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Silburn A, Arndell J. The impact of dengue viruses: Surveillance, response, and public health implications in Queensland, Australia. PUBLIC HEALTH IN PRACTICE 2024; 8:100529. [PMID: 39071864 PMCID: PMC11282963 DOI: 10.1016/j.puhip.2024.100529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 05/22/2024] [Accepted: 06/27/2024] [Indexed: 07/30/2024] Open
Abstract
This study examines dengue transmission, symptoms, vaccination efforts, treatment options, and global impact, focusing on Australia, especially Queensland. It evaluates current surveillance and response systems, identifies areas for improvement, and proposes strategies to enhance public health preparedness. Highlighting the socioeconomic impact of dengue outbreaks, the study underscores the need for integrated public health measures, effective vaccines, advanced surveillance methods, and sustainable mosquito control programs to mitigate the threat of dengue outbreaks and potential endemicity.
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Affiliation(s)
- Alan Silburn
- Western Sydney University, Campbelltown, 2560, NSW, Australia
| | - Joel Arndell
- Western Sydney University, Campbelltown, 2560, NSW, Australia
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Allen T, Crouch A, Russell TL, Topp SM. Factors influencing community engagement approaches used in Aedes aegypti management in Cairns, Australia. Health Promot J Austr 2024. [PMID: 39323226 DOI: 10.1002/hpja.924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 08/06/2024] [Accepted: 08/30/2024] [Indexed: 09/27/2024] Open
Abstract
ISSUE ADDRESSED An important part of preventing and managing Aedes-borne mosquito disease outbreak risk is engaging the community. Research shows that high-income countries tend to use top-down measures for Aedes mosquito management, favouring educational approaches to engage the community over participatory approaches that actively involve and empower the community in addressing disease risk. Little is known about the reasons behind the use of these approaches and how they could be strengthened. This research explores the community engagement approaches used in Aedes mosquito management in Cairns, Queensland, Australia and the factors influencing the choice of these approaches. METHODS A case study design was used, drawing on two qualitative methods-key informant, semi-structured interviews (n = 25), and a document review (n = 20). Thematic analysis was used to identify, analyse and attribute meaning from the data. RESULTS Various approaches were used to engage the community, including direct interaction through door-to-door inspections, broad outreach via mass media campaigns, and community participation in a novel mosquito replacement strategy. Factors influencing the choice of these approaches included government legislative responsibilities, research-related ethical obligations, work norms within local government and public health units, the perceived importance of gaining community trust, constraints on workforce capacity, time and funding. CONCLUSIONS There were multiple factors influencing the community engagement approaches used in this study. Resource constraints, institutional norms and prevailing attitudes and beliefs were identified as hindering the use of more empowering approaches to engaging the community. These barriers should be considered and addressed in the planning of Aedes mosquito management to better support community engagement in this setting. SO WHAT?: Community engagement is an important aspect of managing the Aedes mosquito disease threat. With the global increase in Aedes mosquito-borne disease risk, these findings can help other at-risk settings understand potential organisational impediments to engaging the community. This is particularly important when advocating for the inclusion of bottom-up approaches in policy, and to ensure sufficient resources are allocated to strengthen community engagement in Aedes mosquito management.
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Affiliation(s)
- Tammy Allen
- College of Public Health, Medical and Veterinary Sciences, James Cook University, Cairns, Queensland, Australia
| | - Alan Crouch
- Department of Rural Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Tanya L Russell
- Australian Institute of Tropical Health and Medicine, James Cook University, Queensland, Australia
| | - Stephanie M Topp
- College of Public Health, Medical and Veterinary Sciences, James Cook University, Townsville, Queensland, Australia
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Mokhtar S, Pittman Ratterree DC, Britt AF, Fisher R, Ndeffo-Mbah ML. Global risk of Dengue outbreaks and the impact of El Niño events. ENVIRONMENTAL RESEARCH 2024:119830. [PMID: 39181299 DOI: 10.1016/j.envres.2024.119830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 08/06/2024] [Accepted: 08/21/2024] [Indexed: 08/27/2024]
Abstract
BACKGROUND Dengue fever is an arboviral disease caused by the dengue virus (DENV). Its geographical distribution and health burden have been steadily increasing through tropical and subtropical climates in recent decades. METHODS We developed a temperature- and precipitation-dependent mechanistic model for the global risk of dengue fever outbreaks using the basic reproduction number (R0) as the metric of disease transmission risk. We used our model to evaluate the global risk of dengue outbreaks from 1950-2020 and to investigate the impact of annual seasons and El Niño events. RESULTS We showed that the global annual risk of dengue outbreaks has steadily increased during the last four decades. Highest R0 values were observed in South America, Southeast Asia, and the Equatorial region of Africa year-round with large seasonal variations occurring in other regions. El Niño was shown to be positively correlated with the global risk of dengue outbreaks with a correlation of 0.52. However, the impact of El Niño on dengue R0 was shown to vary across geographical regions and between El Niño events. CONCLUSIONS Strong El Niño events may increase the risk of dengue outbreaks across the globe. The onset of these events may trigger a surge of control efforts to minimize risk of dengue outbreaks.
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Affiliation(s)
- Sina Mokhtar
- Department of Veterinary Integrative Biosciences, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, 77843, USA; Department of Mathematics & Statistics, University of New Mexico, Albuquerque, NM, 87106, USA
| | - Dana C Pittman Ratterree
- Department of Epidemiology and Biostatistics, School of Public Health, Texas A&M University, College Station, TX, 77843, USA
| | - Amber F Britt
- Department of Epidemiology and Biostatistics, School of Public Health, Texas A&M University, College Station, TX, 77843, USA
| | - Rebecca Fisher
- Department of Epidemiology and Biostatistics, School of Public Health, Texas A&M University, College Station, TX, 77843, USA
| | - Martial L Ndeffo-Mbah
- Department of Veterinary Integrative Biosciences, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, 77843, USA; Department of Epidemiology and Biostatistics, School of Public Health, Texas A&M University, College Station, TX, 77843, USA.
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Ren H, Xu N. Forecasting and mapping dengue fever epidemics in China: a spatiotemporal analysis. Infect Dis Poverty 2024; 13:50. [PMID: 38956632 PMCID: PMC11221048 DOI: 10.1186/s40249-024-01219-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Accepted: 06/20/2024] [Indexed: 07/04/2024] Open
Abstract
BACKGROUND Dengue fever (DF) has emerged as a significant public health concern in China. The spatiotemporal patterns and underlying influencing its spread, however, remain elusive. This study aims to identify the factors driving these variations and to assess the city-level risk of DF epidemics in China. METHODS We analyzed the frequency, intensity, and distribution of DF cases in China from 2003 to 2022 and evaluated 11 natural and socioeconomic factors as potential drivers. Using the random forest (RF) model, we assessed the contributions of these factors to local DF epidemics and predicted the corresponding city-level risk. RESULTS Between 2003 and 2022, there was a notable correlation between local and imported DF epidemics in case numbers (r = 0.41, P < 0.01) and affected cities (r = 0.79, P < 0.01). With the increase in the frequency and intensity of imported epidemics, local epidemics have become more severe. Their occurrence has increased from five to eight months per year, with case numbers spanning from 14 to 6641 per month. The spatial distribution of city-level DF epidemics aligns with the geographical divisions defined by the Huhuanyong Line (Hu Line) and Qin Mountain-Huai River Line (Q-H Line) and matched well with the city-level time windows for either mosquito vector activity (83.59%) or DF transmission (95.74%). The RF models achieved a high performance (AUC = 0.92) when considering the time windows. Importantly, they identified imported cases as the primary influencing factor, contributing significantly (24.82%) to local DF epidemics at the city level in the eastern region of the Hu Line (E-H region). Moreover, imported cases were found to have a linear promoting impact on local epidemics, while five climatic and six socioeconomic factors exhibited nonlinear effects (promoting or inhibiting) with varying inflection values. Additionally, this model demonstrated outstanding accuracy (hitting ratio = 95.56%) in predicting the city-level risks of local epidemics in China. CONCLUSIONS China is experiencing an increasing occurrence of sporadic local DF epidemics driven by an unavoidably higher frequency and intensity of imported DF epidemics. This research offers valuable insights for health authorities to strengthen their intervention capabilities against this disease.
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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.
| | - Nankang Xu
- 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 Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
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Sarker I, Karim MR, E‐Barket S, Hasan M. Dengue fever mapping in Bangladesh: A spatial modeling approach. Health Sci Rep 2024; 7:e2154. [PMID: 38812714 PMCID: PMC11130545 DOI: 10.1002/hsr2.2154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 05/10/2024] [Accepted: 05/13/2024] [Indexed: 05/31/2024] Open
Abstract
Background Epidemics of the dengue virus can trigger widespread morbidity and mortality along with no specific treatment. Examining the spatial autocorrelation and variability of dengue prevalence throughout Bangladesh's 64 districts was the focus of this study. Methods The spatial autocorrelation is evaluated with the help of Moran I and Geary C . Local Moran I was used to detect hotspots and cold spots, whereas local Getis Ord G was used to identify only spatial hotspots. The spatial heterogeneity has been detected using various conventional and spatial models, including the Poisson-Gamma model, the Poisson-Lognormal Model, the Conditional Autoregressive (CAR) model, the Convolution model, and the BYM2 model, respectively. These models are implemented using Gibbs sampling and other Bayesian hierarchical approaches to analyze the posterior distribution effectively, enabling inference within a Bayesian context. Results The study's findings show that Moran I and Geary C analysis provides a substantial clustering pattern of positive spatial autocorrelation of dengue fever (DF) rates between surrounding districts at a 90% confidence interval. The Local Indicators of Spatial Autocorrelation cluster mapped spatial clusters and outliers based on prevalence rates, while the local Getis-Ord G displayed a thorough breakdown of high or low rates, omitting outliers. Although Chattogram had the most dengue cases (15,752), Khulna district had a higher prevalence rate (133.636) than Chattogram (104.796). The BYM2 model, determined to be well-fitted based on the lowest Deviance Information Criterion value (527.340), explains a significant association between spatial heterogeneity and prevalence rates. Conclusion This research pinpoints the district with the highest prevalence rate for dengue and the neighboring districts that also have high risk, allowing government agencies and communities to take the necessary precautions to mollify the risk effect of DF.
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Affiliation(s)
- Indrani Sarker
- Department of Statistics and Data ScienceJahangirnagar UniversityDhakaBangladesh
| | - Md. Rezaul Karim
- Department of Statistics and Data ScienceJahangirnagar UniversityDhakaBangladesh
| | - Sefat E‐Barket
- Department of Statistics and Data ScienceJahangirnagar UniversityDhakaBangladesh
| | - Mehedi Hasan
- Department of Statistics and Data ScienceJahangirnagar UniversityDhakaBangladesh
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Vasconcelos D, Nunes NJ, Förster A, Gomes JP. Optimal 2D audio features estimation for a lightweight application in mosquitoes species: Ecoacoustics detection and classification purposes. Comput Biol Med 2024; 168:107787. [PMID: 38070201 DOI: 10.1016/j.compbiomed.2023.107787] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 11/20/2023] [Accepted: 11/28/2023] [Indexed: 01/10/2024]
Abstract
Mosquitoes are the vector of diseases that kill more than one million people per year worldwide. Surveillance systems are essential for understanding their complex ecology and behaviour. This is fundamental for predicting disease risk caused by mosquitoes and formulating effective control strategies against mosquito-borne diseases such as malaria, dengue, and Zika. Mosquito populations vary heterogeneously in urban and rural landscapes, fluctuating with seasonal and climatic trends and human activity. Several approaches provide environmental data for mosquito mapping and risk prediction. However, they rely traditionally upon labour-intensive techniques such as manual traps. This paper presents the optimal audio features for mosquito identification using ecoacoustics signals to automatically identify different mosquito species from their wingbeat sounds based on popular audio features. The audio selection method uses Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Silhouette coefficient to evaluate the clusters in the data through the optimal-combined audio features. To classify the mosquito species and distinguish them from environmental-urban noise, the method comprises the Gaussian Mixture Model (GMM) and Gibbs approach for Aedes aegypti, and Culex quinquefasciatus, using the acoustic recordings of their wingbeat signals. Finally, comparing GMM and Gibbs, the two have very similar accuracy, but the classification time is much faster for Gibbs sampling, making it a good candidate for a lightweight solution. These are essential when deploying the described models to monitor mosquito vectors in the wild with Internet of Things (IoT) technologies.
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Affiliation(s)
- Dinarte Vasconcelos
- ITI/LARSYS, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, Lisbon, 1049-001, Portugal.
| | - Nuno Jardim Nunes
- ITI/LARSYS, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, Lisbon, 1049-001, Portugal.
| | - Anna Förster
- Sustainable Communication Networks, University of Bremen, Otto-Hahn-Allee 1, Bremen, 28359, Germany.
| | - João Pedro Gomes
- ISR/LARSYS, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, Lisbon, 1049-001, Portugal.
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Madzokere ET, Qian W, Webster JA, Walker DMH, Lim EXY, Harley D, Herrero LJ. Human Seroprevalence for Dengue, Ross River, and Barmah Forest viruses in Australia and the Pacific: A systematic review spanning seven decades. PLoS Negl Trop Dis 2022; 16:e0010314. [PMID: 35486651 PMCID: PMC9094520 DOI: 10.1371/journal.pntd.0010314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Revised: 05/11/2022] [Accepted: 03/08/2022] [Indexed: 11/18/2022] Open
Abstract
Background
Dengue (DENV), Ross River (RRV) and Barmah Forest viruses (BFV) are the most common human arboviral infections in Australia and the Pacific Island Countries and Territories (PICTs) and are associated with debilitating symptoms. All are nationally notifiable in Australia, but routine surveillance is limited to a few locations in the PICTs. Understanding the level of human exposure to these viruses can inform disease management and mitigation strategies. To assess the historic and current seroprevalence of DENV, RRV and BFV in Australia and the PICTs we conducted a systematic literature review of all published quantitative serosurveys.
Methodology and principal findings
The Preferred Reporting of Items for Systematic Reviews and Meta-Analyses procedures were adopted to produce a protocol to systematically search for published studies reporting the seroprevalence of DENV, RRV and BFV in Australia and the PICTs. Data for author, research year, location, study population, serosurvey methods and positive tests were extracted. A total of 41 papers, reporting 78 serosurveys of DENV, RRV and BFV including 62,327 samples met the inclusion criteria for this review. Seroprevalence varied depending on the assay used, strategy of sample collection and location of the study population. Significant differences were observed in reported seropositivity depending on the sample collection strategy with clinically targeted sampling reporting the highest seroprevalence across all three viruses. Non-stratified seroprevalence showed wide ranges in reported positivity with DENV 0.0% – 95.6%, RRV 0.0% – 100.0%, and BFV 0.3% – 12.5%. We discuss some of the causes of variation including serological methods used, selection bias in sample collection including clinical or environmental associations, and location of study site. We consider the extent to which serosurveys reflect the epidemiology of the viruses and provide broad recommendations regarding the conduct and reporting of arbovirus serosurveys.
Conclusions and significance
Human serosurveys provide important information on the extent of human exposure to arboviruses across: (1) time, (2) place, and (3) person (e.g., age, gender, clinical presentation etc). Interpreting results obtained at these scales has the potential to inform us about transmission cycles, improve diagnostic surveillance, and mitigate future outbreaks. Future research should streamline methods and reduce bias to allow a better understanding of the burden of these diseases and the factors associated with seroprevalence. Greater consideration should be given to the interpretation of seroprevalence in studies, and increased rigour applied in linking seroprevalence to transmission dynamics.
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Affiliation(s)
- Eugene T. Madzokere
- Institute for Glycomics, Griffith University, Gold Coast Campus, Southport, Australia
| | - Wei Qian
- Centre for Clinical Research, University of Queensland, Brisbane, Australia
| | - Julie A. Webster
- Institute for Glycomics, Griffith University, Gold Coast Campus, Southport, Australia
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Daniel M. H. Walker
- Institute for Glycomics, Griffith University, Gold Coast Campus, Southport, Australia
| | - Elisa X. Y. Lim
- Institute for Glycomics, Griffith University, Gold Coast Campus, Southport, Australia
| | - David Harley
- Centre for Clinical Research, University of Queensland, Brisbane, Australia
| | - Lara J. Herrero
- Institute for Glycomics, Griffith University, Gold Coast Campus, Southport, Australia
- * 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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OUP accepted manuscript. Trans R Soc Trop Med Hyg 2022; 116:853-867. [DOI: 10.1093/trstmh/trac027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2021] [Revised: 01/04/2022] [Accepted: 03/22/2022] [Indexed: 11/12/2022] Open
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Integrating Spatial Modelling and Space-Time Pattern Mining Analytics for Vector Disease-Related Health Perspectives: A Case of Dengue Fever in Pakistan. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph182212018. [PMID: 34831785 PMCID: PMC8618682 DOI: 10.3390/ijerph182212018] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 10/31/2021] [Accepted: 11/10/2021] [Indexed: 11/17/2022]
Abstract
The spatial–temporal assessment of vector diseases is imperative to design effective action plans and establish preventive strategies. Therefore, such assessments have potential public health planning-related implications. In this context, we here propose an integrated spatial disease evaluation (I-SpaDE) framework. The I-SpaDE integrates various techniques such as the Kernel Density Estimation, the Optimized Hot Spot Analysis, space–time assessment and prediction, and the Geographically Weighted Regression (GWR). It makes it possible to systematically assess the disease concentrations, patterns/trends, clustering, prediction dynamics, and spatially varying relationships between disease and different associated factors. To demonstrate the applicability and effectiveness of the I-SpaDE, we apply it in the second largest city of Pakistan, namely Lahore, using Dengue Fever (DF) during 2007–2016 as an example vector disease. The most significant clustering is evident during the years 2007–2008, 2010–2011, 2013, and 2016. Mostly, the clusters are found within the city’s central functional area. The prediction analysis shows an inclination of DF distribution from less to more urbanized areas. The results from the GWR show that among various socio-ecological factors, the temperature is the most significantly associated with the DF followed by vegetation and built-up area. While the results are important to understand the DF situation in the study area and have useful implications for public health planning, the proposed framework is flexible, replicable, and robust to be utilized in other similar regions, particularly in developing countries in the tropics and sub-tropics.
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Gao P, Pilot E, Rehbock C, Gontariuk M, Doreleijers S, Wang L, Krafft T, Martens P, Liu Q. Land use and land cover change and its impacts on dengue dynamics in China: A systematic review. PLoS Negl Trop Dis 2021; 15:e0009879. [PMID: 34669704 PMCID: PMC8559955 DOI: 10.1371/journal.pntd.0009879] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 11/01/2021] [Accepted: 10/05/2021] [Indexed: 12/29/2022] Open
Abstract
Background Dengue is a prioritized public health concern in China. Because of the larger scale, more frequent and wider spatial distribution, the challenge for dengue prevention and control has increased in recent years. While land use and land cover (LULC) change was suggested to be associated with dengue, relevant research has been quite limited. The “Open Door” policy introduced in 1978 led to significant LULC change in China. This systematic review is the first to review the studies on the impacts of LULC change on dengue dynamics in China. This review aims at identifying the research evidence, research gaps and provide insights for future research. Methods A systematic literature review was conducted following the PRISMA protocol. The combinations of search terms on LULC, dengue and its vectors were searched in the databases PubMed, Web of Science, and Baidu Scholar. Research conducted on China published from 1978 to December 2019 and written in English or Chinese was selected for further screening. References listed in articles meeting the inclusion criteria were also reviewed and included if again inclusion criteria were met to minimize the probability of missing relevant research. Results 28 studies published between 1978 and 2017 were included for the full review. Guangdong Province and southern Taiwan were the major regional foci in the literature. The majority of the reviewed studies observed associations between LULC change factors and dengue incidence and distribution. Conflictive evidence was shown in the studies about the impacts of green space and blue space on dengue in China. Transportation infrastructure and urbanization were repeatedly suggested to be positively associated with dengue incidence and spread. The majority of the studies reviewed considered meteorological and sociodemographic factors when they analyzed the effects of LULC change on dengue. Primary and secondary remote sensing (RS) data were the primary source for LULC variables. In 21 of 28 studies, a geographic information system (GIS) was used to process data of environmental variables and dengue cases and to perform spatial analysis of dengue. Conclusions The effects of LULC change on the dynamics of dengue in China varied in different periods and regions. The application of RS and GIS enriches the means and dimensions to explore the relations between LULC change and dengue. Further comprehensive regional research is necessary to assess the influence of LULC change on local dengue transmission to provide practical advice for dengue prevention and control. Dengue is a major public health concern in China. The rapid development of urbanization along with climate change increases the challenge for dengue prevention and control. Previous research has mainly focused on the meteorological variables whereas land use and land cover (LULC) change received comparatively less attention. Our review identified that the regional research hotspots of dengue epidemics in China were Guangdong Province and southern Taiwan. Though inconsistent, most included studies somehow observed associations between at least one of the LULC change factors and dengue. A geographical information system (GIS) was widely used to perform spatial analysis in the selected literature. Its application provided a novel view to describe the relationships between environmental factors and the situation of dengue, which enabled scholars to explore more characteristics of dengue transmission. Meanwhile, the use of remote sensing (RS) enriched the means of environmental monitoring. However, there are research gaps in the area of dengue and LULC change, such as the less consideration of dengue vector study, the lack of interplays between factors, and the lack of considering interventions and policies. Furthermore, because of different research settings, results from these studies were difficult to compare. Thus, further comprehensive and comparable investigations are necessary to better understand the effects of LULC change on dengue in China. This review is the first to expound the studies on the associations between LULC change and dengue dynamics in China. It demonstrates the findings and methodologies and provided insights for future research.
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Affiliation(s)
- Panjun Gao
- Department of Health, Ethics & Society, CAPHRI Care and Public Health Research Institute, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Eva Pilot
- Department of Health, Ethics & Society, CAPHRI Care and Public Health Research Institute, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Cassandra Rehbock
- Department of Health, Ethics & Society, CAPHRI Care and Public Health Research Institute, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Marie Gontariuk
- Department of Health, Ethics & Society, CAPHRI Care and Public Health Research Institute, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Simone Doreleijers
- Department of Health, Ethics & Society, CAPHRI Care and Public Health Research Institute, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Li Wang
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Thomas Krafft
- Department of Health, Ethics & Society, CAPHRI Care and Public Health Research Institute, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Pim Martens
- Maastricht Sustainability Institute (MSI), Maastricht University, Maastricht, The Netherlands
| | - Qiyong Liu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
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Hoyos W, Aguilar J, Toro M. Dengue models based on machine learning techniques: A systematic literature review. Artif Intell Med 2021; 119:102157. [PMID: 34531010 DOI: 10.1016/j.artmed.2021.102157] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 05/08/2021] [Accepted: 08/17/2021] [Indexed: 12/16/2022]
Abstract
BACKGROUND Dengue modeling is a research topic that has increased in recent years. Early prediction and decision-making are key factors to control dengue. This Systematic Literature Review (SLR) analyzes three modeling approaches of dengue: diagnostic, epidemic, intervention. These approaches require models of prediction, prescription and optimization. This SLR establishes the state-of-the-art in dengue modeling, using machine learning, in the last years. METHODS Several databases were selected to search the articles. The selection was made based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. Sixty-four articles were obtained and analyzed to describe their strengths and limitations. Finally, challenges and opportunities for research on machine-learning for dengue modeling were identified. RESULTS Logistic regression was the most used modeling approach for the diagnosis of dengue (59.1%). The analysis of the epidemic approach showed that linear regression (17.4%) is the most used technique within the spatial analysis. Finally, the most used intervention modeling is General Linear Model with 70%. CONCLUSIONS We conclude that cause-effect models may improve diagnosis and understanding of dengue. Models that manage uncertainty can also be helpful, because of low data-quality in healthcare. Finally, decentralization of data, using federated learning, may decrease computational costs and allow model building without compromising data security.
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Affiliation(s)
- William Hoyos
- Grupo de Investigaciones Microbiológicas y Biomédicas de Córdoba, Universidad de Córdoba, Montería, Colombia; Grupo de Investigación en I+D+i en TIC, Universidad EAFIT, Medellín, Colombia.
| | - Jose Aguilar
- Grupo de Investigación en I+D+i en TIC, Universidad EAFIT, Medellín, Colombia; Centro de Estudios en Microelectrónica y Sistemas Distribuidos, Universidad de Los Andes, Mérida, Venezuela; Universidad de Alcalá, Depto. de Automática, Alcalá de Henares, Spain
| | - Mauricio Toro
- Grupo de Investigación en I+D+i en TIC, Universidad EAFIT, Medellín, Colombia
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Long H, Zhang C, Chen C, Tang J, Zhang B, Wang Y, Pang J, Su W, Li K, Di B, Chen YQ, Shu Y, Du X. Assessment of the global circulation and endemicity of dengue. Transbound Emerg Dis 2021; 69:2148-2155. [PMID: 34197697 DOI: 10.1111/tbed.14211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 06/27/2021] [Indexed: 11/30/2022]
Abstract
Dengue is a significant public health issue, affecting hundreds of millions of people worldwide. As it is spreading from tropical and subtropical zones, some regions previously recognised as non-endemic are at risk of becoming endemic. However, the global circulation of dengue is not fully understood and quantitative measurements of endemicity levels are lacking, posing an obstacle in the precise control of dengue spread. In this study, a sequence-based pipeline was designed based on random sampling to study the transmission of dengue. The limited intercontinental transmission was identified, while regional circulation of dengue was quantified in terms of importation, local circulation and exportation. Additionally, hypo- and hyper-endemic regions were identified using a new metric, with the former characterised by low local circulation and increased importation, whereas the latter by high local circulation and reduced importation. In this study, the global circulation pattern of dengue was examined and a sequence-based endemicity measurement was proposed, which will be helpful for future surveillance and targeted control of dengue.
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Affiliation(s)
- Haoyu Long
- School of Public Health (Shenzhen), Sun Yat-Sen University, Guangzhou, China
| | - Chi Zhang
- School of Public Health (Shenzhen), Sun Yat-Sen University, Guangzhou, China
| | - Cai Chen
- School of Public Health (Shenzhen), Sun Yat-Sen University, Guangzhou, China
| | - Jing Tang
- School of Public Health (Shenzhen), Sun Yat-Sen University, Guangzhou, China
| | - Bing Zhang
- School of Public Health (Shenzhen), Sun Yat-Sen University, Guangzhou, China
| | - Yinghan Wang
- School of Public Health (Shenzhen), Sun Yat-Sen University, Guangzhou, China
| | - Jiali Pang
- School of Life Sciences, Sun Yat-Sen University, Guangzhou, China
| | - Wenzhe Su
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Kuibiao Li
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Biao Di
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Yao-Qing Chen
- School of Public Health (Shenzhen), Sun Yat-Sen University, Guangzhou, China
| | - Yuelong Shu
- School of Public Health (Shenzhen), Sun Yat-Sen University, Guangzhou, China.,Key Laboratory of Tropical Disease Control, Ministry of Education, Sun Yat-Sen University, Guangzhou, China
| | - Xiangjun Du
- School of Public Health (Shenzhen), Sun Yat-Sen University, Guangzhou, China.,Key Laboratory of Tropical Disease Control, Ministry of Education, Sun Yat-Sen University, Guangzhou, China
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Chen D, Shevade V, Baer A, He J, Hoffman-Hall A, Ying Q, Li Y, Loboda TV. A Disease Control-Oriented Land Cover Land Use Map for Myanmar. DATA 2021; 6:63. [PMID: 34504894 PMCID: PMC8425379 DOI: 10.3390/data6060063] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Malaria is a serious infectious disease that leads to massive casualties globally. Myanmar is a key battleground for the global fight against malaria because it is where the emergence of drug-resistant malaria parasites has been documented. Controlling the spread of malaria in Myanmar thus carries global significance, because the failure to do so would lead to devastating consequences in vast areas where malaria is prevalent in tropical/subtropical regions around the world. Thanks to its wide and consistent spatial coverage, remote sensing has become increasingly used in the public health domain. Specifically, remote sensing-based land cover/land use (LCLU) maps present a powerful tool that provides critical information on population distribution and on the potential human-vector interactions interfaces on a large spatial scale. Here, we present a 30-meter LCLU map that was created specifically for the malaria control and eradication efforts in Myanmar. This bottom-up approach can be modified and customized to other vector-borne infectious diseases in Myanmar or other Southeastern Asian countries.
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Affiliation(s)
- Dong Chen
- Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
| | - Varada Shevade
- Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
| | - Allison Baer
- Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
| | - Jiaying He
- Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Amanda Hoffman-Hall
- Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
| | - Qing Ying
- Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
- Department of Geosciences, Texas Tech University, Lubbock, TX 79409, USA
| | - Yao Li
- Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
| | - Tatiana V. Loboda
- Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
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15
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Akter R, Hu W, Gatton M, Bambrick H, Cheng J, Tong S. Climate variability, socio-ecological factors and dengue transmission in tropical Queensland, Australia: A Bayesian spatial analysis. ENVIRONMENTAL RESEARCH 2021; 195:110285. [PMID: 33027631 DOI: 10.1016/j.envres.2020.110285] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2020] [Revised: 09/21/2020] [Accepted: 09/30/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Dengue is a wide-spread mosquito-borne disease globally with a likelihood of becoming endemic in tropical Queensland, Australia. The aim of this study was to analyse the spatial variation of dengue notifications in relation to climate variability and socio-ecological factors in the tropical climate zone of Queensland, Australia. METHODS Data on the number of dengue cases and climate variables including minimum temperature, maximum temperature and rainfall for the period of January 1st, 2010 to December 31st, 2015 were obtained for each Statistical Local Area (SLA) from Queensland Health and Australian Bureau of Meteorology, respectively. Socio-ecological data including estimated resident population, percentage of Indigenous population, housing structure (specifically terrace house), socio-economic index and land use types for each SLA were obtained from Australian Bureau of Statistics, and Australian Bureau of Agricultural and Resource Economics and Sciences, respectively. To quantify the relationship between dengue, climate and socio-ecological factors, multivariate Poisson regression models in a Bayesian framework were developed with a conditional autoregressive prior structure. Posterior parameters were estimated using Bayesian Markov Chain Monte Carlo simulation with Gibbs sampling. RESULTS In the tropical climate zone of Queensland, the estimated number of dengue cases was predicted to increase by 85% [95% Credible Interval (CrI): 25%, 186%] and 7% (95% CrI: 0.1%, 14%) for a 1-mm increase in average annual rainfall and 1% increase in the proportion of terrace houses, respectively. The estimated spatial variation (structured random effects) was small compared to the remaining unstructured variation, suggesting that the inclusion of covariates resulted in no residual spatial autocorrelation in dengue data. CONCLUSIONS Climate and socio-ecological factors explained much of the heterogeneity of dengue transmission dynamics in the tropical climate zone of Queensland. Results will help to further understand the risk factors of dengue transmission and will provide scientific evidence in designing effective local dengue control programs in the most needed areas.
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Affiliation(s)
- Rokeya Akter
- School of Public Health and Social Work, Institute of Health & Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, 4059, Australia.
| | - Wenbiao Hu
- School of Public Health and Social Work, Institute of Health & Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, 4059, Australia
| | - Michelle Gatton
- School of Public Health and Social Work, Institute of Health & Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, 4059, Australia
| | - Hilary Bambrick
- School of Public Health and Social Work, Institute of Health & Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, 4059, Australia
| | - Jian Cheng
- School of Public Health and Social Work, Institute of Health & Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, 4059, Australia
| | - Shilu Tong
- School of Public Health and Social Work, Institute of Health & Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, 4059, Australia; Shanghai Children's Medical Centre, Shanghai Jiao Tong University, Shanghai, China; School of Public Health, Anhui Medical University, Hefei, China
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Carrillo MA, Kroeger A, Cardenas Sanchez R, Diaz Monsalve S, Runge-Ranzinger S. The use of mobile phones for the prevention and control of arboviral diseases: a scoping review. BMC Public Health 2021; 21:110. [PMID: 33422034 PMCID: PMC7796697 DOI: 10.1186/s12889-020-10126-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Accepted: 12/23/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The rapid expansion of dengue, Zika and chikungunya with large scale outbreaks are an increasing public health concern in many countries. Additionally, the recent coronavirus pandemic urged the need to get connected for fast information transfer and exchange. As response, health programmes have -among other interventions- incorporated digital tools such as mobile phones for supporting the control and prevention of infectious diseases. However, little is known about the benefits of mobile phone technology in terms of input, process and outcome dimensions. The purpose of this scoping review is to analyse the evidence of the use of mobile phones as an intervention tool regarding the performance, acceptance, usability, feasibility, cost and effectiveness in dengue, Zika and chikungunya control programmes. METHODS We conducted a scoping review of studies and reports by systematically searching: i) electronic databases (PubMed, PLOS ONE, PLOS Neglected Tropical Disease, LILACS, WHOLIS, ScienceDirect and Google scholar), ii) grey literature, using Google web and iii) documents in the list of references of the selected papers. Selected studies were categorized using a pre-determined data extraction form. Finally, a narrative summary of the evidence related to general characteristics of available mobile health tools and outcomes was produced. RESULTS The systematic literature search identified 1289 records, 32 of which met the inclusion criteria and 4 records from the reference lists. A total of 36 studies were included coming from twenty different countries. Five mobile phone services were identified in this review: mobile applications (n = 18), short message services (n=7), camera phone (n = 6), mobile phone tracking data (n = 4), and simple mobile communication (n = 1). Mobile phones were used for surveillance, prevention, diagnosis, and communication demonstrating good performance, acceptance and usability by users, as well as feasibility of mobile phone under real life conditions and effectiveness in terms of contributing to a reduction of vectors/ disease and improving users-oriented behaviour changes. It can be concluded that there are benefits for using mobile phones in the fight against arboviral diseases as well as other epidemic diseases. Further studies particularly on acceptance, cost and effectiveness at scale are recommended.
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Affiliation(s)
- Maria Angelica Carrillo
- Centre for Medicine and Society, Master Programme Global Urban Health, Albert-Ludwigs- University Freiburg, Freiburg im Breisgau, Germany.
| | - Axel Kroeger
- Centre for Medicine and Society, Master Programme Global Urban Health, Albert-Ludwigs- University Freiburg, Freiburg im Breisgau, Germany
| | - Rocio Cardenas Sanchez
- Centre for Medicine and Society, Master Programme Global Urban Health, Albert-Ludwigs- University Freiburg, Freiburg im Breisgau, Germany
| | - Sonia Diaz Monsalve
- Centre for Medicine and Society, Master Programme Global Urban Health, Albert-Ludwigs- University Freiburg, Freiburg im Breisgau, Germany
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Watts MJ, Kotsila P, Mortyn PG, Sarto I Monteys V, Urzi Brancati C. Influence of socio-economic, demographic and climate factors on the regional distribution of dengue in the United States and Mexico. Int J Health Geogr 2020; 19:44. [PMID: 33138827 PMCID: PMC7607660 DOI: 10.1186/s12942-020-00241-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Accepted: 10/19/2020] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND This study examines the impact of climate, socio-economic and demographic factors on the incidence of dengue in regions of the United States and Mexico. We select factors shown to predict dengue at a local level and test whether the association can be generalized to the regional or state level. In addition, we assess how different indicators perform compared to per capita gross domestic product (GDP), an indicator that is commonly used to predict the future distribution of dengue. METHODS A unique spatial-temporal dataset was created by collating information from a variety of data sources to perform empirical analyses at the regional level. Relevant regions for the analysis were selected based on their receptivity and vulnerability to dengue. A conceptual framework was elaborated to guide variable selection. The relationship between the incidence of dengue and the climate, socio-economic and demographic factors was modelled via a Generalized Additive Model (GAM), which also accounted for the spatial and temporal auto-correlation. RESULTS The socio-economic indicator (representing household income, education of the labour force, life expectancy at birth, and housing overcrowding), as well as more extensive access to broadband are associated with a drop in the incidence of dengue; by contrast, population growth and inter-regional migration are associated with higher incidence, after taking climate into account. An ageing population is also a predictor of higher incidence, but the relationship is concave and flattens at high rates. The rate of active physicians is associated with higher incidence, most likely because of more accurate reporting. If focusing on Mexico only, results remain broadly similar, however, workforce education was a better predictor of a drop in the incidence of dengue than household income. CONCLUSIONS Two lessons can be drawn from this study: first, while higher GDP is generally associated with a drop in the incidence of dengue, a more granular analysis reveals that the crucial factors are a rise in education (with fewer jobs in the primary sector) and better access to information or technological infrastructure. Secondly, factors that were shown to have an impact of dengue at the local level are also good predictors at the regional level. These indices may help us better understand factors responsible for the global distribution of dengue and also, given a warming climate, may help us to better predict vulnerable populations on a larger scale.
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Affiliation(s)
- Matthew J Watts
- Institute of Environmental Science and Technology (ICTA), Autonomous University of Barcelona (UAB), Bellaterra, Spain.
| | - Panagiota Kotsila
- Institute of Environmental Science and Technology (ICTA), Autonomous University of Barcelona (UAB), Bellaterra, Spain
- Barcelona Laboratory for Urban Environmental Justice and Sustainability (BCNEJ), Institute of Environmental Science and Technology (ICTA), Autonomous University of Barcelona (UAB), Bellaterra, Spain
| | - P Graham Mortyn
- Institute of Environmental Science and Technology (ICTA), Autonomous University of Barcelona (UAB), Bellaterra, Spain
- Department of Geography, Autonomous University of Barcelona (UAB), Bellaterra, Spain
| | - Victor Sarto I Monteys
- Institute of Environmental Science and Technology (ICTA), Autonomous University of Barcelona (UAB), Bellaterra, Spain
- Servei de Sanitat Vegetal, DARP, Generalitat de Catalunya, Av. Meridiana, 38, 08018, Barcelona, Spain
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Kakarla SG, Bhimala KR, Kadiri MR, Kumaraswamy S, Mutheneni SR. Dengue situation in India: Suitability and transmission potential model for present and projected climate change scenarios. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 739:140336. [PMID: 32758966 DOI: 10.1016/j.scitotenv.2020.140336] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/01/2020] [Revised: 06/16/2020] [Accepted: 06/16/2020] [Indexed: 05/16/2023]
Abstract
Dengue fever is mosquito borne viral disease caused by dengue virus and transmitted by Aedes mosquitoes. In recent years the dengue has spread rapidly to several regions and it becomes a major public health menace globally. Dengue transmission is strongly influenced by environmental factors such as temperature and rainfall. In the present study, a climate driven dengue model was developed and predicted areas vulnerable for dengue transmission under the present and future climate change scenarios in India. The study also projected the dengue distribution risk map using representative concentration pathways (RCP4.5 and RCP8.5) in India in 2018-2030 (forthcoming period), 2031-2050 (intermediate period) and 2051-2080 (long period). The dengue cases assessed in India from 1998 to 2018 and found that the dengue transmission is gradually increasing year over year. The temperature data from 1980 to 2017 shows that, the mean temperatures are raising in the Southern region of India. During 2000-2017 periods the dengue transmission is steadily increasing across the India in compare with 1980-1999 periods. The dengue distribution risk is predicted and it is revealed that the coastal states have yearlong transmission possibility, but the high transmission potential is observed throughout the monsoon period. Due to the climate change, the expansion two more months of dengue transmission risk occurs in many regions of India. Both RCP4.5 and RCP8.5 scenarios revealed that dengue outbreaks might occur at larger volume in Southern, Eastern, and Central regions of India. Furthermore a sensitivity analysis was performed to explore the impact of climate change on dengue transmission. These results helps to suggest appropriate control measures should be implemented to limit the spread in future warmer climates. Besides these, a proper plan is required to mitigate greenhouse gas emissions to reduce the epidemic potential of dengue in India.
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Affiliation(s)
- Satya Ganesh Kakarla
- Applied Biology Division, CSIR-Indian Institute of Chemical Technology, Tarnaka, Hyderabad 500007, Telangana, India
| | - Kantha Rao Bhimala
- CSIR-Fourth Paradigm Institute, NAL Belur Campus, Bangalore 560037, Karnataka, India
| | - Madhusudhan Rao Kadiri
- Applied Biology Division, CSIR-Indian Institute of Chemical Technology, Tarnaka, Hyderabad 500007, Telangana, India
| | - Sriram Kumaraswamy
- Applied Biology Division, CSIR-Indian Institute of Chemical Technology, Tarnaka, Hyderabad 500007, Telangana, India
| | - Srinivasa Rao Mutheneni
- Applied Biology Division, CSIR-Indian Institute of Chemical Technology, Tarnaka, Hyderabad 500007, Telangana, India.
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Climate and climate-sensitive diseases in semi-arid regions: a systematic review. Int J Public Health 2020; 65:1749-1761. [PMID: 32876770 DOI: 10.1007/s00038-020-01464-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 08/04/2020] [Accepted: 08/18/2020] [Indexed: 12/19/2022] Open
Abstract
OBJECTIVES We aim to describe the relationships between climate variables and climate-sensitive diseases (CSDs) in semi-arid regions, highlighting the different main groups of CSDs and their climate patterns. METHODS This systematic review considered Medline, Science Direct, Scopus and Web of Science. The data collection period was August and September 2019 and included studies published between 2008 and 2019. This study followed a protocol based on the PRISMA statement. Data analysis was done in a qualitative way. RESULTS The most of works were from Africa, Asia and Iran (71%), where temperature was the main climatic variable. Although the studies provide climatic conditions that are more favorable for the incidence of vector-borne and respiratory diseases, the influence of seasonal patterns on the onset, development and end of CSDs is still poorly understood, especially for gastrointestinal disorders. Moreover, little is known about the impact of droughts on CSDs. CONCLUSIONS This review summarized the state of art of the relationship between climate and CSDs in semi-arid regions. Moreover, a research agenda was provided, which is fundamental for health policy development, priority setting and public health management.
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Chen Y, Yang Z, Jing Q, Huang J, Guo C, Yang K, Chen A, Lu J. Effects of natural and socioeconomic factors on dengue transmission in two cities of China from 2006 to 2017. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 724:138200. [PMID: 32408449 DOI: 10.1016/j.scitotenv.2020.138200] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Revised: 03/23/2020] [Accepted: 03/23/2020] [Indexed: 06/11/2023]
Abstract
Dengue fever (DF) is a common and rapidly spreading vector-borne viral disease in tropical and subtropical regions. In recent years, in China, DF still poses an increasing threat to public health in many cities; but the incidence shows significant spatiotemporal differences. The purpose of this study was to identify the key factors affecting the spatial and temporal distribution of DF. We collected natural environmental and socio-economic data for two adjacent cities, Guangzhou (73 variables) and Foshan (71 variables), with the most DF cases in China. We performed random forest modelling to rank the factors according to their level of importance, and used negative binomial regression analysis to compare the risk factors between outbreak years and non-outbreak years. The natural environmental factors contributing to DF incidence for Guangzhou were temperature (relative risk (RR) = 18.80, 95% confidence interval (CI) = 3.11-113.67), humidity (RR = 1.85, 95% CI = 1.17-2.90) and green area (RR = 12.11, 95% CI = 6.14-55.50), and for Foshan was forest coverage (RR = 5.83, 95% CI = 2.72-12.45). Socio-economic impact were shown in Guangzhou with foreign visitor (RR = 1.18, 95% CI = 1.05-1.34) and oversea air passenger transport (RR = 7.34, 95% CI = 2.26-23.86); in Foshan, with oversea tourism (RR = 1.65, 95% CI = 1.34-2.04); and in Guangzhou-Foshan, with the development of intercity metro (RR = 1.26, 95% CI = 1.10-1.44). The difference between the two cities was the greater impact of the foreign visitor, green spaces and climate factor on DF in Guangzhou; the impact of the construction of intercity metro; and the more significant impact of oversea tourism on DF in Foshan. Our results suggest meaningful clues to public health authorities implementing joint interventions on DF prevention and early warning, to increase health education on DF prevention for international visitors and oversea travelers, and cross-city metro passengers; using rapid body temperature detection in public places such as airports, metros and parks can help detect cases early.
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Affiliation(s)
- Ying Chen
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, People's Republic of China
| | - Zefeng Yang
- Department of Infectious Diseases, Foshan Center for Disease Control and Prevention, People's Republic of China
| | - Qinlong Jing
- Department of Infectious Diseases, Guangzhou Center for Disease Control and Prevention, People's Republic of China
| | - Jiayin Huang
- Department of Infectious Diseases, Foshan Center for Disease Control and Prevention, People's Republic of China
| | - Cheng Guo
- Center for Infection and Immunity, Mailman School of Public Health, Columbia University, New York, United States of America
| | - Kailiang Yang
- Department of Infectious Diseases, Foshan Center for Disease Control and Prevention, People's Republic of China
| | - Aizhen Chen
- Department of Infectious Diseases, Foshan Center for Disease Control and Prevention, People's Republic of China.
| | - Jiahai Lu
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, People's Republic of China.
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Li Z, Gurgel H, Dessay N, Hu L, Xu L, Gong P. Semi-Supervised Text Classification Framework: An Overview of Dengue Landscape Factors and Satellite Earth Observation. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E4509. [PMID: 32585932 PMCID: PMC7344967 DOI: 10.3390/ijerph17124509] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Revised: 06/17/2020] [Accepted: 06/18/2020] [Indexed: 12/29/2022]
Abstract
In recent years there has been an increasing use of satellite Earth observation (EO) data in dengue research, in particular the identification of landscape factors affecting dengue transmission. Summarizing landscape factors and satellite EO data sources, and making the information public are helpful for guiding future research and improving health decision-making. In this case, a review of the literature would appear to be an appropriate tool. However, this is not an easy-to-use tool. The review process mainly includes defining the topic, searching, screening at both title/abstract and full-text levels and data extraction that needs consistent knowledge from experts and is time-consuming and labor intensive. In this context, this study integrates the review process, text scoring, active learning (AL) mechanism, and bidirectional long short-term memory (BiLSTM) networks, and proposes a semi-supervised text classification framework that enables the efficient and accurate selection of the relevant articles. Specifically, text scoring and BiLSTM-based active learning were used to replace the title/abstract screening and full-text screening, respectively, which greatly reduces the human workload. In this study, 101 relevant articles were selected from 4 bibliographic databases, and a catalogue of essential dengue landscape factors was identified and divided into four categories: land use (LU), land cover (LC), topography and continuous land surface features. Moreover, various satellite EO sensors and products used for identifying landscape factors were tabulated. Finally, possible future directions of applying satellite EO data in dengue research in terms of landscape patterns, satellite sensors and deep learning were proposed. The proposed semi-supervised text classification framework was successfully applied in research evidence synthesis that could be easily applied to other topics, particularly in an interdisciplinary context.
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Affiliation(s)
- Zhichao Li
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System, Science, Tsinghua University, Beijing 100084, China; (Z.L.); (L.X.)
| | - Helen Gurgel
- Department of Geography, University of Brasilia (UnB), Brasilia CEP 70910-900, Brazil;
- International Joint Laboratory Sentinela, FIOCRUZ, UnB, IRD, Rio de Janeiro RJ-21040-900, Brazil;
| | - Nadine Dessay
- International Joint Laboratory Sentinela, FIOCRUZ, UnB, IRD, Rio de Janeiro RJ-21040-900, Brazil;
- IRD, UM, UR, UG, UA, UMR ESPACE-DEV, 34090 Montpellier, France
| | - Luojia Hu
- Qian Xuesen Laboratory of Space Technology, China Academy of Space Technology, Beijing 100094, China;
| | - Lei Xu
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System, Science, Tsinghua University, Beijing 100084, China; (Z.L.); (L.X.)
| | - Peng Gong
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System, Science, Tsinghua University, Beijing 100084, China; (Z.L.); (L.X.)
- Center for Healthy Cities, Institute for China Sustainable Urbanization, Tsinghua University, Beijing 100084, China
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Da Conceição Araújo D, Dos Santos AD, Lima SVMA, Vaez AC, Cunha JO, Conceição Gomes Machado de Araújo K. Determining the association between dengue and social inequality factors in north-eastern Brazil: A spatial modelling. GEOSPATIAL HEALTH 2020; 15. [PMID: 32575962 DOI: 10.4081/gh.2020.854] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2019] [Accepted: 04/15/2020] [Indexed: 06/11/2023]
Abstract
Dengue is a global public health problem. The Dengue Virus (DENV) serotypes are transmitted by an Aedes aegypti mosquito. Vector control is among the primary methods to prevent the disease, especially in tropical countries. This study aimed to analyze the spatial distribution of dengue and its relationship with social inequalities using spatial modelling. An ecological study with temporal and spatial analysis was conducted in the state of Sergipe, Northeast Brazil, over a period of 18 years. Spatial modelling was used to determine the influence of space on dengue incidence and social inequalities. The epidemic rates in 2008, 2012, and 2015 were identified. Spatial modelling explained 40% of the influence of social inequalities on dengue incidence in the state. The main social inequalities related to the occurrence of dengue were the percentage of people living in extreme poverty and inadequate sanitation. The epidemic situation even increased the risk of dengue in the population of the state of Sergipe. These results demonstrate the potential of spatial modelling in determining the factors associated with dengue epidemics and are useful in planning the intersectoral public health policies.
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Affiliation(s)
| | - Allan Dantas Dos Santos
- Nursing Postgraduate Program, Federal University of Sergipe and Research Group in Public Health.
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Akter R, Naish S, Gatton M, Bambrick H, Hu W, Tong S. Spatial and temporal analysis of dengue infections in Queensland, Australia: Recent trend and perspectives. PLoS One 2019; 14:e0220134. [PMID: 31329645 PMCID: PMC6645541 DOI: 10.1371/journal.pone.0220134] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2019] [Accepted: 07/09/2019] [Indexed: 11/22/2022] Open
Abstract
Dengue is a public health concern in northern Queensland, Australia. This study aimed to explore spatial and temporal characteristics of dengue cases in Queensland, and to identify high-risk areas after a 2009 dengue outbreak at fine spatial scale and thereby help in planning resource allocation for dengue control measures. Notifications of dengue cases for Queensland at Statistical Local Area (SLA) level were obtained from Queensland Health for the period 2010 to 2015. Spatial and temporal analysis was performed, including plotting of seasonal distribution and decomposition of cases, using regression models and creating choropleth maps of cumulative incidence. Both the space-time scan statistic (SaTScan) and Geographical Information System (GIS) were used to identify and visualise the space-time clusters of dengue cases at SLA level. A total of 1,773 dengue cases with 632 (35.65%) autochthonous cases and 1,141 (64.35%) overseas acquired cases were satisfied for the analysis in Queensland during the study period. Both autochthonous and overseas acquired cases occurred more frequently in autumn and showed a geographically expanding trend over the study period. The most likely cluster of autochthonous cases (Relative Risk, RR = 54.52, p<0.001) contained 50 SLAs in the north-east region of the state around Cairns occurred during 2013-2015. A cluster of overseas cases (RR of 60.81, p<0.001) occurred in a suburb of Brisbane during 2012 to 2013. These results show a clear spatiotemporal trend of recent dengue cases in Queensland, providing evidence in directing future investigations on risk factors of this disease and effective interventions in the high-risk areas.
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Affiliation(s)
- Rokeya Akter
- School of Public Health and Social Work, Institute of Health & Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Suchithra Naish
- School of Public Health and Social Work, Institute of Health & Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia
- School of Health, Medical and Applied Sciences, Central Queensland University, Queensland, Australia
| | - Michelle Gatton
- School of Public Health and Social Work, Institute of Health & Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Hilary Bambrick
- School of Public Health and Social Work, Institute of Health & Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Wenbiao Hu
- School of Public Health and Social Work, Institute of Health & Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Shilu Tong
- School of Public Health and Social Work, Institute of Health & Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia
- Shanghai Children's Medical Centre, Shanghai Jiao Tong University, Shanghai, China
- School of Public Health, Anhui Medical University, Hefei, China
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Haddawy P, Wettayakorn P, Nonthaleerak B, Su Yin M, Wiratsudakul A, Schöning J, Laosiritaworn Y, Balla K, Euaungkanakul S, Quengdaeng P, Choknitipakin K, Traivijitkhun S, Erawan B, Kraisang T. Large scale detailed mapping of dengue vector breeding sites using street view images. PLoS Negl Trop Dis 2019; 13:e0007555. [PMID: 31356617 PMCID: PMC6687207 DOI: 10.1371/journal.pntd.0007555] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Revised: 08/08/2019] [Accepted: 06/17/2019] [Indexed: 01/21/2023] Open
Abstract
Targeted environmental and ecosystem management remain crucial in control of dengue. However, providing detailed environmental information on a large scale to effectively target dengue control efforts remains a challenge. An important piece of such information is the extent of the presence of potential dengue vector breeding sites, which consist primarily of open containers such as ceramic jars, buckets, old tires, and flowerpots. In this paper we present the design and implementation of a pipeline to detect outdoor open containers which constitute potential dengue vector breeding sites from geotagged images and to create highly detailed container density maps at unprecedented scale. We implement the approach using Google Street View images which have the advantage of broad coverage and of often being two to three years old which allows correlation analyses of container counts against historical data from manual surveys. Containers comprising eight of the most common breeding sites are detected in the images using convolutional neural network transfer learning. Over a test set of images the object recognition algorithm has an accuracy of 0.91 in terms of F-score. Container density counts are generated and displayed on a decision support dashboard. Analyses of the approach are carried out over three provinces in Thailand. The container counts obtained agree well with container counts from available manual surveys. Multi-variate linear regression relating densities of the eight container types to larval survey data shows good prediction of larval index values with an R-squared of 0.674. To delineate conditions under which the container density counts are indicative of larval counts, a number of factors affecting correlation with larval survey data are analyzed. We conclude that creation of container density maps from geotagged images is a promising approach to providing detailed risk maps at large scale.
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Affiliation(s)
- Peter Haddawy
- Faculty of ICT, Mahidol University, Salaya, Thailand
- Bremen Spatial Cognition Center, University of Bremen, Bremen, Germany
| | | | | | - Myat Su Yin
- Faculty of ICT, Mahidol University, Salaya, Thailand
| | | | | | | | - Klestia Balla
- Computer Science Department, School of Science and Technology, University of Camerino, Camerino, Italy
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Hossain MZ, Bambrick H, Wraith D, Tong S, Khan AF, Hore SK, Hu W. Sociodemographic, climatic variability and lower respiratory tract infections: a systematic literature review. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2019; 63:209-219. [PMID: 30680618 DOI: 10.1007/s00484-018-01654-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Revised: 11/15/2018] [Accepted: 11/29/2018] [Indexed: 06/09/2023]
Abstract
Pneumonia is the leading cause of mortality and morbidity in developing countries, particularly for children and elderly. The main objective of this review paper is to review the epidemiological evidence about the effects of sociodemographic and climatic variability on pneumonia and other lower respiratory tract infections. A detailed literature search was conducted in PubMed and Scopus following PRISMA guidelines. The articles, which considered the effect of only climatic or both climatic and sociodemographic factors on pneumonia and other lower respiratory tract infections, included in this review. A total thirty-four relevant articles were reviewed. Of 34 studies, only 14 articles (41%) examined the joint effects of sociodemographic and climate factors on pneumonia and other lower respiratory infections while most of them (59%) assessed climate factors separately. Among these fourteen, only three articles (8.8%) considered detailed sociodemographic factors. All of the reviewed articles suggested different degrees of positive or negative relationship of temperature with pneumonia or other lower respiratory tract infections. Fifteen (44%) articles suggested an association with relative humidity and 13 (38%) with rainfall. Only 3 articles (8.8%) found a relationship with wind speed. Three articles (8.8%) considered other risk factors such as particulate matter 2.5 (PM2.5) and particulate matter 10 (PM10). One study among the reviewed articles used spatial analysis methods but this study did not examine the joint effects. Among the reviewed articles, 18 (53%) articles used different time series models, one article (3%) used spatiotemporal time series model, 8 (23%) studies used other models and rest 7 (21%) studies used simple descriptive analysis. A total of 18 studies (53%) were conducted in Asia, most of them in China. There were 6 studies (17%) in Europe and 8 studies (23%) in America (South, North and Central). In Africa and Oceania, only one study was found for each region. The joint effect of climate and sociodemographic factors on pneumonia and other lower respiratory tract infections remain to be determined and further research is highly recommended for future prevention of this important and common disease.
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Affiliation(s)
- Mohammad Zahid Hossain
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Hilary Bambrick
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Darren Wraith
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Shilu Tong
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia
- Shanghai Children's Medical Centre, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- School of Public Health, Institute of Environment and Population Health, Anhui Medical University, Hefei, China
| | - Al Fazal Khan
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Mohakhali, Dhaka, 1212, Bangladesh
| | - Samar Kumar Hore
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Mohakhali, Dhaka, 1212, Bangladesh
| | - Wenbiao Hu
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia.
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Abstract
Dengue fever (DF) has been a growing public-health concern in China since its emergence in Guangdong Province in 1978. Of all the regions that have experienced dengue outbreaks in mainland China, the city of Guangzhou is the most affected. This study aims to investigate the potential risk factors for dengue virus (DENV) transmission in Guangzhou, China, from 2006 to 2014. The impact of risk factors on DENV transmission was qualified by the q-values calculated using a novel spatial-temporal method, the GeoDetector model. Both climatic and socioeconomic factors were considered. The impacts on DF incidence of each single factor and the interaction of two factors were analysed. The results show that the number of days with rainfall of the month before last has the highest determinant power, with a q-value of 0.898 (P < 0.01); the q-values of the other factors related to temperature and precipitation were around 0.38–0.50. Integrating a Pearson correlation analysis, nonlinear associations were found between the DF incidence in Guangzhou and the climatic factors considered. The coupled impact of the different variables considered was enhanced compared with their individual effects. In addition, an increased number of tourists in the city were associated with a high incidence of DF. This study demonstrates that the number of rain days in a month has great influence on the DF incidence of the month after next; the temperature and precipitation have nonlinear impacts on the DF incidence in Guangzhou; both the domestic and overseas tourists coming to the city increase the risk of DENV transmission. These findings are useful in the risk assessment of DENV transmission, to predict DF outbreaks and to implement preventive DF reduction strategies.
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Chuang TW, Ng KC, Nguyen TL, Chaves LF. Epidemiological Characteristics and Space-Time Analysis of the 2015 Dengue Outbreak in the Metropolitan Region of Tainan City, Taiwan. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2018; 15:ijerph15030396. [PMID: 29495351 PMCID: PMC5876941 DOI: 10.3390/ijerph15030396] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 02/23/2018] [Accepted: 02/23/2018] [Indexed: 12/29/2022]
Abstract
The metropolitan region of Tainan City in southern Taiwan experienced a dengue outbreak in 2015. This manuscript describes basic epidemiological features of this outbreak and uses spatial and temporal analysis tools to understand the spread of dengue during the outbreak. The analysis found that, independently of gender, dengue incidence rate increased with age, and proportionally affected more males below the age of 40 years but females above the age of 40 years. A spatial scan statistic was applied to detect clusters of disease transmission. The scan statistic found that dengue spread in a north-south diffusion direction, which is across the North, West-Central and South districts of Tainan City. Spatial regression models were used to quantify factors associated with transmission. This analysis indicated that neighborhoods with high proportions of residential area (or low wetland cover) were associated with dengue transmission. However, these association patterns were non-linear. The findings presented here can help Taiwanese public health agencies to understand the fundamental epidemiological characteristics and diffusion patterns of the 2015 dengue outbreak in Tainan City. This type of information is fundamental for policy making to prevent future uncontrolled dengue outbreaks, given that results from this study suggest that control interventions should be emphasized in the North and West-Central districts of Tainan city, in areas with a moderate percentage of residential land cover.
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Affiliation(s)
- Ting-Wu Chuang
- Department of Molecular Parasitology and Tropical Diseases, School of Medicine, College of Medicine, Taipei Medical University, No. 250, Wuxing Street, Xinyi District, Taipei 11031, Taiwan.
| | - Ka-Chon Ng
- College of Public Health, National Taiwan University, Taipei 10607, Taiwan.
| | - Thi Luong Nguyen
- College of Medicine, Taipei Medical University, Taipei 11031, Taiwan.
| | - Luis Fernando Chaves
- Instituto Costarricense de Investigación y Enseñanza en Nutrición y Salud (INCIENSA), Apartado Postal 4-2250, Tres Ríos, Cartago, Costa Rica.
- Programa de Investigación en Enfermedades Tropicales (PIET), Escuela de Medicina Veterinaria, Universidad Nacional, Apartado Postal 304-3000, Heredia, Costa Rica.
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Granada Y, Mejía-Jaramillo AM, Strode C, Triana-Chavez O. A Point Mutation V419L in the Sodium Channel Gene from Natural Populations of Aedes aegypti Is Involved in Resistance to λ-Cyhalothrin in Colombia. INSECTS 2018; 9:insects9010023. [PMID: 29443870 PMCID: PMC5872288 DOI: 10.3390/insects9010023] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2017] [Revised: 01/11/2018] [Accepted: 01/17/2018] [Indexed: 01/01/2023]
Abstract
Resistance to pyrethroids in mosquitoes is mainly caused by target site insensitivity known as knockdown resistance (kdr). In this work, we examined the point mutations present in portions of domains I, II, III, and IV of the sodium channel gene in Aedes aegypti mosquitoes from three Colombian municipalities. A partial region coding for the sodium channel gene from resistant mosquitoes was sequenced, and a simple allele-specific PCR-based assay (AS-PCR) was used to analyze mutations at the population level. The previously reported mutations, V1016I and F1534C, were found with frequencies ranging from 0.04 to 0.41, and 0.56 to 0.71, respectively, in the three cities. Moreover, a novel mutation, at 419 codon (V419L), was found in Ae. aegypti populations from Bello, Riohacha and Villavicencio cities with allelic frequencies of 0.06, 0.36, and 0.46, respectively. Interestingly, the insecticide susceptibility assays showed that mosquitoes from Bello were susceptible to λ-cyhalothrin pyrethroid whilst those from Riohacha and Villavicencio were resistant. A positive association between V419L and V1016I mutations with λ-cyhalothrin resistance was established in Riohacha and Villavicencio. The frequency of the F1534C was high in the three populations, suggesting that this mutation could be conferring resistance to insecticides other than λ-cyhalothrin, particularly type I pyrethroids. Further studies are required to confirm this hypothesis.
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Affiliation(s)
- Yurany Granada
- Grupo Biologia y Control de Enfermedades Infecciosas-BCEI, Universidad de Antioquia, Calle 70 No. 52-21, Medellín 050010, Colombia.
| | - Ana María Mejía-Jaramillo
- Grupo Biologia y Control de Enfermedades Infecciosas-BCEI, Universidad de Antioquia, Calle 70 No. 52-21, Medellín 050010, Colombia.
| | - Clare Strode
- Biology Department, Edge Hill University, St. Helens Road, Ormskirk, Lancashire L39 4QP, UK.
| | - Omar Triana-Chavez
- Grupo Biologia y Control de Enfermedades Infecciosas-BCEI, Universidad de Antioquia, Calle 70 No. 52-21, Medellín 050010, Colombia.
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