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Da Re D, Marini G, Bonannella C, Laurini F, Manica M, Anicic N, Albieri A, Angelini P, Arnoldi D, Blaha M, Bertola F, Caputo B, De Liberato C, Della Torre A, Flacio E, Franceschini A, Gradoni F, Kadriaj P, Lencioni V, Del Lesto I, La Russa F, Lia RP, Montarsi F, Otranto D, L'Ambert G, Rizzoli A, Rombolà P, Romiti F, Stancher G, Torina A, Velo E, Virgillito C, Zandonai F, Rosà R. VectAbundance: a spatio-temporal database of Aedes mosquitoes observations. Sci Data 2024; 11:636. [PMID: 38879616 PMCID: PMC11180130 DOI: 10.1038/s41597-024-03482-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 06/05/2024] [Indexed: 06/19/2024] Open
Abstract
Modelling approaches play a crucial role in supporting local public health agencies by estimating and forecasting vector abundance and seasonality. However, the reliability of these models is contingent on the availability of standardized, high-quality data. Addressing this need, our study focuses on collecting and harmonizing egg count observations of the mosquito Aedes albopictus, obtained through ovitraps in monitoring and surveillance efforts across Albania, France, Italy, and Switzerland from 2010 to 2022. We processed the raw observations to obtain a continuous time series of ovitraps observations allowing for an extensive geographical and temporal coverage of Ae. albopictus population dynamics. The resulting post-processed observations are stored in the open-access database VectAbundance.This initiative addresses the critical need for accessible, high-quality data, enhancing the reliability of modelling efforts and bolstering public health preparedness.
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Affiliation(s)
- Daniele Da Re
- Center Agriculture Food Environment, University of Trento, San Michele all'Adige, Italy.
- Research and Innovation Centre, Fondazione Edmund Mach, San Michele all'Adige, Italy.
| | - Giovanni Marini
- Research and Innovation Centre, Fondazione Edmund Mach, San Michele all'Adige, Italy
- Epilab-JRU, FEM-FBK Joint Research Unit, Trento, Italy
| | - Carmelo Bonannella
- OpenGeoHub Foundation, Doorwerth, The Netherlands
- Laboratory of Geo-Information Science and Remote Sensing, Wageningen University & Research, Wageningen, The Netherlands
| | - Fabrizio Laurini
- Department of Economics and Management, University of Parma, Parma, Italy
| | - Mattia Manica
- Epilab-JRU, FEM-FBK Joint Research Unit, Trento, Italy
- Bruno Kessler Foundation, Trento, Italy
| | - Nikoleta Anicic
- Institute of Microbiology, University of Applied Sciences and Arts of Southern Switzerland (SUPSI), Mendrisio, Switzerland
| | | | | | - Daniele Arnoldi
- Research and Innovation Centre, Fondazione Edmund Mach, San Michele all'Adige, Italy
| | - Marharyta Blaha
- Center Agriculture Food Environment, University of Trento, San Michele all'Adige, Italy
- Research and Innovation Centre, Fondazione Edmund Mach, San Michele all'Adige, Italy
| | | | - Beniamino Caputo
- Department of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italy
| | - Claudio De Liberato
- Istituto Zooprofilattico Sperimentale del Lazio e della Toscana "M. Aleandri", Viterbo, Italy
| | - Alessandra Della Torre
- Department of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italy
| | - Eleonora Flacio
- Institute of Microbiology, University of Applied Sciences and Arts of Southern Switzerland (SUPSI), Mendrisio, Switzerland
| | | | | | | | | | - Irene Del Lesto
- Istituto Zooprofilattico Sperimentale del Lazio e della Toscana "M. Aleandri", Viterbo, Italy
| | - Francesco La Russa
- Istituto Zooprofilattico Sperimentale della Sicilia "A. Mirri", Palermo, Italy
| | | | | | - Domenico Otranto
- Department of Veterinary Medicine, University of Bari, Bari, Italy
- Department of Veterinary Clinical Sciences, City University of Hong Kong, Hong Kong, People's Republic of China
| | | | - Annapaola Rizzoli
- Research and Innovation Centre, Fondazione Edmund Mach, San Michele all'Adige, Italy
- Epilab-JRU, FEM-FBK Joint Research Unit, Trento, Italy
| | - Pasquale Rombolà
- Istituto Zooprofilattico Sperimentale del Lazio e della Toscana "M. Aleandri", Viterbo, Italy
| | - Federico Romiti
- Istituto Zooprofilattico Sperimentale del Lazio e della Toscana "M. Aleandri", Viterbo, Italy
| | | | | | | | - Chiara Virgillito
- Department of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italy
| | | | - Roberto Rosà
- Center Agriculture Food Environment, University of Trento, San Michele all'Adige, Italy
- Research and Innovation Centre, Fondazione Edmund Mach, San Michele all'Adige, Italy
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González-Pérez MI, Faulhaber B, Aranda C, Williams M, Villalonga P, Silva M, Costa Osório H, Encarnaçao J, Talavera S, Busquets N. Field evaluation of an automated mosquito surveillance system which classifies Aedes and Culex mosquitoes by genus and sex. Parasit Vectors 2024; 17:97. [PMID: 38424626 PMCID: PMC10905882 DOI: 10.1186/s13071-024-06177-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 02/05/2024] [Indexed: 03/02/2024] Open
Abstract
BACKGROUND Mosquito-borne diseases are a major concern for public and veterinary health authorities, highlighting the importance of effective vector surveillance and control programs. Traditional surveillance methods are labor-intensive and do not provide high temporal resolution, which may hinder a full assessment of the risk of mosquito-borne pathogen transmission. Emerging technologies for automated remote mosquito monitoring have the potential to address these limitations; however, few studies have tested the performance of such systems in the field. METHODS In the present work, an optical sensor coupled to the entrance of a standard mosquito suction trap was used to record 14,067 mosquito flights of Aedes and Culex genera at four temperature regimes in the laboratory, and the resulting dataset was used to train a machine learning (ML) model. The trap, sensor, and ML model, which form the core of an automated mosquito surveillance system, were tested in the field for two classification purposes: to discriminate Aedes and Culex mosquitoes from other insects that enter the trap and to classify the target mosquitoes by genus and sex. The field performance of the system was assessed using balanced accuracy and regression metrics by comparing the classifications made by the system with those made by the manual inspection of the trap. RESULTS The field system discriminated the target mosquitoes (Aedes and Culex genera) with a balanced accuracy of 95.5% and classified the genus and sex of those mosquitoes with a balanced accuracy of 88.8%. An analysis of the daily and seasonal temporal dynamics of Aedes and Culex mosquito populations was also performed using the time-stamped classifications from the system. CONCLUSIONS This study reports results for automated mosquito genus and sex classification using an optical sensor coupled to a mosquito trap in the field with highly balanced accuracy. The compatibility of the sensor with commercial mosquito traps enables the sensor to be integrated into conventional mosquito surveillance methods to provide accurate automatic monitoring with high temporal resolution of Aedes and Culex mosquitoes, two of the most concerning genera in terms of arbovirus transmission.
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Affiliation(s)
- María I González-Pérez
- IRTA, Programa de Sanitat Animal, Centre de Recerca en Sanitat Animal (CReSA), Campus de la Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
- Unitat mixta d'Investigació IRTA-UAB en Sanitat Animal, Centre de Recerca en Sanitat Animal (CReSA), Campus de La Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
| | | | - Carles Aranda
- IRTA, Programa de Sanitat Animal, Centre de Recerca en Sanitat Animal (CReSA), Campus de la Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
- Unitat mixta d'Investigació IRTA-UAB en Sanitat Animal, Centre de Recerca en Sanitat Animal (CReSA), Campus de La Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
- Servei de Control de Mosquits del Consell Comarcal del Baix Llobregat, El Prat de Llobregat, Spain
| | | | | | - Manuel Silva
- National Institute of Health/Centre for Vectors and Infectious Diseases Research, Águas de Moura, Portugal
| | - Hugo Costa Osório
- National Institute of Health/Centre for Vectors and Infectious Diseases Research, Águas de Moura, Portugal
- Instituto de Saúde Ambiental, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal
| | | | - Sandra Talavera
- IRTA, Programa de Sanitat Animal, Centre de Recerca en Sanitat Animal (CReSA), Campus de la Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
- Unitat mixta d'Investigació IRTA-UAB en Sanitat Animal, Centre de Recerca en Sanitat Animal (CReSA), Campus de La Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
| | - Núria Busquets
- IRTA, Programa de Sanitat Animal, Centre de Recerca en Sanitat Animal (CReSA), Campus de la Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain.
- Unitat mixta d'Investigació IRTA-UAB en Sanitat Animal, Centre de Recerca en Sanitat Animal (CReSA), Campus de La Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain.
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Ferraguti M, Martínez-de la Puente J, Brugueras S, Millet JP, Rius C, Valsecchi A, Figuerola J, Montalvo T. Spatial distribution and temporal dynamics of invasive and native mosquitoes in a large Mediterranean city. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 896:165322. [PMID: 37414178 DOI: 10.1016/j.scitotenv.2023.165322] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 06/16/2023] [Accepted: 07/02/2023] [Indexed: 07/08/2023]
Abstract
Mosquitoes, including invasive species like the Asian tiger mosquito Aedes albopictus, alongside native species Culex pipiens s.l., pose a significant nuisance to humans and serve as vectors for mosquito-borne diseases in urban areas. Understanding the impact of water infrastructure characteristics, climatic conditions, and management strategies on mosquito occurrence and effectiveness of control measures to assess their implications on mosquito occurrence is crucial for effective vector control. In this study, we examined data collected during the local vector control program in Barcelona, Spain, focusing on 234,225 visits to 31,334 different sewers, as well as 1817 visits to 152 fountains between 2015 and 2019. We investigated both the colonization and recolonization processes of mosquito larvae within these water infrastructures. Our findings revealed higher larval presence in sandbox-sewers compared to siphonic or direct sewers, and the presence of vegetation and the use of naturalized water positively influenced larval occurrence in fountains. The application of larvicidal treatment significantly reduced larvae presence; however, recolonization rates were negatively affected by the time elapsed since treatment. Climatic conditions played a critical role in the colonization and recolonization of sewers and urban fountains, with mosquito occurrence exhibiting non-linear patterns and, generally, increasing at intermediate temperatures and accumulated rainfall levels. This study emphasizes the importance of considering sewers and fountains characteristics and climatic conditions when implementing vector control programs to optimize resources and effectively reduce mosquito populations.
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Affiliation(s)
- M Ferraguti
- Department of Wetland Ecology, Doñana Biological Station (EBD-CSIC), Avda. Américo Vespucio 26, E-41092, Seville, Spain; CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain.
| | - J Martínez-de la Puente
- Department of Parasitology, University of Granada (UGR), Granada, Spain; CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - S Brugueras
- Agència de Salut Pública de Barcelona (ASPB), Barcelona, Spain
| | - J P Millet
- Agència de Salut Pública de Barcelona (ASPB), Barcelona, Spain; CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - C Rius
- Agència de Salut Pública de Barcelona (ASPB), Barcelona, Spain; CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - A Valsecchi
- Agència de Salut Pública de Barcelona (ASPB), Barcelona, Spain
| | - J Figuerola
- Department of Wetland Ecology, Doñana Biological Station (EBD-CSIC), Avda. Américo Vespucio 26, E-41092, Seville, Spain; CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - T Montalvo
- Agència de Salut Pública de Barcelona (ASPB), Barcelona, Spain; CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
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4
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Marini G, Pugliese A, Wint W, Alexander NS, Rizzoli A, Rosà R. Modelling the West Nile virus force of infection in the European human population. One Health 2022; 15:100462. [DOI: 10.1016/j.onehlt.2022.100462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 11/17/2022] [Accepted: 11/17/2022] [Indexed: 11/23/2022] Open
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5
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Kumar S, Hol FJH, Pujhari S, Ellington C, Narayanan HV, Li H, Rasgon JL, Prakash M. A microfluidic platform for highly parallel bite by bite profiling of mosquito-borne pathogen transmission. Nat Commun 2021; 12:6018. [PMID: 34650045 PMCID: PMC8516912 DOI: 10.1038/s41467-021-26300-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 09/03/2021] [Indexed: 01/02/2023] Open
Abstract
Mosquito bites transmit a number of pathogens via salivary droplets deposited during blood-feeding, resulting in potentially fatal diseases. Little is known about the genomic content of these nanodroplets, including the transmission dynamics of live pathogens. Here we introduce Vectorchip, a low-cost, scalable microfluidic platform enabling high-throughput molecular interrogation of individual mosquito bites. We introduce an ultra-thin PDMS membrane which acts as a biting interface to arrays of micro-wells. Freely-behaving mosquitoes deposit saliva droplets by biting into these micro-wells. By modulating membrane thickness, we observe species-dependent differences in mosquito biting capacity, utilizable for selective sample collection. We demonstrate RT-PCR and focus-forming assays on-chip to detect mosquito DNA, Zika virus RNA, as well as quantify infectious Mayaro virus particles transmitted from single mosquito bites. The Vectorchip presents a promising approach for single-bite-resolution laboratory and field characterization of vector-pathogen communities, and could serve as a powerful early warning sentinel for mosquito-borne diseases.
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Affiliation(s)
- Shailabh Kumar
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Felix J H Hol
- Department of Bioengineering, Stanford University, Stanford, CA, USA.,Insect Virus Interactions Unit, Department of Virology, Institut Pasteur, UMR2000, CNRS, Paris, France.,Center for Research and Interdisciplinarity, U1284 INSERM, Université de Paris, Paris, France
| | - Sujit Pujhari
- Department of Entomology, The Center for Infectious Disease Dynamics, and the Huck Institutes of The Life Sciences, The Pennsylvania State University, University Park, PA, USA.,Department of Pharmacology, Physiology and Neuroscience, University of South Carolina School of Medicine, Columbia, SC, USA
| | - Clayton Ellington
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | | | - Hongquan Li
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Jason L Rasgon
- Department of Entomology, The Center for Infectious Disease Dynamics, and the Huck Institutes of The Life Sciences, The Pennsylvania State University, University Park, PA, USA
| | - Manu Prakash
- Department of Bioengineering, Stanford University, Stanford, CA, USA. .,Woods Institute for the Environment, Stanford University, Stanford, CA, USA.
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6
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Mosquito species identification using convolutional neural networks with a multitiered ensemble model for novel species detection. Sci Rep 2021; 11:13656. [PMID: 34211009 PMCID: PMC8249627 DOI: 10.1038/s41598-021-92891-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 06/16/2021] [Indexed: 11/17/2022] Open
Abstract
With over 3500 mosquito species described, accurate species identification of the few implicated in disease transmission is critical to mosquito borne disease mitigation. Yet this task is hindered by limited global taxonomic expertise and specimen damage consistent across common capture methods. Convolutional neural networks (CNNs) are promising with limited sets of species, but image database requirements restrict practical implementation. Using an image database of 2696 specimens from 67 mosquito species, we address the practical open-set problem with a detection algorithm for novel species. Closed-set classification of 16 known species achieved 97.04 ± 0.87% accuracy independently, and 89.07 ± 5.58% when cascaded with novelty detection. Closed-set classification of 39 species produces a macro F1-score of 86.07 ± 1.81%. This demonstrates an accurate, scalable, and practical computer vision solution to identify wild-caught mosquitoes for implementation in biosurveillance and targeted vector control programs, without the need for extensive image database development for each new target region.
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7
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Michaelakis A, Balestrino F, Becker N, Bellini R, Caputo B, della Torre A, Figuerola J, L’Ambert G, Petric D, Robert V, Roiz D, Saratsis A, Sousa CA, Wint WGR, Papadopoulos NT. A Case for Systematic Quality Management in Mosquito Control Programmes in Europe. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18073478. [PMID: 33801616 PMCID: PMC8037277 DOI: 10.3390/ijerph18073478] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Revised: 03/22/2021] [Accepted: 03/24/2021] [Indexed: 01/23/2023]
Abstract
The recent spread of invasive mosquito species, such as Aedes albopictus and the seasonal sporadic transmission of autochthonous cases of arboviral diseases (e.g., dengue, chikungunya, Zika) in temperate areas, such as Europe and North America, highlight the importance of effective mosquito-control interventions to reduce not only nuisance, but also major threats for public health. Local, regional, and even national mosquito control programs have been established in many countries and are executed on a seasonal basis by either public or private bodies. In order for these interventions to be worthwhile, funding authorities should ensure that mosquito control is (a) planned by competent scientific institutions addressing the local demands, (b) executed following the plan that is based on recommended and effective methods and strategies, (c) monitored regularly by checking the efficacy of the implemented actions, (d) evaluated against the set of targets, and (e) regularly improved according to the results of the monitoring. Adherence to these conditions can only be assured if a formal quality management system is adopted and enforced that ensures the transparency of effectiveness of the control operation. The current paper aims at defining the two components of this quality management system, quality assurance and quality control for mosquito control programs with special emphasis on Europe, but applicable over temperate areas.
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Affiliation(s)
- Antonios Michaelakis
- Scientific Directorate of Entomology and Agricultural Zoology, Benaki Phytopathological Institute, 14561 Kifissia, Greece;
| | - Fabrizio Balestrino
- Centro Agricoltura Ambiente “G. Nicoli”, 40014 Crevalcore, Italy; (F.B.); (R.B.)
| | - Norbert Becker
- German Mosquito Control Association (KABS), 67346 Speyer, Germany;
| | - Romeo Bellini
- Centro Agricoltura Ambiente “G. Nicoli”, 40014 Crevalcore, Italy; (F.B.); (R.B.)
| | - Beniamino Caputo
- Dipartimento di Sanità Pubblica e Malattie Infettive, Università di Roma “Sapienza”, 00185 Rome, Italy; (B.C.); (A.d.T.)
| | - Alessandra della Torre
- Dipartimento di Sanità Pubblica e Malattie Infettive, Università di Roma “Sapienza”, 00185 Rome, Italy; (B.C.); (A.d.T.)
| | - Jordi Figuerola
- Department of Wetland Ecology, Estación Biológica de Doñana, CSIC, Avenida Américo Vespucio 26, E-41092 Sevilla, Spain;
- CIBER Epidemiología y Salud Pública, 28029 Madrid, Spain
| | - Gregory L’Ambert
- EID Méditerranée, Division Research and Development, 34184 Montpellier, France;
| | - Dusan Petric
- Department of Plant and Environment Protection, Faculty of Agriculture, University of Novi Sad, 21000 Novi Sad, Serbia;
| | - Vincent Robert
- MIVEGEC, University Montpellier, IRD, CNRS, 34090 Montpellier, France; (V.R.); (D.R.)
| | - David Roiz
- MIVEGEC, University Montpellier, IRD, CNRS, 34090 Montpellier, France; (V.R.); (D.R.)
| | - Anastasios Saratsis
- Laboratory of Parasitology, Veterinary Research Institute, Hellenic Agricultural Organisation Demeter, 57001 Thermi, Greece;
| | - Carla A. Sousa
- Global Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, 1349-008 Lisboa, Portugal;
| | - William G. R. Wint
- Environmental Research Group Oxford Ltd., c/o Department of Zoology, South Parks Road, Oxford OX1 3PS, UK;
| | - Nikos T. Papadopoulos
- Laboratory of Entomology and Agricultural Zoology, University of Thessaly, 38446 Volos, Greece
- Correspondence:
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Lorenz C, Castro MC, Trindade PMP, Nogueira ML, de Oliveira Lage M, Quintanilha JA, Parra MC, Dibo MR, Fávaro EA, Guirado MM, Chiaravalloti-Neto F. Predicting Aedes aegypti infestation using landscape and thermal features. Sci Rep 2020; 10:21688. [PMID: 33303912 PMCID: PMC7729962 DOI: 10.1038/s41598-020-78755-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Accepted: 11/30/2020] [Indexed: 11/15/2022] Open
Abstract
Identifying Aedes aegypti breeding hotspots in urban areas is crucial for the design of effective vector control strategies. Remote sensing techniques offer valuable tools for mapping habitat suitability. In this study, we evaluated the association between urban landscape, thermal features, and mosquito infestations. Entomological surveys were conducted between 2016 and 2019 in Vila Toninho, a neighborhood of São José do Rio Preto, São Paulo, Brazil, in which the numbers of adult female Ae. aegypti were recorded monthly and grouped by season for three years. We used data from 2016 to 2018 to build the model and data from summer of 2019 to validate it. WorldView-3 satellite images were used to extract land cover classes, and land surface temperature data were obtained using the Landsat-8 Thermal Infrared Sensor (TIRS). A multilevel negative binomial model was fitted to the data, which showed that the winter season has the greatest influence on decreases in mosquito abundance. Green areas and pavements were negatively associated, and a higher cover of asbestos roofs and exposed soil was positively associated with the presence of adult females. These features are related to socio-economic factors but also provide favorable breeding conditions for mosquitos. The application of remote sensing technologies has significant potential for optimizing vector control strategies, future mosquito suppression, and outbreak prediction.
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Affiliation(s)
- Camila Lorenz
- Department of Epidemiology, School of Public Health - University of Sao Paulo, Av. Dr. Arnaldo, São Paulo, SP, 715, Brazil.
| | - Marcia C Castro
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Patricia M P Trindade
- Southern Regional Centre of the National Institute for Space Research (INPE), Santa Maria, RS, Brazil
| | - Maurício L Nogueira
- Virology Research Laboratory, Faculty of Medicine of São José do Rio Preto, São José do Rio Preto, SP, Brazil
| | - Mariana de Oliveira Lage
- Scientific Division of Management, Environmental Science and Technology of the Institute of Energy and Environment - IEE of University of Sao Paulo, São Paulo, SP, Brazil
| | - José A Quintanilha
- Scientific Division of Management, Environmental Science and Technology of the Institute of Energy and Environment - IEE of University of Sao Paulo, São Paulo, SP, Brazil
| | - Maisa C Parra
- Virology Research Laboratory, Faculty of Medicine of São José do Rio Preto, São José do Rio Preto, SP, Brazil
| | - Margareth R Dibo
- Entomology Laboratory, Endemics Control Superintendence, São Paulo, SP, Brazil
| | - Eliane A Fávaro
- Virology Research Laboratory, Faculty of Medicine of São José do Rio Preto, São José do Rio Preto, SP, Brazil
| | - Marluci M Guirado
- Vectors Laboratory, Endemics Control Superintendence, São José do Rio Preto, SP, Brazil
| | - Francisco Chiaravalloti-Neto
- Department of Epidemiology, School of Public Health - University of Sao Paulo, Av. Dr. Arnaldo, São Paulo, SP, 715, Brazil
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9
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Schultes OL, Morais MHF, Cunha MDCM, Sobral A, Caiaffa WT. Spatial analysis of dengue incidence and Aedes aegypti ovitrap surveillance in Belo Horizonte, Brazil. Trop Med Int Health 2020; 26:237-255. [PMID: 33159826 DOI: 10.1111/tmi.13521] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
OBJECTIVES Understanding the intra-urban spatial dynamics of Aedes aegypti and dengue transmission is important to effectively guide vector control. Ovitraps are a sensitive, cost-effective vector surveillance tool, yet few longitudinal studies have evaluated ovitrap indices and dengue occurrence. We aimed to assess the spatial patterns of dengue incidence and Ae. aegypti ovitrap positivity index (OPI) over time and to examine the spatial relationship between these two variables. METHODS This study used 12 years (2007-2018) of dengue case records and biweekly Ae. aegypti ovitrap data in Belo Horizonte, Brazil. We aggregated data by year and health centre catchment area (n = 152) and used both univariate and bivariate global Moran's I statistic and LISA to evaluate spatial clustering. RESULTS Annual dengue incidence ranged from 18 to 6262/100 000 residents and displayed spatial autocorrelation in 10/12 years, with shifting areas of high incidence. Annual OPI ranged from 35.7 to 47.6% and was clustered in all study years, but unlike dengue had consistent spatial patterns over time. Bivariate analysis found both positive (6/12 years) and negative (1/12 years) spatial associations between the two variables. CONCLUSIONS Low detected presence of Ae. aegypti was not a limiting factor in dengue transmission. However, stable spatial distribution of OPI suggests that certain areas may have persistent breeding sites. Future research should identify factors related to persistent Ae. aegypti hotspots to better guide vector management. Vector control efforts should be paired with additional data on population immunity, circulating serotypes and urban factors to better predict and control outbreaks.
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Affiliation(s)
- Olivia Lang Schultes
- Urban Health Observatory of Belo Horizonte, Federal University of Minas Gerais, Brazil
| | | | | | - Andréa Sobral
- National School of Public Health, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
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ZanzaMapp: A Scalable Citizen Science Tool to Monitor Perception of Mosquito Abundance and Nuisance in Italy and Beyond. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17217872. [PMID: 33121060 PMCID: PMC7672598 DOI: 10.3390/ijerph17217872] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 10/20/2020] [Accepted: 10/22/2020] [Indexed: 12/16/2022]
Abstract
Mosquitoes represent a considerable nuisance and are actual/potential vectors of human diseases in Europe. Costly and labour-intensive entomological monitoring is needed to correct planning of interventions aimed at reducing nuisance and the risk of pathogen transmission. The widespread availability of mobile phones and of massive Internet connections opens the way to the contribution of citizen in complementing entomological monitoring. ZanzaMapp is the first mobile “mosquito” application for smartphones specifically designed to assess citizens’ perception of mosquito abundance and nuisance in Italy. Differently from other applications targeting mosquitoes, ZanzaMapp prioritizes the number of records over their scientific authentication by requesting users to answer four simple questions on perceived mosquito presence/abundance/nuisance and geo-localizing the records. The paper analyses 36,867 ZanzaMapp records sent by 13,669 devices from 2016 to 2018 and discusses the results with reference to either citizens’ exploitation and appreciation of the app and to the consistency of the results obtained with the known biology of main mosquito species in Italy. In addition, we provide a first small-scale validation of ZanzaMapp data as predictors of Aedes albopictus biting females and examples of spatial analyses and maps which could be exploited by public institutions and administrations involved in mosquito and mosquito-borne pathogen monitoring and control.
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