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Buya S, Chuangchang P, Owusu BA. Analysis of land surface temperature with land use and land cover and elevation from NASA MODIS satellite data: a case study of Bali, Indonesia. ENVIRONMENTAL MONITORING AND ASSESSMENT 2022; 194:566. [PMID: 35790582 DOI: 10.1007/s10661-022-10252-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 06/28/2022] [Indexed: 06/15/2023]
Abstract
The Moderate Resolution Imaging Spectroradiometer (MODIS) of the National Aeronautics and Space Administration (NASA) offers numerous land products of the Earth's datasets. On the other hand, researchers find it difficult to retrieve this data for specific places. The methods for extracting and analyzing land surface temperature (LST), land use and land cover (LULC), and elevation are presented in this study. The R commands provided make the time-consuming process of extracting data for specific places much more accessible. As a result, a statistical study of LST over Bali is shown as an example. Over the 15 regions of Bali, a quadratic polynomial identified five possible warming patterns, while a logistic regression model assessed the probability of warming. The findings suggest that 25.2% of Bali has warmed during the last two decades, with temperatures being highest in urban and built-up areas and deciduous forests and inversely associated with elevation. Global warming has sparked a lot of academic interest and has become a serious climate problem. The techniques proposed in this work simplify the extraction of LST, LULC, and elevation data from MODIS satellites. These approaches can also be used on other datasets with identical topologies, such as the normalized difference vegetation index (NDVI), aerosol optical depth (AOD), and night light data.
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Affiliation(s)
- Suhaimee Buya
- School of Information, Computer and Communication Technology, Sirindhorn International Institute of Technology, Thammasat University, Khlong Nueng, Thailand.
- School of Knowledge Science, Japan Advanced Institute of Science and Technology, Nomi, Japan.
- Department of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Pattani, 94000, Thailand.
| | - Potjamas Chuangchang
- Department of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Pattani, 94000, Thailand
| | - Benjamin Atta Owusu
- Department of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Pattani, 94000, Thailand
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Mugenyi A, Muhanguzi D, Hendrickx G, Nicolas G, Waiswa C, Torr S, Welburn SC, Atkinson PM. Spatial analysis of G.f.fuscipes abundance in Uganda using Poisson and Zero-Inflated Poisson regression models. PLoS Negl Trop Dis 2021; 15:e0009820. [PMID: 34871296 PMCID: PMC8648107 DOI: 10.1371/journal.pntd.0009820] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Accepted: 09/17/2021] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Tsetse flies are the major vectors of human trypanosomiasis of the form Trypanosoma brucei rhodesiense and T.b.gambiense. They are widely spread across the sub-Saharan Africa and rendering a lot of challenges to both human and animal health. This stresses effective agricultural production and productivity in Africa. Delimiting the extent and magnitude of tsetse coverage has been a challenge over decades due to limited resources and unsatisfactory technology. In a bid to overcome these limitations, this study attempted to explore modelling skills that can be applied to spatially estimate tsetse abundance in the country using limited tsetse data and a set of remote-sensed environmental variables. METHODOLOGY Entomological data for the period 2008-2018 as used in the model were obtained from various sources and systematically assembled using a structured protocol. Data harmonisation for the purposes of responsiveness and matching was carried out. The key tool for tsetse trapping was itemized as pyramidal trap in many instances and biconical trap in others. Based on the spatially explicit assembled data, we ran two regression models; standard Poisson and Zero-Inflated Poisson (ZIP), to explore the associations between tsetse abundance in Uganda and several environmental and climatic covariates. The covariate data were constituted largely by satellite sensor data in form of meteorological and vegetation surrogates in association with elevation and land cover data. We finally used the Zero-Inflated Poisson (ZIP) regression model to predict tsetse abundance due to its superiority over the standard Poisson after model fitting and testing using the Vuong Non-Nested statistic. RESULTS A total of 1,187 tsetse sampling points were identified and considered as representative for the country. The model results indicated the significance and level of responsiveness of each covariate in influencing tsetse abundance across the study area. Woodland vegetation, elevation, temperature, rainfall, and dry season normalised difference vegetation index (NDVI) were important in determining tsetse abundance and spatial distribution at varied scales. The resultant prediction map shows scaled tsetse abundance with estimated fitted numbers ranging from 0 to 59 flies per trap per day (FTD). Tsetse abundance was found to be largest at low elevations, in areas of high vegetative activity, in game parks, forests and shrubs during the dry season. There was very limited responsiveness of selected predictors to tsetse abundance during the wet season, matching the known fact that tsetse disperse most significantly during wet season. CONCLUSIONS A methodology was advanced to enable compilation of entomological data for 10 years, which supported the generation of tsetse abundance maps for Uganda through modelling. Our findings indicate the spatial distribution of the G. f. fuscipes as; low 0-5 FTD (48%), medium 5.1-35 FTD (18%) and high 35.1-60 FTD (34%) grounded on seasonality. This approach, amidst entomological data shortages due to limited resources and absence of expertise, can be adopted to enable mapping of the vector to provide better decision support towards designing and implementing targeted tsetse and tsetse-transmitted African trypanosomiasis control strategies.
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Affiliation(s)
- Albert Mugenyi
- Coordinating Office for Control of Trypanosomiasis in Uganda, Ministry of Agriculture, Animal Industry and Fisheries, Kampala, Uganda
- School of Biomedical Sciences, Edinburgh Medical School, College of Medicine and Veterinary Medicine, The University of Edinburgh, Edinburgh, United Kingdom
- * E-mail:
| | - Dennis Muhanguzi
- College of Veterinary Medicine Animal Resources and Biosecurity, Makerere University, Kampala, Uganda
| | | | | | - Charles Waiswa
- Coordinating Office for Control of Trypanosomiasis in Uganda, Ministry of Agriculture, Animal Industry and Fisheries, Kampala, Uganda
- College of Veterinary Medicine Animal Resources and Biosecurity, Makerere University, Kampala, Uganda
| | - Steve Torr
- Department of Vector Biology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | - Susan Christina Welburn
- School of Biomedical Sciences, Edinburgh Medical School, College of Medicine and Veterinary Medicine, The University of Edinburgh, Edinburgh, United Kingdom
- International Campus, ZJU-UoE Institute, Zhejiang University School of Medicine, Zhejiang University, Zhejiang, China
| | - Peter M. Atkinson
- Faculty of Science and Technology, Lancaster University, Lancaster, United Kingdom
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Charrahy Z, Yaghoobi-Ershadi MR, Shirzadi MR, Akhavan AA, Rassi Y, Hosseini SZ, Webb NJ, Haque U, Bozorg Omid F, Hanafi-Bojd AA. Climate change and its effect on the vulnerability to zoonotic cutaneous leishmaniasis in Iran. Transbound Emerg Dis 2021; 69:1506-1520. [PMID: 33876891 DOI: 10.1111/tbed.14115] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 04/09/2021] [Accepted: 04/14/2021] [Indexed: 11/28/2022]
Abstract
Zoonotic cutaneous leishmaniasis (ZCL) is an important vector-borne disease with an incidence of 15.8 cases per 100,000 people in Iran in 2019. Despite all efforts to control the disease, ZCL has expanded into new areas during the last decades. The aim of this study was to predict the best ecological niches for both vectors and reservoirs of ZCL under climate change scenarios in Iran. Several online scientific databases were searched. In this study, various scientific sources (Google Scholar, PubMed, SID, Ovid Medline, Web of Science, Irandoc, Magiran) were searched. The inclusion criteria for this study included all records with spatial information about vectors and reservoirs of ZCL which were published between 1980 and 2019. The bioclimatic data were downloaded from online databases. MaxEnt model was used to predict the ecological niches for each species under two climate change scenarios in two periods: the 2030s and 2050s. The results obtained from the model were analysed in ArcMap to find the vulnerability of different provinces for the establishment of ZCL foci. The area under the curve (AUC) for all models was >0.8, which suggests the models are able to make an accurate prediction. The distribution of all studied species in different climatic conditions showed changes. The variables affecting each of the studied species are introduced in the article. The predicted maps show that by 2050 there will be more suitable areas for the co-occurrence of vector and reservoir(s) of ZCL in Iran compared to the current climate condition and RCP2.6 scenario. An area in the northwest of Iran is predicted to have suitable environmental conditions for both vectors and reservoirs of ZCL, although the disease has not yet been reported in this area. These areas should be considered for field studies to confirm these results and to prevent the establishment of new ZCL foci in Iran.
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Affiliation(s)
- Zabihollah Charrahy
- Department of Natural Resources, School of Environment, University of Tehran, Tehran, Iran
| | - Mohammad Reza Yaghoobi-Ershadi
- Department of Medical Entomology & Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Reza Shirzadi
- Center for Communicable Diseases Control, Ministry of Health and Medical Education, Tehran, Iran
| | - Amir Ahmad Akhavan
- Department of Medical Entomology & Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Yavar Rassi
- Department of Medical Entomology & Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Seyedeh Zohreh Hosseini
- Department of Medical Entomology & Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Nathaniel J Webb
- Department of Health Behavior Research, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Ubydul Haque
- Department of Biostatistics and Epidemiology, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Faramarz Bozorg Omid
- Department of Medical Entomology & Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Ahmad Ali Hanafi-Bojd
- Department of Medical Entomology & Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.,Zoonoses Research Center, Tehran University of Medical Sciences, Tehran, Iran
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Hu X, Xu H. Spatial variability of urban climate in response to quantitative trait of land cover based on GWR model. ENVIRONMENTAL MONITORING AND ASSESSMENT 2019; 191:194. [PMID: 30815726 DOI: 10.1007/s10661-019-7343-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2018] [Accepted: 02/19/2019] [Indexed: 06/09/2023]
Abstract
Land surface temperature and moisture are central components of the Earth's surface heat budget. China has experienced substantial land use/cover change that has led to deterioration of the urban microclimate, thus affecting global climate change. Understanding the spatial non-stationarity in the relationships between climate and land cover across a highly heterogeneous surface of urban landscapes is important for improving urban planning and management. This study used Landsat-8 OLI/TIRS data to explore the relationship of the three components (index-based built-up index (IBI); bare soil index (SI); and normalized difference vegetation index (NDVI)) with the urban climate (land surface temperature (LST) and land surface moisture (LSM)) using both a global model (ordinary least squares (OLS)) and a local model (geographically weighted regression (GWR)) for a megacity in Southeast China. The global regression results showed that there were significant positive correlations between the LST and the IBI and SI, while significant negative correlations were observed between the LST and the NDVI; opposite results were observed for the LSM. The IBI is the factor having the greatest impact on the LST, while the SI is among the most important factors for the LSM. The local regression results showed that the response of urban climate to land surface is affected greatly by water areas, but the role of the water areas is impacted by their size and surrounding landscape patterns. Moreover, the effects of vegetation and built-up land on the urban climate vary across locations with different wind patterns.
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Affiliation(s)
- Xisheng Hu
- College of Environment and Resources, Fuzhou University, Fuzhou, 350108, Fujian, China
- College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou, 350002, Fujian, China
| | - Hanqiu Xu
- College of Environment and Resources, Fuzhou University, Fuzhou, 350108, Fujian, China.
- Institute of Remote Sensing Information Engineering, Fuzhou University, Fuzhou, 350108, Fujian, China.
- Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion and Disaster Protection, Fuzhou, China.
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Jia P, Stein A, James P, Brownson RC, Wu T, Xiao Q, Wang L, Sabel CE, Wang Y. Earth Observation: Investigating Noncommunicable Diseases from Space. Annu Rev Public Health 2019; 40:85-104. [PMID: 30633713 DOI: 10.1146/annurev-publhealth-040218-043807] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The United Nations has called on all nations to take immediate actions to fight noncommunicable diseases (NCDs), which have become an increasingly significant burden to public health systems around the world. NCDs tend to be more common in developed countries but are also becoming of growing concern in low- and middle-income countries. Earth observation (EO) technologies have been used in many infectious disease studies but have been less commonly employed in NCD studies. This review discusses the roles that EO data and technologies can play in NCD research, including ( a) integrating natural and built environment factors into NCD research, ( b) explaining individual-environment interactions, ( c) scaling up local studies and interventions, ( d) providing repeated measurements for longitudinal studies including cohorts, and ( e) advancing methodologies in NCD research. Such extensions hold great potential for overcoming the challenges of inaccurate and infrequent measurements of environmental exposure at the level of both the individual and the population, which is of great importance to NCD research, practice, and policy.
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Affiliation(s)
- Peng Jia
- Department of Earth Observation Science, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7514 AE Enschede, The Netherlands; .,International Initiative on Spatial Lifecourse Epidemiology (ISLE), 7500 AE Enschede, The Netherlands
| | - Alfred Stein
- Department of Earth Observation Science, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7514 AE Enschede, The Netherlands;
| | - Peter James
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts 02215, USA
| | - Ross C Brownson
- Prevention Research Center in St. Louis, Brown School; Department of Surgery and Alvin J. Siteman Cancer Center, Washington University School of Medicine, Washington University in St. Louis, St. Louis, Missouri 63130, USA
| | - Tong Wu
- School of Life Sciences, Arizona State University, Tempe, Arizona 85287-4701, USA
| | - Qian Xiao
- Department of Health and Human Physiology, University of Iowa, Iowa City, Iowa 52242-1111, USA
| | - Limin Wang
- National Center for Chronic and Non-Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Clive E Sabel
- Department of Environmental Science, Aarhus University, DK-4000 Roskilde, Denmark.,Danish Big Data Centre for Environment and Health (BERTHA), DK-4000 Roskilde, Denmark
| | - Youfa Wang
- Global Health Institute; and Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710049, China
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Dietrich D, Dekova R, Davy S, Fahrni G, Geissbühler A. Applications of Space Technologies to Global Health: Scoping Review. J Med Internet Res 2018; 20:e230. [PMID: 29950289 PMCID: PMC6041558 DOI: 10.2196/jmir.9458] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2017] [Revised: 03/21/2018] [Accepted: 04/22/2018] [Indexed: 12/27/2022] Open
Abstract
Background Space technology has an impact on many domains of activity on earth, including in the field of global health. With the recent adoption of the United Nations’ Sustainable Development Goals that highlight the need for strengthening partnerships in different domains, it is useful to better characterize the relationship between space technology and global health. Objective The aim of this study was to identify the applications of space technologies to global health, the key stakeholders in the field, as well as gaps and challenges. Methods We used a scoping review methodology, including a literature review and the involvement of stakeholders, via a brief self-administered, open-response questionnaire. A distinct search on several search engines was conducted for each of the four key technological domains that were previously identified by the UN Office for Outer Space Affairs’ Expert Group on Space and Global Health (Domain A: remote sensing; Domain B: global navigation satellite systems; Domain C: satellite communication; and Domain D: human space flight). Themes in which space technologies are of benefit to global health were extracted. Key stakeholders, as well as gaps, challenges, and perspectives were identified. Results A total of 222 sources were included for Domain A, 82 sources for Domain B, 144 sources for Domain C, and 31 sources for Domain D. A total of 3 questionnaires out of 16 sent were answered. Global navigation satellite systems and geographic information systems are used for the study and forecasting of communicable and noncommunicable diseases; satellite communication and global navigation satellite systems for disaster response; satellite communication for telemedicine and tele-education; and global navigation satellite systems for autonomy improvement, access to health care, as well as for safe and efficient transportation. Various health research and technologies developed for inhabited space flights have been adapted for terrestrial use. Conclusions Although numerous examples of space technology applications to global health exist, improved awareness, training, and collaboration of the research community is needed.
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Affiliation(s)
- Damien Dietrich
- Hopitaux Universitaires de Genève, eHealth and Telemedicine Division, Geneva, Switzerland
| | - Ralitza Dekova
- Hopitaux Universitaires de Genève, eHealth and Telemedicine Division, Geneva, Switzerland
| | - Stephan Davy
- Hopitaux Universitaires de Genève, eHealth and Telemedicine Division, Geneva, Switzerland
| | - Guillaume Fahrni
- Hopitaux Universitaires de Genève, eHealth and Telemedicine Division, Geneva, Switzerland
| | - Antoine Geissbühler
- Hopitaux Universitaires de Genève, eHealth and Telemedicine Division, Geneva, Switzerland
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Vianna EN, Souza e Guimarães RJDP, Souza CR, Gorla D, Diotaiuti L. Chagas disease ecoepidemiology and environmental changes in northern Minas Gerais state, Brazil. Mem Inst Oswaldo Cruz 2017; 112:760-768. [PMID: 29091136 PMCID: PMC5661899 DOI: 10.1590/0074-02760170061] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2017] [Accepted: 06/01/2017] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Triatoma sordida and Triatoma pseudomaculata are frequently captured triatomine species in the Brazilian savannah and caatinga biomes, respectively, and in Brazilian domiciles. OBJECTIVES This study identified eco-epidemiological changes in Chagas disease in northern Minas Gerais state, Brazil, and considered the influence of environmental shifts and both natural and anthropogenic effects. METHODS Domicile infestation and Trypanosoma cruzi infection rates were obtained from triatomines and sylvatic reservoirs during the following two time periods: the 1980s and 2007/2008. Entomological and climatic data with land cover classification derived from satellite imagery were integrated into a geographic information system (GIS), which was applied for atmospheric correction, segmentation, image classification, and mapping and to analyse data obtained in the field. Climatic data were analysed and compared to land cover classifications. RESULTS A comparison of current data with data obtained in the 1980's showed that T. sordida colonised domiciliary areas in both periods, and that T. pseudomaculata did not colonise these areas. There was a tendency toward a reduction in T. cruzi infection rates in sylvatic reservoirs, and of triatomines captured in both households and in the sylvatic environment. T. sordida populations have reduced in the sylvatic environment, while T. pseudomaculata showed an expanding trend in the region compared to counts observed in the 1980's in the sylvatic environment. This may be related to high deforestation rates as well as gradual increases in land surface temperature (LST) and temperatures along the years. MAIN CONCLUSIONS Our results suggest a geographical expansion of species into new biomes as a result of anthropogenic and climatic changes that directly interfere with the reproductive and infection processes of vectors.
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Affiliation(s)
- Elisa Neves Vianna
- Universidade de Brasília, Faculdade de Medicina, Departamento de Patologia, Brasília, DF, Brasil
| | | | | | - David Gorla
- Universidad Nacional de Córdoba, Instituto de Altos Estudios Espaciales Mario Gulich, CONICET, Córdoba, Argentina
| | - Liléia Diotaiuti
- Fundação Oswaldo Cruz-Fiocruz, Centro de Pesquisas René Rachou, Laboratório de Triatomíneos e Epidemiologia da Doença de Chagas, Belo Horizonte, MG, Brasil
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Analyzing the Potential Risk of Climate Change on Lyme Disease in Eastern Ontario, Canada Using Time Series Remotely Sensed Temperature Data and Tick Population Modelling. REMOTE SENSING 2017. [DOI: 10.3390/rs9060609] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
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9
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Impacts of Land Cover and Seasonal Variation on Maximum Air Temperature Estimation Using MODIS Imagery. REMOTE SENSING 2017. [DOI: 10.3390/rs9030233] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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10
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From Space to the Rocky Intertidal: Using NASA MODIS Sea Surface Temperature and NOAA Water Temperature to Predict Intertidal Logger Temperature. REMOTE SENSING 2017. [DOI: 10.3390/rs9020162] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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11
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Estimating Daily Maximum and Minimum Land Air Surface Temperature Using MODIS Land Surface Temperature Data and Ground Truth Data in Northern Vietnam. REMOTE SENSING 2016. [DOI: 10.3390/rs8121002] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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12
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A Remote Sensing Method for Estimating Surface Air Temperature and Surface Vapor Pressure on a Regional Scale. REMOTE SENSING 2015. [DOI: 10.3390/rs70506005] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Walz Y, Wegmann M, Dech S, Raso G, Utzinger J. Risk profiling of schistosomiasis using remote sensing: approaches, challenges and outlook. Parasit Vectors 2015; 8:163. [PMID: 25890278 PMCID: PMC4406176 DOI: 10.1186/s13071-015-0732-6] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2014] [Accepted: 02/12/2015] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND Schistosomiasis is a water-based disease that affects an estimated 250 million people, mainly in sub-Saharan Africa. The transmission of schistosomiasis is spatially and temporally restricted to freshwater bodies that contain schistosome cercariae released from specific snails that act as intermediate hosts. Our objective was to assess the contribution of remote sensing applications and to identify remaining challenges in its optimal application for schistosomiasis risk profiling in order to support public health authorities to better target control interventions. METHODS We reviewed the literature (i) to deepen our understanding of the ecology and the epidemiology of schistosomiasis, placing particular emphasis on remote sensing; and (ii) to fill an identified gap, namely interdisciplinary research that bridges different strands of scientific inquiry to enhance spatially explicit risk profiling. As a first step, we reviewed key factors that govern schistosomiasis risk. Secondly, we examined remote sensing data and variables that have been used for risk profiling of schistosomiasis. Thirdly, the linkage between the ecological consequence of environmental conditions and the respective measure of remote sensing data were synthesised. RESULTS We found that the potential of remote sensing data for spatial risk profiling of schistosomiasis is - in principle - far greater than explored thus far. Importantly though, the application of remote sensing data requires a tailored approach that must be optimised by selecting specific remote sensing variables, considering the appropriate scale of observation and modelling within ecozones. Interestingly, prior studies that linked prevalence of Schistosoma infection to remotely sensed data did not reflect that there is a spatial gap between the parasite and intermediate host snail habitats where disease transmission occurs, and the location (community or school) where prevalence measures are usually derived from. CONCLUSIONS Our findings imply that the potential of remote sensing data for risk profiling of schistosomiasis and other neglected tropical diseases has yet to be fully exploited.
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Affiliation(s)
- Yvonne Walz
- Department of Remote Sensing, Institute for Geography and Geology, University of Würzburg, Würzburg, Germany. .,United Nations University - Institute for Environment and Human Security, Bonn, Germany.
| | - Martin Wegmann
- Department of Remote Sensing, Institute for Geography and Geology, University of Würzburg, Würzburg, Germany.
| | - Stefan Dech
- Department of Remote Sensing, Institute for Geography and Geology, University of Würzburg, Würzburg, Germany. .,German Remote Sensing Data Centre, German Aerospace Centre, Oberpfaffenhofen, Germany.
| | - Giovanna Raso
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland. .,University of Basel, Basel, Switzerland.
| | - Jürg Utzinger
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland. .,University of Basel, Basel, Switzerland.
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Lauer A, Talamantes J, Castañón Olivares LR, Medina LJ, Baal JDH, Casimiro K, Shroff N, Emery KW. Combining forces--the use of Landsat TM satellite imagery, soil parameter information, and multiplex PCR to detect Coccidioides immitis growth sites in Kern County, California. PLoS One 2014; 9:e111921. [PMID: 25380290 PMCID: PMC4224400 DOI: 10.1371/journal.pone.0111921] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2013] [Accepted: 10/08/2014] [Indexed: 12/29/2022] Open
Abstract
Coccidioidomycosis is a fungal disease acquired through the inhalation of spores of Coccidioides spp., which afflicts primarily humans and other mammals. It is endemic to areas in the southwestern United States, including the San Joaquin Valley portion of Kern County, California, our region of interest (ROI). Recently, incidence of coccidioidomycosis, also known as valley fever, has increased significantly, and several factors including climate change have been suggested as possible drivers for this observation. Up to date details about the ecological niche of C. immitis have escaped full characterization. In our project, we chose a three-step approach to investigate this niche: 1) We examined Landsat-5-Thematic-Mapper multispectral images of our ROI by using training pixels at a 750 m × 750 m section of Sharktooth Hill, a site confirmed to be a C. immitis growth site, to implement a Maximum Likelihood Classification scheme to map out the locations that could be suitable to support the growth of the pathogen; 2) We used the websoilsurvey database of the US Department of Agriculture to obtain soil parameter data; and 3) We investigated soil samples from 23 sites around Bakersfield, California using a multiplex Polymerase Chain Reaction (PCR) based method to detect the pathogen. Our results indicated that a combination of satellite imagery, soil type information, and multiplex PCR are powerful tools to predict and identify growth sites of C. immitis. This approach can be used as a basis for systematic sampling and investigation of soils to detect Coccidioides spp.
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Affiliation(s)
- Antje Lauer
- Department of Biology, California State University, Bakersfield, California, United States of America
| | - Jorge Talamantes
- Department of Physics & Engineering, California State University, Bakersfield, California, United States of America
| | | | - Luis Jaime Medina
- Department of Physics & Engineering, California State University, Bakersfield, California, United States of America
| | - Joe Daryl Hugo Baal
- Department of Biology, California State University, Bakersfield, California, United States of America
| | - Kayla Casimiro
- Department of Biology, California State University, Bakersfield, California, United States of America
| | - Natasha Shroff
- Department of Biology, California State University, Bakersfield, California, United States of America
| | - Kirt W. Emery
- County of Kern Public Health Services Department, Bakersfield, California, United States of America
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Xu Z, Liu Y, Ma Z, Li S, Hu W, Tong S. Impact of temperature on childhood pneumonia estimated from satellite remote sensing. ENVIRONMENTAL RESEARCH 2014; 132:334-41. [PMID: 24834830 DOI: 10.1016/j.envres.2014.04.021] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2014] [Revised: 04/07/2014] [Accepted: 04/10/2014] [Indexed: 05/20/2023]
Abstract
The effect of temperature on childhood pneumonia in subtropical regions is largely unknown so far. This study examined the impact of temperature on childhood pneumonia in Brisbane, Australia. A quasi-Poisson generalized linear model combined with a distributed lag non-linear model was used to quantify the main effect of temperature on emergency department visits (EDVs) for childhood pneumonia in Brisbane from 2001 to 2010. The model residuals were checked to identify added effects due to heat waves or cold spells. Both high and low temperatures were associated with an increase in EDVs for childhood pneumonia. Children aged 2-5 years, and female children were particularly vulnerable to the impacts of heat and cold, and Indigenous children were sensitive to heat. Heat waves and cold spells had significant added effects on childhood pneumonia, and the magnitude of these effects increased with intensity and duration. There were changes over time in both the main and added effects of temperature on childhood pneumonia. Children, especially those female and Indigenous, should be particularly protected from extreme temperatures. Future development of early warning systems should take the change over time in the impact of temperature on children's health into account.
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Affiliation(s)
- Zhiwei Xu
- School of Public Health and Social Work & Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
| | - Yang Liu
- Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Zongwei Ma
- Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Shenghui Li
- School of Public Health, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Wenbiao Hu
- School of Public Health and Social Work & Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
| | - Shilu Tong
- School of Public Health and Social Work & Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia.
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16
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Weiss DJ, Bhatt S, Mappin B, Van Boeckel TP, Smith DL, Hay SI, Gething PW. Air temperature suitability for Plasmodium falciparum malaria transmission in Africa 2000-2012: a high-resolution spatiotemporal prediction. Malar J 2014; 13:171. [PMID: 24886586 PMCID: PMC4022538 DOI: 10.1186/1475-2875-13-171] [Citation(s) in RCA: 54] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2014] [Accepted: 04/24/2014] [Indexed: 11/12/2022] Open
Abstract
Background Temperature suitability for malaria transmission is a useful predictor variable for spatial models of malaria infection prevalence. Existing continental or global models, however, are synoptic in nature and so do not characterize inter-annual variability in seasonal patterns of temperature suitability, reducing their utility for predicting malaria risk. Methods A malaria Temperature Suitability Index (TSI) was created by first modeling minimum and maximum air temperature with an eight-day temporal resolution from gap-filled MODerate Resolution Imaging Spectroradiometer (MODIS) daytime and night-time Land Surface Temperature (LST) datasets. An improved version of an existing biological model for malaria temperature suitability was then applied to the resulting temperature information for a 13-year data series. The mechanism underlying this biological model is simulation of emergent mosquito cohorts on a two-hour time-step and tracking of each cohort throughout its life to quantify the impact air temperature has on both mosquito survival and sporozoite development. Results The results of this research consist of 154 monthly raster surfaces that characterize spatiotemporal patterns in TSI across Africa from April 2000 through December 2012 at a 1 km spatial resolution. Generalized TSI patterns were as expected, with consistently high values in equatorial rain forests, seasonally variable values in tropical savannas (wet and dry) and montane areas, and low values in arid, subtropical regions. Comparisons with synoptic approaches demonstrated the additional information available within the dynamic TSI dataset that is lost in equivalent synoptic products derived from long-term monthly averages. Conclusions The dynamic TSI dataset presented here provides a new product with far richer spatial and temporal information than any other presently available for Africa. As spatiotemporal malaria modeling endeavors evolve, dynamic predictor variables such as the malaria temperature suitability data developed here will be essential for the rational assessment of changing patterns of malaria risk.
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Affiliation(s)
- Daniel J Weiss
- Department of Zoology, Spatial Ecology and Epidemiology Group, Tinbergen Building, University of Oxford, South Parks Road, Oxford, UK.
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17
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An environmental data set for vector-borne disease modeling and epidemiology. PLoS One 2014; 9:e94741. [PMID: 24755954 PMCID: PMC3995884 DOI: 10.1371/journal.pone.0094741] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2012] [Accepted: 03/19/2014] [Indexed: 12/04/2022] Open
Abstract
Understanding the environmental conditions of disease transmission is important in the study of vector-borne diseases. Low- and middle-income countries bear a significant portion of the disease burden; but data about weather conditions in those countries can be sparse and difficult to reconstruct. Here, we describe methods to assemble high-resolution gridded time series data sets of air temperature, relative humidity, land temperature, and rainfall for such areas; and we test these methods on the island of Madagascar. Air temperature and relative humidity were constructed using statistical interpolation of weather station measurements; the resulting median 95th percentile absolute errors were 2.75°C and 16.6%. Missing pixels from the MODIS11 remote sensing land temperature product were estimated using Fourier decomposition and time-series analysis; thus providing an alternative to the 8-day and 30-day aggregated products. The RFE 2.0 remote sensing rainfall estimator was characterized by comparing it with multiple interpolated rainfall products, and we observed significant differences in temporal and spatial heterogeneity relevant to vector-borne disease modeling.
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18
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Distribution and abundance of phlebotominae, vectors of leishmaniasis, in Argentina: spatial and temporal analysis at different scales. J Trop Med 2012; 2012:652803. [PMID: 22315620 PMCID: PMC3270461 DOI: 10.1155/2012/652803] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2011] [Revised: 09/27/2011] [Accepted: 10/02/2011] [Indexed: 11/27/2022] Open
Abstract
The spatial-temporal analysis of the abundance of insects, vectors of tegumentary leishmaniasis (TL) and visceral leishmaniasis (VL), was performed in Argentina using spatial-temporal increasing scales. In the microscale (microfocal), the effect of the primary vegetation-crop interface in vector abundance was observed, and also how the shelters, food sources, and other environmental characteristics contribute to habitat microheterogeneity and so to a microheterogeneous vector distribution. In the mesoscale (locality or epidemic focus), the results from different foci of TL (rural and periurban) and VL (urban) suggested a metapopulation structure determined partially by quantifiable habitat variables that could explain the increase of risk associated to an increase of vector-human contact due to climatic or anthropogenic changes. In the macroscale (regional), captures of vectors and records of human cases allowed the construction of risk maps and predictive models of vector distribution. In conclusion, in order to obtain valid results transferrable to control programs from spatial studies, special attention should be paid in order to assure the consistency between the spatial scales of the hypotheses, data, and analytical tools of each experimental or descriptive design.
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19
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Troyo A, Fuller DO, Calderón-Arguedas O, Solano ME, Beier JC. Urban structure and dengue fever in Puntarenas, Costa Rica. SINGAPORE JOURNAL OF TROPICAL GEOGRAPHY 2009; 30:265-282. [PMID: 20161131 PMCID: PMC2743112 DOI: 10.1111/j.1467-9493.2009.00367.x] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Dengue is currently the most important arboviral disease globally and is usually associated with built environments in tropical areas. Remotely sensed information can facilitate the study of urban mosquito-borne diseases by providing multiple temporal and spatial resolutions appropriate to investigate urban structure and ecological characteristics associated with infectious disease. In this study, coarse, medium and fine resolution satellite imagery (Moderate Resolution Imaging Spectrometer, Advanced Spaceborne Thermal Emission and Reflection Radiometer and QuickBird respectively) and ground-based data were analyzed for the Greater Puntarenas area, Costa Rica for the years 2002-04. The results showed that the mean normalized difference vegetation index (NDVI) was generally higher in the localities with lower incidence of dengue fever during 2002, although the correlation was statistically significant only in the dry season (r=-0.40; p=0.03). Dengue incidence was inversely correlated to built area and directly correlated with tree cover (r=0.75, p=0.01). Overall, the significant correlations between dengue incidence and urban structural variables (tree cover and building density) suggest that properties of urban structure may be associated with dengue incidence in tropical urban settings.
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Affiliation(s)
- Adriana Troyo
- Global Public Health Program, Department of Epidemiology and Public Health, University of Miami, Florida, USA
- Centro de Investigación en Enfermedades Tropicales, Departamento de Parasitología, Facultad de Microbiología, Universidad de Costa Rica, San José, Costa Rica
| | - Douglas O. Fuller
- Department of Geography and Regional Studies, University of Miami, Coral Gables, Florida, USA
| | - Olger Calderón-Arguedas
- Centro de Investigación en Enfermedades Tropicales, Departamento de Parasitología, Facultad de Microbiología, Universidad de Costa Rica, San José, Costa Rica
| | - Mayra E. Solano
- Centro de Investigación en Enfermedades Tropicales, Departamento de Parasitología, Facultad de Microbiología, Universidad de Costa Rica, San José, Costa Rica
| | - John C. Beier
- Global Public Health Program, Department of Epidemiology and Public Health, University of Miami, Florida, USA
- Abess Center for Ecosystem Science and Policy, University of Miami, Coral Gables, Florida, USA
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20
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Lleo MM, Lafaye M, Guell A. Application of space technologies to the surveillance and modelling of waterborne diseases. Curr Opin Biotechnol 2008; 19:307-12. [DOI: 10.1016/j.copbio.2008.04.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2008] [Revised: 03/31/2008] [Accepted: 04/02/2008] [Indexed: 11/27/2022]
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21
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Tatem AJ. Global climate matching: Satellite imagery as a tool for mapping vineyard suitability. ACTA ACUST UNITED AC 2007. [DOI: 10.1080/1260500236682] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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22
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Hay SI, Tatem AJ, Graham AJ, Goetz SJ, Rogers DJ. Global environmental data for mapping infectious disease distribution. ADVANCES IN PARASITOLOGY 2006; 62:37-77. [PMID: 16647967 PMCID: PMC3154638 DOI: 10.1016/s0065-308x(05)62002-7] [Citation(s) in RCA: 125] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
This contribution documents the satellite data archives, data processing methods and temporal Fourier analysis (TFA) techniques used to create the remotely sensed datasets on the DVD distributed with this volume. The aim is to provide a detailed reference guide to the genesis of the data, rather than a standard review. These remotely sensed data cover the entire globe at either 1 x 1 or 8 x 8 km spatial resolution. We briefly evaluate the relationships between the 1 x 1 and 8 x 8 km global TFA products to explore their inter-compatibility. The 8 x 8 km TFA surfaces are used in the mapping procedures detailed in the subsequent disease mapping reviews, since the 1 x 1 km products have been validated less widely. Details are also provided on additional, current and planned sensors that should be able to provide continuity with these environmental variable surfaces, as well as other sources of global data that may be used for mapping infectious disease.
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Affiliation(s)
- S I Hay
- TALA Research Group, Tinbergen Building, Department of Zoology, University of Oxford, South Parks Road, Oxford, UK
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23
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Madder M, Speybroeck N, Bilounga A, Helleputte D, Berkvens D. Survival of unfed Rhipicephalus appendiculatus and Rhipicephalus zambeziensis adults. MEDICAL AND VETERINARY ENTOMOLOGY 2005; 19:245-50. [PMID: 16134972 DOI: 10.1111/j.1365-2915.2005.00566.x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Two ixodid tick species, Rhipicephalus appendiculatus (Neumann) and Rhipicephalus zambeziensis (Walker et al.) (Acari: Ixodidae), both originating from the southern province of Zambia, were used to study the survival time of adults at a range of different humidities and temperatures. In general, the experiment clearly demonstrates the different survival times of the two species in relation to the climatic conditions tested: survival of R. zambeziensis was better under more extreme conditions of temperature and humidity. These findings offer an explanation for the different distribution ranges of the two tick species. Rhipicephalus appendiculatus is more confined to cooler and wetter conditions, whereas R. zambeziensis is adapted to hotter and drier areas.
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Affiliation(s)
- M Madder
- Department of Animal Health, Institute of Tropical Medicine, Nationalestraat 155, B-2000 Antwerp, Belgium.
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24
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Tatem AJ, Goetz SJ, Hay SI. Terra and Aqua: new data for epidemiology and public health. ACTA ACUST UNITED AC 2004; 6:33-46. [PMID: 22545030 DOI: 10.1016/j.jag.2004.07.001] [Citation(s) in RCA: 50] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
Earth-observing satellites have only recently been exploited for the measurement of environmental variables of relevance to epidemiology and public health. Such work has relied on sensors with spatial, spectral and geometric constraints that have allowed large-area questions associated with the epidemiology of vector-borne diseases to be addressed. Moving from pretty maps to pragmatic control tools requires a suite of satellite-derived environmental data of higher fidelity, spatial resolution, spectral depth and at similar temporal resolutions to existing meteorological satellites. Information derived from sensors onboard the next generation of moderate-resolution Earth-observing sensors may provide the key. The MODIS and ASTER sensors onboard the Terra and Aqua platforms provide substantial improvements in spatial resolution, number of spectral channels, choices of bandwidths, radiometric calibration and a much-enhanced set of pre-processed and freely available products. These sensors provide an important advance in moderate-resolution remote sensing and the data available to those concerned with improving public health.
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Affiliation(s)
- Andrew J Tatem
- TALA Research Group, Department of Zoology, University of Oxford, South Parks Road, Oxford, OX1 3PS, UK
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25
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Purse BV, Tatem AJ, Caracappa S, Rogers DJ, Mellor PS, Baylis M, Torina A. Modelling the distributions of Culicoides bluetongue virus vectors in Sicily in relation to satellite-derived climate variables. MEDICAL AND VETERINARY ENTOMOLOGY 2004; 18:90-101. [PMID: 15189233 DOI: 10.1111/j.0269-283x.2004.00492.x] [Citation(s) in RCA: 52] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Surveillance data from 268 sites in Sicily are used to develop climatic models for prediction of the distribution of the main European bluetongue virus (BTV) vector Culicoides imicola Kieffer (Diptera: Ceratopogonidae) and of potential novel vectors, Culicoides pulicaris Linnaeus, Culicoides obsoletus group Meigen and Culicoides newsteadi Austen. The models containing the 'best' climatic predictors of distribution for each species, were selected from combinations of 40 temporally Fourier-processed remotely sensed variables and altitude at a 1 km spatial resolution using discriminant analysis. Kappa values of around 0.6 for all species models indicated substantial levels of agreement between model predictions and observed data. Whilst the distributions of C. obsoletus group and C. newsteadi were predicted by temperature variables, those of C. pulicaris and C. imicola were determined mainly by normalized difference vegetation index (NDVI), a variable correlated with soil moisture and vegetation biomass and productivity. These models were used to predict species presence in unsampled pixels across Italy and for C. imicola across Europe and North Africa. The predicted continuous presence of C. pulicaris along the appenine mountains, from north to south Italy, suggests BTV transmission may be possible in a large proportion of this region and that seasonal transhumance (seasonal movement of livestock between upland and lowland pastures) even in C. imicola-free areas should not generally be considered safe. The predicted distribution of C. imicola distribution shows substantial agreement with observed surveillance data from Greece and Iberia (including the Balearics) and parts of mainland Italy (Lazio, Tuscany and areas of the Ionian coast) but is generally much more restricted than the observed distribution (in Sardinia, Corsica and Morocco). The low number of presence sites for C. imicola in Sicily meant that only a restricted range of potential C. imicola habitats were included in the training set and that predictions could only be made within this range. Future modelling exercises will use abundance data collected according to a standardized protocol across the Mediterranean and, for Sicily in particular, should include non-climatic environmental variables that may influence breeding site suitability such as soil type.
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Affiliation(s)
- B V Purse
- Institute for Animal Health, Pirbright, UK.
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26
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Estrada-Peña A, Quíez J, Sánchez Acedo C. Species composition, distribution, and ecological preferences of the ticks of grazing sheep in north-central Spain. MEDICAL AND VETERINARY ENTOMOLOGY 2004; 18:123-133. [PMID: 15189237 DOI: 10.1111/j.0269-283x.2004.00486.x] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
The distribution and ecological preferences of tick (Acari: Ixodidae) parasites of grazing sheep in the region of Aragón (north-central Spain) were surveyed on flocks four times a year and mapped into a 5 x 5 km grid. Nine tick species were found. These were species of the Rhipicephalus sanguineus group (about 95% of them Rhipicephalus turanicus Pomerantsev, in 91% of cells of the grid), Rhipicephalus bursa Canestrini & Fanzago (79% of cells), Dermacentor marginatus (Sulzer) (58% of cells), Haemaphysalis punctata Canestrini & Fanzago (74% of cells) and Ixodes ricinus (Linnaeus) 14% of cells. Other species weakly represented in the surveys were Dermacentor reticulatus (Fabricius), Haemaphysalis sulcata Canestrini & Fanzago and Hyalomma m. marginatum Koch. Data on temperature, Normalized Difference Vegetation index (NDVI), topography, vegetation categories and plant productivity were used to build models of distribution and abundance of D. marginatus, H. punctata, R. bursa and R. turanicus. The occurrence models largely incorporated climatic variables and had good discrimination ability (P < 0.0001 for every modelled species, correct classification rate or sensitivity within 0.89 and 0.99), whereas the abundance models had a lower explanatory power. These models are relevant in the understanding of the variables composing the main distribution patterns, but they are unable adequately to predict the density. Abundance models produce good predictions in cells with low tick density, whereas poor correlation is observed in sites with high tick abundance. Several causes may be responsible for this low predictive power of the abundance models. Model output might be sensible to host density, to local farming practices, or to the size of the grid used to refer the results of the survey. In the latter case, small patches may support locally important populations of ticks, influencing largely the results of the survey. These patches of particular abiotic conditions, or supporting large host densities, may have been undetected at the resolution of the survey, thus obscuring the impact of the predictive variables.
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Affiliation(s)
- A Estrada-Peña
- Department of Parasitology, Veterinary Faculty, Zaragoza, Spain.
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27
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Wint GRW, Robinson TP, Bourn DM, Durr PA, Hay SI, Randolph SE, Rogers DJ. Mapping bovine tuberculosis in Great Britain using environmental data. Trends Microbiol 2002; 10:441-4. [PMID: 12377548 PMCID: PMC3173847 DOI: 10.1016/s0966-842x(02)02444-7] [Citation(s) in RCA: 42] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
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.
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Affiliation(s)
- G R William Wint
- Environmental Research Group Oxford, PO Box 346, OX1 3QE, Oxford, UK.
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28
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Kistemann T, Dangendorf F, Schweikart J. New perspectives on the use of Geographical Information Systems (GIS) in environmental health sciences. Int J Hyg Environ Health 2002; 205:169-81. [PMID: 12040915 DOI: 10.1078/1438-4639-00145] [Citation(s) in RCA: 81] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
At first glance, the domain of health is no typical area to applicate Geographical Information Systems (GIS). Nevertheless, the recent development clearly shows that also within the domains of environmental health, disease ecology and public health GIS have become an indispensable tool for processing, analysing and visualising spatial data. In the field of geographical epidemiology, GIS are used for drawing up disease maps and for ecological analysis. The striking advantages of GIS for the disease mapping process are the considerably simplified generation and variation of maps as well as a broader variety in terms of determining a real units. In the frame of ecological analysis, GIS can significantly assist with the assessment of the distribution of health-relevant environmental factors via interpolation and modelling. On the other hand, the GIS-supported methods for the detection of striking spatial patterns of disease distribution need to be much improved. An important topic in this respect is the integration of the time dimension. The increasing use of remote sensing as well as the integration into internet functionalities will stimulate the application of GIS in the field of Environmental Health Sciences (EHS). In future, the integration and analysis of health-relevant data in one single data system will open up many new research opportunities.
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Affiliation(s)
- Thomas Kistemann
- University of Bonn, Institute for Hygiene and Public Health, Sigmund-Freud-Str. 25, D-53105 Bonn.
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29
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Estrada-Peña A. A simulation model for environmental population densities, survival rates and prevalence of Boophilus decoloratus (Acari: ixodidae) using remotely sensed environmental information. Vet Parasitol 2002; 104:51-78. [PMID: 11779655 DOI: 10.1016/s0304-4017(01)00607-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
A simulation model for the African tick Boophilus decoloratus is presented. This model is based on the use of a dynamic life table that is driven by abiotic variables (temperature and vegetation status) remotely sensed (AVHRR sensor of the NOAA series of satellites) over time. The model incorporates temperature-dependent rates of egg production and development, climate-driven density-independent mortality rates, and density-dependent regulation of on-host stages. The model successfully describes both the seasonality and annual variation in the numbers of questing larvae and engorging females observed in eight sites throughout sub-Saharan Africa. Climate data from 1983 to 1999 in 10-day intervals are used as the basic input for modelling the dynamic patterns of activity at four different sites in Africa and to understand how abiotic factors can modulate the long-term life cycle of B. decoloratus.
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Affiliation(s)
- Agustin Estrada-Peña
- Veterinary Faculty, Department of Parasitology, Miguel Servet 177, 50013 Zaragoza, Spain.
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30
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Abstract
More than 30 years ago, human beings looked back from the Moon to see the magnificent spectacle of Earth-rise. The technology that put us into space has since been used to assess the damage we are doing to our natural environment and is now being harnessed to monitor and predict diseases through space and time. Satellite sensor data promise the development of early-warning systems for diseases such as malaria, which kills between 1 and 2 million people each year.
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Affiliation(s)
- David J Rogers
- TALA Research Group, Department of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UK.
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31
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Green RM, Hay SI. The potential of Pathfinder AVHRR data for providing surrogate climatic variables across Africa and Europe for epidemiological applications. REMOTE SENSING OF ENVIRONMENT 2002; 79:166-175. [PMID: 22581983 PMCID: PMC3350066 DOI: 10.1016/s0034-4257(01)00270-x] [Citation(s) in RCA: 18] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Surface climatic conditions are key determinants of arthropod vector distribution and abundance and consequently affect transmission rates of any diseases they may carry. Remotely sensed observations by satellite sensors are the only feasible means of obtaining regional and continental scale measurements of climate at regular intervals for real-time epidemiological applications such as disease early warning systems. The potential of Pathfinder AVHRR Land (PAL) data to provide surrogate variables for near-surface air temperature and vapour pressure deficit (VPD) over Africa and Europe were assessed in this context. For the years 1988-1990 and 1992, correlations were examined between meteorological ground measurements (monthly mean air temperature and VPD(grd)) and variables derived from Advanced Very High Resolution Radiometer (AVHRR) data (LST and VPD(sat)). The AVHRR indices were derived from both daily and composite PAL data so that their relative performance could be determined. Furthermore, the ground observations were divided into African and European subsets, so that the relative performance of the satellite data at tropical/sub-tropical and temperate latitudes could be assessed.Significant correlations were shown between air temperature and LST in all months. Temporal variability existed in the strength of correlations throughout any twelve-month period, with the pattern of variability consistent between years. The adjusted r(2) values increased when elevation and the Normalised Difference Vegetation Index (NDVI) were included, in addition to LST, as predictor variables of air temperature. Attempts to derive monthly estimates of atmospheric moisture availability resulted in an over-estimation of VPD(sat) compared to ground observations, VPD(grd). The use of daily PAL data to derive monthly mean climatic indices was shown to be more accurate than those obtained using monthly maximum values from 10-day composite data. A subset of the 1992 data was then used to build linear regression models for the direct retrieval of monthly mean air temperature from PAL data. The accuracy of retrieved estimates was greatest when NDVI was included with LST as predictor variables, with root mean square errors varying from 1.83°C to 3.18 °C with a mean of 2.38 °C over the twelve months.
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Affiliation(s)
- Robert M. Green
- Oxford Tick Research Group (OTRG), Department of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UK
| | - Simon I. Hay
- Oxford Tick Research Group (OTRG), Department of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UK
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32
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Huh OK, Malone JB. New tools: potential medical applications of data from new and old environmental satellites. Acta Trop 2001; 79:35-47. [PMID: 11378140 DOI: 10.1016/s0001-706x(01)00101-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
The last 40 years, beginning with the first TIROS (television infrared observational satellite) launched on 1 April 1960, has seen an explosion of earth environmental satellite systems and their capabilities. They can provide measurements in globe encircling arrays or small select areas, with increasing resolutions, and new capabilities. Concurrently there are expanding numbers of existing and emerging infectious diseases, many distributed according to areal patterns of physical conditions at the earth's surface. For these reasons, the medical and remote sensing communities can beneficially collaborate with the objective of making needed progress in public health activities by exploiting the advances of the national and international space programs. Major improvements in applicability of remotely sensed data are becoming possible with increases in the four kinds of resolution: spatial, temporal, radiometric and spectral, scheduled over the next few years. Much collaborative research will be necessary before data from these systems are fully exploited by the medical community.
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Affiliation(s)
- O K Huh
- Coastal Studies Institute and Pathobiological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA.
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