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Castro Blanco E, Dalmau Llorca MR, Aguilar Martín C, Carrasco-Querol N, Gonçalves AQ, Hernández Rojas Z, Coma E, Fernández-Sáez J. A Predictive Model of the Start of Annual Influenza Epidemics. Microorganisms 2024; 12:1257. [PMID: 39065025 PMCID: PMC11278734 DOI: 10.3390/microorganisms12071257] [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: 05/31/2024] [Revised: 06/14/2024] [Accepted: 06/17/2024] [Indexed: 07/28/2024] Open
Abstract
Influenza is a respiratory disease that causes annual epidemics during cold seasons. These epidemics increase pressure on healthcare systems, sometimes provoking their collapse. For this reason, a tool is needed to predict when an influenza epidemic will occur so that the healthcare system has time to prepare for it. This study therefore aims to develop a statistical model capable of predicting the onset of influenza epidemics in Catalonia, Spain. Influenza seasons from 2011 to 2017 were used for model training, and those from 2017 to 2018 were used for validation. Logistic regression, Support Vector Machine, and Random Forest models were used to predict the onset of the influenza epidemic. The logistic regression model was able to predict the start of influenza epidemics at least one week in advance, based on clinical diagnosis rates of various respiratory diseases and meteorological variables. This model achieved the best punctual estimates for two of three performance metrics. The most important variables in the model were the principal components of bronchiolitis rates and mean temperature. The onset of influenza epidemics can be predicted from clinical diagnosis rates of various respiratory diseases and meteorological variables. Future research should determine whether predictive models play a key role in preventing influenza.
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Affiliation(s)
- Elisabet Castro Blanco
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain; (E.C.B.); (N.C.-Q.); (A.Q.G.); (Z.H.R.); (J.F.-S.)
- Campus Terres de l’Ebre, Universitat Rovira i Virgili, 43500 Tortosa, Spain
- Terres de l’Ebre Research Support Unit, Foundation University Institute for Primary Health Care Research Jordi Gol i Gurina (IDIAPJGol), 43500 Tortosa, Spain
| | - Maria Rosa Dalmau Llorca
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain; (E.C.B.); (N.C.-Q.); (A.Q.G.); (Z.H.R.); (J.F.-S.)
- Campus Terres de l’Ebre, Universitat Rovira i Virgili, 43500 Tortosa, Spain
- Servei d’Atenció Primària Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
| | - Carina Aguilar Martín
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain; (E.C.B.); (N.C.-Q.); (A.Q.G.); (Z.H.R.); (J.F.-S.)
- Terres de l’Ebre Research Support Unit, Foundation University Institute for Primary Health Care Research Jordi Gol i Gurina (IDIAPJGol), 43500 Tortosa, Spain
- Unitat d’Avaluació, Direcció d’Atenció Primària Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
| | - Noèlia Carrasco-Querol
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain; (E.C.B.); (N.C.-Q.); (A.Q.G.); (Z.H.R.); (J.F.-S.)
- Terres de l’Ebre Research Support Unit, Foundation University Institute for Primary Health Care Research Jordi Gol i Gurina (IDIAPJGol), 43500 Tortosa, Spain
| | - Alessandra Queiroga Gonçalves
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain; (E.C.B.); (N.C.-Q.); (A.Q.G.); (Z.H.R.); (J.F.-S.)
- Terres de l’Ebre Research Support Unit, Foundation University Institute for Primary Health Care Research Jordi Gol i Gurina (IDIAPJGol), 43500 Tortosa, Spain
| | - Zojaina Hernández Rojas
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain; (E.C.B.); (N.C.-Q.); (A.Q.G.); (Z.H.R.); (J.F.-S.)
- Servei d’Atenció Primària Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
| | - Ermengol Coma
- Primary Healthcare Information Systems, Health Institute of Catalonia, 08007 Catalonia, Spain;
| | - José Fernández-Sáez
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain; (E.C.B.); (N.C.-Q.); (A.Q.G.); (Z.H.R.); (J.F.-S.)
- Terres de l’Ebre Research Support Unit, Foundation University Institute for Primary Health Care Research Jordi Gol i Gurina (IDIAPJGol), 43500 Tortosa, Spain
- Servei d’Atenció Primària Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
- Unitat de Recerca, Gerència Territorial Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
- Unitat Docent de Medicina de Familia i Comunitària, Tortosa-Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
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Huang X, Abolt CJ, Bennett KE. How does humidity data impact land surface modeling of hydrothermal regimes at a permafrost site in Utqiaġvik, Alaska? THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:168697. [PMID: 37992842 DOI: 10.1016/j.scitotenv.2023.168697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 11/17/2023] [Accepted: 11/17/2023] [Indexed: 11/24/2023]
Abstract
Humidity is a basic and crucial meteorological indicator commonly measured in several forms, including specific humidity, relative humidity, and absolute humidity. These different forms can be inter-derived based on the saturation vapor pressure (SVP). In past decades, dozens of formulae have been developed to calculate the SVP with respect to, and in equilibrium with, liquid water and solid ice surfaces, but many prior studies use a single function for all temperature ranges, without considering the distinction between over the liquid water and ice surfaces. These different approaches can result in humidity estimates that may impact our understanding of surface-subsurface thermal-hydrological dynamics in cold regions. In this study, we compared the relative humidity (RH) downloaded and calculated from four data sources in Alaska based on five commonly used SVP formulas. These RHs, along with other meteorological indicators, were then used to drive physics-rich land surface models at a permafrost-affected site. We found that higher values of RH (up to 40 %) were obtained if the SVP was calculated with the over-ice formulation when air temperatures were below freezing, which could lead to a 30 % maximum difference in snow depths. The choice of whether to separately calculate the SVP over an ice surface in winter also produced a significant range (up to 0.2 m) in simulated annual maximum thaw depths. The sensitivity of seasonal thaw depth to the formulation of SVP increases with the rainfall rate and the height of above-ground ponded water, while it diminishes with warmer air temperatures. These results show that RH variations based on the calculation of SVP with or without over-ice calculation meaningfully impact physically-based predictions of snow depth, sublimation, soil temperature, and active layer thickness. Under particular conditions, when severe flooding (inundation) and cool air temperatures are present, care should be taken to evaluate how humidity data is estimated for land surface and earth system modeling.
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Affiliation(s)
- Xiang Huang
- Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.
| | - Charles J Abolt
- Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
| | - Katrina E Bennett
- Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
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Zhang L, Ma C, Duan W, Yuan J, Wu S, Sun Y, Zhang J, Liu J, Wang Q, Liu M. The role of absolute humidity in influenza transmission in Beijing, China: risk assessment and attributable fraction identification. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2024; 34:767-778. [PMID: 36649482 DOI: 10.1080/09603123.2023.2167948] [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: 06/10/2022] [Accepted: 01/09/2023] [Indexed: 06/17/2023]
Abstract
To assess the impact of absolute humidity on influenza transmission in Beijing from 2014 to 2019, we estimated the influenza transmissibility via the instantaneous reproduction number (Rt), and evaluated its nonlinear exposure-response association and delayed effects with absolute humidity by using the distributed lag nonlinear model (DLNM). Attributable fraction (AF) of Rt due to absolute humidity was calculated. The result showed a significant M-shaped relationship between Rt and absolute humidity. Compared with the effect of high absolute humidity, the low absolute humidity effect was more immediate with the most significant effect observed at lag 6 days. AFs were relatively high for the group aged 15-24 years, and was the lowest for the group aged 0-4 years with low absolute humidity. Therefore, we concluded that the component attributed to the low absolute humidity effect is greater. Young and middle-aged people are more sensitive to low absolute humidity than children and elderly.
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Affiliation(s)
- Li Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Institute for Infectious Disease and Endemic Disease Control, Beijing Center for Disease Prevention and Control, Beijing, China
| | - Chunna Ma
- Institute for Infectious Disease and Endemic Disease Control, Beijing Center for Disease Prevention and Control, Beijing, China
| | - Wei Duan
- Institute for Infectious Disease and Endemic Disease Control, Beijing Center for Disease Prevention and Control, Beijing, China
| | - Jie Yuan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Shuangsheng Wu
- Institute for Infectious Disease and Endemic Disease Control, Beijing Center for Disease Prevention and Control, Beijing, China
| | - Ying Sun
- Institute for Infectious Disease and Endemic Disease Control, Beijing Center for Disease Prevention and Control, Beijing, China
| | - Jiaojiao Zhang
- Institute for Infectious Disease and Endemic Disease Control, Beijing Center for Disease Prevention and Control, Beijing, China
| | - Jue Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Quanyi Wang
- Institute for Infectious Disease and Endemic Disease Control, Beijing Center for Disease Prevention and Control, Beijing, China
| | - Min Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
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Islam A, Munro S, Hassan MM, Epstein JH, Klaassen M. The role of vaccination and environmental factors on outbreaks of high pathogenicity avian influenza H5N1 in Bangladesh. One Health 2023; 17:100655. [PMID: 38116452 PMCID: PMC10728328 DOI: 10.1016/j.onehlt.2023.100655] [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: 09/30/2023] [Accepted: 11/08/2023] [Indexed: 12/21/2023] Open
Abstract
High Pathogenicity Avian Influenza (HPAI) H5N1 outbreaks continue to wreak havoc on the global poultry industry and threaten the health of wild bird populations, with sporadic spillover in humans and other mammals, resulting in widespread calls to vaccinate poultry. Bangladesh has been vaccinating poultry since 2012, presenting a prime opportunity to study the effects of vaccination on HPAI H5N1circulation in both poultry and wild birds. We investigated the efficacy of vaccinating commercial poultry against HPAI H5N1 along with climatic and socio-economic factors considered potential drivers of HPAI H5N1 outbreak risk in Bangladesh. Using a multivariate modeling approach, we estimated that the rate of outbreaks was 18 times higher before compared to after vaccination, with winter months having a three times higher chance of outbreaks than summer months. Variables resulting in small but significant increases in outbreak rate were relatively low ambient temperatures for the time of year, literacy rate, chicken and duck density, crop density, and presence of highways; this may be attributable to low temperatures supporting viral survival outside the host, higher literacy driving reporting rate, density of the host reservoir, and spread of the virus through increased connectivity. Despite the substantial impact of vaccination on outbreaks, we note that HPAI H5N1 is still enzootic in Bangladesh; vaccinated poultry flocks have high rates of H5N1 prevalence, and spillover to wild birds has increased. Vaccination in Bangladesh thus bears the risk of supporting "silent spread," where the vaccine only provides protection against disease and not also infection. Our findings underscore that poultry vaccination can be part of holistic HPAI mitigation strategies when accompanied by monitoring to avoid silent spread.
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Affiliation(s)
- Ariful Islam
- Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Melbourne, Victoria, Australia
- EcoHealth Alliance, New York, NY 10018, USA
| | | | - Mohammad Mahmudul Hassan
- Queensland Alliance for One Health Sciences, School of Veterinary Science, University of Queensland, Brisbane, QLD, Australia
- Faculty of Veterinary Medicine, Chattogram Veterinary and Animal Sciences University, Chattogram 4225, Bangladesh
| | | | - Marcel Klaassen
- Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Melbourne, Victoria, Australia
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Ito G, Takazono T, Hosogaya N, Iwanaga N, Miyazawa S, Fujita S, Watanabe H, Mukae H. Impact of meteorological and demographic factors on the influenza epidemic in Japan: a large observational database study. Sci Rep 2023; 13:13000. [PMID: 37563139 PMCID: PMC10415347 DOI: 10.1038/s41598-023-39617-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 07/27/2023] [Indexed: 08/12/2023] Open
Abstract
Factors affecting the start date of the influenza epidemic season and total number of infected persons per 1,000,000 population in 47 prefectures of Japan were evaluated. This retrospective observational study (September 2014-August 2019; N = 472,740-883,804) evaluated data from a Japanese health insurance claims database. Single and multiple regression analyses evaluated the time to start of the epidemic or total infected persons per 1,000,000 population with time to absolute humidity (AH) or number of days with AH (≤ 5.5, ≤ 6.0, ≤ 6.5, and ≤ 7.0), total visitors (first epidemic month or per day), and total population. For the 2014/15, 2015/16, and 2016/17 seasons, a weak-to-moderate positive correlation (R2: 0.042-0.417) was observed between time to start of the epidemic and time to first day with AH below the cutoff values. Except in the 2016/17 season (R2: 0.089), a moderate correlation was reported between time to start of the epidemic and the total population (R2: 0.212-0.401). For all seasons, multiple regression analysis showed negative R2 for time to start of the epidemic and total visitors and population density (positive for time to AH ≤ 7.0). The earlier the climate becomes suitable for virus transmission and the higher the human mobility (more visitors and higher population density), the earlier the epidemic season tends to begin.
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Affiliation(s)
- Genta Ito
- Data Science Department, Shionogi & Co., Ltd, Osaka, Japan
| | - Takahiro Takazono
- Department of Respiratory Medicine, Nagasaki University Hospital, Nagasaki, Japan.
| | - Naoki Hosogaya
- Department of Respiratory Medicine, Nagasaki University Hospital, Nagasaki, Japan
| | - Naoki Iwanaga
- Department of Respiratory Medicine, Nagasaki University Hospital, Nagasaki, Japan
| | - Shogo Miyazawa
- Data Science Department, Shionogi & Co., Ltd, Osaka, Japan
| | - Satoki Fujita
- Data Science Department, Shionogi & Co., Ltd, Osaka, Japan
| | | | - Hiroshi Mukae
- Department of Respiratory Medicine, Nagasaki University Hospital, Nagasaki, Japan
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Yang Y, Lian J, Jia X, Wang T, Fan J, Yang C, Wang Y, Bao J. Spatial distribution and driving factors of the associations between temperature and influenza-like illness in the United States: a time-stratified case-crossover study. BMC Public Health 2023; 23:1403. [PMID: 37474889 PMCID: PMC10360314 DOI: 10.1186/s12889-023-16240-3] [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: 02/04/2023] [Accepted: 07/04/2023] [Indexed: 07/22/2023] Open
Abstract
BACKGROUND Several previous studies investigated the associations between temperature and influenza in a single city or region without a national picture. The attributable risk of influenza due to temperature and the corresponding driving factors were unclear. This study aimed to evaluate the spatial distribution characteristics of attributable risk of Influenza-like illness (ILI) caused by adverse temperatures and explore the related driving factors in the United States. METHODS ILI, meteorological factors, and PM2.5 of 48 states in the United States were collected during 2011-2019. The time-stratified case-crossover design with a distributed lag non-linear model was carried out to evaluate the association between temperature and ILI at the state level. The multivariate meta-analysis was performed to obtain the combined effects at the national level. The attributable fraction (AF) was calculated to assess the ILI burden ascribed to adverse temperatures. The ordinary least square model (OLS), spatial lag model (SLM), and spatial error model (SEM) were utilized to identify driving factors. RESULTS A total of 7,716,115 ILI cases were included in this study. Overall, the temperature was negatively associated with ILI risk, and lower temperature gave rise to a higher risk of ILI. AF ascribed to adverse temperatures differed across states, from 49.44% (95% eCI: 36.47% ~ 58.68%) in Montana to 6.51% (95% eCI: -6.49% ~ 16.46%) in Wisconsin. At the national level, 29.08% (95% eCI: 27.60% ~ 30.24%) of ILI was attributable to cold. Per 10,000 dollars increase in per-capita income was associated with the increment in AF (OLS: β = -6.110, P = 0.021; SLM: β = -5.496, P = 0.022; SEM: β = -6.150, P = 0.022). CONCLUSION The cold could enhance the risk of ILI and result in a considerable proportion of ILI disease burden. The ILI burden attributed to cold varied across states and was higher in those states with lower economic status. Targeted prevention programs should be considered to lower the burden of influenza.
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Affiliation(s)
- Yongli Yang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Jiao Lian
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Xiaocan Jia
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Tianrun Wang
- School of Public Health, Jilin University, Changchun, 130021, Jilin, China
| | - Jingwen Fan
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Chaojun Yang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Yuping Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Junzhe Bao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China.
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Zhang R, Lai KY, Liu W, Liu Y, Cai W, Webster C, Luo L, Sarkar C. Association of climatic variables with risk of transmission of influenza in Guangzhou, China, 2005-2021. Int J Hyg Environ Health 2023; 252:114217. [PMID: 37418782 DOI: 10.1016/j.ijheh.2023.114217] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 06/16/2023] [Accepted: 06/29/2023] [Indexed: 07/09/2023]
Abstract
BACKGROUND Climatic variables constitute important extrinsic determinants of transmission and seasonality of influenza. Yet quantitative evidence of independent associations of viral transmissibility with climatic factors has thus far been scarce and little is known about the potential effects of interactions between climatic factors on transmission. OBJECTIVE This study aimed to examine the associations of key climatic factors with risk of influenza transmission in subtropical Guangzhou. METHODS Influenza epidemics were identified over a 17-year period using the moving epidemic method (MEM) from a dataset of N = 295,981 clinically- and laboratory-confirmed cases of influenza in Guangzhou. Data on eight key climatic variables were collected from China Meteorological Data Service Centre. Generalized additive model combined with the distributed lag non-linear model (DLNM) were developed to estimate the exposure-lag-response curve showing the trajectory of instantaneous reproduction number (Rt) across the distribution of each climatic variable after adjusting for depletion of susceptible, inter-epidemic effect and school holidays. The potential interaction effects of temperature, humidity and rainfall on influenza transmission were also examined. RESULTS Over the study period (2005-21), 21 distinct influenza epidemics with varying peak timings and durations were identified. Increasing air temperature, sunshine, absolute and relative humidity were significantly associated with lower Rt, while the associations were opposite in the case of ambient pressure, wind speed and rainfall. Rainfall, relative humidity, and ambient temperature were the top three climatic contributors to variance in transmissibility. Interaction models found that the detrimental association between high relative humidity and transmissibility was more pronounced at high temperature and rainfall. CONCLUSION Our findings are likely to help understand the complex role of climatic factors in influenza transmission, guiding informed climate-related mitigation and adaptation policies to reduce transmission in high density subtropical cities.
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Affiliation(s)
- Rong Zhang
- Healthy High Density Cities Lab, HKUrbanLab, The University of Hong Kong, Knowles Building, Pokfulam Road, Pokfulam, Hong Kong, China; Department of Urban Planning and Design, The University of Hong Kong, Knowles Building, Pokfulam Road, Pokfulam, Hong Kong, China
| | - Ka Yan Lai
- Healthy High Density Cities Lab, HKUrbanLab, The University of Hong Kong, Knowles Building, Pokfulam Road, Pokfulam, Hong Kong, China; Department of Urban Planning and Design, The University of Hong Kong, Knowles Building, Pokfulam Road, Pokfulam, Hong Kong, China
| | - Wenhui Liu
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Yanhui Liu
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Wenfeng Cai
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Chris Webster
- Healthy High Density Cities Lab, HKUrbanLab, The University of Hong Kong, Knowles Building, Pokfulam Road, Pokfulam, Hong Kong, China; Department of Urban Planning and Design, The University of Hong Kong, Knowles Building, Pokfulam Road, Pokfulam, Hong Kong, China; Urban Systems Institute, The University of Hong Kong, Hong Kong, China
| | - Lei Luo
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
| | - Chinmoy Sarkar
- Healthy High Density Cities Lab, HKUrbanLab, The University of Hong Kong, Knowles Building, Pokfulam Road, Pokfulam, Hong Kong, China; Department of Urban Planning and Design, The University of Hong Kong, Knowles Building, Pokfulam Road, Pokfulam, Hong Kong, China; Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, OX3 7JX, UK; Urban Systems Institute, The University of Hong Kong, Hong Kong, China.
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Islam A, Amin E, Islam S, Hossain ME, Al Mamun A, Sahabuddin M, Samad MA, Shirin T, Rahman MZ, Hassan MM. Annual trading patterns and risk factors of avian influenza A/H5 and A/H9 virus circulation in turkey birds ( Meleagris gallopavo) at live bird markets in Dhaka city, Bangladesh. Front Vet Sci 2023; 10:1148615. [PMID: 37470075 PMCID: PMC10352991 DOI: 10.3389/fvets.2023.1148615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 05/12/2023] [Indexed: 07/21/2023] Open
Abstract
The impacts of the avian influenza virus (AIV) on farmed poultry and wild birds affect human health, livelihoods, food security, and international trade. The movement patterns of turkey birds from farms to live bird markets (LBMs) and infection of AIV are poorly understood in Bangladesh. Thus, we conducted weekly longitudinal surveillance in LBMs to understand the trading patterns, temporal trends, and risk factors of AIV circulation in turkey birds. We sampled a total of 423 turkeys from two LBMs in Dhaka between May 2018 and September 2019. We tested the swab samples for the AIV matrix gene (M-gene) followed by H5, H7, and H9 subtypes using real-time reverse transcriptase-polymerase chain reaction (rRT-PCR). We used exploratory analysis to investigate trading patterns, annual cyclic trends of AIV and its subtypes, and a generalized estimating equation (GEE) logistic model to determine the factors that influence the infection of H5 and H9 in turkeys. Furthermore, we conducted an observational study and informal interviews with traders and vendors to record turkey trading patterns, demand, and supply and turkey handling practices in LBM. We found that all trade routes of turkey birds to northern Dhaka are unidirectional and originate from the northwestern and southern regions of Bangladesh. The number of trades from the source district to Dhaka depends on the turkey density. The median distance that turkey was traded from its source district to Dhaka was 188 km (Q1 = 165, Q3 = 210, IQR = 45.5). We observed seasonal variation in the median and average distance of turkey. The qualitative findings revealed that turkey farming initially became reasonably profitable in 2018 and at the beginning of 2019. However, the fall in demand and production in the middle of 2019 may be related to unstable market pricing, high feed costs, a shortfall of adequate marketing facilities, poor consumer knowledge, and a lack of advertising. The overall prevalence of AIV, H5, and H9 subtypes in turkeys was 31% (95% CI: 26.6-35.4), 16.3% (95% CI: 12.8-19.8), and 10.2% (95% CI: 7.3-13.1) respectively. None of the samples were positive for H7. The circulation of AIV and H9 across the annual cycle showed no seasonality, whereas the circulation of H5 showed significant seasonality. The GEE revealed that detection of AIV increases in retail vendor business (OR: 1.71; 95% CI: 1.12-2.62) and the bird's health status is sick (OR: 10.77; 95% CI: 4.31-26.94) or dead (OR: 11.33; 95% CI: 4.30-29.89). We also observed that winter season (OR: 5.83; 95% CI: 2.80-12.14) than summer season, dead birds (OR: 61.71; 95% CI: 25.78-147.75) and sick birds (OR 8.33; 95% CI: 3.36-20.64) compared to healthy birds has a higher risk of H5 infection in turkeys. This study revealed that the turkeys movements vary by time and season from the farm to the LBM. This surveillance indicated year-round circulation of AIV with H5 and H9 subtypes in turkey birds in LBMs. The seasonality and health condition of birds influence H5 infection in birds. The trading pattern of turkey may play a role in the transmission of AIV viruses in the birds. The selling of sick turkeys infected with H5 and H9 highlights the possibility of virus transmission to other species of birds sold at LBMs and to people.
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Affiliation(s)
- Ariful Islam
- EcoHealth Alliance, New York, NY, United States
- Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Geelong, VIC, Australia
| | - Emama Amin
- Institute of Epidemiology, Disease Control and Research (IEDCR), Dhaka, Bangladesh
| | - Shariful Islam
- Institute of Epidemiology, Disease Control and Research (IEDCR), Dhaka, Bangladesh
| | - Mohammad Enayet Hossain
- One Health Laboratory, International Centre for Diarrheal Diseases Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | - Abdullah Al Mamun
- Institute of Epidemiology, Disease Control and Research (IEDCR), Dhaka, Bangladesh
| | - Md. Sahabuddin
- One Health Laboratory, International Centre for Diarrheal Diseases Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | - Mohammed Abdus Samad
- National Reference Laboratory for Avian Influenza, Bangladesh Livestock Research Institute (BLRI), Savar, Bangladesh
| | - Tahmina Shirin
- Institute of Epidemiology, Disease Control and Research (IEDCR), Dhaka, Bangladesh
| | - Mohammed Ziaur Rahman
- One Health Laboratory, International Centre for Diarrheal Diseases Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | - Mohammad Mahmudul Hassan
- Queensland Alliance for One Health Sciences, School of Veterinary Science, The University of Queensland, Brisbane, QLD, Australia
- Faculty of Veterinary Medicine, Chattogram Veterinary and Animal Sciences University, Chattogram, Bangladesh
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Chong KC, Chan PKS, Lee TC, Lau SYF, Wu P, Lai CKC, Fung KSC, Tse CWS, Leung SY, Kwok KL, Li C, Jiang X, Wei Y. Determining meteorologically-favorable zones for seasonal influenza activity in Hong Kong. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2023; 67:609-619. [PMID: 36847884 DOI: 10.1007/s00484-023-02439-x] [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: 06/29/2022] [Revised: 02/03/2023] [Accepted: 02/08/2023] [Indexed: 06/18/2023]
Abstract
Investigations of simple and accurate meteorology classification systems for influenza epidemics, particularly in subtropical regions, are limited. To assist in preparing for potential upsurges in the demand on healthcare facilities during influenza seasons, our study aims to develop a set of meteorologically-favorable zones for epidemics of influenza A and B, defined as the intervals of meteorological variables with prediction performance optimized. We collected weekly detection rates of laboratory-confirmed influenza cases from four local major hospitals in Hong Kong between 2004 and 2019. Meteorological and air quality records for hospitals were collected from their closest monitoring stations. We employed classification and regression trees to identify zones that optimize the prediction performance of meteorological data in influenza epidemics, defined as a weekly rate > 50th percentile over a year. According to the results, a combination of temperature > 25.1℃ and relative humidity > 79% was favorable to epidemics in hot seasons, whereas either temperature < 16.4℃ or a combination of < 20.4℃ and relative humidity > 76% was favorable to epidemics in cold seasons. The area under the receiver operating characteristic curve (AUC) in model training achieved 0.80 (95% confidence interval [CI], 0.76-0.83) and was kept at 0.71 (95%CI, 0.65-0.77) in validation. The meteorologically-favorable zones for predicting influenza A or A and B epidemics together were similar, but the AUC for predicting influenza B epidemics was comparatively lower. In conclusion, we established meteorologically-favorable zones for influenza A and B epidemics with a satisfactory prediction performance, even though the influenza seasonality in this subtropical setting was weak and type-specific.
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Affiliation(s)
- Ka Chun Chong
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
- Centre for Health Systems and Policy Research, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Paul K S Chan
- Department of Microbiology, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Tsz Cheung Lee
- Hong Kong Observatory, Hong Kong Special Administrative Region, China
| | - Steven Y F Lau
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Peng Wu
- School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Christopher K C Lai
- Department of Microbiology, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Kitty S C Fung
- Department of Pathology, United Christian Hospital, Hong Kong Special Administrative Region, China
| | - Cindy W S Tse
- Department of Pathology, Kwong Wah Hospital, Hong Kong Special Administrative Region, China
| | - Shuk Yu Leung
- Department of Paediatrics, Kwong Wah Hospital, Hong Kong Special Administrative Region, China
| | - Ka Li Kwok
- Department of Paediatrics, Kwong Wah Hospital, Hong Kong Special Administrative Region, China
| | - Conglu Li
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Xiaoting Jiang
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Yuchen Wei
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
- Centre for Health Systems and Policy Research, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
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10
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Zhang B, Chen T, Liang S, Shen W, Sun Q, Wang D, Wang G, Yang J, Yang L, Wang D, Shu Y, Du X. Subtypes specified environmental dependence of seasonal influenza virus. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 852:158525. [PMID: 36075410 DOI: 10.1016/j.scitotenv.2022.158525] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 08/21/2022] [Accepted: 08/31/2022] [Indexed: 06/15/2023]
Abstract
Understanding the role of meteorological factors in the transmission dynamics of respiratory infectious diseases remains challenging. Our study was to comprehensively investigate the nonlinear effects of environmental factors on influenza transmission, based on multi-region surveillance data from mainland China. An approach related to time-varying reproduction number (Rt) was proposed, which extracts the environment-related components from Rt to estimate the relationship between environmental factors and influenza transmission based on a mixed-effects regression model. Nonlinear relationships for absolute humidity (the lowest transmission was observed at absolute humidity of 12 g/m3) and mean temperature (the lowest transmission was observed at the mean temperature of 18 °C) with influenza transmission were observed. Influenza transmission holds almost constant with the average precipitation below 1 mm or sunshine hour below 9 h/day, but increases for the precipitation and decreases for the sunshine hour afterward. The environmental dependence varies across subtypes: A(H3N2) maintains relatively higher transmission in high temperature and humidity conditions, compared with other influenza subtypes. Overall, the subtypes specified environmental dependence of influenza transmission could explain 23.1 %, 29.2 % and 27.1 % of the variations for A(H1N1)pdm09, A(H3N2) and B-lineage in China. The projected seasonal transmission rates based on our approach could be used as a valuable seasonal proxy to model the influenza dynamics under various meteorological spaces. Finally, our approach is also applicable to obtain novel insights into the impact of environmental factors on other respiratory infectious diseases.
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Affiliation(s)
- Bing Zhang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, PR China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, PR China; Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou 510180, PR China
| | - Tao Chen
- National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing 102206, PR China
| | - Shiwen Liang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, PR China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, PR China; Tongan District Center for Disease Control and Prevention, Xiamen 361100, PR China
| | - Wei Shen
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, PR China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, PR China; Department of Rheumatology and Immunology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing 210008, PR China
| | - Qianru Sun
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, PR China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, PR China
| | - Daoze Wang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, PR China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, PR China
| | - Gang Wang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, PR China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, PR China
| | - Jing Yang
- National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing 102206, PR China
| | - Lei Yang
- National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing 102206, PR China
| | - Dayan Wang
- National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing 102206, PR China.
| | - Yuelong Shu
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, PR China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, PR China; Key Laboratory of Tropical Disease Control, Ministry of Education, Sun Yat-sen University, Guangzhou 510030, PR China; Institute of Pathogen Biology of Chinese Academy of Medical Science (CAMS)/ Peking Union Medical College (PUMC), Beijing 100730, PR China.
| | - Xiangjun Du
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, PR China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, PR China; Key Laboratory of Tropical Disease Control, Ministry of Education, Sun Yat-sen University, Guangzhou 510030, PR China.
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11
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Du M, Zhu H, Yin X, Ke T, Gu Y, Li S, Li Y, Zheng G. Exploration of influenza incidence prediction model based on meteorological factors in Lanzhou, China, 2014-2017. PLoS One 2022; 17:e0277045. [PMID: 36520836 PMCID: PMC9754291 DOI: 10.1371/journal.pone.0277045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Accepted: 10/19/2022] [Indexed: 12/23/2022] Open
Abstract
Humans are susceptible to influenza. The influenza virus spreads quickly and behave seasonally. The seasonality and spread of influenza are often associated with meteorological factors and have spatio-temporal differences. Based on the influenza cases and daily average meteorological factors in Lanzhou from 2014 to 2017, this study firstly aimed to analyze the characteristics of influenza incidence in Lanzhou and the impact of meteorological factors on influenza activities. Then, SARIMA(X) models for the prediction were established. The influenza cases in Lanzhou from 2014 to 2017 was more male than female, and the younger the age, the higher the susceptibility; the epidemic characteristics showed that there is a peak in winter, a secondary peak in spring, and a trough in summer and autumn. The influenza cases in Lanzhou increased with increasing daily pressure, decreasing precipitation, average relative humidity, hours of sunshine, average daily temperature and average daily wind speed. Low temperature was a significant driving factor for the increase of transmission intensity of seasonal influenza. The SARIMAX (1,0,0)(1,0,1)[12] multivariable model with average temperature has better prediction performance than the university model. This model is helpful to establish an early warning system, and provide important evidence for the development of influenza control policies and public health interventions.
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Affiliation(s)
- Meixia Du
- School of Public Health, Gansu University of Chinese Medicine, Gansu Lanzhou, China
- Gansu Provincial Cancer Hospital, Gansu Lanzhou, China
| | - Hai Zhu
- School of Public Health, Gansu University of Chinese Medicine, Gansu Lanzhou, China
| | - Xiaochun Yin
- School of Public Health, Gansu University of Chinese Medicine, Gansu Lanzhou, China
- The Collaborative Innovation Center for Prevention and Control by Chinese Medicine on Disease Related Northwestern Environment and Nutrition, Gansu Lanzhou, China
- * E-mail: (XY); (SL)
| | - Ting Ke
- School of Public Health, Gansu University of Chinese Medicine, Gansu Lanzhou, China
| | - Yonge Gu
- School of Public Health, Gansu University of Chinese Medicine, Gansu Lanzhou, China
- The Collaborative Innovation Center for Prevention and Control by Chinese Medicine on Disease Related Northwestern Environment and Nutrition, Gansu Lanzhou, China
| | - Sheng Li
- First People’s Hospital of Lanzhou City, Gansu Lanzhou, China
- * E-mail: (XY); (SL)
| | - Yongjun Li
- Gansu Provincial Center for Disease Control and Prevention, Gansu Lanzhou, China
| | - Guisen Zheng
- School of Public Health, Gansu University of Chinese Medicine, Gansu Lanzhou, China
- The Collaborative Innovation Center for Prevention and Control by Chinese Medicine on Disease Related Northwestern Environment and Nutrition, Gansu Lanzhou, China
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12
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Ng H, Li Y, Zhang T, Lu Y, Wong C, Ni J, Zhao Q. Association between multiple meteorological variables and seasonal influenza A and B virus transmission in Macau. Heliyon 2022; 8:e11820. [DOI: 10.1016/j.heliyon.2022.e11820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 05/03/2022] [Accepted: 11/15/2022] [Indexed: 11/26/2022] Open
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13
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Zhang S, Sun Z, He J, Li Z, Han L, Shang J, Hao Y. The influences of the East Asian Monsoon on the spatio-temporal pattern of seasonal influenza activity in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 843:157024. [PMID: 35772553 DOI: 10.1016/j.scitotenv.2022.157024] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Revised: 06/24/2022] [Accepted: 06/24/2022] [Indexed: 06/15/2023]
Abstract
Previous research has extensively studied the seasonalities of human influenza infections and the effect of specific climatic factors in different regions. However, there is limited understanding of the influences of monsoons. This study applied generalized additive model with monthly surveillance data from mainland China to explore the influences of the East Asian Monsoon on the spatio-temporal pattern of seasonal influenza in China. The results suggested two influenza active periods in northern China and three active periods in southern China. The study found that the northerly advancement of East Asian Summer Monsoon (EASM) influences the summer influenza spatio-temporal patterns in both southern and northern China. At the interannual scale, the north-south converse effect of EASM on influenza activity is mainly due to the converse effect of EASM on humidity and precipitation. Within the annual scale, influenza activity in southern China gradually reaches its maximum during the summer exacerbated by the northerly advancement of EASM. Furthermore, the winter epidemic in China is related to the low temperature and humidity influenced by the East Asian Winter Monsoon (EAWM). Moreover, the active period in transition season is related partially to the large rapid temperature change influenced by the transition of EAWM and EASM. Despite the delayed onset and instability, the climatic condition influenced by the East Asian Monsoon is one of the potential key drivers of influenza activity.
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Affiliation(s)
- Shuwen Zhang
- School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Zhaobin Sun
- Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China.
| | - Juan He
- School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing 100029, China.
| | - Ziming Li
- Environmental Meteorology Forecast Center of Beijing-Tianjin-Hebei, China Meteorological Administration, Beijing 100089, China; Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China
| | - Ling Han
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Jing Shang
- Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China
| | - Yu Hao
- School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing 100029, China
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14
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Naseri K, Aliashrafzadeh H, Otadi M, Ebrahimzadeh F, Badfar H, Alipourfard I. Human Responses in Public Health Emergencies for Infectious Disease Control: An Overview of Controlled Topologies for Biomedical Applications. CONTRAST MEDIA & MOLECULAR IMAGING 2022; 2022:6324462. [PMID: 36105443 PMCID: PMC9458400 DOI: 10.1155/2022/6324462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Revised: 06/20/2022] [Accepted: 06/27/2022] [Indexed: 11/18/2022]
Abstract
COVID-19 originated in Wuhan city of Hubei Province in China in December three years ago. Since then, it has spread to more than 210 countries and territories. This disease is caused by Severe Acute Respiratory Syndrome Coronavirus 2. The virus has a size of one to two nanometers and a single-stranded positive RNA. Droplets spread the virus from coughing and sneezing. This condition causes coughing, fever, acute respiratory problems, and even death. According to the WHO, the virus can survive outside the body for several hours. This research aimed to determine how environmental factors influenced the COVID-19 virus's survival and behavior, as well as its transmission, in a complex environment. Based on the results, virus transmissions are influenced by various human and environmental factors such as population distribution, travel, social behavior, and climate change. Environmental factors have not been adequately examined concerning the transmission of this epidemic. Thus, it is necessary to examine various aspects of prevention and control of this disease, including its effects on climate and other environmental factors.
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Affiliation(s)
- Kamal Naseri
- Department of Architecture and Urban Studies (DAStU), Politecnico di Milano, Milan, Italy
| | | | - Maryam Otadi
- Chemical Engineering Department, Central Tehran Branch, Islamic Azad University, Tehran, Iran
| | - Farnoosh Ebrahimzadeh
- Department of Internal Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Homayoun Badfar
- Department of Mechanical Engineering, Urmia University of Technology (UUT), PO Box: 57166-419, Urmia, Iran
| | - Iraj Alipourfard
- Institute of Biology,Biotechnology and Environmental Protection, Faculty of Natural Sciences, The University of Silesia in Katowice, Katowice, Poland
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15
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Qi L, Liu T, Gao Y, Li Q, Tang W, Tian D, Su K, Xiong Y, Yang J, Feng L, Liu Q. Effect of absolute humidity on influenza activity across different climate regions in China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:49373-49384. [PMID: 35218485 DOI: 10.1007/s11356-022-19279-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 02/11/2022] [Indexed: 06/14/2023]
Abstract
Until now, we have no thorough understanding the role of absolute humidity on influenza activity, especially in tropical and subtropical areas. In this study, we investigated the relationship between absolute humidity and influenza activity in seven municipalities/provinces covering different climatic zones in China. Weekly meteorological data and influenza surveillance data in seven provinces/municipalities in China were collected from January 2012 to December 2019. A distributed lag nonlinear model was adopted to investigate the association between absolute humidity (AH) and influenza activity in each study site. Then, seven study sites were grouped into three regions: northern, intermediate, and southernmost regions. A multivariate meta-analysis was applied to estimate the exposure-lag-response associations in three regions. The province-specific or municipality-specific curves appeared to be nonlinear, and the association between influenza activity and AH varied across regions. In Beijing and Tianjin, located in northern China, the cumulative relative risks (RRs) increased as weekly average AHmean fell below 3.41 g/m3 and 6.62 g/m3. In Guangdong and Hainan, located in southernmost China, the risk of influenza activity increased with rising average AHmean with 16.74 g/m3 and 20.18 g/m3 as the break points. In Shanghai, Zhejiang, and Chongqing, the relationship between weekly average AHmean and influenza could be described as U-shaped curves, with the lowest RRs when weekly average AHmean was 11.95 g/m3, 11.94 g/m3, and 15.96 g/m3, respectively. Meta-analysis results showed the cumulative RRs significantly increased as weekly average AHmean fell below 3.86 g/m3 in the northern region, whereas significantly increased as weekly average AHmean rose above 18.46 g/m3 and 15.22 g/m3 in intermediate and southernmost regions, respectively. Both low and high AH might increase influenza risk in China, and the relationship varies geographically. Our findings suggest that public health policies for climate change adaptation should be tailored to the local climate conditions.
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Affiliation(s)
- Li Qi
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400042, China
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Tian Liu
- Jingzhou Center for Disease Control and Prevention, Hubei, 434000, China
| | - Yuan Gao
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Qin Li
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Wenge Tang
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Dechao Tian
- School of Public Health (Shenzhen), Sun Yat-Sen University, Shenzhen, 518107, China
| | - Kun Su
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Yu Xiong
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Jun Yang
- School of Public Health, Guangzhou Medical University, Guangzhou, 511436, China.
| | - Luzhao Feng
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
| | - Qiyong Liu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
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16
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Wagatsuma K, Koolhof IS, Saito R. Was the Reduction in Seasonal Influenza Transmission during 2020 Attributable to Non-Pharmaceutical Interventions to Contain Coronavirus Disease 2019 (COVID-19) in Japan? Viruses 2022; 14:v14071417. [PMID: 35891397 PMCID: PMC9320739 DOI: 10.3390/v14071417] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 06/04/2022] [Accepted: 06/27/2022] [Indexed: 02/04/2023] Open
Abstract
We quantified the effects of adherence to various non-pharmaceutical interventions (NPIs) on the seasonal influenza epidemic dynamics in Japan during 2020. The total monthly number of seasonal influenza cases per sentinel site (seasonal influenza activity) reported to the National Epidemiological Surveillance of Infectious Diseases and alternative NPI indicators (retail sales of hand hygiene products and number of airline passenger arrivals) from 2014−2020 were collected. The average number of monthly seasonal influenza cases in 2020 had decreased by approximately 66.0% (p < 0.001) compared to those in the preceding six years. An increase in retail sales of hand hygiene products of ¥1 billion over a 3-month period led to a 15.5% (95% confidence interval [CI]: 10.9−20.0%; p < 0.001) reduction in seasonal influenza activity. An increase in the average of one million domestic and international airline passenger arrivals had a significant association with seasonal influenza activity by 11.6% at lag 0−2 months (95% CI: 6.70−16.5%; p < 0.001) and 30.9% at lag 0−2 months (95% CI: 20.9−40.9%; p < 0.001). NPI adherence was associated with decreased seasonal influenza activity during the COVID-19 pandemic in Japan, which has crucial implications for planning public health interventions to minimize the health consequences of adverse seasonal influenza epidemics.
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Affiliation(s)
- Keita Wagatsuma
- Division of International Health (Public Health), Graduate School of Medical and Dental Sciences, Niigata University, Niigata 951-8510, Japan;
- Japan Society for the Promotion of Science, Tokyo 102-0083, Japan
- Correspondence: ; Tel.: +81-25-227-2129
| | - Iain S. Koolhof
- College of Health and Medicine, School of Medicine, University of Tasmania, Hobart 7000, Australia;
| | - Reiko Saito
- Division of International Health (Public Health), Graduate School of Medical and Dental Sciences, Niigata University, Niigata 951-8510, Japan;
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17
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Wang J, Zhang L, Lei R, Li P, Li S. Effects and Interaction of Meteorological Parameters on Influenza Incidence During 2010-2019 in Lanzhou, China. Front Public Health 2022; 10:833710. [PMID: 35273941 PMCID: PMC8902077 DOI: 10.3389/fpubh.2022.833710] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Accepted: 01/10/2022] [Indexed: 11/13/2022] Open
Abstract
Background Influenza is a seasonal infectious disease, and meteorological parameters critically influence the incidence of influenza. However, the meteorological parameters linked to influenza occurrence in semi-arid areas are not studied in detail. This study aimed to clarify the impact of meteorological parameters on influenza incidence during 2010-2019 in Lanzhou. The results are expected to facilitate the optimization of influenza-related public health policies by the local healthcare departments. Methods Descriptive data related to influenza incidence and meteorology during 2010-2019 in Lanzhou were analyzed. The exposure-response relationship between the risk of influenza occurrence and meteorological parameters was explored according to the distributed lag no-linear model (DLNM) with Poisson distribution. The response surface model and stratified model were used to estimate the interactive effect between relative humidity (RH) and other meteorological parameters on influenza incidence. Results A total of 6701 cases of influenza were reported during 2010-2019. DLNM results showed that the risk of influenza would gradually increase as the weekly mean average ambient temperature (AT), RH, and absolute humidity (AH) decrease at lag 3 weeks when they were lower than 12.16°C, 51.38%, and 5.24 g/m3, respectively. The low Tem (at 5th percentile, P5) had the greatest effect on influenza incidence; the greatest estimated relative risk (RR) was 4.54 (95%CI: 3.19-6.46) at cumulative lag 2 weeks. The largest estimates of RRs for low RH (P5) and AH (P5) were 4.81 (95%CI: 3.82-6.05) and 4.17 (95%CI: 3.30-5.28) at cumulative lag 3 weeks, respectively. An increase in AT by 1°C led to an estimates of percent change (95%CI) of 3.12% (-4.75% to -1.46%) decrease in the weekly influenza case counts in a low RH environment. In addition, RH showed significant interaction with AT and AP on influenza incidence but not with wind speed. Conclusion This study indicated that low AT, low humidity (RH and AH), and high air pressure (AP) increased the risk of influenza. Moreover, the interactive effect of low RH with low AT and high AP can aggravate the incidence of influenza.
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Affiliation(s)
- Jinyu Wang
- School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Ling Zhang
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, China
| | - Ruoyi Lei
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, China
| | - Pu Li
- The Second People's Hospital of Baiyin, Baiyin, China
| | - Sheng Li
- The First People's Hospital of Lanzhou, Lanzhou, China
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18
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Li Y, Wu J, Hao J, Dou Q, Xiang H, Liu S. Short-term impact of ambient temperature on the incidence of influenza in Wuhan, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:18116-18125. [PMID: 34677763 DOI: 10.1007/s11356-021-16948-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 10/04/2021] [Indexed: 06/13/2023]
Abstract
Few studies have estimated the nonlinear association of ambient temperature with the risk of influenza. We therefore applied a time-series analysis to explore the short-term effect of ambient temperature on the incidence of influenza in Wuhan, China. Daily influenza cases were collected from Hubei Provincial Center for Disease Control and Prevention (Hubei CDC) from January 1, 2014, to December 31, 2017. The meteorological and daily pollutant data was obtained from the Hubei Meteorological Service Center and National Air Quality Monitoring Stations, respectively. We used a generalized additive model (GAM) coupled with the distributed lag nonlinear model (DLNM) to explore the exposure-lag-response relationship between the short-term risk of influenza and daily average ambient temperature. Analyses were also performed to assess the extreme cold and hot temperature effects. We observed that the ambient temperature was statistically significant, and the exposure-response curve is approximately S-shaped, with a peak observed at 23.57 ℃. The single-day lag curve showed that extreme hot and cold temperatures were both significantly associated with influenza. The extreme hot temperature has an acute effect on influenza, with the most significant effect observed at lag 0-1. The extreme cold temperature has a relatively smaller effect but lasts longer, with the effect exerted continuously during a lag of 2-4 days. Our study found significant nonlinear and delayed associations between ambient temperature and the incidence of influenza. Our finding contributes to the establishment of an early warning system for airborne infectious diseases.
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Affiliation(s)
- Yanbing Li
- School of Health Sciences, Wuhan University, 115 Donghu Road, Wuhan, 430071, China
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking, Union Medical College, Beijing, 100005, China
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Jingtao Wu
- School of Health Sciences, Wuhan University, 115 Donghu Road, Wuhan, 430071, China
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking, Union Medical College, Beijing, 100005, China
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Jiayuan Hao
- Department of Biostatistics, Harvard University, Cambridge, MA, 02138, USA
| | - Qiujun Dou
- School of Health Sciences, Wuhan University, 115 Donghu Road, Wuhan, 430071, China
| | - Hao Xiang
- School of Health Sciences, Wuhan University, 115 Donghu Road, Wuhan, 430071, China
| | - Suyang Liu
- School of Health Sciences, Wuhan University, 115 Donghu Road, Wuhan, 430071, China.
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Chong KC, Chen Y, Chan EYY, Lau SYF, Lam HCY, Wang P, Goggins WB, Ran J, Zhao S, Mohammad KN, Wei Y. Association of weather, air pollutants, and seasonal influenza with chronic obstructive pulmonary disease hospitalization risks. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 293:118480. [PMID: 34763018 DOI: 10.1016/j.envpol.2021.118480] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2021] [Revised: 11/02/2021] [Accepted: 11/06/2021] [Indexed: 05/21/2023]
Abstract
The influences of weather and air pollutants on chronic obstructive pulmonary disease (COPD) have been well-studied. However, the heterogeneous effects of different influenza viral infections, air pollution and weather on COPD admissions and re-admissions have not been thoroughly examined. In this study, we aimed to elucidate the relationships between meteorological variables, air pollutants, seasonal influenza, and hospital admissions and re-admissions due to COPD in Hong Kong, a non-industrial influenza epicenter. A total number of 507703 hospital admissions (i.e., index admissions) and 301728 re-admission episodes (i.e., episodes within 30 days after the previous discharge) for COPD over 14 years (1998-2011) were obtained from all public hospitals. The aggregated weekly numbers were matched with meteorological records and outdoor air pollutant concentrations. Type-specific and all-type influenza-like illness positive (ILI+) rates were used as proxies for influenza activity. Generalized additive models were used in conjunction with distributed-lag non-linear models to estimate the associations of interest. According to the results, high concentrations of fine particulate matter, oxidant gases, and cold weather were strong independent risk factors of COPD outcomes. The cumulative adjusted relative risks exhibited a monotone increasing trend except for ILI+ B, and the numbers were statistically significant over the entire observed range of ILI+ total and ILI+ A/H3N2 when the reference rate was zero. COPD hospitalization risk from influenza infection was higher in the elderly than that in the general population. In conclusion, our results suggest that health administrators should impose clean air policies, such as strengthening emissions control on petrol vehicles, to reduce pollution from oxidant gases and particulates. An extension of the influenza vaccination program for patients with COPD may need to be encouraged: for example, vaccination may be included in hospital discharge planning, particularly before the winter epidemic.
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Affiliation(s)
- Ka Chun Chong
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong; Clinical Trials and Biostatistics Laboratory, Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China; Centre for Health Systems and Policy Research, The Chinese University of Hong Kong, Hong Kong
| | - Yu Chen
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong
| | - Emily Ying Yang Chan
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong
| | - Steven Yuk Fai Lau
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong
| | - Holly Ching Yu Lam
- National Heart & Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Pin Wang
- Yale Center on Climate Change and Health, Yale School of Public Health, New Haven, Connecticut, United States
| | - William Bernard Goggins
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong
| | - Jinjun Ran
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shi Zhao
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong; Clinical Trials and Biostatistics Laboratory, Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China
| | - Kirran N Mohammad
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong
| | - Yuchen Wei
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong; Centre for Health Systems and Policy Research, The Chinese University of Hong Kong, Hong Kong.
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20
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Soft Computing Paradigms to Find the Numerical Solutions of a Nonlinear Influenza Disease Model. APPLIED SCIENCES-BASEL 2021. [DOI: 10.3390/app11188549] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
The aim of this work is to present the numerical results of the influenza disease nonlinear system using the feed forward artificial neural networks (ANNs) along with the optimization of the combination of global and local search schemes. The genetic algorithm (GA) and active-set method (ASM), i.e., GA-ASM, are implemented as global and local search schemes. The mathematical nonlinear influenza disease system is dependent of four classes, susceptible S(u), infected I(u), recovered R(u) and cross-immune individuals C(u). For the solutions of these classes based on influenza disease system, the design of an objective function is presented using these differential system equations and its corresponding initial conditions. The optimization of this objective function is using the hybrid computing combination of GA-ASM for solving all classes of the influenza disease nonlinear system. The obtained numerical results will be compared by the Adams numerical results to check the authenticity of the designed ANN-GA-ASM. In addition, the designed approach through statistical based operators shows the consistency and stability for solving the influenza disease nonlinear system.
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21
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Lau SY, Cheng W, Yu Z, Mohammad KN, Wang MH, Zee BC, Li X, Chong KC, Chen E. Independent association between meteorological factors, PM2.5, and seasonal influenza activity in Hangzhou, Zhejiang province, China. Influenza Other Respir Viruses 2021; 15:513-520. [PMID: 33342077 PMCID: PMC8189232 DOI: 10.1111/irv.12829] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 11/28/2020] [Accepted: 12/01/2020] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Due to variations in climatic conditions, the effects of meteorological factors and PM2.5 on influenza activity, particularly in subtropical regions, vary in existing literature. In this study, we examined the relationship between influenza activity, meteorological parameters, and PM2.5 . METHODS A total of 20 165 laboratory-confirmed influenza cases in Hangzhou, Zhejiang province, were documented in our dataset and aggregated into weekly counts for downstream analysis. We employed a combination of the quasi-Poisson-generalized additive model and the distributed lag non-linear model to examine the relationship of interest, controlling for long-term trends, seasonal trends, and holidays. RESULTS A hockey-stick association was found between absolute humidity and the risk of influenza infections. The overall cumulative adjusted relative risk (ARR) was statistically significant when weekly mean absolute humidity was low (<10 µg/m3 ) and high (>17.5 µg/m3 ). A slightly higher ARR was observed when weekly mean temperature reached over 30.5°C. A statistically significantly higher ARR was observed when weekly mean relative humidity dropped below 67%. ARR increased statistically significantly with increasing rainfall. For PM2.5 , the ARR was marginally statistically insignificant. In brief, high temperature, wet and dry conditions, and heavy rainfall were the major risk factors associated with a higher risk of influenza infections. CONCLUSIONS The present study contributes additional knowledge to the understanding of the effects of various environmental factors on influenza activities. Our findings shall be useful and important for the development of influenza surveillance and early warning systems.
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Affiliation(s)
- Steven Yuk‐Fai Lau
- School of Public Health and Primary CareThe Chinese University of Hong KongHong KongChina
| | - Wei Cheng
- Zhejiang Province Centre for Disease Control and PreventionHangzhouChina
| | - Zhao Yu
- Zhejiang Province Centre for Disease Control and PreventionHangzhouChina
| | - Kirran N. Mohammad
- School of Public Health and Primary CareThe Chinese University of Hong KongHong KongChina
| | - Maggie Haitian Wang
- School of Public Health and Primary CareThe Chinese University of Hong KongHong KongChina
- Clinical Trials and Biostatistics LaboratoryShenzhen Research InstituteThe Chinese University of Hong KongHong KongChina
| | - Benny Chung‐Ying Zee
- School of Public Health and Primary CareThe Chinese University of Hong KongHong KongChina
- Clinical Trials and Biostatistics LaboratoryShenzhen Research InstituteThe Chinese University of Hong KongHong KongChina
| | - Xi Li
- School of Public Health and Primary CareThe Chinese University of Hong KongHong KongChina
| | - Ka Chun Chong
- School of Public Health and Primary CareThe Chinese University of Hong KongHong KongChina
- Clinical Trials and Biostatistics LaboratoryShenzhen Research InstituteThe Chinese University of Hong KongHong KongChina
- Centre for Health Systems and Policy ResearchThe Chinese University of Hong KongHong KongChina
| | - Enfu Chen
- Zhejiang Province Centre for Disease Control and PreventionHangzhouChina
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22
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Ravindra K, Goyal A, Mor S. Does airborne pollen influence COVID-19 outbreak? SUSTAINABLE CITIES AND SOCIETY 2021; 70:102887. [PMID: 33816082 PMCID: PMC7999829 DOI: 10.1016/j.scs.2021.102887] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 03/04/2021] [Accepted: 03/23/2021] [Indexed: 05/09/2023]
Abstract
The fast spread of SARS-CoV-2 presented a worldwide challenge to public health, economy, and educational system, affecting wellbeing of human society. With high transmission rates, there are increasing evidences of COVID-19 spread via bioaerosols from an infected person. The current review was conducted to examine airborne pollen impact on COVID-19 transmission and to identify the major gaps for post-pandemic research. The study used all key terms to identify revenant literature and observation were collated for the current research. Based on existing literature, there is a potential association between pollen bioaerosols and COVID-19. There are few studies focusing the impact of airborne pollen on SARS-CoV-2, which could be useful to advance future research. Allergic rhinitis and asthma patients were found to have pre-modified immune activation, which could help to provide protection against COVID-19. However, does airborne pollen acts as a potent carrier for SARS-CoV-2 transport, dispersal and its proliferation still require multidisciplinary research. Further, a clear conclusion cannot be drawn due to limited evidence and hence more research is needed to show how pollen bioaerosols could affect virus survivals. The small but growing literature review focuses on searching for every possible answer to provide additional security layers to overcome near future corona-like infectious diseases.
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Key Words
- AAAAI, American Academy of Allergy, Asthma & Immunology
- ACE-2, angiotensin-converting enzyme 2
- ARDS, acute respiratory distress syndrome
- Airborne pollen
- Allergic rhinitis
- Asthma
- Bioaerosols
- CCDC, Chinese Centre for Disease Control and Prevention
- CDC, Centers for Disease Control and Prevention
- CESM, Community Earth System Model
- CMAQ, Community Multiscale Air Quality
- COPD, chronic obstructive pulmonary diseases
- COVID-19
- ERS, European Respiratory Society
- FLI, flu-like illnesses
- GINA, Global Initiative for Asthma
- H1N1, Influenza A virus subtype H1N1
- H5N1, avian influenza virus
- IgE, Immunoglobulin E
- LDT, long-distance transport
- MERS, Middle East respiratory syndrome
- NHC, National Health Commission
- RSV, Respiratory Syncytial Virus infection
- SARS-CoV-2, Severe Acute Respiratory Syndrome Coronavirus-2
- STaMPS, Simulator of Timing and Magnitude of Pollen Season
- Virus
- WAO, World Allergy Organisation
- WHO, World Health Organization
- WRF, Weather Research Forecasting
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Affiliation(s)
- Khaiwal Ravindra
- Department of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, 160012, India
| | - Akshi Goyal
- Department of Environment Studies, Panjab University, Chandigarh, 160014, India
| | - Suman Mor
- Department of Environment Studies, Panjab University, Chandigarh, 160014, India
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Chong KC, Chan EYY, Lee TC, Kwok KL, Lau SYF, Wang P, Lam HCY, Goggins WB, Mohammad KN, Leung SY, Chan PKS. A 21-year retrospective analysis of environmental impacts on paediatric acute gastroenteritis in an affluent setting. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 764:142845. [PMID: 33183801 DOI: 10.1016/j.scitotenv.2020.142845] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 09/08/2020] [Accepted: 10/03/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Extreme weather events happen more frequently along with global warming and they constitute a challenge for public health preparedness. For example, many investigations showed heavy rainfall was associated with an increased risk of acute gastroenteritis. In this study, we examined the associations between different meteorological factors and paediatric acute gastroenteritis in an affluent setting in China controlling for pollutant effects. METHODS Aggregated total weekly number of intestinal infection-related hospital admissions, and meteorological and air pollution data during 1998-2018 in Hong Kong were collected and analysed by a combination of quasi-Poisson generalized additive model and distributed lag nonlinear model. Study population was restricted to children under 5 years of age at the time of admission. RESULTS While heavy rainfall did not exhibit a statistically significant association with the risk of paediatric admission due to intestinal infections, low temperature and humidity extremes (both relative humidity and vapour pressure) did. Compared with the temperature at which the lowest risk was detected (i.e. 22.5 °C), the risk was 6.4% higher (95% confidence interval: 0.0% to 13.0% at 15.1 °C (i.e. the 5th percentile)). We also found the risk of paediatric admission was statistically significantly associated with an increase in the number of extreme cold days in a week over the study period. CONCLUSION Cold condition may have greater impact on disease transmission through increased stability and infectivity of enteric viruses in affluent settings like Hong Kong and thus resulted in an increased risk for paediatric acute gastroenteritis. On the contrary, an insignificant impact from heavy rainfall and high temperature may indicate a minor effect on disease transmission through bacterial growth in contaminated food and water. With the identified impacts of weather factors, extreme weather events are likely to distort the prevalence and seasonal pattern of diarrhoeal diseases in the future.
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Affiliation(s)
- Ka Chun Chong
- School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China; Clinical Trials and Biostatistics Laboratory, Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China; Centre for Health System and Policy Research, The Chinese University of Hong Kong, Hong Kong, China
| | - Emily Ying Yang Chan
- School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | | | - Ka Li Kwok
- Department of Paediatrics, Kwong Wah Hospital, Hong Kong, China
| | - Steven Yuk Fai Lau
- School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.
| | - Pin Wang
- Yale School of Public Health, Yale University
| | - Holly Ching Yu Lam
- National Heart & Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - William Bernard Goggins
- School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Kirran N Mohammad
- School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Shuk Yu Leung
- Department of Paediatrics, Kwong Wah Hospital, Hong Kong, China
| | - Paul Kay Sheung Chan
- Department of Microbiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China; Stanley Ho Centre for Emerging Infectious Diseases, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
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24
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Limited role for meteorological factors on the variability in COVID-19 incidence: A retrospective study of 102 Chinese cities. PLoS Negl Trop Dis 2021; 15:e0009056. [PMID: 33626051 PMCID: PMC7904227 DOI: 10.1371/journal.pntd.0009056] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 12/22/2020] [Indexed: 12/24/2022] Open
Abstract
While many studies have focused on identifying the association between meteorological factors and the activity of COVID-19, we argue that the contribution of meteorological factors to a reduction of the risk of COVID-19 was minimal when the effects of control measures were taken into account. In this study, we assessed how much variability in COVID-19 activity is attributable to city-level socio-demographic characteristics, meteorological factors, and the control measures imposed. We obtained the daily incidence of COVID-19, city-level characteristics, and meteorological data from a total of 102 cities situated in 27 provinces/municipalities outside Hubei province in China from 1 January 2020 to 8 March 2020, which largely covers almost the first wave of the epidemic. Generalized linear mixed effect models were employed to examine the variance in the incidence of COVID-19 explained by different combinations of variables. According to the results, including the control measure effects in a model substantially raised the explained variance to 45%, which increased by >40% compared to the null model that did not include any covariates. On top of that, including temperature and relative humidity in the model could only result in < 1% increase in the explained variance even though the meteorological factors showed a statistically significant association with the incidence rate of COVID-19. In conclusion, we showed that very limited variability of the COVID-19 incidence was attributable to meteorological factors. Instead, the control measures could explain a larger proportion of variance. COVID-19 has a great impact worldwide, especially in some rural settings where healthcare resources are not sufficient. While control measures in these area may be limited, scholars have been discussing the potential effects of meteorological factors on mitigating COVID-19 transmission. Unfortunately, the majority of literatures only looked at the association between COVID-19 and environmental factors in which their findings could mislead readers that certain environmental conditions could be ‘protective’. In this study, we argue that the impact of the meteorological factors was very limited by using the incidence data from 102 Chinese cities in the first epidemic period when control measures have been taken into account. As what we expected, once the control measures have been incorporated in the modelling analysis, the meteorological factors could only explain < 1% increase in variability of COVID-19 while control measure explained the variance for more than 40% in total. Because of it, we suggest stringent control measures are necessary to control COVID-19 regardless the meteorological conditions of an area. Given that no vaccine is available to date, our investigation provides an additional evidence, as advocated by World Meteorological Organization rather than relying on changes in the natural environment for mitigation, active non-pharmaceutical interventions are necessary to curb the COVID-19 pandemic.
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Hoogeveen MJ, van Gorp ECM, Hoogeveen EK. Can pollen explain the seasonality of flu-like illnesses in the Netherlands? THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 755:143182. [PMID: 33131881 PMCID: PMC7580695 DOI: 10.1016/j.scitotenv.2020.143182] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 10/11/2020] [Accepted: 10/12/2020] [Indexed: 05/20/2023]
Abstract
Current models for flu-like epidemics insufficiently explain multi-cycle seasonality. Meteorological factors alone, including the associated behavior, do not predict seasonality, given substantial climate differences between countries that are subject to flu-like epidemics or COVID-19. Pollen is documented to be allergenic, it plays a role in immuno-activation and defense against respiratory viruses, and seems to create a bio-aerosol that lowers the reproduction number of flu-like viruses. Therefore, we hypothesize that pollen may explain the seasonality of flu-like epidemics, including COVID-19, in combination with meteorological variables. We have tested the Pollen-Flu Seasonality Theory for 2016-2020 flu-like seasons, including COVID-19, in the Netherlands, with its 17.4 million inhabitants. We combined changes in flu-like incidence per 100 K/Dutch residents (code: ILI) with pollen concentrations and meteorological data. Finally, a predictive model was tested using pollen and meteorological threshold values, inversely correlated to flu-like incidence. We found a highly significant inverse correlation of r(224) = -0.41 (p < 0.001) between pollen and changes in flu-like incidence, corrected for the incubation period. The correlation was stronger after taking into account the incubation time. We found that our predictive model has the highest inverse correlation with changes in flu-like incidence of r(222) = -0.48 (p < 0.001) when average thresholds of 610 total pollen grains/m3, 120 allergenic pollen grains/m3, and a solar radiation of 510 J/cm2 are passed. The passing of at least the pollen thresholds, preludes the beginning and end of flu-like seasons. Solar radiation is a co-inhibitor of flu-like incidence, while temperature makes no difference. However, higher relative humidity increases with flu-like incidence. We conclude that pollen is a predictor of the inverse seasonality of flu-like epidemics, including COVID-19, and that solar radiation is a co-inhibitor, in the Netherlands.
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Affiliation(s)
- Martijn J Hoogeveen
- Department Technical Sciences & Environment, Open University, the Netherlands.
| | - Eric C M van Gorp
- Department of Viroscience and Department of Infectious Diseases, Erasmus Medical Centre, Rotterdam, the Netherlands
| | - Ellen K Hoogeveen
- Department of Internal Medicine, Jeroen Bosch Hospital, Den Bosch, the Netherlands
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26
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Qi L, Liu T, Gao Y, Tian D, Tang W, Li Q, Feng L, Liu Q. Effect of meteorological factors on the activity of influenza in Chongqing, China, 2012-2019. PLoS One 2021; 16:e0246023. [PMID: 33534840 PMCID: PMC7857549 DOI: 10.1371/journal.pone.0246023] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Accepted: 01/12/2021] [Indexed: 12/29/2022] Open
Abstract
Background The effects of multiple meteorological factors on influenza activity remain unclear in Chongqing, the largest municipality in China. We aimed to fix this gap in this study. Methods Weekly meteorological data and influenza surveillance data in Chongqing were collected from 2012 to 2019. Distributed lag nonlinear models (DLNMs) were conducted to estimate the effects of multiple meteorological factors on influenza activity. Results Inverted J-shaped nonlinear associations between mean temperature, absolute humidity, wind speed, sunshine and influenza activity were found. The relative risks (RRs) of influenza activity increased as weekly average mean temperature fell below 18.18°C, average absolute humidity fell below 12.66 g/m3, average wind speed fell below 1.55 m/s and average sunshine fell below 2.36 hours. Taking the median values as the references, lower temperature, lower absolute humidity and windless could significantly increase the risks of influenza activity and last for 4 weeks. A J-shaped nonlinear association was observed between relative humidity and influenza activity; the risk of influenza activity increased with rising relative humidity with 78.26% as the break point. Taking the median value as the reference, high relative humidity could increase the risk of influenza activity and last for 3 weeks. In addition, we found the relationship between aggregate rainfall and influenza activity could be described with a U-shaped curve. Rainfall effect has significantly higher RR than rainless effect. Conclusions Our study shows that multiple meteorological factors have strong associations with influenza activity in Chongqing, providing evidence for developing a meteorology-based early warning system for influenza to facilitate timely response to upsurge of influenza activity.
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Affiliation(s)
- Li Qi
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Tian Liu
- Jingzhou Center for Disease Control and Prevention, Hubei, China
| | - Yuan Gao
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Dechao Tian
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
| | - Wenge Tang
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Qin Li
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Luzhao Feng
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- * E-mail: (QL); (LF)
| | - Qiyong Liu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- * E-mail: (QL); (LF)
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27
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Leung SY, Lau SYF, Kwok KL, Mohammad KN, Chan PKS, Chong KC. Short-term association among meteorological variation, outdoor air pollution and acute bronchiolitis in children in a subtropical setting. Thorax 2021; 76:360-369. [PMID: 33472969 DOI: 10.1136/thoraxjnl-2020-215488] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Revised: 10/16/2020] [Accepted: 10/26/2020] [Indexed: 11/04/2022]
Abstract
OBJECTIVES To examine the association among acute bronchiolitis-related hospitalisation in children, meteorological variation and outdoor air pollution. METHODS We obtained the daily counts of acute bronchiolitis-related admission of children≤2 years old from all public hospitals, meteorological data and outdoor air pollutants' concentrations between 1 January 2008 and 31 December 2017 in Hong Kong. We used quasi-Poisson generalised additive models together with distributed lag non-linear models to estimate the associations of interest adjusted for confounders. RESULTS A total of 29 688 admissions were included in the analysis. Increased adjusted relative risk (ARR) of acute bronchiolitis-related hospitalisation was associated with high temperature (ambient temperature and apparent temperature) and was marginally associated with high vapour pressure, a proxy for absolute humidity. High concentration of NO2 was associated with elevated risk of acute bronchiolitis admission; the risk of bronchiolitis hospitalisation increased statistically significantly with cumulative NO2 exposure over the range 66.2-119.6 µg/m3. For PM10, the significant effect observed at high concentrations appears to be immediate but not long lasting. For SO2, ARR increased as the concentration approached the 75th percentile and then decreased though the association was insignificant. CONCLUSIONS Acute bronchiolitis-related hospitalisation among children was associated with temperature and exposure to NO2 and PM10 at different lag times, suggesting a need to adopt sustainable clean air policies, especially to target pollutants produced by motor vehicles, to protect young children's health.
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Affiliation(s)
- Shuk Yu Leung
- Department of Paediatrics, Kwong Wah Hospital, Hong Kong, China
| | - Steven Yuk Fai Lau
- School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Ka Li Kwok
- Department of Paediatrics, Kwong Wah Hospital, Hong Kong, China
| | - Kirran N Mohammad
- School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Paul Kay Sheung Chan
- Department of Microbiology, The Chinese University of Hong Kong, Hong Kong, China
| | - Ka Chun Chong
- School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China .,Clinical Trials and Biostatistics Laboratory, Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China.,Centre for Health Systems and Policy Research, The Chinese University of Hong Kong, Hong Kong, China
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28
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Hochman A, Alpert P, Negev M, Abdeen Z, Abdeen AM, Pinto JG, Levine H. The relationship between cyclonic weather regimes and seasonal influenza over the Eastern Mediterranean. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 750:141686. [PMID: 32861075 PMCID: PMC7422794 DOI: 10.1016/j.scitotenv.2020.141686] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 07/30/2020] [Accepted: 08/11/2020] [Indexed: 05/21/2023]
Abstract
The prediction of the occurrence of infectious diseases is of crucial importance for public health, as clearly seen in the ongoing COVID-19 pandemic. Here, we analyze the relationship between the occurrence of a winter low-pressure weather regime - Cyprus Lows - and the seasonal Influenza in the Eastern Mediterranean. We find that the weekly occurrence of Cyprus Lows is significantly correlated with clinical seasonal Influenza in Israel in recent years (R = 0.91; p < .05). This result remains robust when considering a complementary analysis based on Google Trends data for Israel, the Palestinian Authority and Jordan. The weekly occurrence of Cyprus Lows precedes the onset and maximum of Influenza occurrence by about one to two weeks (R = 0.88; p < .05 for the maximum occurrence), and closely follows their timing in eight out of ten years (2008-2017). Since weather regimes such as Cyprus Lows are more robustly predicted in weather and climate models than individual climate variables, we conclude that the weather regime approach can be used to develop tools for estimating the compatibility of the transmission environment for Influenza occurrence in a warming world. Furthermore, this approach may be applied to other regions and climate sensitive diseases. This study is a new cross-border inter-disciplinary regional collaboration for appropriate adaptation to climate change in the Eastern Mediterranean.
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Affiliation(s)
- Assaf Hochman
- Department of Tropospheric Research, Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Eggenstein - Leopoldshafen 76344, Germany.
| | - Pinhas Alpert
- Department of Geophysics, Porter School of the Environment and Earth Sciences, Tel-Aviv University, Tel-Aviv 69978, Israel
| | - Maya Negev
- School of Public Health, University of Haifa, Mt. Carmel 3498838, Israel
| | - Ziad Abdeen
- Al-Quds Public Health Society and the Al-Quds Nutrition and Health Research Institute, Faculty of Medicine-Al-Quds University, Abu-Deis, Palestinian Authority
| | - Abdul Mohsen Abdeen
- Al-Quds Public Health Society and the Al-Quds Nutrition and Health Research Institute, Faculty of Medicine-Al-Quds University, Abu-Deis, Palestinian Authority
| | - Joaquim G Pinto
- Department of Tropospheric Research, Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Eggenstein - Leopoldshafen 76344, Germany
| | - Hagai Levine
- Braun School of Public Health and Community Medicine, Hadassah - Hebrew University, Jerusalem 9110202, Israel
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Hoogeveen MJ. Pollen likely seasonal factor in inhibiting flu-like epidemics. A Dutch study into the inverse relation between pollen counts, hay fever and flu-like incidence 2016-2019. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 727:138543. [PMID: 32498207 PMCID: PMC7162772 DOI: 10.1016/j.scitotenv.2020.138543] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Accepted: 04/05/2020] [Indexed: 05/24/2023]
Abstract
There is uncertainty if current models for the Covid-19 pandemic should already take into account seasonality. That is because current environmental factors do not provide a powerful explanation of such seasonality, especially given climate differences between countries with moderate climates. It is hypothesized that one major factor is overlooked: pollen count. Pollen are documented to invoke strong immune responses and might create an environmental factor that makes it more difficult for flu-like viruses to survive outside a host. This Dutch study confirms that there is a (highly) significant inverse correlation between pollen count and weekly changes in medical flu consults, and that there is a highly significant inverse correlation between hay fever incidence, as measured by prescribed medication revenues, and weekly flu consults. This supports the idea that pollen are a direct or indirect factor in the seasonality of flu-like epidemics. If seasonality will be observed during the covid-19 spread as well, it is not unlikely that pollen play a role.
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Affiliation(s)
- Martijn J Hoogeveen
- Open University Netherlands, De Liesbosch 12d, 3439LC Nieuwegein, the Netherlands.
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30
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Association Between Seasonal Influenza and Absolute Humidity: Time-Series Analysis with Daily Surveillance Data in Japan. Sci Rep 2020; 10:7764. [PMID: 32385282 PMCID: PMC7211015 DOI: 10.1038/s41598-020-63712-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Accepted: 03/20/2020] [Indexed: 11/24/2022] Open
Abstract
Seasonal influenza epidemics are associated with various meteorological factors. Recently absolute humidity (AH) has garnered attention, and some epidemiological studies show an association between AH and human influenza infection. However, they mainly analyzed weekly surveillance data, and daily data remains largely unexplored despite its potential benefits. In this study, we analyze daily influenza surveillance data using a distributed lag non-linear model to examine the association of AH with the number of influenza cases and the magnitude of the association. Additionally, we investigate how adjustment for seasonality and autocorrelation in the model affect results. All models used in the study showed a significant increase in the number of influenza cases as AH decreased, although the magnitude of the association differed substantially by model. Furthermore, we found that relative risk reached a peak at lag 10–14 with extremely low AH. To verify these findings, further analysis should be conducted using data from other locations.
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