ReviewPLoS neglected tropical diseases2015
Earth Observation, Spatial Data Quality, and Neglected Tropical Diseases.
Review in PLoS neglected tropical diseases, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Modelling approaches for predicting the distribution of skin NTDs: A systematic review.PLoS neglected tropical diseases · 2026Pooled it
- Mapping Soil Transmitted Helminths and Schistosomiasis under Uncertainty: A Systematic Review and Critical Appraisal of Evidence.PLoS neglected tropical diseases · 2016Pooled it
- Community-Led Data Collection: Enhancing Local-Level Scabies Surveillance in Remote Aboriginal Communities in Australia.Tropical medicine and infectious disease · 2023Article
- Spatial scales in human movement between reservoirs of infection.Journal of theoretical biology · 2021Article
- Addressing the global snakebite crisis with geo-spatial analyses - Recent advances and future direction.Toxicon: X · 2021Article
- Achieving global malaria eradication in changing landscapes.Malaria journal · 2021Review
- Semi-Supervised Text Classification Framework: An Overview of Dengue Landscape Factors and Satellite Earth Observation.International journal of environmental research and public health · 2020Review
- Availability, access, analysis and dissemination of small-area data.International journal of epidemiology · 2020Article
- Using Earth observation images to inform risk assessment and mapping of climate change-related infectious diseases.Canada communicable disease report = Releve des maladies transmissibles au Canada · 2019Article
- Modeling Schistosoma japonicum Infection under Pure Specification Bias: Impact of Environmental Drivers of Infection.International journal of environmental research and public health · 2019Article
- Modelling local areas of exposure to Schistosoma japonicum in a limited survey data environment.Parasites & vectors · 2018Article
- Evaluating meteorological data from weather stations, and from satellites and global models for a multi-site epidemiological study.Environmental research · 2018Article
- Improving spatial prediction of Schistosoma haematobium prevalence in southern Ghana through new remote sensors and local water access profiles.PLoS neglected tropical diseases · 2018Article
- From global action against malaria to local issues: state of the art and perspectives of web platforms dealing with malaria information.Malaria journal · 2018Article
- Environmental risk factors and changing spatial patterns of human seropositivity for Echinococcus spp. in Xiji County, Ningxia Hui Autonomous Region, China.Parasites & vectors · 2018Article
- Spatiotemporal patterns and environmental drivers of human echinococcoses over a twenty-year period in Ningxia Hui Autonomous Region, China.Parasites & vectors · 2018Article
- A Topology Control Strategy with Reliability Assurance for Satellite Cluster Networks in Earth Observation.Sensors (Basel, Switzerland) · 2017Article
- Article
- Malaria - how this parasitic infection aids and abets EBV-associated Burkitt lymphomagenesis.Current opinion in virology · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.