{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T14:01:52Z","timestamp":1772200912402,"version":"3.50.1"},"reference-count":135,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2020,6,23]],"date-time":"2020-06-23T00:00:00Z","timestamp":1592870400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41801336"],"award-info":[{"award-number":["41801336"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/ijerph17124509","type":"journal-article","created":{"date-parts":[[2020,6,23]],"date-time":"2020-06-23T09:05:33Z","timestamp":1592903133000},"page":"4509","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Semi-Supervised Text Classification Framework: An Overview of Dengue Landscape Factors and Satellite Earth Observation"],"prefix":"10.3390","volume":"17","author":[{"given":"Zhichao","family":"Li","sequence":"first","affiliation":[{"name":"Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System, Science, Tsinghua University, Beijing 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4250-6742","authenticated-orcid":false,"given":"Helen","family":"Gurgel","sequence":"additional","affiliation":[{"name":"Department of Geography, University of Brasilia (UnB), Brasilia CEP 70910-900, Brazil"},{"name":"International Joint Laboratory Sentinela, FIOCRUZ, UnB, IRD, Rio de Janeiro RJ-21040-900, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nadine","family":"Dessay","sequence":"additional","affiliation":[{"name":"International Joint Laboratory Sentinela, FIOCRUZ, UnB, IRD, Rio de Janeiro RJ-21040-900, Brazil"},{"name":"IRD, UM, UR, UG, UA, UMR ESPACE-DEV, 34090 Montpellier, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luojia","family":"Hu","sequence":"additional","affiliation":[{"name":"Qian Xuesen Laboratory of Space Technology, China Academy of Space Technology, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2566-2118","authenticated-orcid":false,"given":"Lei","family":"Xu","sequence":"additional","affiliation":[{"name":"Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System, Science, Tsinghua University, Beijing 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1513-3765","authenticated-orcid":false,"given":"Peng","family":"Gong","sequence":"additional","affiliation":[{"name":"Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System, Science, Tsinghua University, Beijing 100084, China"},{"name":"Center for Healthy Cities, Institute for China Sustainable Urbanization, Tsinghua University, Beijing 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,23]]},"reference":[{"key":"ref_1","unstructured":"WHO (2020, June 01). Dengue and Severe Dengue. Available online: https:\/\/www.who.int\/news-room\/fact-sheets\/detail\/dengue-and-severe-dengue."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Horstick, O., Tozan, Y., and Wilder-Smith, A. (2015). Reviewing dengue: Still a neglected tropical disease?. PLoS Negl. Trop. Dis., 9.","DOI":"10.1371\/journal.pntd.0003632"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1016\/j.cosust.2013.05.006","article-title":"Different ontologies: Land change science and health research","volume":"5","author":"Messina","year":"2013","journal-title":"Curr. Opin. Environ. Sustain."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1473","DOI":"10.1016\/j.mcna.2008.07.007","article-title":"Disease emergence from global climate and land use change","volume":"92","author":"Patz","year":"2008","journal-title":"Med. Clin. N. Am."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1352","DOI":"10.3390\/ijgi3041352","article-title":"Mapping Entomological Dengue Risk Levels in Martinique Using High-Resolution Remote-Sensing Environmental Data","volume":"3","author":"Machault","year":"2014","journal-title":"ISPRS Int. J. Geo Inf."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"889","DOI":"10.1111\/1365-2435.12487","article-title":"The ecological foundations of transmission potential and vector-borne disease in urban landscapes","volume":"29","author":"LaDeau","year":"2015","journal-title":"Funct. Ecol."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Parselia, E., Kontoes, C., Tsouni, A., Hadjichristodoulou, C., Kioutsioukis, I., Magiorkinis, G., and Stilianakis, N.I. (2019). Satellite Earth Observation Data in Epidemiological Modeling of Malaria, Dengue and West Nile Virus: A Scoping Review. Remote Sens., 11.","DOI":"10.3390\/rs11161862"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Sallam, M.F., Fizer, C., Pilant, A.N., and Whung, P.Y. (2017). Systematic Review: Land Cover, Meteorological, and Socioeconomic Determinants of Aedes mosquito Habitat for Risk Mapping. Int. J. Environ. Res. Public Health, 14.","DOI":"10.3390\/ijerph14101230"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Marti, R., Li, Z., Catry, T., Roux, E., Mangeas, M., Handschumacher, P., Gaudart, J., Tran, A., Demagistri, L., and Faure, J.-F. (2020). A Mapping Review on Urban Landscape Factors of Dengue Retrieved from Earth Observation Data, GIS Techniques, and Survey Questionnaires. Remote Sens., 12.","DOI":"10.3390\/rs12060932"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"467","DOI":"10.7326\/M18-0850","article-title":"PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation","volume":"169","author":"Tricco","year":"2018","journal-title":"Ann. Intern. Med."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"416","DOI":"10.12788\/jhm.3248","article-title":"Progress Notes: Methods for Research Evidence Synthesis: The Scoping Review Approach","volume":"14","author":"Sucharew","year":"2019","journal-title":"J. Hosp. Med."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1016\/0306-4573(88)90021-0","article-title":"Term-weighting approaches in automatic text retrieval","volume":"24","author":"Salton","year":"1988","journal-title":"Inf. Process. Manag."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1498","DOI":"10.1016\/j.eswa.2013.08.047","article-title":"Automatic text classification to support systematic reviews in medicine","volume":"41","year":"2014","journal-title":"Expert Syst. Appl."},{"key":"ref_14","first-page":"1","article-title":"Machine learning algorithms for systematic review: Reducing workload in a preclinical review of animal studies and reducing human screening error","volume":"8","author":"Thomas","year":"2019","journal-title":"Syst. Rev."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/2046-4053-3-74","article-title":"Systematic review automation technologies","volume":"3","author":"Tsafnat","year":"2014","journal-title":"Syst. Rev."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1016\/j.neucom.2019.01.078","article-title":"Bidirectional LSTM with attention mechanism and convolutional layer for text classification","volume":"337","author":"Liu","year":"2019","journal-title":"Neurocomputing"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1016\/j.procs.2017.06.037","article-title":"CNN for situations understanding based on sentiment analysis of twitter data","volume":"111","author":"Liao","year":"2017","journal-title":"Procedia Comput. Sci."},{"key":"ref_18","first-page":"277","article-title":"Stacked residual recurrent neural network with word weight for text classification","volume":"44","author":"Cao","year":"2017","journal-title":"IAENG Int. J. Comput. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long Short-Term Memory","volume":"9","author":"Hochreiter","year":"1997","journal-title":"Neural Comput."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"An, B., Wu, W., and Han, H. (2018). Deep Active Learning for Text Classification. Proceedings of the 2nd International Conference on Vision, Image and Signal Processing, ACM.","DOI":"10.1145\/3271553.3271578"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Yang, L., MacEachren, A., Mitra, P., and Onorati, T. (2018). Visually-Enabled Active Deep Learning for (Geo) Text and Image Classification: A Review. ISPRS Int. J. Geo Inf., 7.","DOI":"10.3390\/ijgi7020065"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"536","DOI":"10.1016\/j.neucom.2013.04.017","article-title":"Active deep learning method for semi-supervised sentiment classification","volume":"120","author":"Zhou","year":"2013","journal-title":"Neurocomputing"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2673","DOI":"10.1109\/78.650093","article-title":"Bidirectional recurrent neural networks","volume":"45","author":"Schuster","year":"1997","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_24","unstructured":"Mikolov, T., Chen, K., Corrado, G., and Dean, J. (2013, January 2\u20134). Efficient Estimation of Word Representations in Vector Space. Proceedings of the International Conference on Learning Representations 2013, Scottsdale, AZ, USA."},{"key":"ref_25","first-page":"39","article-title":"A c-lstm neural network for text classification","volume":"1","author":"Zhou","year":"2015","journal-title":"Comput. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Hamm, N.A.S., Soares Magalh\u00e3es, R.J., and Clements, A.C.A. (2015). Earth Observation, Spatial Data Quality, and Neglected Tropical Diseases. PLoS Negl. Trop. Dis., 9.","DOI":"10.1371\/journal.pntd.0004164"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/S0034-4257(02)00096-2","article-title":"Overview of the radiometric and biophysical performance of the MODIS vegetation indices","volume":"83","author":"Huete","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Li, Z., Roux, E., Dessay, N., Girod, R., Stefani, A., Nacher, M., Moiret, A., and Seyler, F. (2016). Mapping a Knowledge-Based Malaria Hazard Index Related to Landscape Using Remote Sensing: Application to the Cross-Border Area between French Guiana and Brazil. Remote Sens., 8.","DOI":"10.3390\/rs8040319"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Li, Z., Catry, T., Dessay, N., da Costa Gurgel, H., Aparecido de Almeida, C., Barcellos, C., and Roux, E. (2017). Regionalization of a Landscape-Based Hazard Index of Malaria Transmission: An Example of the State of Amap\u00e1, Brazil. Data, 2.","DOI":"10.3390\/data2040037"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/j.scib.2019.12.007","article-title":"Mapping essential urban land use categories in China (EULUC-China): Preliminary results for 2018","volume":"65","author":"Gong","year":"2020","journal-title":"Sci. Bull."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Catry, T., Pottier, A., Marti, R., Li, Z., Roux, E., Herbreteau, V., Mangeas, M., Demagistri, L., Gurgel, H., and Dessay, N. (2018). Apports de la combinaison d\u2019images satellites optique et RADAR dans l\u2019\u00e9tude des maladies \u00e0 transmission vectorielle: Cas du paludisme \u00e0 la fronti\u00e8re Guyane fran\u00e7aise\u2013Br\u00e9sil. Confins, 37.","DOI":"10.4000\/confins.15027"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Catry, T., Li, Z., Roux, E., Herbreteau, V., Gurgel, H., Mangeas, M., Seyler, F., and Dessay, N. (2018). Wetlands and Malaria in the Amazon: Guidelines for the Use of Synthetic Aperture Radar Remote-Sensing. Int. J. Environ. Res. Public Health, 15.","DOI":"10.3390\/ijerph15030468"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Xu, J., Xu, K., Li, Z., Meng, F., Tu, T., Xu, L., and Liu, Q. (2020). Forecast of Dengue Cases in 20 Chinese Cities Based on the Deep Learning Method. Int. J. Environ. Res. Public Health, 17.","DOI":"10.3390\/ijerph17020453"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Laureano-Rosario, A.E., Duncan, A.P., Mendez-Lazaro, P.A., Garcia-Rejon, J.E., Gomez-Carro, S., Farfan-Ale, J., Savic, D.A., and Muller-Karger, F.E. (2018). Application of Artificial Neural Networks for Dengue Fever Outbreak Predictions in the Northwest Coast of Yucatan, Mexico and San Juan, Puerto Rico. Trop. Med. Infect. Dis., 3.","DOI":"10.3390\/tropicalmed3010005"},{"key":"ref_35","unstructured":"Rehman, N.A., Saif, U., and Chunara, R. (2019, January 15\u201320). Deep Landscape Features for Improving Vector-borne Disease Prediction. Proceedings of the 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recongnition (CVPR), Long Beach, CA, USA."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Acharya, B.K., Cao, C., Xu, M., Khanal, L., Naeem, S., and Pandit, S. (2018). Temporal Variations and Associated Remotely Sensed Environmental Variables of Dengue Fever in Chitwan District, Nepal. ISPRS Int. J. Geo Inf., 7.","DOI":"10.3390\/ijgi7070275"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1973","DOI":"10.1007\/s00484-018-1601-8","article-title":"Modeling the spatially varying risk factors of dengue fever in Jhapa district, Nepal, using the semi-parametric geographically weighted regression model","volume":"62","author":"Acharya","year":"2018","journal-title":"Int. J. Biometeorol."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Akter, R., Naish, S., Hu, W., and Tong, S. (2017). Socio-demographic, ecological factors and dengue infection trends in Australia. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0185551"},{"key":"ref_39","first-page":"135","article-title":"Urban environmental clustering to assess the spatial dynamics of Aedes aegypti breeding sites","volume":"13","author":"Espinosa","year":"2018","journal-title":"Geospat. Health"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1007\/s41324-018-0187-x","article-title":"Using analytic hierarchy process with GIS for Dengue risk mapping in Kolkata Municipal Corporation, West Bengal, India","volume":"26","author":"Ahmad","year":"2018","journal-title":"Spat. Inf. Res."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Anno, S., Imaoka, K., Tadono, T., Igarashi, T., Sivaganesh, S., Kannathasan, S., Kumaran, V., and Surendran, S.N. (2015). Space-time clustering characteristics of dengue based on ecological, socio-economic and demographic factors in northern Sri Lanka. Geospat. Health, 10.","DOI":"10.4081\/gh.2015.376"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.bjid.2014.10.004","article-title":"Sao Paulo urban heat islands have a higher incidence of dengue than other urban areas","volume":"19","author":"Araujo","year":"2015","journal-title":"Braz. J. Infect. Dis."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"3040","DOI":"10.3390\/ijerph6123040","article-title":"Mapping Environmental Dimensions of Dengue Fever Transmission Risk in the Aburr\u00e1 Valley, Colombia","volume":"6","author":"Arboleda","year":"2009","journal-title":"Int. J. Environ. Res. Public Health"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1111\/j.1948-7134.2012.00198.x","article-title":"Spatial and temporal dynamics of Aedes aegypti larval sites in Bello, Colombia","volume":"37","author":"Arboleda","year":"2012","journal-title":"J. Vector Ecol."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Ashby, J., Moreno-Madrinan, M.J., Yiannoutsos, C.T., and Stanforth, A. (2017). Niche Modeling of Dengue Fever Using Remotely Sensed Environmental Factors and Boosted Regression Trees. Remote Sens., 9.","DOI":"10.3390\/rs9040328"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1016\/j.actatropica.2016.02.018","article-title":"Risk analysis for dengue suitability in Africa using the ArcGIS predictive analysis tools (PA tools)","volume":"158","author":"Attaway","year":"2016","journal-title":"Acta Trop."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"91","DOI":"10.4103\/0972-9062.134805","article-title":"Spatial density of Aedes distribution in urban areas: A case study of breteau index in Kuala Lumpur, Malaysia","volume":"51","author":"Aziz","year":"2014","journal-title":"J. Vector Borne Dis."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1623","DOI":"10.1007\/s10530-012-0177-1","article-title":"Spread of invasive Aedes albopictus and decline of resident Aedes aegypti in urban areas of Mayotte 2007\u20132010","volume":"14","author":"Arnoux","year":"2012","journal-title":"Biol. Invasions"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Bett, B., Grace, D., Lee, H.S., Lindahl, J., Nguyen-Viet, H., Phuc, P.D., Quyen, N.H., Tu, T.A., Phu, T.D., and Tan, D.Q. (2019). Spatiotemporal analysis of historical records (2001\u20132012) on dengue fever in Vietnam and development of a statistical model for forecasting risk. PLoS ONE, 14.","DOI":"10.1371\/journal.pone.0224353"},{"key":"ref_50","first-page":"45","article-title":"Developing a Statistical Dengue Risk Prediction Model for the State of Delhi Based on Various Environmental Variables","volume":"8","author":"Bhardwaj","year":"2012","journal-title":"Int. J. Geoinform."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Buczak, A.L., Koshute, P.T., Babin, S.M., Feighner, B.H., and Lewis, S.H. (2012). A data-driven epidemiological prediction method for dengue outbreaks using local and remote sensing data. BMC Med. Inform. Decis. Mak., 12.","DOI":"10.1186\/1472-6947-12-124"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Carvalho, M.S., Buczak, A.L., Baugher, B., Babin, S.M., Ramac-Thomas, L.C., Guven, E., Elbert, Y., Koshute, P.T., Velasco, J.M.S., and Roque, V.G. (2014). Prediction of High Incidence of Dengue in the Philippines. PLoS Negl. Trop. Dis., 8.","DOI":"10.1371\/journal.pntd.0002771"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1007\/s12518-019-00282-7","article-title":"Towards a Web GIS-based approach for mapping a dengue outbreak","volume":"12","author":"Butt","year":"2019","journal-title":"Appl. Geomat."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Cao, Z., Liu, T., Li, X., Wang, J., Lin, H., Chen, L., Wu, Z., and Ma, W. (2017). Individual and Interactive Effects of Socio-Ecological Factors on Dengue Fever at Fine Spatial Scale: A Geographical Detector-Based Analysis. Int. J. Environ. Res. Public Health, 14.","DOI":"10.3390\/ijerph14070795"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1046\/j.1365-3156.2001.00693.x","article-title":"Dengue transmission risk maps of Argentina","volume":"6","author":"Carbajo","year":"2001","journal-title":"Trop. Med. Int. Health"},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Chen, Y., Ong, J.H.Y., Rajarethinam, J., Yap, G., Ng, L.C., and Cook, A.R. (2018). Neighbourhood level real-time forecasting of dengue cases in tropical urban Singapore. BMC Med., 16.","DOI":"10.1186\/s12916-018-1108-5"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Chen, Y., Zhao, Z., Li, Z., Li, W., Li, Z., Guo, R., and Yuan, Z. (2019). Spatiotemporal Transmission Patterns and Determinants of Dengue Fever: A Case Study of Guangzhou, China. Int. J. Environ. Res. Public Health, 16.","DOI":"10.3390\/ijerph16142486"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.sste.2014.05.002","article-title":"Assessment of land use factors associated with dengue cases in Malaysia using Boosted Regression Trees","volume":"10","author":"Cheong","year":"2014","journal-title":"Spat. Spatio Temporal Epidemiol."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Chiu, C.-H., Wen, T.-H., Chien, L.-C., and Yu, H.-L. (2014). A Probabilistic Spatial Dengue Fever Risk Assessment by a Threshold-Based-Quantile Regression Method. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0106334"},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Chuang, T.-W., Ng, K.-C., Nguyen, T., and Chaves, L. (2018). Epidemiological Characteristics and Space-Time Analysis of the 2015 Dengue Outbreak in the Metropolitan Region of Tainan City, Taiwan. Int. J. Environ. Res. Public Health, 15.","DOI":"10.3390\/ijerph15030396"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"820","DOI":"10.4269\/ajtmh.2007.76.820","article-title":"Habitat segregation of dengue vectors along an urban environmental gradient","volume":"76","author":"Cox","year":"2007","journal-title":"Am. J. Trop. Med. Hyg."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"101437","DOI":"10.1016\/j.tmaid.2019.06.008","article-title":"Spatial and temporal variation of dengue incidence in the island of Bali, Indonesia: An ecological study","volume":"32","author":"Dhewantara","year":"2019","journal-title":"Travel Med. Infect. Dis."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1080\/10106049.2012.696726","article-title":"Coupling of remote sensing data and environmental-related parameters for dengue transmission risk assessment in Subang Jaya, Malaysia","volume":"28","author":"Dom","year":"2013","journal-title":"Geocarto Int."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"e0004621","DOI":"10.1371\/journal.pntd.0004621","article-title":"Temporal Dynamics and Spatial Patterns of Aedes aegypti Breeding Sites, in the Context of a Dengue Control Program in Tartagal (Salta Province, Argentina)","volume":"10","author":"Espinosa","year":"2016","journal-title":"PLoS Negl. Trop. Dis."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"247","DOI":"10.4081\/gh.2018.734","article-title":"Operational satellite-based temporal modelling of Aedes population in Argentina","volume":"13","author":"Espinosa","year":"2018","journal-title":"Geospat. Health"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"5461","DOI":"10.1109\/JSTARS.2016.2604577","article-title":"MODIS Environmental Data to Assess Chikungunya, Dengue, and Zika Diseases Through Aedes (Stegomia) aegypti Oviposition Activity Estimation","volume":"9","author":"Benitez","year":"2016","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Fareed, N., Ghaffar, A., and Malik, T.S. (2016). Spatio-Temporal Extension and Spatial Analyses of Dengue from Rawalpindi, Islamabad and Swat during 2010\u20132014. Climate, 4.","DOI":"10.3390\/cli4020023"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1111\/tmi.12664","article-title":"Species Distribution Modelling of Aedes aegypti in two dengue-endemic regions of Pakistan","volume":"21","author":"Fatima","year":"2016","journal-title":"Trop. Med. Int. Health"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"014011","DOI":"10.1088\/1748-9326\/4\/1\/014011","article-title":"El Ni\u00f1o Southern Oscillation and vegetation dynamics as predictors of dengue fever cases in Costa Rica","volume":"4","author":"Fuller","year":"2009","journal-title":"Environ. Res. Lett."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1080\/01431160902865756","article-title":"Dengue vector (Aedes aegypti) larval habitats in an urban environment of Costa Rica analysed with ASTER and QuickBird imagery","volume":"31","author":"Fuller","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_71","first-page":"53","article-title":"An examination of the spatial factors of dengue cases in Quezon City, Philippines: A Geographic Information System (GLS)-based approach, 2005\u20132008","volume":"45","author":"Garcia","year":"2011","journal-title":"Acta Med. Philipp."},{"key":"ref_72","first-page":"231","article-title":"Exploring satellite based temporal forecast modelling of Aedes aegypti oviposition from an operational perspective","volume":"11","author":"German","year":"2018","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"1002","DOI":"10.1111\/tmi.13125","article-title":"Patterns of occurrence of dengue and chikungunya, and spatial distribution of mosquito vector Aedes albopictus in Swabi district, Pakistan","volume":"23","author":"Hira","year":"2018","journal-title":"Trop. Med. Int. Health"},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Huang, C.C., Tam, T.Y.T., Chern, Y.R., Lung, S.C., Chen, N.T., and Wu, C.D. (2018). Spatial Clustering of Dengue Fever Incidence and Its Association with Surrounding Greenness. Int. J. Environ. Res. Public Health, 15.","DOI":"10.3390\/ijerph15091869"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"888","DOI":"10.1111\/tmi.13248","article-title":"Forest cover and climate as potential drivers for dengue fever in Sumatra and Kalimantan 2006\u20132016: A spatiotemporal analysis","volume":"24","author":"Husnina","year":"2019","journal-title":"Trop. Med. Int. Health"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"13","DOI":"10.21010\/ajid.v12i1S.3","article-title":"Determination of Environmental Factors Affecting Dengue Incidence in Sleman District, Yogyakarta, Indonesia","volume":"12","author":"Kesetyaningsih","year":"2018","journal-title":"Afr. J. Infect. Dis."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1007\/s00484-014-0840-6","article-title":"Dengue transmission based on urban environmental gradients in different cities of Pakistan","volume":"59","author":"Khalid","year":"2014","journal-title":"Int. J. Biometeorol."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"1721","DOI":"10.1007\/s00484-015-0982-1","article-title":"Environmental risk factors and hotspot analysis of dengue distribution in Pakistan","volume":"59","author":"Khalid","year":"2015","journal-title":"Int. J. Biometeorol."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"4713","DOI":"10.1016\/j.scitotenv.2011.08.028","article-title":"Modeling dengue fever risk based on socioeconomic parameters, nationality and age groups: GIS and remote sensing based case study","volume":"409","author":"Khormi","year":"2011","journal-title":"Sci. Total Environ."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2012\/907494","article-title":"Ecologic and Sociodemographic Risk Determinants for Dengue Transmission in Urban Areas in Thailand","volume":"2012","author":"Koyadun","year":"2012","journal-title":"Interdiscip. Perspect. Infect. Dis."},{"key":"ref_81","doi-asserted-by":"crossref","unstructured":"Barrera, R., Lana, R.M., da Costa Gomes, M.F., de Lima, T.F.M., Hon\u00f3rio, N.A., and Code\u00e7o, C.T. (2017). The introduction of dengue follows transportation infrastructure changes in the state of Acre, Brazil: A network-based analysis. PLoS Negl. Trop. Dis., 11.","DOI":"10.1371\/journal.pntd.0006070"},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1111\/j.1948-7134.2012.00245.x","article-title":"Fine scale spatial urban land cover factors associated with adult mosquito abundance and risk in Tucson, Arizona","volume":"37","author":"Landau","year":"2012","journal-title":"J. Vector Ecol."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1007\/s10393-019-01457-9","article-title":"Human Activities Attract Harmful Mosquitoes in a Tropical Urban Landscape","volume":"17","author":"Lee","year":"2019","journal-title":"EcoHealth"},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1177\/1010539511418819","article-title":"Abiotic determinants to the spatial dynamics of dengue fever in Guangzhou","volume":"25","author":"Li","year":"2013","journal-title":"Asia Pac. J. Public Health"},{"key":"ref_85","first-page":"85","article-title":"Spatial, environmental and entomological risk factors analysis on a rural dengue outbreak in Lundu District in Sarawak, Malaysia","volume":"23","author":"Cheah","year":"2006","journal-title":"Trop. Biomed."},{"key":"ref_86","doi-asserted-by":"crossref","unstructured":"Lippi, C.A., Stewart-Ibarra, A.M., Loor, M., Zambrano, J.E.D., Lopez, N.A.E., Blackburn, J.K., and Ryan, S.J. (2019). Geographic shifts in Aedes aegypti habitat suitability in Ecuador using larval surveillance data and ecological niche modeling: Implications of climate change for public health vector control. PLoS Negl. Trop. Dis., 13.","DOI":"10.1371\/journal.pntd.0007322"},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1007\/s10393-011-0708-8","article-title":"Co-occurrence patterns of the dengue vector Aedes aegypti and Aedes mediovitattus, a dengue competent mosquito in Puerto Rico","volume":"8","author":"Little","year":"2011","journal-title":"Ecohealth"},{"key":"ref_88","doi-asserted-by":"crossref","unstructured":"Little, E., Bajwa, W., and Shaman, J. (2017). Local environmental and meteorological conditions influencing the invasive mosquito Ae. albopictus and arbovirus transmission risk in New York City. PLoS Negl. Trop. Dis., 11.","DOI":"10.1371\/journal.pntd.0005828"},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"1183","DOI":"10.1093\/jme\/tjx103","article-title":"Socio-Ecological Mechanisms Supporting High Densities of Aedes albopictus (Diptera: Culicidae) in Baltimore, MD","volume":"54","author":"Little","year":"2017","journal-title":"J. Med. Entomol."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.ijid.2018.09.003","article-title":"Spatiotemporal patterns and determinants of dengue at county level in China from 2005\u20132017","volume":"77","author":"Liu","year":"2018","journal-title":"Int. J. Infect. Dis."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"902","DOI":"10.4269\/ajtmh.2012.12-0244","article-title":"The dengue virus mosquito vector Aedes aegypti at high elevation in Mexico","volume":"87","author":"Hayden","year":"2012","journal-title":"Am. J. Trop. Med. Hyg."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.actatropica.2012.05.001","article-title":"Impact of road networks on the distribution of dengue fever cases in Trinidad, West Indies","volume":"123","author":"Mahabir","year":"2012","journal-title":"Acta Trop."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1007\/s10661-018-7162-9","article-title":"Spatiotemporal analysis of dengue outbreaks in Samanabad town, Lahore metropolitan area, using geospatial techniques","volume":"191","author":"Mahmood","year":"2019","journal-title":"Environ. Monit. Assess."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"2267","DOI":"10.1016\/j.scitotenv.2018.09.357","article-title":"Implications of meteorological and physiographical parameters on dengue fever occurrences in Delhi","volume":"650","author":"Mala","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_95","first-page":"1587","article-title":"Spatiotemporal modeling of relative risk of dengue disease in Colombia","volume":"32","author":"Prieto","year":"2017","journal-title":"Stoch. Environ. Res. Risk Assess."},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1186\/s12942-017-0104-x","article-title":"Relative risk estimation of dengue disease at small spatial scale","volume":"16","year":"2017","journal-title":"Int. J. Health Geogr."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"1509","DOI":"10.1093\/jme\/tjy117","article-title":"Land Use and Larval Habitat Increase Aedes albopictus (Diptera: Culicidae) and Culex quinquefasciatus (Diptera: Culicidae) Abundance in Lowland Hawaii","volume":"55","author":"McClure","year":"2018","journal-title":"J. Med. Entomol."},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"1508","DOI":"10.1038\/s41564-019-0476-8","article-title":"The current and future global distribution and population at risk of dengue","volume":"4","author":"Messina","year":"2019","journal-title":"Nat. Microbiol."},{"key":"ref_99","doi-asserted-by":"crossref","unstructured":"Murdock, C.C., Evans, M.V., McClanahan, T.D., Miazgowicz, K.L., and Tesla, B. (2017). Fine-scale variation in microclimate across an urban landscape shapes variation in mosquito population dynamics and the potential of Aedes albopictus to transmit arboviral disease. PLoS Negl. Trop. Dis., 11.","DOI":"10.1371\/journal.pntd.0005640"},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1186\/1476-072X-4-13","article-title":"An information value based analysis of physical and climatic factors affecting dengue fever and dengue haemorrhagic fever incidence","volume":"4","author":"Nakhapakorn","year":"2005","journal-title":"Int. J. Health Geogr."},{"key":"ref_101","doi-asserted-by":"crossref","first-page":"1660","DOI":"10.3389\/fmicb.2017.01660","article-title":"Potential Risk Areas of Aedes albopictus in South-Eastern Iran: A Vector of Dengue Fever, Zika, and Chikungunya","volume":"8","author":"Nejati","year":"2017","journal-title":"Front. Microbiol."},{"key":"ref_102","first-page":"427","article-title":"Potential association of dengue hemorrhagic fever incidence and remote senses land surface temperature, Thailand, 1998","volume":"38","author":"Nitatpattana","year":"2007","journal-title":"Southeast Asian J. Trop. Med. Public Health"},{"key":"ref_103","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1029\/2019GH000186","article-title":"Spatial-Temporal Assessment of Environmental Factors Related to Dengue Outbreaks in S\u00e3o Paulo, Brazil","volume":"3","author":"Ogashawara","year":"2019","journal-title":"GeoHealth"},{"key":"ref_104","doi-asserted-by":"crossref","first-page":"60","DOI":"10.4103\/1995-7645.250838","article-title":"Modeling and predicting dengue fever cases in key regions of the Philippines using remote sensing data","volume":"12","author":"Clemente","year":"2019","journal-title":"Asian Pac. J. Trop. Med."},{"key":"ref_105","doi-asserted-by":"crossref","unstructured":"Qu, Y., Shi, X., Wang, Y., Li, R., Lu, L., and Liu, Q. (2018). Effects of socio-economic and environmental factors on the spatial heterogeneity of dengue fever investigated at a fine scale. Geospat. Health, 13.","DOI":"10.4081\/gh.2018.682"},{"key":"ref_106","first-page":"1493","article-title":"The distribution of Aedes aegypti (diptera, culicidae) in eight selected parks of Lahore, using oviposition traps during rainy season","volume":"67","author":"Qureshi","year":"2017","journal-title":"J. Pak. Med Assoc."},{"key":"ref_107","doi-asserted-by":"crossref","first-page":"49","DOI":"10.3923\/je.2017.49.57","article-title":"Forecasting of Dengue Disease Incident Risks Using Non-stationary Spatial of Geostatistics Model in Bone Regency Indonesia","volume":"14","author":"Rahim","year":"2016","journal-title":"J. Entomol."},{"key":"ref_108","doi-asserted-by":"crossref","unstructured":"Ren, H., Wu, W., Li, T., and Yang, Z. (2019). Urban villages as transfer stations for dengue fever epidemic: A case study in the Guangzhou, China. PLoS Negl. Trop. Dis., 13.","DOI":"10.1371\/journal.pntd.0007350"},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"863","DOI":"10.1111\/tmi.12325","article-title":"National spatial and temporal patterns of notified dengue cases, Colombia 2007\u20132010","volume":"19","author":"Restrepo","year":"2014","journal-title":"Trop. Med. Int. Health"},{"key":"ref_110","doi-asserted-by":"crossref","first-page":"976","DOI":"10.1093\/jmedent\/43.5.976","article-title":"Spatial Analysis of Aedes albopictus (Diptera: Culicidae) Oviposition in Suburban Neighborhoods of a Piedmont Community in North Carolina","volume":"43","author":"Richards","year":"2006","journal-title":"J. Med Entomol."},{"key":"ref_111","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.actatropica.2013.08.008","article-title":"Using global maps to predict the risk of dengue in Europe","volume":"129","author":"Rogers","year":"2014","journal-title":"Acta Trop."},{"key":"ref_112","doi-asserted-by":"crossref","first-page":"641","DOI":"10.4257\/oeco.2010.1403.04","article-title":"Dengue and Land Cover Heterogeneity in Rio De Janeiro","volume":"14","author":"Freitas","year":"2010","journal-title":"Oecologia Aust."},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.actatropica.2007.05.003","article-title":"Space\u2013time analysis of the dengue spreading dynamics in the 2004 Tartagal outbreak, Northern Argentina","volume":"103","author":"Rotela","year":"2007","journal-title":"Acta Trop."},{"key":"ref_114","doi-asserted-by":"crossref","first-page":"1073","DOI":"10.1007\/s10708-018-9909-9","article-title":"Identification of dengue risk zone: A geo-medical study on Madurai city","volume":"84","author":"Saravanabavan","year":"2018","journal-title":"GeoJournal"},{"key":"ref_115","doi-asserted-by":"crossref","unstructured":"Sarfraz, M.S., Tripathi, N.K., Tipdecho, T., Thongbu, T., Kerdthong, P., and Souris, M. (2012). Analyzing the spatio-temporal relationship between dengue vector larval density and land-use using factor analysis and spatial ring mapping. BMC Public Health, 12.","DOI":"10.1186\/1471-2458-12-853"},{"key":"ref_116","doi-asserted-by":"crossref","first-page":"916","DOI":"10.1080\/17538947.2013.786144","article-title":"Near real-time characterisation of urban environments: A holistic approach for monitoring dengue fever risk areas","volume":"7","author":"Sarfraz","year":"2013","journal-title":"Int. J. Digit. Earth"},{"key":"ref_117","doi-asserted-by":"crossref","first-page":"S685","DOI":"10.4081\/gh.2014.297","article-title":"Mapping urban and peri-urban breeding habitats of Aedes mosquitoes using a fuzzy analytical hierarchical process based on climatic and physical parameters","volume":"8","author":"Sarfraz","year":"2014","journal-title":"Geospat. Health"},{"key":"ref_118","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1016\/j.actatropica.2018.05.003","article-title":"Modeling Dengue vector population using remotely sensed data and machine learning","volume":"185","author":"Scavuzzo","year":"2018","journal-title":"Acta Trop."},{"key":"ref_119","first-page":"937","article-title":"Evaluation of the Spatial Risk Factors for High Incidence of Dengue Fever and Dengue Hemorrhagic Fever Using GIS Application","volume":"40","author":"Shafie","year":"2011","journal-title":"Sains Malays."},{"key":"ref_120","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1007\/s10653-014-9655-y","article-title":"Assessment of changes of vector borne diseases with wetland characteristics using multivariate analysis","volume":"37","author":"Sheela","year":"2014","journal-title":"Environ. Geochem. Health"},{"key":"ref_121","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1016\/j.landusepol.2017.01.047","article-title":"Assessment of relation of land use characteristics with vector-borne diseases in tropical areas","volume":"63","author":"Sheela","year":"2017","journal-title":"Land Use Policy"},{"key":"ref_122","doi-asserted-by":"crossref","unstructured":"Stanforth, A., Moreno-Madrinan, M.J., and Ashby, J. (2016). Exploratory Analysis of Dengue Fever Niche Variables within the Rio Magdalena Watershed. Remote Sens., 8.","DOI":"10.3390\/rs8090770"},{"key":"ref_123","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1007\/s42452-019-0428-1","article-title":"Geostatistical modeling of dengue disease in Lahore, Pakistan","volume":"1","author":"Tariq","year":"2019","journal-title":"SN Appl. Sci."},{"key":"ref_124","doi-asserted-by":"crossref","unstructured":"Teurlai, M., Menk\u00e8s, C.E., Cavarero, V., Degallier, N., Descloux, E., Grangeon, J.-P., Guillaumot, L., Libourel, T., Lucio, P.S., and Mathieu-Daud\u00e9, F. (2015). Socio-economic and Climate Factors Associated with Dengue Fever Spatial Heterogeneity: A Worked Example in New Caledonia. PLoS Negl. Trop. Dis., 9.","DOI":"10.1371\/journal.pntd.0004211"},{"key":"ref_125","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/j.envres.2016.05.039","article-title":"Surface water areas significantly impacted 2014 dengue outbreaks in Guangzhou, China","volume":"150","author":"Tian","year":"2016","journal-title":"Environ. Res."},{"key":"ref_126","first-page":"587","article-title":"Evaluation of land cover and prevalence of dengue in Malaysia","volume":"32","author":"Tiong","year":"2015","journal-title":"Trop. Biomed."},{"key":"ref_127","doi-asserted-by":"crossref","first-page":"191","DOI":"10.4081\/gh.2011.171","article-title":"Socio-geographical factors in vulnerability to dengue in Thai villages: A spatial regression analysis","volume":"5","author":"Tipayamongkholgul","year":"2011","journal-title":"Geospat. Health"},{"key":"ref_128","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1111\/j.1467-9493.2009.00367.x","article-title":"Urban structure and dengue fever in Puntarenas, Costa Rica","volume":"30","author":"Troyo","year":"2009","journal-title":"Singap. J. Trop. Geogr."},{"key":"ref_129","doi-asserted-by":"crossref","first-page":"222","DOI":"10.2987\/8756-971X(2006)22[222:DSDOAA]2.0.CO;2","article-title":"Different Spatial Distribution of Aedes aegypti and Aedes albopictus along an Urban\u2013Rural Gradient and the Relating Environmental Factors Examined in Three Villages in Northern Thailand","volume":"22","author":"Tsuda","year":"2006","journal-title":"J. Am. Mosq. Control Assoc."},{"key":"ref_130","doi-asserted-by":"crossref","first-page":"201","DOI":"10.4269\/ajtmh.2005.72.201","article-title":"Spatial patterns of and risk factors for seropositivity for dengue infection","volume":"72","author":"Vanwambeke","year":"2005","journal-title":"Am. J. Trop. Med. Hyg."},{"key":"ref_131","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1186\/1476-072X-5-5","article-title":"Multi-level analyses of spatial and temporal determinants for dengue infection","volume":"5","author":"Vanwambeke","year":"2006","journal-title":"Int. J. Health Geogr."},{"key":"ref_132","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/j.actatropica.2005.03.010","article-title":"Detailed assessment of microhabitat suitability for Aedes aegypti (Diptera: Culicidae) in Buenos Aires, Argentina","volume":"95","author":"Vezzani","year":"2005","journal-title":"Acta Trop."},{"key":"ref_133","doi-asserted-by":"crossref","unstructured":"Wiese, D., Escalante, A.A., Murphy, H., Henry, K.A., and Gutierrez-Velez, V.H. (2019). Integrating environmental and neighborhood factors in MaxEnt modeling to predict species distributions: A case study of Aedes albopictus in southeastern Pennsylvania. PLoS ONE, 14.","DOI":"10.1371\/journal.pone.0223821"},{"key":"ref_134","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.ijid.2018.07.023","article-title":"Spatial analysis of dengue fever and exploration of its environmental and socio-economic risk factors using ordinary least squares: A case study in five districts of Guangzhou City, China, 2014","volume":"75","author":"Yue","year":"2018","journal-title":"Int. J. Infect. Dis."},{"key":"ref_135","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1186\/s40249-019-0533-9","article-title":"Spatiotemporal characteristics and primary influencing factors of typical dengue fever epidemics in China","volume":"8","author":"Zheng","year":"2019","journal-title":"Infect. Dis. Poverty"}],"container-title":["International Journal of Environmental Research and Public Health"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1660-4601\/17\/12\/4509\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:41:45Z","timestamp":1760175705000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1660-4601\/17\/12\/4509"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,23]]},"references-count":135,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2020,6]]}},"alternative-id":["ijerph17124509"],"URL":"https:\/\/doi.org\/10.3390\/ijerph17124509","relation":{},"ISSN":["1660-4601"],"issn-type":[{"value":"1660-4601","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,6,23]]}}}