Modelling local areas of exposure to Schistosoma japonicum in a limited survey data environment

DOI

Spatial modelling studies of schistosomiasis (SCH) are now commonplace. Covariate values are commonly extracted at survey locations, where infection does not always take place, resulting in an unknown positional exposure mismatch. The present research aims to: (i) describe the nature of the positional exposure mismatch in modelling SCH helminth infections; (ii) delineate exposure areas to correct for such positional mismatch; and (iii) validate exposure areas using human positive cases

Date: 2018-05-31

The recording of all human case locations, including also negative cases was not possible due to ta lack of manpower and material resources, such as the availability of only one GPS device in the field.

Identifier
DOI https://doi.org/10.17026/dans-x57-8g5r
Metadata Access https://lifesciences.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/dans-x57-8g5r
Provenance
Creator A.L. Araujo Navas
Publisher DANS Data Station Life Sciences
Contributor M Th Koelen; L.R. Leonardo (University of The Philippines Manila); University of the Philippines Manila
Publication Year 2018
Rights DANS Licence; info:eu-repo/semantics/restrictedAccess; https://doi.org/10.17026/fp39-0x58
OpenAccess false
Contact M Th Koelen (Faculty of Geo-Information Science and Earth Observation)
Representation
Resource Type Dataset
Format text/csv; application/gml+xml; application/zip; application/pdf; image/png
Size 119747; 44017; 19699; 1294; 736; 2414467; 4250704; 124887; 24311; 7433; 3553168; 374
Version 1.0
Discipline Life Sciences; Medicine