Hand, Foot, and Mouth Disease in China: Patterns of Spread and Transmissibility : Epidemiology

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Infectious Disease

Hand, Foot, and Mouth Disease in China

Patterns of Spread and Transmissibility

Wang, Yua; Feng, Zijiana; Yang, Yangb; Self, Steveb; Gao, Yongjuna; Longini, Ira M.b; Wakefield, Jonc; Zhang, Jinga; Wang, Lipinga; Chen, Xic; Yao, Lenab; Stanaway, Jeffrey D.d; Wang, Zijuna; Yang, Weizhonga

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Epidemiology 22(6):p 781-792, November 2011. | DOI: 10.1097/EDE.0b013e318231d67a




Wang Y, Feng Z, Yang Y, et al. Hand, foot, and mouth disease in China: Patterns of spread and transmissibility. Epidemiology. 2011;22:781–792.

In the abstract, the last sentence of the Results section should read, “A higher risk of transmission was associated with temperatures in the range of 70° F to 80° F, higher relative humidity, higher wind speed, more precipitation, greater population density, and periods during which schools were open.”

The last sentence of the abstract should read, “Timely diagnosis may be key to reducing the high mortality rate in infants.”

In two places (page 783, right column, line 16 and page 792, left column, line 10) the supplementary digital content link should be: https://links.lww.com/EDE/A521.

On page 784, right column, lines 6–7, the following supplementary digital content link should be added to the parenthetical expression “online animation”: https://links.lww.com/EDE/A522.

Epidemiology. 23(2):358, March 2012.

Hand, foot, and mouth disease is a common illness mostly seen in children and is caused by a spectrum of pathogens in the enterovirus (EV) family. Most cases involve mild to moderate symptoms, such as fever, oral ulcer, rashes on the extremities, pharyngitis, and herpangina, with recovery in about 3 to 6 days without medication.1 Although relatively rare, severe neurologic complication (including aseptic meningitis, encephalitis, and acute flaccid paralysis) can develop in children <5 years of age, particularly among those infected with enterovirus 71.2

Historically, outbreaks of hand, foot, and mouth disease have been sporadic and local, but this pattern has changed recently, with 2600 cases reported in Malaysia in 1997, nearly 130,000 cases in Taiwan in 1998, and thousands of cases in Singapore and Australia thereafter. Since then, small-to-medium epidemics have been continuously observed in the Asia-Pacific region.2,3 The number of cases has been increasing rapidly in mainland China since 2007. The cumulative reported number of cases in China reached nearly 500,000 in 2008 and 1.1 million in 2009, marking an era of unprecedented large-scale outbreaks. The occurrence of consecutive annual outbreaks also departs from the previously observed pattern, in which a major outbreak was usually followed by a quiescent period of 1 to 2 years.4

The transmissibility of recent circulating enteroviruses was assessed in the household setting in a prospective family cohort study in Taiwan.5 However, households are unlikely to be the sole transmission environment, and transmission in other settings, such as schools and communities, is likely to be of equal or greater importance for control. Hand, foot, and mouth disease outbreaks exhibit a clear seasonal pattern, with a rapid onset in the spring or early summer, a gradual decline after the peak, and a light second wave in the fall. This pattern has been observed on several continents and across multiple years.2,6 The extensive surveillance data from China, combined with publicly available demographic and environmental data, provide a unique opportunity to study the temporal and spatial patterns of disease spread at the aggregate level, and to assess associated risk factors. This type of analysis, although highly exploratory due to the aggregate nature of the data, can be used to identify hypotheses to be tested in epidemiologic field studies with individual-level data.


The Surveillance System

The Chinese Information System for Disease Control and Prevention is an Internet-based, real-time surveillance system established by the Chinese Center for Disease Control and Prevention (CDC) for monitoring and reporting public health emergency events and 39 notifiable infectious diseases. As of 2009, the surveillance system covers all Chinese CDC branches, more than 90% of hospitals at the county-level and above (>90%), more than 80% of clinics at the township level, and other medical institutes. In 2009, the median time from receiving disease information by a local authority to reporting it via the surveillance system was about 7 hours.

Data Collection

On 2 May 2008, hand, foot, and mouth disease was made a reportable disease, with reporting required within 24 hours via the surveillance system, or by mail for facilities not covered by the system. Clinical diagnosis of hand, foot, and mouth disease was guided by a two-level case definition:

  • Ordinary cases: fever with skin papular or vesicular rash on hand, foot, mouth, or buttock. A few cases may not have fever.
  • Severe cases: definition differs slightly between the 2 years.
  • 2008: Symptoms as in ordinary cases plus complications such as myoclonia, acute flaccid paralysis, encephalitis, cardiopulmonary failure, or pulmonary edema.
  • 2009: Ordinary symptoms with neurologic, respiratory, or circulatory complications (as in 2008), but also including increased peripheral white blood cells, abnormal cerebrospinal fluid, increased blood sugar, or any abnormality in electroencephalogram, cerebrospinal MRI, chest x-ray, or ultrasound cardiogram. Some severe cases may not have rash, and laboratory confirmation is necessary.

Laboratory confirmation is defined as follows:

  • Isolation of enterovirus or detection of enterovirus-specific RNA.
  • A titer of enterovirus-specific neutralizing antibody ≥256, or at least 4-fold increase in the titer between the acute phase and the recovering phase.

Upon diagnosis of a case of hand, foot, and mouth disease, the following information was recorded: birth date, sex, current home address, symptom onset date, diagnosis date, hospitalization date, severe case (yes or no), clinical symptoms, clinical outcome (recovered, stabilized, death, or other), whether specimen was collected, and viral type if specimen was collected and tested. Clinical specimens were collected from all severe and fatal cases and up to 5 ordinary cases per county per month. At the provincial level, at least 10 cases per month were serotyped. Serotyping and sequencing were performed at prefecture or provincial surveillance laboratories, with quality control and training from the Chinese CDC.

The addresses of cases enable their aggregation across various levels of administrative divisions (eg, from lower to higher geographic size: township, county, prefecture, and province). Geographic information, including boundaries and areas for each administrative division, was obtained from the National Fundamental Geographic Information System of China. Demographic information was found in annals of statistics of the administrative divisions. We obtained daily climate indices (including temperature, dew point, wind speed, and precipitation) for nearly 300 weather stations in China from the National Climate Data Center of the Department of Commerce of the United States.

Epidemiologic Description

We define the attack rate as the proportion of reported cases of hand, foot, and mouth disease among the general population, the case-severity ratio as the proportion of severe disease among all reported cases, the case-fatality ratio as the proportion of deaths among all reported cases, and the severe-case-fatality ratio as the proportion of fatal cases among severe cases. Based on the age distribution of, cases in the surveillance data, on availability of population-level demographics, and on previous studies on age-specific immune response to enteroviruses,7–9 we partitioned the population into 5 age-groups: 0 to 0.9 years (infants), 1.0 to 2.9 years, 3.0 to 5.9 years, 6.0 to 9.9 years, and ≥10 years. We partitioned all provinces of mainland China into 7 geographical regions: Central North, Central South, South, Northeast, Southwest, Central West, and West shown in eFigure 1 (https://links.lww.com/EDE/A521). Regions vary by population density, socioeconomic development, ethnicity, climate, and so forth. For instance, the Southwest and the West regions have relatively high proportions of minority ethnic groups. We calculated attack rates, case-severity ratios, case-fatality ratios, and severe-case-fatality ratios by age-group and geographic region for 2008 and 2009 separately. The distribution of time from symptom onset to diagnosis among cases, as well as the distribution of the time from onset to death among fatal cases, were reported by age-group, sex, and geographic region for the 2 years combined.

Transmissibility and Effects of Risk Factors

We used a Poisson regression embedded within an aggregate susceptible-infected-recovered statistical model to evaluate the transmissibility of the disease and the effects of potential risk factors on transmission. Specifically, we aggregated cases into weekly counts by g = 10 age-sex strata in each of the 342 prefectures in mainland China. We used prefectures as the geographic transmission units because (1) the resolution of the data at the prefecture level provides sufficient information for the risk factors that we collected, and (2) our method requires a sufficiently large susceptible population in each transmission unit that may not be available at the county level.

Let Yik(t) be the number of reported cases in stratum k of prefecture i that were infected during week t. Assuming a 1-week incubation period,10Yik(t) is the number of reported cases with symptom onsets in week t + 1. We also assume that the infectious period starts from the symptom-onset week and lasts for d weeks.

The reported cases were assumed to be infected as a result of exposure either to infectious cases or to an unknown local reservoir, including but not limited to environmental persistence (eg, sewage water) or long-term asymptomatic enterovirus carriers. Transmissions from the 2 types of sources are referred to as human-to-human and reservoir-to-human, respectively. We consider 2 levels of human-to-human contact: within prefecture and between prefectures, the latter referring to transmissions between neighboring prefectures or between an ordinary prefecture and the capital prefecture of the province. Let λ0, λ1, and λ2 be (respectively) the baseline transmission rates for reservoir-to-human, human-to-human within-prefecture, and human-to-human between-prefecture infections (where transmission rate is the weekly mean number of new infections a source can generate). Let Ai be the collection of prefectures that are adjacent to prefecture i. Let Xik(t) be the covariates associated with the subpopulation in stratum k of prefecture i in week t. For the climate indices, the prefecture-specific weekly averages are used as covariates. Let λijkl(t) be the transmission rate from an infectious person in stratum l of prefecture j, and λick(t) be the rate from the reservoir, to the susceptible population in stratum k of prefecture i during week t. The transmission rates are adjusted for covariates in regression models:


where 1condition indicates whether the condition is true (1) or not (0), and βS, βI, and αS are the covariate effects on susceptibility (with subscript S) and infectiousness (with subscript I). For a covariate X and its effect β, exp(βx) is the risk ratio at X = x versus at X = 0. The overall transmission rate in stratum k of prefecture i during week t is

where {i} ∪ Ai is the set of prefecture i and all its adjacent prefectures. pt–τ is the probability a case infected in week τ is infectious in week t. The values of pl, l = 1, …, d, together with d, are assumed known and subject to sensitivity analysis. We assume p1 = 1 and pl <1 for l >1 to account for the waning of infectiousness since symptom onset. It is reasonable to assume d = 2 or 3 according to the range of the convalescent period in historic epidemics.11,12 Conditioning on λik(t), we assume that Yik(t) ∼ Poisson(λik(t)). Statistical inference is based on maximum likelihood estimation. A similar model was used for influenza surveillance data, in which transmission rates were interpreted as autoregressive parameters.13 More discussion on the choice of the statistical model and regression covariates is given in the eAppendix (https://links.lww.com/EDE/A522). Data before the third week in May 2008 were ignored to avoid potential bias due to incomplete reporting. The last week in 2009 had only 3 days and was also excluded from analysis.

The local effective reproductive number (R) is defined as the average number of secondary infections a randomly selected case can generate in a fully susceptible population during his or her infectious period. In our setting, this quantity depends on the spatial and temporal location. The average number of secondary infections a case in stratum l of prefecture j with symptom onset in week t can generate during his/her infectious period is as follows:

The local effective R for a randomly selected case in prefecture j with symptom onset in week t is the average weighted by the susceptibility levels across all strata:

where ω1 = exp(Xjl(ts) measures the susceptibility level of stratum l.

is the probability that a randomly selected person is from stratum l, conditioning on that person being a case. The infectiousness levels of infectious sources are identical for all susceptibles in the prefecture and thus cancel out in the conditional probability.


Epidemiologic Characteristics

The epidemic curves of hand, foot, and mouth disease for the nation and its 7 geographic regions during 2008 and 2009 in mainland China are shown in Figure 1. Most regions displayed a common trend of steady increase beginning in early February, rapid increase during March or April, a peak from April to June, a quick decrease in summer, a slower decreasing rate or even a small second increase in early September, and, finally, steady decrease until January. The picture of 2008 is incomplete before May, but the timing of peaks was similar.

Epidemic curves of the 2008 and 2009 hand, foot, and mouth disease epidemics in China for the whole nation and 7 geographic regions. Cases are aggregated by week, that is, each unit of the horizontal axis is a week. Locations of the displayed dates are only approximate, with a resolution of one week.

Number of cases, severe cases, and fatal cases are presented in Table 1 by age, sex, region, and year. Corresponding attack rates, case-severity ratios, case-fatality ratios, and severe-case-fatality ratios are given in Table 2. Children <6 years of age constituted more than 93% of the cases, with the highest annual cumulative incidence (>18 per 1000) in the 1.0- to 2.9-year group in 2009. The case-severity ratio was 12.0 per 1000 in 2009, a dramatic increase from 2.5 per 1000 in 2008, partially due to an expansion of the definition of severe cases. A slight increase in the case-fatality ratio was also observed. The peaks of weekly case-severity ratio occurred mostly in July and August, later than the peaks of the epidemic curves (eFigure 2, https://links.lww.com/EDE/A521). The geographic distributions of prefecture-specific annual attack rates, case-severity ratios, case-fatality ratios, and severe case-fatality ratios across the nation are shown in eFigures 3–6 (https://links.lww.com/EDE/A521). The dynamic changes of prefecture-specific weekly attack rates (online animation) show the movement of the disease from the southern and central regions to the northern and western ones in spring and summer, and the remaining activity in the South during winter.

Reported Hand, Foot, and Mouth Disease Cases, Severe Cases, and Deaths by Age, Sex, Region, and Year
Attack Rates (per 1000), Case-severity Ratios (per 1000), Case-fatality Ratios (per 1000), and Severe-case-fatality Ratios by Age, Sex, Region, and Year

Effects of age, sex, and region on attack rate, case-severity ratio, case-fatality ratio, and severe-case-fatality ratio were estimated for the 2 years separately in Table 3. The estimated odds ratios approximate relative risks because the numerators are much smaller than the denominators. The effects of age and sex are similar between the two years, but the regional effects appear temporally heterogeneous. We focus on the 2009 epidemic because the data are complete for the year. Relative to the age group 1.0–2.9 years, risk of disease was about 40% among infants under the age of 1 year and children 3.0–5.9 years, and 5% and 1% in the 2 oldest age groups. Infants had 40% higher risk of severe disease than the 1.0–2.9 years group; all the older age groups had >50% lower risk. The pattern of the case-fatality ratios and severe-case-fatality ratios across age groups matches with that of the case-severity ratios, but with more dramatic differences in the case-fatality ratios. Boys had 56% higher risk of disease and 10% higher risk of severe disease than girls. Substantial geographic heterogeneity was observed for all 4 measures. The attack rate and case-severity ratio were the highest in the Central North region, with >70% of the nationally reported severe cases in just 3 provinces in this region (Shandong, Henan, and Hebei). The Southwest region had the second-highest case-severity ratio and the highest case-fatality ratio in 2009. Compared with the Central North region, all other regions (particularly by the Central West region) had much higher severe-case-fatality ratios (ORs >5).

Effects of Age, Sex, and Region on the Annual Attack Rate, Case-severity Ratio, Case-fatality Ratio, and Severe-case-fatality Ratio for the Years 2008 and 2009

As shown in Table 4, the mean (median) time from symptom onset to diagnosis among all reported cases in both years combined is 1.6 (1.0) days, and among severe cases, 2.2 (2.0) days. Infant cases had longer times from onset to diagnosis whether severe or not, and longer time from onset to death compared with older groups. A delay in diagnosis among infants may partially account for their higher case-severity ratio and case-fatality ratio. When the logistic models for year 2009 in Table 3 are further adjusted for the onset-to-diagnosis time (with durations of >5 days set to 5 days), the odds of severe disease among infants relative to children age 1.0–2.9 years decrease from 1.42 to 1.14 (95% CI = 1.09–1.19), and the OR regarding death drops from 2.42 to 1.88 (1.48–2.38). In addition, a 1-day delay in diagnosis increased the risk of severe disease by 40% (39%–42%) and the risk of death by 54% (44%–65%). The South region has the longest mean delay in severe cases, about 3 days, followed by the Northeast and Central West regions. Histograms of the delay times in eFigure 7 (https://links.lww.com/EDE/A521) suggest that the long delay in the South region was due to an excessive number of severe cases with ≥5 days of delay in the Guangdong province.

Mean and Median Time (in Days) From Symptom Onset to Diagnosis Among All Cases and Severe Cases, and Time From Symptom Onset to Death Among Fatal Cases, by Age, Sex, and Region

A total of 33,576 (2%) CI cases were laboratory-confirmed for pathogens, of which 26% were Coxsackie A16 (Coxsackie 16) and 48% were enterovirus 71 (Table 5). Between 2008 and 2009, the relative proportion of Coxsackie 16 among tested samples more than doubled, whereas those of enterovirus 71 and other enteroviruses (neither Coxsackie 16 nor enterovirus 71, but exact types are unknown) decreased. In 2009, Coxsackie 16 is mostly found in the Northeast region and the coastline of the Central South region (eFigure 8, https://links.lww.com/EDE/A521), whereas enterovirus 71 cases clustered in the Central North region where most of the severe cases were reported (eFigure 9, https://links.lww.com/EDE/A521). Among laboratory-confirmed severe cases, 81% were infected with enterovirus 71. With Coxsackie 16 as the reference of the odds, the ORs between severe and mild cases during 2009 were 16 (95% CI = 13–18) for enterovirus 71 and 4.2 (95% CI = 3.6–5.0) for other enteroviruses, controlling for age, sex, and time from onset to diagnosis. With death as the outcome, the ORs were 41 (95% CI = 13–130) for enterovirus 71 and 5.0 (95% CI = 1.4–18) for other enteroviruses. The proportion of enterovirus 71 (72%) was the highest in the Southwest region in 2009, which may partially account for its high case-severity ratio and case-fatality ratio.

Laboratory-confirmed Cases, Severe Cases, and Deaths by Pathogen Type and Year

Transmissibility and Effects of Risk Factors

We used (p1, p2, p3) to represent a 3-week infectious period with p2 × 100% and p3 × 100% infectiousness in the second and third weeks, respectively, relative to the first week, where p1 = 1 corresponds to the symptom onset week. We examined 3 settings: (1, 0.2, 0), (1, 0.5, 0), and (1, 0.6, 0.2), and report the results based on the setting of (1, 0.2, 0) as the primary findings because it provides a largest likelihood among the 3 settings.

The results of the aggregate susceptible-infected-recovered transmission model are presented for transmission rates in Table 6. The effects of discrete risk factors are given as risk ratios in Table 7 for human-to-human transmission and in eTable 1 (https://links.lww.com/EDE/A521) for reservoir-to-human transmission. The effects of age and sex are assumed constant for the 2 types of transmission and therefore presented only in Table 7. The risk ratios for the continuous risk factors for human-to-human transmission are displayed in Figure 2.

Estimates and 95% Confidence Intervals for Reservoir-to-human (λ0), Within-prefecture Human-to-human (λ1), and Across-prefecture Human-to-human (λ2) Transmission Rates Based on An Aggregate Susceptible-infected-recovered Model for the 2008–2009 Outbreaks Combined
Effects of Discrete Risk Factors on Susceptibility to Transmission Risk From Human to Human in the 2008–2009 Epidemics
Effects of continuous risk factors, presented as risk ratios (RRs), on aggregate human-to-human transmission rates. For each continuous risk factor X with a mean of , the RR is calculated as exp( 1(XJOURNAL/epide/04.03/00001648-201111000-00004/ENTITY_OV0398/v/2021-02-05T040352Z/r/image-png) + 2(XJOURNAL/epide/04.03/00001648-201111000-00004/ENTITY_OV0398/v/2021-02-05T040352Z/r/image-png)2), where 1 and 2 are estimated regression coefficients. The solid, dashed, and dotted curves correspond to the assumptions about the infectious period (1, 0.2, 0) (1, 0.5, 0), and (1, 0.6, 0.2), respectively. The vertical black dashed line indicates where RR = 1. The gray area is the histogram for the distribution of the corresponding covariate.

Transmission of the disease was driven primarily by contacts within prefectures with a transmission rate of more than 300 times that between neighboring prefectures. eFigure 14 (https://links.lww.com/EDE/A521) shows the model-predicted weekly mean number of cases generated by the unobserved sources (gray area) and by the observed cases in neighboring prefectures. Between-prefecture transmissions dominated over the unobserved reservoir in spring and summer, suggesting that the movement of the disease across prefectures was likely driven by human-to-human transmission during that period. Reservoir-to-human transmission rates were relatively high in the South and the Central South regions (more than 50 cases per week), which is also seen in eTable 1 (https://links.lww.com/EDE/A521).

The 10%, 50%, and 90% percentiles of the model-based local effective R values among all prefectures are shown in Figure 3. Standard deviations range from 0.002 to 0.08, with a median of 0.004, and are not presented in the figure. The peak values appear around the beginning of March in most regions. During peak weeks, the median local effective R reached 1.2 in the Central South and the South, and approximately 1.1 elsewhere. In the Central South and South, around 10% of the prefectures had local effective R values of >1.3 during the peak weeks. As the surveillance period does not cover the ascending phase of 2008, the model based on overall surveillance data likely underestimates the local effective R. Using the data from only the ascending phase of the 2009 epidemic (between 20 January and 20 April 2009), and a model without adjusting for any risk factor, the estimated local R values among all prefectures range from 1.36 to 1.58 (standard deviations = 0.003 to 0.006), with a median of 1.41. Figure 3 also clearly demonstrates the effect of school closure in spring and summer on reducing human-to-human transmission.

Time-dependent prefecture-specific aggregate local effective reproductive numbers (adjusted for covariates) for the overall nation and 7 geographic regions for the 2008–2009 HFMD epidemics in China. Medians are shown in black dots, and 10% and 90% quantiles are shown in gray triangles. The segments in boxes indicate school closure during the spring and summer breaks.

The age and sex effects on weekly risks based on the model differ in magnitudes from those for annual risks in Table 3, but the general trend is similar. Spatial heterogeneity was obvious for reservoir-to-human transmission, but not for human-to-human transmission. Human-to-human transmission rates were 15% higher during school open periods than school closure periods. Higher population densities were associated with higher human-to-human transmission rates except at very low densities, but the differences are generally no more than 5%. The disease favored warm temperature over either too cold or too hot, with 74°F as the most suitable for transmission. Transmission was greater with higher relative humidity levels, and with changes ≤10%. The effect of wind speed was nearly monotonic, increasing with much steeper slopes when the speed was less than or equal to 4 knots. Medium and high levels of precipitation increased the risk of disease by about 5%, suggesting that ground water could be a potential medium for transmission.

eFigure 15 (https://links.lww.com/EDE/A521) contrasts the model-predicted (conditional on observation in previous weeks) with observed weekly counts of cases, and eFigure 16 (https://links.lww.com/EDE/A521) plots standardized residuals of prefecture-specific weekly case numbers over log-transformed case numbers (left) and over time (right). The left panel of eFigure 16 (https://links.lww.com/EDE/A521) indicates that the Poisson model is reasonable for the data, as most residuals lie in a strip of approximately equal width over the observed case numbers. Both eFigure 15 and the right panel of eFigure 16 suggest a reasonable goodness-of-fit. The model captured most of the temporal variation except for the rapid growth in a few weeks in April 2009, in particular, during week 65 (24 March to 30 March 2009), when the case numbers more than doubled compared with the previous week.


The hand, foot, and mouth disease epidemics in China during 2008–2009 share many similarities with previous large outbreaks in the Asia-Pacific region.14,15 Preschool children, particularly those 1.0 to 2.9 years of age, had the highest risk of the disease, whereas infants had the greatest risk of severe complication and death. Boys were more susceptible to disease and complications. enterovirus 71 was responsible for the majority of severe complications and deaths, whereas Coxsackie 16 usually caused only mild symptoms. We found that temperature and wind speed were important, and relative humidity and precipitation were mild risk-modifiers for aggregate human-to-human transmission. The favorable effect of high relative humidity for viral transmission has been previously documented for polioviruses.16

Despite the enormous number of cases, the reported annual attack rates (0.38 and 0.89 per 1000 in 2008 and 2009) are much lower than 6.1 per thousand in Taiwan's 1998 outbreak and 3.5 or more per thousand in Singapore's outbreaks during 2002 and 2005 to 2007.14,17 Ho et al14 reported 0.08 per 1000 for the proportion of severe cases and 19% for the severe-case-fatality ratio among people <15 years of age in the 1998 epidemic of Taiwan, whereas the corresponding figures are 0.09 per thousand and 3% among children <10 years of age in 2009 in mainland China. The gap in the severe-case-fatality ratio could be due to better treatment options for Chinese patients 10 years after the outbreak in Taiwan, or to differences in the definition of severe cases. The enterovirus 71 lineages differ between the 2 outbreaks (C2 in Taiwan and C4 in China) but we are not aware of any systematic comparison of the virulence between various lineages of enterovirus 71.

The proportions of enterovirus 71 among laboratory-confirmed severe cases were similar (around 80%) in the 1998 outbreak of Taiwan and the 2008–2009 outbreaks of China.

We found that severe cases and infant cases are associated with longer delay in diagnosis. Extremity rash or oral ulcers appeared less frequently in severe cases than in mild cases, and neurologic complications are not specific to enteroviruses; both of these observations might have contributed to the delay in diagnosis. It is possible that delay in diagnosis contributed to development of cardiorespiratory complications or even death. Such clinical deterioration, if it occurred, often progressed rapidly, generally in 3 to 5 days.18 The delay in diagnosis in infants may be because infants have a higher baseline body temperature and are thus more tolerant of fever, and also because they cannot communicate their specific discomfort to their parents. A timely diagnosis may be a key to lowering the high mortality rate in infants, perhaps through educational campaigns among parents of newborns about the signs of hand, foot, and mouth disease.

The reason for the longer delay in diagnosis in Guangdong province compared with the rest of China is much less obvious. Guangdong province has been traditionally more industrialized than other regions, with a large volume of migrant labor workers from rural areas of inland provinces. This subpopulation has a relatively lower economic status and hygienic conditions, and medical services are likely to be less accessible.

Hand, foot, and mouth disease is a moderately transmissible infection, with the estimated local effective R between 1.4 and 1.6 during the peak season. Estimates for the basic reproductive number R0 for polioviruses (another family of enterovirus) range from 5 to 15,16 but these estimates were based on serosurveillance data and are not comparable with our estimates for the local effective R. The dominance of local transmission warrants future analysis at a finer spatial scale, such as counties or townships. The lack of finer spatial resolution data for risk factors limited our analysis to the prefecture level.

Although most cases were <6 years of age, our analysis showed a strong effect of school closure on epidemics. A plausible explanation is that substantial numbers of asymptomatic infections occurred at school among young school children, and these asymptomatic children further transmitted the disease to their younger siblings or neighbors. If this speculation is true, the reopening of schools after the summer break may partially account for the second rise of the epidemic curve in September. This speculation is partially supported by a serosurvey study in Taiwan, which found that nearly 70% of enterovirus 71 seropositive children <6 years of age were asymptomatic. Similarly, the New York virus watch program in the 1960s found that more than 40% of children of 5 years and older infected with Coxsackie viruses had no illness.7,19 Adults were found to have high proportions of asymptomatic enterovirus 71 infection in Taiwan5 and high levels of detectable enterovirus 71 antibodies in Germany.20,21 Future serosurvey studies are needed in China to confirm the role of asymptomatic infections among school children and adults in the epidemics. These older children and adults are possible targets for vaccine design, as they generally have much better immune response than preschool children.

Neither asymptomatic infections nor underreporting of symptomatic cases are explicitly considered in our model, due to the lack of information. Underreporting is possible if, for example, overwhelmed medical facilities tended to adopt more strict diagnosis criteria. Ignoring unobserved infections, asymptomatic or unreported, will not bias the estimates of aggregate human-to-human transmissibility under the assumptions that (1) unobserved cases are as infectious as observed symptomatic cases, and (2) the probability of not being observed given infection does not changes over time or space (eAppendix, https://links.lww.com/EDE/A521). However, the effect of a risk factor can be biased if the probability of not being observed differs across the levels of the risk factor. For example, infected adults may be more likely than children to be asymptomatic and less likely to seek medical care, which is a potential source of bias for the age effect on transmissibility.

It is more rational to model the transmission process of each type of enterovirus separately with appropriate consideration of interpathogen interaction. This may be pursued after the completion of the virologic confirmation of local specimens in the national laboratories of Chinese CDC. In contrast, the estimated transmission rates can be interpreted as the averages over the cocirculating pathogens, and the estimated risk ratios have the interpretation of average effects if the true risk ratios are similar across pathogens (online supplementary materials, https://links.lww.com/EDE/A516).

Our model fits the incidence of hand, foot, and mouth disease well for most of the year except for the peak weeks in April and May 2009, suggesting that there are unknown risk factors that drove the epidemic to the peak in such a short time. To inform prevention and control strategies, it is crucial to identify these underlying risk factors. Some insights may be provided by case-control studies that sample subjects over the duration of an outbreak and across spatial regions, tracing exposure history of each subject and performing environmental sampling of the viruses.

The aggregated nature of our data means that we are estimating average effects for risk factors collected at the population level. The results may not reflect the effects of these factors at the individual level, due to the ecological fallacy.22,23 For example, the estimated effects of the climate indices at the prefecture level may not reflect effects at the township level. However, the age and sex effects based on our model can be interpreted as individual-level effects because each age-sex stratum of each prefecture was modeled as a transmission unit.

After the large outbreaks in 2008 and 2009, the incidence of hand, foot, and mouth disease has continued to increase during 2010 in the Western Pacific region, particularly in China, Japan, South Korea, and Singapore.24 Despite the fact that this disease is an ongoing threat to regional health and can potentially become an emerging threat to global health, there appears to be a lack of studies and plans for intervention strategies. Our quantification of the population-level transmissibility and the effects of risk factors using surveillance data provide a basis for the use of mathematical or statistical models to evaluate the effectiveness of possible intervention strategies. The epidemiologic hypotheses generated by our analyses need to be addressed through the collection of more information in surveillance questionnaires and through appropriate field studies.


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