Flooding is one of the most significant disasters in the world. In the 21st century, flood hazard has increased greatly due to climate change, and more than half of global flood damages occur in Asia.Reference Arnell 1 , Reference Hirabayashi, Kanae and Emori 2 China is one of the developing countries most affected by flood disasters in the world. Qingdao, as a coastal city located in Shandong Province, China, suffered from several flood hazards due to extreme precipitation during 2009-2013, causing extensive loss of property and human lives.Reference Ma and Xv 3 - 6
Hand-foot-mouth disease (HFMD), as a kind of infectious gastrointestinal disease, remains a major public problem in Qingdao City.Reference Jia, Pan and Dong 7 , Reference Jia, Hao and Jiang 8 Compared with other cities in Shandong Province, Qingdao has a higher relapse rate of HFMD, which ranged from 0.05 to 62.26 per 100,000 monthly during 2009-2013. 9
There have been several articles that indicated the possibility for increased transmission of infectious gastrointestinal illness following flooding.Reference Toole 10 - Reference Seaman, Leivesley and Hogg 12 However, there has been little direct epidemiologic evidence of this association. HFMD, as one of the infectious gastrointestinal diseases, was considered as a sensitive disease associated with floods. To our best knowledge, the research studying the association between HFMD and floods is rare, and there has been no clear evidence demonstrating the potential impact of floods on HFMD. In order to clearly establish the relationship between HFMD and floods, we applied a time-series Poisson regression to analyze the impact of 5 floods on HFMD in Qingdao City during 2009-2013.
METHODS
Study Area
Figure 1 shows the geographic position of Qingdao City in Shandong Province, which is situated in the East China Sea. Qingdao is located between longitude 119°30′-121°00′ E and latitude 35°35′-37°09′ N, which determines the typical temperate continental monsoon climate with an annual average of 12.7°C and annual cumulative precipitation of 662.1 mm. It is a harbor city and has a population density of 657 persons per km2 (in 2009: population=7,409,000; land size=11,282).

Figure 1 Location of Qingdao in Shandong Province, China.
Disease Surveillance Data
Monthly disease surveillance data on HFMD from 2009 to 2013 in Qingdao were obtained from the Notifiable Diseases Surveillance System (NDSS). All cases of HFMD were diagnosed according to HFMD diagnosis and treatment guidelines edited by the Chinese Ministry of Health in 2010. According to NDSS, the HFMD is defined as an infectious gastrointestinal disease caused by enterovirus including enterovirus 71 (EV71), coxsackievirus A16 (CAV16), or other non-EV71 and non-CAV16, with fever, vesicles, and sores in the mouth and on the palms, soles, and buttocks, with or without neurological abnormalities such as meningitis, encephalitis, and polio-like paralysis.Reference Song, Wang and Wang 13 Only cases that were confirmed clinically and by laboratory tests were included in our study. Information of cases included are age, gender, occupation, address, name of disease, case classification, morbidity, and mortality of disease.
HFMD is classified as a statutory notifiable category C infectious disease in China. According to the measures for administration of public health emergencies and communicable disease monitoring information reporting, all cases of HFMD must be reported by hospitals and clinics to nominated Centers for Disease Control and Prevention (CDC) within 24 hours through the Direct Network Report system. 14 Since the HFMD was made statutorily notifiable in 2008, the quality of CDC reports has been consistent with 99.84% completeness and 92.76% accuracy.Reference Yang, Wu and Cheng 15
Flood Events
Flood data were collected from the Yearbooks of Meteorological Disasters in China, 6 which recorded the occurrence, deaths, damage area, and economic loss of floods in detail during 2009-2013. A flood is defined as a natural disaster resulting from the rivers overflowing due to short-term heavy precipitation, leading to submerged farmland and cities, casualties, and economic losses. According to the Yearbooks of Meteorological Disasters, 5 flood events occurred in Qingdao City from 2009 to 2013.
Meteorological Data
Monthly meteorological data during 2009-2013 were obtained from the China Meteorological Data Sharing Service System (http://cdc.cma.gov.cn/), which includes monthly cumulative precipitation (MCP), monthly average wind velocity, monthly average temperature (MAT), monthly average air pressure, and monthly average relative humidity.
Statistical Analysis
First, the distribution of HFMD morbidity and meteorological variables were described between the flooded and non-flooded months. Second, Spearman correlation was adopted to determine the lag effect between monthly morbidity of HFMD and other variables. Considering the reproducing of pathogens and latency of HFMD, a time lag of 0-1 months was determined in this study.Reference Yong, Jinhui and Xinan 16 In order to adjust the lagged effect, each variable with significant maximum correlation coefficient between 0 and 1 month was included in the subsequent analysis.
Longitudinal data analysis using a generalized linear model is an effective method to analyze the association between flood events and enteric infectious diseases. This method has been applied in several studies.Reference Ni, Ding and Li 17 - Reference Thompsona, Zelner and Nhu 20 After adjusting for the lag effect, a time-series Poisson regression model fixed with floods, meteorological factors, and the seasonal variable, was conducted to examine the association between floods and HFMD quantitatively. In the model, a categorical variable defined by non-flooded and flooded was designed to estimate the risk of floods (relative risk [RR]) on HFMD morbidity. Results show that temperature and precipitation were the main influencing climate factors which could significantly increase the risk of HFMD.Reference Bo, Song and Wang 21 - Reference Liu, Ji and Shan 23 In order to control for seasonal and meteorological effects, a triangular function, temperature and precipitation were selected in the model to simulate the seasonality and eliminate the potential meteorological impact. The regression in model was described as follows:

where Y t denotes monthly morbidity of HFMD at time t, January 2009 to December 2013. β 0 represents the intercept; flood represents flooded and non-flooded months assigning 1 and 0 respectively; temperature and precipitation represent MAT and MCP, respectively.
All statistical analyses were performed using R v. 3.11 (The R Project for Statistical Computing, Vienna, Austria).
Results
Descriptive Analysis of HFMD and Meteorological Data
A total of 55,920 cases of HFMD were recorded over non-flooded and flooded periods from 2009 to 2013 in Qingdao City. Table 1 shows the distributions of HFMD and meteorological factors for the 2 different periods, both total number of cases and broken down by sex and age groups. MAT and MCP were significantly different between non-flooded and flooded months (P<0.05), and were higher during flooded months than non-flooded months.
Table 1 Description of Monthly Hand-Foot-Mouth Disease (HFMD) Morbidity and Meteorological Factors During Non-Flooded and Flooded Periods in 2009-2013

Abbreviations: SD, standard deviation; Min, minimum; P25, 25th percentile; P75, 75th percentile; Max, maximum; 0-1, 0-1 years age; 1-2, 1-2 years age; 3-5, 3-5 years age; 6-14, 6-14 years age; Temperatureav, monthly average temperature; Precipitation, monthly cumulative precipitation.
*P<0.05 versus non-flooded months.
Lag Effects Analysis
The results of Spearman correlation tests between morbidity of HFMD and explanatory variables are shown in Table 2. The tests indicated that floods were positively correlated with morbidity of HFMD among different populations with 1 month lagged, expect for 0-1 year population with no significant month lagged and 1-2 year population with 0 month lagged. In addition, as shown in Table 2, MAT and MCP were significantly related with HFMD morbidity.
Table 2 Lag Effects Between Hand-Foot-Mouth Disease Morbidity and Explanatory Variables According to Monthly Data During 2009-2013

Abbreviations: 0-1, 0-1 years age; 1-2, 1-2 years age; 3-5, 3-5 years age; 6-14, 6-14 years age; Temperatureav, monthly average temperature; Precipitation, monthly cumulative precipitation.
*P<0.05.
Regression Analysis
Results showed that among the total population, male and female populations, 1-2 age population and 3-5 age population, the parameter and RR values of floods were significantly estimated through the longitudinal analysis. Table 3 presents the parameters and RR values of floods on HFMD in the time-series Poisson regression model. After controlling for the lag effect, meteorological factors, and seasonal impact, the increased risks of floods on HFMD were found in the regression models, and the RRs in total population, male, female, 1-2 age population, and 3-5 age population were 1.178, 1.165, 1.198, 1.338, and 1.245, respectively. Figure 2 indicated that the dynamic of monthly morbidity of HFMD corresponded relatively well with the regression models during the study period (r 2: 0.75 in total population; 0.71 in male; 0.69 in female; 0.61 in 1-2 age population; 0.76 in 3-5 age population).

Figure 2 Dynamics of Hand-Foot-Mouth Disease (HFMD) in Qingdao with the Analysis of Poisson Regression From 2009 to 2013 (Morbidity Per 10,000,000 Population). (A) Dynamics of HFMD in total population; (B) dynamics of HFMD in males; (C) dynamics of HFMD in females; (D) dynamics of HFMD in children under 1-2 years old; (E) dynamics of HFMD in children under 3-5 years old.
Table 3 Relative Risks (RRs) Parameters Coefficients Form the Time-Series Poisson Regression Model for Hand-Foot-Mouth Disease

Abbreviations: 0-1, 0-1 years age; 1-2, 1-2 years age; 3-5, 3-5 years age; 6-14, 6-14 years age
*P<0.05.
DISCUSSION
Due to climate change in recent years, HFMD is increasingly considered a significant public health problem in China, not only threatening human health, but also causing tremendous loss and burden to both families and society. Although HFMD outbreaks were observed after floods caused by high-intensity precipitation in summer and autumn,Reference De, Changwen and Wei 24 , Reference Park, Lee and Baek 25 there have been limited studies conducted to discuss the association between floods and HFMD. Additionally, insufficient evidence was available to evaluate the effects of floods on HFMD. To our best knowledge, this is the first time that positive evidence has been found to demonstrate the impact of floods on HFMD according to a quantitative analysis from 2009 to 2013.
Results indicate that after controlling for time-lag effect, seasonal effect, and primary meteorological variables, floods could significantly influence the dynamic of HFMD with increasing disease risk. This suggests that the morbidity of HFMD during flooded months could be higher than during non-flooded months. There exist several reasons why the risk of HFMD increases during floods, which mainly include water-related factors and human contact behaviors. On the one hand, precipitation plays an important role in HFMD infection by changing the living environment, since water is considered a potential reservoir and vehicle for the pathogens.Reference Cheng, Wu and Xu 22 , Reference Huang, Deng and Yu 26 - Reference Onozuka and Hashizume 28 The survival of enteroviruses, related to HFMD, could be enhanced in a much warmer and moister environment.Reference Abad, Pinto and Bosch 29 , Reference Dowdle and Wolff 30 During the flood period, most common in spring and summer, the enteric pathogens could grow fast and reproduce rapidly under a suitable environment.Reference Stetler 31 With the increase of pathogens’ concentration in water, the enteric pathogens could be transmitted by contaminated water, increasing the opportunities for human contact during flood periods. The enteric pathogens may be transported by the contaminated water through surface water, estuarine water, seawater, rivers, aerosols emitted from sewage treatment plants, insufficiently treated water, drinking water, and private wells that receive treated or untreated wastewater either directly or indirectly.Reference Lee and Kim 32 - Reference Lipp and Rose 34 On the other hand, following increased transmission of pathogens by contaminated water, humans could be more likely infected by enterovirus through potential contact behaviors during and after floods. Studies have shown that the probable contact behaviors causing enterovirus exposure include ingesting contaminated water or food, direct contact with contaminated water, and recreational activities in contaminated waters.Reference Ashbolt 35 - Reference Rajtar, Majek and Polanski 37 Contact with infected individuals may be another risk increasing the morbidity of HFMD. During and after floods, people were more likely to spend their time in indoor areas with more crowded or air-conditioned environments, which increased the HFMD infection via contact with infected individuals.
Due to drinking boiled water traditionally, water-related factors may be not the direct risk factors of HFMD during flood periods in China, which means that human contact behaviors may be the predominant reason increasing the risk of HFMD infection. In our study, the relative risks among different populations were evaluated, which indicated that the impact of floods on HFMD was higher in children (RR: 1.338 under 1-2 years old; 1.245 under 3-5 years old). The possible explanations may be low herd immunity and cross infection due to close contact.Reference Wong, Yip and Lau 38 , Reference Li, Zhang and Zhang 39
Results from Tables 1 and 2 suggested the potential relationship among the floods, meteorological factors, and HFMD. On the one hand, the impact of floods and meteorological factors on HFMD remain different and separate with different degrees of lagged correlation. A study assessing the association between meteorological factors and HFMD in Qingdao demonstrated that precipitation and temperature positively related with HMFD incidence, and that HFMD incidence increased with increasing precipitation and temperature.Reference Jiang, Yang and Chen 40 During non-flooded periods, moderate precipitation and temperature could impact the HFMD after a longer process with a bit longer lagged effect. On the other hand, the individual impacts of precipitation, temperature, and floods on HFMD superimposed and increased the risk of HFMD. Flooding in summer could increase the risk of HFMD due to both higher precipitation and higher temperature. The floods in our study all occurred in the summer months, which were also the peak of HFMD incidence during the study period.Reference Jiang, Yang and Chen 40 During the summer months, precipitation was closely associated with floods, and the risk of floods could be increased by the higher precipitation and precipitation variability.Reference Li and Wang 41 Therefore, floods, as a kind of meteorological disaster, could impact HFMD through a stronger and more rapid process with a shorter lagged effect.
Several limitations of this study must be acknowledged. First, due to lack of detailed laboratory information, the impact of floods on pathogens was not analyzed in this study. However, a study analyzing the etiological characteristics of HFMD from 2007 to 2011 suggested that EV71 and CAV16 were the dominant strains of HFMD in Qingdao City during the study period,Reference Jiang, Hao, Dong and Liu 42 which needed further study with floods in the future. In addition, under-reporting is an inevitable issue, which could lead to an underestimation of the impact of floods on HFMD. Finally, all floods were described as city wide, which might also lead to an underestimated RR value if some towns were not affected by the flooding.
CONCLUSIONS
This study has, for the first time, provided the positive evidence of the impact of floods on HFMD. It demonstrates that floods significantly increased the risk of HFMD during the study period. Additionally, among the different populations, the risks were higher among children under 5 years old.
Acknowledgments
The authors thank the Qingdao Center for Disease Control and Prevention and the National Meteorological Information Centre of China for sharing the data needed for the study.
Funding
This work was supported by the National Basic Research Program of China (973 Program) (grant no. 2012CB955502).