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Time series analysis of mumps and meteorological factors in Beijing, China

BACKGROUND: Over the past decades there have been outbreaks of mumps in many countries, even in populations that were vaccinated. Some studies suggest that the incidence of mumps is related to meteorological changes, but the results of these studies vary in different regions. To date there is no rep...

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Autores principales: Hao, Yu, Wang, Ran-ran, Han, Ling, Wang, Hong, Zhang, Xuan, Tang, Qiao-ling, Yan, Long, He, Juan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6525345/
https://www.ncbi.nlm.nih.gov/pubmed/31101079
http://dx.doi.org/10.1186/s12879-019-4011-6
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author Hao, Yu
Wang, Ran-ran
Han, Ling
Wang, Hong
Zhang, Xuan
Tang, Qiao-ling
Yan, Long
He, Juan
author_facet Hao, Yu
Wang, Ran-ran
Han, Ling
Wang, Hong
Zhang, Xuan
Tang, Qiao-ling
Yan, Long
He, Juan
author_sort Hao, Yu
collection PubMed
description BACKGROUND: Over the past decades there have been outbreaks of mumps in many countries, even in populations that were vaccinated. Some studies suggest that the incidence of mumps is related to meteorological changes, but the results of these studies vary in different regions. To date there is no reported study on correlations between mumps incidence and meteorological parameters in Beijing, China. METHODS: A time series analysis incorporating selected weather factors and the number of mumps cases from 1990 to 2012 in Beijing was performed. First, correlations between meteorological variables and the number of mumps cases were assessed. A seasonal autoregressive integrated moving average model with explanatory variables (SARIMAX) was then constructed to predict mumps cases. RESULTS: Mean temperature, rainfall, relative humidity, vapor pressure, and wind speed were significantly associated with mumps incidence. After constructing the SARIMAX model, mean temperature at lag 0 (β = 0.016, p < 0.05, 95% confidence interval 0.001 to 0.032) was positively associated with mumps incidence, while vapor pressure at lag 2 (β = ˗0.018, p < 0.05, 95% confidence interval ˗0.038 to ˗0.002) was negatively associated. SARIMAX (1, 1, 1) (0, 1, 1)(12) with temperature at lag 0 was the best predictive construct. CONCLUSIONS: The incidence of mumps in Beijing from 1990 to 2012 was significantly correlated with meteorological variables. Combining meteorological variables, a predictive SARIMAX model that could be used to preemptively estimate the incidence of mumps in Beijing was established. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12879-019-4011-6) contains supplementary material, which is available to authorized users.
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spelling pubmed-65253452019-05-24 Time series analysis of mumps and meteorological factors in Beijing, China Hao, Yu Wang, Ran-ran Han, Ling Wang, Hong Zhang, Xuan Tang, Qiao-ling Yan, Long He, Juan BMC Infect Dis Research Article BACKGROUND: Over the past decades there have been outbreaks of mumps in many countries, even in populations that were vaccinated. Some studies suggest that the incidence of mumps is related to meteorological changes, but the results of these studies vary in different regions. To date there is no reported study on correlations between mumps incidence and meteorological parameters in Beijing, China. METHODS: A time series analysis incorporating selected weather factors and the number of mumps cases from 1990 to 2012 in Beijing was performed. First, correlations between meteorological variables and the number of mumps cases were assessed. A seasonal autoregressive integrated moving average model with explanatory variables (SARIMAX) was then constructed to predict mumps cases. RESULTS: Mean temperature, rainfall, relative humidity, vapor pressure, and wind speed were significantly associated with mumps incidence. After constructing the SARIMAX model, mean temperature at lag 0 (β = 0.016, p < 0.05, 95% confidence interval 0.001 to 0.032) was positively associated with mumps incidence, while vapor pressure at lag 2 (β = ˗0.018, p < 0.05, 95% confidence interval ˗0.038 to ˗0.002) was negatively associated. SARIMAX (1, 1, 1) (0, 1, 1)(12) with temperature at lag 0 was the best predictive construct. CONCLUSIONS: The incidence of mumps in Beijing from 1990 to 2012 was significantly correlated with meteorological variables. Combining meteorological variables, a predictive SARIMAX model that could be used to preemptively estimate the incidence of mumps in Beijing was established. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12879-019-4011-6) contains supplementary material, which is available to authorized users. BioMed Central 2019-05-17 /pmc/articles/PMC6525345/ /pubmed/31101079 http://dx.doi.org/10.1186/s12879-019-4011-6 Text en © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Hao, Yu
Wang, Ran-ran
Han, Ling
Wang, Hong
Zhang, Xuan
Tang, Qiao-ling
Yan, Long
He, Juan
Time series analysis of mumps and meteorological factors in Beijing, China
title Time series analysis of mumps and meteorological factors in Beijing, China
title_full Time series analysis of mumps and meteorological factors in Beijing, China
title_fullStr Time series analysis of mumps and meteorological factors in Beijing, China
title_full_unstemmed Time series analysis of mumps and meteorological factors in Beijing, China
title_short Time series analysis of mumps and meteorological factors in Beijing, China
title_sort time series analysis of mumps and meteorological factors in beijing, china
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6525345/
https://www.ncbi.nlm.nih.gov/pubmed/31101079
http://dx.doi.org/10.1186/s12879-019-4011-6
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