A relationship between acute respiratory illnesses and weather

Weekly data from 7 years (2004–2010) of primary-care counts of acute respiratory illnesses (ARIs) and local weather readings were used to adjust a multivariate time-series vector error correction model with covariates (VECMX). Weather variables were included through a partial least squares index tha...

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Bibliographic Details
Published in:Epidemiology and infection 2014-07, Vol.142 (7), p.1375-1383
Main Authors: COSTILLA-ESQUIVEL, A., CORONA-VILLAVICENCIO, F., VELASCO-CASTAÑÓN, J. G., MEDINA-DE LA GARZA, C. E., MARTÍNEZ-VILLARREAL, R. T., CORTES-HERNÁNDEZ, D. E., RAMÍREZ-LÓPEZ, L. E., GONZÁLEZ-FARÍAS, G.
Format: Article
Language:English
Subjects:
Adolescent
Adult
Age groups
Biological and medical sciences
Bronchitis
Child
Child, Preschool
Climate
Climate models
Epidemiology
Female
Fundamental and applied biological sciences. Psychology
Gender
Humans
Humidity
Illnesses
Infant
Influenza
Male
Meteorology
Microbiology
Middle Aged
Models, Statistical
Original Papers
Radiation
Rainfall
Relative humidity
Respiratory diseases
Respiratory syncytial virus
Respiratory Tract Infections - epidemiology
Seasonality and Weather
Temperature
Variable coefficients
Variables
Viruses
Weather
Young Adult
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Summary:Weekly data from 7 years (2004–2010) of primary-care counts of acute respiratory illnesses (ARIs) and local weather readings were used to adjust a multivariate time-series vector error correction model with covariates (VECMX). Weather variables were included through a partial least squares index that consisted of weekly minimum temperature (coefficient = − 0·26), weekly median of relative humidity (coefficient = 0·22) and weekly accumulated rainfall (coefficient = 0·5). The VECMX long-term test reported significance for trend (0·01, P = 0·00) and weather index (1·69, P = 0·00). Short-term relationship was influenced by seasonality. The model accounted for 76% of the variability in the series (adj. R 2 = 0·76), and the co-integration diagnostics confirmed its appropriateness. The procedure is easily reproducible by researchers in all climates, can be used to identify relevant weather fluctuations affecting the incidence of ARIs, and could help clarify the influence of contact rates on the spread of these diseases.
ISSN:0950-2688
1469-4409
DOI:10.1017/S0950268813001854