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Guang X, He Y, Chen Z, Yang H, Lu Y, Meng J, Cheng Y, Chen N, Zhou Q, He R, Zhu B, Zhang Z. Development and validation of a potential risk area identification model for hand, foot, and mouth disease in metropolitan China. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 371:123064. [PMID: 39471592 DOI: 10.1016/j.jenvman.2024.123064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 09/29/2024] [Accepted: 10/21/2024] [Indexed: 11/01/2024]
Abstract
Maximum Entropy model (MaxEnt), as a machine learning algorithm, is widely used to identify potential risk areas for emerging infectious diseases. However, MaxEnt usually overlooks the influence of the optimal selection of spatial grid scale and the optimal combination of factor information on identification accuracy. Furthermore, the internal level information of factors is closely related to the potential risk of disease occurrence but is rarely applied to enhance MaxEnt's accuracy. In this study, the Optimal Parameters-based Geographical Detectors-Information Value-MaxEnt (OPGD-IV-MaxEnt) was first proposed to identify the potential risk areas of hand, foot, and mouth disease (HFMD) in Shenzhen and compared its identification accuracy with that of OPGD-MaxEnt and MaxEnt. Firstly, the optimal grid scale and optimal combination of factor information were determined by OPGD. Secondly, the contributions of factors' internal level information to the potential risk of HFMD occurrence were quantified and incorporated by IV. Lastly, the spatial patterns of potential risk areas and their main driving factors were elucidated. Results showed that: (i) Area under the curve (AUC) of single MaxEnt were 0.638, 0.688, 0.763, 0.796, and 0.757 at 100 m, 250 m, 500 m, 750 m, and 1000 m scale, respectively, and 750 m were deemed the optimal scale. (ii) At the optimal scale, OPGD-IV-MaxEnt (AUC = 0.868) identified potential risk areas more accurately than MaxEnt (AUC = 0.796) and OPGD-MaxEnt (AUC = 0.827). (iii) Resident (r = 0.61, q = 0.39) and Market (r = 0.61, q = 0.36) were the primary factors affecting the identification of potential risk areas. (iv) Potential high-risk areas of HFMD were mainly distributed in northwestern, southwestern, and central Shenzhen, with dense resident and market distribution. Such insights are instrumental in devising targeted infection prevention and control measures for emerging infectious diseases and provide references for improving the identification accuracy of similar machine learning algorithms.
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Affiliation(s)
- Xu Guang
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, China
| | - Yifei He
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, China
| | - Zhigao Chen
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Hong Yang
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Yan Lu
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Jun Meng
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Yanpeng Cheng
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Nixuan Chen
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Qingqing Zhou
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, China
| | - Rongxin He
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Bin Zhu
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, China.
| | - Zhen Zhang
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China.
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Zheng D, Shen L, Wen W, Zhuang Z, Qian SE, Ling F, Miao Z, Li R, McMillin SE, Bass S, Sun J, Lin H, Liu K. Effect of EV71 Vaccination on Transmission Dynamics of Hand, Foot, and Mouth Disease and Its Epidemic Prevention Threshold. Vaccines (Basel) 2024; 12:1166. [PMID: 39460332 PMCID: PMC11511198 DOI: 10.3390/vaccines12101166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2024] [Revised: 10/09/2024] [Accepted: 10/11/2024] [Indexed: 10/28/2024] Open
Abstract
OBJECTIVE To investigate the effect of Enterovirus A71 (EV71) vaccination on the transmissibility of different enterovirus serotypes of hand, foot, and mouth disease (HFMD) in Zhejiang, China. METHODS Daily surveillance data of HFMD and EV71 vaccination from August 2016 to December 2019 were collected. Epidemic periods for each HFMD type were defined, and the time-varying effective reproduction number (Rt) was estimated, which could provide more direct evidence of disease epidemics than case number. General additive models (GAMs) were employed to analyze associations between EV71 vaccination quantity and rate and HFMD transmissibility. The epidemic prevention threshold, represented by required vaccination numbers and rates, was also estimated. RESULTS Vaccinating every 100,000 children ≤ 5 years could lead to a decrease in the Rt of EV71-associated HFMD by 14.44% (95%CI: 6.76%, 21.42%). Additionally, a positive correlation was observed between vaccinations among children ≤ 5 years old (per 100,000) and the increased transmissibility of other HFMD types (caused by enteroviruses other than EV71 and CA16) at 1.82% (95%CI: 0.80%, 2.84%). It was estimated that an additional 362,381 vaccinations, corresponding to increased vaccine coverage to 54.51% among children ≤ 5 years could effectively prevent EV71 epidemics in Zhejiang. CONCLUSIONS Our findings highlight the importance of enhancing EV71 vaccine coverage for controlling the epidemic of EV71-HFMD and assisting government officials in developing strategies to prevent HFMD.
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Affiliation(s)
- Dashan Zheng
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; (D.Z.); (H.L.)
| | - Lingzhi Shen
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - Wanqi Wen
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; (D.Z.); (H.L.)
| | - Zitong Zhuang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; (D.Z.); (H.L.)
| | - Samantha E. Qian
- College of Arts and Sciences, Saint Louis University, Saint Louis, MO 63108, USA
| | - Feng Ling
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - Ziping Miao
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - Rui Li
- Department of Epidemiology, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, 169 Changle West Road, Xi’an 710032, China
| | | | - Sabel Bass
- Department of Epidemiology and Biostatistics, College for Public Health and Social Justice, Saint Louis University, Saint Louis, MO 63104, USA
| | - Jimin Sun
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; (D.Z.); (H.L.)
| | - Kun Liu
- Department of Epidemiology, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, 169 Changle West Road, Xi’an 710032, China
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Li J, Zhang R, Lan G, Lin M, Tan S, Zhu Q, Chen H, Huang J, Ding D, Li C, Ruan Y, Wang N. The Distribution and Associated Factors of HIV/AIDS Among Youths in Guangxi, China, From 2014 to 2021: Bayesian Spatiotemporal Analysis. JMIR Public Health Surveill 2024; 10:e53361. [PMID: 39331816 PMCID: PMC11452016 DOI: 10.2196/53361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 05/12/2024] [Accepted: 05/24/2024] [Indexed: 09/29/2024] Open
Abstract
Background In recent years, the number of HIV/AIDS cases among youth has increased year by year around the world. A spatial and temporal analysis of these AIDS cases is necessary for the development of youth AIDS prevention and control policies. Objective This study aimed to analyze the spatial and temporal distribution and associated factors of HIV/AIDS among youth in Guangxi as an example. Methods The reported HIV/AIDS cases of youths aged 15-24 years in Guangxi from January 2014 to December 2021 were extracted from the Chinese Comprehensive Response Information Management System of HIV/AIDS. Data on population, economy, and health resources were obtained from the Guangxi Statistical Yearbook. The ArcGIS (version 10.8; ESRI Inc) software was used to describe the spatial distribution of AIDS incidence among youths in Guangxi. A Bayesian spatiotemporal model was used to analyze the distribution and associated factors of HIV/AIDS, such as gross domestic product per capita, population density, number of health technicians, and road mileage per unit area. Results From 2014 to 2021, a total of 4638 cases of HIV/AIDS infection among youths were reported in Guangxi. The reported incidence of HIV/AIDS cases among youths in Guangxi increased from 9.13/100,000 in 2014 to 11.15/100,000 in 2019 and then plummeted to a low of 8.37/100,000 in 2020, followed by a small increase to 9.66/100,000 in 2021. The districts (counties) with relatively high HIV/AIDS prevalence among youths were Xixiangtang, Xingning, Qingxiu, Chengzhong, and Diecai. The reported incidence of HIV/AIDS among youths was negatively significantly associated with road mileage per unit area (km) at a posterior mean of -0.510 (95% CI -0.818 to 0.209). It was positively associated with population density (100 persons) at a posterior mean of 0.025 (95% CI 0.012-0.038), with the number of health technicians (100 persons) having a posterior mean of 0.007 (95% CI 0.004-0.009). Conclusions In Guangxi, current HIV and AIDS prevention and control among young people should focus on areas with a high risk of disease. It is suggested to strengthen the allocation of AIDS health resources and balance urban development and AIDS prevention. In addition, AIDS awareness, detection, and intervention among Guangxi youths need to be strengthened.
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Affiliation(s)
- Juntong Li
- Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Health, School of Public Health, Guilin Medical University, 1 Zhiyuan Road, Guilin, 541100, China, 86 07733680605
| | - Runxi Zhang
- Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Health, School of Public Health, Guilin Medical University, 1 Zhiyuan Road, Guilin, 541100, China, 86 07733680605
| | - Guanghua Lan
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, 18 Jinzhou Road, Nanning, China
| | - Mei Lin
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, 18 Jinzhou Road, Nanning, China
| | - Shengkui Tan
- Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Health, School of Public Health, Guilin Medical University, 1 Zhiyuan Road, Guilin, 541100, China, 86 07733680605
| | - Qiuying Zhu
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, 18 Jinzhou Road, Nanning, China
| | - Huanhuan Chen
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, 18 Jinzhou Road, Nanning, China
| | - Jinghua Huang
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, 18 Jinzhou Road, Nanning, China
| | - Dongni Ding
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, 18 Jinzhou Road, Nanning, China
| | - Chunying Li
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, 18 Jinzhou Road, Nanning, China
| | - Yuhua Ruan
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Na Wang
- Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Health, School of Public Health, Guilin Medical University, 1 Zhiyuan Road, Guilin, 541100, China, 86 07733680605
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, 18 Jinzhou Road, Nanning, China
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Shen L, Sun M, Wei M, Hu Q, Bai Y, Shao Z, Liu K. The non-stationary and spatially varying associations between hand, foot and mouth disease and multiple environmental factors: A Bayesian spatiotemporal mapping model study. Infect Dis Model 2024; 9:373-386. [PMID: 38385017 PMCID: PMC10879665 DOI: 10.1016/j.idm.2024.02.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 01/29/2024] [Accepted: 02/04/2024] [Indexed: 02/23/2024] Open
Abstract
The transmission and prevalence of Hand, Foot and Mouth Disease (HFMD) are affected by a variety of natural and socio-economic environmental factors. This study aims to quantitatively investigate the non-stationary and spatially varying associations between various environmental factors and HFMD risk. We collected HFMD surveillance cases and a series of relevant environmental data from 2013 to 2021 in Xi'an, Northwest China. By controlling the spatial and temporal mixture effects of HFMD, we constructed a Bayesian spatiotemporal mapping model and characterized the impacts of different driving factors into global linear, non-stationary and spatially varying effects. The results showed that the impact of meteorological conditions on HFMD risk varies in both type and magnitude above certain thresholds (temperature: 30 °C, precipitation: 70 mm, solar radiation: 13000 kJ/m2, pressure: 945 hPa, humidity: 69%). Air pollutants (PM2.5, PM10, NO2) showed an inverted U-shaped relationship with the risk of HFMD, while other air pollutants (O3, SO2) showed nonlinear fluctuations. Moreover, the driving effect of increasing temperature on HFMD was significant in the 3-year period, while the inhibitory effect of increasing precipitation appeared evident in the 5-year period. In addition, the proportion of urban/suburban/rural area had a strong influence on HFMD, indicating that the incidence of HFMD firstly increased and then decreased during the rapid urbanization process. The influence of population density on HFMD was not only limited by spatial location, but also varied between high and low intervals. Higher road density inhibited the risk of HFMD, but higher night light index promoted the occurrence of HFMD. Our findings further demonstrated that both ecological and socioeconomic environmental factors can pose multiple driving effects on increasing the spatiotemporal risk of HFMD, which is of great significance for effectively responding to the changes in HFMD epidemic outbreaks.
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Affiliation(s)
- Li Shen
- School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, Hubei Province, China
| | - Minghao Sun
- School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, Hubei Province, China
| | - Mengna Wei
- School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, Hubei Province, China
| | - Qingwu Hu
- School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, Hubei Province, China
| | - Yao Bai
- Department of Infection Disease Control and Prevention, Xi'an Center for Disease Control and Prevention, Xi'an, Shaanxi, China
| | - Zhongjun Shao
- Department of Epidemiology, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi'an, Shaanxi Province, China
| | - Kun Liu
- Department of Epidemiology, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi'an, Shaanxi Province, China
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Cao H, Xu R, Liang Y, Li Q, Jiang W, Jin Y, Wang W, Yuan J. Effects of extreme meteorological factors and high air pollutant concentrations on the incidence of hand, foot and mouth disease in Jining, China. PeerJ 2024; 12:e17163. [PMID: 38766480 PMCID: PMC11102053 DOI: 10.7717/peerj.17163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 03/06/2024] [Indexed: 05/22/2024] Open
Abstract
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.
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Affiliation(s)
- Haoyue Cao
- School of Public Health, North China University of Science and Technology, Tangshan, Hebei Province, China
| | - Rongrong Xu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Yongmei Liang
- Business Management Department, Jining Center For Disease Control And Prevention, Jining, Shandong, China
| | - Qinglin Li
- School of Public Health, North China University of Science and Technology, Tangshan, Hebei Province, China
| | - Wenguo Jiang
- Infectious Disease Prevention and Control Department, Jining Center For Disease Control And Prevention, Jining, Shandong, China
| | - Yudi Jin
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Wenjun Wang
- Weifang Nursing Vocational College, Weifang, Shandong, China
| | - Juxiang Yuan
- School of Public Health, North China University of Science and Technology, Tangshan, Hebei Province, China
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Zhang C, Wang X, Sun D, Li Y, Feng Y, Zhang R, Zheng Y, Kou Z, Liu Y. Modification effects of long-term air pollution levels on the relationship between short-term exposure to meteorological factors and hand, foot, and mouth disease: A distributed lag non-linear model-based study in Shandong Province, China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 272:116060. [PMID: 38310825 DOI: 10.1016/j.ecoenv.2024.116060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 01/28/2024] [Accepted: 01/29/2024] [Indexed: 02/06/2024]
Abstract
The occurrence of hand, foot, and mouth disease (HFMD) is closely related to meteorological factors. However, location-specific characteristics, such as persistent air pollution, may increase the complexity of the impact of meteorological factors on HFMD, and studies across different areas and populations are largely lacking. In this study, a two-stage multisite time-series analysis was conducted using data from 16 cities in Shandong Province from 2015 to 2019. In the first stage, we obtained the cumulative exposure-response curves of meteorological factors and the number of HFMD cases for each city. In the second stage, we merged the estimations from the first stage and included city-specific air pollution variables to identify significant effect modifiers and how they modified the short-term relationship between HFMD and meteorological factors. High concentrations of air pollutants may reduce the risk effects of high average temperature on HFMD and lead to a distinct peak in the cumulative exposure-response curve, while lower concentrations may increase the risk effects of high relative humidity. Furthermore, the effects of average wind speed on HFMD were different at different levels of air pollution. The differences in modification effects between subgroups were mainly manifested in the diversity and quantity of significant modifiers. The modification effects of long-term air pollution levels on the relationship between sunshine hours and HFMD may vary significantly depending on geographical location. The people in age<3 and male groups were more susceptible to long-term air pollution. These findings contribute to a deepening understanding of the relationship between meteorological factors and HFMD and provide evidence for relevant public health decision-making.
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Affiliation(s)
- Chao Zhang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China; Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250000, China
| | - Xianjun Wang
- Shandong Center for Disease Control and Prevention, Jinan, China
| | - Dapeng Sun
- Shandong Center for Disease Control and Prevention, Jinan, China
| | - Yan Li
- Shandong Center for Disease Control and Prevention, Jinan, China
| | - Yiping Feng
- Shandong Center for Disease Control and Prevention, Jinan, China
| | - Rongguo Zhang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China; Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250000, China
| | - Yongxiao Zheng
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China; Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250000, China
| | - Zengqiang Kou
- Shandong Center for Disease Control and Prevention, Jinan, China.
| | - Yunxia Liu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China; Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250000, China; Climate Change and Health Center, Shandong University, Jinan, Shandong 250012, China.
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Wei Y, Ma Y, Zhang T, Luo X, Yin F, Shui T. Spatiotemporal patterns and risk mapping of provincial hand, foot, and mouth disease in mainland China, 2014-2017. Front Public Health 2024; 12:1291361. [PMID: 38344231 PMCID: PMC10853440 DOI: 10.3389/fpubh.2024.1291361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Accepted: 01/08/2024] [Indexed: 02/15/2024] Open
Abstract
Background Hand, foot, and mouth disease (HFMD) has remained a serious public health threat since its first outbreak in China. Analyzing the province-level spatiotemporal distribution of HFMD and mapping the relative risk in mainland China will help determine high-risk provinces and periods of infection outbreaks for use in formulating new priority areas for prevention and control of this disease. Furthermore, our study examined the effect of air pollution on HFMD nationwide, which few studies have done thus far. Methods Data were collected on the number of provincial monthly HFMD infections, air pollution, meteorological variables, and socioeconomic variables from 2014 to 2017 in mainland China. We used spatial autocorrelation to determine the aggregate distribution of HFMD incidence. Spatiotemporal patterns of HFMD were analyzed, risk maps were developed using the Bayesian spatiotemporal model, and the impact of potential influencing factors on HFMD was assessed. Results In our study, from 2014 to 2017, the HFMD annual incidence rate in all provinces of mainland China ranged from 138.80 to 203.15 per 100,000 people, with an average annual incidence rate of 165.86. The temporal risk of HFMD for 31 Chinese provinces exhibited cyclical and seasonal characteristics. The southern and eastern provinces had the highest spatial relative risk (RR > 3) from 2014 to 2017. The HFMD incidence risk in provinces (Hunan, Hubei, and Chongqing) located in central China increased over time. Among the meteorological variables, except for the mean two-minute wind speed (RR 0.6878; 95% CI 0.5841, 0.8042), all other variables were risk factors for HFMD. High GDP per capita (RR 0.9922; 95% CI 0.9841, 0.9999) was a protective factor against HFMD. The higher the birth rate was (RR 1.0657; 95% CI 1.0185, 1.1150), the higher the risk of HFMD. Health workers per 1,000 people (RR 1.2010; 95% CI 1.0443, 1.3771) was positively correlated with HFMD. Conclusions From 2014 to 2017, the central provinces (Hunan, Hubei, and Chongqing) gradually became high-risk regions for HFMD. The spatiotemporal pattern of HFMD risk may be partially attributed to meteorological and socioeconomic factors. The prevalence of HFMD in the central provinces requires attention, as prevention control efforts should be strengthened there.
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Affiliation(s)
- Yuxin Wei
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yue Ma
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Tao Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xuelian Luo
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Fei Yin
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Tiejun Shui
- Yunnan Center for Disease Control and Prevention, Kunming, China
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Associations between ambient air pollutants and childhood hand, foot, and mouth disease in Sichuan, China: a spatiotemporal study. Sci Rep 2023; 13:3993. [PMID: 36899026 PMCID: PMC10006415 DOI: 10.1038/s41598-023-31035-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 03/06/2023] [Indexed: 03/12/2023] Open
Abstract
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 (PM2.5, 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 PM2.5 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 PM2.5, 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.
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Yang Z, Rui J, Qi L, Ye W, Niu Y, Luo K, Deng B, Zhang S, Yu S, Liu C, Li P, Wang R, Wei H, Zhang H, Huang L, Zuo S, Zhang L, Zhang S, Yang S, Guo Y, Zhao Q, Wu S, Li Q, Chen Y, Chen T. Study on the interaction between different pathogens of Hand, foot and mouth disease in five regions of China. Front Public Health 2022; 10:970880. [PMID: 36238254 PMCID: PMC9552780 DOI: 10.3389/fpubh.2022.970880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 08/22/2022] [Indexed: 01/25/2023] Open
Abstract
Objectives This study aims to explore the interaction of different pathogens in Hand, foot and mouth disease (HFMD) by using a mathematical epidemiological model and the reported data in five regions of China. Methods A cross-regional dataset of reported HFMD cases was built from four provinces (Fujian Province, Jiangsu province, Hunan Province, and Jilin Province) and one municipality (Chongqing Municipality) in China. The subtypes of the pathogens of HFMD, including Coxsackievirus A16 (CV-A16), enteroviruses A71 (EV-A71), and other enteroviruses (Others), were included in the data. A mathematical model was developed to fit the data. The effective reproduction number (R eff ) was calculated to quantify the transmissibility of the pathogens. Results In total, 3,336,482 HFMD cases were collected in the five regions. In Fujian Province, the R eff between CV-A16 and EV-A71&CV-A16, and between CV-A16 and CV-A16&Others showed statistically significant differences (P < 0.05). In Jiangsu Province, there was a significant difference in R eff (P < 0.05) between the CV-A16 and Total. In Hunan Province, the R eff between CV-A16 and EV-A71&CV-A16, between CV-A16 and Total were significant (P < 0.05). In Chongqing Municipality, we found significant differences of the R eff (P < 0.05) between CV-A16 and CV-A16&Others, and between Others and CV-A16&Others. In Jilin Province, significant differences of the R eff (P < 0.05) were found between EV-A71 and Total, and between Others and Total. Conclusion The major pathogens of HFMD have changed annually, and the incidence of HFMD caused by others and CV-A16 has surpassed that of EV-A71 in recent years. Cross-regional differences were observed in the interactions between the pathogens.
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Affiliation(s)
- Zimei Yang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Jia Rui
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Li Qi
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Wenjing Ye
- Fujian Center for Disease Control and Prevention, Fuzhou, Fujian, China
| | - Yan Niu
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Kaiwei Luo
- Hunan Center for Disease Control and Prevention, Changsha, Hunan, China
| | - Bin Deng
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Shi Zhang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Shanshan Yu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Chan Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Peihua Li
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Rui Wang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Hongjie Wei
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Hesong Zhang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Lijin Huang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Simiao Zuo
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Lexin Zhang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Shurui Zhang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Shiting Yang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Yichao Guo
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Qinglong Zhao
- Jilin Center for Disease Control and Prevention, Changchun, Jilin, China
| | - Shenggen Wu
- Fujian Center for Disease Control and Prevention, Fuzhou, Fujian, China,Shenggen Wu
| | - Qin Li
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China,Qin Li
| | - Yong Chen
- Department of Stomatology, School of Medicine, Xiamen University, Xiamen, China,Yong Chen
| | - Tianmu Chen
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China,*Correspondence: Tianmu Chen
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Li C, Zhu Y, She K, Jia Y, Liu T, Han C, Fang Q, Cheng C, Han L, Liu Y, Zhang Y, Li X. Modified effects of air pollutants on the relationship between temperature variability and hand, foot, and mouth disease in Zibo City, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:44573-44581. [PMID: 35133585 DOI: 10.1007/s11356-022-18817-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 01/19/2022] [Indexed: 06/14/2023]
Abstract
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.
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Affiliation(s)
- Chunyu Li
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China
| | - Yuchen Zhu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China
| | - Kaili She
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China
| | - Yan Jia
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China
| | - Tingxuan Liu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China
| | - Chuang Han
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China
| | - Qidi Fang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China
| | - Chuanlong Cheng
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China
| | - Luyi Han
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China
| | - Ying Liu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China
| | - Ying Zhang
- School of Public Health, Faculty of Medicine and Health, University of Sydney, Camperdown, NSW, 2006, Australia
| | - Xiujun Li
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China.
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11
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Yi Z, Pei S, Suo W, Wang X, Huang Z, Yi A, Wang B, He Z, Wang R, Li Y, Fan W, Huang X. Epidemiological characteristics, routine laboratory diagnosis, clinical signs and risk factors for hand, -foot -and -mouth disease: A systematic review and meta-analysis. PLoS One 2022; 17:e0267716. [PMID: 35482791 PMCID: PMC9049560 DOI: 10.1371/journal.pone.0267716] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 04/13/2022] [Indexed: 01/18/2023] Open
Abstract
Background For the past few years, only a few monovalent EV71 vaccines have been developed, while other enterovirus vaccines are in short supply. We conducted a quantitative meta-analysis to explore the epidemiological characteristics, routine laboratory diagnosis, clinical signs and risk factors for hand, foot and mouth disease (HFMD). Methods PubMed, Embase and the Web of Science were searched for eligible reports published before April 16, 2021, with no publication time or language restrictions. The primary outcome was the odds ratio of the epidemiological characteristics, routine laboratory diagnosis, and clinical signs associated with HFMD severity and death. Results After screening 10522 records, we included 32 articles comprising 781903 cases of hand, foot and mouth disease. Patients with severe illness developed some clinical signs (hypersomnia (OR = 21.97, 95% CI: 4.13 to 116.74), convulsion (OR = 16.18, 95% CI: 5.30 to 49.39), limb shaking (OR = 47.96, 95% CI: 15.17 to 151.67), and breathlessness (OR = 7.48, 95% CI: 1.90 to 29.40)) and had some changes in laboratory parameters (interleukin-6 levels standardized mean difference (SMD) = 1.57, 95%CI: 0.55 to 2.60), an increased neutrophils ratio (SMD = 0.55, 95%CI: 0.17 to 0.93), cluster of differentiation 4 (CD4+) (SMD = -1.38, 95%CI: -2.33 to -0.43) and a reduced lymphocytes ratio (SMD = -0.48, 95%CI: -0.93 to -0.33)) compared with patients with mild illness. The risk factors for death included cyanosis (OR = 5.82, 95% CI: 2.29 to 14.81), a fast heart rate (OR = 3.22, 95% CI: 1.65 to 6.30), vomiting (OR = 2.70, 95% CI: 1.33 to 5.49) and an increased WBC count (SMD = 0.60, 95% CI: 0.27 to 0.93). Conclusions China has the highest incidence of HFMD. Our meta-analyses revealed important risk factors that are associated with the severity and mortality of HFMD.
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Affiliation(s)
- Zhijie Yi
- College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Shujun Pei
- College of Public Health, Xinxiang Medical University, Xinxiang, China
| | - Wenshuai Suo
- College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Xiaoyang Wang
- College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Zengyuan Huang
- Fifth Clinical Medical College of Henan University of Chinese Medicine, Zhengzhou, China
| | - Aihua Yi
- First Affiliated Hospital of Shaoyang University, Shaoyang, China
| | - Bohao Wang
- Quality Control Department of Henan Children’s Hospital, Zhengzhou, China
| | - Zhiquan He
- Henan Province Center for Disease Control and Prevention, Zhengzhou, China
| | - Ruolin Wang
- Henan Province Center for Disease Control and Prevention, Zhengzhou, China
| | - Yi Li
- Henan Province Center for Disease Control and Prevention, Zhengzhou, China
| | - Wei Fan
- Henan Province Center for Disease Control and Prevention, Zhengzhou, China
| | - Xueyong Huang
- College of Public Health, Zhengzhou University, Zhengzhou, China
- * E-mail:
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12
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Li P, Rui J, Niu Y, Xie F, Wang Y, Li Z, Liu C, Yu S, Huang J, Luo L, Deng B, Liu W, Yang T, Li Q, Chen T. Analysis of HFMD Transmissibility Among the Whole Population and Age Groups in a Large City of China. Front Public Health 2022; 10:850369. [PMID: 35480581 PMCID: PMC9035867 DOI: 10.3389/fpubh.2022.850369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 03/02/2022] [Indexed: 11/29/2022] Open
Abstract
Background Hand-Foot-and-Mouth-Disease (HFMD) has been widely spread in Asia, and has result in a high disease burden for children in many countries. However, the dissemination characteristics intergroup and between different age groups are still not clear. In this study, we aim to analyze the differences in the transmissibility of HFMD, in the whole population and among age groups in Shenzhen city, by utilizing mathematical models. Methods A database that reports HFMD cases in Shenzhen city from January 2010 to December 2017 was collected. In the first stage, a Susceptive-Infected-Recovered (SIR) model was built to fit data of Shenzhen city and its districts, and Reff was used to assess transmissibility in each district. In the second stage, a cross-age groups SIR model was constructed to calculate the difference in transmissibility of reported cases among three age groups of EV71 virus: 0–3 years, 3–5 years, and over 5 years which was denoted as age group 1, 2, and 3, respectively. Results From 2010 to 2017, 345,807 cases of HFMD were reported in Shenzhen city, with peak incidence in spring and autumn in Shenzhen city and most of its districts each year. Analysis of the EV71 incidence data by age group revealed that age Group 1 have the highest incidence (3.13 ×10−7–2.31 ×10−4) while age group 3 had the lowest incidence (0–3.54 ×10−5). The differences in weekly incidence of EV71 between age groups were statistically significant (t12 = 7.563, P < 0.0001; t23 = 12.420, P < 0.0001; t13 = 16.996, P < 0.0001). The R2 of the SIR model Shenzhen city population-wide HFMD fit for each region was >0.5, and P < 0.001. Reff values were >1 for the vast majority of time and regions, indicating that the HFMD virus has the ability to spread in Shenzhen city over the long-term. Differences in Reff values between regions were judged by using analysis of variance (ANOVA) (F = 0.541, P = 0.744). SiIiRi-SjIjRj models between age groups had R2 over 0.7 for all age groups and P <0.001. The Reff values between groups show that the 0–2 years old group had the strongest transmissibility (median: 2.881, range: 0.017–9.897), followed by the over 5 years old group (median: 1.758, range: 1.005–5.279), while the 3–5 years old group (median: 1.300, range: 0.005–1.005) had the weakest transmissibility of the three groups. Intra-group transmissibility was strongest in the 0–2 years age group (median: 1.787, range: 0–9.146), followed by Group 1 to Group 2 (median: 0.287, range: 0–1.988) and finally Group 1 to Group 3 (median: 0.287, range: 0–1.988). Conclusion The incidence rate of HFMD is high in Shenzhen city. In the data on the incidence of EV71 in each age group, the highest incidence was in the 0–2 years age group, and the lowest incidence was in the over 5 years age group. The differences in weekly incidence rate of EV71 among age groups were statistically significant. Children with the age of 0–2 years had the highest transmissibility.
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Affiliation(s)
- Peihua Li
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Jia Rui
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Yan Niu
- Chinese Center for Disease Control and Prevention, Public Health Emergency Center, Beijing, China
| | - Fang Xie
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Yifang Wang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Zhuoyang Li
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Chan Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Shanshan Yu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Jiefeng Huang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Li Luo
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Bin Deng
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Weikang Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Tianlong Yang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Qun Li
- Chinese Center for Disease Control and Prevention, Public Health Emergency Center, Beijing, China
- Qun Li
| | - Tianmu Chen
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
- *Correspondence: Tianmu Chen ;
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Liu R, Cai J, Guo W, Guo W, Wang W, Yan L, Ma N, Zhang X, Zhang S. Effects of temperature and PM 2.5 on the incidence of hand, foot, and mouth in a heavily polluted area, Shijiazhuang, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:11801-11814. [PMID: 34550518 DOI: 10.1007/s11356-021-16397-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 09/03/2021] [Indexed: 06/13/2023]
Abstract
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, PM2.5, 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 PM2.5 between 76 and 200 μg/m3 has a certain risk of the onset of hand, foot, and mouth disease, but the extreme PM2.5 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.
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Affiliation(s)
- Ran Liu
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, 361 Zhongshan East Road, Shijiazhuang, 050017, China
| | - Jianning Cai
- The Department of Epidemic Treating and Preventing, Center for Disease Prevention and Control of Shijiazhuang City, Likang Road 3#, Shijiazhuang, 050011, China
| | - Weiheng Guo
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, 361 Zhongshan East Road, Shijiazhuang, 050017, China
| | - Wei Guo
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, 361 Zhongshan East Road, Shijiazhuang, 050017, China
| | - Wenjuan Wang
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, 361 Zhongshan East Road, Shijiazhuang, 050017, China
| | - Lina Yan
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, 361 Zhongshan East Road, Shijiazhuang, 050017, China
| | - Ning Ma
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, 361 Zhongshan East Road, Shijiazhuang, 050017, China
| | - Xiaolin Zhang
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, 361 Zhongshan East Road, Shijiazhuang, 050017, China.
| | - Shiyong Zhang
- The Department of Epidemic Treating and Preventing, Center for Disease Prevention and Control of Shijiazhuang City, Likang Road 3#, Shijiazhuang, 050011, China.
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