The Association between Ambient Temperature and Childhood Hand, Foot, and Mouth Disease in Chengdu, China: A Distributed Lag Non-linear Analysis

Association between ambient temperature and risk of notifiable infectious diseases in China from 2011 to 2019

Previous studies on temperature and infectious diseases primarily focused on individual disease types, yielding inconsistent conclusions. This study collected monthly data on notifiable infectious disease cases and meteorological variables across 7 provinces in China from 2011 to 2019. A distributed lag nonlinear model was used to evaluate the association between ambient temperature and infectious diseases within each province, and random meta-analysis was applied to evaluate the pooled effect. Extreme hot temperature (the 97.5th percentile) was positively associated with the risk of respiratory infectious diseases with the relative risk (RR) of 1.45 (95%CI: 1.01-2.08). Conversely, extreme cold temperature (the 2.5th percentile) was negatively associated with intestinal infectious diseases and zoonotic diseases and vector-borne diseases, reporting RRs of 0.43 (95%CI: 0.30-0.60) and 0.46 (95%CI: 0.38-0.57), respectively. This study described the nonlinear association between ambient temperature and infectious diseases with different transmission routes, informing comprehensive prevention and control strategies for temperature-related infectious diseases.

Short-Term Effects of Extreme Meteorological Factors on Hand, Foot, and Mouth Disease Infection During 2010-2017 in Jiangsu, China: A Distributed Lag Non-Linear Analysis

Hand, Foot, and Mouth Disease (HFMD) is an infectious disease that primarily affects young children. In densely populated Jiangsu Province in China, the impact of extreme meteorological factors on HFMD is a concern. We aimed to examine the association between extreme meteorological variables and HFMD infection risk using daily HFMD infections and meteorological data from 2010 to 2017 in Jiangsu Province. We used distributed lag non-linear model (DLNM) to analyze the data, which can effectively capture the nuanced non-linear dynamics and lag effects in the relationship between HFMD and extreme meteorological factors. Comparing the 10th and 90th percentiles of meteorological variables with their respective median values, our results showed that extremely low temperatures and high humidity were significantly associated with increased HFMD infection risk. The greatest effect of extremely low temperatures was observed at a lag of 1-2 days, elevating the risk by 18 ∼ 33% (RR = 1.18 ∼ 1.33). Extremely high humidity was found to increase the risk of infection, starting at a lag of 4 days. In contrast, extremely high temperatures, low humidity, and high wind speed were associated with reduced risk of infection at lag of 0-12 days, with the range of RR values being 0.60-0.98 for extremely high temperatures, 0.69-0.89 for extremely low humidity, and 0.84-0.98 for extremely high wind speed respectively. Our findings suggest that extreme meteorological factors can significantly impact the incidence of HFMD in Jiangsu Province, and highlight the need for effective public health protection measures during the periods of extreme meteorological condition, particularly for vulnerable populations.

Protocol of an individual participant data meta-analysis to quantify the impact of high ambient temperatures on maternal and child health in Africa (HE2AT IPD)

INTRODUCTION

Globally, recognition is growing of the harmful impacts of high ambient temperatures (heat) on health in pregnant women and children. There remain, however, major evidence gaps on the extent to which heat increases the risks for adverse health outcomes, and how this varies between settings. Evidence gaps are especially large in Africa. We will conduct an individual participant data (IPD) meta-analysis to quantify the impacts of heat on maternal and child health in sub-Saharan Africa. A detailed understanding and quantification of linkages between heat, and maternal and child health is essential for developing solutions to this critical research and policy area.

METHODS AND ANALYSIS

We will use IPD from existing, large, longitudinal trial and cohort studies, on pregnant women and children from sub-Saharan Africa. We will systematically identify eligible studies through a mapping review, searching data repositories, and suggestions from experts. IPD will be acquired from data repositories, or through collaboration with data providers. Existing satellite imagery, climate reanalysis data, and station-based weather observations will be used to quantify weather and environmental exposures. IPD will be recoded and harmonised before being linked with climate, environmental, and socioeconomic data by location and time. Adopting a one-stage and two-stage meta-analysis method, analytical models such as time-to-event analysis, generalised additive models, and machine learning approaches will be employed to quantify associations between exposure to heat and adverse maternal and child health outcomes.

ETHICS AND DISSEMINATION

The study has been approved by ethics committees. There is minimal risk to study participants. Participant privacy is protected through the anonymisation of data for analysis, secure data transfer and restricted access. Findings will be disseminated through conferences, journal publications, related policy and research fora, and data may be shared in accordance with data sharing policies of the National Institutes of Health.

PROSPERO REGISTRATION NUMBER

CRD42022346068.

Association between temperature and mortality: a multi-city time series study in Sichuan Basin, southwest China

BACKGROUND

There are few multi-city studies on the association between temperature and mortality in basin climates. This study was based on the Sichuan Basin in southwest China to assess the association of basin temperature with non-accidental mortality in the population and with the temperature-related mortality burden.

METHODS

Daily mortality data, meteorological and air pollution data were collected for four cities in the Sichuan Basin of southwest China. We used a two-stage time-series analysis to quantify the association between temperature and non-accidental mortality in each city, and a multivariate meta-analysis was performed to obtain the overall cumulative risk. The attributable fractions (AFs) were calculated to access the mortality burden attributable to non-optimal temperature. Additionally, we performed a stratified analyses by gender, age group, education level, and marital status.

RESULTS

A total of 751,930 non-accidental deaths were collected in our study. Overall, 10.16% of non-accidental deaths could be attributed to non-optimal temperatures. A majority of temperature-related non-accidental deaths were caused by low temperature, accounting for 9.10% (95% eCI: 5.50%, 12.19%), and heat effects accounted for only 1.06% (95% eCI: 0.76%, 1.33%). The mortality burden attributable to non-optimal temperatures was higher among those under 65 years old, females, those with a low education level, and those with an alternative marriage status.

CONCLUSIONS

Our study suggested that a significant association between non-optimal temperature and non-accidental mortality. Those under 65 years old, females, and those with a low educational level or alternative marriage status had the highest attributable burden.

Non-linear association between daily mean temperature and children's hand foot and mouth disease in Chongqing, China

Chongqing was seriously affected by hand, foot, and mouth disease (HFMD), but the relationships between daily mean temperature and the incidence of HFMD remain unclear. This study used distributed lag nonlinear model to evaluate the effect of daily mean temperature on the incidence of HFMD in children aged < 5 years in Chongqing. Daily HFMD data from 2012 to 2019 in Chongqing were retrieved from the notifiable infectious disease surveillance system. A total of 413,476 HFMD cases aged < 5 years were reported in Chongqing from 2012 to 2019. The exposure-response curve of daily mean temperature and daily HFMD cases was wavy-shaped. The relative risks (RRs) increased as daily mean temperature below 5.66 °C or above 9.43 °C, with two peaks at 16.10 °C and 26.68 °C. The RRs reached the highest when the daily mean temperature at 26.68 °C on the current day (RR = 1.20, 95% CI 1.09-1.32), followed by the daily mean temperature at 16.10 °C at lag 5 days (RR = 1.07, 95% CI 1.05-1.08). The RRs for girls and daycare children were much higher than those for boys and scattered children, respectively. Taken together, daily mean temperature has strong effect on HFMD in children aged < 5 years old in Chongqing, particularly for girls and daycare children.

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.

The Effect of High and Low Ambient Temperature on Infant Health: A Systematic Review

Children, and particularly infants, have physiological, anatomic, and social factors that increase vulnerability to temperature extremes. We performed a systematic review to explore the association between acute adverse infant outcomes (children 0-1 years) and exposure to high and low ambient temperatures. MEDLINE (Pubmed), Embase, CINAHL Plus, and Global Health were searched alongside the reference lists of key papers. We included published journal papers in English that assessed adverse infant outcomes related to short-term weather-related temperature exposure. Twenty-six studies met our inclusion criteria. Outcomes assessed included: infant mortality (n = 9), sudden infant death syndrome (n = 5), hospital visits or admissions (n = 5), infectious disease outcomes (n = 5), and neonatal conditions such as jaundice (n = 2). Higher temperatures were associated with increased risk of acute infant mortality, hospital admissions, and hand, foot, and mouth disease. Several studies identified low temperature impacts on infant mortality and episodes of respiratory disease. Findings on temperature risks for sudden infant death syndrome were inconsistent. Only five studies were conducted in low- or middle-income countries, and evidence on subpopulations and temperature-sensitive infectious diseases was limited. Public health measures are required to reduce the impacts of heat and cold on infant health.

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 ambient temperature and atopic dermatitis in Lanzhou, China: a time series analysis

Many studies have explored the association between temperature and atopic dermatitis (AD); however, the results are inconsistent. We used a quasi-Poisson function fitted to a distributed lag nonlinear model (DLNM) to evaluate the association between daily average temperature and AD outpatient visits from January 1, 2013, to December 31, 2019, in Lanzhou, China. We found that the exposure-response association curve was inversely "s-shaped," low-temperature effects occurred at a lag of 11 days and then lasted for 10 days, and high-temperature effects occurred on the current day and then significantly decreased. Both low and high ambient temperatures can increase the risk of outpatient visits. Compared with median temperature (12.89°C), the cumulative relative risk (RR) of extreme high temperature and moderate-high temperature were 1.847 (95% confidence interval [CI]: 1.613, 2.114) and 1.447 (95% CI: 1.298, 1.614), respectively, at lag0-7 days, and the cumulative RRs of extremely low temperature and moderate-low temperature were 1.004 (95% CI: 0.904, 1.115) and 1.056 (95% CI: 0.925, 1.205), respectively, at lag0-21 days. Females were more sensitive to high temperatures than males, and high or low temperatures had significant effects on children ≤14 years of age. Graphical abstract.

Spatial and Temporal Characteristics of Hand-Foot-and-Mouth Disease and Their Influencing Factors in Urumqi, China

Hand, foot, and mouth disease (HFMD) remains a serious health threat to young children. Urumqi is one of the most severely affected cities in northwestern China. This study aims to identify the spatiotemporal distribution characteristics of HFMD, and explore the relationships between driving factors and HFMD in Urumqi, Xinjiang.

METHODS

HFMD surveillance data from 2014 to 2018 were obtained from the China Center for Disease Control and Prevention. The center of gravity and geographical detector model were used to analyze the spatiotemporal distribution characteristics of HFMD and identify the association between these characteristics and socioeconomic and meteorological factors.

RESULTS

A total of 10,725 HFMD cases were reported in Urumqi during the study period. Spatially, the morbidity number of HFMD differed regionally and the density was higher in urban districts than in rural districts. Overall, the development of HFMD in Urumqi expanded toward the southeast. Temporally, we observed that the risk of HFMD peaked from June to July. Furthermore, socioeconomic and meteorological factors, including population density, road density, GDP, temperature and precipitation were significantly associated with the occurrence of HFMD.

CONCLUSIONS

HFMD cases occurred in spatiotemporal clusters. Our findings showed strong associations between HFMD and socioeconomic and meteorological factors. We comprehensively considered the spatiotemporal distribution characteristics and influencing factors of HFMD, and proposed some intervention strategies that may assist in predicting the morbidity number of HFMD.

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.

The temporal characteristics of the lag-response relationship and related key time points between ambient temperature and hand, foot and mouth disease: A multicity study from mainland China

BACKGROUND

Previous studies have thoroughly elucidated the exposure-response relationship between ambient temperature and hand, foot, and mouth disease (HFMD), whereas very little concern has been to the lag-response relationship and related key time points.

OBJECTIVES

We aimed to clarify the temporal characteristics of the lag-response relationship between ambient temperature and HFMD and how they may vary spatially.

METHODS

We retrieved the daily time series of meteorological variables and HFMD counts for 143 cities in mainland China between 2009 and 2014. We estimated the city-specific lag-response curve between ambient temperature and HFMD and related key time points by applying common distributed lag nonlinear models (DLNM) and Monte Carlo simulation methods. Then, we pooled the city-specific estimates by performing a meta-regression with the city-specific characteristics as meta-predictors to explain the potential spatial heterogeneity.

RESULTS

We found a robust lag pattern between temperature and HFMD for different levels of temperatures. The temporal change of risk obtained its maximum value on the current day but dropped sharply thereafter and then rebounded to a secondary peak, which implied the presence of a harvesting effect. By contrast, the estimation of key time points showed substantial heterogeneity, especially at high temperature (the I² statistics ranged from 47% to 80%). With one unit increase in the geographic index, the secondary peak would arrive 0.37 (0.02, 0.71) days later. With one unit increase in the economic index and climatic index, the duration time of the lag-response curve would be lengthened by 0.36 (0.1, 0.62) and 0.92 (0.54, 1.29) days, respectively.

CONCLUSION

Our study examined the lag pattern and spatial heterogeneity of the lag-response relationship between temperature and HFMD. Those findings gave us new insights into the complex association and the related mechanisms between weather and HFMD and important information for weather-based disease early warning systems.

A review of the impact of outdoor and indoor environmental factors on human health in China

The Intergovernmental Panel on Climate Change (IPCC) reported that global climate change has led to the increased occurrence of extreme weather events. In the context of global climate change, more evidence indicates that abnormal meteorological conditions could increase the risk of epidemiological mortality and morbidity. In this study, using a systematic review, we evaluated a total of 175 studies (including 158 studies on outdoor environment and 17 studies on indoor environment) to summarize the impact of outdoor and indoor environment on human health in China using the database of PubMed, Web of Science, the Cochrane Library, and Embase. In particular, we focused on studies about cardiovascular and respiratory mortality and morbidity, the prevalence of digestive system diseases, infectious diseases, and preterm birth. Most of the studies we reviewed were conducted in three of the metropolises of China, including Beijing, Guangzhou, and Shanghai. For the outdoor environment, we summarized the effects of climate change-related phenomena on health, including ambient air temperature, diurnal temperature range (DTR), temperature extremes, and so on. Studies on the associations between temperature and human health accounted for 79.7% of the total studies reviewed. We also screened out 19 articles to explore the effect of air temperature on cardiovascular diseases in different cities in the final meta-analysis. Besides, modern lifestyle involves a large amount of time spent indoors; therefore, indoor environment also plays an important role in human health. Nevertheless, studies on the impact of indoor environment on human health are rarely reported in China. According to the limited reports, adverse indoor environment could impose a high health risk on children.

Association of Short-Term Exposure to Meteorological Factors and Risk of Hand, Foot, and Mouth Disease: A Systematic Review and Meta-Analysis

(1) Background: Inconsistencies were observed in studies on the relationship between short-term exposure to meteorological factors and the risk of hand, foot, and mouth disease (HFMD). This systematic review and meta-analysis was aimed to assess the overall effects of meteorological factors on the incidence of HFMD to help clarify these inconsistencies and serve as a piece of evidence for policy makers to determine relevant risk factors. (2) Methods: Articles published as of 24 October 2020, were searched in the four databases, namely, PubMed, Web of Science, Embase, and MEDLINE. We applied a meta-analysis to assess the impact of ambient temperature, relative humidity, rainfall, wind speed, and sunshine duration on the incidence of HFMD. We conducted subgroup analyses by exposure metrics, exposure time resolution, regional climate, national income level, gender, and age as a way to seek the source of heterogeneity. (3) Results: Screening by the given inclusion and exclusion criteria, a total of 28 studies were included in the analysis. We observed that the incidence of HFMD based on the single-day lag model is significantly associated with ambient temperature, relative humidity, rainfall, and wind speed. In the cumulative lag model, ambient temperature and relative humidity significantly increased the incidence of HFMD as well. Subgroup analysis showed that extremely high temperature and relative humidity significantly increased the risk of HFMD. Temperate regions, high-income countries, and children under five years old are major risk factors for HFMD. (4) Conclusions: Our results suggest that various meteorological factors can increase the incidence of HFMD. Therefore, the general public, especially susceptible populations, should pay close attention to weather changes and take protective measures in advance.

Association between diurnal temperature range and outpatient visits for hand, foot, and mouth disease in Hefei, China: a distributed lag nonlinear analysis

We aimed to quantify the relationship between the outpatient visits of hand, foot, and mouth disease (HFMD) and diurnal temperature range (DTR). The data of daily HFMD outpatient visits and meteorological parameters were obtained. A distributed lag nonlinear model combined with generalized linear model was used to estimate simultaneously nonlinear and delayed effects between DTR and daily HFMD outpatient visits after controlling confounding factors. A total of 15,275 HFMD visits were enrolled. DTR was significantly associated with HFMD outpatient visits in children. High DTR (P₇₅: 11.4 °C) and extreme DTR (P₉₅: 15.3 °C) were compared with 8.5 °C, and HFMD visits increased by a maximum of 3.93% (95% CI: 1.82 to 6.07%) and 4.47% (95% CI: 0.45 to 8.65%) in single-day lag effect, respectively. Furthermore, the extreme DTR effect decreased with the lag time and lasted for 10 days. Cumulative lag effects with markedly increasing percent of visits are over 64.88%. Furthermore, the effects were most pronounced among female children and children aged 0-2 years. Our study suggested that DTR changes were associated with HFMD outpatient visits, and populations of female and aged 0-2 years were more sensitive.

Assessment of Temperature-Hand, Foot, and Mouth Disease Association and Its Variability across Urban and Rural Populations in Wuxi, China: A Distributed Lag Nonlinear Analysis

Hand, foot, and mouth disease (HFMD) has brought millions of attacks and a substantial burden in the Asia-Pacific region. Previous studies assessed disease risks around the world, which demonstrated great heterogeneity, and few determined the modification effect of social factors on temperature-disease relationship. We conducted a time-series study to evaluate the temperature-associated HFMD morbidity risk using daily data (from 2011 to 2017) and to identify potential modifiers relating to urban-rural status and aggregation mode of children. By applying a distributed lag nonlinear model (DLNM) and controlling for time-varying factors and other meteorological factors, we found that the relationship between daily mean temperature and the cumulative risk of HFMD was an approximately M-shaped curve. The effects of higher temperature appeared to be greater and more persistent than those of lower temperature. With the reference of -6°C, the cumulative relative risk (RR) values of high temperature (95 percentile) and low temperature (5 percentile) were 3.74 (95% CI: 2.50-5.61) and 1.72 (95% CI: 1.24-2.37) at lag 4-7, respectively. Temperature-associated HFMD morbidity risks were more pronounced among rural children and those attending kindergartens or schools at specific lags and temperatures. Relative risk values for temperature-disease association was highest among the 3- to 6-year group, whereas no gender difference was observed. Studying effect estimates and their modifications using the DLNM on a daily scale helps to identify susceptible groups and guide policy-making and resource allocation according to specific local conditions.

Seasonal Distribution and Meteorological Factors Associated with Hand, Foot, and Mouth Disease among Children in Xi'an, Northwestern China

Hand, foot, and mouth disease (HFMD) is a common infectious disease in the Asia-Pacific region that primarily affects children younger than 5 years. Previous studies have confirmed that the seasonal transmission of this disease is strongly related to meteorological factors, but the results are not consistent. In addition, the associations between weather conditions and HFMD in northwestern China have not been investigated. Therefore, we aimed to examine this issue in Xi'an, the largest city of northwestern China that has been suffering from serious HFMD epidemics. In the current study, data for HFMD and six meteorological factors were collected from 2009 to 2018. Using cross-correlation analysis, the Granger causality test, and the distributed lag nonlinear model, we estimated the quantitative relationships and exposure-lag-response effects between weekly meteorological factors and HFMD incidence among children. We found that the seasonal distribution of HFMD in Xi'an has two peaks each year and is significantly impacted by the weekly temperature, precipitation, and evaporation over an 8-week period. Higher values of temperature and evaporation had positive associations with disease transmission, whereas the association between precipitation and HFMD showed an inverted-U shape. The maximum relative risks (RRs) of HFMD for the weekly mean temperature (approximately 31.1°C), weekly cumulative evaporation (57.9 mm), and weekly cumulative precipitation (30.0 mm) were 1.56 (95% CI: 1.35-1.81), 1.40 (95% CI: 1.05-1.88), and 1.16 (95% CI: 1.11-1.70), respectively. The identified risk determinants and lag effects could provide important information for early interventions to reduce the local disease burden.

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.

The effect of temperature on childhood hand, foot and mouth disease in Guangdong Province, China, 2010-2013: a multicity study

Background

Hand, foot and mouth disease (HFMD) is a serious infectious disease, which has become a public health problem. Previous studies have shown that temperature may influence the incidence of HFMD, but most only focus on single city and the results are highly heterogeneous. Therefore, a multicity study was conducted to explore the association between temperature and HFMD in different cities and search for modifiers that influence the heterogeneity.

Methods

We collected daily cases of childhood HFMD (aged 0–5 years) and meteorological factors of 21 cities in Guangdong Province in the period of 2010–2013. Distributed lag non-linear model (DLNM) with quasi-Poisson was adopted to quantify the effects of temperature on HFMD in 21 cities. Then the effects of each city were pooled by multivariate meta-analysis to obtain the heterogeneity among 21 cities. Potential city-level factors were included in meta-regression to explore effect modifiers.

Results

A total of 1,048,574 childhood cases were included in this study. There was a great correlation between daily childhood HFMD cases and temperature in each city, which was non-linear and lagged. High heterogeneity was showed in the associations between temperature and HFMD in 21 cities. The pooled temperature-HFMD association was peaking at the 79th percentile of temperature with relative risk (RR) of 2.474(95% CI: 2.065–2.965) as compared to the median temperature. Latitude was the main modifier for reducing the heterogeneity to 69.28% revealed by meta-analysis.

Conclusions

There was a strong non-linear and lagged correlation between temperature and HFMD. Latitude was strongly associated with the relationship between temperature and HFMD. Meanwhile, it had an effect on modifying the relationship. These findings can conducive to local governments developing corresponding preventive measures.

Dynamic Bayesian network in infectious diseases surveillance: a simulation study

The surveillance of infectious diseases relies on the identification of dynamic relations between the infectious diseases and corresponding influencing factors. However, the identification task confronts with two practical challenges: small sample size and delayed effect. To overcome both challenges to imporve the identification results, this study evaluated the performance of dynamic Bayesian network(DBN) in infectious diseases surveillance. Specifically, the evaluation was conducted by two simulations. The first simulation was to evaluate the performance of DBN by comparing it with the Granger causality test and the least absolute shrinkage and selection operator (LASSO) method; and the second simulation was to assess how the DBN could improve the forecasting ability of infectious diseases. In order to make both simulations close to the real-world situation as much as possible, their simulation scenarios were adapted from real-world studies, and practical issues such as nonlinearity and nuisance variables were also considered. The main simulation results were: ① When the sample size was large (n = 340), the true positive rates (TPRs) of DBN (≥98%) were slightly higher than those of the Granger causality method and approximately the same as those of the LASSO method; the false positive rates (FPRs) of DBN were averagely 46% less than those of the Granger causality test, and 22% less than those of the LASSO method. ② When the sample size was small, the main problem was low TPR, which would be further aggravated by the issues of nonlinearity and nuisance variables. In the worst situation (i.e., small sample size, nonlinearity and existence of nuisance variables), the TPR of DBN declined to 43.30%. However, it was worth noting that such decline could also be found in the corresponding results of Granger causality test and LASSO method. ③ Sample size was important for identifying the dynamic relations among multiple variables, in this case, at least three years of weekly historical data were needed to guarantee the quality of infectious diseases surveillance. ④ DBN could improve the foresting results through reducing forecasting errors by 7%. According to the above results, DBN is recommended to improve the quality of infectious diseases surveillance.

The complex transmission seasonality of hand, foot, and mouth disease and its driving factors

Background

The transmission rate seasonality is an important index for transmission dynamics in many childhood infections, and has been widely studied in industrialized countries. However, it has been neglected in the study of pathogens in China.

Methods

To understand the transmission dynamics of hand, foot and mouth disease (HFMD), we examined the transmission rate seasonality of HFMD in three provinces, Henan, Anhui and Chongqing, in China, using a dynamical stochastic SIR model. We investigated potential driving factors, including school terms, the Chinese Spring Festival period, meteorological factors and population flux for their effects on the HFMD transmission seasonality using multiple regression models.

Results

The transmission rate of HFMD had complex seasonality with one large major peak in March and one small peak in autumn. School terms, the Chinese Spring Festival period, population flux and meteorological factors had combined effects on the HFMD transmission seasonality in mainland China. The school terms reflects the seasonal contact rate in Children, while the population flux and the Chinese Spring Festival period reflect the seasonal contact rate in population. They drove HFMD transmission rate seasonality in different time periods of the year in China. Contact rate seasonality in population dominated effects on HFMD transmission in February and March. The dramatic increase in transmission rate during February coincides with the Chinese Spring Festival period and high population flux in this month. The contact rate seasonality in children dominated effects on the transmission in the other months of the year in Chongqing. Meteorological factors can not solely explain the seasonality in HFMD transmission in mainland China; however, they may have combined effects with school terms and the highway passenger traffic on the transmission rate in Anhui during the fall semester.

Conclusion

The transmission rate of HFMD in three provinces in China had complex seasonality. The Chinese Spring Festival period, population flux and (or) school terms explained the majority of the transmission rate seasonality of HFMD, and they drove HFMD transmission rate seasonality in different time periods of the year. The Chinese Spring Festival period dominantly caused the dramatic increase of the HFMD transmission rate during February.

Electronic supplementary material

The online version of this article (10.1186/s12879-019-4153-6) contains supplementary material, which is available to authorized users.

The surveillance of the epidemiological and serotype characteristics of hand, foot, mouth disease in Neijiang city, China, 2010-2017: A retrospective study

Hand, foot, and mouth disease (HFMD) is well recognized as one of the major threats to children’s health globally. The increasing complexity of the etiology of HFMD still challenges disease control in China. There is little surveillance of the molecular epidemiological characteristics of the enteroviruses (EVs) that cause HFMD in Neijiang city or the Sichuan Basin area in Southwest China. In this study, demographic and epidemiological information for 14,928 probable HFMD cases was extracted and analyzed to describe the epidemic features of HFMD in Neijiang city from Jan 2010 to Dec 2017. The swab samples of select probable HFMD cases from 2012 to 2017 were tested by reverse transcription (RT) real-time PCR to identify the serotype distribution of EVs, and 110 randomly selected RT-real-time PCR positive samples were then amplified and analyzed for the VP1 or VP4 regions of EVs to further analyze the phylogenetic characteristics of the circulating strains in this area. The eight-year average annual incidence was 49.82 per 100,000 in Neijiang. The incidence rates varied between 19.51 and 70.73 per 100,000, demonstrating peaks of incidence in even-number years (2012, 2014 and 2016). The median age of the probable cases was 27 months and the interquartile range (25^th to 75^th percentile) of ages for the probable HFMD cases was between 14 and 42 months. The male-to-female ratio of the probable HFMD cases was 1.47:1, and scattered children were the major population classification (81.7%). Two epidemic peaks were observed: one major peak between April and July and the other lesser peak between October and December. Of 6513 probable cases tested with RT-real-time PCR, 4015 (61.6%) were positive for enterovirus with the serotype distribution as follows: EV71+, 30.1% (n = 1210); CV-A16+, 28.7% (n = 1154) and a sole pan-enterovirus+, 41.1% (n = 1651). A total of 91 cases (82.7%, 91/110) were successfully amplified and underwent phylogenetic analysis: all EV71+ cases were C4a serotype (n = 23/30); all CV-A16+ cases were B2b serotype (n = 24/30); of 42 sole pan-enterovirus+ samples, 20 were CV-A6, 14 were CV-A10 and the rest within this group were CV-A4 (n = 4), CV-A8 (n = 2), CV-A9 (n = 1) and CV-B3 (n = 1). Our findings provide important evidence that aids the improvement of strategies for vaccination against HFMD and comprehensive disease control in China.

Impact of PM10 and meteorological factors on the incidence of hand, foot, and mouth disease in female children in Ningbo, China: a spatiotemporal and time-series study

Hand, foot, and mouth disease (HFMD) is a viral illness that is considered a critical public health challenge worldwide. Previous studies have demonstrated that meteorological parameters are significantly related to the incidence of HFMD in children; however, few studies have focused only on female children. This study quantified the associations of HFMD incidence with meteorological parameters and PM₁₀ (particulate matter with an aerodynamic diameter of 10 μm) among female children. Data were collected on daily HFMD cases, meteorological variables, and PM₁₀ levels in Ningbo, China, from January 2012 to December 2016. Data were assessed using a distributed lag nonlinear model (DLNM) with Poisson distribution. A total of 59,809 female children aged 0-15 years with HFMD were enrolled. The results showed that highest relative risk (RR) of HFMD for temperature was 3 °C and the lag effect was 3 days. The highest RR for PM₁₀ was 80 mg/m³ and the lag effect was 5 days. Spatial analysis showed that female HFMD incidence was mainly concentrated in the suburban of Ningbo city indicating that female children in this area should be more paid attention on avoiding this disease outbreak. Our findings suggest that HFMD prevention strategies should focus more attention on local meteorological parameters.

Temperature and humidity affect the incidence of hand, foot, and mouth disease: a systematic review of the literature - a report from the International Society of Dermatology Climate Change Committee

Hand, foot, and mouth disease (HFMD) is an enterovirus-mediated condition that predominantly affects children under 5 years of age. The tendency for outbreaks to peak in warmer summer months suggests a relationship between HFMD and weather patterns. We reviewed the English-language literature for articles describing a relationship between meteorological variables and HFMD. Seventy-two studies meeting criteria were identified. A positive, statistically significant relationship was identified between HFMD cases and both temperature (61 of 67 studies, or 91.0%, reported a positive relationship) [CI 81.8-95.8%, P = 0.0001] and relative humidity (41 of 54 studies, or 75.9%) [CI 63.1-85.4%, P = 0.0001]. No significant relationship was identified between HFMD and precipitation, wind speed, and/or sunshine. Most countries reported a single peak of disease each year (most commonly early Summer), but subtropical and tropical climate zones were significantly more likely to experience a bimodal distribution of cases throughout the year (two peaks a year; most commonly late spring/early summer, with a smaller peak in autumn). The rising global incidence of HFMD, particularly in Pacific Asia, may be related to climate change. Weather forecasting might be used effectively in the future to indicate the risk of HFMD outbreaks and the need for targeted public health interventions.

Modeling the Present and Future Incidence of Pediatric Hand, Foot, and Mouth Disease Associated with Ambient Temperature in Mainland China

BACKGROUND

There is limited evidence about the association between ambient temperature and the incidence of pediatric hand, foot, and mouth disease (HFMD) nationwide in China.

OBJECTIVES

We examined the childhood temperature-HFMD associations across mainland China, and we projected the change in HFMD cases due to projected temperature change by the 2090s.

METHODS

Data on daily HFMD (children 0-14 y old) counts and weather were collected from 362 sites during 2009-2014. Daily temperature by the 2090s was downscaled under the Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios. Temperature-HFMD associations were quantified using a two-stage Poisson regression with a distributed lag nonlinear model. The impact of changes in temperature on the incidence of HFMD was estimated by combining the fitted temperature-HFMD associations with projected temperatures under each scenario, assuming a constant population structure. Sensitivity analyses were performed to assess the influence of primary model assumptions.

RESULTS

During 2009-2014, >11 million HFMD cases were reported. In most regions, the temperature-HFMD association had an inverted U shape with a peak at approximately 20°C, but the association leveled off or continued to increase in the Inner Mongolia and Northeast regions. When estimates were pooled across all regions and the population size was held constant, the projected incidence of HFMD increased by 3.2% [95% empirical confidence interval (eCI): −13.5%, 20.0%] and 5.3% (95% eCI: −33.3%, 44.0%) by the 2090s under the RCP 4.5 and 8.5 scenarios, respectively. However, regional projections suggest that HFMD may decrease with climate change in temperate areas of central and eastern China.

CONCLUSION

Our estimates suggest that the association between temperature and HFMD varies across China and that the future impact of climate change on HFMD incidence will vary as well. Other factors, including changes in the size of the population at risk (children 0-14 y old) will also influence future HFMD trends. https://doi.org/10.1289/EHP3062.

Predicting the outbreak of hand, foot, and mouth disease in Nanjing, China: a time-series model based on weather variability

Hand, foot, and mouth disease (HFMD) is a significant public health issue in China and an accurate prediction of epidemic can improve the effectiveness of HFMD control. This study aims to develop a weather-based forecasting model for HFMD using the information on climatic variables and HFMD surveillance in Nanjing, China. Daily data on HFMD cases and meteorological variables between 2010 and 2015 were acquired from the Nanjing Center for Disease Control and Prevention, and China Meteorological Data Sharing Service System, respectively. A multivariate seasonal autoregressive integrated moving average (SARIMA) model was developed and validated by dividing HFMD infection data into two datasets: the data from 2010 to 2013 were used to construct a model and those from 2014 to 2015 were used to validate it. Moreover, we used weekly prediction for the data between 1 January 2014 and 31 December 2015 and leave-1-week-out prediction was used to validate the performance of model prediction. SARIMA (2,0,0)₅₂ associated with the average temperature at lag of 1 week appeared to be the best model (R ² = 0.936, BIC = 8.465), which also showed non-significant autocorrelations in the residuals of the model. In the validation of the constructed model, the predicted values matched the observed values reasonably well between 2014 and 2015. There was a high agreement rate between the predicted values and the observed values (sensitivity 80%, specificity 96.63%). This study suggests that the SARIMA model with average temperature could be used as an important tool for early detection and prediction of HFMD outbreaks in Nanjing, China.

Association between Severe Fever with Thrombocytopenia Syndrome Incidence and Ambient Temperature

Severe fever with thrombocytopenia syndrome (SFTS) is emerging in China. To explore the lagged effects and nonlinear association between temperature and SFTS, we collected data on ambient temperature and SFTS cases and analyzed the data using a distributed lag nonlinear model. A total of 1,933 SFTS cases were reported in the study area from 2011 to 2015. Our study revealed a nonlinear relationship between weekly temperature and SFTS. The exposure-response curve was an approximately reversed U-shaped peak at 23°C. High temperatures had acute and short-term effects, whereas low temperatures had persistent and long-term effects. The effects of lower temperatures (1.62°C and 6.97°C) could last 24 weeks, but the effect of 29.30°C was not significant at lag 8 weeks. Our results provide information to better understand the effect of temperature variation on SFTS and may have policy implications for disease prevention and control.

Quantifying the influence of temperature on hand, foot and mouth disease incidence in Wuhan, Central China

Hand, foot and mouth disease (HFMD) is a substantial burden throughout Asia, but the effects of temperature pattern on HFMD risk are inconsistent. To quantify the effect of temperature on HFMD incidence, Wuhan was chosen as the study site because of its high temperature variability and high HFMD incidence. Daily series of HFMD counts and meteorological variables during 2010-2015 were obtained. Distributed lag non-linear models were applied to characterize the temperature-HFMD relationship and to assess its variability across different ages, genders, and types of child care. Totally, 80,219 patients of 0-5 years experienced HFMD in 2010-2015 in Wuhan. The cumulative relative risk of HFMD increased linearly with temperature over 7 days (lag0-7), while it presented as an approximately inverted V-shape over 14 days (lag0-14). The cumulative relative risk at lag0-14 peaked at 26.4 °C with value of 2.78 (95%CI: 2.08-3.72) compared with the 5^th percentile temperature (1.7 °C). Subgroup analyses revealed that children attended daycare were more vulnerable to temperature variation than those cared for at home. This study suggests that public health actions should take into consideration local weather conditions and demographic characteristics.

Impact of meteorological factors on the incidence of childhood hand, foot, and mouth disease (HFMD) analyzed by DLNMs-based time series approach

BACKGROUND

Hand, foot, and mouth disease (HFMD) has become an emerging infectious disease in China in the last decade. There has been evidence that meteorological factors can influence the HFMD incidence, and understanding the mechanisms can help prevent and control HFMD.

METHODS

HFMD incidence data and meteorological data in Minhang District, Shanghai were obtained for the period between 2009 and 2015. Distributed lag non-linear models (DLNMs) were utilized to investigate the impact of meteorological factors on HFMD incidence after adjusting for potential confounders of long time trend, weekdays and holidays.

RESULTS

There was a non-linear relationship between temperature and HFMD incidence, the RR of 5th percentile compared to the median is 0.836 (95% CI: 0.671-1.042) and the RR of 95th percentile is 2.225 (95% CI: 1.774-2.792), and the effect of temperature varied across age groups. HFMD incidence increased with increasing average relative humidity (%) (RR = 1.009, 95% CI: 1.005-1.015) and wind speed (m/s) (RR = 1.197, 95% CI: 1.118-1.282), and with decreasing daily rainfall (mm) (RR = 0.992, 95% CI: 0.987-0.997) and sunshine hours (h) (RR = 0.966, 95% CI: 0.951-0.980).

CONCLUSIONS

There were significant relationships between meteorological factors and childhood HFMD incidence in Minhang District, Shanghai. This information can help local health agencies develop strategies for the control and prevention of HFMD under specific climatic conditions.