Impact of public health and social measures on hand-foot-mouth disease transmission and prediction of upcoming season after relaxation of COVID-19 control measures

doi:10.21203/rs.3.rs-1999622/v1

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Impact of public health and social measures on hand-foot-mouth disease transmission and prediction of upcoming season after relaxation of COVID-19 control measures

https://doi.org/10.21203/rs.3.rs-1999622/v1

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Background

School based-measures such as school closure and school holidays have been considered a viable intervention during the hand-foot-mouth disease (HFMD) epidemic. However, the impact of public health and social measures (PHSMs) on HFMD transmission and the consequences of the HFMD epidemic after relaxing the PHSMs remains unclear.

Methods

Korean national surveillance data on HFMD from 2014 to 2019 was used to estimate the temporal changes in HFMD transmissibility (instantaneous reproductive number, ${R}_{t}$). Furthermore, we used a simulation based stochastic transmission model to predict the future burden of HFMDs after relaxation of COVID-19 PHSMs, assuming all the Korean population was susceptible to HFMD in 2023, the stochastic transmission model simulated the number of HFMD cases in South Korea.

Results

We found that school holidays and 2015 PHSMs reduced the ${R}_{t}$ by 2–7% and 13%, respectively. Model projections indicated that the peak magnitude for season 2023, after relaxation of COVID-19 PHSMs in late 2022, could be 2·5–8·5 fold larger than that of the HFMD seasons during the pre-pandemic.

Conclusions

PHSMs likely have a larger impact on HFMD transmission than school-based measures alone (i.e. school holidays). Furthermore, complete relaxation of COVID-19 PHSMs could significantly increase the HFMD infection burden for the upcoming HFMD season. Preventive measures targeting preschoolers could be considered as potential options for reducing the future burden of HFMD.

hand-foot-and-mouth disease

school holidays

public health and social measures

transmissibility

simulation

Hand-foot-mouth disease (HFMD) is a communicable disease that primarily affects children and is characterized by a rash or vesicular appearance on the hands, feet, and tongue [1]. HFMD is caused by RNA viruses belonging to the Picornaviridae family, such as enteroviruses and coxsackieviruses, and is spread through direct contact with contaminated saliva or fomites.[2] While the number of mild cases of HFMD vastly outnumbers severe cases, HFMD is a high-incidence pediatric disease that affects millions of children every year across Asia, and is estimated to cause 97,000 disability-adjusted life-year losses per annum [3].

South Korea, a country in East Asia located on the southern half of the Korean peninsula, has 51.7 million people and four distinct seasons. HFMD epidemics recur in South Korea from April to August, peaking in late June or July each year, and their annual socioeconomic burden is estimated to be approximately 100 million USD [4]. Several studies have demonstrated that meteorological factors such as temperature, rainy season, and humidity may affect the seasonality of HFMD [5, 6], and HFMD epidemics have been linked to school activity, including kindergartens and childcare centers [7, 8]. Therefore, school closures may be a viable intervention during an HFMD epidemic [2, 9]. However, the effectiveness of school-based interventions such as scheduled school holidays or reactive school closures in reducing the HFMD burden is controversial [10, 11]. Furthermore, as public health and social measures (PHSMs) are rarely used to mitigate HFMD transmission, the evidence demonstrating the benefits of nationwide PHSMs in the community setting remains limited at present.[10]

In South Korea, the summer school holiday is typically for a month between mid-July and mid-August [6]. The school holidays from 2014 to 2019 and the nationwide PHSMs for the epidemic of Middle East respiratory syndrome coronavirus (MERS-CoV) in 2015 coincided with the HFMD season, allowing us to assess their impact on HFMD transmission. Additionally, various PHSMs have been implemented for the coronavirus 2019 (COVID-19) pandemic in 2020–2022. Along with several countries, the Korean government had planned to relax all PHSMs after achieving a high seroprevalence rate for SARS-CoV-2 in the community, and is expected to make this announcement in July or October 2022 on the basis of the nationwide quarterly seroprevalence studies [12]. At present, the COVID-19 PHSMs have restricted HFMD transmission for more than two years, allowing us to estimate the possible HFMD burden after relaxation of all PHSMs in late 2022 as a reasonable scenario.

Thus, this study aimed to quantify the impact of school holidays and nationwide PHSMs on the HFMD epidemic and to predict the future burden of HFMD in South Korea after the relaxation of COVID-19 PHSMs.

This study was approved by the Konyang University Institutional Review Board (2022-05-003). HFMD data used in this study acquired from the publicly available surveillance report published by Korea Disease Control and Prevention Agency. Thus, there was no need for ethical approval to collect or use the data.

Data for analysis

We obtained data from the Korea Disease Control and Prevention Agency (KCDA) case-based weekly sentinel surveillance of HFMD [13]. This nationwide surveillance was carried out through a network of 100 pediatric clinics, which reported all cases of HFMD, including probable and confirmed cases, and the total number of patients seen to the KCDA. We estimated the weekly number of patients with HFMD in South Korea on the basis of the data for the overall number of patient visits in pediatric clinics obtained from the Korean national health insurance service (which covers 95% of the Korean population). The clinical criteria for a notified case of HFMD were individuals who have the rash and/or vesicles on hands, feet, and tongue [14]. The numbers of patients with HFMD and confirmed cases of MERS-CoV and SARS-CoV-2 were collected weekly from the KCDA’s National Notifiable Infectious Diseases database [13]. The implemented period of PHSM was defined based on the press release from public health authorities (Supplement).

The South Korean Meteorological Administration provided us with data for the rainy season (i.e., the monsoon), which was the period with heavy rains in the Korean peninsula, for 2014–2021 [15]. We also retrieved daily relative humidity and temperature data from 2014 to 2021 and calculated absolute humidity, which reflects the actual amount of water vapor in the air at a given temperature (Supplement). Then, we compared the models to develop a better fitting regression model for HFMD transmission (eTable 1 in the Supplement).

Impact of school holidays and 2015 PHSMs on the HFMD epidemics

To investigate the impact of 2015 PHSMs on the duration of the HFMD epidemic, we first identified the time of epidemic onset, which was defined by the baseline of the 50% of the non-zero HFMD cases for each year from 2014 to 2019, since an HFMD epidemic was not observed in 2020–2021 (during the COVID-19 pandemic period) [16]. We measured the epidemic duration, defined as the time between the onset and end of the epidemic, which is the retrospective ending on the same number of cases as its epidemic onset. Furthermore, we measured the epidemic peak’s timing and magnitude, and the epidemic size which was defined as the total number of cases during the epidemic’s duration each year. We also estimated the attack rate, defined as the number of cumulative cases divided by the population size.

Impact of school holidays and 2015 PHSMs on the HFMD transmissibility

We estimated the changes in HFMD transmissibility over time by using the effective reproduction number (${R}_{t}$) to assess the immediate effect of the 2014–2019 school holidays and 2015 PHSMs on HFMD transmission [17]. The mean number of secondary infections per primary case at time t is represented by ${R}_{t}$, and ${R}_{t}$ values < 1 indicate that the epidemic is under control. We first used the flexible cubic splines to interpolate the daily cases from weekly cases as reported in surveillance data [18]. We opted to utilize the branching process model to evaluate the daily ${R}_{t}$ considering the serial interval distribution [19, 20]. The serial interval, which is defined as the duration between the onset of symptoms in the primary and secondary cases, was assumed to follow a Weibull distribution, with a mean of 3.7 days and a standard deviation of 2.6 days [11]. We compared the mean ${R}_{t}$ for two weeks before and during the interventions (school holiday and 2015 PHSMs) in each season to evaluate the mean reduction in transmissibility by these interventions.

The overall impact of school holidays and 2015 PHSMs were evaluated by fitting a multivariable regression model for ${R}_{t}$, which accounted for the intrinsic factors such as the initial intensity of disease transmission (i.e., basic reproduction number, ${R}_{0}$) and the depletion of susceptible individuals in the population at time t is represented by ${S}_{t}$ along with other extrinsic drivers (school holidays and meteorological factors). In theory, we have the transmissibility under no interventions as:

$${R}_{t}={R}_{0}{S}_{t}$$

The transmissibility of HFMD (${R}_{t}$) is known to be affected by extrinsic factors such as humidity (${H}_{t}$), school holidays (${V}_{t}$), and 2015 PHSMs (${P}_{t}$) at time t.[6, 11] Therefore, we adjusted the factor of (${H}_{t}$), because the incidence of HFMD in South Korea is known to increase during low rainfall (low humidity) and then decrease with increasing rainfall (or rainy season). We set ${H}_{t}$, a dummy variable, to indicate one for the rainy season and zero for the non-rainy season because a bivariate variable for the rainy season yielded a better-fitted regression model for ${R}_{t}$ than a variable for absolute humidity (eTable in the Supplement). ${V}_{t}$ and ${P}_{t}$ are indicator variables that are set to one for implementation periods and zero for non-implementation periods for holidays. Therefore, ${R}_{t}$ can be expressed as:[11]

$${R}_{t}={R}_{0}{S}_{t}{e}^{{{\beta }_{H}{H}_{t}{+\beta }_{V}{V}_{t}+\beta }_{P}{P}_{t}}$$

where ${\beta }_{H}$, ${\beta }_{V}$, and ${\beta }_{P}$ are the parameters, indicating the effects of the rainy season, school holidays, and PHSMs, respectively.

We simplified the model further as [18]:

$${R}_{t}={R}_{0}{S}_{0}{e}^{{\alpha h}_{t}}{e}^{{{\beta }_{H}{H}_{t}+{\beta }_{V}{V}_{t}+ \beta }_{P}{P}_{t}}$$

where, ${S}_{0}$ is the fraction of the population that was susceptible at the start of the epidemic season, ${h}_{t}$ (i.e., ${\sum }_{x=1}^{t-1}{I}_{x}$, ${I}_{x}$ is the cases at time $x$) is a measure of the depletion of susceptible persons at time t. Taking the logarithms of both sides of Eq. (3), we get the following log-linear multivariable regression model.

$$ln\left({R}_{t}\right)={ ln}({R}_{0}{S}_{0})+\alpha {h}_{t}+{\beta }_{H}{H}_{t} + {\beta }_{V}{V}_{t}+ {\beta }_{P}{P}_{t}$$

where $\alpha$, ${\beta }_{H}$, ${\beta }_{V}$, and ${\beta }_{P}$ are regression coefficients for the depletion of susceptible individuals, rainy seasons, school holidays, and 2015 PHSMs, respectively.

Impact of school holidays and 2015 PHSMs on HFMD attack rate

We simulated the HFMD incidence using a susceptible-exposed-infectious-recovered (SEIR) deterministic transmission model under the counterfactual scenario of with and without school holidays and non-PHSMs and estimated the reduction in attack rate by the school holidays in 2014–2019 and the PHSMs in 2015. The standard SEIR model is presented as:

$$\frac{dS}{dt}=-{\beta }_{t}SI$$

$$\frac{dE}{dt}={\beta }_{t}SI - \sigma E$$

$$\frac{dI}{dt}=\sigma E- \gamma I$$

$$\frac{dR}{dt}=\gamma I$$

where $S$ is the proportion of susceptible individuals in a population, $t$ is time, ${\beta }_{t}$ is the transmission rate per infected individual, $I$ is the proportion of infected individual, $\sigma$ is the rate of becoming infectious, E is the proportion individual who have been exposed, and $\gamma$ is the rate of recovery ($\gamma$ = 1/average duration of infectiousness). We set the values of $\sigma$ to 0.57 because we assumed HFMD spread before the symptoms (3–6 days) [20], and we set the value of $\gamma$ to 0.50 because we assumed that most children with symptoms are generally immediately removed from childcare and school in South Korea [21, 22]. R is the proportion of recovered individuals. On the basis of the SEIR model above, we have ${R}_{t}={S}_{t}\times \frac{{\beta }_{t}}{\gamma }$. Using Eq. (3), we can rewrite ${\beta }_{t}$ = ${\beta }_{0}{e}^{{\beta }_{H}{H}_{t}+{{\beta }_{V}{P}_{t}+\beta }_{P}{P}_{t}}$, since ${\beta }_{0}=$ ${R}_{0}\gamma$ when ${S}_{0}\approx 1$. Then, using the multivariable log-linear regression model in Eq. (4), the regression coefficients can be estimated. We calculated the reduction in overall infections by comparing the counterfactual simulated incidence/attack rate between with and without summer school holidays and PHSMs (i.e., setting ${\beta }_{P}$ = 0 for the scenario without PHSMs).

Prediction of HFMD season after relaxation of COVID-19 PHSMs

We developed a simulation-based prediction model based on the SEIR model above to infer the upcoming HFMD epidemic after the relaxation of PHSMs [16, 18]. We assumed the Korean population’s herd immunity to HFMD would decrease significantly as the humoral immune response to HFMD remained stable for two years after infection [23] and the HFMD epidemic had no sustained circulation for more than two years in 2020–2022 [23, 24]. We used the mean value of the peak timing and epidemic duration during 2014–2019 to predict the 2023 HFMD season after the relaxation of PHSMs in December 2022.

All statistical analyses were performed in R version 4.0.1 (R Foundation for Statistical Computing).

Figures 1 and 2 show the weekly number of HFMD cases, estimated daily ${R}_{t}$, and absolute humidity and the rainy season during the study period, of which ${R}_{t}$ was not estimated in 2020 and 2021 due to no sustained transmission of HFMD in these two years.

The epidemic onset and peak timing for the HFMD epidemic in 2015 were identified on average 1.74 (range: 0.6 to 3.0) weeks leading and 6.6 (range: 3.9 to 8.2) weeks leading, respectively, in comparison with other usual years (2014 and 2016–2019) (eTable 2 in the Supplement). The average peak magnitude and attack rate for the 2015 season reduced by 1809 (range: 811 to 3380) cases and 1.4 (range: 0.4 to 3.0), respectively, while the duration of the 2015 epidemic was shortened up to 1–2 weeks comparatively.

In the two weeks prior to the summer school holidays, the mean ${R}_{t}$ was 1.01 (range: 0.93 to 1.08), while it dropped to 0.93 (range: 0.90 to 0.98) during the holidays and remained at 0.96 (range: 0.87 to 1.04) in the following weeks (Table 1), corresponding to an average of 7.65% (range: 0.28–14.57%) reduction in the ${R}_{t}$ during the summer school holidays. The school holidays were associated with a 4.57% (range: 1.83–6.53%) reduction in overall HFMD transmissibility in the regression analysis for R_t adjusted for the rainy season (eTable 2 in the Supplement). We estimated that 2015 PHSMs were associated with a 13.35% (95% confidence interval [CI], 9.95–16.76%) reduction in HFMD transmissibility (eTable 3 in the Supplement).

Table 1

Estimated daily reproductive number ${R}_{t}$ in South Korea during, 2 weeks before, and 2 weeks after summer school holiays in 2014–2019, and the associated reductions in${R}_{t}$
	Mean estimated ${R}_{t}$ (95% CI)			Reduction in ${R}_{t}$, school holidays vs. 2weeks before, % (95% CI)	Overall reduction in ${R}_{t}$ associated with the school holidays, % (95% CI)*
Year	During 2 weeks before the school holidays started	During the school holidays	During 2 weeks after the school holidays ended
2014	0.94 (0.90–0.98)	0.90 (0.84–0.95)	0.98 (0.91–1.06)	4.22 (2.54–5.9)	6.53 (5.37–7.69)
2015	0.99 (0.91–1.06)	0.98 (0.91–1.06)	1.04 (0.96–1.13)	0.28 (0.05–0.51)	1.83 (-0.58-4.23)
2016	0.93 (0.90–0.97)	0.91 (0.86–0.95)	0.87 (0.81–0.93)	2.75 (1.64–3.86)	2.67 (1.33–4.01)
2017	1.08 (1.03–1.12)	0.95 (0.90-1.00)	0.94 (0.89–0.99)	12.71 (12.55–12.87)	4.13 (2.25–6.01)
2018	1.07 (1.03–1.12)	0.93 (0.88–0.97)	0.95 (0.89–1.01)	14.57 (14.21–14.93)	6.01 (4.93–7.09)
2019	1.03 (1.00-1.05)	0.91 (0.88–0.94)	0.96 (0.92-1.00)	11.36 (10.87–11.84)	6.25 (3.49–9.01)
Note: The years 2020–2021 were not included since they did not show hand-foot-mouth-disease epidemics.
*Estimated from the regression model for ${R}_{t}$ adjusted to rainy season

For the impact of summer school holidays and PHSMs on HFMD attack rate, we found that it was reduced by an average 1.10% (range: 0.38–1.51%) during the epidemic period (Fig. 3, eTable 4 in the Supplement). The estimated reduction in infections was similar to that observed by sensitivity analysis for the simulation analysis with different levels of preexisting immunity (0.1–30%) and ${\text{R}}_{0}$ (2.5–4.5) (eTable 5 in the Supplement).

We predicted that the peak magnitude and duration of the upcoming HFMD epidemic in 2023 would be 4.8 (range: 2.5 to 8.5) and 1.1 (Range: 1.0 to 1.2) folds larger than the epidemics in the previous years from 2014 to 2019 (Fig. 4).

Changes in host susceptibility and extrinsic factors such as school holidays, PHSMs, and rainy seasons have been identified as driving factors for HFMD transmission in the community [9, 11]. However, after adjustment for the rainy season, the findings of our study showed that summer school holidays during an HFMD epidemic season had a minor impact on HFMD transmission.

School closure has been considered as one of the effective PHSMs to control epidemic and pandemic preparedness of infectious diseases in the community, because school-aged children have a higher contact rate and are more susceptible to infection than adults [25]. However, previous studies have shown that preschool children account for most cases of HFMD [26, 27], implying that a school closure for HFMD is alone not sufficient to restrict the infections. Another reason for the limited influence of school holidays in our study could be that the length of school holidays (around a month) was insufficient to significantly change the degree of overall transmissibility [11, 28]. Our finding is comparable to the results of previous studies on influenza showing that shorter school breaks of only two weeks were an effective measure for mitigating influenza transmission, which generally affects a broader range of ages [18, 29].

Because many HFMD cases present with respiratory symptoms, and the patients’ respiratory droplets can transmit HFMD [21], PHSMs for respiratory viruses can be considered as useful preventive measures to mitigate the HFMD epidemic. Our study showed that the PHSMs implemented for the prevention of the MERS-CoV epidemic and SARS-CoV-2 pandemic had a significant impact on HFMD transmission. The PHSMs that were implemented at the start of the HFMD epidemic in 2015 reduced the peak magnitude, attack rate of HFMD infections, and duration of the epidemic. Similarly, HFMD activity reduced to near-zero during the COVID-19 pandemic, since nationwide PHSMs for the pandemic were implemented before the HFMD epidemic (as of end of June, 2022, the weekly number of HFMD cases reported to the Korean sentinel surveillance site in 2022 was near-zero) [13].

When compared to absolute humidity, we observed that the rainy season improved our regression model for HFMD transmission (eTable 2 in the Supplement). Our study also showed that the rainy season has a positive effect on reduction of HFMD transmission (eTable 6 in the Supplement). This finding is similar with the findings of previous studies in which the rainy season was reported to have likely reduced outdoor activities and social mixing (i.e., rainy season offered a social-distancing benefit against the epidemic) [30, 31].

The 2015 HFMD epidemic was different to the findings for the 2020–2021 season. This difference in the HFMD epidemic size is most likely due to the different levels of PHSMs implemented in South Korea (i.e., PHSMs were not mandated in 2015). Because the 2015 MERS-CoV-2 outbreak in South Korea primarily occurred in hospitals, public health authorities focused on hospital infection control measures rather than community-based measures. As the number of MERS-CoV cases and people’s anxiety grew, public mass media began to advocate for voluntary PHSMs, such as improving personal hygiene and avoiding crowds. The Korean ministry of education also launched a student infectious disease control program on June 1, 2015, and implemented school-based measures such as frequent hand washing and sick leaves [32]. However, in accordance with the World Health Organization’s recommendations, the school-based measures were relaxed on June 10, 2015, since MERS-CoV transmission was not linked to schools [33]. We found that these school-based measures had no significant impact on HFMD transmission in 2015 (associated reduction rate, 1.83%; 95% CI, − 0.58–4.28%). We also found that relaxation of COVID-19 PHSMs could significantly increase the HFMD infection burden for the upcoming HFMD season. This finding is consistent with a prediction of the upcoming seasons for other infectious diseases including influenza and RSV, which found that the increased population susceptibility to these viruses during the COVID-19 pandemic increased the burden of the forthcoming season by up to 3–5 times in terms of the peak magnitude [24, 34].

Our study had some limitations. First, we did not include viral pathogen data for HFMD because laboratory-based surveillance using small sample sizes (< 500) began in 2017. However, the available laboratory-based surveillance data suggests that coxsackievirus A16 is a major HFMD pathogen in South Korea (95% in 2017 and 85% in 2018; data not available for the other years) [13]. Thus, in our simulation model, it was reasonable to set the ${R}_{0}$ to 2.7 [35]. Second, our results from the simulation analysis were influenced by variations in model parameters. However, in the sensitivity analysis, we found no significant difference in the levels of other parameters (eTable 5 in the Supplement). Third, in addition to PHSMs, a mandatory SARS-CoV-2 quarantine for international travelers was implemented in 2020–2022 to control one of the possible drivers of an infectious disease epidemic. Finally, we used syndromic data that could have been influenced by changes in healthcare-seeking behavior during the MERS-CoV and SAR-CoV-2 epidemics.

In conclusion, when nationwide PHSMs were implemented, HFMD transmissibility and attack rates decreased significantly, while school holidays showed limited effectiveness. Complete elimination of PHSMs would result in a larger burden of the HFMD epidemic in coming years than that in previous seasons.

COVID-19

Coronavirus disease 2019

SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2

MERS-CoV

Middle east respiratory syndrome coronavirus

PHSMs

Public health and social measures

HFMD

Hand-foot-mouth disease

KCDA

Korea Disease Control and Prevention Agency

Ethical Approval and consent to participate

Consent for publication

Not applicable.

Availability of data and materials
The data that support the findings of this study are available from the corresponding author, SR, upon reasonable request.

Competing interests
We declare that we have no conflicts of interest.

Funding

This work was supported by the Basic Science Research Program through the National Research Foundation of Korea by the Ministry of Education (grant number NRF-2020R1I1A3066471).

Author’s contribution
SR and STA conceived the study, designed the statistical methods. SR and CH did the data collection and assimilation. SR and CH did the data analysis. SR and CH wrote the first draft of the manuscript. STA, BY and SP critically reviewed and edited the manuscript. All authors contributed to the interpretation of the results, revision of the manuscript critically and have given final approval of the version to be published.

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Impact of public health and social measures on hand-foot-mouth disease transmission and prediction of upcoming season after relaxation of COVID-19 control measures

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Abstract

Background

Methods

Results

Conclusions

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Introduction

Methods

Data for analysis

Impact of school holidays and 2015 PHSMs on the HFMD epidemics

Impact of school holidays and 2015 PHSMs on the HFMD transmissibility

Impact of school holidays and 2015 PHSMs on HFMD attack rate

Prediction of HFMD season after relaxation of COVID-19 PHSMs

Results

Discussion

Conclusions

Abbreviations

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References

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