Short-term exposure to sulfur dioxide and the risk of childhood hand, foot, and mouth disease during different seasons in Hefei, China

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

Background

The evidence on the effects of extreme meteorological conditions and high air pollution levels on incidence of hand, foot and mouth disease (HFMD) is limited. Moreover, results of the available studies are inconsistent. Further investigations are imperative to elucidate the specific issue.

Methods

Data on the daily cases of HFMD, meteorological factors and air pollution were obtained from 2017 to 2022 in Jining City. We employed distributed lag nonlinear model (DLNM) incorporated with Poisson regression to explore the impacts of extreme meteorological conditions and air pollution on HFMD incidence.

Results

We found that there were nonlinear relationships between temperature, wind speed, PM2.5, SO2, O3 and HFMD. The cumulative risk of extreme high temperature was higher at the 95th percentile (P95th) than at the 90th percentile(P90th), and the RR values for both reached their maximum at 10-day lag (P95th RR = 1.880 (1.261-2.804), P90th RR = 1.787 (1.244-2.569)), the hazardous effect of extreme low temperatures on HFMD is faster than that of extreme high temperatures. The cumulative effect of extreme low wind speeds reached its maximum at 14-day lag (P95th RR = 1.702 (1.389-2.085), P90th RR = 1.498(1.283-1.750)). The cumulative effect of PM2.5 concentration at the P90th was largest at 14-day lag (RR = 1.637 (1.069-2.506)), and the cumulative effect at the P95th was largest at 10-day lag (RR = 1.569 (1.021-2.411)). High SO2 concentration at the P95th at 14-day lag was associated with higher risk for HFMD (RR: 1.425 (1.001-2.030)).

Conclusion

Our findings suggest that high temperature, low wind speed, and high concentrations of PM2.5 and SO2 are associated with an increased risk of HFMD. This study not only adds insights to the understanding of the impact of extreme meteorological conditions and high levels of air pollutants on HFMD incidence but also holds practical significance for the development and enhancement of an early warning system for HFMD.

How multiple air pollutants affect hand, foot, and mouth disease incidence in children: assessing effect modification by geographical context in multicity of Sichuan, southwest China

BACKGROUND

Several studies have suggested a significant association of hand, foot, and mouth disease (HFMD) with ambient air pollutants. Existing studies have characterized the role of air pollutants on HFMD using only risk ratio measures while ignoring the attributable burden. And whether the geographical context (i.e., diverse topographic features) could modulate the relationships is unclear.

METHODS

Daily reported childhood HFMD counts, ambient air pollution, and meteorological data during 2015-2017 were collected for each of 21 cities in Sichuan Province. A multistage analysis was carried out in different populations based on geographical context to assess effect modification by topographic conditions. We first constructed a distributed lag nonlinear model (DLNM) for each city to describe the relationships with risk ratio measures. Then, we applied a multivariate meta-regression to estimate the pooled effects of multiple air pollutants on HFMD from the exposure and lagged dimensions. Finally, attributable risks measures were calculated to quantify HFMD burden by air pollution.

RESULTS

Based on 207554 HFMD cases in Sichuan Province, significant associations of HFMD with ambient air pollutants were observed mainly at relatively high exposure ranges. The effects of ambient air pollutants on HFMD are most pronounced on lag0 or around lag7, with relative risks gradually approaching the reference line thereafter. The attributable risks of O3 were much greater than those of other air pollutants, particularly in basin and mountain regions.

CONCLUSIONS

This study revealed significant pooled relationships between multiple air pollutants and HFMD incidence from both exposure and lag dimensions. However, the specific effects, including RRs and ARs, differ depending on the air pollution variable and geographical context. These findings provide local authorities with more evidence to determine key air pollutants and regions for devising and implementing targeted interventions.

Evaluation of models for multi-step forecasting of hand, foot and mouth disease using multi-input multi-output: A case study of Chengdu, China

BACKGROUND

Hand, foot and mouth disease (HFMD) is a public health concern that threatens the health of children. Accurately forecasting of HFMD cases multiple days ahead and early detection of peaks in the number of cases followed by timely response are essential for HFMD prevention and control. However, many studies mainly predict future one-day incidence, which reduces the flexibility of prevention and control.

METHODS

We collected the daily number of HFMD cases among children aged 0-14 years in Chengdu from 2011 to 2017, as well as meteorological and air pollutant data for the same period. The LSTM, Seq2Seq, Seq2Seq-Luong and Seq2Seq-Shih models were used to perform multi-step prediction of HFMD through multi-input multi-output. We evaluated the models in terms of overall prediction performance, the time delay and intensity of detection peaks.

RESULTS

From 2011 to 2017, HFMD in Chengdu showed seasonal trends that were consistent with temperature, air pressure, rainfall, relative humidity, and PM10. The Seq2Seq-Shih model achieved the best performance, with RMSE, sMAPE and PCC values of 13.943~22.192, 17.880~27.937, and 0.887~0.705 for the 2-day to 15-day predictions, respectively. Meanwhile, the Seq2Seq-Shih model is able to detect peaks in the next 15 days with a smaller time delay.

CONCLUSIONS

The deep learning Seq2Seq-Shih model achieves the best performance in overall and peak prediction, and is applicable to HFMD multi-step prediction based on environmental factors.

Dynamic modeling and data fitting of climatic and environmental factors and people's behavior factors on hand, foot, and mouth disease (HFMD) in Shanghai, China

Background

Hand, foot, and mouth disease (HFMD) appear to be a multi-wave outbreak with unknown mechanisms. We investigate the effects of climatic and environmental factors and changes in people's behavior factors that may be caused by external factors: temperature, relative humidity, and school opening and closing.

Methods

Distributed lag nonlinear model (DLNM) and dynamic model are used to research multi-wave outbreaks of HFMD. Climatic and environmental factors impact on transmission rate β ( t ) is modeled through DLNM and then substituted into this relationship to establish the dynamic model with reported case data to test for validity.

Results

Relative risk (RR) of HFMD infection increases with increasing temperature. The RR of infection first increases and then decreases with the increase of relative humidity. For the model fitting HFMD dynamic, time average basic reproduction number [ R 0 ] of Stage I (without vaccine) and Stage II (with EV71 vaccine) are 1.9362 and 1.5478, respectively. Temperature has the highest explanatory power, followed by school opening and closing, and relative humidity.

Conclusion

We obtain three conclusions about the prevention and control of HFMD. 1) According to the temperature, relative humidity and school start time, the outbreak peak of HFMD should be warned and targeted prevention and control measures should be taken. 2) Reduce high indoor temperature when more than 31.5 oC, and increase low relative humidity when less than 77.5% by opening the window for ventilation, adding houseplants, using air conditioners and humidifiers, reducing the incidence of HFMD and the number of infections. 3) The risk of HFMD transmission during winter vacations is higher than during summer vacations. It is necessary to strengthen the publicity of HFMD prevention knowledge before winter vacations and strengthen the disinfection control measures during winter vacations in children's hospitals, school classrooms, and other places where children gather to reduce the frequency of staff turnover during winter vacations.

Exploring the relationship between air quality and health shocks to the elderly: A retrospective cross-sectional study in China

Methods

We selected 5,172 microdata on individuals from the China Health and Retirement Longitudinal Study (CHARLS) 2018. The binary logit model, the ordered logit model, and the stepwise regression were employed to compare the effects of air pollution on self-rated health (SRH) and activities of daily living (ADL) in an elderly population. The effects on health shocks were explored in different age groups, different gender groups, different regions and different sources of pollutants, respectively.

Results

We found that air pollution significantly increased the risk of health shocks in the elderly population, especially in the 60–69 year age group, and the eastern/central region, where NO2 and O3 were important pollutant sources.

Conclusion

Targeted management of the environment is necessary to improve the health status of China's elderly population. In addition, paying attention to the health status of vulnerable populations is needed to achieve social equity.

Associations between ambient air pollutants and childhood hand, foot, and mouth disease in Sichuan, China: a spatiotemporal study

Hand, foot, and mouth disease (HFMD) is a major public health concern in the Asia-Pacific region. Previous studies have implied that ambient air pollution may affect the incidence of HFMD, but the results among different regions are inconsistent. We aimed to deepen the understanding of the associations between air pollutants and HFMD by conducting a multicity study. Daily data on childhood HFMD counts and meteorological and ambient air pollution (PM_2.5, PM₁₀, NO₂, CO, O₃, and SO₂) concentrations in 21 cities in Sichuan Province from 2015 to 2017 were collected. A spatiotemporal Bayesian hierarchical model framework was established, and then a distributed lag nonlinear models (DLNMs) was constructed to reveal exposure-lag-response relationships between air pollutants and HFMD while controlling for spatiotemporal effects. Furthermore, given the differences in the levels and seasonal trends of air pollutants between the basin region and plateau region, we explored whether these associations varied between different areas (basin and plateau). The associations between air pollutants and HFMD were nonlinear, with different lag responses. Low NO₂ concentrations and both low and high PM_2.5 and PM₁₀ concentrations were associated with a decreased risk of HFMD. No significant associations between CO, O₃, and SO₂ and HFMD were found. The associations between air pollutant concentrations and HFMD were different between the basin and plateau regions. Our study revealed associations between PM_2.5, PM₁₀, and NO₂ concentrations and HFMD, deepening the understanding of the relationships between air pollutants and HFMD. These findings provide evidence to support the formulation of relevant prevention measures and the establishment of an early warning system.

Interactive effects of meteorological factors and air pollutants on hand, foot, and mouth disease in Chengdu, China: a time-series study

OBJECTIVES

Hand, foot, and mouth disease (HFMD) is a viral infectious disease that poses a substantial threat in the Asia-Pacific region. It is widely reported that meteorological factors are associated with HFMD. However, the relationships between air pollutants and HFMD are still controversial. In addition, the interactive effects between meteorological factors and air pollutants on HFMD remain unknown. To fill this research gap, we conducted a time-series study.

DESIGN

A time-series study.

SETTING AND PARTICIPANTS

Daily cases of HFMD as well as meteorological and air pollution data were collected in Chengdu from 2011 to 2017. A total of 184 610 HFMD cases under the age of 15 were included in our study.

OUTCOME MEASURES

Distributed lag nonlinear models were used to investigate the relationships between HFMD and environmental factors, including mean temperature, relative humidity, SO₂, NO₂, and PM₁₀. Then, the relative excess risk due to interaction (RERI) and the proportion attributable to interaction were calculated to quantitatively evaluate the interactions between meteorological factors and air pollutants on HFMD. Bivariate response surface models were used to visually display the interactive effects.

RESULTS

The cumulative exposure-response curves of SO₂ and NO₂ were inverted 'V'-shaped and 'M'-shaped, respectively, and the risk of HFMD gradually decreased with increasing PM₁₀ concentrations. We found that there were synergistic interactions between mean temperature and SO₂, relative humidity and SO₂, as well as relative humidity and PM₁₀ on HFMD, with individual RERIs of 0.334 (95% CI 0.119 to 0.548), 0.428 (95% CI 0.214 to 0.642) and 0.501 (95% CI 0.262 to 0.741), respectively, indicating that the effects of SO₂ and PM₁₀ on HFMD were stronger under high temperature (>17.3°C) or high humidity (>80.0%) conditions.

CONCLUSIONS

There were interactive effects between meteorological factors and air pollutants on HFMD. Our findings could provide guidance for targeted and timely preventive and control measures for HFMD.

Modification effects of socioeconomic factors on associations between air pollutants and hand, foot, and mouth disease: A multicity time-series study based on heavily polluted areas in the basin area of Sichuan Province, China

BACKGROUND

Hand, foot, and mouth disease (HFMD) is a serious threat among children in China. Some studies have found that air pollution is associated with HFMD incidence, but the results showed heterogeneity. In this study, we aimed to explore the heterogeneity of associations between air pollutants and the number of HFMD cases and to identify significant socioeconomic effect modifiers.

METHODS

We collected daily surveillance data on HFMD cases in those aged less than 15 years, air pollution variables and meteorological variables from 2015 to 2017 in the basin area of Sichuan Province. We also collected socioeconomic indicator data. We conducted a two-stage multicity time-series analysis. In the first stage, we constructed a distributed lag nonlinear model (DLNM) to obtain cumulative exposure-response curves between each air pollutant and the numbers of HFMD cases for every city. In the second stage, we carried out a multivariable meta-regression to merge the estimations in the first stage and to identify significant socioeconomic effect modifiers.

RESULTS

We found that PM10, NO2 and O3 concentrations were associated with the number of HFMD cases. An inverted V-shaped association between PM10 and the number of HFMD cases was observed. The overall NO2-HFMD association was a hockey-stick shape. For the relationships of PM10, SO2, NO2, O3 and CO with HFMD counts, approximately 58.5%, 48.4%, 51.0%, 55.6% and 52.5% of the heterogeneity could be explained, respectively. The proportion of primary school students, population density, urbanization rate, number of licensed physicians and number of hospital beds explained part of the heterogeneity and modified the relationships.

CONCLUSION

Our study explored the heterogeneity of associations between air pollutants and HFMD counts. The proportion of primary school students, population density, urbanization rate, number of licensed physicians and number of hospital beds could modify the relationships. The results can serve as a reference for relevant public health decision making.

Effects of Meteorological Factors and Atmospheric Pollution on Hand, Foot, and Mouth Disease in Urumqi Region

Background

Hand, foot, and mouth disease (HFMD) is a febrile rash infection caused by enteroviruses, spreading mainly via the respiratory tract and close contact. In the past two decades, HFMD has been prevalent mainly in Asia, including China and South Korea, causing a huge disease burden and putting the lives and health of children at risk. Therefore, a further study of the factors influencing HFMD incidences has far-reaching implications. In existing studies, the environmental factors affecting such incidences are mainly divided into two categories: meteorological and air. Among these studies, the former are the majority of studies on HFMD. Some scholars have studied both factors at the same, but the number is not large and the findings are quite different.

Methods

We collect monthly cases of HFMD in children, meteorological factors and atmospheric pollution in Urumqi from 2014 to 2020. Trend plots are used to understand the approximate trends between meteorological factors, atmospheric pollution and the number of HFMD cases. The association between meteorological factors, atmospheric pollution and the incidence of HFMD in the Urumqi region of northwest China is then investigated using multiple regression models.

Results

A total of 16,168 cases in children are included in this study. According to trend plots, the incidence of HFMD shows a clear seasonal pattern, with O3 (ug/m3) and temperature (°C) showing approximately the same trend as the number of HFMD cases, while AQI, PM2.5 (ug/m3), PM10 (ug/m3) and NO2 (ug/m3) all show approximately opposite trends to the number of HFMD cases. Based on multiple regression results, O3 (P = 0.001) and average station pressure (P = 0.037) are significantly and negatively associated with HFMD incidences, while SO2 (P = 0.102), average dew point temperature (P = 0.072), hail (P = 0.077), and thunder (P = 0.14) have weak significant relationships with them.

Modified effects of air pollutants on the relationship between temperature variability and hand, foot, and mouth disease in Zibo City, China

Hand, foot, and mouth disease (HFMD) poses a great disease burden in China. However, there are few studies on the relationship between temperature variability (TV) and HFMD. Moreover, whether air pollutions have modified effects on this relationship is still unknown. Therefore, this study aims to explore the modified effects of air pollutants on TV-HFMD association in Zibo City, China. Daily data of HFMD cases, meteorological factors, and air pollutants from 2015 to 2019 were collected for Zibo City. TV was estimated by calculating standard deviation of minimum and maximum temperatures over the exposure days. We used generalized additive model to estimate the association between TV and HFMD. The modified effects of air pollutants were assessed by comparing the estimated TV-HFMD associations between different air stratums. We found that TV increased the risk of HFMD. The effect was strongest at TV03 (4 days of exposure), when the incidence of HFMD increased by 3.6% [95% CI: 1.3-5.9%] for every 1℃ increases in TV. Males, children aged 0-4 years, were more sensitive to TV. We found that sulfur dioxide (SO₂) enhanced TV's effects on all considered exposure days, while ozone (O₃) reduced TV's effects on some exposure days in whole concerned population. However, we did not detect significant effect modification by particulate matter less than 10 microns in aerodynamic diameter (PM₁₀). These findings are of significance in developing policies and public health practices to reduce the risks of HFMD by integrating changes in temperatures and air pollutants.

Relationship between meteorological factors, air pollutants and hand, foot and mouth disease from 2014 to 2020

Background

Meteorological factors and air pollutants have been reported to be associated with hand, foot, and mouth disease (HFMD) epidemics before the introduction of vaccine. However, there is limited evidence for studies with long-term dimensions.

Methods

We collected the daily HFMD counts, weather and air pollution data from 2014 to 2020 in Chengdu. Distributed lag non-linear models (DLNM) were used to assess the associations of meteorological factors and air pollutants on HFMD cases.

Results

From 2014–2020, high relative humidity and precipitation and extremely high and low levels of PM₁₀, O₃, SO₂ and CO increased the risk of HFMD. In pre-vaccination period, extreme high and low temperatures, PM₁₀ and NO₂, low precipitation and high concentrations of PM_2.5 and O₃ significantly increase the risk of HFMD; In post-vaccination period, high relative humidity and low level of CO can significantly increase the incidence of HFMD; During the period of COVID-19, only low temperature will significantly increase the risk of HFMD; Low concentration of air pollutants has the greatest impact on the 6–14 age group, while the high concentration of air pollutants has the greatest impact on the 0–1 age group.

Conclusions

Our study suggest that high relative humidity and precipitation and extremely high and low levels of PM₁₀, O₃, SO₂ and CO increased the risk of HFMD from 2014 to 2020. The results of this study provide a reference for local authorities to formulate intervention measures and establish an environment-based disease early warning system.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13365-9.

Effects of temperature and PM2.5 on the incidence of hand, foot, and mouth in a heavily polluted area, Shijiazhuang, China

The influence of weather and air pollution factors on hand, foot, and mouth disease (HFMD) has received widespread attention. However, most of the existing studies came from lightly polluted areas and the results were inconsistent. There was a lack of relevant evidence of heavily polluted areas. This study aims to quantify the relationship between weather factors and air pollution with HFMD in heavily polluted areas. We collected the daily number of hand, foot, and mouth disease in Shijiazhuang, China from 2014 to 2018, as well as meteorological and air pollutant data over the same period. The generalized linear model combined with the distributed lag model was used to study the effect of meteorological factors and air pollutants on the daily cases of HFMD and its hysteresis effect. We found that the dose-response relationship between temperature, PM_2.5, and the risk of hand-foot-mouth disease was non-linear. Both low temperature and high temperature increased the risk of hand-foot-mouth disease. The cumulative effect of high temperature reached the maximum at 0-10 lag days, and the cumulative effect of low temperature reached the maximum at 0-3 lag days. The concentration of PM_2.5 between 76 and 200 μg/m³ has a certain risk of the onset of hand, foot, and mouth disease, but the extreme PM_2.5 concentration has a certain protective effect. In addition, low humidity, low wind speed, and low-O₃ can increase the risk of HFMD. Risks of humidity and low concentration of O₃ increased as lag days extended. In conclusion, our study found that climate factors and air pollutants exert varying degrees of impact on HFMD. Our research provided the scientific basis for establishing an early warning system so that medical staff and parents can take corresponding measures to prevent HFMD.

Association between short-term exposure to ambient nitrogen dioxide and the risk of conjunctivitis in Hefei, China: A time-series analysis

BACKGROUND

Conjunctivitis, one of the most common ocular surface diseases, can be caused by many contributors. However, the important role of air pollution has been inadequately evaluated, particularly in countries with poor air quality. This study aims to explore the possible association of short-term ambient nitrogen dioxide (NO₂) exposure with the risk of outpatient visits for conjunctivitis.

METHODS

A total of 43,462 conjunctivitis patients from January 1, 2014 to December 31, 2018 were identified from the Department of Ophthalmology of The Second Affiliated Hospital of Anhui Medical University, Hefei, China. Such data were linked to the daily mean concentration of NO₂ at ten fixed air quality monitoring stations. A distributed lag nonlinear model (DLNM) combined with a quasi-Poisson generalized linear regression model was employed to assess the association between NO₂ exposure and the risk of outpatient visits for conjunctivitis. Stratified analyses were also performed on the basis of gender, age group and season.

RESULTS

The association of NO₂ exposure with the risk of outpatient visits for conjunctivitis was statistically significant. In the single-day lags (lag 0 to lag 11) analysis, the largest effect estimates were observed at lag 0. In the moving average exposure lags (lag 0-1 to lag 0-11) analysis, the cumulative effects were stronger than the single-day lag effects. The stratified analyses suggested that the effect of NO₂ exposure was more pronounced in females and patients aged 19-65 years and in the cold season.

CONCLUSIONS

This study confirms the evidence that short-term NO₂ exposure is associated with an increased risk of conjunctivitis outpatient visits. Our research encourages individuals to avoid outdoor activities on severe air pollution days and the government is obliged to adopt more stringent environmental policies to alleviate the effects of air pollution on human health, particularly for individuals at risk of developing conjunctivitis.

How to improve infectious disease prediction by integrating environmental data: an application of a novel ensemble analysis strategy to predict HFMD

This study proposed a novel ensemble analysis strategy to improve hand, foot and mouth disease (HFMD) prediction by integrating environmental data. The approach began by establishing a vector autoregressive model (VAR). Then, a dynamic Bayesian networks (DBN) model was used for variable selection of environmental factors. Finally, a VAR model with constraints (CVAR) was established for predicting the incidence of HFMD in Chengdu city from 2011 to 2017. DBN showed that temperature was related to HFMD at lags 1 and 2. Humidity, wind speed, sunshine, PM₁₀, SO₂ and NO₂ were related to HFMD at lag 2. Compared with the autoregressive integrated moving average model with external variables (ARIMAX), the CVAR model had a higher coefficient of determination (R², average difference: + 2.11%; t = 6.2051, P = 0.0003 < 0.05), a lower root mean-squared error (−24.88%; t = −5.2898, P = 0.0007 < 0.05) and a lower mean absolute percentage error (−16.69%; t = −4.3647, P = 0.0024 < 0.05). The accuracy of predicting the time-series shape was 88.16% for the CVAR model and 86.41% for ARIMAX. The CVAR model performed better in terms of variable selection, model interpretation and prediction. Therefore, it could be used by health authorities to identify potential HFMD outbreaks and develop disease control measures.

Effects of short-term ambient air pollution exposure on HPV infections: A five-year hospital-based study

Human papillomavirus (HPV) infections are common sexually-transmitted diseases among reproductive-aged women with increasing concern. Until now, there are no prior study about the association between HPV infections and ambient air pollution. This study aimed to explore the relationship between short-term exposure to ambient pollutants and daily outpatient visits for HPV infections in China. Data of daily outpatient visits for HPV infections were obtained from January 1, 2014 to December 31, 2018 (1826 days). Over-dispersed Poisson generalized additive models were applied by adjusting weather conditions and day of the week. We identified a total of 39,746 cases for HPV infections. A 10 μg/m³ increase of PM₁₀, PM_2.5, SO₂, and NO₂ or a 0.1 mg/m³ rise of CO in concurrent day (lag 0) concentrations was related to an elevation of 0.822% (95% Cl: 0.282%, 1.36%), 1.05% (95% Cl: 0.280%, 1.81%), 5.72% (95% Cl: 1.79%, 9.65%), 5.02% (95% Cl: 3.45%, 6.60%), and 2.40% (95% Cl: 1.43%, 3.37%) in daily outpatient-visits for HPV infections, respectively. The association was more significant in those women aged 41 or over. As for 10 μg/m³ increase of O₃, a -1.33% (95% Cl: -2.13%, -0.530%) change was observed on the lag 03 and such effects appeared to be more obvious in the aged 18-40 group. Our results provided the first evidence that short-term exposure to ambient pollutants was related to, which may be indirectly, the increased risk of HPV infections while O₃ may act as a "protective" factor.

Associations between ambient air pollution and daily incidence of pediatric hand, foot and mouth disease in Ningbo, 2014-2016: a distributed lag nonlinear model

Hand, foot and mouth disease (HFMD) has high prevalence around the world, with serious consequences for children. Due to the long survival period of HFMD virus in ambient air, air pollutants may play a critical role in HFMD epidemics. We collected data on daily cases of HFMD among children aged 0–14 years in Ningbo City between 2014 and 2016. Distributed lag nonlinear models were used to assess the effects of particulate matter (PM_2.5), sulphur dioxide (SO₂), nitrogen dioxide (NO₂) and ozone (O₃) on the daily incidence of HFMD among children, with analyses stratified by gender and age. Compared with moderate levels of air pollution, high SO₂ levels had a relative risk (RR) of 2.32 (95% CI 1.42–3.79) and high NO₂ levels had a RR of 2.01 (95% CI 1.22–3.31). The RR of O₃ was 2.12 (95% CI 1.47–3.05) and that of PM_2.5 was 0.77 (95% CI 0.64–0.92) at moderate levels of air pollution. Specifically, high levels of SO₂ and NO₂ had RRs of 2.39 (95% CI 1.44–3.96) and 2.02 (95% CI 1.21–3.39), respectively, among 0–4-year-old children, while high O₃ had an RR of 2.31 (95% CI 1.09–4.89) among 5–14-year-old children. Our findings suggest significant associations of high SO₂ and NO₂ levels and moderate O₃ levels in HFMD epidemics, and also indicate that air pollution causes lagged effects on HFMD epidemics. Our study provides practical and useful data for targeted prevention and control of HMFD based on environmental evidence.

Using a Bayesian spatiotemporal model to identify the influencing factors and high-risk areas of hand, foot and mouth disease (HFMD) in Shenzhen

BACKGROUND

The epidemic of hand, foot, and mouth disease (HFMD) has become a severe public health problem in the world and has also brought a high economic and health burden. Furthermore, the prevalence of HFMD varies significantly among different locations. However, there have been few investigations of the effects of socioeconomic factors and air pollution factors on the incidence of HFMD.

METHODS

This study collected data on HFMD in Shenzhen, China, from 2012 to 2015. We selected eleven factors as potential risk factors for HFMD. A Bayesian spatiotemporal model was used to quantify the influence of the factors on HFMD and to identify the relative risks in different districts.

RESULTS

The risk factors of HFMD were the population, population density, concentration of SO2, and concentration of NO2. The relative risks (RRs) were 1.00473 (95% CI: 1.00059-1.00761), 1.00010 (95% CI: 1.00002-1.00016), 1.00215 (95% CI: 1.00170-1.00232) and 1.00058 (95% CI: 1.00028-1.00078), respectively. The protective factors against HFMD were the per capita GDP, the number of public kindergartens, the concentration of PM10, and the concentration of O3. The RRs were 0.98840 (95% CI: 0.98660-0.99026), 0.97686 (95% CI: 0.96946-0.98403), 0.99108 (95% CI: 0.98551-0.99840) and 0.99587 (95% CI: 0.99534-0.99610), respectively. The risk of incidence in Longgang district and Pingshan district decreased, while the risk of incidence in Baoan district increased.

CONCLUSIONS

Studies have confirmed that socioeconomic factors and air pollution factors have an impact on the incidence of HFMD in Shenzhen, China. The results will be of great practical significance to local authorities, which is conducive to accurate prevention and can be used to formulate HFMD early warning systems.

Effects of extreme meteorological factors on daily mumps cases in Hefei, China, during 2011-2016

Mumps remains one of the worldwide major health problems over the past decade. Seasonal variations of mumps indicate that meteorological factors play an important role in the development of mumps, but few studies have investigated the relationship between extreme meteorological factors and the incidence of mumps. Daily mumps cases and meteorological factors in Hefei, China, from 2011 to 2016 were obtained. A generalized additive model combined with the distributed lag nonlinear model (DLNM) was used to quantify the risk of extreme meteorological factors on mumps incidence. Nonlinear relationships were observed among all meteorological factors and mumps incidence. We found that extremely low and high temperatures increased the risk of mumps. The relative risks (RRs) of the cumulative effects along 30 lag days were 2.02 (95%CI: 1.14-3.56) and 2.42 (95%CI: 1.37-4.24), respectively. Both short and long sunshine duration had negative correlation on mumps, with cumulative RRs of 0.64 (95%CI: 0.46-0.92) and 0.57 (95%CI: 0.44-0.74), respectively. In the subgroup analysis, males were found to be more sensitive to extreme weather, especially extreme temperatures and sunshine duration. This study suggests that extreme meteorological factors, especially extreme temperatures and sunshine duration, exert a significant impact on the incidence of mumps. When formulating and implementing effective strategies to the prevention and control of mumps, authorities should take the effect caused by extreme meteorological factors into consideration and pay more attention to susceptible populations, such as male children and teenagers.

Impact of Ambient Temperature and Relative Humidity on the Incidence of Hand-Foot-Mouth Disease in Wuhan, China

Background: Few studies have previously explored the relationship between hand, foot, and mouth disease (HFMD) and meteorological factors with the effect modification of air pollution, and these studies had inconsistent findings. We therefore applied a time-series analysis assessing the effects of temperature and humidity on the incidence of HFMD in Wuhan, China to deepen our understanding of the relationship between meteorological factors and the risk of HFMD. Methods: Daily HFMD cases were retrieved from Hubei Provincial Center for Disease Control and Prevention from 1 February 2013 to 31 January 2017. Daily meteorological data including 24 h average temperature, relative humidity, wind velocity, and atmospheric pressure were obtained from Hubei Meteorological Bureau. Data on Air pollution was collected from 10 national air-monitoring stations in Wuhan city. We adopted a distributed lag non-linear model (DLNM) combined with Poisson regression and time-series analysis to estimate the effects of temperature and relative humidity on the incidence HFMD. Results: We found that the association between temperature and HFMD incidence was non-linear, exhibiting an approximate "M" shape with two peaks occurring at 2.3 °C (RR = 1.760, 95% CI: 1.218-2.542) and 27.9 °C (RR = 1.945, 95% CI: 1.570-2.408), respectively. We observed an inverted "V" shape between relative humidity and HFMD. The risk of HFMD reached a maximum value at a relative humidity of 89.2% (RR = 1.553, 95% CI: 1.322-1.824). The largest delayed cumulative effects occurred at lag 6 for temperature and lag 13 for relative humidity. Conclusions: The non-linear relationship between meteorological factors and the incidence of HFMD on different lag days could be used in the early targeted warning system of infectious diseases, reducing the possible outbreaks and burdens of HFMD among sensitive populations.

Impact of Ambient Temperature and Relative Humidity on the Incidence of Hand-Foot-Mouth Disease in Wuhan, China

Background: Few studies have previously explored the relationship between hand, foot, and mouth disease (HFMD) and meteorological factors with the effect modification of air pollution, and these studies had inconsistent findings. We therefore applied a time-series analysis assessing the effects of temperature and humidity on the incidence of HFMD in Wuhan, China to deepen our understanding of the relationship between meteorological factors and the risk of HFMD. Methods: Daily HFMD cases were retrieved from Hubei Provincial Center for Disease Control and Prevention from 1 February 2013 to 31 January 2017. Daily meteorological data including 24 h average temperature, relative humidity, wind velocity, and atmospheric pressure were obtained from Hubei Meteorological Bureau. Data on Air pollution was collected from 10 national air-monitoring stations in Wuhan city. We adopted a distributed lag non-linear model (DLNM) combined with Poisson regression and time-series analysis to estimate the effects of temperature and relative humidity on the incidence HFMD. Results: We found that the association between temperature and HFMD incidence was non-linear, exhibiting an approximate "M" shape with two peaks occurring at 2.3 °C (RR = 1.760, 95% CI: 1.218-2.542) and 27.9 °C (RR = 1.945, 95% CI: 1.570-2.408), respectively. We observed an inverted "V" shape between relative humidity and HFMD. The risk of HFMD reached a maximum value at a relative humidity of 89.2% (RR = 1.553, 95% CI: 1.322-1.824). The largest delayed cumulative effects occurred at lag 6 for temperature and lag 13 for relative humidity. Conclusions: The non-linear relationship between meteorological factors and the incidence of HFMD on different lag days could be used in the early targeted warning system of infectious diseases, reducing the possible outbreaks and burdens of HFMD among sensitive populations.

Epidemiological and time series analysis of haemorrhagic fever with renal syndrome from 2004 to 2017 in Shandong Province, China

Shandong Province is an area of China with a high incidence of haemorrhagic fever with renal syndrome (HFRS); however, the general epidemic trend of HFRS in Shandong remains unclear. Therefore, we established a mathematical model to predict the incidence trend of HFRS and used Joinpoint regression analysis, a generalised additive model (GAM), and other methods to evaluate the data. Incidence data from the first half of 2018 were included in a range predicted by a modified sum autoregressive integrated moving average-support vector machine (ARIMA-SVM) combination model. The highest incidence of HFRS occurred in October and November, and the annual mortality rate decreased by 7.3% (p < 0.05) from 2004 to 2017. In cold months, the incidence of HFRS increased by 4%, −1%, and 0.8% for every unit increase in temperature, relative humidity, and rainfall, respectively; in warm months, this incidence changed by 2%, −3%, and 0% respectively. Overall, HFRS incidence and mortality in Shandong showed a downward trend over the past 10 years. In both cold and warm months, the effects of temperature, relative humidity, and rainfall on HFRS incidence varied. A modified ARIMA-SVM combination model could effectively predict the occurrence of HFRS.