Impact of meteorological factors on the incidence of bacillary dysentery in Beijing, China: A time series analysis (1970-2012).
Influence of meteorological variables on the transmission of bacillary dysentery (BD) is under investigated topic and effective forecasting models as public health tool are lacking. This paper aimed to quantify the relationship between meteorological variables and BD cases in Beijing and to establis...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2017-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC5552134?pdf=render |
| _version_ | 1819156053517926400 |
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| author | Long Yan Hong Wang Xuan Zhang Ming-Yue Li Juan He |
| author_facet | Long Yan Hong Wang Xuan Zhang Ming-Yue Li Juan He |
| author_sort | Long Yan |
| collection | DOAJ |
| description | Influence of meteorological variables on the transmission of bacillary dysentery (BD) is under investigated topic and effective forecasting models as public health tool are lacking. This paper aimed to quantify the relationship between meteorological variables and BD cases in Beijing and to establish an effective forecasting model.A time series analysis was conducted in the Beijing area based upon monthly data on weather variables (i.e. temperature, rainfall, relative humidity, vapor pressure, and wind speed) and on the number of BD cases during the period 1970-2012. Autoregressive integrated moving average models with explanatory variables (ARIMAX) were built based on the data from 1970 to 2004. Prediction of monthly BD cases from 2005 to 2012 was made using the established models. The prediction accuracy was evaluated by the mean square error (MSE).Firstly, temperature with 2-month and 7-month lags and rainfall with 12-month lag were found positively correlated with the number of BD cases in Beijing. Secondly, ARIMAX model with covariates of temperature with 7-month lag (β = 0.021, 95% confidence interval(CI): 0.004-0.038) and rainfall with 12-month lag (β = 0.023, 95% CI: 0.009-0.037) displayed the highest prediction accuracy.The ARIMAX model developed in this study showed an accurate goodness of fit and precise prediction accuracy in the short term, which would be beneficial for government departments to take early public health measures to prevent and control possible BD popularity. |
| first_indexed | 2024-12-22T15:46:45Z |
| format | Article |
| id | doaj.art-c631c4ba514043dd988b77b17b04be1b |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-22T15:46:45Z |
| publishDate | 2017-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-c631c4ba514043dd988b77b17b04be1b2022-12-21T18:21:01ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01128e018293710.1371/journal.pone.0182937Impact of meteorological factors on the incidence of bacillary dysentery in Beijing, China: A time series analysis (1970-2012).Long YanHong WangXuan ZhangMing-Yue LiJuan HeInfluence of meteorological variables on the transmission of bacillary dysentery (BD) is under investigated topic and effective forecasting models as public health tool are lacking. This paper aimed to quantify the relationship between meteorological variables and BD cases in Beijing and to establish an effective forecasting model.A time series analysis was conducted in the Beijing area based upon monthly data on weather variables (i.e. temperature, rainfall, relative humidity, vapor pressure, and wind speed) and on the number of BD cases during the period 1970-2012. Autoregressive integrated moving average models with explanatory variables (ARIMAX) were built based on the data from 1970 to 2004. Prediction of monthly BD cases from 2005 to 2012 was made using the established models. The prediction accuracy was evaluated by the mean square error (MSE).Firstly, temperature with 2-month and 7-month lags and rainfall with 12-month lag were found positively correlated with the number of BD cases in Beijing. Secondly, ARIMAX model with covariates of temperature with 7-month lag (β = 0.021, 95% confidence interval(CI): 0.004-0.038) and rainfall with 12-month lag (β = 0.023, 95% CI: 0.009-0.037) displayed the highest prediction accuracy.The ARIMAX model developed in this study showed an accurate goodness of fit and precise prediction accuracy in the short term, which would be beneficial for government departments to take early public health measures to prevent and control possible BD popularity.http://europepmc.org/articles/PMC5552134?pdf=render |
| spellingShingle | Long Yan Hong Wang Xuan Zhang Ming-Yue Li Juan He Impact of meteorological factors on the incidence of bacillary dysentery in Beijing, China: A time series analysis (1970-2012). PLoS ONE |
| title | Impact of meteorological factors on the incidence of bacillary dysentery in Beijing, China: A time series analysis (1970-2012). |
| title_full | Impact of meteorological factors on the incidence of bacillary dysentery in Beijing, China: A time series analysis (1970-2012). |
| title_fullStr | Impact of meteorological factors on the incidence of bacillary dysentery in Beijing, China: A time series analysis (1970-2012). |
| title_full_unstemmed | Impact of meteorological factors on the incidence of bacillary dysentery in Beijing, China: A time series analysis (1970-2012). |
| title_short | Impact of meteorological factors on the incidence of bacillary dysentery in Beijing, China: A time series analysis (1970-2012). |
| title_sort | impact of meteorological factors on the incidence of bacillary dysentery in beijing china a time series analysis 1970 2012 |
| url | http://europepmc.org/articles/PMC5552134?pdf=render |
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