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Zhang K, Shen G, Yuan Y, Shi C. Association Between Climatic Factors and Varicella Incidence in Wuxi, East China, 2010-2019: Surveillance Study. JMIR Public Health Surveill 2024; 10:e62863. [PMID: 39228304 PMCID: PMC11483255 DOI: 10.2196/62863] [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: 06/03/2024] [Revised: 08/18/2024] [Accepted: 09/02/2024] [Indexed: 09/05/2024] Open
Abstract
BACKGROUND Varicella is a common infectious disease and a growing public health concern in China, with increasing outbreaks in Wuxi. Analyzing the correlation between climate factors and varicella incidence in Wuxi is crucial for guiding public health prevention efforts. OBJECTIVE This study examines the impact of meteorological variables on varicella incidence in Wuxi, eastern China, from 2010 to 2019, offering insights for public health interventions. METHODS We collected daily meteorological data and varicella case records from January 1, 2010, to December 31, 2019, in Wuxi, China. Generalized cross-validation identified optimal lag days by selecting those with the lowest score. The relationship between meteorological factors and varicella incidence was analyzed using Poisson generalized additive models and segmented linear regression. Subgroup analyses were conducted by gender and age. RESULTS The study encompassed 64,086 varicella cases. Varicella incidence in Wuxi city displayed a bimodal annual pattern, with peak occurrences from November to January of the following year and lower peaks from May to June. Several meteorological factors influencing varicella risk were identified. A decrease of 1°C when temperatures were ≤20°C corresponded to a 1.99% increase in varicella risk (95% CI 1.57-2.42, P<.001). Additionally, a decrease of 1°C below 22.38°C in ground temperature was associated with a 1.36% increase in varicella risk (95% CI 0.96-1.75, P<.001). Each 1 mm increase in precipitation above 4.88 mm was associated with a 1.62% increase in varicella incidence (95% CI 0.93-2.30, P<.001). A 1% rise in relative humidity above 57.18% increased varicella risk by 2.05% (95% CI 1.26-2.84, P<.001). An increase in air pressure of 1 hPa below 1011.277 hPa was associated with a 1.75% rise in varicella risk (95% CI 0.75-2.77, P<.001). As wind speed and evaporation increased, varicella risk decreased linearly with a 16-day lag. Varicella risk was higher with sunshine durations exceeding 1.825 hours, with a 14-day lag, increasing by 1.30% for each additional hour of sunshine (95% CI 0.62-2.00, P=.006). Subgroup analyses revealed that teenagers and children under 17 years of age faced higher varicella risks associated with temperature, average ground temperature, precipitation, relative humidity, and air pressure. Adults aged 18-64 years experienced increased risk with longer sunshine durations. Additionally, males showed higher varicella risks related to ground temperature and air pressure compared with females. However, no significant gender differences were observed regarding varicella risks associated with temperature (male: P<.001; female P<.001), precipitation (male: P=.001; female: P=.06), and sunshine duration (male: P=.53; female: P=.04). CONCLUSIONS Our preliminary findings highlight the interplay between varicella outbreaks in Wuxi city and meteorological factors. These insights provide valuable support for developing policies aimed at reducing varicella risks through informed public health measures.
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Affiliation(s)
- Kehong Zhang
- Department of Public Health, Wuxi Hospital Affiliated to Nanjing University of Chinese Medicine, Wuxi, China
| | - Ganglei Shen
- Department of Public Health, Wuxi Hospital Affiliated to Nanjing University of Chinese Medicine, Wuxi, China
| | - Yue Yuan
- President Office, Wuxi Hospital Affiliated to Nanjing University of Chinese Medicine, Wuxi, China
| | - Chao Shi
- Department of Acute Infectious Disease, Wuxi Center for Disease Control and Prevention, Wuxi, China
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Luan G, Hu Y, Chen M, You M, Xu C, Yin D, Liu J, Yao H. Associations Between Air Temperature and Daily Varicella Cases - Jinan City, Shandong Province, China, 2019-2021. China CDC Wkly 2024; 6:36-39. [PMID: 38250698 PMCID: PMC10797300 DOI: 10.46234/ccdcw2024.008] [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: 12/12/2023] [Accepted: 01/05/2024] [Indexed: 01/23/2024] Open
Abstract
What is already known about this topic? The impact of air temperature on varicella has been studied, but there is limited research exploring its effect on varicella by gender and age group. What is added by this report? We conducted a time series analysis to examine the differential effects of air temperature on varicella infection across different demographic groups. Our findings indicate that lower temperatures have a more pronounced influence on varicella incidence among males and children compared to females and adults. What are the implications for public health practice? These findings can assist in identifying populations that are vulnerable to temperature-related varicella and in guiding the implementation of effective measures for varicella control.
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Affiliation(s)
- Guijie Luan
- Chinese Center for Disease Control and Prevention, Beijing, China
- Institute for Immunization management, Shandong Center for Disease Control and Prevention, Jinan City, Shandong Province, China
| | - Yuehua Hu
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Meng Chen
- Institute for Immunization management, Shandong Center for Disease Control and Prevention, Jinan City, Shandong Province, China
| | - Meiying You
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Chengdong Xu
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Dapeng Yin
- Hainan Provincial Center for Disease Control and Prevention, Haikou City, Hainan Province, China
| | - Jianjun Liu
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Hongyan Yao
- Chinese Center for Disease Control and Prevention, Beijing, China
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Wang H, Huang S, Wang Z, Zhen H, Li Z, Fan W, Lu M, Han X, Du L, Zhao M, Yan Y, Zhang X, Zhen Q, Shui T. Association between meteorological factors and varicella incidence: a multicity study in Yunnan Province, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:117817-117828. [PMID: 37874521 DOI: 10.1007/s11356-023-30457-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 10/09/2023] [Indexed: 10/25/2023]
Abstract
This multicenter study aimed to investigate the relationship between varicella incidence and meteorological factors including mean temperature, relative humidity, sunshine duration, diurnal temperature difference, wind speed, and rainfall, as previous studies have produced varying results. Our study also sought to identify potential sources of heterogeneity. Data on reported daily varicella numbers and meteorological factors were collected for 14 cities in Yunnan Province from 2017 to 2021. A distribution-lagged nonlinear model was constructed to explore the relationship between meteorological conditions and varicella incidence in each included city. We then used multiple meta-regression to explore sources of heterogeneity using demographic economics indicators, air pollutants, and geographic location as potential modifiers. The cumulative hazard effect plot showed an inverted S-shape for the relationship between temperature and varicella, with the smallest RR (relative risk) (0.533, 95% CI: 0.401-0.708) at temperatures up to 27.2 °C. The maximum RR (1.171, 95% CI: 1.001-1.371) was obtained when the relative humidity was equal to 98.5%. The RR (1.164, 95% CI: 1.002-1.352) was greatest at a diurnal temperature range of 2 °C (1.164, 95% CI: 1.002-1.352) and least (0.913, 95% CI: 0.834-0.999) at a diurnal temperature range of 16.1 °C. The maximum RR (1.214, 95% CI: 1.089-1.354) was obtained at 0 h of sunshine, and the minimum RR (0.808, 95% CI: 0.675-0.968) was obtained at 12.4 h of sunshine. The RR (0.792, 95% CI: 0.633-0.992) was minimum at a wind velocity of 4.8 m/s. Residual heterogeneity ranged from 1 to 42.7%, with PM10 (particles with an aerodynamic diameter less than 10 μm), GDP (gross domestic product), and population density explaining some of this heterogeneity. The temperature has a dual effect on varicella incidence. Varicella cases are negatively correlated with diurnal temperature range, sunshine duration, and wind speed, and positively correlated with relative humidity. GDP and PM10 may have a significant role in altering the association between temperature and varicella, while PM10 and population density may alter the association between wind velocity and varicella.
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Affiliation(s)
- Hao Wang
- Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis, Ministry of Education, School of Public Health, Jilin University, Changchun, Jilin, China
- State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonoses Research of the Ministry of Education, Changchun, China
| | - Shanjun Huang
- Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis, Ministry of Education, School of Public Health, Jilin University, Changchun, Jilin, China
| | - Zhaohan Wang
- Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis, Ministry of Education, School of Public Health, Jilin University, Changchun, Jilin, China
| | - Hua Zhen
- Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis, Ministry of Education, School of Public Health, Jilin University, Changchun, Jilin, China
| | - Zhuo Li
- Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis, Ministry of Education, School of Public Health, Jilin University, Changchun, Jilin, China
| | - Wenqi Fan
- Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis, Ministry of Education, School of Public Health, Jilin University, Changchun, Jilin, China
| | - Menghan Lu
- Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis, Ministry of Education, School of Public Health, Jilin University, Changchun, Jilin, China
| | - Xin Han
- Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis, Ministry of Education, School of Public Health, Jilin University, Changchun, Jilin, China
| | - Lanping Du
- Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis, Ministry of Education, School of Public Health, Jilin University, Changchun, Jilin, China
| | - Meifang Zhao
- Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis, Ministry of Education, School of Public Health, Jilin University, Changchun, Jilin, China
| | - Yuke Yan
- Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis, Ministry of Education, School of Public Health, Jilin University, Changchun, Jilin, China
| | - Xinyao Zhang
- Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis, Ministry of Education, School of Public Health, Jilin University, Changchun, Jilin, China
- Department of Social Medicine and Health Care Management, School of Public Health, Jilin University, Changchun, China
| | - Qing Zhen
- Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis, Ministry of Education, School of Public Health, Jilin University, Changchun, Jilin, China.
- State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonoses Research of the Ministry of Education, Changchun, China.
| | - Tiejun Shui
- Yunnan Center for Disease Control and Prevention, Kunming, Yunnan, China
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Zhang T, Qin W, Nie T, Zhang D, Wu X. Effects of meteorological factors on the incidence of varicella in Lu'an, Eastern China, 2015-2020. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:10052-10062. [PMID: 36066801 DOI: 10.1007/s11356-022-22878-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Accepted: 08/31/2022] [Indexed: 06/15/2023]
Abstract
Varicella (chickenpox) is a serious public health problem in China, with the most reported cases among childhood vaccine-preventable infectious diseases, and its reported incidence has increased over 20-fold since 2005. Few previous studies have explored the association of multiple meteorological factors with varicella and considered the potential confounding effects of air pollutants. It is the first study to investigate and analyze the effects of multiple meteorological factors on varicella incidence, controlling for the confounding effects of various air pollutants. Daily meteorological and air pollution data and varicella cases were collected from January 1, 2015, to December 31, 2020, in Lu'an, Eastern China. A combination of the quasi-Poisson generalized additive model (GAM) and distributed lag nonlinear model (DLNM) was used to evaluate the meteorological factor-lag-varicella relationship, and the risk of varicella in extreme meteorological conditions. The maximum single-day lag effects of varicella were 1.288 (95%CI, 1.201-1.381, lag 16 day), 1.475 (95%CI, 1.152-1.889, lag 0 day), 1.307 (95%CI, 1.196-1.427, lag 16 day), 1.271 (95%CI, 0.981-1.647, lag 4 day), and 1.266 (95%CI, 1.162-1.378, lag 21 day), when mean temperature, diurnal temperature range (DTR), mean air pressure, wind speed, and sunshine hours were -5.8°C, 13.5°C, 1035.5 hPa, 6 m/s, and 0 h, respectively. At the maximum lag period, the overall effects of mean temperature and pressure on varicella showed W-shaped curves, peaked at 17.5°C (RR=2.085, 95%CI: 1.480-2.937) and 1035.5 hPa (RR=5.481, 95%CI: 1.813-16.577), while DTR showed an M-shaped curve and peaked at 4.4°C (RR=6.131, 95%CI: 1.120-33.570). Sunshine hours were positively correlated with varicella cases at the lag of 0-8 days and 0-9 days when sunshine duration exceeded 10 h. Furthermore, the lag effects of extreme meteorological factors on varicella cases were statistically significant, except for the extremely high wind speed. We found that mean temperature, mean air pressure, DTR, and sunshine hours had significant nonlinear effects on varicella incidence, which may be important predictors of varicella early warning.
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Affiliation(s)
- Tingting Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Wei Qin
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Department of Expanded Program on Immunization, Lu'an Municipal Center for Disease Control and Prevention, Lu'an, 237000, Anhui, China
| | - Tingyue Nie
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Deyue Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Xuezhong Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China.
- The First Affiliated Hospital of Anhui University of Science and Technology, Huainan, 232000, Anhui, China.
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Costa ACTRB, Pereira CR, Sáfadi T, Heinemann MB, Dorneles EMS. Climate influence the human leptospirosis cases in Brazil, 2007-2019: a time series analysis. Trans R Soc Trop Med Hyg 2021; 116:124-132. [PMID: 34192338 DOI: 10.1093/trstmh/trab092] [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: 06/03/2021] [Accepted: 06/03/2021] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Human leptospirosis is responsible for great losses and deaths, especially in developing countries, which can be mitigated by knowing the correct health indicators and climate influence on the disease. METHODS Leptospirosis cases and deaths, population and precipitation were recovered from different databases (2007-2019). Annual incidence, mortality and case fatality rates (CFRs) of human leptospirosis and average precipitation were calculated for Brazil and its regions. Time series analysis using an moving average with external variable (ARMAX) model was used to analyse the monthly contribution and precipitation influence over leptospirosis cases for each Brazilian region and for the whole country. A forecast model to predict cases for 2020 was created for Brazil. RESULTS Human leptospirosis exhibited heterogeneous distribution among Brazilian regions, with most cases occurring during the rainy season and precipitation influenced the disease occurrence in all regions but the South. The forecast model predicted 3276.99 cases for 2020 (mean absolute percentage error 14.680 and root mean square error 53.013). Considering the annual average for the period, the leptospirosis incidence was 1913 cases per 100 000 inhabitants, mortality was 0.168 deaths per 100 000 inhabitants and the CFR was 8.83%. CONCLUSIONS The models built can be useful for planning leptospirosis surveillance and control actions for the whole country and its regions and, together with the health indicators, revealed no uniform epidemiological situation of leptospirosis in Brazil.
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Affiliation(s)
| | - Carine Rodrigues Pereira
- Departamento de Medicina Veterinária, Universidade Federal de Lavras, Lavras, 37200-900, Minas Gerais, Brazil
| | - Thelma Sáfadi
- Departamento de Estatística, Universidade Federal de Lavras, Lavras, 37200-900, Minas Gerais, Brazil
| | - Marcos Bryan Heinemann
- Departamento de Medicina Veterinária Preventiva e Saúde Animal, Faculdade de Medicina Veterinária e Zootecnia, Universidade de São Paulo, São Paulo, 05508-270, São Paulo, Brazil
| | - Elaine Maria Seles Dorneles
- Departamento de Medicina Veterinária, Universidade Federal de Lavras, Lavras, 37200-900, Minas Gerais, Brazil
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Lu JY, Zhang ZB, He Q, Ma XW, Yang ZC. Association between climatic factors and varicella incidence in Guangzhou, Southern China, 2006-2018. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 728:138777. [PMID: 32330739 DOI: 10.1016/j.scitotenv.2020.138777] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Revised: 04/15/2020] [Accepted: 04/16/2020] [Indexed: 06/11/2023]
Abstract
OBJECTIVE To analyze the correlation between climatic factors and the incidence of varicella in Guangzhou, and improve the prevention measures about public health. METHODS Data for daily climatic variables and varicella incidence from 2006 to 2018 in Guangzhou were collected from the Guangzhou Meteorological Bureau and the National Notifiable Disease Report System. Distributed lag nonlinear models were applied to evaluate the association between climatic factors and varicella incidence. RESULTS The nonlinear effects of meteorological factors were observed. At lag day21,when the mean temperature was 31.8 °C, the relative risk was the highest as 1.11 (95% CI: 1.07-1.16). When the diurnal temperature range was 24.0 °C at lag day 20, the highest RR was 1.11 (95% CI: 1.05-1.17). For rainfall, the highest RR was 1.09 (95% CI: 1.01-1.19) at lag day 21,when the aggregate rainfall was 160 mm. When air pressure was 1028 hPa, the highest RR was 1.08 (95% CI: 1.04-1.13) at lag day 21. When wind speed was 0.7 m/s, the highest RR was 1.07 (95% CI: 1.04-1.11) at lag day 7. When the hours of sunshine were 9.0 h at lag day 21, the RR was highest as 1.04 (95% CI: 1.02-1.05). Aggregate rainfall, air pressure, and sunshine hours were positively correlated with the incidence of varicella, which was inconsistent with the wind velocity. Mean temperature showed a reverse U-shape curve relationship with varicella, while the diurnal temperature range showed a binomial distribution curve. The extreme effect of climatic factors on the varicella cases was statistically significant, apart from the extremely low effect of rainfall. CONCLUSION Our preliminary results offered fundamental knowledge which might be benefit to give an insight into epidemic trends of varicella and develop an early warning system. We could use our findings about influential factors to strengthen the intervention and prevention of varicella.
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Affiliation(s)
- Jian-Yun Lu
- Department of Infectious Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Baiyun District Qi De Road in Guangzhou, Guangdong Province 510440, China
| | - Zhou-Bin Zhang
- Guangzhou Center for Disease Control and Prevention, Baiyun District Qi De Road in Guangzhou, Guangdong Province 510440, China
| | - Qing He
- Department of Infectious Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Baiyun District Qi De Road in Guangzhou, Guangdong Province 510440, China
| | - Xiao-Wei Ma
- Department of Public Health Emergency Preparedness and Response, Guangzhou Center for Disease Control and Prevention, Baiyun District Qi De Road in Guangzhou, Guangdong Province 510440, China
| | - Zhi-Cong Yang
- Guangzhou Center for Disease Control and Prevention, Baiyun District Qi De Road in Guangzhou, Guangdong Province 510440, China.
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Todorova TT. Seasonal dynamics of varicella incidence in Bulgaria. Future Virol 2020. [DOI: 10.2217/fvl-2020-0012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Aim: Spatial and temporal distribution of varicella is heterogenic and insufficiently studied in Europe. The present study tries to fill the gap that exists about the seasonality of the infection in Bulgaria. Materials & methods: A 4-year retrospective study of the monthly and seasonal varicella epidemiology was performed at both national and district level. Results: In Bulgaria, varicella incidence peaked during winter (37% of the 2015–2018 cases), followed by spring (33%) and autumn (23%). Highly populated districts were more likely to follow this pattern, while less inhabited districts with smaller urbanized areas showed different periodicity of the infection. Conclusion: Winter peak in varicella incidence is positively associated with high accumulation of people in the large cities (>75,000 inhabitants).
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Affiliation(s)
- Tatina T Todorova
- Department of Microbiology & Virology, Medical University Varna, Faculty of Medicine, Varna, Bulgaria
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Basile L, Oviedo de la Fuente M, Torner N, Martínez A, Jané M. Real-time predictive seasonal influenza model in Catalonia, Spain. PLoS One 2018. [PMID: 29513710 PMCID: PMC5841785 DOI: 10.1371/journal.pone.0193651] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
Influenza surveillance is critical to monitoring the situation during epidemic seasons and predictive mathematic models may aid the early detection of epidemic patterns. The objective of this study was to design a real-time spatial predictive model of ILI (Influenza Like Illness) incidence rate in Catalonia using one- and two-week forecasts. The available data sources used to select explanatory variables to include in the model were the statutory reporting disease system and the sentinel surveillance system in Catalonia for influenza incidence rates, the official climate service in Catalonia for meteorological data, laboratory data and Google Flu Trend. Time series for every explanatory variable with data from the last 4 seasons (from 2010–2011 to 2013–2014) was created. A pilot test was conducted during the 2014–2015 season to select the explanatory variables to be included in the model and the type of model to be applied. During the 2015–2016 season a real-time model was applied weekly, obtaining the intensity level and predicted incidence rates with 95% confidence levels one and two weeks away for each health region. At the end of the season, the confidence interval success rate (CISR) and intensity level success rate (ILSR) were analysed. For the 2015–2016 season a CISR of 85.3% at one week and 87.1% at two weeks and an ILSR of 82.9% and 82% were observed, respectively. The model described is a useful tool although it is hard to evaluate due to uncertainty. The accuracy of prediction at one and two weeks was above 80% globally, but was lower during the peak epidemic period. In order to improve the predictive power, new explanatory variables should be included.
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Affiliation(s)
- Luca Basile
- Public Health Agency of Catalonia, Barcelona, Spain
| | - Manuel Oviedo de la Fuente
- Technological Institute for Industrial Mathematics (ITMATI), Campus Vida, Santiago de Compostela, Spain
- MODESTYA Group, Department of Statistics, Mathematical Analysis and Optimization, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Nuria Torner
- Public Health Agency of Catalonia, Barcelona, Spain
- Department of Medicine, University of Barcelona Barcelona, Spain
- CIBER Epidemiology and Public Health CIBERESP, Carlos III Health Institute, Madrid, Spain
- * E-mail:
| | - Ana Martínez
- Public Health Agency of Catalonia, Barcelona, Spain
- CIBER Epidemiology and Public Health CIBERESP, Carlos III Health Institute, Madrid, Spain
| | - Mireia Jané
- Public Health Agency of Catalonia, Barcelona, Spain
- CIBER Epidemiology and Public Health CIBERESP, Carlos III Health Institute, Madrid, Spain
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Hervás D, Hervás-Masip J, Ferrés L, Ramírez A, Pérez JL, Hervás JA. Effects of meteorologic factors and schooling on the seasonality of group A streptococcal pharyngitis. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2016; 60:763-769. [PMID: 26446674 DOI: 10.1007/s00484-015-1072-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2015] [Revised: 08/20/2015] [Accepted: 09/23/2015] [Indexed: 06/05/2023]
Abstract
The objective of this study was to determine the seasonal pattern of group A streptococcal pharyngitis in children attended at a hospital emergency department in the Mediterranean island of Mallorca (Spain), and its association with meteorologic factors and schooling. We conducted a retrospective review of the medical records of children aged 1-15 years with a diagnosis of Streptococcus pyogenes pharyngitis between January 2006 and December 2011. The number of S. pyogenes pharyngitis was correlated to temperature, humidity, rainfall, atmospheric pressure, wind speed, solar radiation, and schooling, using regression and time series techniques. A total of 906 patients (median, 4 years old) with S. pyogenes pharyngitis, confirmed by throat culture, were attended during the study period. A seasonal pattern was observed with a peak activity in June and a minimum in September. Mean temperature, solar radiation, and school holidays were the best predicting variables (R(2) = 0.68; p < 0.001). S. pyogenes activity increased with the decrease of mean temperature (z = -2.4; p < 0.05), the increase of solar radiation (z = 4.2; p < 0.001), and/or the decrease in school holidays (z = -2.4; p < 0.05). In conclusion, S. pyogenes pharyngitis had a clear seasonality predominating in springtime, and an association with mean temperature, solar radiation, and schooling was observed. The resulting model predicted 68 % of S. pyogenes pharyngitis.
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Affiliation(s)
- Daniel Hervás
- University Institute for Health Sciences Research, IUNICS, University of the Balearic Islands, Palma de Mallorca, Spain
- IdISPa, Departments of Pediatrics and Microbiology, Son Espases University Hospital, Palma de Mallorca, Spain
| | - Juan Hervás-Masip
- University Institute for Health Sciences Research, IUNICS, University of the Balearic Islands, Palma de Mallorca, Spain
| | - Laia Ferrés
- Departments of Pediatrics, Son Espases University Hospital, Ctra Valldemosa 79, Palma de Mallorca, 07010, Spain
| | - Antonio Ramírez
- Departments of Microbiology, Son Espases University Hospital, Palma de Mallorca, Spain
| | - José L Pérez
- Departments of Microbiology, Son Espases University Hospital, Palma de Mallorca, Spain
| | - Juan A Hervás
- University Institute for Health Sciences Research, IUNICS, University of the Balearic Islands, Palma de Mallorca, Spain.
- IdISPa, Departments of Pediatrics and Microbiology, Son Espases University Hospital, Palma de Mallorca, Spain.
- Departments of Pediatrics, Son Espases University Hospital, Ctra Valldemosa 79, Palma de Mallorca, 07010, Spain.
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Yang Y, Geng X, Liu X, Wang W, Zhang J. Association between the incidence of varicella and meteorological conditions in Jinan, Eastern China, 2012-2014. BMC Infect Dis 2016; 16:179. [PMID: 27102884 PMCID: PMC4840874 DOI: 10.1186/s12879-016-1507-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2015] [Accepted: 04/11/2016] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND Varicella remains an important public health issue in China. In this study we explored the effect of weather conditions on the incidence of varicella in the temperate city of Jinan, Eastern China during 2012-2014 to inform public health prevention and control measures. METHODS Data on reported cases of varicella were obtained from National Notifiable Disease Report System. Meteorological data for the same time period were obtained from the Jinan Meteorological Bureau. A negative binomial regression model was used to assess the relationships between meteorological variables and the incidence of varicella. Given collinearity between average temperature and atmospheric pressure, separate models were constructed: one including average temperature without atmospheric pressure, the other including atmospheric pressure but without average temperature. Both models included relative humidity, wind velocity, rainfall, sunshine, and year as independent variables. RESULTS Annual incidence rates of varicella were 44.47, 53.69, and 46.81 per 100,000 for 2012, 2013, and 2014, respectively. Each increase of 100 Pa (hPa) in atmospheric pressure was estimated to be associated with an increase in weekly incidence of 3.35 % (95 % CI = 2.94-3.67 %), while a 1 °C rise in temperature was associated with a decrease of 3.44 % (95 % CI = -3.73-3.15 %) in the weekly incidence of varicella. Similarly, a 1 % rise in relative humidity corresponded to a decrease of 0.50 % or 1.00 %, a 1 h rise in sunshine corresponded to an increase of 1.10 % or 0.50 %, and a 1 mm rise in rainfall corresponded to an increase of 0.20 % or 0.30 %, in the weekly incidence of varicella cases, depending on the variable considered in the model. CONCLUSION Our findings show that weather factors have a significant influence on the incidence of varicella. Meteorological conditions should be considered as important predictors of varicella incidence in Jinan, Eastern China.
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Affiliation(s)
- Yunqing Yang
- />Faculty of Public Health, Shandong University, Shandong Province, 250100 P. R. China
| | - Xingyi Geng
- />Jinan Center for Disease Control and Prevention, Shandong Province, 250021 P. R. China
| | - Xiaoxue Liu
- />Jinan Center for Disease Control and Prevention, Shandong Province, 250021 P. R. China
| | - Weiru Wang
- />Jinan Center for Disease Control and Prevention, Shandong Province, 250021 P. R. China
| | - Ji Zhang
- />Jinan Center for Disease Control and Prevention, Shandong Province, 250021 P. R. China
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