Literature DB >> 10827111

Remote sensing and human health: new sensors and new opportunities.

L R Beck1, B M Lobitz, B L Wood.   

Abstract

Since the launch of Landsat-1 28 years ago, remotely sensed data have been used to map features on the earth's surface. An increasing number of health studies have used remotely sensed data for monitoring, surveillance, or risk mapping, particularly of vector-borne diseases. Nearly all studies used data from Landsat, the French Système Pour l'Observation de la Terre, and the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer. New sensor systems are in orbit, or soon to be launched, whose data may prove useful for characterizing and monitoring the spatial and temporal patterns of infectious diseases. Increased computing power and spatial modeling capabilities of geographic information systems could extend the use of remote sensing beyond the research community into operational disease surveillance and control. This article illustrates how remotely sensed data have been used in health applications and assesses earth-observing satellites that could detect and map environmental variables related to the distribution of vector-borne and other diseases.

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Mesh:

Year:  2000        PMID: 10827111      PMCID: PMC2640871          DOI: 10.3201/eid0603.000301

Source DB:  PubMed          Journal:  Emerg Infect Dis        ISSN: 1080-6040            Impact factor:   6.883


  21 in total

1.  Mapping malaria risk in Africa: What can satellite data contribute?

Authors:  M C Thomson; S J Connor; P Milligan; S P Flasse
Journal:  Parasitol Today       Date:  1997-08

2.  Application of polar-orbiting, meteorological satellite data to detect flooding of Rift Valley Fever virus vector mosquito habitats in Kenya.

Authors:  K J Linthicum; C L Bailey; C J Tucker; K D Mitchell; T M Logan; F G Davies; C W Kamau; P C Thande; J N Wagateh
Journal:  Med Vet Entomol       Date:  1990-10       Impact factor: 2.739

3.  Assessment of a remote sensing-based model for predicting malaria transmission risk in villages of Chiapas, Mexico.

Authors:  L R Beck; M H Rodriguez; S W Dister; A D Rodriguez; R K Washino; D R Roberts; M A Spanner
Journal:  Am J Trop Med Hyg       Date:  1997-01       Impact factor: 2.345

4.  Climate and infectious disease: use of remote sensing for detection of Vibrio cholerae by indirect measurement.

Authors:  B Lobitz; L Beck; A Huq; B Wood; G Fuchs; A S Faruque; R Colwell
Journal:  Proc Natl Acad Sci U S A       Date:  2000-02-15       Impact factor: 11.205

5.  Remote sensing of tropical wetlands for malaria control in Chiapas, Mexico.

Authors:  K O Pope; E Rejmankova; H M Savage; J I Arredondo-Jimenez; M H Rodriguez; D R Roberts
Journal:  Ecol Appl       Date:  1994-02       Impact factor: 4.657

6.  Bancroftian filariasis distribution and diurnal temperature differences in the southern Nile delta.

Authors:  D F Thompson; J B Malone; M Harb; R Faris; O K Huh; A A Buck; B L Cline
Journal:  Emerg Infect Dis       Date:  1996 Jul-Sep       Impact factor: 6.883

7.  Use of weather data and remote sensing to predict the geographic and seasonal distribution of Phlebotomus papatasi in southwest Asia.

Authors:  E R Cross; W W Newcomb; C J Tucker
Journal:  Am J Trop Med Hyg       Date:  1996-05       Impact factor: 2.345

8.  Temperature data from satellite imagery and the distribution of schistosomiasis in Egypt.

Authors:  J B Malone; O K Huh; D P Fehler; P A Wilson; D E Wilensky; R A Holmes; A I Elmagdoub
Journal:  Am J Trop Med Hyg       Date:  1994-06       Impact factor: 2.345

9.  Remote sensing as a landscape epidemiologic tool to identify villages at high risk for malaria transmission.

Authors:  L R Beck; M H Rodriguez; S W Dister; A D Rodriguez; E Rejmankova; A Ulloa; R A Meza; D R Roberts; J F Paris; M A Spanner
Journal:  Am J Trop Med Hyg       Date:  1994-09       Impact factor: 2.345

10.  Predictions of malaria vector distribution in Belize based on multispectral satellite data.

Authors:  D R Roberts; J F Paris; S Manguin; R E Harbach; R Woodruff; E Rejmankova; J Polanco; B Wullschleger; L J Legters
Journal:  Am J Trop Med Hyg       Date:  1996-03       Impact factor: 2.345

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  62 in total

1.  The physiologic climate of Nigeria.

Authors:  Oyenike Mary Eludoyin; Ibidun Onikepo Adelekan
Journal:  Int J Biometeorol       Date:  2012-05-20       Impact factor: 3.787

2.  Environmental risk factors for the incidence of American cutaneous leishmaniasis in a sub-Andean zone of Colombia (Chaparral, Tolima).

Authors:  Carlos Valderrama-Ardila; Neal Alexander; Cristina Ferro; Horacio Cadena; Dairo Marín; Theodore R Holford; Leonard E Munstermann; Clara B Ocampo
Journal:  Am J Trop Med Hyg       Date:  2010-02       Impact factor: 2.345

3.  Using Earth observation images to inform risk assessment and mapping of climate change-related infectious diseases.

Authors:  S O Kotchi; C Bouchard; A Ludwig; E E Rees; S Brazeau
Journal:  Can Commun Dis Rep       Date:  2019-05-02

4.  Modeling the spatially varying risk factors of dengue fever in Jhapa district, Nepal, using the semi-parametric geographically weighted regression model.

Authors:  Bipin Kumar Acharya; ChunXiang Cao; Tobia Lakes; Wei Chen; Shahid Naeem; Shreejana Pandit
Journal:  Int J Biometeorol       Date:  2018-09-04       Impact factor: 3.787

5.  Spatial risk assessments based on vector-borne disease epidemiologic data: importance of scale for West Nile virus disease in Colorado.

Authors:  Anna M Winters; Rebecca J Eisen; Mark J Delorey; Marc Fischer; Roger S Nasci; Emily Zielinski-Gutierrez; Chester G Moore; W John Pape; Lars Eisen
Journal:  Am J Trop Med Hyg       Date:  2010-05       Impact factor: 2.345

Review 6.  A Review and Framework for Categorizing Current Research and Development in Health Related Geographical Information Systems (GIS) Studies.

Authors:  A K Lyseen; C Nøhr; E M Sørensen; O Gudes; E M Geraghty; N T Shaw; C Bivona-Tellez
Journal:  Yearb Med Inform       Date:  2014-08-15

7.  Upscale or downscale: applications of fine scale remotely sensed data to Chagas disease in Argentina and schistosomiasis in Kenya.

Authors:  Uriel Kitron; Julie A Clennon; M Carla Cecere; Ricardo E Gürtler; Charles H King; Gonzalo Vazquez-Prokopec
Journal:  Geospat Health       Date:  2006-11       Impact factor: 1.212

8.  Satellite derived forest phenology and its relation with nephropathia epidemica in Belgium.

Authors:  José Miguel Barrios; Willem W Verstraeten; Piet Maes; Jan Clement; Jean-Marie Aerts; Sara Amirpour Haredasht; Julie Wambacq; Katrien Lagrou; Geneviève Ducoffre; Marc Van Ranst; Daniel Berckmans; Pol Coppin
Journal:  Int J Environ Res Public Health       Date:  2010-06-09       Impact factor: 3.390

9.  A geographical sampling method for surveys of mosquito larvae in an urban area using high-resolution satellite imagery.

Authors:  Adriana Troyo; Douglas O Fuller; Olger Calderón-Arguedas; John C Beier
Journal:  J Vector Ecol       Date:  2008-06       Impact factor: 1.671

10.  Spatial epidemiology in zoonotic parasitic diseases: insights gained at the 1st International Symposium on Geospatial Health in Lijiang, China, 2007.

Authors:  Xiao-Nong Zhou; Shan Lv; Guo-Jing Yang; Thomas K Kristensen; N Robert Bergquist; Jürg Utzinger; John B Malone
Journal:  Parasit Vectors       Date:  2009-02-04       Impact factor: 3.876

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