Earth Observation, Spatial Data Quality, and Neglected Tropical Diseases

Hamm, Nicholas A.S., Soares Magalhaes, Ricardo J. and Clements, Archie C.A. (2015) Earth Observation, Spatial Data Quality, and Neglected Tropical Diseases. PLoS Neglected Tropical Diseases, 9 12: . doi:10.1371/journal.pntd.0004164

Author Hamm, Nicholas A.S.
Soares Magalhaes, Ricardo J.
Clements, Archie C.A.
Title Earth Observation, Spatial Data Quality, and Neglected Tropical Diseases
Journal name PLoS Neglected Tropical Diseases   Check publisher's open access policy
ISSN 1935-2735
Publication date 2015-12-17
Year available 2015
Sub-type Critical review of research, literature review, critical commentary
DOI 10.1371/journal.pntd.0004164
Open Access Status DOI
Volume 9
Issue 12
Total pages 24
Place of publication San Francisco, CA, United States
Publisher Public Library of Science
Collection year 2016
Language eng
Abstract Earth observation (EO) is the use of remote sensing and in situ observations to gather data on the environment. It finds increasing application in the study of environmentally modulated neglected tropical diseases (NTDs). Obtaining and assuring the quality of the relevant spatially and temporally indexed EO data remain challenges. Our objective was to review the Earth observation products currently used in studies of NTD epidemiology and to discuss fundamental issues relating to spatial data quality (SDQ), which limit the utilization of EO and pose challenges for its more effective use. We searched Web of Science and PubMed for studies related to EO and echinococossis, leptospirosis, schistosomiasis, and soil-transmitted helminth infections. Relevant literature was also identified from the bibliographies of those papers. We found that extensive use is made of EO products in the study of NTD epidemiology; however, the quality of these products is usually given little explicit attention. We review key issues in SDQ concerning spatial and temporal scale, uncertainty, and the documentation and use of quality information. We give examples of how these issues may interact with uncertainty in NTD data to affect the output of an epidemiological analysis. We conclude that researchers should give careful attention to SDQ when designing NTD spatial-epidemiological studies. This should be used to inform uncertainty analysis in the epidemiological study. SDQ should be documented and made available to other researchers.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Critical review of research, literature review, critical commentary
Collections: Official 2016 Collection
School of Public Health Publications
School of Veterinary Science Publications
Child Health Research Centre Publications
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