Pedro Gullón1, Carmen Varela2, Elena Vanessa Martínez2, Diana Gómez-Barroso2. 1. National School of Public Health, Carlos III Institute of Health. Madrid, Spain; Social and Cardiovascular Epidemiology Research Group, School of Medicine, University of Alcalá, Alcalá de Henares, Madrid, Spain. Electronic address: pgullon@isciii.es. 2. National Centre for Epidemiology, Carlos III Institute of Health, Madrid, Spain; CIBER en Epidemiología y Salud Pública (CIBERESP), Spain.
Abstract
BACKGROUND: There is growing concern of how climate change could affect public health, due to the increase number of extreme climate events. Hence, the study of the role that climate events play on the distribution of waterborne diseases, like Hepatitis A, could be key for developing new prevention approaches. OBJECTIVE: To investigate the association between climate factors and Hepatitis A in Spain between 2010 and 2014. METHODS: Weekly Hepatitis A cases between 2010 and 2014 were obtained from the Spanish Epidemiology Surveillance Network. Climate variables (weekly cumulative rainfall, rainy days, storm days and snow days) were obtained from National Climatic Data Center (NOAA satellite and information Service of USA). Each municipality was assigned to the nearest weather station (N=73). A Mixed-Effects Poisson regression was performed to estimate Incidence Rate Ratios (IRR), including a time lag of 2, 3 and 4weeks (most probable incubation period for Hepatitis A). RESULTS: Rainfall higher than 90th percentile (extreme precipitation) was associated with increased number of Hepatitis A cases 2weeks (IRR=1.24 CI 95%=1.09-1.40) and 4weeks after the event (IRR=1.15 CI 95%=1.01-1.30). An extra rainy day increased the risk of Hepatitis A two weeks after (IRR=1.03 CI 95%=1.01-1.05). We found higher risk of Hepatitis A two weeks after each extra storm day (IRR=1.06 CI 95%=1.00-1.12), and lower risk with 3 and 4weeks' lag (IRR=0.93 CI 95%=0.88-0.99 for lag3; IRR=0.94 CI 95%=0.88-0.99 for lag 4). CONCLUSIONS: There is an increased risk of Hepatitis A 2weeks after water-related climate events. Including meteorological information in surveillance systems might improve to develop early prevention strategies for waterborne diseases.
BACKGROUND: There is growing concern of how climate change could affect public health, due to the increase number of extreme climate events. Hence, the study of the role that climate events play on the distribution of waterborne diseases, like Hepatitis A, could be key for developing new prevention approaches. OBJECTIVE: To investigate the association between climate factors and Hepatitis A in Spain between 2010 and 2014. METHODS: Weekly Hepatitis A cases between 2010 and 2014 were obtained from the Spanish Epidemiology Surveillance Network. Climate variables (weekly cumulative rainfall, rainy days, storm days and snow days) were obtained from National Climatic Data Center (NOAA satellite and information Service of USA). Each municipality was assigned to the nearest weather station (N=73). A Mixed-Effects Poisson regression was performed to estimate Incidence Rate Ratios (IRR), including a time lag of 2, 3 and 4weeks (most probable incubation period for Hepatitis A). RESULTS: Rainfall higher than 90th percentile (extreme precipitation) was associated with increased number of Hepatitis A cases 2weeks (IRR=1.24 CI 95%=1.09-1.40) and 4weeks after the event (IRR=1.15 CI 95%=1.01-1.30). An extra rainy day increased the risk of Hepatitis A two weeks after (IRR=1.03 CI 95%=1.01-1.05). We found higher risk of Hepatitis A two weeks after each extra storm day (IRR=1.06 CI 95%=1.00-1.12), and lower risk with 3 and 4weeks' lag (IRR=0.93 CI 95%=0.88-0.99 for lag3; IRR=0.94 CI 95%=0.88-0.99 for lag 4). CONCLUSIONS: There is an increased risk of Hepatitis A 2weeks after water-related climate events. Including meteorological information in surveillance systems might improve to develop early prevention strategies for waterborne diseases.
Authors: Joanna A Ruszkiewicz; Alexey A Tinkov; Anatoly V Skalny; Vasileios Siokas; Efthimios Dardiotis; Aristidis Tsatsakis; Aaron B Bowman; João B T da Rocha; Michael Aschner Journal: Environ Res Date: 2019-08-08 Impact factor: 6.498
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