Time series analysis of reported cases of hand, foot, and mouth disease from 2010 to 2013 in Wuhan, China

BMC Infectious Diseases

Nobumichi Kobayashi¹  Junchan Zhao²  Keiji Mise³  Dunjin Zhou⁶  Quan Hu⁶  Shin’ichi Toyoda⁵  Ayako Sumi¹  Banghua Chen⁴ 

[1] Department of Hygiene, Sapporo Medical University School of Medicine, S-1, W-17, Chuo-ku, Sapporo 060-8556, Hokkaido, Japan;School of Mathematics and Statistics, Hunan University of Commerce, Changsha, Hunan, China;Department of Admission, Center of Medical Education, Sapporo Medical University, Hokkaido, Japan;Department of Infectious Diseases Prevention and Control, Wuhan Centers for Disease Control and Prevention, Wuhan, Hubei, China;Department of Information Engineering, College of Industrial Technology, Hyogo, Japan;Wuhan Centers for Disease Control and Prevention, 24 Jianghanbei Road, Wuhan 430000, Hubei, China

关键词: Spectral analysis;    Time series analysis;    Meteorological variable;    Seasonality;    Hand, foot, and mouth disease;   

Others  :  1231027
DOI  :  10.1186/s12879-015-1233-0

 received in 2015-02-02, accepted in 2015-10-19,  发布年份 2015

【 摘 要 】

Background

Hand, foot, and mouth disease (HFMD) is an infectious disease caused by a group of enteroviruses, including Coxsackievirus A16 (CVA16) and Enterovirus A71 (EV-A71). In recent decades, Asian countries have experienced frequent and widespread HFMD outbreaks, with deaths predominantly among children. In several Asian countries, epidemics usually peak in the late spring/early summer, with a second small peak in late autumn/early winter. We investigated the possible underlying association between the seasonality of HFMD epidemics and meteorological variables, which could improve our ability to predict HFMD epidemics.

Methods

We used a time series analysis composed of a spectral analysis based on the maximum entropy method (MEM) in the frequency domain and the nonlinear least squares method in the time domain. The time series analysis was applied to three kinds of monthly time series data collected in Wuhan, China, where high-quality surveillance data for HFMD have been collected: (i) reported cases of HFMD, (ii) reported cases of EV-A71 and CVA16 detected in HFMD patients, and (iii) meteorological variables.

Results

In the power spectral densities for HFMD and EV-A71, the dominant spectral lines were observed at frequency positions corresponding to 1-year and 6-month cycles. The optimum least squares fitting (LSF) curves calculated for the 1-year and 6-month cycles reproduced the bimodal cycles that were clearly observed in the HFMD and EV-A71 data. The peak months on the LSF curves for the HFMD data were consistent with those for the EV-A71 data. The risk of infection was relatively high at 10 °C ≤ t < 15 °C (t, temperature [°C]) and 15 °C ≤ t < 20 °C, and peaked at 20 °C ≤ t < 25 °C.

Conclusion

In this study, the HFMD infections occurring in Wuhan showed two seasonal peaks, in summer (June) and winter (November or December). The results obtained with a time series analysis suggest that the bimodal seasonal peaks in HFMD epidemics are attributable to EV-A71 epidemics. Our results suggest that controlling the spread of EV-A71 infections when the temperature is approximately 20–25 °C should be considered to prevent HFMD infections in Wuhan, China.

【 授权许可】

   
2015 Chen et al.

【 图 表 】

Fig. 1.

Fig. 2.

Fig. 3.

Fig. 4.

Fig. 5.

Fig. 6.

Fig. 7.

Fig. 8.

Fig. 9.

Fig. 10.

Fig. 1.

Fig. 2.

Fig. 3.

Fig. 4.

Fig. 5.

Fig. 6.

Fig. 7.

Fig. 8.

Fig. 9.

Fig. 10.

【 参考文献 】

• [1]Melnick JL. Poliovirus and other enteroviruses. In: Viral infections of humans –epidemiology and control. 4th ed. Evans AS, Kaslow RA, editors. Plenum Publishing Corporation, New York; 1997: p.583-663.
• [2]Tu PV, Thao NT, Perera D, Huu TK, Tien NT, Thuong TC, How OM, Cardosa MJ, McMinn PC. Epidemiological and virologic investigation of hand, foot, and mouth disease, Southern Vietnam. Emerg Infect Dis. 2005; 13:1733-41.
• [3]Fujimoto T, Chikahira M, Yoshida S, Ebira H, Hasegawa A, Totsuka A, Nishio O. Outbreak of central nervous system disease associated with hand, foot, and mouth disease in Japan during the summer 2000: detection and molecular epidemiology of enterovirus 71. Microbiol Immunol. 2002; 46:621-7.
• [4]Wang Y, Feng Z, Yang Y, Self S, Gao Y, Longini IM, Wakefield J, Zhang J, Wang L, Chen X, Yao L, Stanaway JD, Wang Z, Yang W. Hand, foot, and mouth disease in China: patterns of spread and transmissibility. Epidemiology. 2011; 22:781-92.
• [5]Ang LW, Phoon MC, Wu Y, Cutter J, James L, Chow V. The changing seroepidemiology of enterovirus 71 infection among children and adolescents in Singapore. BMC Infect Dis. 2011; 11:270. BioMed Central Full Text
• [6]Pueppa J, Theamboonlers A, Korkong S, Linsuwanon P, Thongmee C, Chatproedprai S, Poovorawan Y. Molecular characterization and complete genome analysis of human enterovirus 71 and coxsackievirus A16 from children with hand, foot and mouth disease in Thailand during 2008-2011. Arch Viol. 2011; 156:2007-13.
• [7]Chinese Center for Disease Control and Prevention. National Incidence and death cases of notifiable class A or class B infectious diseases. [http://www.chinacdc.cn]. Accessed 10 October 2015.
• [8]Xing W, Liao Q, Viboud C, Zhang J, Sun J, Yu JT, Chang Z, Liu F, Fang VJ, Zheng Y, Cowling BJ, Varma JK, Farrar JJ, Leung GM, Yu H. Hand, foot, and mouth disease in China, 2008-12: an epidemiological study. Lancet Infect Dis. 2014; 14:308-18.
• [9]Feng H, Duan G, Zhang R, Zhang W. Time series analysis of hand-foot-mouth disease hospitalization in Zhengzhou: establishment of forecasting models using climate variables as predictors. PLoS One. 2014; 9:e87916.
• [10]Liu Y, Wang X, Liu Y, Sun D, Ding S, Zhang B, Du Z, Xue F. Detecting spatial-temporal clusters of HFMD from 2007 to 2011 in Shandong province, China. PLoS One. 2013; 8:e63447.
• [11]Wu H, Wnag H, Wang Q, Xin Q, Lin H. The effect of meteorological factors on adolescent hand, foot, and mouth disease and associated effect modifiers. Global Health Action. 2014; 7:1-8.
• [12]Huang Y, Deng T, Yu S, Gu J, Huang C, Xiao G, Hao Y. Effect of meteorological variables on the incidence of hand, foot, and mouth disease in children: a time-series analysis in Guangzhou, China. BMC Infect Dis. 2013; 13:134-42. BioMed Central Full Text
• [13]Zou X, Zhang XZ, Wang B, Qiu YT. Etiologic and epidemiologic analysis of hand, foot, and mouth disease in Guangzhou city: a review of 4,753 cases. Braz J Infect Dis. 2012; 16:457-65.
• [14]Sumi A, Luo T, Zhou D, Yu B, Kong D, Kobayashi N. Time-series analysis of hepatitis A, B, C and E infections in a large Chinese city: application to prediction analysis. Epidemiol Infect. 2013; 141:905-15.
• [15]Sumi A, Rajendran K, Ramamurthy T, Krishinan T, Nair GB, Harigane K, Kobayashi N. Effect of temperature, relative humidity and rainfall on rotavirus infections in Kolkata, India. Epidemiol Infect. 2013; 141:1652-61.
• [16]Luo T, Sumi A, Zhou D, Kobayashi N, Mise K, Yu B, Kong D, Wang J, Duan Q. Seasonality of reported tuberculosis cases from 2006 to 2010 in Wuhan, China. Epidemiol Infect. 2014; 142:2036-48.
• [17]Ohtomo K, Kobayashi N, Sumi A, Ohtomo N. Relationship of cholera incidence to El Niño and solar activity elucidated by time-series analysis. Epidemiol Infect. 2010; 138:99-107.
• [18]Harigane K, Sumi A, Mise K, Kobayashi N. The role of temperature in reported chickenpox cases from 2000 to 2011 in Japan. Epidemiol Infect. (in press).
• [19]Guideline for the diagnosis and treatment of hand, foot and mouth disease. 2010. Available at: http://www. moh.gov.cn/yzygj/s3593g/201306/6d935c0f43cd4a1fb46f8f71acf8e245.shtml
• [20]Guideline for the Prevention and Control of HFMD, 2009. Available at: http://www.chinacdc.cn/jkzt/crb/szkb/jszl_2275/200906/t20090612_24707.htm. Accessed 10 October 2015.
• [21]Ohtomo N, Terachi S, Tanaka Y, Tokiwano K, Kaneko N. New method of time series analysis and its application to Wolf’s sunspot number data. Jpn J Appl Phys. 1994; 33:2321-831.
• [22]Sumi A, Ohtomo N, Tanaka Y, Sawamura S, Olsen LF, Kobayashi N. Prediction analysis for measles epidemics. Jpn J Appl Phys. 2003; 42:7611-20.
• [23]Armitage P, Berry G, Matthews JNS. Statistical methods in medical research. 4th ed. Blackwell Science, Oxford; 2012.
• [24]Papoulis A. Probability, random variables, and stochastic process. 3rd ed. MacGrawHill, New York; 1991.
• [25]Chang HL, Chio CP, Su HJ, Liao CM, Lin CY, Shau WY, Chi YC, Chen YT, Chou YL, Li CY, Chen KL, Chen KT. The association between enterovirus 71 infections and meteorological parameters in Taiwan. PLoS One. 2012; 7:e46845.
• [26]Chen Z, Sun H, Yan Y, Wang Y, Zhu C, Zhou W, Huang L, Wang M, Mize M, Tian J, Ji W. Epidemiological profiles of hand, foot, and mouth disease, including meteorological factors, in Suzhou, China. Arch Viol. 2015; 160:315-21.
• [27]Singapore MH. EV71-associated epidemic hand, foot and mouth disease in Singapore. Epidemiol News Bull. 2008; 34:63-6.
• [28]Karmer A, Schwebke I, Kampf G. How long do nosocominal pathogens persists on inanimate surface? A systematic review. BMC Infect Dis. 2006; 6:130. BioMed Central Full Text
• [29]Abad FX, Pinto RM, Bosch A. Survival of enteric viruses on environmental fomites. Appl Environ Microbiol. 1994; 60:3704-10.
• [30]Anderson RM, May RM. Infectious diseases of humans: dynamics and control. Oxford University Press, London; 1991.
• [31]Olsen LF, Schaffer WM. Chaos versus noisy periodicity: alternative hypotheses for childhood epidemics. Science. 1990; 249:499-504.
• [32]Li Y, Zhang J, Zhang X. Modeling and preventive measures of Hand, foot and mouth disease (HFMD) in China. Int J Environ Res Public Health. 2014; 11:3108-17.
• [33]Ma E, Lam T, Wong C, Chuang SK. Is hand, foot and mouth disease associated with meteorological parameters? Epidemiol Infect. 2010; 138:1779-88.
• [34]Song Y, Wang F, Wang, B, Tao S, Zhang H, Liu S, Ramirez O, Zeng Q. Time series analyses of hand, foot and mouth disease integrating weather variables. PLoS One. doi:. 10. 1371/journal.pone.0117296 webcite
• [35]McCarthy JJ, Canziani OF, Leary NA, Dokken DJ, White KS. Climate change 2001: impacts, application, and vulnerability. Cambridge University Press, Cambridge; 2001.
• [36]Meeburg BG, Kijllstra A. Changing climate-changing pathogens: Toxoplasma gondii in North-Western Europe. Parasitol Res. 2009; 105:17-24.
• [37]Patz JA, Campbell-Lendrum D, Holloway T, Foley JA. Impact of regional climate change on human health. Nature. 2005; 438:310-7.