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Wan H, Wu Y, Fan G, Li D. Wolbachia invasion dynamics of a random mosquito population model with imperfect maternal transmission and incomplete CI. J Math Biol 2024; 88:72. [PMID: 38678110 DOI: 10.1007/s00285-024-02094-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 04/10/2023] [Accepted: 04/11/2024] [Indexed: 04/29/2024]
Abstract
In this work, we formulate a random Wolbachia invasion model incorporating the effects of imperfect maternal transmission and incomplete cytoplasmic incompatibility (CI). Under constant environments, we obtain the following results: Firstly, the complete invasion equilibrium of Wolbachia does not exist, and thus the population replacement is not achievable in the case of imperfect maternal transmission; Secondly, imperfect maternal transmission or incomplete CI may obliterate bistability and backward bifurcation, which leads to the failure of Wolbachia invasion, no matter how many infected mosquitoes would be released; Thirdly, the threshold number of the infected mosquitoes to be released would increase with the decrease of the maternal transmission rate or the intensity of CI effect. In random environments, we investigate in detail the Wolbachia invasion dynamics of the random mosquito population model and establish the initial release threshold of infected mosquitoes for successful invasion of Wolbachia into the wild mosquito population. In particular, the existence and stability of invariant probability measures for the establishment and extinction of Wolbachia are determined.
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Affiliation(s)
- Hui Wan
- Ministry of Education Key Laboratory of NSLSCS, School of Mathematical Sciences, Nanjing Normal University, Nanjing, 210023, China
| | - Yin Wu
- Ministry of Education Key Laboratory of NSLSCS, School of Mathematical Sciences, Nanjing Normal University, Nanjing, 210023, China
| | - Guihong Fan
- Department of Mathematics, Columbus State University, Columbus, GA, 31907, USA
| | - Dan Li
- School of Mathematical Sciences, Anhui University, Hefei, 230601, China.
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Cheng Q, Jing Q, Collender PA, Head JR, Li Q, Yu H, Li Z, Ju Y, Chen T, Wang P, Cleary E, Lai S. Prior water availability modifies the effect of heavy rainfall on dengue transmission: a time series analysis of passive surveillance data from southern China. Front Public Health 2023; 11:1287678. [PMID: 38106890 PMCID: PMC10722414 DOI: 10.3389/fpubh.2023.1287678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Accepted: 10/31/2023] [Indexed: 12/19/2023] Open
Abstract
Introduction Given the rapid geographic spread of dengue and the growing frequency and intensity of heavy rainfall events, it is imperative to understand the relationship between these phenomena in order to propose effective interventions. However, studies exploring the association between heavy rainfall and dengue infection risk have reached conflicting conclusions, potentially due to the neglect of prior water availability in mosquito breeding sites as an effect modifier. Methods In this study, we addressed this research gap by considering the impact of prior water availability for the first time. We measured prior water availability as the cumulative precipitation over the preceding 8 weeks and utilized a distributed lag non-linear model stratified by the level of prior water availability to examine the association between dengue infection risk and heavy rainfall in Guangzhou, a dengue transmission hotspot in southern China. Results Our findings suggest that the effects of heavy rainfall are likely to be modified by prior water availability. A 24-55 day lagged impact of heavy rainfall was associated with an increase in dengue risk when prior water availability was low, with the greatest incidence rate ratio (IRR) of 1.37 [95% credible interval (CI): 1.02-1.83] occurring at a lag of 27 days. In contrast, a heavy rainfall lag of 7-121 days decreased dengue risk when prior water availability was high, with the lowest IRR of 0.59 (95% CI: 0.43-0.79), occurring at a lag of 45 days. Discussion These findings may help to reconcile the inconsistent conclusions reached by previous studies and improve our understanding of the complex relationship between heavy rainfall and dengue infection risk.
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Affiliation(s)
- Qu Cheng
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qinlong Jing
- Department of Infectious Diseases, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Philip A. Collender
- Division of Environmental Health Sciences, School of Public Health, , University of California, Berkeley, Berkeley, CA, United States
| | - Jennifer R. Head
- Division of Epidemiology, School of Public Health, University of California, Berkeley, Berkeley, CA, United States
| | - Qi Li
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hailan Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhichao Li
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Yang Ju
- School of Architecture and Urban Planning, Nanjing University, Nanjing, China
| | - Tianmu Chen
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Peng Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Eimear Cleary
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
| | - Shengjie Lai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
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Cheng Q, Jing Q, Collender PA, Head JR, Li Q, Yu H, Li Z, Ju Y, Chen T, Wang P, Cleary E, Lai S. Prior water availability modifies the effect of heavy rainfall on dengue transmission: a time series analysis of passive surveillance data from southern China. RESEARCH SQUARE 2023:rs.3.rs-3302421. [PMID: 37693392 PMCID: PMC10491345 DOI: 10.21203/rs.3.rs-3302421/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Background Given the rapid geographic spread of dengue and the growing frequency and intensity of heavy rainfall events, it is imperative to understand the relationship between these phenomena in order to propose effective interventions. However, studies exploring the association between heavy rainfall and dengue infection risk have reached conflicting conclusions. Methods In this study, we use a distributed lag non-linear model to examine the association between dengue infection risk and heavy rainfall in Guangzhou, a dengue transmission hotspot in southern China, stratified by prior water availability. Results Our findings suggest that the effects of heavy rainfall are likely to be modified by prior water availability. A 24-55 day lagged impact of heavy rainfall was associated with an increase in dengue risk when prior water availability was low, with the greatest incidence rate ratio (IRR) of 1.37 (95% credible interval (CI): 1.02-1.83) occurring at a lag of 27 days. In contrast, a heavy rainfall lag of 7-121 days decreased dengue risk when prior water availability was high, with the lowest IRR of 0.59 (95% CI: 0.43-0.79), occurring at a lag of 45 days. Conclusions These findings may help to reconcile the inconsistent conclusions reached by previous studies and improve our understanding of the complex relationship between heavy rainfall and dengue infection risk.
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Affiliation(s)
- Qu Cheng
- Huazhong University of Science and Technology
| | - Qinlong Jing
- Guangzhou Center for Disease Control and Prevention
| | | | | | - Qi Li
- Huazhong University of Science and Technology
| | - Hailan Yu
- Huazhong University of Science and Technology
| | | | | | | | - Peng Wang
- Huazhong University of Science and Technology
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Zeng Q, Yu X, Ni H, Xiao L, Xu T, Wu H, Chen Y, Deng H, Zhang Y, Pei S, Xiao J, Guo P. Dengue transmission dynamics prediction by combining metapopulation networks and Kalman filter algorithm. PLoS Negl Trop Dis 2023; 17:e0011418. [PMID: 37285385 DOI: 10.1371/journal.pntd.0011418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 05/24/2023] [Indexed: 06/09/2023] Open
Abstract
Predicting the specific magnitude and the temporal peak of the epidemic of individual local outbreaks is critical for infectious disease control. Previous studies have indicated that significant differences in spatial transmission and epidemic magnitude of dengue were influenced by multiple factors, such as mosquito population density, climatic conditions, and population movement patterns. However, there is a lack of studies that combine the above factors to explain their complex nonlinear relationships in dengue transmission and generate accurate predictions. Therefore, to study the complex spatial diffusion of dengue, this research combined the above factors and developed a network model for spatiotemporal transmission prediction of dengue fever using metapopulation networks based on human mobility. For improving the prediction accuracy of the epidemic model, the ensemble adjusted Kalman filter (EAKF), a data assimilation algorithm, was used to iteratively assimilate the observed case data and adjust the model and parameters. Our study demonstrated that the metapopulation network-EAKF system provided accurate predictions for city-level dengue transmission trajectories in retrospective forecasts of 12 cities in Guangdong province, China. Specifically, the system accurately predicts local dengue outbreak magnitude and the temporal peak of the epidemic up to 10 wk in advance. In addition, the system predicted the peak time, peak intensity, and total number of dengue cases more accurately than isolated city-specific forecasts. The general metapopulation assimilation framework presented in our study provides a methodological foundation for establishing an accurate system with finer temporal and spatial resolution for retrospectively forecasting the magnitude and temporal peak of dengue fever outbreaks. These forecasts based on the proposed method can be interoperated to better support intervention decisions and inform the public of potential risks of disease transmission.
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Affiliation(s)
- Qinghui Zeng
- Department of Preventive Medicine, Shantou University Medical College, Shantou, China
| | - Xiaolin Yu
- Department of Preventive Medicine, Shantou University Medical College, Shantou, China
| | - Haobo Ni
- Department of Preventive Medicine, Shantou University Medical College, Shantou, China
| | - Lina Xiao
- Department of Preventive Medicine, Shantou University Medical College, Shantou, China
| | - Ting Xu
- Department of Preventive Medicine, Shantou University Medical College, Shantou, China
| | - Haisheng Wu
- Department of Preventive Medicine, Shantou University Medical College, Shantou, China
| | - Yuliang Chen
- Department of Medical Quality Management, Nanfang Hospital, Guangzhou, China
| | - Hui Deng
- Institute of Vector Control, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Yingtao Zhang
- Institute of Infectious Disease Control and Prevention, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Sen Pei
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, United States of America
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Pi Guo
- Department of Preventive Medicine, Shantou University Medical College, Shantou, China
- Guangdong Provincial Key Laboratory of Infectious Diseases and Molecular Immunopathology, Shantou, China
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Ma Y, Kalantari Z, Destouni G. Infectious Disease Sensitivity to Climate and Other Driver-Pressure Changes: Research Effort and Gaps for Lyme Disease and Cryptosporidiosis. GEOHEALTH 2023; 7:e2022GH000760. [PMID: 37303696 PMCID: PMC10251199 DOI: 10.1029/2022gh000760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 05/24/2023] [Accepted: 05/25/2023] [Indexed: 06/13/2023]
Abstract
Climate sensitivity of infectious diseases is discussed in many studies. A quantitative basis for distinguishing and predicting the disease impacts of climate and other environmental and anthropogenic driver-pressure changes, however, is often lacking. To assess research effort and identify possible key gaps that can guide further research, we here apply a scoping review approach to two widespread infectious diseases: Lyme disease (LD) as a vector-borne and cryptosporidiosis as a water-borne disease. Based on the emerging publication data, we further structure and quantitatively assess the driver-pressure foci and interlinkages considered in the published research so far. This shows important research gaps for the roles of rarely investigated water-related and socioeconomic factors for LD, and land-related factors for cryptosporidiosis. For both diseases, the interactions of host and parasite communities with climate and other driver-pressure factors are understudied, as are also important world regions relative to the disease geographies; in particular, Asia and Africa emerge as main geographic gaps for LD and cryptosporidiosis research, respectively. The scoping approach developed and gaps identified in this study should be useful for further assessment and guidance of research on infectious disease sensitivity to climate and other environmental and anthropogenic changes around the world.
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Affiliation(s)
- Y. Ma
- Department of Physical GeographyStockholm UniversityStockholmSweden
| | - Z. Kalantari
- Department of Physical GeographyStockholm UniversityStockholmSweden
- Department of Sustainable DevelopmentEnvironmental Science and Engineering (SEED)KTH Royal Institute of TechnologyStockholmSweden
| | - G. Destouni
- Department of Physical GeographyStockholm UniversityStockholmSweden
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Guo Z, Liu W, Liu X, Abudunaibi B, Luo L, Wu S, Deng B, Yang T, Huang J, Wu S, Lei L, Zhao Z, Li Z, Li P, Liu C, Zhan M, Chen T. Model-based risk assessment of dengue fever transmission in Xiamen City, China. Front Public Health 2023; 11:1079877. [PMID: 36860401 PMCID: PMC9969104 DOI: 10.3389/fpubh.2023.1079877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 01/25/2023] [Indexed: 02/15/2023] Open
Abstract
Background Quantitative assessment of the risk of local transmission from imported dengue cases makes a great challenge to the development of public health in China. The purpose of this study is to observe the risk of mosquito-borne transmission in Xiamen City through ecological and insecticide resistance monitoring. Quantitative evaluation of mosquito insecticide resistance, community population and the number of imported cases affecting the transmission of dengue fever (DF) in Xiamen was carried out based on transmission dynamics model, so as to reveal the correlation between key risk factors and DF transmission. Methods Based on the dynamics model and combined with the epidemiological characteristics of DF in Xiamen City, a transmission dynamics model was built to simulate the secondary cases caused by imported cases to evaluate the transmission risk of DF, and to explore the influence of mosquito insecticide resistance, community population and imported cases on the epidemic situation of DF in Xiamen City. Results For the transmission model of DF, when the community population is between 10,000 and 25,000, changing the number of imported DF cases and the mortality rate of mosquitoes will have an impact on the spread of indigenous DF cases, however, changing the birth rate of mosquitoes did not gain more effect on the spread of local DF transmission. Conclusions Through the quantitative evaluation of the model, this study determined that the mosquito resistance index has an important influence on the local transmission of dengue fever caused by imported cases in Xiamen, and the Brayton index can also affect the local transmission of the disease.
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Affiliation(s)
- Zhinan Guo
- Xiamen Center for Disease Control and Prevention, Xiamen, Fujian, China
| | - Weikang Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Xingchun Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Buasiyamu Abudunaibi
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Li Luo
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Sihan Wu
- Xiamen Center for Disease Control and Prevention, Xiamen, Fujian, China
| | - Bin Deng
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Tianlong Yang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Jiefeng Huang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Shenggen Wu
- Fujian Provincial Center for Disease Control and Prevention, Fuzhou, Fujian, China
| | - Lei Lei
- Xiamen Center for Disease Control and Prevention, Xiamen, Fujian, China
| | - Zeyu Zhao
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Zhuoyang Li
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Peihua Li
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Chan Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Meirong Zhan
- Fujian Provincial Center for Disease Control and Prevention, Fuzhou, Fujian, China
| | - Tianmu Chen
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
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Liu WH, Shi C, Lu Y, Luo L, Ou CQ. Epidemiological characteristics of imported acute infectious diseases in Guangzhou, China, 2005-2019. PLoS Negl Trop Dis 2022; 16:e0010940. [PMID: 36472963 PMCID: PMC9725138 DOI: 10.1371/journal.pntd.0010940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 11/09/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND The global spread of infectious diseases is currently a prominent threat to public health, with the accelerating pace of globalization and frequent international personnel intercourse. The present study examined the epidemiological characteristics of overseas imported cases of acute infectious diseases in Guangzhou, China. METHODS We retrospectively investigated the distribution of diseases, demographic characteristics, and temporal and spatial variations of imported cases of acute infectious diseases in Guangzhou based on the surveillance data of notifiable infectious diseases from 2005 to 2019, provided by Guangzhou center for Disease Control and Prevention. The Cochran-Armitage trend test was applied to examine the trend in the number of imported cases over time. RESULTS A total of 1,025 overseas imported cases of acute infectious diseases were identified during the study period. The top three diseases were dengue (67.12%), malaria (12.39%), and influenza A (H1N1) pdm09 (4.10%). Imported cases were predominantly males, with a sex ratio of 2.6: 1 and 75.22% of the cases were those aged 20-49 years. Businessmen, workers, students and unemployed persons accounted for a large proportion of the cases (68.49%) and many of the cases came from Southeast Asia (59.02%). The number of imported cases of acute infectious diseases increased during the study period and hit 318 in 2019. A clear seasonal pattern was observed in the number of imported cases with a peak period between June and November. Imported cases were reported in all of the 11 districts in Guangzhou and the central districts were more seriously affected compared with other districts. CONCLUSIONS The burden of dengue imported from overseas was substantial and increasing in Guangzhou, China, with the peak period from June to November. Dengue was the most common imported disease. Most imported cases were males aged 20-49 years and businessmen. Further efforts, such as strengthening surveillance of imported cases, paying close attention to the epidemics in hotspots, and improving the ability to detect the imported cases from overseas, are warranted to control infectious diseases especially in the center of the city with a higher population density highly affected by imported cases.
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Affiliation(s)
- Wen-Hui Liu
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Chen Shi
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Ying Lu
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Lei Luo
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
- * E-mail: (LL); (CO)
| | - Chun-Quan Ou
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
- * E-mail: (LL); (CO)
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Lu X, Bambrick H, Frentiu FD, Huang X, Davis C, Li Z, Yang W, Devine GJ, Hu W. Species-specific climate Suitable Conditions Index and dengue transmission in Guangdong, China. Parasit Vectors 2022; 15:342. [PMID: 36167577 PMCID: PMC9516795 DOI: 10.1186/s13071-022-05453-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 08/26/2022] [Indexed: 12/02/2022] Open
Abstract
Background Optimal climatic conditions for dengue vector mosquito species may play a significant role in dengue transmission. We previously developed a species-specific Suitable Conditions Index (SCI) for Aedes aegypti and Aedes albopictus, respectively. These SCIs rank geographic locations based on their climatic suitability for each of these two dengue vector species and theoretically define parameters for transmission probability. The aim of the study presented here was to use these SCIs together with socio-environmental factors to predict dengue outbreaks in the real world. Methods A negative binomial regression model was used to assess the relationship between vector species-specific SCI and autochthonous dengue cases after accounting for potential confounders in Guangdong, China. The potential interactive effect between the SCI for Ae. albopictus and the SCI for Ae. aegypti on dengue transmission was assessed. Results The SCI for Ae. aegypti was found to be positively associated with autochthonous dengue transmission (incidence rate ratio: 1.06, 95% confidence interval: 1.03, 1.09). A significant interaction effect between the SCI of Ae. albopictus and the SCI of Ae. aegypti was found, with the SCI of Ae. albopictus significantly reducing the effect of the SCI of Ae. aegypti on autochthonous dengue cases. The difference in SCIs had a positive effect on autochthonous dengue cases. Conclusions Our results suggest that dengue fever is more transmittable in regions with warmer weather conditions (high SCI for Ae. aegypti). The SCI of Ae. aegypti would be a useful index to predict dengue transmission in Guangdong, China, even in dengue epidemic regions with Ae. albopictus present. The results also support the benefit of the SCI for evaluating dengue outbreak risk in terms of vector sympatry and interactions in the absence of entomology data in future research. Graphical Abstract ![]()
Supplementary Information The online version contains supplementary material available at 10.1186/s13071-022-05453-x.
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Affiliation(s)
- Xinting Lu
- School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia
| | - Hilary Bambrick
- School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia.,National Centre for Epidemiology and Population Health, The Australian National University, Canberra ACT, Australia
| | - Francesca D Frentiu
- Centre for Immunology and Infection Control, School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia
| | - Xiaodong Huang
- Centre for Immunology and Infection Control, School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia
| | - Callan Davis
- School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia
| | - Zhongjie Li
- Division of Infectious Disease, Key Laboratory of Surveillance and Early Warning of Infectious Disease, Chinese Centre for Disease Control and Prevention, Beijing, China
| | - Weizhong Yang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early Warning of Infectious Disease, Chinese Centre for Disease Control and Prevention, Beijing, China.,School of Population Medicine & Public Health, Chinese Academy of Medical Science, Peking Union Medical College, Beijing, China
| | - Gregor J Devine
- Mosquito Control Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Wenbiao Hu
- School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia.
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Molina-Guzmán LP, Gutiérrez-Builes LA, Ríos-Osorio LA. Models of spatial analysis for vector-borne diseases studies: A systematic review. Vet World 2022; 15:1975-1989. [PMID: 36313837 PMCID: PMC9615510 DOI: 10.14202/vetworld.2022.1975-1989] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 06/24/2022] [Indexed: 11/16/2022] Open
Abstract
Background and Aim: Vector-borne diseases (VBDs) constitute a global problem for humans and animals. Knowledge related to the spatial distribution of various species of vectors and their relationship with the environment where they develop is essential to understand the current risk of VBDs and for planning surveillance and control strategies in the face of future threats. This study aimed to identify models, variables, and factors that may influence the emergence and resurgence of VBDs and how these factors can affect spatial local and global distribution patterns.
Materials and Methods: A systematic review was designed based on identification, screening, selection, and inclusion described in the research protocols according to the preferred reporting items for systematic reviews and meta-analyses guide. A literature search was performed in PubMed, ScienceDirect, Scopus, and SciELO using the following search strategy: Article type: Original research, Language: English, Publishing period: 2010–2020, Search terms: Spatial analysis, spatial models, VBDs, climate, ecologic, life cycle, climate variability, vector-borne, vector, zoonoses, species distribution model, and niche model used in different combinations with "AND" and "OR."
Results: The complexity of the interactions between climate, biotic/abiotic variables, and non-climate factors vary considerably depending on the type of disease and the particular location. VBDs are among the most studied types of illnesses related to climate and environmental aspects due to their high disease burden, extended presence in tropical and subtropical areas, and high susceptibility to climate and environment variations.
Conclusion: It is difficult to generalize our knowledge of VBDs from a geospatial point of view, mainly because every case is inherently independent in variable selection, geographic coverage, and temporal extension. It can be inferred from predictions that as global temperatures increase, so will the potential trend toward extreme events. Consequently, it will become a public health priority to determine the role of climate and environmental variations in the incidence of infectious diseases. Our analysis of the information, as conducted in this work, extends the review beyond individual cases to generate a series of relevant observations applicable to different models.
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Affiliation(s)
- Licet Paola Molina-Guzmán
- Grupo Biología de Sistemas, Escuela de Ciencias de la Salud, Facultad de Medicina, Universidad Pontificia Bolivariana, Medellín, Colombia; Grupo de Investigación Salud y Sostenibilidad, Escuela de Microbiología, Universidad de Antioquia UdeA, Calle 70 No. 52-21, Medellin - Colombia
| | - Lina A. Gutiérrez-Builes
- Grupo Biología de Sistemas, Escuela de Ciencias de la Salud, Facultad de Medicina, Universidad Pontificia Bolivariana, Medellín, Colombia
| | - Leonardo A. Ríos-Osorio
- Grupo de Investigación Salud y Sostenibilidad, Escuela de Microbiología, Universidad de Antioquia UdeA, Calle 70 No. 52-21, Medellin - Colombia
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Fukui S, Kuwano Y, Ueno K, Atsumi K, Ohta S. Modeling the effect of rainfall changes to predict population dynamics of the Asian tiger mosquito Aedes albopictus under future climate conditions. PLoS One 2022; 17:e0268211. [PMID: 35613220 PMCID: PMC9132271 DOI: 10.1371/journal.pone.0268211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Accepted: 04/25/2022] [Indexed: 11/29/2022] Open
Abstract
The population dynamics of mosquitoes in temperate regions are not as well understood as those in tropical and subtropical regions, despite concerns that vector-borne diseases may be prevalent in future climates. Aedes albopictus, a vector mosquito in temperate regions, undergoes egg diapause while overwintering. To assess the prevalence of mosquito-borne diseases in the future, this study aimed to simulate and predict mosquito population dynamics under estimated future climatic conditions. In this study, we tailored the physiology-based climate-driven mosquito population (PCMP) model for temperate mosquitoes to incorporate egg diapauses for overwintering. We also investigated how the incorporation of the effect of rainfall on larval carrying capacity (into a model) changes the population dynamics of this species under future climate conditions. The PCMP model was constructed to simulate mosquito population dynamics, and the parameters of egg diapause and rainfall effects were estimated for each model to fit the observed data in Tokyo. We applied the global climate model data to the PCMP model and observed an increase in the mosquito population under future climate conditions. By applying the PCMP models (with or without the rainfall effect on the carrying capacity of the A. albopictus), our projections indicated that mosquito population dynamics in the future could experience changes in the patterns of their active season and population abundance. According to our results, the peak population number simulated using the highest CO2 emission scenario, while incorporating the rainfall effect on the carrying capacity, was approximately 1.35 times larger than that predicted using the model that did not consider the rainfall effect. This implies that the inclusion of rainfall effects on mosquito population dynamics has a major impact on the risk assessments of mosquito-borne diseases in the future.
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Affiliation(s)
- Shin Fukui
- Department of Human Behavior and Environment Sciences, Faculty of Human Sciences, Waseda University, Tokyo, Japan
- Fisheries Data Sciences Division, Fisheries Stock Assessment Center, Fisheries Resources Institute, Japan Fisheries Research and Education Agency, Yokohama, Japan
| | - Yusuke Kuwano
- Department of Human Behavior and Environment Sciences, Faculty of Human Sciences, Waseda University, Tokyo, Japan
- Department of Evolutionary Studies of Biosystems, School of Advanced Sciences, SOKENDAI (The Graduate University for Advanced Studies), Hayama, Japan
| | - Kazuki Ueno
- Department of Human Behavior and Environment Sciences, Faculty of Human Sciences, Waseda University, Tokyo, Japan
| | - Kazuyuki Atsumi
- Department of Human Behavior and Environment Sciences, Faculty of Human Sciences, Waseda University, Tokyo, Japan
| | - Shunji Ohta
- Department of Human Behavior and Environment Sciences, Faculty of Human Sciences, Waseda University, Tokyo, Japan
- * E-mail:
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Stephenson C, Coker E, Wisely S, Liang S, Dinglasan RR, Lednicky JA. Imported Dengue Case Numbers and Local Climatic Patterns Are Associated with Dengue Virus Transmission in Florida, USA. INSECTS 2022; 13:insects13020163. [PMID: 35206736 PMCID: PMC8880009 DOI: 10.3390/insects13020163] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 01/27/2022] [Accepted: 01/31/2022] [Indexed: 12/07/2022]
Abstract
Aedes aegypti mosquitoes are the main vector of dengue viruses globally and are present throughout much of the state of Florida (FL) in the United States of America. However, local transmission of dengue viruses in FL has mainly occurred in the southernmost counties; specifically Monroe and Miami-Dade counties. To get a better understanding of the ecologic risk factors for dengue fever incidence throughout FL, we collected and analyzed numerous environmental factors that have previously been connected to local dengue cases in disease-endemic regions. We analyzed these factors for each county-year in FL, between 2009–2019, using negative binomial regression. Monthly minimum temperature of 17.5–20.8 °C, an average temperature of 26.1–26.7 °C, a maximum temperature of 33.6–34.7 °C, rainfall between 11.4–12.7 cm, and increasing numbers of imported dengue cases were associated with the highest risk of dengue incidence per county-year. To our knowledge, we have developed the first predictive model for dengue fever incidence in FL counties and our findings provide critical information about weather conditions that could increase the risk for dengue outbreaks as well as the important contribution of imported dengue cases to local establishment of the virus in Ae. aegypti populations.
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Affiliation(s)
- Caroline Stephenson
- Department of Environmental and Global Health, University of Florida, Gainesville, FL 32610, USA; (C.S.); (E.C.); (S.L.)
- Emerging Pathogens Institute, University of Florida, Gainesville, FL 32610, USA;
| | - Eric Coker
- Department of Environmental and Global Health, University of Florida, Gainesville, FL 32610, USA; (C.S.); (E.C.); (S.L.)
| | - Samantha Wisely
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, FL 32611, USA;
| | - Song Liang
- Department of Environmental and Global Health, University of Florida, Gainesville, FL 32610, USA; (C.S.); (E.C.); (S.L.)
- Emerging Pathogens Institute, University of Florida, Gainesville, FL 32610, USA;
| | - Rhoel R. Dinglasan
- Emerging Pathogens Institute, University of Florida, Gainesville, FL 32610, USA;
- Department of Infectious Diseases and Immunology, University of Florida, Gainesville, FL 32608, USA
| | - John A. Lednicky
- Department of Environmental and Global Health, University of Florida, Gainesville, FL 32610, USA; (C.S.); (E.C.); (S.L.)
- Emerging Pathogens Institute, University of Florida, Gainesville, FL 32610, USA;
- Correspondence: ; Tel.: +1-352-273-9204
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12
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The Epidemic Risk of Dengue Fever in Japan: Climate Change and Seasonality. CANADIAN JOURNAL OF INFECTIOUS DISEASES & MEDICAL MICROBIOLOGY 2021; 2021:6699788. [PMID: 34721747 PMCID: PMC8553502 DOI: 10.1155/2021/6699788] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Accepted: 10/08/2021] [Indexed: 12/27/2022]
Abstract
Dengue fever is a leading cause of illness and death in the tropics and subtropics, and the disease has become a threat to many nonendemic countries where the competent vectors such as Aedes albopictus and Aedes aegypti are abundant. The dengue epidemic in Tokyo, 2014, poses the critical importance to accurately model and predict the outbreak risk of dengue fever in nonendemic regions. Using climatological datasets and traveler volumes in Japan, where dengue was not seen for 70 years by 2014, we investigated the outbreak risk of dengue in 47 prefectures, employing the temperature-dependent basic reproduction number and a branching process model. Our results show that the effective reproduction number varies largely by season and by prefecture, and, moreover, the probability of outbreak if an untraced case is imported varies greatly with the calendar time of importation and location of destination. Combining the seasonally varying outbreak risk with time-dependent traveler volume data, the unconditional outbreak risk was calculated, illustrating different outbreak risks between southern coastal areas and northern tourist cities. As the main finding, the large travel volume with nonnegligible risk of outbreak explains the reason why a summer outbreak in Tokyo, 2014, was observed. Prefectures at high risk of future outbreak would be Tokyo again, Kanagawa or Osaka, and highly populated prefectures with large number of travelers.
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Wu W, Ren H, Lu L. Increasingly expanded future risk of dengue fever in the Pearl River Delta, China. PLoS Negl Trop Dis 2021; 15:e0009745. [PMID: 34559817 PMCID: PMC8462684 DOI: 10.1371/journal.pntd.0009745] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 08/18/2021] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND In recent years, frequent outbreaks of dengue fever (DF) have become an increasingly serious public health issue in China, especially in the Pearl River Delta (PRD) with fast socioeconomic developments. Previous studies mainly focused on the historic DF epidemics, their influencing factors, and the prediction of DF risks. However, the future risks of this disease under both different socioeconomic development and representative concentration pathways (RCPs) scenarios remain little understood. METHODOLOGY AND PRINCIPAL FINDINGS In this study, a spatial dataset of gross domestic product (GDP), population density, and land use and land coverage (LULC) in 2050 and 2070 was obtained by simulation based on the different shared socioeconomic pathways (SSPs), and the future climatic data derived from the RCP scenarios were integrated into the Maxent models for predicting the future DF risk in the PRD region. Among all the variables included in this study, socioeconomics factors made the dominant contribution (83% or so) during simulating the current spatial distribution of the DF epidemics in the PRD region. Moreover, the spatial distribution of future DF risk identified by the climatic and socioeconomic (C&S) variables models was more detailed than that of the climatic variables models. Along with global warming and socioeconomic development, the zones with DF high and moderate risk will continue to increase, and the population at high and moderate risk will reach a maximum of 48.47 million (i.e., 63.78% of the whole PRD) under the RCP 4.5/SSP2 in 2070. CONCLUSIONS The increasing DF risk may be an inevitable public health threat in the PRD region with rapid socioeconomic developments and global warming in the future. Our results suggest that curbs in emissions and more sustainable socioeconomic growth targets offer hope for limiting the future impact of dengue, and effective prevention and control need to continue to be strengthened at the junction of Guangzhou-Foshan, north-central Zhongshan city, and central-western Dongguan city. Our study provides useful clues for relevant hygienic authorities making targeted adapting strategies for this disease.
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Affiliation(s)
- Wei Wu
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- School of Geography and Ocean Science, Nanjing University, Nanjing, China
- Key Laboratory of Coastal zone Development and Protection, Ministry of Land and Resources of China, Nanjing, China
| | - Hongyan Ren
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- * E-mail:
| | - Liang Lu
- 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, China
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Climate Variability, Dengue Vector Abundance and Dengue Fever Cases in Dhaka, Bangladesh: A Time-Series Study. ATMOSPHERE 2021. [DOI: 10.3390/atmos12070905] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Numerous studies on climate change and variability have revealed that these phenomena have noticeable influence on the epidemiology of dengue fever, and such relationships are complex due to the role of the vector—the Aedes mosquitoes. By undertaking a step-by-step approach, the present study examined the effects of climatic factors on vector abundance and subsequent effects on dengue cases of Dhaka city, Bangladesh. Here, we first analyzed the time-series of Stegomyia indices for Aedes mosquitoes in relation to temperature, rainfall and relative humidity for 2002–2013, and then in relation to reported dengue cases in Dhaka. These data were analyzed at three sequential stages using the generalized linear model (GLM) and generalized additive model (GAM). Results revealed strong evidence that an increase in Aedes abundance is associated with the rise in temperature, relative humidity, and rainfall during the monsoon months, that turns into subsequent increases in dengue incidence. Further we found that (i) the mean rainfall and the lag mean rainfall were significantly related to Container Index, and (ii) the Breteau Index was significantly related to the mean relative humidity and mean rainfall. The relationships of dengue cases with Stegomyia indices and with the mean relative humidity, and the lag mean rainfall were highly significant. In examining longitudinal (2001–2013) data, we found significant evidence of time lag between mean rainfall and dengue cases.
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15
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Liu W, Hu W, Dong Z, You X. Travel-related infection in Guangzhou, China,2009-2019. Travel Med Infect Dis 2021; 43:102106. [PMID: 34116241 DOI: 10.1016/j.tmaid.2021.102106] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Revised: 06/01/2021] [Accepted: 06/04/2021] [Indexed: 11/16/2022]
Abstract
BACKGROUND We analyzed the epidemiological characteristics of travel-related infectious diseases in reported Guangzhou between 2009 and 2019 to provide a scientific basis for prevention and control strategies. METHOD The infectious diseases report information system of China was mined for case reports, combined with clinical diagnosis records, and analyzed. RESULTS Between 2009 and 2019, 1478 cases of imported infectious diseases were reported in Guangzhou. Dengue fever accounted for 46.14%of cases and malaria accounted for 45.47% of cases. The patients with imported travel-related infection cases were mainly male (75.88%), Chinese (75.57%), and aged 20-45 years (83.01%). Cases increased from May each year, peaked between August and September, and declined rapidly after October. The main source areas of import were Africa and other countries in Asia. CONCLUSIONS Dengue fever and malaria are the main travel-related infection in Guangzhou, and are generally brought in by male Chinese workers. Intervention and health education in this population should be strengthened to prevent and control travel-related infection.
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Affiliation(s)
- Weisi Liu
- Guangzhou Center for Disease Control and Prevention, China.
| | - Wensui Hu
- Guangzhou Center for Disease Control and Prevention, China
| | - Zhiqiang Dong
- Guangzhou Center for Disease Control and Prevention, China
| | - Xiaojin You
- Guangzhou Center for Disease Control and Prevention, China
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16
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Zhao S, Musa SS, Meng J, Qin J, He D. The long-term changing dynamics of dengue infectivity in Guangdong, China, from 2008-2018: a modelling analysis. Trans R Soc Trop Med Hyg 2021; 114:62-71. [PMID: 31638154 DOI: 10.1093/trstmh/trz084] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2018] [Revised: 07/02/2019] [Accepted: 07/19/2019] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Dengue remains a severe threat to public health in tropical and subtropical regions. In China, over 85% of domestic dengue cases are in the Guangdong province and there were 53 139 reported cases during 2008-2018. In Guangdong, the 2014 dengue outbreak was the largest in the last 20 y and it was probably triggered by a new strain imported from other regions. METHODS We studied the long-term patterns of dengue infectivity in Guangdong from 2008-2018 and compared the infectivity estimates across different periods. RESULTS We found that the annual epidemics approximately followed exponential growth during 2011-2014. The transmission rates were at a low level during 2008-2012, significantly increased 1.43-fold [1.22, 1.69] during 2013-2014 and then decreased back to a low level after 2015. By using the mosquito index and the likelihood-inference approach, we found that the new strain most likely invaded Guangdong in April 2014. CONCLUSIONS The long-term changing dynamics of dengue infectivity are associated with the new dengue virus strain invasion and public health control programmes. The increase in infectiousness indicates the potential for dengue to go from being imported to becoming an endemic in Guangdong, China.
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Affiliation(s)
- Shi Zhao
- School of Nursing, Hong Kong Polytechnic University, Hong Kong, China.,Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China
| | - Salihu S Musa
- Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China
| | - Jiayi Meng
- School of Economics and Finance, Xi'an International Studies University, Xi'an, China
| | - Jing Qin
- School of Nursing, Hong Kong Polytechnic University, Hong Kong, China
| | - Daihai He
- Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China
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Xavier LL, Honório NA, Pessanha JFM, Peiter PC. Analysis of climate factors and dengue incidence in the metropolitan region of Rio de Janeiro, Brazil. PLoS One 2021; 16:e0251403. [PMID: 34014989 PMCID: PMC8136695 DOI: 10.1371/journal.pone.0251403] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Accepted: 04/26/2021] [Indexed: 11/19/2022] Open
Abstract
Dengue is a re-emerging disease, currently considered the most important mosquito-borne arbovirus infection affecting humankind, taking into account both its morbidity and mortality. Brazil is considered an endemic country for dengue, such that more than 1,544,987 confirmed cases were notified in 2019, which means an incidence rate of 735 for every 100 thousand inhabitants. Climate is an important factor in the temporal and spatial distribution of vector-borne diseases, such as dengue. Thus, rainfall and temperature are considered macro-factors determinants for dengue, since they directly influence the population density of Aedes aegypti, which is subject to seasonal fluctuations, mainly due to these variables. This study examined the incidence of dengue fever related to the climate influence by using temperature and rainfall variables data obtained from remote sensing via artificial satellites in the metropolitan region of Rio de Janeiro, Brazil. The mathematical model that best fits the data is based on an auto-regressive moving average with exogenous inputs (ARMAX). It reproduced the values of incidence rates in the study period and managed to predict with good precision in a one-year horizon. The approach described in present work may be replicated in cities around the world by the public health managers, to build auxiliary operational tools for control and prevention tasks of dengue, as well of other arbovirus diseases.
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Affiliation(s)
- Leandro Layter Xavier
- Parasitic Diseases Laboratory, Tropical Medicine Program, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
| | - Nildimar Alves Honório
- Hematozoan Transmitting Mosquito, Tropical Medicine Program, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
| | | | - Paulo César Peiter
- Parasitic Diseases Laboratory, Tropical Medicine Program, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
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Metelmann S, Liu X, Lu L, Caminade C, Liu K, Cao L, Medlock JM, Baylis M, Morse AP, Liu Q. Assessing the suitability for Aedes albopictus and dengue transmission risk in China with a delay differential equation model. PLoS Negl Trop Dis 2021; 15:e0009153. [PMID: 33770107 PMCID: PMC7996998 DOI: 10.1371/journal.pntd.0009153] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Accepted: 01/20/2021] [Indexed: 01/04/2023] Open
Abstract
Dengue is considered non-endemic to mainland China. However, travellers frequently import the virus from overseas and local mosquito species can then spread the disease in the population. As a consequence, mainland China still experiences large dengue outbreaks. Temperature plays a key role in these outbreaks: it affects the development and survival of the vector and the replication rate of the virus. To better understand its implication in the transmission risk of dengue, we developed a delay differential equation model that explicitly simulates temperature-dependent development periods and tested it with collected field data for the Asian tiger mosquito, Aedes albopictus. The model predicts mosquito occurrence locations with a high accuracy (Cohen's κ of 0.78) and realistically replicates mosquito population dynamics. Analysing the infection dynamics during the 2014 dengue outbreak that occurred in Guangzhou showed that the outbreak could have lasted for another four weeks if mosquito control interventions had not been undertaken. Finally, we analyse the dengue transmission risk in mainland China. We find that southern China, including Guangzhou, can have more than seven months of dengue transmission per year while even Beijing, in the temperate north, can have dengue transmission during hot summer months. The results demonstrate the importance of using detailed vector and infection ecology, especially when vector-borne disease transmission risk is modelled over a broad range of climatic zones.
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Affiliation(s)
- Soeren Metelmann
- Institute for Infection and Global Health, University of Liverpool, Liverpool, United Kingdom
- NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, Liverpool, United Kingdom
| | - Xiaobo Liu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, WHO Collaborating Centre for Vector Surveillance and Management, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Liang Lu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, WHO Collaborating Centre for Vector Surveillance and Management, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Cyril Caminade
- Institute for Infection and Global Health, University of Liverpool, Liverpool, United Kingdom
- NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, Liverpool, United Kingdom
| | - Keke Liu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, WHO Collaborating Centre for Vector Surveillance and Management, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Lina Cao
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, WHO Collaborating Centre for Vector Surveillance and Management, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Public Health, Shandong University, Jinan, China
| | - Jolyon M. Medlock
- NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, Liverpool, United Kingdom
- Medical Entomology Group, Public Health England, Salisbury, United Kingdom
| | - Matthew Baylis
- Institute for Infection and Global Health, University of Liverpool, Liverpool, United Kingdom
- NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, Liverpool, United Kingdom
| | - Andrew P. Morse
- NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, Liverpool, United Kingdom
- School of Environmental Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Qiyong Liu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, WHO Collaborating Centre for Vector Surveillance and Management, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Public Health, Shandong University, Jinan, China
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Ma M, Wu S, He Z, Yuan L, Bai Z, Jiang L, Marshall J, Lu J, Yang Z, Jing Q. New genotype invasion of dengue virus serotype 1 drove massive outbreak in Guangzhou, China. Parasit Vectors 2021; 14:126. [PMID: 33639996 PMCID: PMC7910771 DOI: 10.1186/s13071-021-04631-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Accepted: 02/06/2021] [Indexed: 11/26/2022] Open
Abstract
Background Dengue fever is a mosquito-borne infectious disease that has caused major health problems. Variations in dengue virus (DENV) genes are important features of epidemic outbreaks. However, the associations of DENV genes with epidemic potential have not been extensively examined. Here, we assessed new genotype invasion of DENV-1 isolated from Guangzhou in China to evaluate associations with epidemic outbreaks. Methodology/principal findings We used DENV-1 strains isolated from sera of dengue cases from 2002 to 2016 in Guangzhou for complete genome sequencing. A neighbor-joining phylogenetic tree was constructed to elucidate the genotype characteristics and determine if new genotype invasion was correlated with major outbreaks. In our study, a new genotype invasion event was observed during each significant outbreak period in 2002–2003, 2006–2007, and 2013–2014. Genotype II was the main epidemic genotype in 2003 and before. Invasion of genotype I in 2006 caused an unusual outbreak with 765 cases (relative risk [RR] = 16.24, 95% confidence interval [CI] 12.41–21.25). At the middle and late stages of the 2013 outbreak, genotype III was introduced to Guangzhou as a new genotype invasion responsible for 37,340 cases with RR 541.73 (95% CI 417.78–702.45), after which genotypes I and III began co-circulating. Base mutations occurred after new genotype invasion, and the gene sequence of NS3 protein had the lowest average similarity ratio (99.82%), followed by the gene sequence of E protein (99.86%), as compared to the 2013 strain. Conclusions/significance Genotype replacement and co-circulation of multiple DENV-1 genotypes were observed. New genotype invasion was highly correlated with local unusual outbreaks. In addition to DENV-1 genotype I in the unprecedented outbreak in 2014, new genotype invasion by DENV-1 genotype III occurred in Guangzhou.![]()
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Affiliation(s)
- Mengmeng Ma
- Department of Infectious Diseases, Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, People's Republic of China
| | - Sean Wu
- Department of Biostatistics and Epidemiology, School of Public Health, University of California, Berkeley, CA, USA
| | - Zhenjian He
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, People's Republic of China
| | - Lihong Yuan
- School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, Guangdong, People's Republic of China
| | - Zhijun Bai
- Department of Infectious Diseases, Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, People's Republic of China
| | - Liyun Jiang
- Department of Infectious Diseases, Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, People's Republic of China
| | - John Marshall
- Department of Biostatistics and Epidemiology, School of Public Health, University of California, Berkeley, CA, USA
| | - Jiahai Lu
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, People's Republic of China
| | - Zhicong Yang
- Department of Infectious Diseases, Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, People's Republic of China
| | - Qinlong Jing
- Department of Infectious Diseases, Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, People's Republic of China.
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20
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Liu X, Zhang M, Cheng Q, Zhang Y, Ye G, Huang X, Zhao Z, Rui J, Hu Q, Frutos R, Chen T, Song T, Kang M. Dengue fever transmission between a construction site and its surrounding communities in China. Parasit Vectors 2021; 14:22. [PMID: 33407778 PMCID: PMC7787407 DOI: 10.1186/s13071-020-04463-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2020] [Accepted: 11/05/2020] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Due to an increase in mosquito habitats and the lack facilities to carry out basic mosquito control, construction sites in China are more likely to experience secondary dengue fever infection after importation of an initial infection, which may then increase the number of infections in the neighboring communities and the chance of community transmission. The aim of this study was to investigate how to effectively reduce the transmission of dengue fever at construction sites and the neighboring communities. METHODS The Susceptible-Exposed-Infectious/Asymptomatic-Recovered (SEIAR) model of human and SEI model of mosquitoes were developed to estimate the transmission of dengue virus between humans and mosquitoes within the construction site and within a neighboring community, as well between each of these. With the calibrated model, we further estimated the effectiveness of different intervention scenarios targeting at reducing the transmissibility at different locations (i.e. construction sites and community) with the total attack rate (TAR) and the duration of the outbreak (DO). RESULTS A total of 102 construction site-related and 131 community-related cases of dengue fever were reported in our area of study. Without intervention, the number of cases related to the construction site and the community rose to 156 (TAR: 31.25%) and 10,796 (TAR: 21.59%), respectively. When the transmission route from mosquitoes to humans in the community was cut off, the number of community cases decreased to a minimum of 33 compared with other simulated scenarios (TAR: 0.068%, DO: 60 days). If the transmission route from infectious mosquitoes in the community and that from the construction site to susceptible people on the site were cut off at the same time, the number of cases on the construction site dropped to a minimum of 74 (TAR: 14.88%, DO: 66 days). CONCLUSIONS To control the outbreak of dengue fever effectively on both the construction site and in the community, interventions needed to be made both within the community and from the community to the construction site. If interventions only took place within the construction site, the number of cases on the construction site would not be reduced. Also, interventions implemented only within the construction site or between the construction site and the community would not lead to a reduction in the number of cases in the community.
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Affiliation(s)
- Xingchun Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian People’s Republic of China
| | - Meng Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong People’s Republic of China
| | - Qu Cheng
- Division of Environmental Health Sciences School of Public Health, University of California, Berkeley, CA 94720 USA
| | - Yingtao Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong People’s Republic of China
| | - Guoqiang Ye
- Zhanjiang Municipal Center for Disease Control and Prevention, Zhanjiang, Guangdong People’s Republic of China
| | - Xiqing Huang
- Zhanjiang Municipal Center for Disease Control and Prevention, Zhanjiang, Guangdong People’s Republic of China
| | - Zeyu Zhao
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian People’s Republic of China
| | - Jia Rui
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian People’s Republic of China
| | - Qingqing Hu
- Division of Public Health, School of Medicine, University of Utah, 201 Presidents Circle, Salt Lake City, UT 84112 USA
| | | | - Tianmu Chen
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian People’s Republic of China
| | - Tie Song
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong People’s Republic of China
| | - Min Kang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong People’s Republic of China
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Huang M, Hu L. Modeling the suppression dynamics of Aedes mosquitoes with mating inhomogeneity. JOURNAL OF BIOLOGICAL DYNAMICS 2020; 14:656-678. [PMID: 32748704 DOI: 10.1080/17513758.2020.1799083] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Accepted: 07/13/2020] [Indexed: 06/11/2023]
Abstract
A novel strategy for controlling mosquito-borne diseases, such as dengue, malaria and Zika, involves releases of Wolbachia-infected mosquitoes as Wolbachia cause early embryo death when an infected male mates with an uninfected female. In this work, we introduce a delay differential equation model with mating inhomogeneity to discuss mosquito population suppression based on Wolbachia. Our analyses show that the wild mosquitoes could be eliminated if either the adult mortality rate exceeds the threshold [Formula: see text] or the release amount exceeds the threshold [Formula: see text] uniformly. We also present the nonlinear dependence of [Formula: see text] and [Formula: see text] on the parameters, respectively, as well as the effect of pesticide spraying on wild mosquitoes. Our simulations suggest that the releasing should be started at least 5 weeks before the peak dengue season, taking into account both the release amount and the suppression speed.
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Affiliation(s)
- Mugen Huang
- School of Statistics and Mathematics, Big Data and Educational Statistics Application Lab, Guangdong University of Finance and Economics, Guangzhou, People's Republic of China
| | - Linchao Hu
- Center for Applied Mathematics, College of Mathematics and Information Sciences, Guangzhou University, Guangzhou, People's Republic of China
- School of mathematics and statistics, Qiannan Normal University for Nationalities, Douyun, People's Republic of China
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22
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Thongsripong P, Qu Z, Yukich JO, Hyman JM, Wesson DM. An Investigation of Human-Mosquito Contact Using Surveys and Its Application in Assessing Dengue Viral Transmission Risk. JOURNAL OF MEDICAL ENTOMOLOGY 2020; 57:1942-1954. [PMID: 32652036 DOI: 10.1093/jme/tjaa134] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Indexed: 06/11/2023]
Abstract
Aedes-borne viral diseases such as dengue fever are surging in incidence in recent years. To investigate viral transmission risks, the availability of local transmission parameters is essential. One of the most important factors directly determining infection risk is human-mosquito contact. Yet the contact rate is not often characterized, compared with other risk metrics such as vector density, because of the limited research tool options. In this study, human-mosquito contact was assessed in two study sites in the Southern United States using self-administered standardized survey instruments. The fraction of mosquito bites attributed to important vector species was estimated by human landing sampling. The survey participants reported a significantly higher outdoor mosquito bite exposure than indoor. The reported bite number was positively correlated with outdoor time during at-risk periods. There was also a significant effect of the study site on outdoor bite exposure, possibly due to the differing vector density. Thus, the levels of human-mosquito contact in this study were influenced both by the mosquito density and human behaviors. A dengue virus transmission model demonstrated that the observed difference in the contact rates results in differential virus transmission risks. Our findings highlight the practicality of using surveys to investigate human-mosquito contact in a setting where bite exposure levels differ substantially, and serve as a basis for further evaluations. This study underscores a new avenue that can be used in combination with other field methods to understand how changes in human behavior may influence mosquito bite exposure which drives mosquito-borne virus transmission.
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Affiliation(s)
| | - Zhuolin Qu
- Department of Mathematics, Tulane University, New Orleans, LA
| | - Joshua O Yukich
- Department of Tropical Medicine, Tulane University, New Orleans, LA
| | - James M Hyman
- Department of Mathematics, Tulane University, New Orleans, LA
| | - Dawn M Wesson
- Department of Tropical Medicine, Tulane University, New Orleans, LA
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Global Research Output and Theme Trends on Climate Change and Infectious Diseases: A Restrospective Bibliometric and Co-Word Biclustering Investigation of Papers Indexed in PubMed (1999-2018). INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17145228. [PMID: 32698499 PMCID: PMC7400491 DOI: 10.3390/ijerph17145228] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 07/14/2020] [Accepted: 07/14/2020] [Indexed: 12/15/2022]
Abstract
Climate change is a challenge for the sustainable development of an international economy and society. The impact of climate change on infectious diseases has been regarded as one of the most urgent research topics. In this paper, an analysis of the bibliometrics, co-word biclustering, and strategic diagram was performed to evaluate global scientific production, hotspots, and developing trends regarding climate change and infectious diseases, based on the data of two decades (1999–2008 and 2009–2018) from PubMed. According to the search strategy and inclusion criteria, a total of 1443 publications were found on the topic of climate change and infectious diseases. There has been increasing research productivity in this field, which has been supported by a wide range of subject categories. The top highly-frequent major MeSH (medical subject headings)/subheading combination terms could be divided into four clusters for the first decade and five for the second decade using a biclustering analysis. At present, some significant public health challenges (global health, and travel and tropical climate, etc.) are at the center of the whole target research network. In the last ten years, “Statistical model”, “Diarrhea”, “Dengue”, “Ecosystem and biodiversity”, and “Zoonoses” have been considered as emerging hotspots, but they still need more attention for further development.
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Sweileh WM. Bibliometric analysis of peer-reviewed literature on climate change and human health with an emphasis on infectious diseases. Global Health 2020; 16:44. [PMID: 32384901 PMCID: PMC7206222 DOI: 10.1186/s12992-020-00576-1] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Accepted: 05/01/2020] [Indexed: 12/12/2022] Open
Abstract
Background Assessing research activity is important for planning future protective and adaptive policies. The objective of the current study was to assess research activity on climate change and health with an emphasis on infectious diseases. Method A bibliometric method was applied using SciVerse Scopus. Documents on climate change and human health were called “health-related literature” while documents on climate change and infectious diseases were called “infection-related literature”. The study period was from 1980 to 2019. Results The search query found 4247 documents in the health-related literature and 1207 in the infection-related literature. The growth of publications showed a steep increase after 2007. There were four research themes in the health-related literature: (1) climate change and infectious diseases; (2) climate change, public health and food security; (3) heat waves, mortality, and non-communicable diseases; and (4) climate change, air pollution, allergy, and respiratory health. The most frequently encountered pathogens/infectious diseases in the infection-related literature were malaria and dengue. Documents in infection-related literature had a higher h-index than documents in the health-related literature. The top-cited documents in the health-related literature focused on food security, public health, and infectious diseases while those in infection-related literature focused on water-, vector-, and mosquito-borne diseases. The European region had the highest contribution in health-related literature (n = 1626; 38.3%) and infection-related literature (n = 497; 41.2%). The USA led with 1235 (29.1%) documents in health-related literature and 365 (30.2%) documents in infection-related literature. The Australian National University ranked first in the health-related literature while the London School of Hygiene & Tropical Medicine ranked first in the infection-related literature. International research collaboration was inadequate. Documents published in the Environmental Health Perspectives journal received the highest citations per document. A total of 1416 (33.3%) documents in the health-related literature were funded while 419 (34.7%) documents in the infection-related literature were funded. Conclusion Research on climate change and human health is on the rise with research on infection-related issues making a good share. International research collaboration should be funded and supported. Future research needs to focus on the impact of climate change on psychosocial, mental, innovations, policies, and preparedness of health systems.
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Affiliation(s)
- Waleed M Sweileh
- Department of Physiology, Pharmacology/Toxicology, Division of Biomedical Sciences, College of Medicine and Health Sciences, An-Najah National University, Nablus, Palestine.
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Abstract
Dengue infection in China has increased dramatically in recent years. Guangdong province (main city Guangzhou) accounted for more than 94% of all dengue cases in the 2014 outbreak. Currently, there is no existing effective vaccine and most efforts of control are focused on the vector itself. This study aimed to evaluate different dengue management strategies in a region where this disease is emerging. This work was done by establishing a dengue simulation model for Guangzhou to enable the testing of control strategies aimed at vector control and vaccination. For that purpose, the computer-based dengue simulation model (DENSiM) together with the Container-Inhabiting Mosquito Simulation Model (CIMSiM) has been used to create a working dengue simulation model for the city of Guangzhou. In order to achieve the best model fit against historical surveillance data, virus introduction scenarios were run and then matched against the actual dengue surveillance data. The simulation model was able to predict retrospective outbreaks with a sensitivity of 0.18 and a specificity of 0.98. This new parameterisation can now be used to evaluate the potential impact of different control strategies on dengue transmission in Guangzhou. The knowledge generated from this research would provide useful information for authorities regarding the historic patterns of dengue outbreaks, as well as the effectiveness of different disease management strategies.
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The driver of dengue fever incidence in two high-risk areas of China: A comparative study. Sci Rep 2019; 9:19510. [PMID: 31862993 PMCID: PMC6925307 DOI: 10.1038/s41598-019-56112-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Accepted: 12/06/2019] [Indexed: 11/24/2022] Open
Abstract
In China, the knowledge of the underlying causes of heterogeneous distribution pattern of dengue fever in different high-risk areas is limited. A comparative study will help us understand the influencing factors of dengue in different high-risk areas. In the study, we compared the effects of climate, mosquito density and imported cases on dengue fever in two high-risk areas using Generalized Additive Model (GAM), random forests and Structural Equation Model (SEM). GAM analysis identified a similar positive correlation between imported cases, density of Aedes larvae, climate variables and dengue fever occurrence in the studied high-risk areas of both Guangdong and Yunnan provinces. Random forests showed that the most important factors affecting dengue fever occurrence were the number of imported cases, BI and the monthly average minimum temperature in Guangdong province; whereas the imported cases, the monthly average temperature and monthly relative humidity in Yunnan province. We found the rainfall had the indirect effect on dengue fever occurrence in both areas mediated by mosquito density; while the direct effect in high-risk areas of Guangdong was dominated by temperature and no obvious effect in Yunnan province by SEM. In total, climate factors and mosquito density are the key drivers on dengue fever incidence in different high-risk areas of China. These findings could provide scientific evidence for early warning and the scientific control of dengue fever in high-risk areas.
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Analysis and Nonstandard Numerical Design of a Discrete Three-Dimensional Hepatitis B Epidemic Model. MATHEMATICS 2019. [DOI: 10.3390/math7121157] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
In this work, we numerically investigate a three-dimensional nonlinear reaction-diffusion susceptible-infected-recovered hepatitis B epidemic model. To that end, the stability and bifurcation analyses of the mathematical model are rigorously discussed using the Routh–Hurwitz condition. Numerically, an efficient structure-preserving nonstandard finite-difference time-splitting method is proposed to approximate the solutions of the hepatitis B model. The dynamical consistency of the splitting method is verified mathematically and graphically. Moreover, we perform a mathematical study of the stability of the proposed scheme. The properties of consistency, stability and convergence of our technique are thoroughly analyzed in this work. Some comparisons are provided against existing standard techniques in order to validate the efficacy of our scheme. Our computational results show a superior performance of the present approach when compared against existing methods available in the literature.
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Zhang Z, Jing Q, Chen Z, Li T, Jiang L, Li Y, Luo L, Marshall J, Yang Z. The increasing menace of dengue in Guangzhou, 2001-2016: the most important epicenter in mainland China. BMC Infect Dis 2019; 19:1002. [PMID: 31775646 PMCID: PMC6880554 DOI: 10.1186/s12879-019-4504-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Accepted: 09/24/2019] [Indexed: 11/15/2022] Open
Abstract
Background Dengue is the most prevalent mosquito-borne disease in the world, with China affected seriously in recent years. 65.8% of dengue cases identified in mainland China since 2005 were reported from the city of Guangzhou. Methods In this study, we described the incidence rate and distribution of dengue cases using data collected form National Notifiable Infectious Disease Reporting Information System data in Guangzhou for 2001 to 2016. All dengue cases were investigated using standardized questionnaire. Results A total of 42,469 dengue cases were reported, with an average annual incidence rate of 20.99 per 100,000 resident population. Over this time period, the incidence rate of indigenous cases increased. Dengue affected areas also expanded sharply geographically from 58.1% of communities affected during 2001–2005 to 96.4% of communities affected in 2011–2016. Overall 95.30% of the overseas imported cases were reported during March and December, while 99.79% of indigenous cases were reported during July and November. All four dengue virus serotypes were identified both in imported cases and indigenous cases. The Aedes albopictus mosquito was the only vector for dengue transmission in the area. Conclusions Guangzhou has become the dengue epicenter in mainland China. Control strategies for dengue should be adjusted to the epidemiological characteristics above and intensive study need to be conducted to explore the factors that driving the rapid increase of dengue.
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Affiliation(s)
- Zhoubin Zhang
- Guangzhou Center for Disease Control and Prevention, Guangzhou, 510440, People's Republic of China
| | - Qinlong Jing
- Guangzhou Center for Disease Control and Prevention, Guangzhou, 510440, People's Republic of China
| | - Zongqiu Chen
- Guangzhou Center for Disease Control and Prevention, Guangzhou, 510440, People's Republic of China
| | - Tiegang Li
- Guangzhou Center for Disease Control and Prevention, Guangzhou, 510440, People's Republic of China
| | - Liyun Jiang
- Guangzhou Center for Disease Control and Prevention, Guangzhou, 510440, People's Republic of China
| | - Yilan Li
- Guangzhou Center for Disease Control and Prevention, Guangzhou, 510440, People's Republic of China
| | - Lei Luo
- Guangzhou Center for Disease Control and Prevention, Guangzhou, 510440, People's Republic of China
| | | | - Zhicong Yang
- Guangzhou Center for Disease Control and Prevention, Guangzhou, 510440, People's Republic of China.
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Yi B, Chen Y, Ma X, Rui J, Cui JA, Wang H, Li J, Chan SF, Wang R, Ding K, Xie L, Zhang D, Jiao S, Lao X, Chiang YC, Su Y, Zhao B, Xu G, Chen T. Incidence dynamics and investigation of key interventions in a dengue outbreak in Ningbo City, China. PLoS Negl Trop Dis 2019; 13:e0007659. [PMID: 31415559 PMCID: PMC6711548 DOI: 10.1371/journal.pntd.0007659] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2019] [Revised: 08/27/2019] [Accepted: 07/24/2019] [Indexed: 11/19/2022] Open
Abstract
Background The reported incidence of dengue fever increased dramatically in recent years in China. This study aimed to investigate and to assess the effectiveness of intervention implemented in a dengue outbreak in Ningbo City, Zhejiang Province, China. Methods Data of a dengue outbreak were collected in Ningbo City in China by a field epidemiological survey according to a strict protocol and case definition. Serum specimens of all cases were collected for diagnosis and the virological characteristics were detected by using polymerase chain reaction (PCR) and gene sequencing. Vector surveillance was implemented during the outbreak to collect the larva and adult mosquito densities to calculate the Breteau Index (BI) and human biting rate (HBR), respectively. Data of monthly BI and light-trap density in 2018 were built to calculate the seasonality of the vector. A transmission mathematical model was developed to dynamic the incidence of the disease. The parameters of the model were estimated by the data of the outbreak and vector surveillance data in 2018. The effectiveness of the interventions implemented during the outbreak was assessed by the data and the modelling. Results From 11 August to 8 September, 2018, a dengue outbreak was reported with 27 confirmed cases in a population of 5536-people community (community A) of Ningbo City. Whole E gene sequences were obtained from 24 cases and were confirmed as dengue virus type 1 (DENV-1). The transmission source of the outbreak was origin from community B where a dengue case having the same E gene sequence was onset on 30 July. Aedes albopictus was the only vector species in the area. The value of BI and HBR was 57.5 and 12 per person per hour respectively on 18 August, 2018 and decreased dramatically after interventions. The transmission model fitted well (χ2 = 6.324, P = 0.388) with the reported cases data. With no intervention, the total simulated number of the cases would be 1728 with a total attack rate (TAR) of 31.21% (95%CI: 29.99%– 32.43%). Case isolation and larva control (LC) have almost the same TAR and duration of outbreak (DO) as no intervention. Different levels of reducing HBR (rHBR) had different effectiveness with TARs ranging from 1.05% to 31.21% and DOs ranging from 27 days to 102 days. Adult vector control (AVC) had a very low TAR and DO. “LC+AVC” had a similar TAR and DO as that of AVC. “rHBR100%+LC”, “rHBR100%+AVC”, “rHBR100%+LC+AVC” and “rHBR100%+LC+AVC+Iso” had the same effectiveness. Conclusions Without intervention, DENV-1 could be transmitted rapidly within a short period of time and leads to high attack rate in community in China. AVC or rHBR should be recommended as primary interventions to control rapid transmission of the dengue virus at the early stage of an outbreak. Dengue has led to heavy disease burden in China. The reported incidence of the disease increased dramatically in recent years and cases have expanded from southern to central and northern part of China. In this study, the findings include that DENV-1 can transmit rapidly with a short period of time and leads to high attack rate in community, and that rHBR or AVC should be recommended as primary interventions to control rapid transmission of dengue virus at the early stage of an outbreak. Therefore, dengue outbreak is at high risk in many areas in China because of the potential high receptivity (widely distribution of Ae. albopictus) and vulnerability (high frequency of the importation) of the transmission. The high transmissibility of the virus makes it hard and urgent to control the outbreak. Delayed intervention (larvae control or case isolation) is hard to show its effectiveness and the interventions without delay are strongly recommended. Bed net or mosquito repellents were encouraged to use in the community to reduce HBR, and space spraying of insecticides were recommended to control adult vector during the outbreak.
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Affiliation(s)
- Bo Yi
- Ningbo Municipal Center for Disease Control and Prevention, Ningbo City, Zhejiang Province, People’s Republic of China
| | - Yi Chen
- Ningbo Municipal Center for Disease Control and Prevention, Ningbo City, Zhejiang Province, People’s Republic of China
| | - Xiao Ma
- Ningbo Municipal Center for Disease Control and Prevention, Ningbo City, Zhejiang Province, People’s Republic of China
| | - Jia Rui
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People’s Republic of China
| | - Jing-An Cui
- School of Science, Beijing University of Civil Engineering and Architecture, Beijing, People's Republic of China
| | - Haibin Wang
- Haishu District Center for Disease Control and Prevention, Ningbo City, Zhejiang Province, People’s Republic of China
| | - Jia Li
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People’s Republic of China
| | - Soi-Fan Chan
- Center for Disease Control and Prevention, Health Bureau, Macao SAR, People’s Republic of China
| | - Rong Wang
- Ningbo Municipal Center for Disease Control and Prevention, Ningbo City, Zhejiang Province, People’s Republic of China
| | - Keqin Ding
- Ningbo Municipal Center for Disease Control and Prevention, Ningbo City, Zhejiang Province, People’s Republic of China
| | - Lei Xie
- Ningbo Municipal Center for Disease Control and Prevention, Ningbo City, Zhejiang Province, People’s Republic of China
| | - Dongliang Zhang
- Ningbo Municipal Center for Disease Control and Prevention, Ningbo City, Zhejiang Province, People’s Republic of China
| | - Shuli Jiao
- Ningbo Municipal Center for Disease Control and Prevention, Ningbo City, Zhejiang Province, People’s Republic of China
| | - Xuying Lao
- Ningbo Municipal Center for Disease Control and Prevention, Ningbo City, Zhejiang Province, People’s Republic of China
| | - Yi-Chen Chiang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People’s Republic of China
| | - Yanhua Su
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People’s Republic of China
| | - Benhua Zhao
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People’s Republic of China
| | - Guozhang Xu
- Ningbo Municipal Center for Disease Control and Prevention, Ningbo City, Zhejiang Province, People’s Republic of China
| | - Tianmu Chen
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People’s Republic of China
- * E-mail:
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Wu H, Wu C, Lu Q, Ding Z, Xue M, Lin J. Evaluating the effects of control interventions and estimating the inapparent infections for dengue outbreak in Hangzhou, China. PLoS One 2019; 14:e0220391. [PMID: 31393899 PMCID: PMC6687121 DOI: 10.1371/journal.pone.0220391] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2019] [Accepted: 07/15/2019] [Indexed: 11/19/2022] Open
Abstract
Background The number of dengue fever (DF) cases and the number of dengue outbreaks have increased in recent years in Zhejiang Province, China. An unexpected dengue outbreak was reported in Hangzhou in 2017 and caused more than one thousand dengue cases. This study was undertaken to evaluate the effectiveness of the actual control measures, estimate the proportion of inapparent infections during this outbreak and simulate epidemic development based on different levels of control measures taking inapparent infections into consideration. Methods The epidemic data of dengue cases in Hangzhou, Zhejiang Province, in 2017 and the number of the people exposed to the outbreaks were obtained from the China Information Network System of Disease Prevention and Control. The epidemic without intervention measures was used to estimate the unknown parameters. A susceptible-exposed-infectious/inapparent-recovered (SEIAR) model was used to estimate the effectiveness of the control interventions. The inapparent infections were also evaluated at the same time. Results In total, 1137 indigenous dengue cases were reported in Hangzhou in 2017. The number of indigenous dengue cases was estimated by the SEIAR model. This number was predicted to reach 6090 by the end of November 2, 2017, if no control measures were implemented. The total number of reported cases was reduced by 81.33% in contrast to the estimated incidence without intervention. The number of average daily inapparent cases was 10.18 times higher than the number of symptomatic cases. The earlier and more rigorously the vector control interventions were implemented, the more effective they were. The results showed that implementing vector control continuously for more than twenty days was more effective than every few days of implementation. Case isolation is not sufficient enough for epidemic control and only reduced the incidence by 38.10% in contrast to the estimated incidence without intervention, even if case isolation began seven days after the onset of the first case. Conclusions The practical control interventions in the outbreaks that occurred in Hangzhou City were highly effective. The proportion of inapparent infections was large, and it played an important role in transmitting the disease during this epidemic. Early, continuous and high efficacy vector control interventions are necessary to limit the development of a dengue epidemic. Timely diagnosis and case reporting are important in the intervention at an early stage of the epidemic.
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Affiliation(s)
- Haocheng Wu
- Zhejiang Province Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, China
- Key Laboratory for Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Hangzhou, Zhejiang Province, China
| | - Chen Wu
- Zhejiang Province Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, China
| | - Qinbao Lu
- Zhejiang Province Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, China
| | - Zheyuan Ding
- Zhejiang Province Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, China
| | - Ming Xue
- Hangzhou Centre for Disease Control and Prevention, Hangzhou, Zhejiang, Province, China
| | - Junfen Lin
- Zhejiang Province Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, China
- Key Laboratory for Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Hangzhou, Zhejiang Province, China
- * E-mail:
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31
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Cheng D, Chen S, Huang Y, Pierce NE, Riegler M, Yang F, Zeng L, Lu Y, Liang G, Xu Y. Symbiotic microbiota may reflect host adaptation by resident to invasive ant species. PLoS Pathog 2019; 15:e1007942. [PMID: 31323076 PMCID: PMC6668852 DOI: 10.1371/journal.ppat.1007942] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Revised: 07/31/2019] [Accepted: 06/24/2019] [Indexed: 01/27/2023] Open
Abstract
Exotic invasive species can influence the behavior and ecology of native and resident species, but these changes are often overlooked. Here we hypothesize that the ghost ant, Tapinoma melanocephalum, living in areas that have been invaded by the red imported fire ant, Solenopsis invicta, displays behavioral differences to interspecific competition that are reflected in both its trophic position and symbiotic microbiota. We demonstrate that T. melanocephalum workers from S. invicta invaded areas are less aggressive towards workers of S. invicta than those inhabiting non-invaded areas. Nitrogen isotope analyses reveal that colonies of T. melanocephalum have protein-rich diets in S. invicta invaded areas compared with the carbohydrate-rich diets of colonies living in non-invaded areas. Analysis of microbiota isolated from gut tissue shows that T. melanocephalum workers from S. invicta invaded areas also have different bacterial communities, including a higher abundance of Wolbachia that may play a role in vitamin B provisioning. In contrast, the microbiota of workers of T. melanocephalum from S. invicta-free areas are dominated by bacteria from the orders Bacillales, Lactobacillales and Enterobacteriales that may be involved in sugar metabolism. We further demonstrate experimentally that the composition and structure of the bacterial symbiont communities as well as the prevalence of vitamin B in T. melanocephalum workers from S. invicta invaded and non-invaded areas can be altered if T. melanocephalum workers are supplied with either protein-rich or carbohydrate-rich food. Our results support the hypothesis that bacterial symbiont communities can help hosts by buffering behavioral changes caused by interspecies competition as a consequence of biological invasions. Insects display a wide range of dependence on symbiotic bacteria for basic functions. Responses by resident species to selective pressures imposed by invasive species, as well as specific underlying mechanisms that give rise to these responses are still poorly understood. Here we investigate the role of the symbiotic bacteria of the ghost ant, Tapinoma melanocephalum, to changes in host behavior associated with interspecies competition in areas invaded by fire ants, Solenopsis invicta. We show that Wolbachia is significantly enriched in workers of T. melanocephalum from S. invicta infested areas, and that these bacteria also increase in abundance in colonies that have been supplied with protein-rich food. Our results suggest that bacterial symbiont communities can play an important role in enabling ants to tolerate changes in behavior and diet as a result of biological invasions.
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Affiliation(s)
- Daifeng Cheng
- Department of Entomology, South China Agricultural University, Guangzhou, China
| | - Siqi Chen
- Department of Entomology, South China Agricultural University, Guangzhou, China
| | - Yuquan Huang
- Department of Entomology, South China Agricultural University, Guangzhou, China
| | - Naomi E. Pierce
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge MA, United States of America
| | - Markus Riegler
- Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, Australia
| | - Fan Yang
- Department of Entomology, South China Agricultural University, Guangzhou, China
| | - Ling Zeng
- Department of Entomology, South China Agricultural University, Guangzhou, China
| | - Yongyue Lu
- Department of Entomology, South China Agricultural University, Guangzhou, China
| | - Guangwen Liang
- Department of Entomology, South China Agricultural University, Guangzhou, China
| | - Yijuan Xu
- Department of Entomology, South China Agricultural University, Guangzhou, China
- * E-mail:
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Jing Q, Li Y, Liu J, Jiang L, Chen Z, Su W, Birkhead GS, Lu J, Yang Z. Dengue Underestimation in Guangzhou, China: Evidence of Seroprevalence in Communities With No Reported Cases Before a Large Outbreak in 2014. Open Forum Infect Dis 2019; 6:ofz256. [PMID: 31304186 PMCID: PMC6612883 DOI: 10.1093/ofid/ofz256] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2018] [Accepted: 06/01/2019] [Indexed: 12/28/2022] Open
Abstract
Objective Dengue has become a serious public health problem in southern China particularly with a record-breaking outbreak in 2014. Serological evidence from areas with no known dengue cases reported prior to 2014 could provide information on possible unrecognized circulation of dengue virus (DENV) before this outbreak. Method Between March and May 2015, we performed a cross-sectional serosurvey using a stratified random sampling method among individuals aged 1-84 years-old in 7 communities in Guangzhou with no reported dengue cases before 2014. Sera of subjects were initially screened with the indirect DENV IgG enzyme-linked immunosorbent assay, and positive samples were further tested by the indirect immunofluorescence assay to identify specific serotypes. Results A total of 850 subjects had complete information available. The overall seroprevalence against DENV was 6.59% (56 of 850; 95% CI, 4.92%-8.26%). The seroprevalence increased with age in general (3.86%, 4.58%, 8.72%, 7.22%, and 10.69% among participants in ≤14, 15-29, 30-44, 45-59 and ≥60 years age group, respectively). Living in rural or peri-urban communities and longer years of residence therein were risk factors for higher seroprevalence, whereas wearing long sleeves and pants when outdoors was associated with lower seroprevalence. Of the total subjects, 55.36% (31 of 56) sera were successfully identified with specific serotypes, with 12.90% (4 of 31) being coinfected with 2 serotypes. Conclusions Dengue transmission in the study communities had occurred prior to the 2014 massive outbreak, possibly for many years, but went undiagnosed and unreported. A proportion of the study population experienced secondary infection as different serotypes of DENV increased the risk for severe diseases. Active surveillance and education of both healthcare providers and the general population should be conducted in areas at risk for dengue emergence in order to better reduce disease burden.
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Affiliation(s)
- Qinlong Jing
- Department of Infectious Diseases, Guangzhou Center for Disease Control and Prevention, People's Republic of China
| | - Yilan Li
- Department of Infectious Diseases, Guangzhou Center for Disease Control and Prevention, People's Republic of China
| | - Jianhua Liu
- Department of Infectious Diseases, Guangzhou Center for Disease Control and Prevention, People's Republic of China
| | - Liyun Jiang
- Department of Infectious Diseases, Guangzhou Center for Disease Control and Prevention, People's Republic of China
| | - Zongqiu Chen
- Department of Infectious Diseases, Guangzhou Center for Disease Control and Prevention, People's Republic of China
| | - Wenzhe Su
- Department of Infectious Diseases, Guangzhou Center for Disease Control and Prevention, People's Republic of China
| | - Guthrie S Birkhead
- Department of Epidemiology and Biostatistics, School of Public Health, University at Albany, State University of New York, US
| | - Jiahai Lu
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, People's Republic of China
| | - Zhicong Yang
- Department of Infectious Diseases, Guangzhou Center for Disease Control and Prevention, People's Republic of China
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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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Ren H, Wu W, Li T, Yang Z. Urban villages as transfer stations for dengue fever epidemic: A case study in the Guangzhou, China. PLoS Negl Trop Dis 2019; 13:e0007350. [PMID: 31022198 PMCID: PMC6504109 DOI: 10.1371/journal.pntd.0007350] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Revised: 05/07/2019] [Accepted: 03/30/2019] [Indexed: 12/21/2022] Open
Abstract
Background Numerous urban villages (UVs) and frequent infectious disease outbreaks are major environmental and public health concerns in highly urbanized regions, especially in developing countries. However, the spatial and quantitative associations between UVs and infections remain little understood on a fine scale. Methodology and principal findings In this study, the relationships between reported dengue fever (DF) epidemics during 2012–2017, gross domestic product (GDP), the traffic system (road density, bus and/or subway stations), and UVs derived from high-resolution remotely sensed imagery in the central area of Guangzhou, were explored using geographically weighted regression (GWR) models based on a 1 km × 1 km grid scale. Accounting for 16.53%–18.07% of residential area and 16.84%–18.02% of population, UVs possessed 28.55%–38.24% of total reported DF cases in the core area of Guangzhou. The density of DF cases and the DF incidence rates in UVs were 1.81–3.13 and 1.82–3.06 times of that of normal construction land. Approximately 90% of the total cases were concentrated in the UVs and their buffering zones of radius ranged from 0 to 500 m. Significantly positive associations were observed between gridded DF incidence rates and UV area (r = 0.33, P = 0.000), the number of bus stops (r = 0.49, P = 0.000) and subway stations (r = 0.27, P = 0.000), and road density (r = 0.39, P = 0.000). About 60% of spatial variations in the gridded DF incidence rates were interpreted by the different variables of GDP, UVs, and bus stops integrated in GWR models. Conclusions UVs likely acted as special transfer stations, receiving and/or exporting DF cases during epidemics. This work increases our understanding of the influences of UVs on vector-borne diseases in highly urbanized areas, supplying valuable clues to local authorities making targeted interventions for the prevention and control of DF epidemics. Due to the rapid urbanization of China, many villages in the urban fringe are enveloped by ever-expanding cities and become so-called urban villages (UVs). UVs are widely distributed in not only the Guangzhou core areas but also the other cities in the highly urbanized region of China (e.g., Shenzhen, Wuhan). UVs are commonly featured by poor sanitation, overcrowding population, absent infrastructure, and some environmental pollution due to the development is neither authorized nor planned, resulting in a high environmental suitability for some vectors (e.g., Aedes albopictus), as well as the vetor-borne diseases (i.e., dengue fever) in these regions. In this study, we demonstrated that UVs may serve as transfer stations for the transmission of DF epidemic in the regions with developed transportation, higher GDP and dense population. This is manifested as that the rates of DF incidences were significantly positively associated with UV area. Furthermore, the density of DF cases and the DF incidence rates in UVs were 1.81–3.13 and 1.82–3.06 times of that of normal construction land and about 90% of the total DF cases were concentrated in 500m radius of UVs’ buffers. And the aggregation effects of UVs on this epidemic in the central region were obviously affected by public traffic conditions at the grid level. This study is the first quantitative analysis of the spatial relationship between UVs, public transportation, road density, population density, GDP and DF epidemics, which will provide a useful reference for accurately preventing and controlling DF epidemic in urban regions with numerous UVs.
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Affiliation(s)
- Hongyan Ren
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- * E-mail: (HR); (ZY)
| | - Wei Wu
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- College of Geographical Science, Fujian Normal University, Fuzhou, China
| | - Tiegang Li
- Department of Infectious Diseases, Guangzhou Center for Disease Control and Prevention, Guangzhou, People’s Republic of China
| | - Zhicong Yang
- Department of Infectious Diseases, Guangzhou Center for Disease Control and Prevention, Guangzhou, People’s Republic of China
- * E-mail: (HR); (ZY)
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Oidtman RJ, Lai S, Huang Z, Yang J, Siraj AS, Reiner RC, Tatem AJ, Perkins TA, Yu H. Inter-annual variation in seasonal dengue epidemics driven by multiple interacting factors in Guangzhou, China. Nat Commun 2019; 10:1148. [PMID: 30850598 PMCID: PMC6408462 DOI: 10.1038/s41467-019-09035-x] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2018] [Accepted: 02/12/2019] [Indexed: 02/07/2023] Open
Abstract
Vector-borne diseases display wide inter-annual variation in seasonal epidemic size due to their complex dependence on temporally variable environmental conditions and other factors. In 2014, Guangzhou, China experienced its worst dengue epidemic on record, with incidence exceeding the historical average by two orders of magnitude. To disentangle contributions from multiple factors to inter-annual variation in epidemic size, we fitted a semi-mechanistic model to time series data from 2005-2015 and performed a series of factorial simulation experiments in which seasonal epidemics were simulated under all combinations of year-specific patterns of four time-varying factors: imported cases, mosquito density, temperature, and residual variation in local conditions not explicitly represented in the model. Our results indicate that while epidemics in most years were limited by unfavorable conditions with respect to one or more factors, the epidemic in 2014 was made possible by the combination of favorable conditions for all factors considered in our analysis.
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Affiliation(s)
- Rachel J Oidtman
- Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, 46556, IN, USA
| | - Shengjie Lai
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, 200032, China
- WorldPop, Department of Geography and Environment, University of Southampton, Southampton, SO17 1BJ, UK
- Flowminder Foundation, Stockholm, SE-11355, Sweden
| | - Zhoujie Huang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, 200032, China
| | - Juan Yang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, 200032, China
| | - Amir S Siraj
- Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, 46556, IN, USA
| | - Robert C Reiner
- Institute for Health and Metrics and Evaluation, University of Washington, Seattle, 98195, WA, USA
| | - Andrew J Tatem
- WorldPop, Department of Geography and Environment, University of Southampton, Southampton, SO17 1BJ, UK
- Flowminder Foundation, Stockholm, SE-11355, Sweden
| | - T Alex Perkins
- Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, 46556, IN, USA.
| | - Hongjie Yu
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, 200032, China.
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Zhu G, Liu T, Xiao J, Zhang B, Song T, Zhang Y, Lin L, Peng Z, Deng A, Ma W, Hao Y. Effects of human mobility, temperature and mosquito control on the spatiotemporal transmission of dengue. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 651:969-978. [PMID: 30360290 DOI: 10.1016/j.scitotenv.2018.09.182] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Revised: 09/14/2018] [Accepted: 09/14/2018] [Indexed: 05/06/2023]
Abstract
Dengue transmission exhibits evident geographic variations and seasonal differences. Such heterogeneity is caused by various impact factors, in which temperature and host/vector behaviors could drive its spatiotemporal transmission, but mosquito control could stop its progression. These factors together contribute to the observed distributions of dengue incidence from surveillance systems. To effectively and efficiently monitor and response to dengue outbreak, it would be necessary to systematically model these factors and their impacts on dengue transmission. This paper introduces a new modeling framework with consideration of multi-scale factors and surveillance data to clarify the hidden dynamics accounting for dengue spatiotemporal transmission. The model is based on compartmental system which takes into account the biting-based interactions among humans, viruses and mosquitoes, as well as the essential impacts of human mobility, temperature and mosquito control. This framework was validated with real epidemic data by applying retrospectively to the 2014 dengue epidemic in the Pearl River Delta (PRD) in southern China. The results indicated that suitable condition of temperature could be responsible for the explosive dengue outbreak in the PRD, and human mobility could be the causal factor leading to its spatial transmission across different cities. It was further found that mosquito intervention has significantly reduced dengue incidence, where a total of 52,770 (95% confidence interval [CI]: 29,231-76,308) dengue cases were prevented in the PRD in 2014. The findings can offer new insights for improving the predictability and risk assessment of dengue epidemics. The model also can be readily extended to investigate the transmission dynamics of other mosquito-borne diseases.
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Affiliation(s)
- Guanghu Zhu
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; Department of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin 541004, China; Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Tao Liu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Bing Zhang
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Tie Song
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Yonghui Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Lifeng Lin
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Zhiqiang Peng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Aiping Deng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Wenjun Ma
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China.
| | - Yuantao Hao
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
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Wolbachia spread dynamics in multi-regimes of environmental conditions. J Theor Biol 2019; 462:247-258. [DOI: 10.1016/j.jtbi.2018.11.009] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2018] [Revised: 10/25/2018] [Accepted: 11/13/2018] [Indexed: 12/18/2022]
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Wang X, Tang S, Wu J, Xiao Y, Cheke RA. A combination of climatic conditions determines major within-season dengue outbreaks in Guangdong Province, China. Parasit Vectors 2019; 12:45. [PMID: 30665469 PMCID: PMC6341621 DOI: 10.1186/s13071-019-3295-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2018] [Accepted: 01/07/2019] [Indexed: 11/16/2022] Open
Abstract
Background China’s Guangdong Province experienced a major dengue outbreak in 2014. Here we investigate if the weather conditions contributing to the outbreak can be elucidated by multi-scale models. Methods A multi-scale modelling framework, parameterized by available weather, vector and human case data, was used to examine the integrative effect of temperature and precipitation variation on the effective reproduction number (ERN) of dengue fever. Results With temperature in the range of 25–30 °C, increasing precipitation leads to an increase in the ERN with an average lag of 10 days. With monthly precipitation fixed, the more regular the pattern of rainfall (i.e. higher numbers of rainy days), the larger is the total number of adult mosquitoes. A rainfall distribution peaking in June and July produces a large ERN, beneficial to transmission. Climate conditions conducive to major outbreaks within a season are a combination of relatively high temperature, high precipitation peaking in June and July, and uninterrupted drizzle or regular rainfall. Conclusions Evaluating a set of weather conditions favourable to a future major dengue outbreak requires near-future prediction of temperature variation, total rainfall and its peaking times. Such information permits seasonal rapid response management decisions due to the lags between the precipitation events and the realisation of the ERN. Electronic supplementary material The online version of this article (10.1186/s13071-019-3295-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Xia Wang
- School of Mathematics and Information Science, Shaanxi Normal University, Xi'an, 710119, People's Republic of China
| | - Sanyi Tang
- School of Mathematics and Information Science, Shaanxi Normal University, Xi'an, 710119, People's Republic of China
| | - Jianhong Wu
- Centre for Disease Modelling, York Institute for Health Research, York University, Toronto, ON, M3J 1P3, Canada
| | - Yanni Xiao
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, People's Republic of China
| | - Robert A Cheke
- Natural Resources Institute, University of Greenwich at Medway, Central Avenue, Chatham Maritime, Kent, ME4 4TB, UK. .,Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Mary's campus), Imperial College London, Norfolk Place, London, W2 1PG, UK.
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GREENHALGH DAVID, LIANG YANFENG, NAZNI WASIAHMAD, TEOH GUATNEY, LEE HANLIM, MASSAD EDUARDO. MODELING THE EFFECT OF A NOVEL AUTO-DISSEMINATION TRAP ON THE SPREAD OF DENGUE IN HIGH-RISE CONDOMINIA, MALAYSIA. J BIOL SYST 2019. [DOI: 10.1142/s0218339018500250] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
In this paper, we use the classical Ross–Macdonald model to analyze the effect of the Mosquito Home System (MHS), which is an example of an auto-dissemination trap, in controlling the spread of dengue in Malaysia in a high-rise condominium environment. By using the national dengue data from Malaysia, we are able to estimate [Formula: see text] which represents the initial growth rate of the dengue epidemic and thus allows us to estimate the number of mosquitoes in Malaysia. The basic reproduction number [Formula: see text] is also obtained. We have constructed a mathematical expression which allows us to estimate the potential number of breeding sites for Aedes mosquitoes. Later on, by using the data available from the 11 months trials carried out in three blocks of flats in Selangor, we improved on our dengue model by including the effect of the MHS and thus modeling the impact it has on the spread of dengue within the flats. Numerical simulations and tables are also produced to illustrate our results.
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Affiliation(s)
- DAVID GREENHALGH
- Department of Mathematics and Statistics, University of Strathclyde, Glasgow G1 1XH, UK
| | - YANFENG LIANG
- Department of Mathematics and Statistics, University of Strathclyde, Glasgow G1 1XH, UK
| | - WASI AHMAD NAZNI
- Medical Entomology Unit, Institute for Medical Research, Jalan Pahang, 50588 Kuala Lumpur, Malaysia
| | - GUAT-NEY TEOH
- Medical Entomology Unit, Institute for Medical Research, Jalan Pahang, 50588 Kuala Lumpur, Malaysia
| | - HAN LIM LEE
- Vector-Borne Disease Control Branch, Disease Control Division, Ministry of Health, Putrajaya, Malaysia
| | - EDUARDO MASSAD
- School of Applied Mathematics, Fundacao Getulio Vargas, Rio de Janeiro, Brazil
- Department of Legal Informatics, School of Medicine, University of Sao Paulo and LIM 01/HCFMUSP, Av. Dr. Arnaldo 455, Sao Paulo, SP01246-903, Brazil
- London School of Hygiene and Tropical Medicine, London, UK
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Pasin C, Halloran ME, Gilbert PB, Langevin E, Ochiai RL, Pitisuttithum P, Capeding MR, Carrasquilla G, Frago C, Cortés M, Chambonneau L, Moodie Z. Periods of high dengue transmission defined by rainfall do not impact efficacy of dengue vaccine in regions of endemic disease. PLoS One 2018; 13:e0207878. [PMID: 30543657 PMCID: PMC6292612 DOI: 10.1371/journal.pone.0207878] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2018] [Accepted: 11/07/2018] [Indexed: 11/22/2022] Open
Abstract
OBJECTIVE To evaluate the association of rainy season with overall dengue disease incidence and with the efficacy of the Sanofi Pasteur recombinant, live, attenuated, tetravalent vaccine (CYD-TDV) in two randomized, controlled multicenter phase III clinical trials in Asia and Latin America. METHODS Rainy seasons were defined for each study site using climatological information from the World Meteorological Organization. The dengue attack rate in the placebo group for each study month was calculated as the number of symptomatic, virologically-confirmed dengue events in a given month divided by the number of participants at risk in the same month. Time-dependent Cox proportional hazard models were used to test whether rainy season was associated with dengue disease and whether it modified vaccine efficacy in each of the two trials and in both of the trials combined. FINDINGS Rainy season, country, and age were all significantly associated with dengue disease in both studies. Vaccine efficacy did not change during the rainy season in any of the analyses. CONCLUSIONS Although dengue transmission and exposure are expected to increase during the rainy season, our results indicate that CYD-TDV vaccine efficacy remains constant throughout the year in endemic regions.
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Affiliation(s)
- Chloé Pasin
- Université de Bordeaux, INSERM U1219 Bordeaux Population Health center, INRIA SISTM, Bordeaux, France
- Vaccine Research Institute, Creteil, France
- ENS Cachan, Université Paris-Saclay, Cachan, France
| | - M. Elizabeth Halloran
- Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
- University of Washington, Seattle, Washington, United States of America
| | - Peter B. Gilbert
- Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
- University of Washington, Seattle, Washington, United States of America
| | | | | | - Punnee Pitisuttithum
- Vaccine Trial Centre and Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Nakorn Pratum, Thailand
| | | | | | | | | | | | - Zoe Moodie
- Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
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León TM, Porco TC, Kim CS, Kaewkes S, Kaewkes W, Sripa B, Spear RC. Modeling liver fluke transmission in northeast Thailand: Impacts of development, hydrology, and control. Acta Trop 2018; 188:101-107. [PMID: 30149023 DOI: 10.1016/j.actatropica.2018.08.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2018] [Revised: 07/17/2018] [Accepted: 08/08/2018] [Indexed: 12/20/2022]
Abstract
Human infection with the Southeast Asian liver fluke Opisthorchis viverrini and liver fluke-associated cholangiocarcinoma cause significant disease burden in Southeast Asia. While there has been considerable work to understand liver fluke pathology and to reduce infection prevalence, there remains a limited understanding of the environmental determinants of parasite transmission dynamics to inform treatment and control programs. A particular setting where targeted control efforts have taken place is the Lawa Lake complex in northeast Thailand. Here, we describe the recent history of host infections, as well as the hydrologic characteristics of this floodplain ecosystem that influence the extent of snail habitat and fish mobility and the transport of human waste and parasite cercariae. Using mathematical modeling, we outline a framework for reconstructing environmental transmission of O. viverrini over the course of the Lawa Project control program from its inception in 2008 until 2016, using locally acquired but fragmentary longitudinal infection data for both humans and environmental hosts. The role of water flow in facilitating movement between snail, fish, human, and reservoir hosts is a particular focus with respect to its relevant scales and its impact on success of interventions. In this setting, we argue that an understanding of the key environmental drivers of disease transmission processes is central to the effectiveness of any environmental intervention.
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Affiliation(s)
- Tomás M León
- School of Public Health, University of California, Berkeley, USA; Tropical Disease Research Center, Khon Kaen University, Thailand.
| | | | - Christina S Kim
- Tropical Disease Research Center, Khon Kaen University, Thailand
| | | | - Wanlop Kaewkes
- Tropical Disease Research Center, Khon Kaen University, Thailand
| | - Banchob Sripa
- Tropical Disease Research Center, Khon Kaen University, Thailand
| | - Robert C Spear
- School of Public Health, University of California, Berkeley, USA
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42
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Zheng B, Yu J, Xi Z, Tang M. The annual abundance of dengue and Zika vector Aedes albopictus and its stubbornness to suppression. Ecol Modell 2018. [DOI: 10.1016/j.ecolmodel.2018.09.004] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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43
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Fang LQ, Sun Y, Zhao GP, Liu LJ, Jiang ZJ, Fan ZW, Wang JX, Ji Y, Ma MJ, Teng J, Zhu Y, Yu P, Li K, Tian YJ, Cao WC. Travel-related infections in mainland China, 2014-16: an active surveillance study. Lancet Public Health 2018; 3:e385-e394. [PMID: 30033200 PMCID: PMC7164813 DOI: 10.1016/s2468-2667(18)30127-0] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2018] [Revised: 06/14/2018] [Accepted: 06/18/2018] [Indexed: 11/17/2022]
Abstract
BACKGROUND Transmission of infection through international travel is a growing health issue, and the frequency of imported infection is increasing in China. We aimed to quantify the total number of infections imported into mainland China by arriving travellers. METHODS We actively surveyed arriving travellers at all 272 international entry-exit ports in mainland China. Suspected cases were detected through fever screening, medical inspection, self-declaration, and reporting by on-board staff. Participants completed a standardised questionnaire with questions about demographics, their travel itinerary (including detailed information about all countries or regions visited), and clinical manifestations. Nasopharyngeal swabs, sputum samples, faecal samples, vomitus, blood, and serum were collected as appropriate for diagnoses. Diagnosis was made by specific laboratory tests according to the national technical guidelines. Infections were classified as respiratory, gastrointestinal, vector-borne, blood-transmitted and sex-transmitted, or mucocutaneous. We divided arriving travellers into two groups: travellers coming from countries other than China, and travellers coming from Hong Kong, Macau, and Taiwan. We integrated surveillance data for 2014-16, calculated incidences of travel-related infections, and compared the frequency of infections among subgroups. FINDINGS Between Jan 1, 2014, and Dec 31, 2016, 22 797 cases were identified among 805 993 392 arriving travellers-an overall incidence of 28·3 per million. 45 pathogens were detected in participants: 18 respiratory (19 662 cases), ten gastrointestinal (189 cases), seven vector-borne (831 cases), seven blood-transmitted and sex-transmitted (1531 cases), and three mucocutaneous (584 cases). Both the overall number and incidence of infection were more than five times higher in 2016 than in 2014. Case numbers and incidences also varied substantially by province, autonomous region, and municipality. Overall, 17 643 (77%) infections were detected by fever screening, but 753 (49%) blood-transmitted and sex-transmitted infections were identified through medical inspection. 14 305 (73%) cases of respiratory infection and 96 (51%) of gastrointestinal infections were in tourists. Tuberculosis, hepatitis A virus, vector-borne, and blood-transmitted and sex-transmitted infections were common among Chinese labourers who worked abroad. Dengue and malaria were most commonly diagnosed in travellers arriving from Africa. 12 126 (93%) of the 12 985 cases arriving from Hong Kong, Macau, or Taiwan were respiratory infections. Hand, foot, and mouth disease accounted for 2·90% of infections in travellers from Hong Kong, Macau, or Taiwan and 0·31% of infections in international travellers. INTERPRETATION This report is the first to characterise the profile of travel-related infections among arriving travellers in mainland China. Our findings should increase public awareness of the potential risk of imported infections, and help health-care providers to make evidence-based health recommendations to travellers. FUNDING The Natural Science Foundation of China.
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Affiliation(s)
- Li-Qun Fang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China; Institute of EcoHealth, Shandong University, Jinan, China
| | - Yu Sun
- Institute of EcoHealth, Shandong University, Jinan, China; University of Chinese Academy of Sciences, Beijing, China
| | - Guo-Ping Zhao
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China; The Logistics University of the Chinese People's Armed Police Force, Tianjin, China
| | - Li-Juan Liu
- Institute of Health Quarantine, The Chinese Academy of Inspection and Quarantine, Beijing, China
| | - Zhe-Jun Jiang
- Institute of Health Services and Transfusion Medicine, Academy of Military Medical Science, Beijing, China
| | - Zheng-Wei Fan
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Jing-Xue Wang
- Institute of Health Services and Transfusion Medicine, Academy of Military Medical Science, Beijing, China
| | - Yang Ji
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Mai-Juan Ma
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China; Institute of EcoHealth, Shandong University, Jinan, China
| | - Juan Teng
- State Key Surveillance Laboratory of Vector-borne Infectious Diseases, Hainan Customs District, Haikou, China
| | - Yan Zhu
- International Travel Healthcare Center, Xining Customs District, Xining, China
| | - Ping Yu
- Xi'an Xian Yang Airport Customs House, Xian Yang, China
| | - Kai Li
- International Travel Healthcare Center, Ningxia Customs District, Yinchuan, China
| | - Ying-Jie Tian
- University of Chinese Academy of Sciences, Beijing, China
| | - Wu-Chun Cao
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China; Institute of EcoHealth, Shandong University, Jinan, China.
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Spatiotemporal responses of dengue fever transmission to the road network in an urban area. Acta Trop 2018; 183:8-13. [PMID: 29608873 DOI: 10.1016/j.actatropica.2018.03.026] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2017] [Revised: 03/27/2018] [Accepted: 03/29/2018] [Indexed: 12/19/2022]
Abstract
Urbanization is one of the important factors leading to the spread of dengue fever. Recently, some studies found that the road network as an urbanization factor affects the distribution and spread of dengue epidemic, but the study of relationship between the distribution of dengue epidemic and road network is limited, especially in highly urbanized areas. This study explores the temporal and spatial spread characteristics of dengue fever in the distribution of road network by observing a dengue epidemic in the southern Chinese cities. Geographic information technology is used to extract the spatial location of cases and explore the temporal and spatial changes of dengue epidemic and its spatial relationship with road network. The results showed that there was a significant "severe" period in the temporal change of dengue epidemic situation, and the cases were mainly concentrated in the vicinity of narrow roads, the spread of the epidemic mainly along the high-density road network area. These results show that high-density road network is an important factor to the direction and scale of dengue epidemic. This information may be helpful to the development of related epidemic prevention and control strategies.
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Kong L, Wang J, Li Z, Lai S, Liu Q, Wu H, Yang W. Modeling the Heterogeneity of Dengue Transmission in a City. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2018; 15:ijerph15061128. [PMID: 29857503 PMCID: PMC6025315 DOI: 10.3390/ijerph15061128] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/05/2018] [Revised: 05/02/2018] [Accepted: 05/19/2018] [Indexed: 12/14/2022]
Abstract
Dengue fever is one of the most important vector-borne diseases in the world, and modeling its transmission dynamics allows for determining the key influence factors and helps to perform interventions. The heterogeneity of mosquito bites of humans during the spread of dengue virus is an important factor that should be considered when modeling the dynamics. However, traditional models generally assumed homogeneous mixing between humans and vectors, which is inconsistent with reality. In this study, we proposed a compartmental model with negative binomial distribution transmission terms to model this heterogeneity at the population level. By including the aquatic stage of mosquitoes and incorporating the impacts of the environment and climate factors, an extended model was used to simulate the 2014 dengue outbreak in Guangzhou, China, and to simulate the spread of dengue in different scenarios. The results showed that a high level of heterogeneity can result in a small peak size in an outbreak. As the level of heterogeneity decreases, the transmission dynamics approximate the dynamics predicted by the corresponding homogeneous mixing model. The simulation results from different scenarios showed that performing interventions early and decreasing the carrying capacity for mosquitoes are necessary for preventing and controlling dengue epidemics. This study contributes to a better understanding of the impact of heterogeneity during the spread of dengue virus.
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Affiliation(s)
- Lingcai Kong
- Department of Mathematics and Physics, North China Electric Power University; Baoding 071003, China.
| | - Jinfeng Wang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences; Beijing 100864, China.
- Key Laboratory of Surveillance and Early-Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
| | - Zhongjie Li
- Key Laboratory of Surveillance and Early-Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
| | - Shengjie Lai
- WorldPop, Department of Geography and Environment, University of Southampton, Southampton SO17 IBJ, UK.
- Key Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai 200433, China.
- Flowminder Foundation, Roslagsgatan 17, SE-11355 Stockholm, Sweden.
| | - Qiyong Liu
- State Key Laboratory for 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.
- WHO Collaborating Center for Vector Surveillance and Management, Beijing 102206, China.
| | - Haixia Wu
- State Key Laboratory for 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.
| | - Weizhong Yang
- Key Laboratory of Surveillance and Early-Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
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46
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Imported cases and minimum temperature drive dengue transmission in Guangzhou, China: evidence from ARIMAX model. Epidemiol Infect 2018; 146:1226-1235. [PMID: 29781412 PMCID: PMC9134281 DOI: 10.1017/s0950268818001176] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Dengue is the fastest spreading mosquito-transmitted disease in the world. In China, Guangzhou City is believed to be the most important epicenter of dengue outbreaks although the transmission patterns are still poorly understood. We developed an autoregressive integrated moving average model incorporating external regressors to examine the association between the monthly number of locally acquired dengue infections and imported cases, mosquito densities, temperature and precipitation in Guangzhou. In multivariate analysis, imported cases and minimum temperature (both at lag 0) were both associated with the number of locally acquired infections (P < 0.05). This multivariate model performed best, featuring the lowest fitting root mean squared error (RMSE) (0.7520), AIC (393.7854) and test RMSE (0.6445), as well as the best effect in model validation for testing outbreak with a sensitivity of 1.0000, a specificity of 0.7368 and a consistency rate of 0.7917. Our findings suggest that imported cases and minimum temperature are two key determinants of dengue local transmission in Guangzhou. The modelling method can be used to predict dengue transmission in non-endemic countries and to inform dengue prevention and control strategies.
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Zhu G, Xiao J, Zhang B, Liu T, Lin H, Li X, Song T, Zhang Y, Ma W, Hao Y. The spatiotemporal transmission of dengue and its driving mechanism: A case study on the 2014 dengue outbreak in Guangdong, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2018; 622-623:252-259. [PMID: 29216466 DOI: 10.1016/j.scitotenv.2017.11.314] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2017] [Revised: 11/15/2017] [Accepted: 11/27/2017] [Indexed: 05/19/2023]
Abstract
Dengue transmission is a complex spatiotemporal process with hidden interactions between hosts, vectors, and viruses as well as environment. This study aims to identify the transmission patterns and the driving mechanism that contributed to the dengue epidemics occurred in Guangdong Province of China in 2014. Based on the city-specific epidemiological, meteorological, demographic and geographic data, we first performed wavelet analysis and then integrated the key dynamics (i.e., mosquito population dynamics, human movement, virus transmission, and parameter estimation) into a transmission model. Using these methods, we found a clear temporal sequence and correlation of dengue transmission between cities, and such relationship is associated with socioeconomic factors. We further obtained the specific component of dengue incidence data in each city, and presented the underlying infectivity networks for characterizing how dengue transmits from one location to another. The results showed that the communication of in-out infections with Guangzhou and Foshan could be responsible for the large-scale diffusion of dengue epidemics in Guangdong in 2014. Our findings can offer new insights into how to improve the predictability and risk assessment of dengue transmission.
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Affiliation(s)
- Guanghu Zhu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Bing Zhang
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Tao Liu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Hualiang Lin
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Xing Li
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Tie Song
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Yonghui Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Wenjun Ma
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China.
| | - Yuantao Hao
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
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48
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Spatial and Temporal Characteristics of 2014 Dengue Outbreak in Guangdong, China. Sci Rep 2018; 8:2344. [PMID: 29402909 PMCID: PMC5799376 DOI: 10.1038/s41598-018-19168-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2017] [Accepted: 12/22/2017] [Indexed: 11/23/2022] Open
Abstract
The record-breaking number of dengue cases reported in Guangdong, China in 2014 has been topic for many studies. However, the spatial and temporal characteristics of this unexpectedly explosive outbreak are still poorly understood. We adopt an integrated approach to ascertain the spatial-temporal progression of the outbreak in each city in Guangdong as well as in each district in Guangzhou, where the majority of cases occurred. We utilize the Richards model, which determines the waves of reported cases at each location and identifies the turning point for each wave, in combination with a spatial association analysis conducted by computing the standardized G* statistic that measures the degree of spatial autocorrelation of a set of geo-referenced data from a local perspective. We found that Yuexiu district in Guangzhou was the initial hot spot for the outbreak, subsequently spreading to its neighboring districts in Guangzhou and other cities in Guangdong province. Hospital isolation of cases during early stage of outbreak in neighboring Zhongshan (in effort to prevent disease transmission to the vectors) might have played an important role in the timely mitigation of the disease. Integration of modeling approach and spatial association analysis allows us to pinpoint waves that spread the disease to communities beyond the borders of the initially affected regions.
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49
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Erraguntla M, Zapletal J, Lawley M. Framework for Infectious Disease Analysis: A comprehensive and integrative multi-modeling approach to disease prediction and management. Health Informatics J 2017; 25:1170-1187. [PMID: 29278956 DOI: 10.1177/1460458217747112] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
The impact of infectious disease on human populations is a function of many factors including environmental conditions, vector dynamics, transmission mechanics, social and cultural behaviors, and public policy. A comprehensive framework for disease management must fully connect the complete disease lifecycle, including emergence from reservoir populations, zoonotic vector transmission, and impact on human societies. The Framework for Infectious Disease Analysis is a software environment and conceptual architecture for data integration, situational awareness, visualization, prediction, and intervention assessment. Framework for Infectious Disease Analysis automatically collects biosurveillance data using natural language processing, integrates structured and unstructured data from multiple sources, applies advanced machine learning, and uses multi-modeling for analyzing disease dynamics and testing interventions in complex, heterogeneous populations. In the illustrative case studies, natural language processing from social media, news feeds, and websites was used for information extraction, biosurveillance, and situation awareness. Classification machine learning algorithms (support vector machines, random forests, and boosting) were used for disease predictions.
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50
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Ren H, Zheng L, Li Q, Yuan W, Lu L. Exploring Determinants of Spatial Variations in the Dengue Fever Epidemic Using Geographically Weighted Regression Model: A Case Study in the Joint Guangzhou-Foshan Area, China, 2014. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2017; 14:ijerph14121518. [PMID: 29211001 PMCID: PMC5750936 DOI: 10.3390/ijerph14121518] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/14/2017] [Revised: 12/04/2017] [Accepted: 12/04/2017] [Indexed: 01/09/2023]
Abstract
Dengue fever (DF) is a common and rapidly spreading vector-borne viral disease in tropical and subtropical regions. In recent years, this imported disease has posed an increasing threat to public health in China, especially in many southern cities. Although the severity of DF outbreaks in these cities is generally associated with known risk factors at various administrative levels, spatial heterogeneities of these associations remain little understood on a finer scale. In this study, the neighboring Guangzhou and Foshan (GF) cities were considered as a joint area for characterizing the spatial variations in the 2014 DF epidemic at various grid levels from 1 × 1 km2 to 6 × 6 km2. On an appropriate scale, geographically weighted regression (GWR) models were employed to interpret the influences of socioeconomic and environmental factors on this epidemic across the GF area. DF transmissions in Guangzhou and Foshan cities presented synchronous temporal changes and spatial expansions during the main epidemic months. Across the GF area, this epidemic was obviously spatially featured at various grid levels, especially on the 2 × 2 km2 scale. Its spatial variations were relatively sufficiently explained by population size, road density, and economic status integrated in the GWR model with the lowest Akaike Information Criterion (AICc = 5227.97) and highest adjusted R square (0.732) values. These results indicated that these three socioeconomic factors acted as geographical determinants of spatial variability of the 2014 DF epidemic across the joint GF area, although some other potential factors should be added to improve the explaining the spatial variations in the central zones. This work improves our understanding of the effects of socioeconomic conditions on the spatial variations in this epidemic and helps local hygienic authorities to make targeted joint interventions for preventing and controlling this epidemic across the GF area.
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Affiliation(s)
- Hongyan Ren
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
| | - Lan Zheng
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
- Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China.
| | - Qiaoxuan Li
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
- College of Geographical Science, Fujian Normal University, Fuzhou 350007, China.
| | - Wu Yuan
- School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China.
| | - Liang Lu
- Department of Vector Biology and Control, Natural Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
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