TY - JOUR
T1 - Time series analysis of mumps and meteorological factors in Beijing, China
AU - Hao, Yu
AU - Wang, Ran Ran
AU - Han, Ling
AU - Wang, Hong
AU - ZHANG, Xuan
AU - Tang, Qiao Ling
AU - Yan, Long
AU - He, Juan
N1 - Funding Information:
The study was supported by the National Natural Science Foundation of China (funding numbers 81574098 and 81503678). The funding bodies played no role in the design of the study, data collection, data analysis, interpretation of data, and writing of the manuscript.
PY - 2019/5/17
Y1 - 2019/5/17
N2 - 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 = Ë-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.
AB - 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 = Ë-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.
KW - Beijing
KW - Meteorological factors
KW - Mumps
KW - Time series
UR - http://www.scopus.com/inward/record.url?scp=85065912998&partnerID=8YFLogxK
U2 - 10.1186/s12879-019-4011-6
DO - 10.1186/s12879-019-4011-6
M3 - Journal article
C2 - 31101079
AN - SCOPUS:85065912998
SN - 1471-2334
VL - 19
JO - BMC Infectious Diseases
JF - BMC Infectious Diseases
IS - 1
M1 - 435
ER -