TY - JOUR
KW - Public Health, Environmental and Occupational Health
KW - Parasitology
KW - Infectious Diseases
KW - General Medicine
AU - Diggle PJ
AU - Amoah B
AU - Fronterrè C
AU - Giorgi E
AU - Johnson O
AB - <jats:title>Abstract</jats:title>
               <jats:p>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.</jats:p>
BT - Transactions of The Royal Society of Tropical Medicine and Hygiene
DO - 10.1093/trstmh/trab020
LA - eng
N2 - <jats:title>Abstract</jats:title>
               <jats:p>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.</jats:p>
PB - Oxford University Press (OUP)
PY - 2021
T2 - Transactions of The Royal Society of Tropical Medicine and Hygiene
TI - Rethinking neglected tropical disease prevalence survey design and analysis: a geospatial paradigm
UR - https://academic.oup.com/trstmh/advance-article-pdf/doi/10.1093/trstmh/trab020/36264755/trab020.pdf
SN - 0035-9203, 1878-3503
ER -