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Beggs PJ, Trueck S, Linnenluecke MK, Bambrick H, Capon AG, Hanigan IC, Arriagada NB, Cross TJ, Friel S, Green D, Heenan M, Jay O, Kennard H, Malik A, McMichael C, Stevenson M, Vardoulakis S, Dang TN, Garvey G, Lovett R, Matthews V, Phung D, Woodward AJ, Romanello MB, Zhang Y. The 2023 report of the MJA-Lancet Countdown on health and climate change: sustainability needed in Australia's health care sector. Med J Aust 2024; 220:282-303. [PMID: 38522009 DOI: 10.5694/mja2.52245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 12/06/2023] [Indexed: 03/25/2024]
Abstract
The MJA-Lancet Countdown on health and climate change in Australia was established in 2017 and produced its first national assessment in 2018 and annual updates in 2019, 2020, 2021 and 2022. It examines five broad domains: health hazards, exposures and impacts; adaptation, planning and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement. In this, the sixth report of the MJA-Lancet Countdown, we track progress on an extensive suite of indicators across these five domains, accessing and presenting the latest data and further refining and developing our analyses. Our results highlight the health and economic costs of inaction on health and climate change. A series of major flood events across the four eastern states of Australia in 2022 was the main contributor to insured losses from climate-related catastrophes of $7.168 billion - the highest amount on record. The floods also directly caused 23 deaths and resulted in the displacement of tens of thousands of people. High red meat and processed meat consumption and insufficient consumption of fruit and vegetables accounted for about half of the 87 166 diet-related deaths in Australia in 2021. Correction of this imbalance would both save lives and reduce the heavy carbon footprint associated with meat production. We find signs of progress on health and climate change. Importantly, the Australian Government released Australia's first National Health and Climate Strategy, and the Government of Western Australia is preparing a Health Sector Adaptation Plan. We also find increasing action on, and engagement with, health and climate change at a community level, with the number of electric vehicle sales almost doubling in 2022 compared with 2021, and with a 65% increase in coverage of health and climate change in the media in 2022 compared with 2021. Overall, the urgency of substantial enhancements in Australia's mitigation and adaptation responses to the enormous health and climate change challenge cannot be overstated. Australia's energy system, and its health care sector, currently emit an unreasonable and unjust proportion of greenhouse gases into the atmosphere. As the Lancet Countdown enters its second and most critical phase in the leadup to 2030, the depth and breadth of our assessment of health and climate change will be augmented to increasingly examine Australia in its regional context, and to better measure and track key issues in Australia such as mental health and Aboriginal and Torres Strait Islander health and wellbeing.
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Affiliation(s)
| | | | | | - Hilary Bambrick
- National Centre for Epidemiology and Population Health, Australian National University, Canberra, ACT
| | - Anthony G Capon
- Monash Sustainable Development Institute, Monash University, Melbourne, VIC
| | | | | | | | | | - Donna Green
- Climate Change Research Centre and ARC Centre of Excellence for Climate Extremes, UNSW, Sydney, NSW
| | - Maddie Heenan
- Australian Prevention Partnership Centre, Sax Institute, Sydney, NSW
- The George Institute for Global Health, Sydney, NSW
| | - Ollie Jay
- Thermal Ergonomics Laboratory, University of Sydney, Sydney, NSW
| | - Harry Kennard
- Center on Global Energy Policy, Columbia University, New York, NY, USA
| | | | | | - Mark Stevenson
- Transport, Health and Urban Design (THUD) Research Lab, University of Melbourne, Melbourne, VIC
| | - Sotiris Vardoulakis
- National Centre for Epidemiology and Population Health, Australian National University, Canberra, ACT
| | - Tran N Dang
- University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | | | - Raymond Lovett
- National Centre for Epidemiology and Population Health, Australian National University, Canberra, ACT
- Australian Institute of Aboriginal and Torres Strait Islander Studies, Canberra, ACT
| | - Veronica Matthews
- University Centre for Rural Health, University of Sydney, Sydney, NSW
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Linh Tran NQ, Cam Hong Le HT, Pham CT, Nguyen XH, Tran ND, Thi Tran TH, Nghiem S, Ly Luong TM, Bui V, Nguyen-Huy T, Doan VQ, Dang KA, Thuong Do TH, Thi Ngo HK, Nguyen TV, Nguyen NH, Do MC, Ton TN, Thu Dang TA, Nguyen K, Tran XB, Thai P, Phung D. Climate change and human health in Vietnam: a systematic review and additional analyses on current impacts, future risk, and adaptation. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2023; 40:100943. [PMID: 38116497 PMCID: PMC10730327 DOI: 10.1016/j.lanwpc.2023.100943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 09/29/2023] [Accepted: 10/09/2023] [Indexed: 12/21/2023]
Abstract
This study aims to investigate climate change's impact on health and adaptation in Vietnam through a systematic review and additional analyses of heat exposure, heat vulnerability, awareness and engagement, and projected health costs. Out of 127 reviewed studies, findings indicated the wider spread of infectious diseases, and increased mortality and hospitalisation risks associated with extreme heat, droughts, and floods. However, there are few studies addressing health cost, awareness, engagement, adaptation, and policy. Additional analyses showed rising heatwave exposure across Vietnam and global above-average vulnerability to heat. By 2050, climate change is projected to cost up to USD1-3B in healthcare costs, USD3-20B in premature deaths, and USD6-23B in work loss. Despite increased media focus on climate and health, a gap between public and government publications highlighted the need for more governmental engagement. Vietnam's climate policies have faced implementation challenges, including top-down approaches, lack of cooperation, low adaptive capacity, and limited resources.
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Affiliation(s)
- Nu Quy Linh Tran
- Centre for Environment and Population Health, School of Medicine and Dentistry, Griffith University, Australia
| | - Huynh Thi Cam Hong Le
- Child Health Research Centre, Faculty of Medicine, University of Queensland, Australia
| | | | - Xuan Huong Nguyen
- Centre for Scientific Research and International Collaboration, Phan Chau Trinh University, Quang Nam, Vietnam
| | - Ngoc Dang Tran
- University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | | | - Son Nghiem
- Department of Health Economics, Wellbeing and Society, Australian National University, Australia
| | - Thi Mai Ly Luong
- Faculty of Environmental Sciences, Vietnam University of Science, Hanoi, Vietnam
| | - Vinh Bui
- Faculty of Science and Engineering, Southern Cross University, Australia
| | - Thong Nguyen-Huy
- Centre for Applied Climate Sciences, University of Southern Queensland, Australia
| | - Van Quang Doan
- Centre for Computational Sciences, University of Tsukuba, Japan
| | - Kim Anh Dang
- Queensland Alliance for Environmental Health Sciences, The University of Queensland, Australia
| | - Thi Hoai Thuong Do
- University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - Hieu Kim Thi Ngo
- University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | | | - Ngoc Huy Nguyen
- Vietnam National University - Vietnam Japan University, Hanoi, Vietnam
| | - Manh Cuong Do
- Health Environment Management Agency, Ministry of Health, Vietnam
| | | | - Thi Anh Thu Dang
- Hue University of Medicine and Pharmacy, Hue University, Hue City, Vietnam
| | - Kien Nguyen
- Hue University of Economics, Hue University, Hue City, Vietnam
| | | | - Phong Thai
- Queensland Alliance for Environmental Health Sciences, The University of Queensland, Australia
| | - Dung Phung
- School of Public Health, The University of Queensland, Australia
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3
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Deep learning models for forecasting dengue fever based on climate data in Vietnam. PLoS Negl Trop Dis 2022; 16:e0010509. [PMID: 35696432 PMCID: PMC9232166 DOI: 10.1371/journal.pntd.0010509] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 06/24/2022] [Accepted: 05/17/2022] [Indexed: 11/30/2022] Open
Abstract
Background Dengue fever (DF) represents a significant health burden in Vietnam, which is forecast to worsen under climate change. The development of an early-warning system for DF has been selected as a prioritised health adaptation measure to climate change in Vietnam. Objective This study aimed to develop an accurate DF prediction model in Vietnam using a wide range of meteorological factors as inputs to inform public health responses for outbreak prevention in the context of future climate change. Methods Convolutional neural network (CNN), Transformer, long short-term memory (LSTM), and attention-enhanced LSTM (LSTM-ATT) models were compared with traditional machine learning models on weather-based DF forecasting. Models were developed using lagged DF incidence and meteorological variables (measures of temperature, humidity, rainfall, evaporation, and sunshine hours) as inputs for 20 provinces throughout Vietnam. Data from 1997–2013 were used to train models, which were then evaluated using data from 2014–2016 by Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). Results and discussion LSTM-ATT displayed the highest performance, scoring average places of 1.60 for RMSE-based ranking and 1.95 for MAE-based ranking. Notably, it was able to forecast DF incidence better than LSTM in 13 or 14 out of 20 provinces for MAE or RMSE, respectively. Moreover, LSTM-ATT was able to accurately predict DF incidence and outbreak months up to 3 months ahead, though performance dropped slightly compared to short-term forecasts. To the best of our knowledge, this is the first time deep learning methods have been employed for the prediction of both long- and short-term DF incidence and outbreaks in Vietnam using unique, rich meteorological features. Conclusion This study demonstrates the usefulness of deep learning models for meteorological factor-based DF forecasting. LSTM-ATT should be further explored for mitigation strategies against DF and other climate-sensitive diseases in the coming years. Dengue fever (DF) represents a significant health burden worldwide and in Vietnam, which is forecast to worsen under climate change. The development of an early-warning system for DF has been selected as a prioritised health adaptation measure to climate change in Vietnam. This study aimed to use deep learning models to develop a prediction model of DF rates in Vietnam using a wide range of climate factors as input variables to inform public health responses for outbreak prevention in the context of future climate change. The study found that LSTM-ATT outperformed competing models, scoring average places of 1.60 for RMSE-based ranking and 1.90 for MAE-based ranking. Notably, it was able to forecast DF incidence better than LSTM in 12 or 14 out of 20 provinces for MAE or RMSE, respectively. Moreover, LSTM-ATT was able to accurately predict DF incidence and outbreaks up to 3 months ahead, though performance dropped slightly compared to short-term forecasts. This is the first time deep learning methods have been employed for the prediction of both long- and short-term DF incidence and outbreaks in Vietnam using unique, rich climate features, and it demonstrates the usefulness of deep learning models for climate-based DF forecasting.
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Looi KW, Matsui Y, Kono M, Samudi C, Kojima N, Ong JX, Tan CA, Ang CS, Tan PHY, Shamnugam H, Sekaran SD, Syed Omar SF, Lum LCS. Evaluation of immature platelet fraction as a marker of dengue fever progression. Int J Infect Dis 2021; 110:187-194. [PMID: 34302960 DOI: 10.1016/j.ijid.2021.07.048] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 07/05/2021] [Accepted: 07/16/2021] [Indexed: 01/01/2023] Open
Abstract
OBJECTIVES Progression of dengue is often associated with thrombocytopenia resulting from viral-induced bone marrow suppression and immune-mediated peripheral platelet consumption. Immature platelet fraction (IPF), which can be measured using a haematology analyser, is a precursor indicating platelet formation in the bone marrow. This study evaluated the trend of IPF as an early recovery indicator of platelets in dengue patients with thrombocytopenia, and its relationship with severe dengue in conjunction with reticulocyte count. METHODS Hospitalized patients with dengue were enrolled and followed-up daily until discharge. Blood investigations included daily full blood counts and IPF measured using a haematology analyser. RESULTS In total, 287 patients with confirmed dengue were enrolled in this study, 25 of whom had severe dengue. All patients had a decreasing trend in platelet count in the first week of illness, concomitant with an increasing trend in the percentage of immature platelets to total platelets (IPF%) for more than 3 days prior to platelet recovery. IPF% was significantly increased in patients with severe dengue compared with patients with non-severe dengue on days 3-5 after the onset of fever. Reticulocyte count increased significantly in patients with severe dengue on day 5. CONCLUSIONS IPF can be utilized as an early recovery indicator of platelets in patients with dengue and thrombocytopenia.
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Affiliation(s)
- Kah Wai Looi
- Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | | | - Mari Kono
- Scientific Affairs, Sysmex Corporation, Kobe, Japan
| | | | | | - Jin Xu Ong
- Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Chin Aun Tan
- Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Chong Siang Ang
- Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
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Wang JN, Hou J, Zhong JY, Cao GP, Yu ZY, Wu YY, Li TQ, Liu QM, Gong ZY. Relationships between traditional larval indices and meteorological factors with the adult density of Aedes albopictus captured by BG-mosquito trap. PLoS One 2020; 15:e0234555. [PMID: 32525905 PMCID: PMC7289416 DOI: 10.1371/journal.pone.0234555] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2020] [Accepted: 05/28/2020] [Indexed: 12/02/2022] Open
Abstract
Objectives Larval indices have been used for Ae. albopictus surveillance for many years, while there is limited use in assessing dengue transmission risk and adult mosquito emergence. This study is aimed to explore the relationships between larval indices and the Ae. albopictus density captured by BG-mosquito trap (BG-trap) method, with considering the meteorological factors. Methods Data on larval density, adult mosquito density and meteorology factors were collected in an entomological survey carried out in Quzhou City, Zhejiang Province of China in 2018. The Spearman’s rank correlation and Pearson correlation were used for the analysis on the correlation of density indices. Generalized additive models were established to analyze the influencing factors of mosquito density. Results Breteau index (BI), House index (HI) and Container index (CI) were highly correlated with each other (r>0.7, p<0.05). The Ae. albopictus density was significantly correlated with CI (rs = 0.260, p<0.05), CI pre one week (rs = 0.259, p<0.05), and CI pre three weeks (rs = 0.329, p<0.05). BI was correlated with female Ae. albopictus density pre 4 weeks (r = -0.299, p<0.05). Female Ae. albopictus density was correlated with CI pre 3 weeks (rs = 0.303, p<0.05). The influencing factors of BI were average wind speed pre 1 week, average temperature and female Ae. albopictus density pre 4 weeks. The influencing factors of CI were average humidity pre 3 weeks and average temperature. The influencing factors of HI were average temperature and precipitation pre 4 weeks. The influencing factor of Ae. albopictus density and female Ae. albopictus density was temperature. Conclusions The adult Ae. albopictus density had low correlation with certain larval indices. Some of the meteorology factors played significant roles in the density of adult Ae. albopictus and larva with or without a time lag.
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Affiliation(s)
- Jin-Na Wang
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Juan Hou
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Jian-Yue Zhong
- Quzhou Center for Disease Control and Prevention, Quzhou, China
| | - Guo-Ping Cao
- Quzhou Center for Disease Control and Prevention, Quzhou, China
| | - Zhang-You Yu
- Quzhou Center for Disease Control and Prevention, Quzhou, China
| | - Yu-Yan Wu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Tian-Qi Li
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Qin-Mei Liu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Zhen-Yu Gong
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
- * E-mail:
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Ashmore P, Lindahl JF, Colón-González FJ, Sinh Nam V, Quang Tan D, Medley GF. Spatiotemporal and Socioeconomic Risk Factors for Dengue at the Province Level in Vietnam, 2013-2015: Clustering Analysis and Regression Model. Trop Med Infect Dis 2020; 5:tropicalmed5020081. [PMID: 32438628 PMCID: PMC7345007 DOI: 10.3390/tropicalmed5020081] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Revised: 05/05/2020] [Accepted: 05/14/2020] [Indexed: 01/22/2023] Open
Abstract
Dengue is a serious infectious disease threat in Vietnam, but its spatiotemporal and socioeconomic risk factors are not currently well understood at the province level across the country and on a multiannual scale. We explore spatial trends, clusters and outliers in dengue case counts at the province level from 2011–2015 and use this to extract spatiotemporal variables for regression analysis of the association between dengue case counts and selected spatiotemporal and socioeconomic variables from 2013–2015. Dengue in Vietnam follows anticipated spatial trends, with a potential two-year cycle of high-high clusters in some southern provinces. Small but significant associations are observed between dengue case counts and mobility, population density, a province’s dengue rates the previous year, and average dengue rates two years previous in first and second order contiguous neighbours. Significant associations were not found between dengue case counts and housing pressure, access to electricity, clinician density, province-adjusted poverty rate, percentage of children below one vaccinated, or percentage of population in urban settings. These findings challenge assumptions about socioeconomic and spatiotemporal risk factors for dengue, and support national prevention targeting in Vietnam at the province level. They may also be of wider relevance for the study of other arboviruses, including Japanese encephalitis, Zika, and Chikungunya.
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Affiliation(s)
- Polly Ashmore
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London WC1H 9SH, UK
| | - Johanna F Lindahl
- Department of Medical Biochemistry and Microbiology, Uppsala University, SE-751 23 Uppsala, Sweden
- International Livestock Research Institute, Hanoi 10 000, Vietnam
- Department of Clinical Sciences, Swedish University of Agricultural Sciences, SE-750 07 Uppsala, Sweden
| | - Felipe J Colón-González
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London WC1H 9SH, UK
| | - Vu Sinh Nam
- National Institute of Hygiene and Epidemiology, Hanoi 10 000, Vietnam
| | - Dang Quang Tan
- General Department of Preventive Medicine, Ministry of Health of Vietnam, Hanoi 10 000, Vietnam
| | - Graham F Medley
- Department of Global Health and Development, London School of Hygiene & Tropical Medicine, London WC1H 9SH, UK
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Tuyet Hanh TT, Huong LTT, Huong NTL, Linh TNQ, Quyen NH, Nhung NTT, Ebi K, Cuong ND, Van Nhu H, Kien TM, Hales S, Cuong DM, Tho NTT, Toan LQ, Bich NN, Van Minh H. Vietnam Climate Change and Health Vulnerability and Adaptation Assessment, 2018. ENVIRONMENTAL HEALTH INSIGHTS 2020; 14:1178630220924658. [PMID: 32612364 PMCID: PMC7309337 DOI: 10.1177/1178630220924658] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Accepted: 04/15/2020] [Indexed: 05/22/2023]
Abstract
BACKGROUND The Global Climate Risk Index 2020 ranked Vietnam as the sixth country in the world most affected by climate variability and extreme weather events over the period 1999-2018. Sea level rise and extreme weather events are projected to be more severe in coming decades, which, without additional action, will increase the number of people at risk of climate-sensitive diseases, challenging the health system. This article summaries the results of a health vulnerability and adaptation (V&A) assessment conducted in Vietnam as evidences for development of the National Climate Change Health Adaptation Plan to 2030. METHODS The assessment followed the first 4 steps outlined in the World Health Organization's Guidelines in conducting "Vulnerability and Adaptation Assessments." A framework and list of indicators were developed for semi-quantitative assessment for the period 2013 to 2017. Three sets of indicators were selected to assess the level of (1) exposure to climate change and extreme weather events, (2) health sensitivity, and (3) adaptation capacity. The indicators were rated and analyzed using a scoring system from 1 to 5. RESULTS The results showed that climate-sensitive diseases were common, including dengue fever, diarrheal, influenza, etc, with large burdens of disease that are projected to increase. From 2013 to 2017, the level of "exposure" to climate change-related hazards of the health sector was "high" to "very high," with an average score from 3.5 to 4.4 (out of 5.0). For "health sensitivity," the scores decreased from 3.8 in 2013 to 3.5 in 2017, making the overall rating as "high." For "adaptive capacity," the scores were from 4.0 to 4.1, which meant adaptive capacity was "very low." The overall V&A rating in 2013 was "very high risk" (score 4.1) and "high risk" with scores of 3.8 in 2014 and 3.7 in 2015 to 2017. CONCLUSIONS Adaptation actions of the health sector are urgently needed to reduce the vulnerability to climate change in coming decades. Eight adaptation solutions, among recommendations of V&A assessment, were adopted in the National Health Climate Change Adaptation Plan.
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Affiliation(s)
- Tran Thi Tuyet Hanh
- Faculty of Environmental and Occupational Health, Hanoi University of Public Health, Hanoi, Vietnam
| | - Le Thi Thanh Huong
- Faculty of Environmental and Occupational Health, Hanoi University of Public Health, Hanoi, Vietnam
- Le Thi Thanh Huong, Hanoi University of Public Health, 1A Duc Thang Road, Duc Thang Ward, North Tu Liem District, Hanoi 100000, Vietnam.
| | | | - Tran Nu Quy Linh
- Center for Environment and Population Health, School of Medicine, Griffith University, Brisbane, Queensland, Australia
| | - Nguyen Huu Quyen
- Climate research and Climate Forecasting Division, Institute of Hydrology and Meteorology Science and Climate Change, Hanoi, Vietnam
| | | | - Kristie Ebi
- Center for Health and the Global Environment, University of Washington, Seattle, WA, USA
| | | | - Ha Van Nhu
- Faculty of Environmental and Occupational Health, Hanoi University of Public Health, Hanoi, Vietnam
| | - Tran Mai Kien
- Climate Change Research Center, Institute of Hydrology and Meteorology Science and Climate Change, Hanoi, Vietnam
| | - Simon Hales
- Public Health Department, University of Otago, Otago, New Zealand
| | - Do Manh Cuong
- Vietnam Health Environment Management Agency, Hanoi, Vietnam
| | - Nguyen Thi Thi Tho
- Department of Non-Communicable Diseases Prevention and Control, National Institute of Hygiene and Epidemiology, Hanoi, Vietnam
| | - Luu Quoc Toan
- Faculty of Environmental and Occupational Health, Hanoi University of Public Health, Hanoi, Vietnam
| | - Nguyen Ngoc Bich
- Faculty of Environmental and Occupational Health, Hanoi University of Public Health, Hanoi, Vietnam
| | - Hoang Van Minh
- Vice-Rector, Hanoi University of Public Health, Hanoi, Vietnam
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Thi Tuyet-Hanh T, Nhat Cam N, Thi Thanh Huong L, Khanh Long T, Mai Kien T, Thi Kim Hanh D, Huu Quyen N, Nu Quy Linh T, Rocklöv J, Quam M, Van Minh H. Climate Variability and Dengue Hemorrhagic Fever in Hanoi, Viet Nam, During 2008 to 2015. Asia Pac J Public Health 2018; 30:532-541. [PMID: 30045631 DOI: 10.1177/1010539518790143] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Dengue fever/dengue hemorrhagic fever (DF/DHF) has been an important public health challenge in Viet Nam and worldwide. This study was implemented in 2016-2017 using retrospective secondary data to explore associations between monthly DF/DHF cases and climate variables during 2008 to 2015. There were 48 175 DF/DHF cases reported, and the highest number of cases occurred in November. There were significant correlations between monthly DF/DHF cases with monthly mean of evaporation ( r = 0.236, P < .05), monthly relative humidity ( r = -0.358, P < .05), and monthly total hours of sunshine ( r = 0.389, P < .05). The results showed significant correlation in lag models but did not find direct correlations between monthly DF/DHF cases and monthly average rainfall and temperature. The study recommended that health staff in Hanoi should monitor DF/DHF cases at the beginning of epidemic period, starting from May, and apply timely prevention and intervention measures to avoid the spreading of the disease in the following months. A larger scale study for a longer period of time and adjusting for other potential influencing factors could better describe the correlations, modelling/projection, and developing an early warning system for the disease, which is important under the impacts of climate change and climate variability.
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Affiliation(s)
| | | | | | - Tran Khanh Long
- 3 Queensland University of Technology, Brisbane, Queensland, Australia
| | - Tran Mai Kien
- 4 Institute of Meteorology, Hydrology, and Climate Change, Hanoi, Viet Nam
| | | | - Nguyen Huu Quyen
- 4 Institute of Meteorology, Hydrology, and Climate Change, Hanoi, Viet Nam
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