Background
Hand, foot, and mouth disease (HFMD) is an infectious disease that typically presents as vesicular exanthema of the oral mucosa and peripheral extremities. Enteroviruses, such as Coxsackievirus A16 (CVA16) and Enterovirus A71 (EV-A71), are most commonly isolated from HFMD patients [
1]. Over the past decade, Asian countries have experienced enormous large-scale HFMD outbreaks, with deaths predominantly among children [
2‐
6]. The epidemics in China have been particularly serious and HFMD has become one of the leading causes of child death in China and a public health priority [
7]. In 2008–2012, 7,200,092 cases of HFMD, including 2457 fatal cases, were reported by the Chinese Center for Disease Control and Prevention [
8]. However, no vaccine or effective curative treatment is currently available. The incidence of HFMD will be also significantly affected by the continued mutation of the virus and increasing climate change. Therefore, HFMD remains an important public health problem in China.
Many studies have reported the seasonality of HFMD epidemics in China, and understanding the seasonality of these epidemics may identify potentially modifiable risk factors. Epidemics in several regions of China peak in late spring/early summer, with a second smaller peak in late autumn/early winter [
9‐
13]. Researchers have interpreted the seasonality of HFMD cases in terms of climate variables in specific regions. Meteorological parameters, such as temperature and relative humidity, may affect the transmission and frequency of HFMD. However, the effects of climate variables are not consistent across published studies, and these discrepancies could arise from various local climatic conditions, differences in socioeconomic status, and the demographic characteristics of different regions. Therefore, our understanding of the impact of seasonal and meteorological variables on disease transmission remains limited. Further research is required into the effects of climate variations on the incidence of HFMD.
Wuhan in Hubei Province is the largest mega-city in Central China, and has experienced a relatively high prevalence of HFMD in recent years. A better understanding of the temporal pattern of HFMD incidence might allow the appropriate allocation of health-care resources for better disease control and prevention. No study has yet examined the effects of meteorological variables on the occurrence of HFMD in Wuhan.
In this study, we investigated the association between the incidence of HFMD and its pathogens and several meteorological variables (including monthly average temperature, maximum temperature, minimum temperature, relative humidity, total rainfall, and wind velocity) in Wuhan, China, where high-quality surveillance data for HFMD have been collected. We used the time series analysis method “MemCalc” (Suwa-Trast, Tokyo, Japan) [
14‐
16], which has been successfully used to investigate associations between the occurrence of infectious diseases, pathogens, and meteorological variables, including rotavirus in India [
15], cholera in Bangladesh [
17], and chickenpox in Japan [
18]. Based on the result for the seasonality of HFMD, we conducted a prediction analysis for HFMD epidemics.
Discussion
In this study, we found that the HFMD infections occurring in Wuhan showed two seasonal peaks, in summer (June) and winter (November or December). The LSF curves shown in Fig.
7 suggest that the bimodal seasonal peaks in the HFMD epidemics are attributable to EV-A71 and CVA16 epidemics. The following factors may explain the bimodal seasonal peaks in the EV-A71 and CVA16 epidemics in Wuhan (Fig.
4b): (i) the association between EV-A71 and CVA16 infections and meteorological variables; and (ii) the environmental conditions in Wuhan.
(i)
Association between EV-A71 and CVA16 infections and meteorological variables. The results shown in Fig.
10 support the results of Chang et al. [
25], who found that cases of HFMD were reported in Taiwan at temperatures of 13–26 °C, the temperature range in which the EV-A71 virus is activated, and decreased at temperatures lower than 13 °C or higher than 26 °C. In Wuhan, where the temperature falls below 15 °C during autumn-winter and exceeds 25 °C in summer, the occurrence of HFMD epidemics is bimodal (Fig.
4a). This is similar to a previous finding in Guangzhou, China [
12], where the association between the incidence of HFMD and temperature increased rapidly below 25 °C but flattened above 25 °C.
However, the results shown in Fig.
10a indicate that the low value of
NT{A},E when 25 °C ≤
Temp < 30 °C returns to a high value when 30 °C ≤
Temp < 35 °C, which differs from the infections recorded in Taiwan [
25] and Guangzhou, China [
12]. This large value for
NT{A},E in Wuhan when 30 °C ≤
Temp < 35 °C was recorded on only one isolated occasion in July 2010 (Fig.
4b). To understand the correlation between EV-A71 infection and temperature in Wuhan in more detail, further surveillance data for EV-A71 (including data on HFMD) and other pathogens will be required. The findings of this study show that when the temperature is between 15 and 25 °C in Wuhan, public-health authorities should prepare fully to respond to an epidemic of HFMD, including increasing access to health-care resources, the distribution of scientific knowledge to the public, medical staff and public health personnel, the availability of essential medical equipment, active disease surveillance, and the design of other more-specific control measures to mitigate the risk of disease transmission.
Our finding of a positive correlation between the reported cases of EV-A71 infections and rainfall (Fig.
10d) is supported by a previous study that demonstrated that some tropical and subtropical countries experienced more outbreaks in the rainy season [
26]. The large values for
NRF,E when 250 mm ≤
r < 400 mm (Fig.
10d) are consistent with the peak rainfall during the monsoon, which brought large amounts of rain in June 2010, June 2011, June 2012, and May–June 2013 (Fig.
4f). The large values of
NRF,E when 150 mm ≤
r < 200 mm correspond to the relatively high values for rainfall before and after the monsoons in April–May and July–August (Fig.
4f).
(ii)
Environmental conditions in Wuhan. The winter peak in HFMD, which occurs after the first peak in summer, is probably attributable to disease transmission from the patients who formed the first peak because EV-A71 persists in the environment [
27]. EV-A71 can be found in an infected person’s feces for several weeks after the onset of symptoms, and possibly remains for days or weeks on materials in domestic and institutional environments [
28,
29]. The high population density in Wuhan could also increase the disease transmission rate and the likelihood of outbreaks.
The strong correlation between RH and CVA16 infections (Fig.
10e) may explain the fairly large numbers of CVA16 infections in the winter of 2011 and the spring of 2012, with very few cases in other years (Fig.
4c), although there has been no convincing explanation of these annual fluctuations in CVA16 infections. The annual fluctuations in disease have been interpreted in terms of many factors, including meteorological factors, host susceptibility, and changing contact rates between susceptible and infectious individuals [
30]. This organizational process has been investigated with the susceptible/exposed/infective/recovered (SEIR) model, which is described with nonlinear differential equations [
31,
32], but no definite conclusions regarding CVA16 infections have yet been drawn.
We found no statistically significant association between WV and either EV-A71 or CVA16. This result is inconsistent with a Hong Kong study [
33] for the period 1981–2010, when WV was reported to be 3.1 m/s, which was greater than the average wind speed in Wuhan during the present study period (2.1 m/s; Table
1). It is possible that there is a threshold effect of wind speed, which is not exceeded in Wuhan.
The prevalent month/week of the seasonal cycle of HFMD incidence has attracted the attention of researchers in the hope of predicting disease outbreaks [
9‐
13]. To investigate the seasonality of the disease incidence, some studies have used time series analyses [
9‐
12]. One of the important approaches used with time series is the autoregressive model, which is a special case of the linear filter model, and includes sophisticated versions, such as the autoregressive moving-average model and the seasonal autoregressive integrated moving-average model [
9,
34]. In the present study, we applied our prediction analysis method to the HFMD data (Fig.
8). The present method is based on the most traditional method of prediction analysis, which uses an extrapolation curve corresponding to the underlying variations of the time series data,
X(t) (Eq. (
2)) in future. The reproducibility of the HFMD data is considered to arise because the fundamental modes constructing
X(t) (Table
2) were well assigned by the MEM spectral analysis and reconstruct the periodic structure of the underlying variation in the data in the prediction range (Fig.
8). We anticipate that the present method of time series analysis using an MEM spectral analysis and LSM will allow the further development of prediction analyses for HFMD epidemics.
A limitation of this study was that we used monthly pathology data for EV-A71 and CVA16 rather than daily or weekly data, because monthly measures are the minimum unit of measurement released by the CISDCP. Further studies using daily or weekly data are required in the future. Another limitation was that the percentage of laboratory confirmation was low (< 5 %), because the purpose of testing samples from HFMD cases is to determine the predominant virus circulating in Wuhan, rather than to identify further patients with the disease.
Conclusion
The results of our study indicate that in Wuhan, EV-A71-based HFMD infections correlate strongly with the average, maximum, and minimum temperatures and total rainfall, and that CVA16-based HFMD infections correlate strongly with relative humidity.
The Intergovernmental Panel on Climate Change Third Assessment Report states that “changes in climate that will affect potential transmission of infectious diseases include temperature, humidity, altered rainfall, and sea-level rise” [
35]. EV-A71 and CVA16 lack a thermostatic mechanism, and their reproduction and survival rates are strongly affected by fluctuations in
temperature, as are those of other viruses, parasites, and bacteria [
36,
37]. Therefore, the effects of meteorological variables on the epidemiology of EV-A71 and CVA16 must be investigated to control HFMD, as in this study.
Acknowledgments
This study was supported, in part, by Grants-in-Aid for Scientific Research from the Health and Family Planning Commission of Hubei Province of China (grant no. JX6B102), the Health and Family Planning Commission of Wuhan Municipality of China (grant no. WG13B02), the National Science Foundation of China (grant no. 61203159), and the Ministry of Education, Culture, Sports, Science, and Technology of Japan (grant no. 25305022 and no. 25460769). The authors thank Edanz Group Ltd for their careful checking of the grammar and spelling of the manuscript.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
BC conceived the study, and managed and analyzed the HFMD incidence data. Data collection was administered and supervised by QH and DZ. AS, ST, and KM analyzed the data and AS drafted the manuscript. JZ partly analyzed the data. NK attracted funding. All authors contributed to writing the final version of this paper. All authors read and approved the final manuscript.