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Rethinking neglected tropical disease prevalence survey design and analysis: a geospatial paradigm
- Source :
- Transactions of the Royal Society of Tropical Medicine and Hygiene, Diggle, P J, Amoah, B, Fronterrè, C, Giorgi, E & Johnson, O 2021, ' Rethinking neglected tropical disease prevalence survey design and analysis : a geospatial paradigm ', Transactions of the Royal Society of Tropical Medicine and Hygiene, vol. 115, no. 3, pp. 208-210 . https://doi.org/10.1093/trstmh/trab020
- Publication Year :
- 2021
- Publisher :
- Oxford University Press, 2021.
-
Abstract
- Current methods for the design and analysis of neglected tropical disease prevalence surveys largely rely on classical survey sampling ideas that treat prevalence data from different locations as an independent random sample from the probability distribution induced by a random sampling design. We set out an alternative, explicitly geospatial paradigm that can deliver much more precise estimates of the geospatial variation in prevalence over a country or region of interest. We describe the advantages of this approach under three headings: Streamlining, whereby more precise results can be obtained with smaller sample sizes; integrating, whereby a joint analysis of data from two or more diseases can bring further gains in precision; and adapting, whereby the choice of future sampling location is informed by past data. © 2021 The Author(s). Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene.
- Subjects :
- Geospatial analysis
Computer science
030231 tropical medicine
Survey sampling
Variation (game tree)
elimination surveys
computer.software_genre
01 natural sciences
1117 Public Health and Health Services
010104 statistics & probability
03 medical and health sciences
Predictive inference
0302 clinical medicine
1108 Medical Microbiology
Surveys and Questionnaires
Tropical Medicine
Prevalence
Humans
AcademicSubjects/MED00860
0101 mathematics
Set (psychology)
Public, Environmental & Occupational Health
Science & Technology
prevalence mapping
Public Health, Environmental and Occupational Health
predictive inference
Sampling (statistics)
Neglected Diseases
geospatial methods
General Medicine
Data science
Infectious Diseases
AcademicSubjects/MED00290
Sample size determination
Commentary
Probability distribution
Parasitology
computer
Life Sciences & Biomedicine
0605 Microbiology
Subjects
Details
- Language :
- English
- ISSN :
- 18783503 and 00359203
- Volume :
- 115
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- Transactions of the Royal Society of Tropical Medicine and Hygiene
- Accession number :
- edsair.doi.dedup.....e7c461c2d2d147b36a891c226b3aa82c
- Full Text :
- https://doi.org/10.1093/trstmh/trab020