate how access to urban centres stratifies the economic, educational, and health status of humanity.
632 citations
TL;DR: The results indicated that the Landsat 8, GEE, and improved PPPM algorithm can effectively support the yearly mapping of paddy rice in NE Asia and has a high accuracy with the producer (user) accuracy of 73% (92%), based on the validation using very high resolution images and intensive field photos.
496 citations
Cites background from "Predicting the risk of avian influe..."
...Finally, paddy rice agriculture is related to avian influenza virus transmission as paddy rice fields are important habitats for free-ranging ducks and wild waterfowls (Gilbert et al., 2008, 2014)....
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01 Jan 2014
TL;DR: Details of primers used for quantitative PCR and Reverse Transcriptase PCR Gene symbol Forward strand (5’→3’) Reverse strand ( 5’ →3”) FLK-1.
Abstract: Name Sequence Exon 2 mG6pc S 5’-TCCCTGTCACCTGTGAG-3’ Exon 5 mG6pc AS 5’-CACAAGAAGTCTTTGTAA-3’ Exon1 mG6pcS 5’-TTACCAAGACTCCCAGGACTG-3’ Exon2 mG6pcAS 5’-GAGCTGTTGCTGTAGTAGTCG-3’ Pck1S 5’-AGCCTTTGGTCAACAACTGG-3’ Pck1AS 5’-TGCCTTCGGGGTTAGTTATG-3’ GcgR S 5’-ACCCAACTATTGCTGGTTGC-3’ GcgR AS 5’-CCATGTTGTCATTGCTGGTC-3’ Hmgcs2 S 5’-CCGTATGGGCTTCTGTTCAG-3’ Hmgcs2 AS 5’-AGCTTTGTGCGTTCCATCAG-3’ mL19S 5’-AGAAGATTGACCGCCATAT-3’ mL19AS 5’-TTCGTGCTTCCTTGGTCTTAGA-3’ CRU G6pc S 5’-TTTGCTATTTTACGTAAATCACCCT-3’ CRU G6pc AS 5’-GTACCTCAGGAAGCTGCCA-3’ CRU Pck1 S 5’-GGCCTCCCAACATTCATTAAC-3’ CRU Pck1 AS 5’-GTAGCTAGCCCTCCTCGCTTTAA-3’ GRU G6pc S 5’-CACCCCTTAGCACTGTAAGCCGTGTG-3’ GRU G6pc AS 5’-GGATTCAGTCTGTAGGTCAACCTAGCCC-3’ GRU Pck1 S 5’-TGCAGCCAGCAACATATGAA-3’
384 citations
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TL;DR: Copyright (©) 1999–2012 R Foundation for Statistical Computing; permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and permission notice are preserved on all copies.
Abstract: Copyright (©) 1999–2012 R Foundation for Statistical Computing. Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice are preserved on all copies. Permission is granted to copy and distribute modified versions of this manual under the conditions for verbatim copying, provided that the entire resulting derived work is distributed under the terms of a permission notice identical to this one. Permission is granted to copy and distribute translations of this manual into another language, under the above conditions for modified versions, except that this permission notice may be stated in a translation approved by the R Core Team.
272,030 citations
University of Melbourne1, Stony Brook University2, City University of New York3, Princeton University4, University of Lausanne5, University of California, Berkeley6, University of Alaska Fairbanks7, National Institute of Water and Atmospheric Research8, Commonwealth Scientific and Industrial Research Organisation9, University of São Paulo10, University of Missouri11, Consejo Nacional de Ciencia y Tecnología12, University of Kansas13, Landcare Research14, AT&T15, McGill University16, James Cook University17, Swiss Federal Institute for Forest, Snow and Landscape Research18
TL;DR: This work compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date and found that presence-only data were effective for modelling species' distributions for many species and regions.
Abstract: Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species' distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species' occurrence data. Presence-only data were effective for modelling species' distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.
7,589 citations
TL;DR: These new risk maps and infection estimates provide novel insights into the global, regional and national public health burden imposed by dengue and will help to guide improvements in disease control strategies using vaccine, drug and vector control methods, and in their economic evaluation.
Abstract: 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.
7,238 citations
6,448 citations