Effects of extreme meteorological factors and high air pollutant concentrations on the incidence of hand, foot and mouth disease in Jining, China

Introduction

Hand, foot, and mouth disease (HFMD) represents a highly contagious ailment primarily instigated by Coxsackievirus A16 (CV-A16) and Enterovirus 71 (EV-71) (Kimmis, Downing & Tyring, 2018). The primary mode of transmission is contact-based, with a predilection for affecting individuals under the age of five (World Health Organization (WHO), 2018). The majority of HFMD cases exhibit an incubation period ranging from 3 to 10 days, characterized by prominent symptoms such as fever and the development of vesicular lesions on the hands, feet, and oral mucosa (Gu, Li & Lu, 2020; Cox & Levent, 2018). While the overall prognosis for HFMD is generally favorable, it is noteworthy that the disease may elicit severe manifestations, including neurological symptoms, thereby imparting a substantial disease burden upon both individuals and society at large (Ooi et al., 2010; Huang et al., 1999).

In the past few decades, several epidemics and outbreaks of HFMD had occurred worldwide since the first report of HFMD in New Zealand in 1957 (Zhuang et al., 2015). Since the beginning of the 21st century, the proportion of severe cases of HFMD in the Asia-Pacific region has been unusually high and the epidemic has continued (Yi et al., 2020). The burden of HFMD in China is about 75,881 disability-adjusted life years per year, the largest proportion among many high-burden countries (Koh et al., 2018). From 2008 to the end of 2019, more than 22 million cases of HFMD were reported, resulting in 3,500 deaths. In 2021, it was listed as a category C infectious disease with the highest incidence in China (The Chinese Bureau for Disease Prevention and Control, 2020; National Health Commission of the People’s Republic of China, 2022).

In numerous epidemiological investigations, the close association between the survival and transmission of the HFMD pathogen and the surrounding environment has been consistently demonstrated (Tian et al., 2018; Zhong et al., 2018). In recent years, there has been a heightened focus on the impact of meteorological factors on infectious diseases. Previous research has presented compelling evidence regarding the correlation between HFMD incidence and meteorological factors. For instance, a study conducted in Minhang District, Shanghai, identified a positive correlation between HFMD and wind speed, coupled with a negative correlation with precipitation and sunshine hours (Qi et al., 2018). However, research exploring the relationship between HFMD incidence and weather extremes remains limited. Extreme weather events, typically occurring less frequently than 90 or 10 percent of the probability density function estimated from observations (Chen et al., 2020), have not been extensively investigated in the context of HFMD. A multi-city study in mainland China unveiled a non-linear relationship between temperature and HFMD, where high temperatures were recognized as a risk factor for the disease (Xiao et al., 2017). Low temperatures were found to exhibit a protective effect on HFMD in Shijiazhuang, while posing a risk in Wuhan (Liu et al., 2022; Hao et al., 2020). Furthermore, a study in Hefei identified low wind speed as a risk factor for HFMD development (Zhang et al., 2019), which contradicts the findings of a study in Guilin, where low wind speed was deemed a protective factor for HFMD development (Yu et al., 2018). Consequently, the results from various studies investigating the relationship between HFMD and meteorological factors exhibit significant heterogeneity, underscoring the imperative for additional research to comprehensively explore these intricate associations.

Compared to meteorological factors, the relationship between HFMD and air pollutants has been less well studied. Air pollution has been shown to have adverse effects on the respiratory and cardiovascular systems (Chen et al., 2020; Cheng et al., 2018). A study in Shanghai found that the higher the PM_2.5 concentration, the more years of human life lost (Ruan et al., 2020). Currently, there are few studies on air pollutants and HFMD and the findings vary widely. Qian et al. (2023) found that high concentrations of PM_2.5 can reduce the incidence of HFMD, but in Peng et al. (2022), high concentrations of PM_2.5 was risk factor for the incidence of HFMD. In addition, studies of the relationship between other high-level pollutants and HFMD vary widely. For example, a study in Hefei (Wei et al., 2019) found that high concentrations of SO₂ increased the risk of HFMD, while a study in Shijiazhuang (Liu et al., 2022) reached the opposite conclusion. A study in Ningbo (Huang et al., 2016) found that high concentrations of O₃ increased the risk factors for HFMD incidence. However, a study in Guilin (Yu et al., 2019) obtained that high concentrations of O₃ decreased HFMD incidence. Therefore, more research is needed to elucidate the relationship between high concentrations of air pollutants and HFMD.

In this study, we analyzed the relationship between the incidence of HFMD and different extreme meteorological conditions as well as varying concentrations of pollutants. The intention is to furnish a foundation for the proactive implementation of warning systems to prevent the onset and progression of HFMD.

Materials and Methods

Results

As shown in Table 1. The average number of HFMD cases per day was 12; the daily mean temperature, atmospheric pressure, humidity, and wind speed were 14.82 °C, 100.84 kPa, 67.30% and 2.29 m/s; the average concentrations of PM_2.5, PM₁₀, NO₂, SO₂, and O₃ were 50.77, 88.57, 32.62, 15.78 and 112.26 ug/m³.

As depicted in Fig. 1, the daily incidence of HFMD exhibits a distinct seasonal pattern, characterized by a prominent peak from May to August and a minor peak in October to November each year. There has been a declining trend observed annually since 2018. Both meteorological factors and air pollutants demonstrate evident seasonality and cyclical patterns.

Table 2 presents the correlation coefficents among different variables. The correlation between temperature and HFMD stands out as the most substantial among meteorological factors (r = 0.457). Among air pollutants, O₃ exhibits the highest correlation coefficient with HFMD (r = 0.248).

Figure 2 visualizes the exposure-lag-response relationships of meteorological factors and air pollutants with HFMD using three-dimensional plots. The cumulative effects of meteorological factors and air pollutants on the incidence of HFMD are shown in the Fig. 3. A nonlinear associations are found between temperature, wind speed, PM_2.5, SO₂, O₃, and the risk of HFMD. The effect of temperature on the risk of HFMD development was generally upward, with the RR reaching its maximum at about 34 °C (RR = 2.411, 95% CI [1.251–4.646]); the relationship of wind speed with HFMD development was a “J” shape, with the RR reaching its maximum at about 6.5 m/s (RR = 3.535, 95% CI [0.556–22.480]);. The exposure-response curves of PM_2.5 and HFMD were similar to a “W” shape, with the peak value occurring at a PM_2.5 concentration of 116 ug/m³ (RR = 1.921, 95% CI [1.131–3.262]). In addition, the risk of HFMD also showed an increasing trend with increasing SO₂ concentration, whereas an overall decreasing trend was presented with increasing O₃ concentration.

Figure 2 illustrates the exposure-lag-response relationships between meteorological factors, air pollutants, and HFMD through three-dimensional plots. The cumulative effects of these variables on HFMD incidence are depicted in Fig. 3. Nonlinear associations are evident between temperature, wind speed, PM_2.5, SO₂, O₃, and the risk of HFMD. The impact of temperature on HFMD risk displays an upward trend, reaching its peak at approximately 34 °C (RR = 2.411, 95% CI [1.251–4.646]). The relationship between wind speed and HFMD follows a “J” shape, with the RR peaking at around 6.5 m/s (RR = 3.535, 95% CI [0.556–22.480]). The exposure-response curves for PM_2.5 and HFMD exhibit a “W” shape, with the peak value occurring at a PM_2.5 concentration of 116 µg/m³ (RR = 1.921, 95% CI [1.131–3.262]). Furthermore, the risk of HFMD demonstrates an increasing trend with rising SO₂ concentration, while an overall decreasing trend is observed with increasing O₃ concentration.

The impact of extreme low temperatures peaked on lag day 1 and subsequently demonstrated a decreasing trend, reaching a minimum at lag day 4. Extreme high temperatures reached their maximum effect on lag day 0 and exhibited a minimum at lag day 1. The influence of extreme low temperature on HFMD manifested more rapidly than the impact of extreme high temperature, with a higher risk observed at the P₅th compared to the P₁₀th. Both extreme high and low wind speeds emerged as significant risk factors for HFMD. For high wind speeds, the critical period was between lag days 9–14 of the P₉₅th and lag days 11–14 of the P₉₀th, with the risk of development showing an increasing trend with the exacerbation of extreme wind speed. Detailed information can be found in Fig. 4.

High PM_2.5 concentrations exhibited a risk effect on the incidence of HFMD on days 1 and 2 of the lag, with a higher risk observed at the P₉₅th compared to the P₉₀th. High SO2 concentrations were identified as a primary risk factor for HFMD incidence, showing statistically significant effects at lag 1 day and lag 9–12 days. The risk of single-day incidence was higher at the P₉₅th SO2 concentration compared to the P₉₀th. Refer to Fig. 5 for a detailed representation.

Table 3 displays the RR for extreme high temperature and low wind speed at both the P₉₀th and P₉₅th. The P₉₅th RR values for high temperature and low wind speed were observed to be higher than the corresponding P₉₀th RR values. Cumulative effects of high temperature were maximized at lags of 0–10 days for both the P₉₀th and P₉₅th, with RR values of 1.787 (1.244–2.569) and 1.880 (1.261–2.804), respectively. Similarly, cumulative lagged effects of low wind speed increased with the number of lag days. The cumulative effect of low wind speed P₉₀th and P₉₅th was largest at 14 day lag with RR values of 1.498 (1.283–1.750) and 1.702 (1.389–2.085), respectively. Additionally, the cumulative hazardous effects of extreme high winds (P₉₅th) were statistically significant at 14 day lag. For high PM_2.5 concentration, statistically significant hazard effects on HFMD were observed from lag 0–3 days to lag 0–14 days. The maximum effect was observed at the P₉₀th at 14 day lag, with an RR value of 1.637 (1.069–2.506), and at the P₉₅th at lag 0–10 days, with an RR value of 1.569 (1.021–2.411). Furthermore, higher concentration of SO₂ (P₉₅th) exhibited a statistically significant RR value at 14 day lag, with an RR value of 1.425 (1.001–2.030).

Discussion

Our investigation revealed a significant annual peak in the incidence of HFMD in Jining City, with a pronounced surge observed from May to August and a secondary, peak occurring between October and November. Nonlinear associations were identified between HFMD and environmental variables including temperature, wind speed, PM_2.5, SO₂, and O₃.

Time series analysis revealed an approximately linear association between temperature and the incidence of HFMD, where the risk of incidence exhibited a positive correlation with temperature escalation. Consistent with prior research in Guangzhou and Japan, a linear relationship between temperature and HFMD was reported (Chen et al., 2014; Onozuka & Hashizume, 2011). However, recent investigations have indicated an inverted “V” or “J” shape in the temperature-HFMD relationship (Du et al., 2019; Dong et al., 2016; Yu et al., 2019). These divergent trends may be attributed to variations in climate characteristics and regional indicators across different geographical locations, encompassing factors such as healthcare infrastructure and economic conditions. Furthermore, discrepancies in model design, including lag days and covariables, also contribute to the observed differences (Yu et al., 2018). High and low temperature exhibit contrasting impact on HFMD. The deleterious effects of cold manifest more rapidly than those of hot, potentially attributable to a deterioration in personal hygiene behaviors during the winter season, thereby elevating the risk of infection. Additionally, the decrease in children’s immunity during winter accelerates the occurrence of the disease (Chiu et al., 2020; Lin et al., 2014). The typical incubation period for HFMD spans 3–7 days, during which elevated temperatures contribute to an increased disease incidence, with a higher risk observed at the P₉₅th compared to the P₉₀th. Within an optimal temperature range, high temperatures facilitate the replication and transmission of enterovirus (Fong & Lipp, 2005; Rajtar et al., 2008). The cumulative effect of high temperature on HFMD peaked at 14 days, which is consistent with the findings of Guilin (Yu et al., 2019). In contrast, Shijiazhuang reported a peak cumulative effect after 10 days, possibly attributed to lower temperatures in Shijiazhuang compared to Jining city, resulting in a relatively shorter duration of disease impact on the population (Liu et al., 2022).

Our investigation revealed a ‘J’-shaped dose-response relationship between wind speed and HFMD, indicating that both low and high wind speeds contribute to the promotion of HFMD occurrence. Consistent findings from studies in Malaysia and the Yili region support the significant impact of wind speed on HFMD incidence (Wahid, Suhaila & Rahman, 2021; Yi et al., 2021). Notably, we observed that the P₉₅th wind speed posed a greater risk than the P₉₀th. Parallel research in Hefei City indicated that low wind speed correlates with increased HFMD incidence (Zhang et al., 2019). This phenomenon may be attributed to heightened child activity during periods of low wind speed, leading to increased exposure to the HFMD virus. Our study demonstrated that the cumulative effect of high wind speed was statistically significant only on days 14 at the P₉₅th. While high wind speed facilitated the spread of the HFMD virus, the rapid dilution of virus content in droplets by high wind speed resulted in a hysteresis effect, diminishing the danger after the initial period (Liu et al., 2022). Contrary findings have been reported, as demonstrated by the Sichuan study, which wind speed showed no positive correlation with HFMD (Song et al., 2019). In a Guilin study, both high and low wind speeds were found to have a protective effect on HFMD (Yu et al., 2019). Conversely, a study in Guangzhou found no correlation between wind speed and HFMD (Huang et al., 2013). The observed disparities across studies may be attributed to geographical, social, and economic variations among different regions.

Limited research has explored the associations between particulate matter (PM) and HFMD, yielding varied results. Yin’s investigation identified PM₁₀ as a risk factor for HFMD, in contrast to He’s study, which reported a negative correlation between PM₁₀ concentration and HFMD (Yin et al., 2019; He et al., 2020). However, the Ningbo study found no correlation between PM₁₀ and HFMD (Huang et al., 2016). Our study results reveal that elevated PM_2.5 concentration poses a risk for HFMD. Specifically, at the P₉₀th PM2.5 concentration, the cumulative risk increases with lag days, reaching a maximum at a 14-day lag. However, at the P₉₅th pollutant concentration, the cumulative risk attained its maximum after a 10-day lag, demonstrating a subsequent decreasing trend. This observed trend may be attributed to exceptionally high pollutant concentrations, prompting corresponding governmental measures to safeguard public health, such as school closures and advisories for residents to stay indoors. Concurrently, individuals adopt self-protective measures, including increased water consumption to maintain respiratory tract moisture and the use of masks during going out, thereby reducing pollutant-related risks (Allen & Barn, 2020; Onishi, 2017). Peng’s study also identified high concentrations of both PM₁₀ and PM_2.5 as HFMD risk factors, suggesting that children may come into contact with HFMD viruses adhered to particulate matter, facilitating transmission through the fecal-oral route or close contact (Peng et al., 2022). Moreover, considering the respiratory tract as one of the transmission routes for HFMD, exposure to fine particulate matter heightens the body’s inflammatory response and exacerbates reactions to respiratory viral infections (Smith et al., 2006). The extensive surface area of PM2.5 and PM10 provides attachment sites for HFMD viruses, allowing them to enter the lungs and bloodstream through the respiratory system (Xiao et al., 2017; Lee et al., 2014). Additionally, airborne particulate matter may obstruct sunlight’s ultraviolet light, with sterilizing properties, thereby prolonging the survival time of viruses in the air (Huang et al., 2016; Shimasaki et al., 2016).

The exposure-response relationship SO2 concentration and HFMD exhibited a ‘J’-shaped pattern, aligning with findings in Ningbo (Gu, Li & Lu, 2020). The lagged effect of a single day at high concentrations was more often shown as a risk factor, and the P₉₅th was higher than the P₉₀th. A study in Shijiazhuang City reported no significant effect of high SO₂ concentration on HFMD (Liu et al., 2022). Conversely, elevated SO₂ concentrations were associated with increased HFMD incidence in a study in Hefei City, consistent with our findings (Wei et al., 2019). SO₂ is a major air pollutant primarily stemming from fossil fuel combustion in daily life and chemical industry activities (Lou et al., 2017), which has been linked to adverse health effects in children, including increased disease incidence such as eczema in studies conducted in the United States (Kathuria & Silverberg, 2016). Moreover, research suggests that SO₂ can impact the normal flora of the intestinal tract, potentially affecting children’s immunity (Beamish, Osornio-Vargas & Wine, 2011). Wigenstam’s study further revealed that SO₂, beyond its toxic impact on the respiratory system, serves as a risk factor for inflammation development, thereby heightening susceptibility to diseases in children (Wigenstam et al., 2016).

The dose-response relationship between O₃ and HFMD was observed to exhibit an ‘S’-shaped pattern, consistent with findings from a study conducted in Shijiazhuang (Liu et al., 2022). High concentrations of O₃ demonstrated no impact on the single-day onset of HFMD at the P₉₀th. However, it exerted a protective effect on the lagged 3rd and 4th days at the P₉₅th. Research conducted in Guilin similarly identified that elevated concentrations of O₃ conferred a protective effect against HFMD (Yu et al., 2019). However, a study in Ningbo found that O₃ was a risk factor for HFMD, which may be explained by the fact that the effect of temperature on HFMD was not controlled for in the Ningbo analysis (Huang et al., 2016). Furthermore, the higher temperature in Ningbo compared to Jining concurrently suggests that the effect of ozone on humans intensifies at elevated temperatures, as supported by previous studies (Li et al., 2022; Shi et al., 2020). O₃ exhibits not only bactericidal and antiviral characteristics but also facilitates wound healing, positioning O₃ therapy as a potential method for tissue repair (Lim et al., 2019). Animal experiments have revealed that exposure to ozone prolongs cell survival and stimulates the production of pertinent cytokines at optimal ozone concentrations, thereby restricting viral spread by inhibiting their propagation (Ching, Juan & Cheng, 2007).

Our research has several limitations. Firstly, our examination focused solely on HFMD incidence data in Jining City, potentially restricting the generalizability of our findings. Secondly, the study could not comprehensively account for all potential confounding factors, including geographic influences, host susceptibility, and preventive measures. Thirdly, the data collection relied on passive testing, possibly leading to an underestimation of the true number of HFMD cases. Lastly, our analysis primarily explored the impact of a single environmental factor variable on HFMD incidence. Future investigations should consider the effects of multiple environmental variables on infectious disease incidence, employing approaches such as the analysis of HFMD incidence through bioindices.

Conclusions

In conclusion, there were significantly lagged effects of temperature, wind speed, PM_2.5, SO₂ and O₃ on HFMD incidence. High temperature, low wind speed, high concentrations of PM_2.5 and SO₂ were associated with increased risk for HFMD. This study contributes to the understanding of the impacts of extreme meteorological conditions and elevated levels of air pollutants on HFMD, which provided a scientific basis for relevant authorities to implement targeted preventive measures under the contexts of extreme meteorological events and high air pollution levels. These findings have great significance for the establishment and improvement of an early warning system for HFMD, facilitating proactive interventions in public health.

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