1
|
Chiu MC, Neoh KB, Hwang SY. The effect of attractive toxic sugar bait on the Asian tiger mosquito, Aedes albopictus (Diptera: Culicidae) in community farms in Northern Taiwan. Acta Trop 2024; 250:107102. [PMID: 38104884 DOI: 10.1016/j.actatropica.2023.107102] [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: 10/18/2023] [Revised: 11/30/2023] [Accepted: 12/14/2023] [Indexed: 12/19/2023]
Abstract
Attractive toxic sugar baits (ATSBs) lure mosquitoes to feed on the baits and subsequently killed them. We investigated the effects of a boric acid-containing ATSB on the population of Aedes albopictus at 48 h exposure and assessed the field effectiveness on this ATSB on two types of community farms in New Taipei City, Taiwan, including isolated ATSB farms and nonisolated ATSB farms. The result showed that mosquitoes exposed to the ATSB solution for 48 h were killed within 7 d under laboratory conditions. Exposure of female and male mosquitoes to ATSB resulted in mean survival times ranging from 52 to 62 h and 30 to 48 h, respectively. For field efficacy test, on isolated ATSB farms, a significant reduction of ovitrap density index (ODI) up to 24 % was noted after the replacement frequency was increased to every 2 weeks. However, the intervention efficacy on nonisolated ATSB farms had mixed results. The ODI significantly reduced by 21.4 % and 6.9 % on the nonisolated ATSB Chongmin and Nanjing farms, respectively, when bait replacement was done every 2 weeks instead of every 3 weeks. By contrast, the ODI on the nonisolated ATSB Yongchang farms increased significantly, irrespectively of the bait replacement frequency. Nevertheless, the total number of eggs trapped on all ATSB farms exhibited a concave curve pattern; while the mosquito population on non-ATSB control farms continued to increase over time. In conclusion, deploying simple ATSB stations containing boric acid is a practical approach for integrated vector management programs.
Collapse
Affiliation(s)
- Meng-Chieh Chiu
- Department of Entomology, National Chung Hsing University, 145 Xingda Rd., Taichung 402, Taiwan
| | - Kok-Boon Neoh
- Department of Entomology, National Chung Hsing University, 145 Xingda Rd., Taichung 402, Taiwan.
| | - Shaw-Yhi Hwang
- Department of Entomology, National Chung Hsing University, 145 Xingda Rd., Taichung 402, Taiwan.
| |
Collapse
|
2
|
Wan-Norafikah O, Hasani NAH, Nabila AB, Najibah I, Nurjuani AHH, Masliana M, Aliah-Diyanah S, Alia-Yasmin Z, Yasmin-Zafirah I, Farah-Farhani A, Azahari AH, Faiqah-Nadhirah M, Nurul-Azira MS. Profiling Insecticide Susceptibility of Aedes Albopictus From Hot Springs in Selangor, Malaysia. JOURNAL OF THE AMERICAN MOSQUITO CONTROL ASSOCIATION 2023; 39:183-191. [PMID: 37796735 DOI: 10.2987/23-7125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/07/2023]
Abstract
The present study establishes insecticide susceptibility profiles of Aedes albopictus adult populations from 4 hot springs in Selangor, Malaysia, against 7 pyrethroids through an adult mosquito susceptibility bioassay. All Ae. albopictus populations were subjected to a 1-h exposure to each pyrethroid following the World Health Organization. The mortalities were recorded at 60 min of exposure to bifenthrin, 30 min for other pyrethroids, and 24 h posttreatment for all pyrethroids. Complete mortalities were observed upon exposures to the pyrethroids under 60 min and at 24 h posttreatment, excluding permethrin 0.25%, alpha-cypermethrin 0.05%, and bifenthrin 0.2%. These findings indicated that permethrin, deltamethrin, lambda-cyhalothrin, cyfluthrin, and etofenprox possess the recommended pyrethroid adulticide active ingredients that could be applied in vector control programs at these hot springs in the future. Nevertheless, the application of pyrethroids should be carefully monitored in rotation with other insecticide classes, including organophosphates and carbamates to avoid the development of insecticide resistance among mosquito vectors towards all insecticides. Although there were no reported cases of Aedes-borne pathogens at these hot springs to date, the current study results could still assist the Malaysian health authorities in determining approaches to control Aedes populations in these hot springs, if required in the future.
Collapse
|
3
|
Weather-Based Prediction Models for the Prevalence of Dengue Vectors Aedes aegypti and Ae. albopictus. J Trop Med 2022; 2022:4494660. [PMID: 36605885 PMCID: PMC9810403 DOI: 10.1155/2022/4494660] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 11/26/2022] [Accepted: 11/28/2022] [Indexed: 12/29/2022] Open
Abstract
Dengue is an important vector-borne disease transmitted by the mosquitoes Aedes aegypti and Ae. albopictus. In the absence of an effective vaccine, vector control has become the key intervention tool in controlling the disease. Vector densities are significantly affected by the changing weather patterns of a region. The present study was conducted in three selected localities, i.e., urban Bandaranayakapura, semiurban Galgamuwa, and rural Buluwala in the Kurunegala district of Sri Lanka to assess spatial and temporal distribution of dengue vector mosquitoes and to predict vector prevalence with respect to changing weather parameters. Monthly ovitrap surveys and larval surveys were conducted from January to December 2019 and continued further in the urban area up to December 2021. Aedes aegypti was found moderately in the urban area and to a lesser extent in semiurban but not in the rural area. Aedes albopictus had the preference for rural over urban areas. Aedes aegypti preferred indoor breeding, while Ae. albopictus preferred both indoor and outdoor. For Ae. albopictus, ovitrap index (OVI), premise index (PI), container index (CI), and Breteau index (BI) correlated with both the rainfall (RF) and relative humidity (RH) of the urban site. Correlations were stronger between OVI and RH and also between BI and RF. Linear regression analysis was fitted, and a prediction model was developed using BI and RF with no lag period (R 2 (sq) = 86.3%; F = 53.12; R 2 (pred) = 63.12%; model: Log10 (BI) = 0.153 + 0.286 ∗ Log10 (RF); RMSE = 1.49). Another prediction model was developed using OVI and RH with one month lag period (R 2 (sq) = 70.21%; F = 57.23; model: OVI predicted = 15.1 + 0.528 ∗ Lag 1 month RH; RMSE = 2.01). These two models can be used to monitor the population dynamics of Ae. albopictus in urban settings to predict possible dengue outbreaks.
Collapse
|
4
|
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: 4] [Impact Index Per Article: 1.3] [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.
Collapse
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.
| |
Collapse
|
5
|
Lin CH, Wen TH. How Spatial Epidemiology Helps Understand Infectious Human Disease Transmission. Trop Med Infect Dis 2022; 7:164. [PMID: 36006256 PMCID: PMC9413673 DOI: 10.3390/tropicalmed7080164] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 07/15/2022] [Accepted: 07/15/2022] [Indexed: 02/06/2023] Open
Abstract
Both directly and indirectly transmitted infectious diseases in humans are spatial-related. Spatial dimensions include: distances between susceptible humans and the environments shared by people, contaminated materials, and infectious animal species. Therefore, spatial concepts in managing and understanding emerging infectious diseases are crucial. Recently, due to the improvements in computing performance and statistical approaches, there are new possibilities regarding the visualization and analysis of disease spatial data. This review provides commonly used spatial or spatial-temporal approaches in managing infectious diseases. It covers four sections, namely: visualization, overall clustering, hot spot detection, and risk factor identification. The first three sections provide methods and epidemiological applications for both point data (i.e., individual data) and aggregate data (i.e., summaries of individual points). The last section focuses on the spatial regression methods adjusted for neighbour effects or spatial heterogeneity and their implementation. Understanding spatial-temporal variations in the spread of infectious diseases have three positive impacts on the management of diseases. These are: surveillance system improvements, the generation of hypotheses and approvals, and the establishment of prevention and control strategies. Notably, ethics and data quality have to be considered before applying spatial-temporal methods. Developing differential global positioning system methods and optimizing Bayesian estimations are future directions.
Collapse
Affiliation(s)
- Chia-Hsien Lin
- Department of Health Promotion and Health Education, National Taiwan Normal University, Taipei City 10610, Taiwan
- Department of Geography, National Taiwan University, Taipei City 10617, Taiwan;
| | - Tzai-Hung Wen
- Department of Geography, National Taiwan University, Taipei City 10617, Taiwan;
| |
Collapse
|
6
|
Yang B, Borgert BA, Alto BW, Boohene CK, Brew J, Deutsch K, DeValerio JT, Dinglasan RR, Dixon D, Faella JM, Fisher-Grainger SL, Glass GE, Hayes R, Hoel DF, Horton A, Janusauskaite A, Kellner B, Kraemer MUG, Lucas KJ, Medina J, Morreale R, Petrie W, Reiner RC, Riles MT, Salje H, Smith DL, Smith JP, Solis A, Stuck J, Vasquez C, Williams KF, Xue RD, Cummings DAT. Modelling distributions of Aedes aegypti and Aedes albopictus using climate, host density and interspecies competition. PLoS Negl Trop Dis 2021; 15:e0009063. [PMID: 33764975 PMCID: PMC8051819 DOI: 10.1371/journal.pntd.0009063] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Revised: 04/16/2021] [Accepted: 12/09/2020] [Indexed: 12/22/2022] Open
Abstract
Florida faces the challenge of repeated introduction and autochthonous transmission of arboviruses transmitted by Aedes aegypti and Aedes albopictus. Empirically-based predictive models of the spatial distribution of these species would aid surveillance and vector control efforts. To predict the occurrence and abundance of these species, we fit a mixed-effects zero-inflated negative binomial regression to a mosquito surveillance dataset with records from more than 200,000 trap days, representative of 53% of the land area and ranging from 2004 to 2018 in Florida. We found an asymmetrical competitive interaction between adult populations of Aedes aegypti and Aedes albopictus for the sampled sites. Wind speed was negatively associated with the occurrence and abundance of both vectors. Our model predictions show high accuracy (72.9% to 94.5%) in validation tests leaving out a random 10% subset of sites and data since 2017, suggesting a potential for predicting the distribution of the two Aedes vectors.
Collapse
Affiliation(s)
- Bingyi Yang
- Department of Biology, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - Brooke A. Borgert
- Department of Biology, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - Barry W. Alto
- Department of Entomology and Nematology, Florida Medical Entomology Laboratory, University of Florida, Vero Beach, Florida, United States of America
| | - Carl K. Boohene
- Polk County Mosquito Control, Parks and Natural Resources Division, Florida, United States of America
| | - Joe Brew
- Institut de Salut Global de Barcelona, Carrer del Rosselló, Barcelona, Catalonia, Spain
| | - Kelly Deutsch
- Orange County Government, Florida, Orange County Mosquito Control Division, Florida, United States of America
| | - James T. DeValerio
- University of Florida Institute of Food and Agricultural Sciences, Bradford County Extension, Starke, Florida, United States of America
| | - Rhoel R. Dinglasan
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
- Department of Infectious Diseases and Immunology, University of Florida, Gainesville, Florida, United States of America
| | - Daniel Dixon
- Anastasia Mosquito Control District, St. Augustine, Florida, United States of America
| | - Joseph M. Faella
- Brevard County Mosquito Control, Florida, United States of America
| | | | - Gregory E. Glass
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
- Department of Geography, University of Florida, Gainesville, Florida, United States of America
| | - Reginald Hayes
- Palm Beach County Mosquito Control, Florida, United States of America
| | - David F. Hoel
- Lee County Mosquito Control District, Florida, United States of America
| | - Austin Horton
- Gulf County Mosquito Control, Florida, United States of America
| | - Agne Janusauskaite
- Pasco County Mosquito Control District, Florida, United States of America
| | - Bill Kellner
- Citrus County Mosquito Control District, Florida, United States of America
| | - Moritz U. G. Kraemer
- Harvard Medical School, Boston, Massachusetts, United States of America
- Computational Epidemiology Lab, Boston Children’s Hospital, Boston, Massachusetts, United States of America
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Keira J. Lucas
- Collier Mosquito Control District, Naples, Florida, United States of America
| | - Johana Medina
- Miami-Dade County Mosquito Control, Florida, United States of America
| | - Rachel Morreale
- Lee County Mosquito Control District, Florida, United States of America
| | - William Petrie
- Miami-Dade County Mosquito Control, Florida, United States of America
| | - Robert C. Reiner
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America
| | - Michael T. Riles
- Beach Mosquito Control District, Florida, United States of America
| | - Henrik Salje
- Mathematical Modelling Unit, Institut Pasteur, Paris, France
| | - David L. Smith
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America
| | - John P. Smith
- Florida State University, Panama City, Florida, United States of America
| | - Amy Solis
- Clarke: Aquatic and Mosquito Control Services and Products, St. Charles, Illinois, United States of America
| | - Jason Stuck
- Pinellas County Mosquito Control, Stormwater and Vegetation Division, Florida, United States of America
| | - Chalmers Vasquez
- Miami-Dade County Mosquito Control, Florida, United States of America
| | - Katie F. Williams
- Manatee County Mosquito Control District, Florida, United States of America
| | - Rui-De Xue
- Brevard County Mosquito Control, Florida, United States of America
| | - Derek A. T. Cummings
- Department of Biology, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| |
Collapse
|
7
|
Merging High-Resolution Satellite Surface Radiation Data with Meteorological Sunshine Duration Observations over China from 1983 to 2017. REMOTE SENSING 2021. [DOI: 10.3390/rs13040602] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Surface solar radiation (Rs) is essential to climate studies. Thanks to long-term records from the Advanced Very High-Resolution Radiometers (AVHRR), the recent release of International Satellite Cloud Climatology Project (ISCCP) HXG cloud products provide a promising opportunity for building long-term Rs data with high resolutions (3 h and 10 km). In this study, we compare three satellite Rs products based on AVHRR cloud products over China from 1983 to 2017 with direct observations of Rs and sunshine duration (SunDu)-derived Rs. The results show that SunDu-derived Rs have higher accuracy than the direct observed Rs at time scales of a month or longer by comparing with the satellite Rs products. SunDu-derived Rs is available from the 1960s at more than 2000 stations over China, which provides reliable decadal estimations of Rs. However, the three AVHRR-based satellite Rs products have significant biases in quantifying the trend of Rs from 1983 to 2016 (−4.28 W/m2/decade to 2.56 W/m2/decade) due to inhomogeneity in satellite cloud products and the lack of information on atmospheric aerosol optical depth. To adjust the inhomogeneity of the satellite Rs products, we propose a geographically weighted regression fusion method (HGWR) to merge ISCCP-HXG Rs with SunDu-derived Rs. The merged Rs product over China from 1983 to 2017 with a spatial resolution of 10 km produces nearly the same trend as that of the SunDu-derived Rs. This study makes a first attempt to adjust the inhomogeneity of satellite Rs products and provides the merged high-resolution Rs product from 1983 to 2017 over China, which can be downloaded freely.
Collapse
|
8
|
Lau MJ, Ross PA, Endersby-Harshman NM, Hoffmann AA. Impacts of Low Temperatures on Wolbachia (Rickettsiales: Rickettsiaceae)-Infected Aedes aegypti (Diptera: Culicidae). JOURNAL OF MEDICAL ENTOMOLOGY 2020; 57:1567-1574. [PMID: 32307514 PMCID: PMC7566743 DOI: 10.1093/jme/tjaa074] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Indexed: 05/10/2023]
Abstract
In recent decades, the occurrence and distribution of arboviral diseases transmitted by Aedes aegypti mosquitoes has increased. In a new control strategy, populations of mosquitoes infected with Wolbachia are being released to replace existing populations and suppress arboviral disease transmission. The success of this strategy can be affected by high temperature exposure, but the impact of low temperatures on Wolbachia-infected Ae. aegypti is unclear, even though low temperatures restrict the abundance and distribution of this species. In this study, we considered low temperature cycles relevant to the spring season that are close to the distribution limits of Ae. aegypti, and tested the effects of these temperature cycles on Ae. aegypti, Wolbachia strains wMel and wAlbB, and Wolbachia phage WO. Low temperatures influenced Ae. aegypti life-history traits, including pupation, adult eclosion, and fertility. The Wolbachia-infected mosquitoes, especially wAlbB, performed better than uninfected mosquitoes. Temperature shift experiments revealed that low temperature effects on life history and Wolbachia density depended on the life stage of exposure. Wolbachia density was suppressed at low temperatures but densities recovered with adult age. In wMel Wolbachia there were no low temperature effects specific to Wolbachia phage WO. The findings suggest that Wolbachia-infected Ae. aegypti are not adversely affected by low temperatures, indicating that the Wolbachia replacement strategy is suitable for areas experiencing cool temperatures seasonally.
Collapse
Affiliation(s)
- Meng-Jia Lau
- Pest and Environmental Adaptation Research Group, Bio21 Institute and the School of BioSciences, The University of Melbourne, Parkville, Victoria, Australia
| | - Perran A Ross
- Pest and Environmental Adaptation Research Group, Bio21 Institute and the School of BioSciences, The University of Melbourne, Parkville, Victoria, Australia
| | - Nancy M Endersby-Harshman
- Pest and Environmental Adaptation Research Group, Bio21 Institute and the School of BioSciences, The University of Melbourne, Parkville, Victoria, Australia
| | - Ary A Hoffmann
- Pest and Environmental Adaptation Research Group, Bio21 Institute and the School of BioSciences, The University of Melbourne, Parkville, Victoria, Australia
| |
Collapse
|
9
|
Rostami AA, Isazadeh M, Shahabi M, Nozari H. Evaluation of geostatistical techniques and their hybrid in modelling of groundwater quality index in the Marand Plain in Iran. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2019; 26:34993-35009. [PMID: 31659709 DOI: 10.1007/s11356-019-06591-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 09/24/2019] [Indexed: 05/15/2023]
Abstract
In many parts of the world, groundwater is considered as one of the main sources of urban and rural drinking water. Over the past three decades, the qualitative and quantitative characteristics of aquifers have been negatively affected by different factors such as excessive use of chemical fertilizers in agriculture, indiscreet, and over-exploitation use of groundwater. Therefore, finding the effective method for mapping the water quality index (WQI) is important for locating suitable and non-suitable areas for urban and rural drinking waters. In the present paper, the best method to estimate the spatial distribution of WQI was assessed using the inverse distance weighted, kriging, cokriging, geographically weighted regression (GWR), and hybrid models. Creating hybrid models can increase modeling capabilities. Hybrid methods make use of a combination of estimated model capabilities. In addition, to improve the results of cokriging, GWR, and hybrid methods, the auxiliary parameters of land slope, groundwater table, and groundwater transmissibility were used. In order to assess the proposed methodology, 11 qualitative parameters obtained from 63 observation wells in Marand Plain (Iran) were utilized. Four statistical measures, namely the root mean square error (RMSE), the mean absolute error (MAE), the Akaike coefficient (AIC), and the correlation coefficient (R2) along with the Taylor diagram, have been done. Classification of the WQI index showed that the quality of a number of 1, 27, 18, and 17 wells was, respectively, in excellent, good, moderate, and poor grades. The results of modeling the WQI index based on IDW, kriging, cokriging, GWR, and hybrid methods showed that the best estimate of WQI was obtained by using hybrid GWR-kriging method with three input parameters of land slope, groundwater table, and groundwater transmissibility. Therefore, hybrid kriging and GWR methods have been fairly well able to simulate the WQI index.
Collapse
Affiliation(s)
| | - Mohammad Isazadeh
- Department of Water Engineering, University of Tabriz, Tabriz, Iran.
| | - Mahmoud Shahabi
- Department of Soil Science, University of Tabriz, Tabriz, Iran
| | - Hamed Nozari
- Department of Water Engineering, Bu-Ali Sina University, Hamedan, Iran
| |
Collapse
|
10
|
Hettiarachchige C, von Cavallar S, Lynar T, Hickson RI, Gambhir M. Risk prediction system for dengue transmission based on high resolution weather data. PLoS One 2018; 13:e0208203. [PMID: 30521550 PMCID: PMC6283552 DOI: 10.1371/journal.pone.0208203] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2018] [Accepted: 11/13/2018] [Indexed: 01/24/2023] Open
Abstract
BACKGROUND Dengue is the fastest spreading vector-borne viral disease, resulting in an estimated 390 million infections annually. Precise prediction of many attributes related to dengue is still a challenge due to the complex dynamics of the disease. Important attributes to predict include: the risk of and risk factors for an infection; infection severity; and the timing and magnitude of outbreaks. In this work, we build a model for predicting the risk of dengue transmission using high-resolution weather data. The level of dengue transmission risk depends on the vector density, hence we predict risk via vector prediction. METHODS AND FINDINGS We make use of surveillance data on Aedes aegypti larvae collected by the Taiwan Centers for Disease Control as part of the national routine entomological surveillance of dengue, and weather data simulated using the IBM's Containerized Forecasting Workflow, a high spatial- and temporal-resolution forecasting system. We propose a two stage risk prediction system for assessing dengue transmission via Aedes aegypti mosquitoes. In stage one, we perform a logistic regression to determine whether larvae are present or absent at the locations of interest using weather attributes as the explanatory variables. The results are then aggregated to an administrative division, with presence in the division determined by a threshold percentage of larvae positive locations resulting from a bootstrap approach. In stage two, larvae counts are estimated for the predicted larvae positive divisions from stage one, using a zero-inflated negative binomial model. This model identifies the larvae positive locations with 71% accuracy and predicts the larvae numbers producing a coverage probability of 98% over 95% nominal prediction intervals. This two-stage model improves the overall accuracy of identifying larvae positive locations by 29%, and the mean squared error of predicted larvae numbers by 9.6%, against a single-stage approach which uses a zero-inflated binomial regression approach. CONCLUSIONS We demonstrate a risk prediction system using high resolution weather data can provide valuable insight to the distribution of risk over a geographical region. The work also shows that a two-stage approach is beneficial in predicting risk in non-homogeneous regions, where the risk is localised.
Collapse
Affiliation(s)
- Chathurika Hettiarachchige
- IBM Research Australia, Southgate, Victoria, Australia
- School of Mathematics and Statistics, The University of Melbourne, Parkville, Victoria, Australia
| | | | - Timothy Lynar
- IBM Research Australia, Southgate, Victoria, Australia
| | - Roslyn I. Hickson
- IBM Research Australia, Southgate, Victoria, Australia
- School of Mathematics and Statistics, The University of Melbourne, Parkville, Victoria, Australia
| | - Manoj Gambhir
- IBM Research Australia, Southgate, Victoria, Australia
| |
Collapse
|
11
|
Ng KC, Chaves LF, Tsai KH, Chuang TW. Increased Adult Aedes aegypti and Culex quinquefasciatus (Diptera: Culicidae) Abundance in a Dengue Transmission Hotspot, Compared to a Coldspot, within Kaohsiung City, Taiwan. INSECTS 2018; 9:insects9030098. [PMID: 30104501 PMCID: PMC6164640 DOI: 10.3390/insects9030098] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Revised: 07/30/2018] [Accepted: 08/10/2018] [Indexed: 12/30/2022]
Abstract
The assumption that vector abundance differences might drive spatial and temporal heterogeneities in vector-borne disease transmission is common, though data supporting it is scarce. Here, we present data from two common mosquito species Aedes aegypti (Linnaeus) and Culex quinquefasciatus Say, biweekly sampled as adults, from March 2016 through December 2017, with BG-sentinel traps in two neighboring districts of Kaohsiung City (KC), Taiwan. One district has historically been a dengue transmission hotspot (Sanmin), and the other a coldspot (Nanzih). We collected a total 41,027 mosquitoes, and we found that average mosquito abundance (mean ± S.D.) was higher in Sanmin (Ae. aegypti: 9.03 ± 1.46; Cx. quinquefasciatus: 142.57 ± 14.38) than Nanzih (Ae. aegypti: 6.21 ± 0.47; Cx. quinquefasciatus: 63.37 ± 8.71) during the study period. In both districts, Ae. aegypti and Cx. quinquefasciatus population dynamics were sensitive to changes in temperature, the most platykurtic environmental variable at KC during the study period, a pattern predicted by Schmalhausen’s law, which states that organisms are more sensitive to small changes in environmental variables whose average value is more uncertain than its extremes. Our results also suggest that differences in Ae. aegypti abundance might be responsible for spatial differences in dengue transmission at KC. Our comparative approach, where we also observed a significant increment in the abundance of Cx. quinquefasciatus in the dengue transmission hotspot, suggests this area might be more likely to experience outbreaks of other vector borne diseases and should become a primary focus for vector surveillance and control.
Collapse
Affiliation(s)
- Ka-Chon Ng
- College of Public Health, National Taiwan University, Taipei 10055, 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.
| | - Kun-Hsien Tsai
- College of Public Health, National Taiwan University, Taipei 10055, Taiwan.
| | - 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.
| |
Collapse
|
12
|
Tsai PJ, Lin TH, Teng HJ, Yeh HC. Critical low temperature for the survival of Aedes aegypti in Taiwan. Parasit Vectors 2018; 11:22. [PMID: 29310716 PMCID: PMC5759216 DOI: 10.1186/s13071-017-2606-6] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2017] [Accepted: 12/25/2017] [Indexed: 11/17/2022] Open
Abstract
Background Taiwan is geographically located in a region that spans both tropical and subtropical climates (22–25°N and 120–122°E). The Taiwan Centers for Disease Control have found that the ecological habitat of Aedes aegypti appears only south of 23.5°N. Low temperatures may contribute to this particular habitat distribution of Ae. aegypti under the influence of the East Asian winter monsoon. However, the threshold condition related to critically low temperatures remains unclear because of the lack of large-scale spatial studies. This topic warrants further study, particularly through national entomological surveillance and satellite-derived land surface temperature (LST) data. Methods We hypothesized that the distribution of Ae. aegypti is highly correlated with the threshold nighttime LST and that a critical low LST limits the survival of Ae. aegypti. A mosquito dataset collected from the Taiwan Centers for Disease Control was utilized in conjunction with image data obtained from the moderate resolution imaging spectroradiometer (MODIS) during 2009–2011. Spatial interpolation and phi coefficient methods were used to analyze the correlation between the distributions of immature forms of Ae. aegypti and threshold LST, which was predicted from MODIS calculations for 348 townships in Taiwan. Results According to the evaluation of the correlation between estimated nighttime temperatures and the occurrence of Ae. aegypti, winter had the highest peak phi coefficient, and the corresponding estimated threshold temperatures ranged from 13.7 to 14 °C in the ordinary kriging model, which was the optimal interpolation model in terms of the root mean square error. The mean threshold temperature was determined to be 13.8 °C, which is a critical temperature to limit the occurrence of Ae. aegypti. Conclusions An LST of 13.8 °C was found to be the critical temperature for Ae. aegypti larvae, which results in the near disappearance of Ae. aegypti during winter in the subtropical regions of Taiwan under the influence of the prevailing East Asian winter monsoon.
Collapse
Affiliation(s)
- Pui-Jen Tsai
- Center for General Education, Aletheia University, New Taipei City, 25103, Taiwan, Republic of China
| | - Tang-Huang Lin
- Center for Space and Remote Sensing Research, National Central University, Jhongli, 32001, Taiwan, Republic of China
| | - Hwa-Jen Teng
- Center for Diagnostics and Vaccine Development, Centers for Disease Control, Taipei, Taiwan, Republic of China
| | - Hsi-Chyi Yeh
- Center for General Education, Aletheia University, New Taipei City, 25103, Taiwan, Republic of China.
| |
Collapse
|
13
|
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: 2.6] [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.
Collapse
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.
| |
Collapse
|