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Ngu L, Fotso HO, Nyebe I, Tchadji JC, Ambada G, Ndah A, Atechi B, Lissom A, Atabonkeng PE, Chukwuma G, Efezeuh V, Gyu PC, Esimone C, Nguedia JCA, Akum EA, Okeke M, Titanji VPK, Mbacham W, Bopda-Waffo A, Wapimewah GN. Immunoglobulin G (IgG) specific responses to recombinant Qβ displayed MSP3 and UB05 in plasma of asymptomatic Plasmodium falciparum-infected children living in two different agro-ecological settings of Cameroon. Pan Afr Med J 2024; 47:175. [PMID: 39036016 PMCID: PMC11260061 DOI: 10.11604/pamj.2024.47.175.38169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 02/25/2024] [Indexed: 07/23/2024] Open
Abstract
Introduction in areas with intense perennial malaria transmission, limited data is available on the impact of environmental conditions especially rainfall on naturally acquired immunity against promising malaria vaccine candidates. For this reason, we have compared IgG antibody responses specific to Plasmodium spp. derived MSP3 and UB05 vaccine candidates, in plasma of children living in two areas of Cameroon differing in rainfall conditions. Methods data about children less than 5 years old was collected during the years 2017 and 2018. Next malaria asymptomatic P. falciparum (Pf) infected children were selected following malaria test confirmation. MSP3 and UB05 specific IgG antibody responses were measured in participant´s plasma using enzyme-linked immunosorbent assay (ELISA). Results interestingly, IgG antibody responses specific to UB05 were significantly higher (p<0.0001) in Pf-negative children when compared to their asymptomatic Pf-infected counterparts living in monomodal rainfall areas. In contrast, a significantly higher (p<0.0001) IgG response to MSP3 was observed instead in asymptomatic Pf-infected children in the same population. In addition, IgG responses specific to UB05 remained significantly higher in bimodal when compared to monomodal rainfall areas irrespective of children´s Pf infection status (p<0.0055 for Pf-positive and p<0.0001 for negative children). On the contrary, IgG antibody responses specific to MSP3 were significantly higher in bimodal relative to monomodal rainfall areas (P<0.0001) just for Pf-negative children. Conclusion thus IgG antibody responses specific to UBO5 are a better correlate of naturally acquired immunity against malaria in Pf-negative Cameroonian children especially in monomodal rainfall areas.
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Affiliation(s)
- Loveline Ngu
- Laboratory of Vaccinology/Biobanking, Chantal Biya International Reference Center for Research on the Prevention and Management of HIV/AIDS, Yaounde, Cameroon
- Department of Biochemistry, Faculty of Sciences, University of Yaounde I, Yaounde, Cameroon
| | - Herve Ouambo Fotso
- Laboratory of Vaccinology/Biobanking, Chantal Biya International Reference Center for Research on the Prevention and Management of HIV/AIDS, Yaounde, Cameroon
- Pan African Center for Clinical and Translational Sciences (PANECTS), Yaounde, Cameroon
| | - Inès Nyebe
- Laboratory of Vaccinology/Biobanking, Chantal Biya International Reference Center for Research on the Prevention and Management of HIV/AIDS, Yaounde, Cameroon
- Pan African Center for Clinical and Translational Sciences (PANECTS), Yaounde, Cameroon
- Department of Microbiology, Faculty of Sciences, University of Yaounde I, Yaounde, Cameroon
| | - Jules Colince Tchadji
- Laboratory of Vaccinology/Biobanking, Chantal Biya International Reference Center for Research on the Prevention and Management of HIV/AIDS, Yaounde, Cameroon
- Department of Animal Biology and Physiology, Faculty Of Sciences, University of Yaounde I, Yaoundé, Cameroon
| | - Georgia Ambada
- Laboratory of Vaccinology/Biobanking, Chantal Biya International Reference Center for Research on the Prevention and Management of HIV/AIDS, Yaounde, Cameroon
- Department of Animal Biology and Physiology, Faculty Of Sciences, University of Yaounde I, Yaoundé, Cameroon
| | - Akeleke Ndah
- Pan African Center for Clinical and Translational Sciences (PANECTS), Yaounde, Cameroon
| | - Bloomfield Atechi
- Pan African Center for Clinical and Translational Sciences (PANECTS), Yaounde, Cameroon
| | - Abel Lissom
- Laboratory of Vaccinology/Biobanking, Chantal Biya International Reference Center for Research on the Prevention and Management of HIV/AIDS, Yaounde, Cameroon
- Department of Biological Sciences, Faculty of Sciences, University of Bamenda, Bamenda, Cameroon
| | | | - George Chukwuma
- Department of Medical Laboratory Science, College of Health Sciences, Nnamdi Azikiwe University, Awka, Nigeria
| | - Vitalis Efezeuh
- Department of Biochemistry and Molecular Biology, University of Buea, Buea, Cameroon
| | - Park Chae Gyu
- Laboratory of Immunology, Brain Korea 21 PLUS Project for Medical Science, Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Charles Esimone
- Department of Pharmaceutical Microbiology and Biotechnology, Nnamdi Azikiwe University, Awka, Nigeria
| | | | - Eric Achidi Akum
- Department of Medical Laboratory Sciences, University of Buea, Buea, Cameroon
| | - Malachy Okeke
- Department of Natural and Environmental Sciences, Biomedical Science Concentration, School of Arts and Sciences, American University of Nigeria, 98 Lamido Zubairu Way, Yola, Nigeria
| | | | - Wilfred Mbacham
- Department of Biochemistry, Faculty of Sciences, University of Yaounde I, Yaounde, Cameroon
| | - Alain Bopda-Waffo
- Pan African Center for Clinical and Translational Sciences (PANECTS), Yaounde, Cameroon
- Biochemistry and Molecular Biology, Indiana University School of Medicine, 635 Barnhill Drive, MS1017Q Lab MS1015, Indianapolis, IN, United States of America
| | - Godwin Nchinda Wapimewah
- Laboratory of Vaccinology/Biobanking, Chantal Biya International Reference Center for Research on the Prevention and Management of HIV/AIDS, Yaounde, Cameroon
- Pan African Center for Clinical and Translational Sciences (PANECTS), Yaounde, Cameroon
- Department of Pharmaceutical Microbiology and Biotechnology, Nnamdi Azikiwe University, Awka, Nigeria
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Lu G, Zhao L, Chai L, Cao Y, Chong Z, Liu K, Lu Y, Zhu G, Xia P, Müller O, Zhu G, Cao J. Assessing the risk of malaria local transmission and re-introduction in China from pre-elimination to elimination: A systematic review. Acta Trop 2024; 249:107082. [PMID: 38008371 DOI: 10.1016/j.actatropica.2023.107082] [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: 09/27/2023] [Revised: 11/22/2023] [Accepted: 11/23/2023] [Indexed: 11/28/2023]
Abstract
Assessing the risk of malaria local transmission and re-introduction is crucial for the preparation and implementation of an effective elimination campaign and the prevention of malaria re-introduction in China. Therefore, this review aims to evaluate the risk factors for malaria local transmission and re-introduction in China over the period of pre-elimination to elimination. Data were obtained from six databases searched for studies that assessed malaria local transmission risk before malaria elimination and re-introduction risk after the achievement of malaria elimination in China since the launch of the NMEP in 2010, employing the keywords "malaria" AND ("transmission" OR "re-introduction") and their synonyms. A total of 8,124 articles were screened and 53 articles describing 55 malaria risk assessment models in China from 2010 to 2023, including 40 models assessing malaria local transmission risk (72.7%) and 15 models assessing malaria re-introduction risk (27.3%). Factors incorporated in the 55 models were extracted and classified into six categories, including environmental and meteorological factors (39/55, 70.9%), historical epidemiology (35/55, 63.6%), vectorial factors (32/55, 58.2%), socio-demographic information (15/26, 53.8%), factors related to surveillance and response capacity (18/55, 32.7%), and population migration aspects (13/55, 23.6%). Environmental and meteorological factors as well as vectorial factors were most commonly incorporated in models assessing malaria local transmission risk (29/40, 72.5% and 21/40, 52.5%) and re-introduction risk (10/15, 66.7% and 11/15, 73.3%). Factors related to surveillance and response capacity and population migration were also important in malaria re-introduction risk models (9/15, 60%, and 6/15, 40.0%). A total of 18 models (18/55, 32.7%) reported the modeling performance. Only six models were validated internally and five models were validated externally. Of 53 incorporated studies, 45 studies had a quality assessment score of seven and above. Environmental and meteorological factors as well as vectorial factors play a significant role in malaria local transmission and re-introduction risk assessment. The factors related to surveillance and response capacity and population migration are more important in assessing malaria re-introduction risk. The internal and external validation of the existing models needs to be strengthened in future studies.
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Affiliation(s)
- Guangyu Lu
- School of Public Health, Medical College of Yangzhou University, Yangzhou University, Yangzhou, China; Jiangsu Key Laboratory of Zoonosis, Yangzhou, China.
| | - Li Zhao
- School of Public Health, Medical College of Yangzhou University, Yangzhou University, Yangzhou, China
| | - Liying Chai
- School of Public Health, Medical College of Yangzhou University, Yangzhou University, Yangzhou, China
| | - Yuanyuan Cao
- National Health Commission Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory on Parasite and Vector Control Technology, Jiangsu Institute of Parasitic Diseases, Wuxi, China
| | - Zeyin Chong
- School of Public Health, Medical College of Yangzhou University, Yangzhou University, Yangzhou, China
| | - Kaixuan Liu
- School of Public Health, Medical College of Yangzhou University, Yangzhou University, Yangzhou, China
| | - Yan Lu
- Nanjing Health and Customs Quarantine Office, Nanjing, China
| | - Guoqiang Zhu
- Jiangsu Key Laboratory of Zoonosis, Yangzhou, China
| | - Pengpeng Xia
- Jiangsu Key Laboratory of Zoonosis, Yangzhou, China
| | - Olaf Müller
- Institute of Global Health, Medical School, Ruprecht-Karls-University Heidelberg, Germany
| | - Guoding Zhu
- National Health Commission Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory on Parasite and Vector Control Technology, Jiangsu Institute of Parasitic Diseases, Wuxi, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
| | - Jun Cao
- National Health Commission Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory on Parasite and Vector Control Technology, Jiangsu Institute of Parasitic Diseases, Wuxi, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
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Meena P, Jha V. Environmental Change, Changing Biodiversity, and Infections-Lessons for Kidney Health Community. Kidney Int Rep 2023; 8:1714-1729. [PMID: 37705916 PMCID: PMC10496083 DOI: 10.1016/j.ekir.2023.07.002] [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: 07/07/2023] [Accepted: 07/12/2023] [Indexed: 09/15/2023] Open
Abstract
There is a direct and accelerating connection between ongoing environmental change, the unprecedented decline in biodiversity, and the increase in infectious disease epidemiology worldwide. Rising global temperatures are threatening the biodiversity that underpins the richness and diversity of flora and fauna species in our ecosystem. Anthropogenic activities such as burning fossil fuels, deforestation, rapid urbanization, and expanding population are the primary drivers of environmental change resulting in biodiversity collapse. Climate change is influencing the emergence, prevalence, and transmission of infectious diseases both directly and through its impact on biodiversity. The environment is gradually becoming more suitable for infectious diseases by affecting a variety of pathogens, hosts, and vectors and by favoring transmission rates in many parts of the world that were until recently free of these infections. The acute effects of these zoonotic, vector and waterborne diseases are well known; however, evidence is emerging about their role in the development of chronic kidney disease. The pathways linking environmental change and biodiversity loss to infections impacting kidney health are diverse and complex. Climate change and biodiversity loss disproportionately affect the vulnerable and limit their ability to access healthcare. The kidney health community needs to contribute to the issue of environmental change and biodiversity loss through multisectoral action alongside government, policymakers, advocates, businesses, and the general population. We describe various aspects of the environmental change effects on the transmission and emergence of infectious diseases particularly focusing on its potential impact on kidney health. We also discuss the adaptive and mitigation measures and the gaps in research and policy action.
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Affiliation(s)
- Priti Meena
- Department of Nephrology, All India Institute of Medical Sciences, Bhubaneswar, India
| | - Vivekanand Jha
- George Institute for Global Health, UNSW, New Delhi, India
- Prasanna School of Public Health, Manipal Academy of Higher Education, Manipal, India
- School of Public Health, Imperial College, London, UK
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Lu G, Zhang D, Chen J, Cao Y, Chai L, Liu K, Chong Z, Zhang Y, Lu Y, Heuschen AK, Müller O, Zhu G, Cao J. Predicting the risk of malaria re-introduction in countries certified malaria-free: a systematic review. Malar J 2023; 22:175. [PMID: 37280626 DOI: 10.1186/s12936-023-04604-4] [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: 01/10/2023] [Accepted: 05/22/2023] [Indexed: 06/08/2023] Open
Abstract
BACKGROUND Predicting the risk of malaria in countries certified malaria-free is crucial for the prevention of re-introduction. This review aimed to identify and describe existing prediction models for malaria re-introduction risk in eliminated settings. METHODS A systematic literature search following the PRISMA guidelines was carried out. Studies that developed or validated a malaria risk prediction model in eliminated settings were included. At least two authors independently extracted data using a pre-defined checklist developed by experts in the field. The risk of bias was assessed using both the prediction model risk of bias assessment tool (PROBAST) and the adapted Newcastle-Ottawa Scale (aNOS). RESULTS A total 10,075 references were screened and 10 articles describing 11 malaria re-introduction risk prediction models in 6 countries certified malaria free. Three-fifths of the included prediction models were developed for the European region. Identified parameters predicting malaria re-introduction risk included environmental and meteorological, vectorial, population migration, and surveillance and response related factors. Substantial heterogeneity in predictors was observed among the models. All studies were rated at a high risk of bias by PROBAST, mostly because of a lack of internal and external validation of the models. Some studies were rated at a low risk of bias by the aNOS scale. CONCLUSIONS Malaria re-introduction risk remains substantial in many countries that have eliminated malaria. Multiple factors were identified which could predict malaria risk in eliminated settings. Although the population movement is well acknowledged as a risk factor associated with the malaria re-introduction risk in eliminated settings, it is not frequently incorporated in the risk prediction models. This review indicated that the proposed models were generally poorly validated. Therefore, future emphasis should be first placed on the validation of existing models.
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Affiliation(s)
- Guangyu Lu
- School of Public Health, Medical College of Yangzhou University, Yangzhou University, Yangzhou, 225007, China.
- Jiangsu Key Laboratory of Zoonosis, Yangzhou, China.
| | - Dongying Zhang
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Juan Chen
- School of Nursing, Medical College of Yangzhou University, Yangzhou University, Yangzhou, China
| | - Yuanyuan Cao
- National Health Commission Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory On Parasite and Vector Control Technology, Jiangsu Institute of Parasitic Diseases, Wuxi, China
| | - Liying Chai
- School of Public Health, Medical College of Yangzhou University, Yangzhou University, Yangzhou, 225007, China
| | - Kaixuan Liu
- School of Public Health, Medical College of Yangzhou University, Yangzhou University, Yangzhou, 225007, China
| | - Zeying Chong
- School of Public Health, Medical College of Yangzhou University, Yangzhou University, Yangzhou, 225007, China
| | - Yuying Zhang
- School of Public Health, Medical College of Yangzhou University, Yangzhou University, Yangzhou, 225007, China
| | - Yan Lu
- Nanjing Health and Customs Quarantine Office, Nanjing, China
| | | | - Olaf Müller
- Institute of Global Health, Medical School, Ruprecht-Karls-University, Heidelberg, Germany
| | - Guoding Zhu
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
- National Health Commission Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory On Parasite and Vector Control Technology, Jiangsu Institute of Parasitic Diseases, Wuxi, China.
| | - Jun Cao
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
- National Health Commission Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory On Parasite and Vector Control Technology, Jiangsu Institute of Parasitic Diseases, Wuxi, China.
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Kamana E, Bai D, Brown HE, Zhao J. The malaria transmission in Anhui province China. Infect Dis Model 2023; 8:1-10. [PMID: 36582746 PMCID: PMC9764179 DOI: 10.1016/j.idm.2022.11.009] [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: 09/07/2022] [Accepted: 11/22/2022] [Indexed: 11/28/2022] Open
Abstract
Plasmodium vivax and Plasmodium falciparum cases have opposite trends in Anhui China in the past decade. Long term and seasonal trends in the transmission rate of P. falciparum in Africa has been well studied, however that of P. vivax transmitted by Anopheles sinensis in China has not been investigated. There is a lot of work on the relationship between P. vivax cases and climatic factors in China, with sometimes contradicting results. However, how climatic factors affect transmission rate of P. vivax in China is unknown. We used Anhui province as an example to analyze the recent transmission dynamics where two types of malaria have been reported with differing etiologies. We examined breakpoints of the P. vivax and P. falciparum malaria long term dynamics in the recent decade. For locally transmitted P. vivax malaria, we analyzed the transmission rate and its seasonality using the combined human and mosquitos SIR-SI model with time-varied mosquito biting rate. We identified the effects of meteorological factors on the seasonality in transmission rate using a GAM model. For the imported P. falciparum malaria, we analyzed the potential reason for the observed increase in cases. The breakpoints of P. vivax and P. falciparum dynamics happened in a same year, 2010. The seasonality in the transmission rate of P. vivax malaria was high (42.4%) and was linearly associated with temperature and nonlinearly with rainfall. The abrupt increase in imported P. falciparum cases after the breakpoint was significantly related to the increased annual Chinese investment in Africa. Under the conditions of the existing vectors of malaria, long-term trends in climatic factors, and increasing trend in migration to/from endemic areas and imported malaria cases, we should be cautious of the possibility of the reestablishment of malaria in regions where it has been eliminated or the establishment of other vector-borne diseases.
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Affiliation(s)
- Eric Kamana
- Complexity Science Institute, Qingdao University, Qingdao, China
| | - Di Bai
- Complexity Science Institute, Qingdao University, Qingdao, China
| | - Heidi E. Brown
- Department of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, The University of Arizona, Tucson, AZ, USA
| | - Jijun Zhao
- Complexity Science Institute, Qingdao University, Qingdao, China
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Jacobsen AP, Khiew YC, Duffy E, O'Connell J, Brown E, Auwaerter PG, Blumenthal RS, Schwartz BS, McEvoy JW. Climate change and the prevention of cardiovascular disease. Am J Prev Cardiol 2022; 12:100391. [PMID: 36164332 PMCID: PMC9508346 DOI: 10.1016/j.ajpc.2022.100391] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 08/27/2022] [Accepted: 09/10/2022] [Indexed: 11/26/2022] Open
Abstract
Climate change is a worsening global crisis that will continue negatively impacting population health and well-being unless adaptation and mitigation interventions are rapidly implemented. Climate change-related cardiovascular disease is mediated by air pollution, increased ambient temperatures, vector-borne disease and mental health disorders. Climate change-related cardiovascular disease can be modulated by climate change adaptation; however, this process could result in significant health inequity because persons and populations of lower socioeconomic status have fewer adaptation options. Clear scientific evidence for climate change and its impact on human health have not yet resulted in the national and international impetus and policies necessary to slow climate change. As respected members of society who regularly communicate scientific evidence to patients, clinicians are well-positioned to advocate on the importance of addressing climate change. This narrative review summarizes the links between climate change and cardiovascular health, proposes actionable items clinicians and other healthcare providers can execute both in their personal life and as an advocate of climate policies, and encourages communication of the health impacts of climate change when counseling patients. Our aim is to inspire the reader to invest more time in communicating the most crucial public health issue of the 21st century to their patients.
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Affiliation(s)
- Alan P. Jacobsen
- Ciccarone Center for the Prevention of Cardiovascular Disease, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Yii Chun Khiew
- Division of Gastroenterology, Department of Gastroenterology, MedStar Georgetown University Hospital, Washington, DC, United States
| | - Eamon Duffy
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY, United States
| | - James O'Connell
- Department of Public Health, Health Service Executive West, Galway, Ireland
| | - Evans Brown
- Department of Medicine, Division of Hospital Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Paul G. Auwaerter
- Sherrilyn and Ken Fisher Center for Environmental Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Roger S. Blumenthal
- Ciccarone Center for the Prevention of Cardiovascular Disease, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Brian S. Schwartz
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - John William McEvoy
- Ciccarone Center for the Prevention of Cardiovascular Disease, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- National Institute for Prevention and Cardiovascular Health, National University of Ireland Galway, Galway, Ireland
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Baharom M, Soffian SSS, Peng CS, Baharudin MH, Mirza U, Madrim MF, Jeffree MS, Rahim SSSA, Hassan MR. Projecting Malaria Incidence Based on Climate Change Modeling Approach: A Systematic Review. Open Access Maced J Med Sci 2022. [DOI: 10.3889/oamjms.2022.10141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND: Climate change will affect the transmission of malaria by shifting the geographical space of the vector.
AIM: The review aims to examine the climate change modeling approach and climatic variables used for malaria projection.
METHODS: Articles were systematically searched from four databases, Scopus, Web of Science, PubMed, and SAGE. The PICO concept was used for formulation search and PRISMA approach to identify the final articles.
RESULTS: A total of 27 articles were retrieved and reviewed. There were six climate factors identified in this review: Temperature, rainfall/precipitation, humidity, wind, solar radiation, and climate change scenarios. Modeling approaches used to project future malarial trend includes mathematical and computational approach.
CONCLUSION: This review provides robust evidence of an association between the impact of climate change and malaria incidence. Prediction on seasonal patterns would be useful for malaria surveillance in public health prevention and mitigation strategies.
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Kamana E, Zhao J, Bai D. Predicting the impact of climate change on the re-emergence of malaria cases in China using LSTMSeq2Seq deep learning model: a modelling and prediction analysis study. BMJ Open 2022; 12:e053922. [PMID: 35361642 PMCID: PMC8971767 DOI: 10.1136/bmjopen-2021-053922] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
Abstract
OBJECTIVES Malaria is a vector-borne disease that remains a serious public health problem due to its climatic sensitivity. Accurate prediction of malaria re-emergence is very important in taking corresponding effective measures. This study aims to investigate the impact of climatic factors on the re-emergence of malaria in mainland China. DESIGN A modelling study. SETTING AND PARTICIPANTS Monthly malaria cases for four Plasmodium species (P. falciparum, P. malariae, P. vivax and other Plasmodium) and monthly climate data were collected for 31 provinces; malaria cases from 2004 to 2016 were obtained from the Chinese centre for disease control and prevention and climate parameters from China meteorological data service centre. We conducted analyses at the aggregate level, and there was no involvement of confidential information. PRIMARY AND SECONDARY OUTCOME MEASURES The long short-term memory sequence-to-sequence (LSTMSeq2Seq) deep neural network model was used to predict the re-emergence of malaria cases from 2004 to 2016, based on the influence of climatic factors. We trained and tested the extreme gradient boosting (XGBoost), gated recurrent unit, LSTM, LSTMSeq2Seq models using monthly malaria cases and corresponding meteorological data in 31 provinces of China. Then we compared the predictive performance of models using root mean squared error (RMSE) and mean absolute error evaluation measures. RESULTS The proposed LSTMSeq2Seq model reduced the mean RMSE of the predictions by 19.05% to 33.93%, 18.4% to 33.59%, 17.6% to 26.67% and 13.28% to 21.34%, for P. falciparum, P. vivax, P. malariae, and other plasmodia, respectively, as compared with other candidate models. The LSTMSeq2Seq model achieved an average prediction accuracy of 87.3%. CONCLUSIONS The LSTMSeq2Seq model significantly improved the prediction of malaria re-emergence based on the influence of climatic factors. Therefore, the LSTMSeq2Seq model can be effectively applied in the malaria re-emergence prediction.
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Affiliation(s)
- Eric Kamana
- Complexity Science Institute, School of Automation, Qingdao University, Qingdao, China
| | - Jijun Zhao
- Complexity Science Institute, School of Automation, Qingdao University, Qingdao, China
| | - Di Bai
- Complexity Science Institute, School of Automation, Qingdao University, Qingdao, China
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9
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Trájer AJ. The changing risk patterns of Plasmodium vivax malaria in Greece due to climate change. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2022; 32:665-690. [PMID: 32683891 DOI: 10.1080/09603123.2020.1793918] [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: 04/09/2020] [Revised: 07/01/2020] [Accepted: 07/06/2020] [Indexed: 06/11/2023]
Abstract
It has great importance to study the potential effects of climate change on Plasmodium vivax malaria in Greece because the country can be the origin of the spread of vivax malaria to the northern areas. The potential lengths of the transmission seasons of Plasmodium vivax malaria were forecasted for 2041-2060 and 2061-2080 and were combined. The potential ranges were predicted by Climate Envelope Modelling Method. The models show moderate areal increase and altitudinal shift in the malaria-endemic areas in Greece in the future. The length of the transmission season is predicted to increase by 1 to 2 months, mainly in the mid-elevation regions and the Aegean Archipelago. The combined factors also predict the decrease of vivax malaria-free area in Greece. It can be concluded that rather the elongation of the transmission season will lead to an increase of the malaria risk in Greece than the increase in the suitability values.
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Affiliation(s)
- Attila J Trájer
- Institute of Environmental Engineering, University of Pannonia, Veszprém, Hungary
- Department of Limnology, University of Pannonia, Veszprém, Hungary
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10
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Baharom M, Ahmad N, Hod R, Arsad FS, Tangang F. The Impact of Meteorological Factors on Communicable Disease Incidence and Its Projection: A Systematic Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph182111117. [PMID: 34769638 PMCID: PMC8583681 DOI: 10.3390/ijerph182111117] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 10/17/2021] [Accepted: 10/18/2021] [Indexed: 11/25/2022]
Abstract
Background: Climate change poses a real challenge and has contributed to causing the emergence and re-emergence of many communicable diseases of public health importance. Here, we reviewed scientific studies on the relationship between meteorological factors and the occurrence of dengue, malaria, cholera, and leptospirosis, and synthesized the key findings on communicable disease projection in the event of global warming. Method: This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 flow checklist. Four databases (Web of Science, Ovid MEDLINE, Scopus, EBSCOhost) were searched for articles published from 2005 to 2020. The eligible articles were evaluated using a modified scale of a checklist designed for assessing the quality of ecological studies. Results: A total of 38 studies were included in the review. Precipitation and temperature were most frequently associated with the selected climate-sensitive communicable diseases. A climate change scenario simulation projected that dengue, malaria, and cholera incidence would increase based on regional climate responses. Conclusion: Precipitation and temperature are important meteorological factors that influence the incidence of climate-sensitive communicable diseases. Future studies need to consider more determinants affecting precipitation and temperature fluctuations for better simulation and prediction of the incidence of climate-sensitive communicable diseases.
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Affiliation(s)
- Mazni Baharom
- Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur 56000, Malaysia; (M.B.); (R.H.); (F.S.A.)
| | - Norfazilah Ahmad
- Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur 56000, Malaysia; (M.B.); (R.H.); (F.S.A.)
- Correspondence:
| | - Rozita Hod
- Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur 56000, Malaysia; (M.B.); (R.H.); (F.S.A.)
| | - Fadly Syah Arsad
- Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur 56000, Malaysia; (M.B.); (R.H.); (F.S.A.)
| | - Fredolin Tangang
- Department of Earth Sciences and Environment, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia;
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11
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Rotejanaprasert C, Lee D, Ekapirat N, Sudathip P, Maude RJ. Spatiotemporal distributed lag modelling of multiple Plasmodium species in a malaria elimination setting. Stat Methods Med Res 2021; 30:22-34. [PMID: 33595402 DOI: 10.1177/0962280220938977] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
In much of the Greater Mekong Sub-region, malaria is now confined to patches and small foci of transmission. Malaria transmission is seasonal with the spatiotemporal patterns being associated with variation in environmental and climatic factors. However, the possible effect at different lag periods between meteorological variables and clinical malaria has not been well studied in the region. Thus, in this study we developed distributed lagged modelling accounting for spatiotemporal excessive zero cases in a malaria elimination setting. A multivariate framework was also extended to incorporate multiple data streams and investigate the spatiotemporal patterns from multiple parasite species via their lagged association with climatic variables. A simulation study was conducted to examine robustness of the methodology and a case study is provided of weekly data of clinical malaria cases at sub-district level in Thailand.
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Affiliation(s)
- Chawarat Rotejanaprasert
- Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.,Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Duncan Lee
- School of Mathematics and Statistics, University of Glasgow, Glasgow, UK
| | - Nattwut Ekapirat
- Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Prayuth Sudathip
- Division of Vector Borne Diseases, Department of Disease Control, Ministry of Public Health, Nonthaburi, Thailand
| | - Richard J Maude
- Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.,Harvard T.H. Chan School of Public Health, Harvard University, Cambridge, MA, USA.,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
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12
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Tong MX, Hansen A, Hanson-Easey S, Xiang J, Cameron S, Liu Q, Liu X, Sun Y, Weinstein P, Han GS, Mahmood A, Bi P. Public health professionals' perceptions of the capacity of China's CDCs to address emerging and re-emerging infectious diseases. J Public Health (Oxf) 2021; 43:209-216. [PMID: 31251367 DOI: 10.1093/pubmed/fdz070] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2019] [Revised: 05/13/2019] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND China's capacity to control and prevent emerging and re-emerging infectious diseases is critical to the nation's population health. This study aimed to explore the capacity of Centers for Disease Control and Prevention (CDCs) in China to deal with infectious diseases now and in the future. METHODS A survey was conducted in 2015 among 973 public health professionals at CDCs in Beijing and four provinces, to assess their capacity to deal with emerging and re-emerging infectious diseases. RESULTS Although most professionals were confident with the current capacity of CDCs to cope with outbreaks, nearly all indicated more funding was required to meet future challenges. Responses indicated that Yunnan Province faced more challenges than Anhui, Henan and Liaoning Provinces in being completely prepared and able to deal with outbreaks. Participants aged 20-39 years were more likely than those aged 40 and over to believe strategies such as interdisciplinary and international collaborations for disease surveillance and control, would assist capacity building. CONCLUSION The capacity of China's CDCs to deal with infectious diseases was excellent. However, findings suggest it is imperative to increase the number of skilled CDC staff, financial support, and strengthen county level staff training and health education programs.
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Affiliation(s)
- Michael Xiaoliang Tong
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
| | - Alana Hansen
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
| | - Scott Hanson-Easey
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
| | - Jianjun Xiang
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
| | - Scott Cameron
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
| | - 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
| | - Xiaobo 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
| | - Yehuan Sun
- Department of Epidemiology, Anhui Medical University, Hefei, Anhui, China
| | - Philip Weinstein
- School of Biological Sciences, The University of Adelaide, Adelaide, South Australia, Australia
| | - Gil-Soo Han
- Communications & Media Studies, School of Media, Film and Journalism, Monash University, Clayton, Victoria, Australia
| | - Afzal Mahmood
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
| | - Peng Bi
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
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13
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Liu Z, Wang S, Zhang Y, Xiang J, Tong MX, Gao Q, Zhang Y, Sun S, Liu Q, Jiang B, Bi P. Effect of temperature and its interactions with relative humidity and rainfall on malaria in a temperate city Suzhou, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:16830-16842. [PMID: 33394450 DOI: 10.1007/s11356-020-12138-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/26/2019] [Accepted: 12/16/2020] [Indexed: 06/12/2023]
Abstract
Malaria is a climate-sensitive infectious disease. Many ecological studies have investigated the independent impacts of ambient temperature on malaria. However, the optimal temperature measures of malaria and its interaction with other meteorological factors on malaria transmission are less understood. This study aims to investigate the effect of ambient temperature and its interactions with relative humidity and rainfall on malaria in Suzhou, a temperate climate city in Anhui Province, China. Weekly malaria and meteorological data from 2005 to 2012 were obtained for Suzhou. A distributed lag nonlinear model was conducted to quantify the effect of different temperature measures on malaria. The best measure was defined as that with the minimum quasi-Akaike information criterion. GeoDetector and Poisson regression models were employed to quantify the interactions of temperature, relative humidity, and rainfall on malaria transmission. A total of 13,382 malaria cases were notified in Suzhou from 2005 to 2012. Each 5 °C rise in average temperature over 10 °C resulted in a 22% (95% CI: 17%, 28%) increase in malaria cases at lag of 4 weeks. In terms of cumulative effects from lag 1 to 8 weeks, each 5 °C increase over 10 °C caused a 175% growth in malaria cases (95% CI: 139%, 216%). Average temperature achieved the best performance in terms of model fitting, followed by minimum temperature, most frequent temperature, and maximum temperature. Temperature had an interactive effect on malaria with relative humidity and rainfall. High temperature together with high relative humidity and high rainfall could accelerate the transmission of malaria. Meteorological factors may affect malaria transmission interactively. The research findings could be helpful in the development of weather-based malaria early warning system, especially in the context of climate change for the prevention of possible malaria resurgence.
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Affiliation(s)
- Zhidong Liu
- Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan City, Shandong Province, People's Republic of China
- Shandong University Climate Change and Health Center, Jinan City, Shandong Province, People's Republic of China
| | - Shuzi Wang
- Shandong University Climate Change and Health Center, Jinan City, Shandong Province, People's Republic of China
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, No. 44 Wenhuaxi Road, Jinan City, 250012, Shandong Province, People's Republic of China
| | - Ying Zhang
- School of Public Health, China Studies Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - Jianjun Xiang
- School of Public Health, Fujian Medical University, Fuzhou, People's Republic of China
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
| | - Michael Xiaoliang Tong
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
| | - Qi Gao
- Shandong University Climate Change and Health Center, Jinan City, Shandong Province, People's Republic of China
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, No. 44 Wenhuaxi Road, Jinan City, 250012, Shandong Province, People's Republic of China
| | - Yiwen Zhang
- Shandong University Climate Change and Health Center, Jinan City, Shandong Province, People's Republic of China
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, No. 44 Wenhuaxi Road, Jinan City, 250012, Shandong Province, People's Republic of China
| | - Shuyue Sun
- National Meteorological Center, China Meteorological Administration, Beijing, People's Republic of China
| | - Qiyong Liu
- Shandong University Climate Change and Health Center, Jinan City, Shandong Province, People's Republic of China
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People's Republic of China
| | - Baofa Jiang
- Shandong University Climate Change and Health Center, Jinan City, Shandong Province, People's Republic of China.
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, No. 44 Wenhuaxi Road, Jinan City, 250012, Shandong Province, People's Republic of China.
| | - Peng Bi
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
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14
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Malaria in Cambodia: A Retrospective Analysis of a Changing Epidemiology 2006-2019. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18041960. [PMID: 33670471 PMCID: PMC7922556 DOI: 10.3390/ijerph18041960] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 01/22/2021] [Accepted: 02/12/2021] [Indexed: 11/17/2022]
Abstract
Background: In Cambodia, malaria persists with changing epidemiology and resistance to antimalarials. This study aimed to describe how malaria has evolved spatially from 2006 to 2019 in Cambodia. Methods: We undertook a secondary analysis of existing malaria data from all government healthcare facilities in Cambodia. The epidemiology of malaria was described by sex, age, seasonality, and species. Spatial clusters at the district level were identified with a Poisson model. Results: Overall, incidence decreased from 7.4 cases/1000 population in 2006 to 1.9 in 2019. The decrease has been drastic for females, from 6.7 to 0.6/1000. Adults aged 15–49 years had the highest malaria incidence among all age groups. The proportion of Plasmodium (P.) falciparum + Mixed among confirmed cases declined from 87.9% (n = 67,489) in 2006 to 16.6% (n = 5290) in 2019. Clusters of P. falciparum + Mixed and P. vivax + Mixed were detected in forested provinces along all national borders. Conclusions: There has been a noted decrease in P. falciparum cases in 2019, suggesting that an intensification plan should be maintained. A decline in P. vivax cases was also noted, although less pronounced. Interventions aimed at preventing new infections of P. vivax and relapses should be prioritized. All detected malaria cases should be captured by the national surveillance system to avoid misleading trends.
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15
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Yi L, Xu X, Ge W, Xue H, Li J, Li D, Wang C, Wu H, Liu X, Zheng D, Chen Z, Liu Q, Bi P, Li J. The impact of climate variability on infectious disease transmission in China: Current knowledge and further directions. ENVIRONMENTAL RESEARCH 2019; 173:255-261. [PMID: 30928856 DOI: 10.1016/j.envres.2019.03.043] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Revised: 01/20/2019] [Accepted: 03/17/2019] [Indexed: 05/27/2023]
Abstract
BACKGROUND Climate change may lead to emerging and re-emerging infectious diseases and pose public health challenges to human health and the already overloaded healthcare system. It is therefore important to review current knowledge and identify further directions in China, the largest developing country in the world. METHODS A comprehensive literature review was conducted to examine the relationship between climate variability and infectious disease transmission in China in the new millennium. Literature was identified using the following MeSH terms and keywords: climatic variables [temperature, precipitation, rainfall, humidity, etc.] and infectious disease [viral, bacterial and parasitic diseases]. RESULTS Fifty-eight articles published from January 1, 2000 to May 30, 2018 were included in the final analysis, including bacterial diarrhea, dengue, malaria, Japanese encephalitis, HFRS, HFMD, Schistosomiasis. Each 1 °C rise may lead to 3.6%-14.8% increase in the incidence of bacillary dysentery disease in south China. A 1 °C rise was corresponded to an increase of 1.8%-5.9% in the weekly notified HFMD cases in west China. Each 1 °C rise of temperature, 1% rise in relative humidity and one hour rise in sunshine led to an increase of 0.90%, 3.99% and 0.68% in the monthly malaria cases, respectively. Climate change with the increased temperature and irregular patterns of rainfall may affect the pathogen reproduction rate, their spread and geographical distribution, change human behavior and influence the ecology of vectors, and increase the rate of disease transmission in different regions of China. CONCLUSION Exploring relevant adaptation strategies and the health burden of climate change will assist public health authorities to develop an early warning system and protect China's population health, especially in the new 1.5 °C scenario of the newly released IPCC special report.
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Affiliation(s)
- Liping Yi
- Division of Environmental Health, School of Public Health and Management, Weifang Medical University, Weifang, 261053, Shandong Province, PR China
| | - Xin Xu
- Department of Dentistry, Affiliated Hospital, Weifang Medical University, Weifang, 261053, Shandong Province, PR China
| | - Wenxin Ge
- Division of Environmental Health, School of Public Health and Management, Weifang Medical University, Weifang, 261053, Shandong Province, PR China
| | - Haibin Xue
- Clinical Laboratory, Weifang People's Hospital, Weifang, 261000. Shandong Province, PR China
| | - Jin Li
- Department of Dentistry, Weifang People's Hospital, Weifang, 261000, Shandong Province, PR China
| | - Daoyuan Li
- Department of Emergency, Weifang No.2 People's Hospital, Weifang, 261041, Shandong Province, PR China
| | - Chunping Wang
- Division of Environmental Health, School of Public Health and Management, Weifang Medical University, Weifang, 261053, Shandong Province, PR China
| | - Haixia Wu
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, PR China
| | - Xiaobo Liu
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, PR China
| | - Dashan Zheng
- Division of Environmental Health, School of Public Health and Management, Weifang Medical University, Weifang, 261053, Shandong Province, PR China
| | - Zhe Chen
- Division of Environmental Health, School of Public Health and Management, Weifang Medical University, Weifang, 261053, Shandong Province, PR China
| | - Qiyong Liu
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, PR China
| | - Peng Bi
- School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia; School of Public Health, Anhui Medical University, Hefei, 230032, Anhui Province, PR China.
| | - Jing Li
- Division of Environmental Health, School of Public Health and Management, Weifang Medical University, Weifang, 261053, Shandong Province, PR China; "Health Shandong" Major Social Risk Prediction and Governance Collaborative Innovation Center, Weifang, 261053, Shandong Province, PR China.
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16
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Malaria Risk Stratification and Modeling the Effect of Rainfall on Malaria Incidence in Eritrea. JOURNAL OF ENVIRONMENTAL AND PUBLIC HEALTH 2019; 2019:7314129. [PMID: 31061663 PMCID: PMC6466923 DOI: 10.1155/2019/7314129] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Accepted: 02/24/2019] [Indexed: 11/18/2022]
Abstract
Background Malaria risk stratification is essential to differentiate areas with distinct malaria intensity and seasonality patterns. The development of a simple prediction model to forecast malaria incidence by rainfall offers an opportunity for early detection of malaria epidemics. Objectives To construct a national malaria stratification map, develop prediction models and forecast monthly malaria incidences based on rainfall data. Methods Using monthly malaria incidence data from 2012 to 2016, the district level malaria stratification was constructed by nonhierarchical clustering. Cluster validity was examined by the maximum absolute coordinate change and analysis of variance (ANOVA) with a conservative post hoc test (Bonferroni) as the multiple comparison test. Autocorrelation and cross-correlation analyses were performed to detect the autocorrelation of malaria incidence and the lagged effect of rainfall on malaria incidence. The effect of rainfall on malaria incidence was assessed using seasonal autoregressive integrated moving average (SARIMA) models. Ljung-Box statistics for model diagnosis and stationary R-squared and Normalized Bayesian Information Criteria for model fit were used. Model validity was assessed by analyzing the observed and predicted incidences using the spearman correlation coefficient and paired samples t-test. Results A four cluster map (high risk, moderate risk, low risk, and very low risk) was the most valid stratification system for the reported malaria incidence in Eritrea. Monthly incidences were influenced by incidence rates in the previous months. Monthly incidence of malaria in the constructed clusters was associated with 1, 2, 3, and 4 lagged months of rainfall. The constructed models had acceptable accuracy as 73.1%, 46.3%, 53.4%, and 50.7% of the variance in malaria transmission were explained by rainfall in the high-risk, moderate-risk, low-risk, and very low-risk clusters, respectively. Conclusion Change in rainfall patterns affect malaria incidence in Eritrea. Using routine malaria case reports and rainfall data, malaria incidences can be forecasted with acceptable accuracy. Further research should consider a village or health facility level modeling of malaria incidence by including other climatic factors like temperature and relative humidity.
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17
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Anyamba A, Chretien JP, Britch SC, Soebiyanto RP, Small JL, Jepsen R, Forshey BM, Sanchez JL, Smith RD, Harris R, Tucker CJ, Karesh WB, Linthicum KJ. Global Disease Outbreaks Associated with the 2015-2016 El Niño Event. Sci Rep 2019; 9:1930. [PMID: 30760757 PMCID: PMC6374399 DOI: 10.1038/s41598-018-38034-z] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2018] [Accepted: 12/18/2018] [Indexed: 11/16/2022] Open
Abstract
Interannual climate variability patterns associated with the El Niño-Southern Oscillation phenomenon result in climate and environmental anomaly conditions in specific regions worldwide that directly favor outbreaks and/or amplification of variety of diseases of public health concern including chikungunya, hantavirus, Rift Valley fever, cholera, plague, and Zika. We analyzed patterns of some disease outbreaks during the strong 2015-2016 El Niño event in relation to climate anomalies derived from satellite measurements. Disease outbreaks in multiple El Niño-connected regions worldwide (including Southeast Asia, Tanzania, western US, and Brazil) followed shifts in rainfall, temperature, and vegetation in which both drought and flooding occurred in excess (14-81% precipitation departures from normal). These shifts favored ecological conditions appropriate for pathogens and their vectors to emerge and propagate clusters of diseases activity in these regions. Our analysis indicates that intensity of disease activity in some ENSO-teleconnected regions were approximately 2.5-28% higher during years with El Niño events than those without. Plague in Colorado and New Mexico as well as cholera in Tanzania were significantly associated with above normal rainfall (p < 0.05); while dengue in Brazil and southeast Asia were significantly associated with above normal land surface temperature (p < 0.05). Routine and ongoing global satellite monitoring of key climate variable anomalies calibrated to specific regions could identify regions at risk for emergence and propagation of disease vectors. Such information can provide sufficient lead-time for outbreak prevention and potentially reduce the burden and spread of ecologically coupled diseases.
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Affiliation(s)
- Assaf Anyamba
- Universities Space Research Association, Columbia, Maryland, USA.
- NASA Goddard Space Flight Center, Biospheric Sciences Laboratory, Greenbelt, Maryland, USA.
| | - Jean-Paul Chretien
- Department of Defense, Armed Forces Health Surveillance Branch, Silver Spring, Maryland, USA
- National Center for Medical Intelligence, Fort Detrick, Maryland, USA
| | - Seth C Britch
- USDA-Agricultural Research Service Center for Medical, Agricultural, and Veterinary Entomology, Gainesville, Florida, USA
| | - Radina P Soebiyanto
- Universities Space Research Association, Columbia, Maryland, USA
- NASA Goddard Space Flight Center, Biospheric Sciences Laboratory, Greenbelt, Maryland, USA
| | - Jennifer L Small
- NASA Goddard Space Flight Center, Biospheric Sciences Laboratory, Greenbelt, Maryland, USA
- Science Systems and Applications, Inc., Lanham, Maryland, USA
| | - Rikke Jepsen
- NASA Goddard Space Flight Center, Biospheric Sciences Laboratory, Greenbelt, Maryland, USA
- Science Systems and Applications, Inc., Lanham, Maryland, USA
- Interstate Commission on the Potomac River Basin, Rockville, Maryland, USA
| | - Brett M Forshey
- Department of Defense, Armed Forces Health Surveillance Branch, Silver Spring, Maryland, USA
- Cherokee Nation Technology Solutions, Silver Spring, Maryland, USA
| | - Jose L Sanchez
- Department of Defense, Armed Forces Health Surveillance Branch, Silver Spring, Maryland, USA
| | - Ryan D Smith
- United States Air Force, 14th Weather Squadron - DoD Climate Services, Asheville, North Carolina, USA
| | - Ryan Harris
- United States Air Force, 14th Weather Squadron - DoD Climate Services, Asheville, North Carolina, USA
| | - Compton J Tucker
- NASA Goddard Space Flight Center, Biospheric Sciences Laboratory, Greenbelt, Maryland, USA
| | | | - Kenneth J Linthicum
- USDA-Agricultural Research Service Center for Medical, Agricultural, and Veterinary Entomology, Gainesville, Florida, USA
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18
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Caminade C, McIntyre KM, Jones AE. Impact of recent and future climate change on vector-borne diseases. Ann N Y Acad Sci 2019; 1436:157-173. [PMID: 30120891 PMCID: PMC6378404 DOI: 10.1111/nyas.13950] [Citation(s) in RCA: 239] [Impact Index Per Article: 47.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Revised: 07/12/2018] [Accepted: 07/17/2018] [Indexed: 12/22/2022]
Abstract
Climate change is one of the greatest threats to human health in the 21st century. Climate directly impacts health through climatic extremes, air quality, sea-level rise, and multifaceted influences on food production systems and water resources. Climate also affects infectious diseases, which have played a significant role in human history, impacting the rise and fall of civilizations and facilitating the conquest of new territories. Our review highlights significant regional changes in vector and pathogen distribution reported in temperate, peri-Arctic, Arctic, and tropical highland regions during recent decades, changes that have been anticipated by scientists worldwide. Further future changes are likely if we fail to mitigate and adapt to climate change. Many key factors affect the spread and severity of human diseases, including mobility of people, animals, and goods; control measures in place; availability of effective drugs; quality of public health services; human behavior; and political stability and conflicts. With drug and insecticide resistance on the rise, significant funding and research efforts must to be maintained to continue the battle against existing and emerging diseases, particularly those that are vector borne.
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Affiliation(s)
- Cyril Caminade
- Department of Epidemiology and Population Health, Institute of Infection and Global HealthUniversity of LiverpoolLiverpoolUK
- NIHR Health Protection Research Unit in Emerging and Zoonotic InfectionsLiverpoolUK
| | - K. Marie McIntyre
- Department of Epidemiology and Population Health, Institute of Infection and Global HealthUniversity of LiverpoolLiverpoolUK
- NIHR Health Protection Research Unit in Emerging and Zoonotic InfectionsLiverpoolUK
| | - Anne E. Jones
- Department of Mathematical SciencesUniversity of LiverpoolLiverpoolUK
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Babaie J, Barati M, Azizi M, Ephtekhari A, Sadat SJ. A systematic evidence review of the effect of climate change on malaria in Iran. J Parasit Dis 2018; 42:331-340. [PMID: 30166779 PMCID: PMC6104236 DOI: 10.1007/s12639-018-1017-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2018] [Accepted: 07/03/2018] [Indexed: 11/26/2022] Open
Abstract
Climate is an effective factor in the ecological structure which plays an important role in control and outbreak of the diseases caused by biological factors like malaria. With regard to the occurring climatic change, this study aimed to review the effects of climate change on malaria in Iran. In this systematic review, Cochrane, PubMed and ScienceDirect (as international databases), SID and Magiran as Persian databases were investigated through MESH keywords including climate change, global warming, malaria, Anopheles, and Iran. The related articles were screened and finally their results were extracted using data extraction sheets. Totally 41 papers were resulted through databases searching process. Finally 14 papers which met inclusion criteria were included in data extraction stage. The findings indicated that Anopheles mosquitoes are present at least in 115 places in Iran; they are compatible with climatic zones of Iran. Malaria and it's vectors are affected by climate change. Temperature, precipitation, relative humidity, wind intensity and direction are the most important climatic factors affecting the growth and proliferation of Anopheles, Plasmodium and the prevalence of malaria. The transmission of malaria in Iran is associated with the climatic factors of temperature, rainfall, and humidity. Therefore, with regard to the occurring climatic change, the incidence of the disease may also change which needs to be taken into consideration while planning of malaria control.
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Affiliation(s)
- Javad Babaie
- Iranian Center of Excellence in Health Management, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Mohammad Barati
- Infectious Diseases Research Center, Aja University of Medical Sciences, Tehran, Iran
| | - Maryam Azizi
- Department of Health in Disaster and Emergency, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
| | - Adel Ephtekhari
- Department of Health in Disaster and Emergency, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
| | - Seyed Javad Sadat
- Department of Health in Disaster and Emergency, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
- Social Determinants of Health Research Center, Yasuj University of Medical Sciences, Yasuj, Iran
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20
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Nanvyat N, Mulambalah CS, Barshep Y, Ajiji JA, Dakul DA, Tsingalia HM. Malaria transmission trends and its lagged association with climatic factors in the highlands of Plateau State, Nigeria. Trop Parasitol 2018; 8:18-23. [PMID: 29930902 PMCID: PMC5991042 DOI: 10.4103/tp.tp_35_17] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/07/2017] [Indexed: 12/18/2022] Open
Abstract
Background: Malaria is a serious disease and still remains a public health problem in many parts of Nigeria. Objectives: The aim of this study was to describe malaria transmission trends and analyzed the impact of climatic factors on malaria transmission in the highlands of Plateau State, Central Nigeria. Methods: The study was a retrospective survey which used archival data of climate parameters and medical case records on malaria. Rainfall, relative humidity, and temperature data were obtained from the nearest weather stations to the study locations from 1980 to 2015. Data on reported malaria cases were collected from general hospitals in the selected local government areas (LGAs) from 2003 to 2015. Generalized Additive Models were used to model trends in malaria incidences over time, and it is lagged association with climatic factors. Results: The results show a significant cyclical trend in malaria incidence in all the study areas (P < 0.001). The association between monthly malaria cases and mean monthly temperature, rainfall, and relative humidity show significant association at different time lags and locations. Conclusion: Our findings suggest that climatic factors are among the major determinants of malaria transmission in the highlands of Plateau state except in Jos-North LGA where the low model deviance explained (35.4%) could mean that there are other important factors driving malaria transmission in the area other than climatic factors.
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Affiliation(s)
- N Nanvyat
- Department of Zoology, Faculty of Natural Sciences, University of Jos, Jos, Plateau State, Nigeria.,Department of Biological Sciences, School of Biological and Physical Sciences, Moi University, Eldoret, Kenya
| | - C S Mulambalah
- Department of Medical Microbiology and Parasitology, School of Medicine, College of Health Sciences, Moi University, Eldoret, Kenya
| | - Y Barshep
- Department of Zoology, Faculty of Natural Sciences, University of Jos, Jos, Plateau State, Nigeria
| | - J A Ajiji
- Medical Services Department, Plateau State Ministry of Health, Jos, Plateau State, Nigeria
| | - D A Dakul
- Department of Zoology, Faculty of Natural Sciences, University of Jos, Jos, Plateau State, Nigeria
| | - H M Tsingalia
- Department of Biological Sciences, School of Biological and Physical Sciences, Moi University, Eldoret, Kenya
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21
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Hundessa S, Williams G, Li S, Guo J, Zhang W, Guo Y. The weekly associations between climatic factors and Plasmodium vivax and Plasmodium falciparum malaria in China, 2005-2014. Trans R Soc Trop Med Hyg 2018; 111:211-219. [PMID: 28957472 DOI: 10.1093/trstmh/trx048] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2017] [Accepted: 07/31/2017] [Indexed: 12/22/2022] Open
Abstract
Background Meteorological factors play a crucial role in malaria transmission, but limited evidence is available from China. This study aimed to estimate the weekly associations between meteorological factors and Plasmodium vivax and Plasmodium falciparum malaria in China. Methods The Distributed Lag Non-Linear Model was used to examine non-linearity and delayed effects of average temperature, rainfall, relative humidity, sunshine hours, wind speed and atmospheric pressure on malaria. Results Average temperature was associated with P. vivax and P. falciparum cases over long ranges of lags. The effect was more immediate on P. vivax (0-6 weeks) than on P. falciparum (1-9 weeks). Relative humidity was associated with P. vivax and P. falciparum over 8-10 weeks and 5-8 weeks lag, respectively. A significant effect of wind speed on P. vivax was observed at 0-2 weeks lag, but no association was found with P. falciparum. Rainfall had a decreasing effect on P. vivax, but no association was found with P. falciparum. Sunshine hours were negatively associated with P. falciparum, but the association was unclear for P. vixax. However, the effects of atmospheric pressure on both malaria types were not significant at any lag. Conclusions Our study highlights a substantial effect of weekly climatic factors on P. vivax and P. falciparum malaria transmission in China, with different lags. This provides an evidence base for health authorities in developing a malaria early-warning system.
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Affiliation(s)
- Samuel Hundessa
- Division of Epidemiology and Biostatistics, School of Public Health, University of Queensland, Brisbane, 4006
| | - Gail Williams
- Division of Epidemiology and Biostatistics, School of Public Health, University of Queensland, Brisbane, 4006
| | - Shanshan Li
- School of Public Health and Preventive Medicine, Monash University, Melbourne VIC 3004, Australia
| | - Jinpeng Guo
- Institute for Disease Control and Prevention, Academy of Military Medical Science, Beijing, People's Republic of China
| | - Wenyi Zhang
- Institute for Disease Control and Prevention, Academy of Military Medical Science, Beijing, People's Republic of China
| | - Yuming Guo
- School of Public Health and Preventive Medicine, Monash University, Melbourne VIC 3004, Australia
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22
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Tong MX, Hansen A, Hanson-Easey S, Xiang J, Cameron S, Liu Q, Liu X, Sun Y, Weinstein P, Han GS, Bi P. China's capacity of hospitals to deal with infectious diseases in the context of climate change. Soc Sci Med 2018; 206:60-66. [PMID: 29684649 PMCID: PMC7116943 DOI: 10.1016/j.socscimed.2018.04.021] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Revised: 02/22/2018] [Accepted: 04/13/2018] [Indexed: 02/07/2023]
Abstract
OBJECTIVES Infectious diseases are a major cause of morbidity and mortality in China. The capacity of hospitals to deal with the challenge from emerging and re-emerging infectious diseases due to climate change is of great importance to population health. This study aimed to explore the capacity of hospitals in China to deal with such challenges. METHODS A cross-sectional questionnaire survey was utilized to gauge information regarding capacity of hospitals to deal with infectious diseases in the context of climate change among 611 clinical professionals whose roles pertained to infectious disease diagnosis, treatment and management in Anhui Province of China. Descriptive analysis and logistic regression analysis were performed on the data. RESULTS More than 90% of participants believed climate change would have an adverse influence on population health and infectious disease control in China. Most indicated that their hospitals were well prepared for emerging infectious diseases at present, and they considered that logistical support in hospitals (e.g. administrative and maintenance services) should be strengthened for future capacity building. The majority of participants suggested that effective prevention and control measures, more interdisciplinary collaborations, more funding in rural areas for health care, and improved access to facilities enabling online reporting of infectious diseases, were extremely important strategies in building capacity to curb the population health impact of emerging and re-emerging infectious diseases due to climate change in China. CONCLUSIONS Clinical professionals recognized that climate change will likely increase the transmission of infectious diseases. Although rural health care and hospitals' logistical support need to be improved, most professionals believed their hospitals to be capable of dealing with emerging diseases. They thought that interdisciplinary and cross-regional collaborations, together with necessary resource support (e.g. improved facilities for rural health care) would be important control strategies.
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Affiliation(s)
- Michael Xiaoliang Tong
- School of Public Health, The University of Adelaide, Adelaide, South Australia, 5005, Australia.
| | - Alana Hansen
- School of Public Health, The University of Adelaide, Adelaide, South Australia, 5005, Australia.
| | - Scott Hanson-Easey
- School of Public Health, The University of Adelaide, Adelaide, South Australia, 5005, Australia.
| | - Jianjun Xiang
- School of Public Health, The University of Adelaide, Adelaide, South Australia, 5005, Australia.
| | - Scott Cameron
- School of Public Health, The University of Adelaide, Adelaide, South Australia, 5005, Australia.
| | - 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.
| | - Xiaobo 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.
| | - Yehuan Sun
- Department of Epidemiology, Anhui Medical University, Hefei, Anhui, 230032, China.
| | - Philip Weinstein
- School of Biological Sciences, The University of Adelaide, Adelaide, South Australia, 5005, Australia.
| | - Gil-Soo Han
- Communications & Media Studies, School of Media, Film and Journalism, Monash University, Clayton, Victoria, 3800, Australia.
| | - Peng Bi
- School of Public Health, The University of Adelaide, Adelaide, South Australia, 5005, Australia.
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23
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Hundessa S, Li S, Liu DL, Guo J, Guo Y, Zhang W, Williams G. Projecting environmental suitable areas for malaria transmission in China under climate change scenarios. ENVIRONMENTAL RESEARCH 2018; 162:203-210. [PMID: 29353124 DOI: 10.1016/j.envres.2017.12.021] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/03/2017] [Revised: 11/23/2017] [Accepted: 12/22/2017] [Indexed: 06/07/2023]
Abstract
INTRODUCTION The proportion of imported malaria cases in China has increased over recent years, and has presented challenges for the malaria elimination program in China. However, little is known about the geographic distribution and environmental suitability for malaria transmission under projected climate change scenarios. METHODS Using the MaxEnt model based on malaria presence-only records, we produced environmental suitability maps and examined the relative contribution of topographic, demographic, and environmental risk factors for P. vivax and P. falciparum malaria in China. RESULTS The MaxEnt model estimated that environmental suitability areas (ESAs) for malaria cover the central, south, southwest, east and northern regions, with a slightly wider range of ESAs extending to the northeast region for P. falciparum. There was spatial agreement between the location of imported cases and area environmentally suitable for malaria transmission. The ESAs of P. vivax and P. falciparum are projected to increase in some parts of southwest, south, central, north and northeast regions in the 2030s, 2050s, and 2080s, by a greater amount for P. falciparum under the RCP8.5 scenario. Temperature and NDVI values were the most influential in defining the ESAs for P. vivax, and temperature and precipitation the most influential for P. falciparum malaria. CONCLUSION This study estimated that the ESA for malaria transmission in China will increase with climate change and highlights the potential establishment of further local transmission. This model should be used to support malaria control by targeting areas where interventions on malaria transmission need to be enhanced.
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Affiliation(s)
- Samuel Hundessa
- Division of Epidemiology and Biostatistics, School of Public Health, University of Queensland, Brisbane 4006, Australia
| | - Shanshan Li
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - De Li Liu
- NSW Department of Primary Industries, WaggaWagga Agricultural Institute, New South Wales 2650, Wagga Wagga, Australia
| | - Jinpeng Guo
- Institutefor Disease Control and Prevention of PLA, Beijing 100039, People's Republic of China
| | - Yuming Guo
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia.
| | - Wenyi Zhang
- Institutefor Disease Control and Prevention of PLA, Beijing 100039, People's Republic of China.
| | - Gail Williams
- Division of Epidemiology and Biostatistics, School of Public Health, University of Queensland, Brisbane 4006, Australia
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Nejati J, Moosa-Kazemi SH, Saghafipour A, Soofi K. Knowledge, attitude and practice (KAP) on malaria, from high malaria burden rural communities, southeastern Iran. J Parasit Dis 2018; 42:62-67. [PMID: 29491561 PMCID: PMC5825367 DOI: 10.1007/s12639-017-0965-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2017] [Accepted: 10/24/2017] [Indexed: 01/02/2023] Open
Abstract
Nowadays, community based control strategies are considered efficient in reaching the malaria elimination goal. For this reason, this study was conducted to access the knowledge, attitude and practice of people on malaria from rural areas with high malaria incidence. In this descriptive-analytic study, a total of 200 rural residents of southeastern Iran were recruited. They were selected based on cluster and simple random sampling methods. Data collection was done using questionnaire with reliability confirmation by Cronbach's alpha and data was analyzed using SPSS. Mosquito's bite was answered as the main route of malaria transmission. Also, majority of the participants correctly expressed most important symptoms of malaria. Most of them believed that malaria is preventable and the best strategy for its control is indoor residual spraying. Very few number of the respondents mentioned sleeping under insecticide treated bed net as a method for controlling the transmission of malaria. Chi square test shows significant difference between the level of education and usage of mosquito nets, but there was no significant difference between the use of bed nets and time of usage. Another significant relationship was seen between malaria infection, use of mosquito nets and place of sleeping at nights during summer. The current study showed the appropriate level of KAP among rural communities in southeast of Iran. Alongside of people's knowledge and attitudes, their practice about malaria should be increased as an effective factor for achieving to great goal of malaria elimination.
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Affiliation(s)
- Jalil Nejati
- Health Promotion Research Center, Zahedan University of Medical Sciences, Zahedan, Iran
- Department of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Seyed Hassan Moosa-Kazemi
- Department of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Abedin Saghafipour
- Department of Public Health, School of Health, Qom University of Medical Sciences, Qom, Iran
| | - Khodamorad Soofi
- Center for Disease Control and Prevention, Sarbaz Health Center, Iranshahr University of Medical Sciences, Iranshahr, Iran
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25
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Zhai J, Lu Q, Hu W, Tong S, Wang B, Yang F, Xu Z, Xun S, Shen X. Development of an empirical model to predict malaria outbreaks based on monthly case reports and climate variables in Hefei, China, 1990-2011. Acta Trop 2018; 178:148-154. [PMID: 29138004 DOI: 10.1016/j.actatropica.2017.11.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2017] [Revised: 10/20/2017] [Accepted: 11/03/2017] [Indexed: 01/10/2023]
Abstract
Malaria remains a significant public health concern in developing countries. Drivers of malaria transmission vary across different geographical regions. Climatic variables are major risk factor in seasonal and secular patterns of P. vivax malaria transmission along Anhui province. The study aims to forecast malaria outbreaks using empirical model developed in Hefei, China. Data on the monthly numbers of notified malaria cases and climatic factors were obtained for the period of January 1st 1990 to December 31st 2011 from the Hefei CDC and Anhui Institute of Meteorological Sciences, respectively. Two logistic regression models with time series seasonal decomposition were used to explore the impact of climatic and seasonal factors on malaria outbreaks. Sensitivity and specificity statistics were used for evaluating the predictive power. The results showed that relative humidity (OR = 1.171, 95% CI = 1.090-1.257), sunshine (OR = 1.076, 95% CI = 1.043-1.110) and barometric pressure (OR = 1.051, 95% CI = 1.003-1.100) were significantly associated with malaria outbreaks after adjustment for seasonality in Hefei area. The validation analyses indicated the overall agreement of 70.42% (sensitivity: 70.52%; specificity: 70.30%). The research suggested that the empirical model developed based on disease surveillance and climatic conditions may have applications in malaria control and prevention activities.
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26
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Association between malaria incidence and meteorological factors: a multi-location study in China, 2005-2012. Epidemiol Infect 2017; 146:89-99. [PMID: 29248024 DOI: 10.1017/s0950268817002254] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
This study aims to investigate the climate-malaria associations in nine cities selected from malaria high-risk areas in China. Daily reports of malaria cases in Anhui, Henan, and Yunnan Provinces for 2005-2012 were obtained from the Chinese Center for Disease Control and Prevention. Generalized estimating equation models were used to quantify the city-specific climate-malaria associations. Multivariate random-effects meta-regression analyses were used to pool the city-specific effects. An inverted-U-shaped curve relationship was observed between temperatures, average relative humidity, and malaria. A 1 °C increase of maximum temperature (T max) resulted in 6·7% (95% CI 4·6-8·8%) to 15·8% (95% CI 14·1-17·4%) increase of malaria, with corresponding lags ranging from 7 to 45 days. For minimum temperature (T min), the effect estimates peaked at lag 0 to 40 days, ranging from 5·3% (95% CI 4·4-6·2%) to 17·9% (95% CI 15·6-20·1%). Malaria is more sensitive to T min in cool climates and T max in warm climates. The duration of lag effect in a cool climate zone is longer than that in a warm climate zone. Lagged effects did not vanish after an epidemic season but waned gradually in the following 2-3 warm seasons. A warming climate may potentially increase the risk of malaria resurgence in China.
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27
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Short EE, Caminade C, Thomas BN. Climate Change Contribution to the Emergence or Re-Emergence of Parasitic Diseases. Infect Dis (Lond) 2017; 10:1178633617732296. [PMID: 29317829 PMCID: PMC5755797 DOI: 10.1177/1178633617732296] [Citation(s) in RCA: 52] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2017] [Accepted: 08/20/2017] [Indexed: 01/07/2023] Open
Abstract
The connection between our environment and parasitic diseases may not always be straightforward, but it exists nonetheless. This article highlights how climate as a component of our environment, or more specifically climate change, has the capability to drive parasitic disease incidence and prevalence worldwide. There are both direct and indirect implications of climate change on the scope and distribution of parasitic organisms and their associated vectors and host species. We aim to encompass a large body of literature to demonstrate how a changing climate will perpetuate, or perhaps exacerbate, public health issues and economic stagnation due to parasitic diseases. The diseases examined include those caused by ingested protozoa and soil helminths, malaria, lymphatic filariasis, Chagas disease, human African trypanosomiasis, leishmaniasis, babesiosis, schistosomiasis, and echinococcus, as well as parasites affecting livestock. It is our goal to impress on the scientific community the magnitude a changing climate can have on public health in relation to parasitic disease burden. Once impending climate changes are now upon us, and as we see these events unfold, it is critical to create management plans that will protect the health and quality of life of the people living in the communities that will be significantly affected.
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Affiliation(s)
- Erica E Short
- Environmental Science Program, Thomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, Rochester, NY, USA
| | - Cyril Caminade
- Department of Epidemiology and Population Health, Institute of Infection and Global Health, University of Liverpool, Liverpool, UK.,NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, Liverpool, UK
| | - Bolaji N Thomas
- Department of Biomedical Sciences, College of Health Sciences and Technology, Rochester Institute of Technology, Rochester, NY, USA
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28
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Huang Q, Hu L, Liao QB, Xia J, Wang QR, Peng HJ. Spatiotemporal Analysis of the Malaria Epidemic in Mainland China, 2004-2014. Am J Trop Med Hyg 2017; 97:504-513. [PMID: 28829728 DOI: 10.4269/ajtmh.16-0711] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
The purpose of this study is to characterize spatiotemporal heterogeneities in malaria distribution at a provincial level and investigate the association between malaria incidence and climate factors from 2004 to 2014 in China to inform current malaria control efforts. National malaria incidence peaked (4.6/100,000) in 2006 and decreased to a very low level (0.21/100,000) in 2014, and the proportion of imported cases increased from 16.2% in 2004 to 98.2% in 2014. Statistical analyses of global and local spatial autocorrelations and purely spatial scan statistics revealed that malaria was localized in Hainan, Anhui, and Yunnan during 2004-2009 and then gradually shifted and clustered in Yunnan after 2010. Purely temporal clusters shortened to less than 5 months during 2012-2014. The two most likely clusters detected using spatiotemporal analysis occurred in Anhui between July 2005 and November 2007 and Yunnan between January 2010 and June 2012. Correlation coefficients for the association between malaria incidence and climate factors sharply decreased after 2010, and there were zero-month lag effects for climate factors during 2010-2014. Overall, the spatiotemporal distribution of malaria in China changed from relatively scattered (2004-2009) to relatively clustered (2010-2014). As the proportion of imported cases increased, the effect of climate factors on malaria incidence has gradually become weaker since 2011. Therefore, new warning systems should be applied to monitor resurgence and outbreaks of malaria in mainland China, and quarantine at borders should be reinforced to control the increasingly trend of imported malaria cases.
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Affiliation(s)
- Qiang Huang
- Department of Pathogen Biology, Guangdong Provincial Key Laboratory of Tropical Disease Research, and Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes, School of Public Health, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Lin Hu
- Department of Pathogen Biology, Guangdong Provincial Key Laboratory of Tropical Disease Research, and Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes, School of Public Health, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Qi-Bin Liao
- Department of Pathogen Biology, Guangdong Provincial Key Laboratory of Tropical Disease Research, and Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes, School of Public Health, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Jing Xia
- Department of Pathogen Biology, Guangdong Provincial Key Laboratory of Tropical Disease Research, and Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes, School of Public Health, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Qian-Ru Wang
- Department of Atmospheric Science, College of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, Sichuan, China
| | - Hong-Juan Peng
- Department of Pathogen Biology, Guangdong Provincial Key Laboratory of Tropical Disease Research, and Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes, School of Public Health, Southern Medical University, Guangzhou, Guangdong Province, China
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29
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Kumar R, Dash C, Rani K. Ecological covariates based predictive model of malaria risk in the state of Chhattisgarh, India. J Parasit Dis 2017; 41:761-767. [PMID: 28848275 DOI: 10.1007/s12639-017-0885-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2015] [Accepted: 01/27/2017] [Indexed: 11/28/2022] Open
Abstract
Malaria being an endemic disease in the state of Chhattisgarh and ecologically dependent mosquito-borne disease, the study is intended to identify the ecological covariates of malaria risk in districts of the state and to build a suitable predictive model based on those predictors which could assist developing a weather based early warning system. This secondary data based analysis used one month lagged district level malaria positive cases as response variable and ecological covariates as independent variables which were tested with fixed effect panelled negative binomial regression models. Interactions among the covariates were explored using two way factorial interaction in the model. Although malaria risk in the state possesses perennial characteristics, higher parasitic incidence was observed during the rainy and winter seasons. The univariate analysis indicated that the malaria incidence risk was statistically significant associated with rainfall, maximum humidity, minimum temperature, wind speed, and forest cover (p < 0.05). The efficient predictive model include the forest cover [IRR-1.033 (1.024-1.042)], maximum humidity [IRR-1.016 (1.013-1.018)], and two-way factorial interactions between district specific averaged monthly minimum temperature and monthly minimum temperature, monthly minimum temperature was statistically significant [IRR-1.44 (1.231-1.695)] whereas the interaction term has a protective effect [IRR-0.982 (0.974-0.990)] against malaria infections. Forest cover, maximum humidity, minimum temperature and wind speed emerged as potential covariates to be used in predictive models for modelling the malaria risk in the state which could be efficiently used for early warning systems in the state.
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Affiliation(s)
- Rajesh Kumar
- Child Right and You (CRY), Sayad Ul Ajab, Westend Marg, New Delhi, 110030 India
| | | | - Khushbu Rani
- Women and Child Welfare Consultant, New Delhi, India
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30
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Tong MX, Hansen A, Hanson-Easey S, Cameron S, Xiang J, Liu Q, Liu X, Sun Y, Weinstein P, Han GS, Williams C, Bi P. Perceptions of malaria control and prevention in an era of climate change: a cross-sectional survey among CDC staff in China. Malar J 2017; 16:136. [PMID: 28359315 PMCID: PMC5374624 DOI: 10.1186/s12936-017-1790-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Accepted: 03/24/2017] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Though there was the significant decrease in the incidence of malaria in central and southwest China during the 1980s and 1990s, there has been a re-emergence of malaria since 2000. METHODS A cross-sectional survey was conducted amongst the staff of eleven Centers for Disease Control and Prevention (CDC) in China to gauge their perceptions regarding the impacts of climate change on malaria transmission and its control and prevention. Descriptive analysis was performed to study CDC staff's knowledge, attitudes, perceptions and suggestions for malaria control in the face of climate change. RESULTS A majority (79.8%) of CDC staff were concerned about climate change and 79.7% believed the weather was becoming warmer. Most participants (90.3%) indicated climate change had a negative effect on population health, 92.6 and 86.8% considered that increasing temperatures and precipitation would influence the transmission of vector-borne diseases including malaria. About half (50.9%) of the surveyed staff indicated malaria had re-emerged in recent years, and some outbreaks were occurring in new geographic areas. The main reasons for such re-emergence were perceived to be: mosquitoes in high-density, numerous imported cases, climate change, poor environmental conditions, internal migrant populations, and lack of health awareness. CONCLUSIONS This study found most CDC staff endorsed the statement that climate change had a negative impact on infectious disease transmission. Malaria had re-emerged in some areas of China, and most of the staff believed that this can be managed. However, high densities of mosquitoes and the continuous increase in imported cases of malaria in local areas, together with environmental changes are bringing about critical challenges to malaria control in China. This study contributes to an understanding of climate change related perceptions of malaria control and prevention amongst CDC staff. It may help to formulate in-house training guidelines, community health promotion programmes and policies to improve the capacity of malaria control and prevention in the face of climate change in China.
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Affiliation(s)
- Michael Xiaoliang Tong
- School of Public Health, The University of Adelaide, Level 8, Hughes Building, North Terrace Campus, Adelaide, SA 5005 Australia
| | - Alana Hansen
- School of Public Health, The University of Adelaide, Level 8, Hughes Building, North Terrace Campus, Adelaide, SA 5005 Australia
| | - Scott Hanson-Easey
- School of Public Health, The University of Adelaide, Level 8, Hughes Building, North Terrace Campus, Adelaide, SA 5005 Australia
| | - Scott Cameron
- School of Public Health, The University of Adelaide, Level 8, Hughes Building, North Terrace Campus, Adelaide, SA 5005 Australia
| | - Jianjun Xiang
- School of Public Health, The University of Adelaide, Level 8, Hughes Building, North Terrace Campus, Adelaide, SA 5005 Australia
| | - 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
| | - Xiaobo 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
| | - Yehuan Sun
- Department of Epidemiology, Anhui Medical University, Hefei, 230032 Anhui China
| | - Philip Weinstein
- School of Biological Sciences, The University of Adelaide, Adelaide, SA 5005 Australia
| | - Gil-Soo Han
- Communications and Media Studies, School of Media, Film and Journalism, Monash University, Clayton, VIC 3800 Australia
| | - Craig Williams
- School of Pharmacy and Medical Sciences, University of South Australia, Adelaide, SA 5001 Australia
| | - Peng Bi
- School of Public Health, The University of Adelaide, Level 8, Hughes Building, North Terrace Campus, Adelaide, SA 5005 Australia
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31
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Song Y, Ge Y, Wang J, Ren Z, Liao Y, Peng J. Spatial distribution estimation of malaria in northern China and its scenarios in 2020, 2030, 2040 and 2050. Malar J 2016; 15:345. [PMID: 27387921 PMCID: PMC4936159 DOI: 10.1186/s12936-016-1395-2] [Citation(s) in RCA: 26] [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: 11/10/2015] [Accepted: 06/15/2016] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Malaria is one of the most severe parasitic diseases in the world. Spatial distribution estimation of malaria and its future scenarios are important issues for malaria control and elimination. Furthermore, sophisticated nonlinear relationships for prediction between malaria incidence and potential variables have not been well constructed in previous research. This study aims to estimate these nonlinear relationships and predict future malaria scenarios in northern China. METHODS Nonlinear relationships between malaria incidence and predictor variables were constructed using a genetic programming (GP) method, to predict the spatial distributions of malaria under climate change scenarios. For this, the examples of monthly average malaria incidence were used in each county of northern China from 2004 to 2010. Among the five variables at county level, precipitation rate and temperature are used for projections, while elevation, water density index, and gross domestic product are held at their present-day values. RESULTS Average malaria incidence was 0.107 ‰ per annum in northern China, with incidence characteristics in significant spatial clustering. A GP-based model fit the relationships with average relative error (ARE) = 8.127 % for training data (R(2) = 0.825) and 17.102 % for test data (R(2) = 0.532). The fitness of GP results are significantly improved compared with those by generalized additive models (GAM) and linear regressions. With the future precipitation rate and temperature conditions in Special Report on Emission Scenarios (SRES) family B1, A1B and A2 scenarios, spatial distributions and changes in malaria incidences in 2020, 2030, 2040 and 2050 were predicted and mapped. CONCLUSIONS The GP method increases the precision of predicting the spatial distribution of malaria incidence. With the assumption of varied precipitation rate and temperature, and other variables controlled, the relationships between incidence and the varied variables appear sophisticated nonlinearity and spatially differentiation. Using the future fluctuated precipitation and the increased temperature, median malaria incidence in 2020, 2030, 2040 and 2050 would significantly increase that it might increase 19 to 29 % in 2020, but currently China is in the malaria elimination phase, indicating that the effective strategies and actions had been taken. While the mean incidences will not increase even reduce due to the incidence reduction in high-risk regions but the simultaneous expansion of the high-risk areas.
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Affiliation(s)
- Yongze Song
- />School of Land Science and Technology, China University of Geosciences, Beijing, China
- />State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Yong Ge
- />State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Jinfeng Wang
- />State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- />Key Laboratory of Surveillance and Early Warning on Infectious Diseases, Chinese Center for Diseases Control and Prevention, Beijing, China
| | - Zhoupeng Ren
- />State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- />Key Laboratory of Surveillance and Early Warning on Infectious Diseases, Chinese Center for Diseases Control and Prevention, Beijing, China
- />University of Chinese Academy of Sciences, Beijing, China
| | - Yilan Liao
- />State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Junhuan Peng
- />School of Land Science and Technology, China University of Geosciences, Beijing, China
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The relation between climatic factors and malaria incidence in Kerman, South East of Iran. Parasite Epidemiol Control 2016; 1:205-210. [PMID: 29988199 PMCID: PMC5991842 DOI: 10.1016/j.parepi.2016.06.001] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2015] [Revised: 06/11/2016] [Accepted: 06/11/2016] [Indexed: 11/28/2022] Open
Abstract
Background and objectives Malaria is among the most important parasitic diseases, and is one of the endemic diseases in Iran. This disease is often known as a disease related to climate changes. Due to the health and economic burden of malaria and the location of Kerman province in an area with high incidence of malaria, the present study aimed to evaluate the effects of climatic factors on the incidence of this disease. Material and methods Data on the incidence of malaria in Kerman province was inquired from Kerman and Jiroft Medical Universities and climatic variables were inquired from the meteorological organization of Kerman. The data was analyzed monthly from 2000 to 2012. Variations in incidence of malaria with climatic factors were assessed with negative binomial regression model in STATA11software. In order to determine the delayed effects of meteorological variables on malaria incidence, cross-correlation analysis was done with Minitab16. Results The most effective meteorological factor on the incidence of malaria was temperature. As the mean, maximum, and minimum of monthly temperature increased, the incidence rate raised significantly. The multivariate negative binomial regression model indicates that a 1 °C increase in maximum temperature in a given month was related to a 15% and 19% increase on malaria incidence on the same and subsequent month, respectively (p-value = 0.001). Humidity and Rainfall were not significant in the adjusted model. Conclusion Temperature is among the effective climatic parameters on the incidence of malaria which should be considered in planning for control and prevention of the disease.
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Bicout DJ, Vautrin M, Vignolles C, Sabatier P. Modeling the dynamics of mosquito breeding sites vs rainfall in Barkedji area, Senegal. Ecol Modell 2015. [DOI: 10.1016/j.ecolmodel.2015.08.027] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Buczak AL, Baugher B, Guven E, Ramac-Thomas LC, Elbert Y, Babin SM, Lewis SH. Fuzzy association rule mining and classification for the prediction of malaria in South Korea. BMC Med Inform Decis Mak 2015; 15:47. [PMID: 26084541 PMCID: PMC4472166 DOI: 10.1186/s12911-015-0170-6] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2014] [Accepted: 05/28/2015] [Indexed: 11/10/2022] Open
Abstract
Background Malaria is the world’s most prevalent vector-borne disease. Accurate prediction of malaria outbreaks may lead to public health interventions that mitigate disease morbidity and mortality. Methods We describe an application of a method for creating prediction models utilizing Fuzzy Association Rule Mining to extract relationships between epidemiological, meteorological, climatic, and socio-economic data from Korea. These relationships are in the form of rules, from which the best set of rules is automatically chosen and forms a classifier. Two classifiers have been built and their results fused to become a malaria prediction model. Future malaria cases are predicted as LOW, MEDIUM or HIGH, where these classes are defined as a total of 0–2, 3–16, and above 17 cases, respectively, for a region in South Korea during a two-week period. Based on user recommendations, HIGH is considered an outbreak. Results Model accuracy is described by Positive Predictive Value (PPV), Sensitivity, and F-score for each class, computed on test data not previously used to develop the model. For predictions made 7–8 weeks in advance, model PPV and Sensitivity are 0.842 and 0.681, respectively, for the HIGH classes. The F0.5 and F3 scores (which combine PPV and Sensitivity) are 0.804 and 0.694, respectively, for the HIGH classes. The overall FARM results (as measured by F-scores) are significantly better than those obtained by Decision Tree, Random Forest, Support Vector Machine, and Holt-Winters methods for the HIGH class. For the MEDIUM class, Random Forest and FARM obtain comparable results, with FARM being better at F0.5, and Random Forest obtaining a higher F3. Conclusions A previously described method for creating disease prediction models has been modified and extended to build models for predicting malaria. In addition, some new input variables were used, including indicators of intervention measures. The South Korea malaria prediction models predict LOW, MEDIUM or HIGH cases 7–8 weeks in the future. This paper demonstrates that our data driven approach can be used for the prediction of different diseases.
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Affiliation(s)
- Anna L Buczak
- Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Rd, Laurel, MD, 20723-6099, USA.
| | - Benjamin Baugher
- Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Rd, Laurel, MD, 20723-6099, USA
| | - Erhan Guven
- Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Rd, Laurel, MD, 20723-6099, USA
| | - Liane C Ramac-Thomas
- Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Rd, Laurel, MD, 20723-6099, USA
| | - Yevgeniy Elbert
- Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Rd, Laurel, MD, 20723-6099, USA
| | - Steven M Babin
- Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Rd, Laurel, MD, 20723-6099, USA
| | - Sheri H Lewis
- Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Rd, Laurel, MD, 20723-6099, USA
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Liu K, Zhou H, Sun RX, Yao HW, Li Y, Wang LP, Di Mu, Li XL, Yang Y, Gray GC, Cui N, Yin WW, Fang LQ, Yu HJ, Cao WC. A national assessment of the epidemiology of severe fever with thrombocytopenia syndrome, China. Sci Rep 2015; 5:9679. [PMID: 25902910 PMCID: PMC4407178 DOI: 10.1038/srep09679] [Citation(s) in RCA: 89] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2015] [Accepted: 03/12/2015] [Indexed: 01/18/2023] Open
Abstract
First discovered in rural areas of middle-eastern China in 2009, severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne zoonosis affecting hundreds of cases reported in China each year. Using the national surveillance data from 2010 to 2013, we conducted this retrospective epidemiological study and risk assessment of SFTS in China. We found that the incidence of SFTS and its epidemic areas are continuing to grow, but the case fatality rate (CFR) has steadily decreased. SFTS most commonly affected elderly farmers who acquired infection between May and July in middle-eastern China. However, other epidemiological characteristics such as incidence, sex ratio, CFR, and seasonality differ substantially across the affected provinces, which seem to be consistent with local agricultural activities and the seasonal abundance of ticks. Spatial scan statistics detected three hot spots of SFTS that accounted for 69.1% of SFTS cases in China. There was a strong association of SFTS incidence with temporal changes in the climate within the clusters. Multivariate modeling identified climate conditions, elevation, forest coverage, cattle density, and the presence of Haemaphysalis longicornis ticks as independent risk factors in the distribution of SFTS, based on which a predicted risk map of the disease was derived.
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Affiliation(s)
- Kun Liu
- The State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, P. R. China
| | - Hang Zhou
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Centre for Disease Control and Prevention, Beijing 102206, P. R. China
| | - Ruo-Xi Sun
- The State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, P. R. China.,Anhui Medical University, Hefei, 230032, P. R. China
| | - Hong-Wu Yao
- The State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, P. R. China
| | - Yu Li
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Centre for Disease Control and Prevention, Beijing 102206, P. R. China
| | - Li-Ping Wang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Centre for Disease Control and Prevention, Beijing 102206, P. R. China
| | - Di Mu
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Centre for Disease Control and Prevention, Beijing 102206, P. R. China
| | - Xin-Lou Li
- The State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, P. R. China
| | - Yang Yang
- Department of Biostatistics, College of Public Health and Health Professions, and Emerging Pathogens Institute, University of Florida, 32311, Florida, USA
| | - Gregory C Gray
- Duke University School of Medicine, Durham, 27710, North Carolina, USA
| | - Ning Cui
- The 154 Hospital, People's Liberation Army, Xinyang, 464000, P.R. China
| | - Wen-Wu Yin
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Centre for Disease Control and Prevention, Beijing 102206, P. R. China
| | - Li-Qun Fang
- The State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, P. R. China
| | - Hong-Jie Yu
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Centre for Disease Control and Prevention, Beijing 102206, P. R. China
| | - Wu-Chun Cao
- The State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, P. R. China
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Feng XY, Xia ZG, Vong S, Yang WZ, Zhou SS. Surveillance and response to drive the national malaria elimination program. ADVANCES IN PARASITOLOGY 2015; 86:81-108. [PMID: 25476882 DOI: 10.1016/b978-0-12-800869-0.00004-4] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The national action plan for malaria elimination in China (2010-2020) was issued by the Chinese Ministry of Health along with other 13 ministries and commissions in 2010. The ultimate goal of the national action plan was to eliminate local transmission of malaria by the end of 2020. Surveillance and response are the most important components driving the whole process of the national malaria elimination programme (NMEP), under the technical guidance used in NMEP. This chapter introduces the evolution of the surveillance from the control to the elimination stages and the current structure of national surveillance system in China. When the NMEP launched, both routine surveillance and sentinel surveillance played critical role in monitoring the process of NMEP. In addition, the current response strategy of NMEP was also reviewed, including the generally developed "1-3-7 Strategy". More effective and sensitive risk assessment tools were introduced, which cannot only predict the trends of malaria, but also are important for the design and adjustment of the surveillance and response systems in the malaria elimination stage. Therefore, this review presents the landscape of malaria surveillance and response in China as well as their contribution to the NMEP, with a focus on activities for early detection of malaria cases, timely control of malaria foci and epidemics, and risk prediction. Furthermore, challenges and recommendations for accelerating NMEP through surveillance are put forward.
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Affiliation(s)
- Xin-Yu Feng
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory of Parasite and Vector Biology, MOH; WHO Collaborating Centre for Malaria, Schistosomiasis and Filariasis, Shanghai, People's Republic of China
| | - Zhi-Gui Xia
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory of Parasite and Vector Biology, MOH; WHO Collaborating Centre for Malaria, Schistosomiasis and Filariasis, Shanghai, People's Republic of China
| | - Sirenda Vong
- World Health Organization, China Representative Office, Beijing, People's Republic of China
| | - Wei-Zhong Yang
- Chinese Preventive Medicine Association, Beijing, People's Republic of China; Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Shui-Sen Zhou
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory of Parasite and Vector Biology, MOH; WHO Collaborating Centre for Malaria, Schistosomiasis and Filariasis, Shanghai, People's Republic of China
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Zhou XN, Xia ZG, Wang RB, Qian YJ, Zhou SS, Utzinger J, Tanner M, Kramer R, Yang WZ. Feasibility and roadmap analysis for malaria elimination in China. ADVANCES IN PARASITOLOGY 2015; 86:21-46. [PMID: 25476880 DOI: 10.1016/b978-0-12-800869-0.00002-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
To understand the current status of the malaria control programme at the county level in accordance with the criteria of the World Health Organisation, the gaps and feasibility of malaria elimination at the county and national levels were analysed based on three kinds of indicators: transmission capacity, capacity of the professional team, and the intensity of intervention. Finally, a roadmap for national malaria elimination in the People's Republic of China is proposed based on the results of a feasibility assessment at the national level.
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Affiliation(s)
- Xiao-Nong Zhou
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, People's Republic of China; Key Laboratory of Parasite and Vector Biology, MOH; WHO Collaborating Centre for Malaria, Schistosomiasis and Filariasis, Shanghai, People's Republic of China
| | - Zhi-Gui Xia
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, People's Republic of China; Key Laboratory of Parasite and Vector Biology, MOH; WHO Collaborating Centre for Malaria, Schistosomiasis and Filariasis, Shanghai, People's Republic of China
| | - Ru-Bo Wang
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, People's Republic of China; Key Laboratory of Parasite and Vector Biology, MOH; WHO Collaborating Centre for Malaria, Schistosomiasis and Filariasis, Shanghai, People's Republic of China
| | - Ying-Jun Qian
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, People's Republic of China; Key Laboratory of Parasite and Vector Biology, MOH; WHO Collaborating Centre for Malaria, Schistosomiasis and Filariasis, Shanghai, People's Republic of China
| | - Shui-Sen Zhou
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, People's Republic of China; Key Laboratory of Parasite and Vector Biology, MOH; WHO Collaborating Centre for Malaria, Schistosomiasis and Filariasis, Shanghai, People's Republic of China
| | - Jürg Utzinger
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Marcel Tanner
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Randall Kramer
- Duke Global Health Institute, Duke University, Durham, NC, USA
| | - Wei-Zhong Yang
- Chinese Preventive Medicine Association, Beijing, People's Republic of China; Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
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Chretien JP, Anyamba A, Small J, Britch S, Sanchez JL, Halbach AC, Tucker C, Linthicum KJ. Global climate anomalies and potential infectious disease risks: 2014-2015. PLOS CURRENTS 2015; 7. [PMID: 25685635 PMCID: PMC4323421 DOI: 10.1371/currents.outbreaks.95fbc4a8fb4695e049baabfc2fc8289f] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Background: The El Niño/Southern Oscillation (ENSO) is a global climate phenomenon that impacts human infectious disease risk worldwide through droughts, floods, and other climate extremes. Throughout summer and fall 2014 and winter 2015, El Niño Watch, issued by the US National Oceanic and Atmospheric Administration, assessed likely El Niño development during the Northern Hemisphere fall and winter, persisting into spring 2015.
Methods: We identified geographic regions where environmental conditions may increase infectious disease transmission if the predicted El Niño occurs using El Niño indicators (Sea Surface Temperature [SST], Outgoing Longwave Radiation [OLR], and rainfall anomalies) and literature review of El Niño-infectious disease associations.
Results: SSTs in the equatorial Pacific and western Indian Oceans were anomalously elevated during August-October 2014, consistent with a developing weak El Niño event. Teleconnections with local climate is evident in global precipitation patterns, with positive OLR anomalies (drier than average conditions) across Indonesia and coastal southeast Asia, and negative anomalies across northern China, the western Indian Ocean, central Asia, north-central and northeast Africa, Mexico/Central America, the southwestern United States, and the northeastern and southwestern tropical Pacific. Persistence of these conditions could produce environmental settings conducive to increased transmission of cholera, dengue, malaria, Rift Valley fever, and other infectious diseases in regional hotspots as during previous El Niño events.
Discussion and Conclusions: The current development of weak El Niño conditions may have significant potential implications for global public health in winter 2014-spring 2015. Enhanced surveillance and other preparedness measures in predicted infectious disease hotspots could mitigate health impacts.
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Affiliation(s)
- Jean-Paul Chretien
- Division of Integrated Biosurveillance, Armed Forces Health Surveillance Center, Silver Spring, Maryland, USA
| | - Assaf Anyamba
- Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
| | - Jennifer Small
- Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
| | - Seth Britch
- Center for Medical, Agricultural, and Veterinary Entomology, USDA Agricultural Research Service, Gainesville, Florida, USA
| | - Jose L Sanchez
- Division of Global Emerging Infections Surveillance and Response System (GEIS), Armed Forces Health Surveillance Center (AFHSC), Silver Spring, Maryland, USA
| | - Alaina C Halbach
- Division of Global Emerging Infections Surveillance and Response System (GEIS), Armed Forces Health Surveillance Center (AFHSC), Silver Spring, Maryland, USA
| | - Compton Tucker
- Earth Sciences Division, NASA/Goddard Space Flight Center, Greenbelt, Maryland, USA
| | - Kenneth J Linthicum
- Center for Medical, Agricultural, and Veterinary Entomology, USDA Agricultural Research Service, Gainesville, Florida, USA
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Ren Z, Wang D, Hwang J, Bennett A, Sturrock HJW, Ma A, Huang J, Xia Z, Feng X, Wang J. Spatial-temporal variation and primary ecological drivers of Anopheles sinensis human biting rates in malaria epidemic-prone regions of China. PLoS One 2015; 10:e0116932. [PMID: 25611483 PMCID: PMC4303435 DOI: 10.1371/journal.pone.0116932] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2014] [Accepted: 11/26/2014] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Robust malaria vector surveillance is essential for optimally selecting and targeting vector control measures. Sixty-two vector surveillance sites were established between 2005 and 2008 by the national malaria surveillance program in China to measure Anopheles sinensis human biting rates. Using these data to determine the primary ecological drivers of malaria vector human biting rates in malaria epidemic-prone regions of China will allow better targeting of vector control resources in space and time as the country aims to eliminate malaria. METHODS We analyzed data from 62 malaria surveillance sentinel sites from 2005 to 2008. Linear mixed effects models were used to identify the primary ecological drivers for Anopheles sinensis human biting rates as well as to explore the spatial-temporal variation of relevant factors at surveillance sites throughout China. RESULTS Minimum semimonthly temperature (β = 2.99; 95% confidence interval (CI) 2.07- 3.92), enhanced vegetation index (β =1.07; 95% CI 0.11-2.03), and paddy index (the percentage of rice paddy field in the total cultivated land area of each site) (β = 0.86; 95% CI 0.17-1.56) were associated with greater An. Sinensis human biting rates, while increasing distance to the nearest river was associated with lower An. Sinensis human biting rates (β = -1.47; 95% CI -2.88, -0.06). The temporal variation (σ(s0)(2) = 0.83) in biting rates was much larger than the spatial variation (σ(t)(2) = 1.35), with 19.3% of temporal variation attributable to differences in minimum temperature and enhanced vegetation index and 16.9% of spatial variance due to distance to the nearest river and the paddy index. DISCUSSION Substantial spatial-temporal variation in An. Sinensis human biting rates exists in malaria epidemic-prone regions of China, with minimum temperature and enhanced vegetation index accounting for the greatest proportion of temporal variation and distance to nearest river and paddy index accounting for the greatest proportion of spatial variation amongst observed ecological drivers. CONCLUSIONS Targeted vector control measures based on these findings can support the ongoing malaria elimination efforts in China more effectively.
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Affiliation(s)
- Zhoupeng Ren
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Duoquan Wang
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, WHO Collaborating Center for Malaria, Schistosomiasis and Filariasis, Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, People’s Republic of China
| | - Jimee Hwang
- Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, California, United States of America
- Malaria Branch, Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Adam Bennett
- Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, California, United States of America
| | - Hugh J. W. Sturrock
- Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, California, United States of America
| | - Aimin Ma
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
- College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing, China
| | - Jixia Huang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
- Center of 3S Technology and Mapping, Beijing Forestry University, Beijing, China
| | - Zhigui Xia
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, WHO Collaborating Center for Malaria, Schistosomiasis and Filariasis, Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, People’s Republic of China
| | - Xinyu Feng
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, WHO Collaborating Center for Malaria, Schistosomiasis and Filariasis, Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, People’s Republic of China
| | - Jinfeng Wang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
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Salvador F, Cossio Y, Riera M, Sánchez-Montalvá A, Bocanegra C, Mendioroz J, Eugenio AN, Sulleiro E, Meredith W, López T, Moreno M, Molina I. Changes in malaria epidemiology in a rural area of Cubal, Angola. Malar J 2015; 14:21. [PMID: 25604647 PMCID: PMC4308942 DOI: 10.1186/s12936-014-0540-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2014] [Accepted: 12/29/2014] [Indexed: 11/20/2022] Open
Abstract
Background Scarce information about malaria epidemiology in Angola has been published. The objective of this study is to describe the epidemiology of malaria at the Hospital Nossa Senhora da Paz (Cubal, Angola) and the fatality rate due to malaria (total and in children under five years) in the last five years. Methods A retrospective, observational study was performed at the Hospital Nossa Senhora da Paz, a 400-bed rural hospital located in Benguela Province of Angola. The study population included all patients who attended the hospital from January 2009 to December 2013. Outcome variables were calculated as follows: the percentage of malaria cases (number of positive thick blood films, divided by the total thick blood films performed); the percentage of in-patients for malaria (number of in-patients diagnosed with malaria, divided by the total number of in-patients); and, the fatality rate (number of deaths due to malaria divided by the number of positive thick blood films). Results Overall, 23,106 thick blood films were performed, of which 3,279 (14.2%) were positive for Plasmodium falciparum infection. During this five-year period, a reduction of 40% (95% CI 37-43%, p < 0.001) in the malaria-positive slides was detected. Distribution of positive-malaria slides showed a seasonal distribution with a peak from December to March (rainy season). An average annual reduction of 52% (95% CI 50-54%, p < 0.001) in the admissions due to malaria was observed. The overall fatality rate due to malaria was 8.3%, and no significant differences in the annual fatality rate were found (p = 0.553). Conclusions A reduction in the number of malaria cases and the number of admissions due to malaria has been observed at the Hospital Nossa Senhora da Paz, during the last five years, and incidence along the study period showed a seasonal distribution. All this information could be useful when deciding which malaria control strategies have to be implemented in this area.
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Affiliation(s)
- Fernando Salvador
- Department of Infectious Diseases, Vall d'Hebron University Hospital, Universitat Autònoma de Barcelona, Barcelona, Spain.
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Gao D, Lou Y, Ruan S. A PERIODIC ROSS-MACDONALD MODEL IN A PATCHY ENVIRONMENT. DISCRETE AND CONTINUOUS DYNAMICAL SYSTEMS. SERIES B 2014; 19:3133-3145. [PMID: 25473381 PMCID: PMC4244283 DOI: 10.3934/dcdsb.2014.19.3133] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Based on the classical Ross-Macdonald model, in this paper we propose a periodic malaria model to incorporate the effects of temporal and spatial heterogeneity on disease transmission. The temporal heterogeneity is described by assuming that some model coefficients are time-periodic, while the spatial heterogeneity is modeled by using a multi-patch structure and assuming that individuals travel among patches. We calculate the basic reproduction number [Formula: see text] and show that either the disease-free periodic solution is globally asymptotically stable if [Formula: see text] or the positive periodic solution is globally asymptotically stable if [Formula: see text]. Numerical simulations are conducted to confirm the analytical results and explore the effect of travel control on the disease prevalence.
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Affiliation(s)
- Daozhou Gao
- Francis I. Proctor Foundation for Research in Ophthalmology University of California, San Francisco San Francisco, CA 94143, USA
| | - Yijun Lou
- Department of Applied Mathematics The Hong Kong Polytechnic University Hung Hom, Kowloon, Hong Kong, China
| | - Shigui Ruan
- Department of Mathematics University of Miami Coral Gables, FL 33124, USA
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Zhang Q, Lai S, Zheng C, Zhang H, Zhou S, Hu W, Clements ACA, Zhou XN, Yang W, Hay SI, Yu H, Li Z. The epidemiology of Plasmodium vivax and Plasmodium falciparum malaria in China, 2004-2012: from intensified control to elimination. Malar J 2014; 13:419. [PMID: 25363492 PMCID: PMC4232696 DOI: 10.1186/1475-2875-13-419] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2014] [Accepted: 10/25/2014] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND In China, the national malaria elimination programme has been operating since 2010. This study aimed to explore the epidemiological changes in patterns of malaria in China from intensified control to elimination stages. METHODS Data on nationwide malaria cases from 2004 to 2012 were extracted from the Chinese national malaria surveillance system. The secular trend, gender and age features, seasonality, and spatial distribution by Plasmodium species were analysed. RESULTS In total, 238,443 malaria cases were reported, and the proportion of Plasmodium falciparum increased drastically from <10% before 2010 to 55.2% in 2012. From 2004 to 2006, malaria showed a significantly increasing trend and with the highest incidence peak in 2006 (4.6/100,000), while from 2007 onwards, malaria decreased sharply to only 0.18/100,000 in 2012. Males and young age groups became the predominantly affected population. The areas affected by Plasmodium vivax malaria shrunk, while areas affected by P. falciparum malaria expanded from 294 counties in 2004 to 600 counties in 2012. CONCLUSIONS This study demonstrated that malaria has decreased dramatically in the last five years, especially since the Chinese government launched a malaria elimination programme in 2010, and areas with reported falciparum malaria cases have expanded over recent years. These findings suggest that elimination efforts should be improved to meet these changes, so as to achieve the nationwide malaria elimination goal in China in 2020.
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Affiliation(s)
- Qian Zhang
- />Division of Infectious Diseases, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, 155 Changbai Road, Changping District, Beijing 102206 China
| | - Shengjie Lai
- />Division of Infectious Diseases, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, 155 Changbai Road, Changping District, Beijing 102206 China
| | - Canjun Zheng
- />Division of Infectious Diseases, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, 155 Changbai Road, Changping District, Beijing 102206 China
| | - Honglong Zhang
- />Division of Infectious Diseases, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, 155 Changbai Road, Changping District, Beijing 102206 China
| | - Sheng Zhou
- />Division of Infectious Diseases, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, 155 Changbai Road, Changping District, Beijing 102206 China
| | - Wenbiao Hu
- />School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia
| | - Archie CA Clements
- />Research School of Population Health, College of Medicine, Biology and Environment, The Australian National University, Canberra, Australia
| | - Xiao-Nong Zhou
- />National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Ruijin 2nd Road, Shanghai, China
- />Key Laboratory on Biology of Parasite and Vector, Ministry of Health, WHO Collaborating, Shanghai, China
| | - Weizhong Yang
- />Division of Infectious Diseases, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, 155 Changbai Road, Changping District, Beijing 102206 China
| | - Simon I Hay
- />Spatial Ecology and Epidemiology Group, Tinbergen Building, Department of Zoology, University of Oxford, South Parks Road, Oxford, OX1 3PS UK
- />Fogarty International Center, National Institutes of Health, Bethesda, MD 20892 USA
| | - Hongjie Yu
- />Division of Infectious Diseases, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, 155 Changbai Road, Changping District, Beijing 102206 China
| | - Zhongjie Li
- />Division of Infectious Diseases, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, 155 Changbai Road, Changping District, Beijing 102206 China
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Huang B, Huang S, Su XZ, Tong X, Yan J, Li H, Lu F. Molecular surveillance of pvdhfr, pvdhps, and pvmdr-1 mutations in Plasmodium vivax isolates from Yunnan and Anhui provinces of China. Malar J 2014; 13:346. [PMID: 25179752 PMCID: PMC4161776 DOI: 10.1186/1475-2875-13-346] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2014] [Accepted: 07/10/2014] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Plasmodium vivax is the predominant species of human malaria parasites present in China. Although sulphadoxine-pyrimethamine (SP) and chloroquine (CQ) have been widely used for malaria treatment in China, the resistance profiles of these drugs are not available. Analysis of dihydrofolate reductase (dhfr), dihydropteroate synthase (dhps), and multidrug resistance (mdr-1) gene mutations in P. vivax isolates is a valuable molecular approach for mapping resistance to SP and CQ. This study investigates the prevalence of pvdhfr, pvdhps, and pvmdr-1 of P. vivax clinical isolates from China and provides baseline molecular epidemiologic data on SP- and CQ-associated resistance in P. vivax. METHODS Plasmodium vivax clinical isolates were collected from two malaria-endemic regions of China, subtropical (Xishuangbanna, Yunnan province) and temperate (Bozhou, Anhui province), from 2009 to 2012. All isolates were analysed for single nucleotide polymorphism haplotypes in pvdhfr, pvdhps, and pvmdr-1 using direct DNA sequencing. RESULTS In pvdhfr, 15% of Xishuangbanna isolates carried wild-type (WT) allele, whereas the majority of isolates carried mutant genes with substitutions at five codons. Eight mutant haplotypes of pvdhfr were detected, while limited polymorphism of pvdhfr was found in Bozhou isolates. A size polymorphism was present in pvdhfr, with the three-repeat type being the most predominate in both Xishuangbanna (79%) and Bozhou (97%) isolates. In pvdhps, mutations at four codons were detected in Xishuangbanna isolates leading to six haplotypes, including WT allele, single-mutation, double-mutation, and triple-mutation alleles. All Bozhou isolates carried WT pvhdps. In pvmdr-1, isolates from Xishuangbanna carried mutations at codons Y976F and F1076L, whereas all isolates from Bozhou had only a single mutation at codon F1076L. CONCLUSIONS Plasmodium vivax isolates from subtropical and temperate zones of China are shown to have dramatically different frequencies and patterns of mutations in pvdhfr, pvdhps, and pvmdr-1. Whereas P. vivax populations in subtropical China are highly resistant to SP and CQ, those in the temperate zone may still be susceptible to SP and CQ. This information is useful for establishing treatment policy and provides a baseline for molecular surveillance of drug-resistant P. vivax in these areas.
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Affiliation(s)
- Bo Huang
- />Department of Parasitology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080 Guangdong China
- />Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Guangzhou, 510080 Guangdong China
| | - Shiguang Huang
- />School of Medicine, Jinan University, Guangzhou, 510632 Guangdong China
| | - Xin-zhuan Su
- />Laboratory of Malaria and Vector Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892 USA
- />State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, 361005 Fujian China
| | - Xinxin Tong
- />Department of Parasitology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080 Guangdong China
- />Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Guangzhou, 510080 Guangdong China
| | - Junping Yan
- />Department of Parasitology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080 Guangdong China
- />Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Guangzhou, 510080 Guangdong China
| | - Hongbin Li
- />Xishuangbanna CDC, Xishuangbanna Prefecture Jinghong, 666100 Yunnan China
| | - Fangli Lu
- />Department of Parasitology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080 Guangdong China
- />Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Guangzhou, 510080 Guangdong China
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A mixed method to evaluate burden of malaria due to flooding and waterlogging in Mengcheng County, China: a case study. PLoS One 2014; 9:e97520. [PMID: 24830808 PMCID: PMC4022516 DOI: 10.1371/journal.pone.0097520] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2014] [Accepted: 04/20/2014] [Indexed: 11/19/2022] Open
Abstract
Background Malaria is a highly climate-sensitive vector-borne infectious disease that still represents a significant public health problem in Huaihe River Basin. However, little comprehensive information about the burden of malaria caused by flooding and waterlogging is available from this region. This study aims to quantitatively assess the impact of flooding and waterlogging on the burden of malaria in a county of Anhui Province, China. Methods A mixed method evaluation was conducted. A case-crossover study was firstly performed to evaluate the relationship between daily number of cases of malaria and flooding and waterlogging from May to October 2007 in Mengcheng County, China. Stratified Cox models were used to examine the lagged time and hazard ratios (HRs) of the risk of flooding and waterlogging on malaria. Years lived with disability (YLDs) of malaria attributable to flooding and waterlogging were then estimated based on the WHO framework of calculating potential impact fraction in the Global Burden of Disease study. Results A total of 3683 malaria were notified during the study period. The strongest effect was shown with a 25-day lag for flooding and a 7-day lag for waterlogging. Multivariable analysis showed that an increased risk of malaria was significantly associated with flooding alone [adjusted hazard ratio (AHR) = 1.467, 95% CI = 1.257, 1.713], waterlogging alone (AHR = 1.879, 95% CI = 1.696, 2.121), and flooding and waterlogging together (AHR = 2.926, 95% CI = 2.576, 3.325). YLDs per 1000 of malaria attributable to flooding alone, waterlogging alone and flooding and waterlogging together were 0.009 per day, 0.019 per day and 0.022 per day, respectively. Conclusion Flooding and waterlogging can lead to higher burden of malaria in the study area. Public health action should be taken to avoid and control a potential risk of malaria epidemics after these two weather disasters.
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Zhao X, Chen F, Feng Z, Li X, Zhou XH. The temporal lagged association between meteorological factors and malaria in 30 counties in south-west China: a multilevel distributed lag non-linear analysis. Malar J 2014; 13:57. [PMID: 24528891 PMCID: PMC3932312 DOI: 10.1186/1475-2875-13-57] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2013] [Accepted: 02/13/2014] [Indexed: 11/26/2022] Open
Abstract
Background The association between malaria and meteorological factors is complex due to the lagged and non-linear pattern. Without fully considering these characteristics, existing studies usually concluded inconsistent findings. Investigating the lagged correlation pattern between malaria and climatic variables may improve the understanding of the association and generate possible better prediction models. This is especially beneficial to the south-west China, which is a high-incidence area in China. Methods Thirty counties in south-west China were selected, and corresponding weekly malaria cases and four weekly meteorological variables were collected from 2004 to 2009. The Multilevel Distributed Lag Non-linear Model (MDLNM) was used to study the temporal lagged correlation between weekly malaria and weekly meteorological factors. The counties were divided into two groups, hot and cold weathers, in order to compare the difference under different climatic conditions and improve reliability and generalizability within similar climatic conditions. Results Rainfall was associated with malaria cases in both hot and cold weather counties with a lagged correlation, and the lag range was relatively longer than those of other meteorological factors. Besides, the lag range was longer in hot weather counties compared to cold weather counties. Relative humidity was correlated with malaria cases at early and late lags in hot weather counties. Minimum temperature had a longer lag range and larger correlation coefficients for hot weather counties compared to cold weather counties. Maximum temperature was only associated with malaria cases at early lags. Conclusion Using weekly malaria cases and meteorological information, this work studied the temporal lagged association pattern between malaria cases and meteorological information in south-west China. The results suggest that different meteorological factors show distinct patterns and magnitudes for the lagged correlation, and the patterns will depend on the climatic condition. Existing inconsistent findings for climatic factors’ lags could be due to either the invalid assumption of a single fixed lag or the distinct temperature conditions from different study sites. The lag pattern for meteorological factors should be considered in the development of malaria early warning system.
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Affiliation(s)
| | | | | | - Xiaosong Li
- West China School of Public Health, Sichuan University, No,17 Section 3, South Renmin Road, 610041 Chengdu, China.
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Gao J, Sun Y, Lu Y, Li L. Impact of ambient humidity on child health: a systematic review. PLoS One 2014; 9:e112508. [PMID: 25503413 PMCID: PMC4264743 DOI: 10.1371/journal.pone.0112508] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2014] [Accepted: 10/19/2014] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Changes in relative humidity, along with other meteorological factors, accompany ongoing climate change and play a significant role in weather-related health outcomes, particularly among children. The purpose of this review is to improve our understanding of the relationship between ambient humidity and child health, and to propose directions for future research. METHODS A comprehensive search of electronic databases (PubMed, Medline, Web of Science, ScienceDirect, OvidSP and EBSCO host) and review of reference lists, to supplement relevant studies, were conducted in March 2013. All identified records were selected based on explicit inclusion criteria. We extracted data from the included studies using a pre-designed data extraction form, and then performed a quality assessment. Various heterogeneities precluded a formal quantitative meta-analysis, therefore, evidence was compiled using descriptive summaries. RESULTS Out of a total of 3797 identified records, 37 papers were selected for inclusion in this review. Among the 37 studies, 35% were focused on allergic diseases and 32% on respiratory system diseases. Quality assessment revealed 78% of the studies had reporting quality scores above 70%, and all findings demonstrated that ambient humidity generally plays an important role in the incidence and prevalence of climate-sensitive diseases among children. CONCLUSIONS With climate change, there is a significant impact of ambient humidity on child health, especially for climate-sensitive infectious diseases, diarrhoeal diseases, respiratory system diseases, and pediatric allergic diseases. However, some inconsistencies in the direction and magnitude of the effects are observed.
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Affiliation(s)
- Jinghong Gao
- Injury Prevention Research Center, Shantou University Medical College, No. 22 Xinling Road, Shantou, Guangdong, 515041, China
| | - Yunzong Sun
- Department of Public Health, Shantou University Medical College, No. 22 Xinling Road, Shantou, Guangdong, 515041, China
| | - Yaogui Lu
- Injury Prevention Research Center, Shantou University Medical College, No. 22 Xinling Road, Shantou, Guangdong, 515041, China
| | - Liping Li
- Injury Prevention Research Center, Shantou University Medical College, No. 22 Xinling Road, Shantou, Guangdong, 515041, China
- * E-mail:
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