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A simplistic approach to detect health anomalies at a regional level using shrimp production data
Author(s) -
Muniesa Ana,
CabanillasRamos Julio,
RuizZarzuela Imanol,
MagallónBarajas Francisco J.,
Blas Ignacio
Publication year - 2018
Publication title -
reviews in aquaculture
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.998
H-Index - 47
eISSN - 1753-5131
pISSN - 1753-5123
DOI - 10.1111/raq.12220
Subject(s) - shrimp , stocking , production (economics) , statistics , yield (engineering) , outbreak , environmental science , regression analysis , biology , geography , fishery , mathematics , economics , macroeconomics , materials science , virology , metallurgy
The global production and yield of shrimp ponds depend on multiple factors, and an unexpected variation in production parameters could be an indicator of pathological events such as white spot disease (WSD) outbreaks in a syndromic surveillance system. Using the production data from 7139 production cycles at farm level collected at two Mexican states (Sonora and Sinaloa) from 2004 to 2011, an ecological survey (also called correlational study) has been carried out summarizing data for year and oceanic basin. The production results had been analysed looking for significant association ( P < 0.050) using correlation and linear regression. The average yield at harvest was not correlated with the frequency of WSD outbreaks. However, four strong and significant relationships were observed as follows: the total stocked area depends on previous total stocked area, the weight at harvest depends on the length of cycle, the yield at harvest depends on the harvest density and the stocking density depends on previous average stocking density. Within these associations, some observed results differed significantly from expected values, and these may be related to changes in production management or undetected pathological events. The analysis of significant deviations from predictions of regression analysis could provide additional evidence of changes in the production system, and in some cases could be an early indicator of subclinical and/or emergent diseases.