Logistic regression models for predicting daily airborne Alternaria and Cladosporium concentration levels in Catalonia (NE Spain)
Alternaria and Cladosporium are the most common airborne fungal spores responsible for health problems, as well as for crop pathologies. The study of their behavior in the air is a necessary step for establishing control and prevention measures. The aim of this paper is to develop a logistic regress...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2019
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
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- oai:repositorio.utb.edu.co:20.500.12585/8873
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/8873
- Palabra clave:
- Fungal spore daily concentration levels
Fungal spore dispersal patterns
Prediction model
Threshold
Alternaria
Cladosporium
Fungus spore
Microbiology
Season
Spain
Statistical model
Air Microbiology
Alternaria
Cladosporium
Logistic Models
Seasons
Spain
Spores, Fungal
- Rights
- restrictedAccess
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- http://creativecommons.org/licenses/by-nc-nd/4.0/
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Logistic regression models for predicting daily airborne Alternaria and Cladosporium concentration levels in Catalonia (NE Spain) |
| title |
Logistic regression models for predicting daily airborne Alternaria and Cladosporium concentration levels in Catalonia (NE Spain) |
| spellingShingle |
Logistic regression models for predicting daily airborne Alternaria and Cladosporium concentration levels in Catalonia (NE Spain) Fungal spore daily concentration levels Fungal spore dispersal patterns Prediction model Threshold Alternaria Cladosporium Fungus spore Microbiology Season Spain Statistical model Air Microbiology Alternaria Cladosporium Logistic Models Seasons Spain Spores, Fungal |
| title_short |
Logistic regression models for predicting daily airborne Alternaria and Cladosporium concentration levels in Catalonia (NE Spain) |
| title_full |
Logistic regression models for predicting daily airborne Alternaria and Cladosporium concentration levels in Catalonia (NE Spain) |
| title_fullStr |
Logistic regression models for predicting daily airborne Alternaria and Cladosporium concentration levels in Catalonia (NE Spain) |
| title_full_unstemmed |
Logistic regression models for predicting daily airborne Alternaria and Cladosporium concentration levels in Catalonia (NE Spain) |
| title_sort |
Logistic regression models for predicting daily airborne Alternaria and Cladosporium concentration levels in Catalonia (NE Spain) |
| dc.subject.keywords.none.fl_str_mv |
Fungal spore daily concentration levels Fungal spore dispersal patterns Prediction model Threshold Alternaria Cladosporium Fungus spore Microbiology Season Spain Statistical model Air Microbiology Alternaria Cladosporium Logistic Models Seasons Spain Spores, Fungal |
| topic |
Fungal spore daily concentration levels Fungal spore dispersal patterns Prediction model Threshold Alternaria Cladosporium Fungus spore Microbiology Season Spain Statistical model Air Microbiology Alternaria Cladosporium Logistic Models Seasons Spain Spores, Fungal |
| description |
Alternaria and Cladosporium are the most common airborne fungal spores responsible for health problems, as well as for crop pathologies. The study of their behavior in the air is a necessary step for establishing control and prevention measures. The aim of this paper is to develop a logistic regression model for predicting the daily concentrations of airborne Alternaria and Cladosporium fungal spores from meteorological variables. To perform the logistic regression analysis, the concentration levels are binarized using concentration thresholds. The fungal spore data have been obtained at eight aerobiological monitoring stations of the Aerobiological Network of Catalonia (NE Spain). The meteorological data used were the maximum and minimum daily temperatures and daily rainfall provided by the meteorological services. The relationship between the meteorological variables and the fungal spore levels has been modeled by means of logistic regression equations, using data from the period 1995–2012. Values from years 2013–2014 were used for validation. In the case of Alternaria, three equations for predicting the presence and the exceedance of the thresholds 10 and 30 spores/m3 have been established. For Cladosporium, four equations for the thresholds 200, 500, 1000, and 1500 spores/m3 have been established. The temperature and cumulative rainfall in the last 3 days showed a positive correlation with airborne fungal spore levels, while the rain on the same day had a negative correlation. Sensitivity and specificity were calculated to measure the predictive power of the model, showing a reasonable percentage of correct predictions (ranging from 48 to 99%). The simple equations proposed allow us to forecast the levels of fungal spores that will be in the air the next day, using only the maximum and minimum temperatures and rainfall values provided by weather forecasting services. © 2019, ISB. |
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2019 |
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2019 |
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2020-03-26T16:32:32Z |
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2020-03-26T16:32:32Z |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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Artículo |
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International Journal of Biometeorology; Vol. 63, Núm. 12; pp. 1541-1553 |
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00207128 |
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https://hdl.handle.net/20.500.12585/8873 |
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10.1007/s00484-019-01767-1 |
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Universidad Tecnológica de Bolívar |
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Repositorio UTB |
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55817731200 13407293800 6701707061 7005080602 |
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International Journal of Biometeorology; Vol. 63, Núm. 12; pp. 1541-1553 00207128 10.1007/s00484-019-01767-1 Universidad Tecnológica de Bolívar Repositorio UTB 55817731200 13407293800 6701707061 7005080602 |
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https://hdl.handle.net/20.500.12585/8873 |
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eng |
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eng |
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2020-03-26T16:32:32Z2020-03-26T16:32:32Z2019International Journal of Biometeorology; Vol. 63, Núm. 12; pp. 1541-155300207128https://hdl.handle.net/20.500.12585/887310.1007/s00484-019-01767-1Universidad Tecnológica de BolívarRepositorio UTB558177312001340729380067017070617005080602Alternaria and Cladosporium are the most common airborne fungal spores responsible for health problems, as well as for crop pathologies. The study of their behavior in the air is a necessary step for establishing control and prevention measures. The aim of this paper is to develop a logistic regression model for predicting the daily concentrations of airborne Alternaria and Cladosporium fungal spores from meteorological variables. To perform the logistic regression analysis, the concentration levels are binarized using concentration thresholds. The fungal spore data have been obtained at eight aerobiological monitoring stations of the Aerobiological Network of Catalonia (NE Spain). The meteorological data used were the maximum and minimum daily temperatures and daily rainfall provided by the meteorological services. The relationship between the meteorological variables and the fungal spore levels has been modeled by means of logistic regression equations, using data from the period 1995–2012. Values from years 2013–2014 were used for validation. In the case of Alternaria, three equations for predicting the presence and the exceedance of the thresholds 10 and 30 spores/m3 have been established. For Cladosporium, four equations for the thresholds 200, 500, 1000, and 1500 spores/m3 have been established. The temperature and cumulative rainfall in the last 3 days showed a positive correlation with airborne fungal spore levels, while the rain on the same day had a negative correlation. Sensitivity and specificity were calculated to measure the predictive power of the model, showing a reasonable percentage of correct predictions (ranging from 48 to 99%). The simple equations proposed allow us to forecast the levels of fungal spores that will be in the air the next day, using only the maximum and minimum temperatures and rainfall values provided by weather forecasting services. © 2019, ISB.Ministerio de Ciencia y Tecnología, MICYT: CGL2012-39523-C02-01/CLI European Commission, EC: ENV4-CT98-0755 CSD 2007_00067 GRACCIE 2005SGR00519, 2009SGR1102, 2017SGR1692, 2014SGR1274 CGL2012-39523-C02-01, CGL2005-07543/CLI, REN2001-10659-CO3-01, AMB97-0457-CO7-021, CTM2017-89565-C2-1-P, BOS2002-03474, GGL2006-12648-CO3-02, CGL2009-11205 Federación Española de Enfermedades Raras, FEDERThis work was supported by the Spanish Ministry of Science and Technology through the project “CGL2012-39523-C02-01/CLI” and by the Administrative Department of Science, Technology and Innovation-COLCIENCIAS (Colombia) through the doctoral fellowship to Andrés M. Vélez-Pereira.The authors wish to thank the entities and projects that make possible to obtain the database used in this study: Laboratorios LETI S.A.; Servei Meteorològic de Catalunya; Diputacions de Barcelona, Girona and Tarragona; SCAIC; SEAIC; Stallergenes Iberica; J. Uriach y Cia; European Commission for “ENV4-CT98-0755”; Spanish Ministry of Science and Technology I+D+I for “AMB97-0457-CO7-021,” “REN2001-10659-CO3-01,” “BOS2002-03474,” “CGL2004-21166-E,” “CGL2005-07543/CLI,” “GGL2006-12648-CO3-02,” “CGL2009-11205,” “CGL2012-39523-C02-01,” “CTM2017-89565-C2-1-P,” FEDER “A way to build Europe,” and CONSOLIDER CSD 2007_00067 GRACCIE; and Catalan Government AGAUR for “2005SGR00519,” “2009SGR1102,” “2014SGR1274,” and “2017SGR1692.” This work is contributing to the ICTA “Unit of Excellence” (MinECo, MDM2015-0552). The authors wish to thank the anonymous referees for careful reading and very helpful comments that resulted in an overall improvement of the paper.Recurso electrónicoapplication/pdfengSpringer New York LLChttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/restrictedAccessAtribución-NoComercial 4.0 Internacionalhttp://purl.org/coar/access_right/c_16echttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85072154915&doi=10.1007%2fs00484-019-01767-1&partnerID=40&md5=196567149daaaa95ffd04f7f8129792fLogistic regression models for predicting daily airborne Alternaria and Cladosporium concentration levels in Catalonia (NE Spain)info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_2df8fbb1Fungal spore daily concentration levelsFungal spore dispersal patternsPrediction modelThresholdAlternariaCladosporiumFungus sporeMicrobiologySeasonSpainStatistical modelAir MicrobiologyAlternariaCladosporiumLogistic ModelsSeasonsSpainSpores, FungalVélez-Pereira A.M.De Linares C.Canela M.-A.Belmonte J.Allue Andrade, J.L., (1990) Phytoclimatic atlas of Spain, , Taxonomies. Instituto Nacional de Investigaciones Agrarias, Ministerio de Agricultura, Pesca y Alimentación, Madrid, EspañaAlmeida, E., Caeiro, E., Todo-Bom, A., Ferro, R., Dionísio, A., Duarte, A., Gazarini, L., The influence of meteorological parameters on Alternaria and Cladosporium fungal spore concentrations in Beja (Southern Portugal): preliminary results (2018) Aerobiologia, 34, pp. 219-226Astray, G., Rodríguez-Rajo, F.J., Ferreiro-Lage, J.A., Fernández-González, M., Jato, V., Mejuto, J.C., The use of artificial neural networks to forecast biological atmospheric allergens or pathogens only as Alternaria spores (2010) J Environ Monit, 12, pp. 2145-2152Barbosa, A.M., Real, R., Olivero, J., Vargas, J.M., Otter (Lutra lutra) distribution modeling at two resolution scales suited to conservation planning in the Iberian Peninsula (2003) Biol Conserv, 114, pp. 377-387Barkai-Golan, R., Alternaria mycotoxins (2008) Mycotoxins in fruits and vegetables, pp. 185-204. , Barkai-Golan R, Paster N, (eds), 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