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Developing a Time Series Predictive Model for Dengue in Zhongshan, China Based on Weather and Guangzhou Dengue Surveillance Data.

Zhang Y, Wang T, Liu K, Xia Y, Lu Y, Jing Q, Yang Z, Hu W, Lu J - PLoS Negl Trop Dis (2016)

Bottom Line: Models established during k-fold cross-validation also had considerable AUC (average 0.938-0.967).The sensitivity and specificity obtained from k-fold cross-validation was 78.83% and 92.48% respectively, with a forecasting threshold of 3 cases per week; 91.17% and 91.39%, with a threshold of 2 cases; and 85.16% and 87.25% with a threshold of 1 case.The out-of-sample prediction for the epidemics in 2014 also showed satisfactory performance.

View Article: PubMed Central - PubMed

Affiliation: Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong Province, P. R. China.

ABSTRACT

Background: Dengue is a re-emerging infectious disease of humans, rapidly growing from endemic areas to dengue-free regions due to favorable conditions. In recent decades, Guangzhou has again suffered from several big outbreaks of dengue; as have its neighboring cities. This study aims to examine the impact of dengue epidemics in Guangzhou, China, and to develop a predictive model for Zhongshan based on local weather conditions and Guangzhou dengue surveillance information.

Methods: We obtained weekly dengue case data from 1st January, 2005 to 31st December, 2014 for Guangzhou and Zhongshan city from the Chinese National Disease Surveillance Reporting System. Meteorological data was collected from the Zhongshan Weather Bureau and demographic data was collected from the Zhongshan Statistical Bureau. A negative binomial regression model with a log link function was used to analyze the relationship between weekly dengue cases in Guangzhou and Zhongshan, controlling for meteorological factors. Cross-correlation functions were applied to identify the time lags of the effect of each weather factor on weekly dengue cases. Models were validated using receiver operating characteristic (ROC) curves and k-fold cross-validation.

Results: Our results showed that weekly dengue cases in Zhongshan were significantly associated with dengue cases in Guangzhou after the treatment of a 5 weeks prior moving average (Relative Risk (RR) = 2.016, 95% Confidence Interval (CI): 1.845-2.203), controlling for weather factors including minimum temperature, relative humidity, and rainfall. ROC curve analysis indicated our forecasting model performed well at different prediction thresholds, with 0.969 area under the receiver operating characteristic curve (AUC) for a threshold of 3 cases per week, 0.957 AUC for a threshold of 2 cases per week, and 0.938 AUC for a threshold of 1 case per week. Models established during k-fold cross-validation also had considerable AUC (average 0.938-0.967). The sensitivity and specificity obtained from k-fold cross-validation was 78.83% and 92.48% respectively, with a forecasting threshold of 3 cases per week; 91.17% and 91.39%, with a threshold of 2 cases; and 85.16% and 87.25% with a threshold of 1 case. The out-of-sample prediction for the epidemics in 2014 also showed satisfactory performance.

Conclusion: Our study findings suggest that the occurrence of dengue outbreaks in Guangzhou could impact dengue outbreaks in Zhongshan under suitable weather conditions. Future studies should focus on developing integrated early warning systems for dengue transmission including local weather and human movement.

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Related in: MedlinePlus

Locations of Guangzhou, Zhongshan and the neighboring cities.Nowadays, Guangzhou is considered a prominent commercial and business center in the PRD region. To maintain its role, major infrastructural projects were undertaken, including the construction of ring roads, highways, and railway tracks. This in turn provided easily accessible transportation between Guangzhou and other cities for the public. As Zhongshan is 86 kilometers from Guangzhou (a distance interconnected by Guangzhou-Zhuhai local train and several highways), workers and businessmen frequently travel between these two cities, and some go to work in Guangzhou during the day and return home to Zhongshan after work.
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pntd.0004473.g001: Locations of Guangzhou, Zhongshan and the neighboring cities.Nowadays, Guangzhou is considered a prominent commercial and business center in the PRD region. To maintain its role, major infrastructural projects were undertaken, including the construction of ring roads, highways, and railway tracks. This in turn provided easily accessible transportation between Guangzhou and other cities for the public. As Zhongshan is 86 kilometers from Guangzhou (a distance interconnected by Guangzhou-Zhuhai local train and several highways), workers and businessmen frequently travel between these two cities, and some go to work in Guangzhou during the day and return home to Zhongshan after work.

Mentions: Guangzhou, located at the northern tip of the Pearl River Delta (PRD), is the provincial capital of Guangdong Province (Fig 1). Because of its location, Guangzhou possessed exceptional conditions as a port with a nickname “southern gate of China” [27]. Zhongshan, a medium-size city in Guangdong Province, adjacent to Guangzhou, is located along the west side of the mouth of the Pearl River, directly opposite Shenzhen and Hong Kong, south of Guangzhou and Foshan, east of Jiangmen, and north of Zhuhai and Macau (Fig 1), occupying an area of 1,800.14 square kilometers with 3.12 million permanent residents (Census reference 2010). It has a typical subtropical monsoon climate with hot and humid summer, mild to cool winter, monthly average temperature range from 13.8°C to 28.6°C, and annual rainfall of about 1,750 mm.


Developing a Time Series Predictive Model for Dengue in Zhongshan, China Based on Weather and Guangzhou Dengue Surveillance Data.

Zhang Y, Wang T, Liu K, Xia Y, Lu Y, Jing Q, Yang Z, Hu W, Lu J - PLoS Negl Trop Dis (2016)

Locations of Guangzhou, Zhongshan and the neighboring cities.Nowadays, Guangzhou is considered a prominent commercial and business center in the PRD region. To maintain its role, major infrastructural projects were undertaken, including the construction of ring roads, highways, and railway tracks. This in turn provided easily accessible transportation between Guangzhou and other cities for the public. As Zhongshan is 86 kilometers from Guangzhou (a distance interconnected by Guangzhou-Zhuhai local train and several highways), workers and businessmen frequently travel between these two cities, and some go to work in Guangzhou during the day and return home to Zhongshan after work.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4764515&req=5

pntd.0004473.g001: Locations of Guangzhou, Zhongshan and the neighboring cities.Nowadays, Guangzhou is considered a prominent commercial and business center in the PRD region. To maintain its role, major infrastructural projects were undertaken, including the construction of ring roads, highways, and railway tracks. This in turn provided easily accessible transportation between Guangzhou and other cities for the public. As Zhongshan is 86 kilometers from Guangzhou (a distance interconnected by Guangzhou-Zhuhai local train and several highways), workers and businessmen frequently travel between these two cities, and some go to work in Guangzhou during the day and return home to Zhongshan after work.
Mentions: Guangzhou, located at the northern tip of the Pearl River Delta (PRD), is the provincial capital of Guangdong Province (Fig 1). Because of its location, Guangzhou possessed exceptional conditions as a port with a nickname “southern gate of China” [27]. Zhongshan, a medium-size city in Guangdong Province, adjacent to Guangzhou, is located along the west side of the mouth of the Pearl River, directly opposite Shenzhen and Hong Kong, south of Guangzhou and Foshan, east of Jiangmen, and north of Zhuhai and Macau (Fig 1), occupying an area of 1,800.14 square kilometers with 3.12 million permanent residents (Census reference 2010). It has a typical subtropical monsoon climate with hot and humid summer, mild to cool winter, monthly average temperature range from 13.8°C to 28.6°C, and annual rainfall of about 1,750 mm.

Bottom Line: Models established during k-fold cross-validation also had considerable AUC (average 0.938-0.967).The sensitivity and specificity obtained from k-fold cross-validation was 78.83% and 92.48% respectively, with a forecasting threshold of 3 cases per week; 91.17% and 91.39%, with a threshold of 2 cases; and 85.16% and 87.25% with a threshold of 1 case.The out-of-sample prediction for the epidemics in 2014 also showed satisfactory performance.

View Article: PubMed Central - PubMed

Affiliation: Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong Province, P. R. China.

ABSTRACT

Background: Dengue is a re-emerging infectious disease of humans, rapidly growing from endemic areas to dengue-free regions due to favorable conditions. In recent decades, Guangzhou has again suffered from several big outbreaks of dengue; as have its neighboring cities. This study aims to examine the impact of dengue epidemics in Guangzhou, China, and to develop a predictive model for Zhongshan based on local weather conditions and Guangzhou dengue surveillance information.

Methods: We obtained weekly dengue case data from 1st January, 2005 to 31st December, 2014 for Guangzhou and Zhongshan city from the Chinese National Disease Surveillance Reporting System. Meteorological data was collected from the Zhongshan Weather Bureau and demographic data was collected from the Zhongshan Statistical Bureau. A negative binomial regression model with a log link function was used to analyze the relationship between weekly dengue cases in Guangzhou and Zhongshan, controlling for meteorological factors. Cross-correlation functions were applied to identify the time lags of the effect of each weather factor on weekly dengue cases. Models were validated using receiver operating characteristic (ROC) curves and k-fold cross-validation.

Results: Our results showed that weekly dengue cases in Zhongshan were significantly associated with dengue cases in Guangzhou after the treatment of a 5 weeks prior moving average (Relative Risk (RR) = 2.016, 95% Confidence Interval (CI): 1.845-2.203), controlling for weather factors including minimum temperature, relative humidity, and rainfall. ROC curve analysis indicated our forecasting model performed well at different prediction thresholds, with 0.969 area under the receiver operating characteristic curve (AUC) for a threshold of 3 cases per week, 0.957 AUC for a threshold of 2 cases per week, and 0.938 AUC for a threshold of 1 case per week. Models established during k-fold cross-validation also had considerable AUC (average 0.938-0.967). The sensitivity and specificity obtained from k-fold cross-validation was 78.83% and 92.48% respectively, with a forecasting threshold of 3 cases per week; 91.17% and 91.39%, with a threshold of 2 cases; and 85.16% and 87.25% with a threshold of 1 case. The out-of-sample prediction for the epidemics in 2014 also showed satisfactory performance.

Conclusion: Our study findings suggest that the occurrence of dengue outbreaks in Guangzhou could impact dengue outbreaks in Zhongshan under suitable weather conditions. Future studies should focus on developing integrated early warning systems for dengue transmission including local weather and human movement.

Show MeSH
Related in: MedlinePlus