Daily mean temperature and HFMD: risk assessment and attributable fraction identification in Ningbo China

Zhang, Rui; Lin, Zhehan; Guo, Zhen; Chang, Zhaorui; Niu, Ran; Wang, Yu; Wang, Songwang; Li, Yonghong

doi:10.1038/s41370-021-00291-y

Cited by 11 publications

(4 citation statements)

References 32 publications

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“…Meteorological factors could affect the incidence of HFMD by influencing the breeding, growth, and transmission of pathogens, as well as human behaviors [ 29 , 30 , 31 ]. Many previous studies have shed light on the non-linear effects of meteorological factors on HFMD [ 32 , 33 , 34 , 35 ]. According to the principle of the neural network model, LSTM can effectively fit these non-linear meteorological data.…”

Section: Discussionmentioning

confidence: 99%

Comparison of ARIMA and LSTM in Forecasting the Incidence of HFMD Combined and Uncombined with Exogenous Meteorological Variables in Ningbo, China

Zhang

Guo

Meng

et al. 2021

IJERPH

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Background: This study intends to identify the best model for predicting the incidence of hand, foot and mouth disease (HFMD) in Ningbo by comparing Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory Neural Network (LSTM) models combined and uncombined with exogenous meteorological variables. Methods: The data of daily HFMD incidence in Ningbo from January 2014 to November 2017 were set as the training set, and the data of December 2017 were set as the test set. ARIMA and LSTM models combined and uncombined with exogenous meteorological variables were adopted to fit the daily incidence of HFMD by using the data of the training set. The forecasting performances of the four fitted models were verified by using the data of the test set. Root mean square error (RMSE) was selected as the main measure to evaluate the performance of the models. Results: The RMSE for multivariate LSTM, univariate LSTM, ARIMA and ARIMAX (Autoregressive Integrated Moving Average Model with Exogenous Input Variables) was 10.78, 11.20, 12.43 and 14.73, respectively. The LSTM model with exogenous meteorological variables has the best performance among the four models and meteorological variables can increase the prediction accuracy of LSTM model. For the ARIMA model, exogenous meteorological variables did not increase the prediction accuracy but became the interference factor of the model. Conclusions: Multivariate LSTM is the best among the four models to fit the daily incidence of HFMD in Ningbo. It can provide a scientific method to build the HFMD early warning system and the methodology can also be applied to other communicable diseases.

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Section: Discussionmentioning

confidence: 99%

Comparison of ARIMA and LSTM in Forecasting the Incidence of HFMD Combined and Uncombined with Exogenous Meteorological Variables in Ningbo, China

Zhang

Guo

Meng

et al. 2021

IJERPH

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“…A comparison of the attributable fractions of air pollutants revealed that the health effects of O 3 were much greater than those of other air pollutants, particularly in basin and mountain regions. In previous studies, temperature and relative humidity, the two most popular environmental factors, were commonly identified to have significant impacts on HFMD risks [ 33 , 54 , 55 ]. The attributable fractions of high temperature and relative humidity in previous studies reached 39.55% [ 54 ] and 14.56% [ 33 ], respectively.…”

Section: Discussionmentioning

confidence: 99%

“…In previous studies, temperature and relative humidity, the two most popular environmental factors, were commonly identified to have significant impacts on HFMD risks [ 33 , 54 , 55 ]. The attributable fractions of high temperature and relative humidity in previous studies reached 39.55% [ 54 ] and 14.56% [ 33 ], respectively. The latter was relatively close to the AFs for the high levels of PM 10 (13.38%) and O 3 (16.83%) that were calculated in this study.…”

Section: Discussionmentioning

confidence: 99%

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

Luo,

Ma,

et al. 2024

BMC Public Health

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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.

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“…Ambient heat exposure was suggested to be one of the most important environmental factors that were associated with an elevated risk of HFMD in numerous previous studies [ 10 , 11 ]. For example, a systematic review on top of 11 studies previously conducted in Asia-Pacific regions suggested an average 5(2–8)% increase in the incidence of HFMD per 1°C increase in the temperature [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

Assessing the impact of ambient temperature on the risk of hand, foot, and mouth disease in Guangdong, China: New insight from the disease severity and burden

Zhang

et al. 2022

PLoS Negl Trop Dis

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Background The association between the incidence of hand, foot, and mouth disease (HFMD) and ambient temperature has been well documented. Although the severity of symptoms is an important indicator of disease burden and varies significantly across cases, it usually was ignored in previous studies, potentially leading to biased estimates of the health impact of temperature. Methods We estimated the disability-adjusted life year (DALY) by considering the severity of symptoms for each HFMD case reported during 2010–2012 in Guangdong and used distributed lag-nonlinear models to estimate the association between the daily average temperature and daily DALY of HFMD cases at the city-level. We investigated the potential effect modifiers on the pathway between temperature and DALY and pooled city-specific estimates to a provincial association using a meta-regression. The overall impact of temperature was further evaluated by estimates of DALYs that could be attributed to HFMD. Results The overall cumulative effect of daily mean temperature on the DALY of HFMD showed an inverse-U shape, with the maximum effect estimated to be β = 0.0331 (95%CI: 0.0199–0.0463) DALY at 23.8°C. Overall, a total of 6.432 (95%CI: 3.942–8.885) DALYs (attributable fraction = 2.721%, 95%CI: 1.660–3.759%) could be attributed to temperature exposure. All the demographic subgroups had a similar trend as the main analysis, while the magnitude of the peak of the temperature impact tended to be higher among the males, those aged ≥3yrs or from the Pear-River Delta region. Additionally, the impact of temperature on DALY elevated significantly with the increasing population density, per capita GDP, and per capita green space in parks. Conclusions Temperature exposure was associated with increased burden of HFMD nonlinearly, with certain groups such as boys and those from areas with greater population density being more vulnerable.

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Daily mean temperature and HFMD: risk assessment and attributable fraction identification in Ningbo China

Cited by 11 publications

References 32 publications

Comparison of ARIMA and LSTM in Forecasting the Incidence of HFMD Combined and Uncombined with Exogenous Meteorological Variables in Ningbo, China

Comparison of ARIMA and LSTM in Forecasting the Incidence of HFMD Combined and Uncombined with Exogenous Meteorological Variables in Ningbo, China

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

Assessing the impact of ambient temperature on the risk of hand, foot, and mouth disease in Guangdong, China: New insight from the disease severity and burden

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