Prediction of H7N9 epidemic in China.
BACKGROUND
In March 2013, human cases of infection with a novel A (H7N9) influenza virus emerged in China. The epidemic spread quickly and as of 6 May 2013, there were 129 confirmed cases. The purpose of this study was to analyze the epidemiology of the confirmed cases, determine the impacts of bird migration and temperature changes on the H7N9 epidemic, predict the future trends of the epidemic, explore the response patterns of the government and propose preventive suggestions.


METHODS
The geographic, temporal and population distribution of all cases reported up to 6 May 2013 were described from available records. Risk assessment standard was established by analysing the temperature and relative humidity records during the period of extensive outbreak in three epidemic regions in eastern China, including Shanghai, Zhejiang and Jiangsu provinces. Risk assessment maps were created by combining the bird migration routes in eastern China with the monthly average temperatures from May 1993 to December 2012 nationwide.


RESULTS
Among the confirmed cases, there were more men than women, and 50.4% were elderly adults (age >61 years). The major demographic groups were retirees and farmers. The temperature on the days of disease onset was concentrated in the range of 9°C-19°C; we defined 9°C-19°C as the high-risk temperature range, 0°C-9°C or 19°C-25°C as medium risk and <0°C or >25°C as low risk. The relative humidity on the days of disease onset ranged widely from 25% to 99%, but did not correlate with the incidence of infection. Based on the temperature analysis and the eastern bird migration routes, we predicted that after May, the high-risk region would move to the northeast and inland, while after September, it would move back to north China.


CONCLUSIONS
Temperature and bird migration strongly influence the spread of the H7N9 virus. In order to control the H7N9 epidemic effectively, Chinese authorities should strengthen the surveillance of migrating birds, increase poultry and environmental sampling, improve live poultry selling and husbandry patterns and move from a "passive response pattern" to an "active response pattern" in focused preventive measures.
School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510030, China.
Zhaojie
Z
Zhang
Department of Earth Science, Sun Yat-sen University, Guangzhou, Guangdong 510275, China.
Yao
Y
Xia
School of Public Health, Southern Medical University, Guangzhou, Guangdong 510515, China.
Yi
Y
Lu
Key Laboratory of Tropical Disease Control, Ministry of Education, Guangzhou, Guangdong 510080, China.
Jingchao
J
Yang
School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510030, China.
Luwen
L
Zhang
School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510030, China.
Hui
H
Su
School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510030, China.
Lili
L
Lin
Haizhu District Center for Disease Control and Prevention, Guangzhou, Guangdong 510288, China.
Guoling
G
Wang
Department of Atmospheric Science, School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou, Guangdong 510275, China.
Tongmei
T
Wang
School of Public Health, University at Albany, State University of New York, Rensselaer, New York, USA.
Shao
S
Lin
School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510030, China. Email: lujiahai@mail.sysu.edu.cn.
Zhongmin
Z
Guo
School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510030, China.
Jiahai
J
Lu
D000818:Animals; D001717:Birds; D002681:China / Q000453:epidemiology; D064766:Influenza A Virus, H7N9 Subtype / Q000472:pathogenicity*; D005585:Influenza in Birds / Q000453:epidemiology*; D013696:Temperature