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  1. Article ; Online: Thermal environment and indices: an analysis for effectiveness in operational weather applications in a Mediterranean city (Athens, Greece).

    Pantavou, Katerina / Kotroni, Vassiliki / Lagouvardos, Konstantinos

    International journal of biometeorology

    2023  Volume 68, Issue 1, Page(s) 79–87

    Abstract: The large number of thermal indices introduced in the literature poses a challenge to identify the appropriate one for a given application. The aim of this study was to examine the effectiveness of widely used indices in quantifying the thermal ... ...

    Abstract The large number of thermal indices introduced in the literature poses a challenge to identify the appropriate one for a given application. The aim of this study was to examine the effectiveness of widely used indices in quantifying the thermal environment for operational weather applications within a Mediterranean climate. Eight indices (six simple and two thermo-physiological) were considered, i.e., apparent temperature, heat index, humidex, net effective temperature (NET), physiologically equivalent temperature (PET), universal thermal climate index (UTCI), wet-bulb globe temperature, and wind chill temperature. They were estimated using hourly meteorological data between 2010 and 2021, recorded in 15 stations from the Automatic Weather Station Network of the National Observatory of Athens in the Athens metropolitan area, Greece. The statistical analysis focused on examining indices' sensitivity to variations of the thermal environment. NET, PET, and UTCI were evaluated as suitable for operational use, assessing both cool and warm environments, and extending their estimations to the entire range of their assessment scales. NET and PET often tended to classify thermal perception in the negative categories of their scales, with 63% of NET and 56% of PET estimations falling within the range of cool/slightly cool to very cold. UTCI estimations in the negative categories accounted for 25.8% (p < 0.001), while most estimations were classified in the neutral category (53.1%). The common occasions of extreme warm conditions in terms of both air temperature (Tair) and NET was 77.7%, Tair and UTCI 64.4%, and Tair and PET 33.6% (p < 0.001). According to the indices considered and the method followed, NET and UTCI satisfied sufficiently the requirements for operational use in the climate conditions of the Mediterranean climate.
    MeSH term(s) Greece ; Thermosensing ; Weather ; Climate ; Temperature
    Language English
    Publishing date 2023-11-15
    Publishing country United States
    Document type Journal Article
    ZDB-ID 280324-0
    ISSN 1432-1254 ; 0020-7128
    ISSN (online) 1432-1254
    ISSN 0020-7128
    DOI 10.1007/s00484-023-02572-7
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  2. Article ; Online: Machine learning and features for the prediction of thermal sensation and comfort using data from field surveys in Cyprus

    Pantavou, Katerina / Delibasis, Konstantinos K. / Nikolopoulos, Georgios K.

    Int J Biometeorol. 2022 Oct., v. 66, no. 10 p.1973-1984

    2022  

    Abstract: Perception can influence individuals’ behaviour and attitude affecting responses and compliance to precautionary measures. This study aims to investigate the performance of methods for thermal sensation and comfort prediction. Four machine learning ... ...

    Abstract Perception can influence individuals’ behaviour and attitude affecting responses and compliance to precautionary measures. This study aims to investigate the performance of methods for thermal sensation and comfort prediction. Four machine learning algorithms (MLA), artificial neural networks, random forest (RF), support vector machines, and linear discriminant analysis were examined and compared to the physiologically equivalent temperature (PET). Data were collected in field surveys conducted in outdoor sites in Cyprus. The seven- and nine-point assessment scales of thermal sensation and a two-point scale of thermal comfort were considered. The models of MLA included meteorological and physiological features. The results indicate RF as the best MLA applied to the data. All MLA outperformed PET. For thermal sensation, the lowest prediction error (1.32 points) and the highest accuracy (30%) were found in the seven-point scale for the feature vector consisting of air temperature, relative humidity, wind speed, grey globe temperature, clothing insulation, activity, age, sex, and body mass index. The accuracy increased to 63.8% when considering prediction with at most one-point difference from the correct thermal sensation category. The best performed feature vector for thermal sensation also produced one of the best models for thermal comfort yielding an accuracy of 71% and an F-score of 0.81.
    Keywords Cyprus ; air temperature ; body mass index ; compliance ; discriminant analysis ; insulating materials ; prediction ; relative humidity ; sensation ; wind speed
    Language English
    Dates of publication 2022-10
    Size p. 1973-1984.
    Publishing place Springer Berlin Heidelberg
    Document type Article ; Online
    ZDB-ID 127361-9
    ISSN 0067-8902 ; 0020-7128
    ISSN 0067-8902 ; 0020-7128
    DOI 10.1007/s00484-022-02333-y
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  3. Article ; Online: Machine learning and features for the prediction of thermal sensation and comfort using data from field surveys in Cyprus.

    Pantavou, Katerina / Delibasis, Konstantinos K / Nikolopoulos, Georgios K

    International journal of biometeorology

    2022  Volume 66, Issue 10, Page(s) 1973–1984

    Abstract: Perception can influence individuals' behaviour and attitude affecting responses and compliance to precautionary measures. This study aims to investigate the performance of methods for thermal sensation and comfort prediction. Four machine learning ... ...

    Abstract Perception can influence individuals' behaviour and attitude affecting responses and compliance to precautionary measures. This study aims to investigate the performance of methods for thermal sensation and comfort prediction. Four machine learning algorithms (MLA), artificial neural networks, random forest (RF), support vector machines, and linear discriminant analysis were examined and compared to the physiologically equivalent temperature (PET). Data were collected in field surveys conducted in outdoor sites in Cyprus. The seven- and nine-point assessment scales of thermal sensation and a two-point scale of thermal comfort were considered. The models of MLA included meteorological and physiological features. The results indicate RF as the best MLA applied to the data. All MLA outperformed PET. For thermal sensation, the lowest prediction error (1.32 points) and the highest accuracy (30%) were found in the seven-point scale for the feature vector consisting of air temperature, relative humidity, wind speed, grey globe temperature, clothing insulation, activity, age, sex, and body mass index. The accuracy increased to 63.8% when considering prediction with at most one-point difference from the correct thermal sensation category. The best performed feature vector for thermal sensation also produced one of the best models for thermal comfort yielding an accuracy of 71% and an F-score of 0.81.
    MeSH term(s) Cyprus ; Humans ; Machine Learning ; Temperature ; Thermosensing/physiology ; Wind
    Language English
    Publishing date 2022-07-27
    Publishing country United States
    Document type Journal Article
    ZDB-ID 280324-0
    ISSN 1432-1254 ; 0020-7128
    ISSN (online) 1432-1254
    ISSN 0020-7128
    DOI 10.1007/s00484-022-02333-y
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  4. Article ; Online: A novel artificial neural network methodology to produce high-resolution bioclimatic maps using Earth Observation data: A case study for Cyprus

    Philippopoulos, Kostas / Pantavou, Katerina / Cartalis, Constantinos / Agathangelidis, Ilias / Mavrakou, Thaleia / Polydoros, Anastasios / Nikolopoulos, Georgios

    Science of the Total Environment. 2023 Oct., v. 893 p.164734-

    2023  

    Abstract: The aim of this research is to propose a novel methodology that exploits Earth Observation (EO) data to accurately produce high-resolution bioclimatic maps at large spatiotemporal scales. This method directly links EO products (i.e., land surface ... ...

    Abstract The aim of this research is to propose a novel methodology that exploits Earth Observation (EO) data to accurately produce high-resolution bioclimatic maps at large spatiotemporal scales. This method directly links EO products (i.e., land surface temperature - LST and Normalized Difference Vegetation Index - NDVI) to air temperature (Tair) and such thermal indices as the Universal Thermal Climate Index (UTCI), and the Physiologically Equivalent Temperature (PET) to produce large-scale high-quality bioclimatic maps at a spatial resolution of 100 m. The proposed methodology is based on Artificial Neural Networks (ANNs), and the bioclimatic maps are developed with the use of Geographical Information Systems. High-resolution LST maps are produced from the spatial downscaling of EO images and the application of the methodology in the case of the island of Cyprus highlights the ability of EO parameters to estimate accurately Tₐᵢᵣ as well as the above mentioned thermal indices. The results are validated for different conditions and the overall Mean Absolute Error for each case ranges from 1.9 °C for Tair to 2.8 °C for PET and UTCI. The trained ANNs could be used in near real-time for estimating the spatial distribution of outdoor thermal conditions and for assessing the relationship between human health and the outdoor thermal environment. On the basis of the developed bioclimatic maps, high-risk areas were identified. Furthermore, the study examines the relationship between land cover and Tair, UTCI, and PET, and the results provide evidence of the suitability of the method to monitor the dynamics of the urban environment and the effectiveness of urban nature-based solutions. Studies on bioclimate analysis monitor thermal environment, raise awareness and enhance the capacity of national public health systems to respond to thermally-induced health risks.
    Keywords Cyprus ; air temperature ; bioclimate ; case studies ; environment ; human health ; land cover ; neural networks ; normalized difference vegetation index ; public health ; spatial data ; surface temperature ; urban areas ; Earth observation ; Big data ; Universal thermal climate index ; Physiologically equivalent temperature ; Bioclimatic maps
    Language English
    Dates of publication 2023-10
    Publishing place Elsevier B.V.
    Document type Article ; Online
    ZDB-ID 121506-1
    ISSN 1879-1026 ; 0048-9697
    ISSN (online) 1879-1026
    ISSN 0048-9697
    DOI 10.1016/j.scitotenv.2023.164734
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  5. Article ; Online: A novel artificial neural network methodology to produce high-resolution bioclimatic maps using Earth Observation data: A case study for Cyprus.

    Philippopoulos, Kostas / Pantavou, Katerina / Cartalis, Constantinos / Agathangelidis, Ilias / Mavrakou, Thaleia / Polydoros, Anastasios / Nikolopoulos, Georgios

    The Science of the total environment

    2023  Volume 893, Page(s) 164734

    Abstract: The aim of this research is to propose a novel methodology that exploits Earth Observation (EO) data to accurately produce high-resolution bioclimatic maps at large spatiotemporal scales. This method directly links EO products (i.e., land surface ... ...

    Abstract The aim of this research is to propose a novel methodology that exploits Earth Observation (EO) data to accurately produce high-resolution bioclimatic maps at large spatiotemporal scales. This method directly links EO products (i.e., land surface temperature - LST and Normalized Difference Vegetation Index - NDVI) to air temperature (Tair) and such thermal indices as the Universal Thermal Climate Index (UTCI), and the Physiologically Equivalent Temperature (PET) to produce large-scale high-quality bioclimatic maps at a spatial resolution of 100 m. The proposed methodology is based on Artificial Neural Networks (ANNs), and the bioclimatic maps are developed with the use of Geographical Information Systems. High-resolution LST maps are produced from the spatial downscaling of EO images and the application of the methodology in the case of the island of Cyprus highlights the ability of EO parameters to estimate accurately T
    Language English
    Publishing date 2023-06-09
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 121506-1
    ISSN 1879-1026 ; 0048-9697
    ISSN (online) 1879-1026
    ISSN 0048-9697
    DOI 10.1016/j.scitotenv.2023.164734
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  6. Article ; Online: Season of birth and multiple sclerosis: a systematic review and multivariate meta-analysis.

    Pantavou, Katerina G / Bagos, Pantelis G

    Journal of neurology

    2019  Volume 267, Issue 10, Page(s) 2815–2822

    Abstract: Season of birth is considered to be associated with multiple sclerosis (MS) although some findings opposing to this assumption raise doubts about the seasonality pattern in MS births. The present work synthesizes the evidence of previous published ... ...

    Abstract Season of birth is considered to be associated with multiple sclerosis (MS) although some findings opposing to this assumption raise doubts about the seasonality pattern in MS births. The present work synthesizes the evidence of previous published studies aiming at examining whether the month of birth is associated with a higher number of MS births. Pubmed and Scopus were systematically searched and a multivariate meta-analysis of case-control studies was conducted. Data of healthy controls births were retrieved from census reports when not included in the studies. For comparisons, October was set as a reference month and autumn (September-October-November) as a reference season. The meta-analysis included studies that provided the number of MS births for each month or season. Twenty-two eligible studies were included in the meta-analysis involving twenty-four different populations and overall 145,672 MS patients and 75,169,550 healthy controls. The multivariate analysis supports that MS births in spring are higher compared to autumn [odds ratio (OR) 1.14, 95% confidence interval (CI) 1.04, 1.24]. Univariate analyses confirm the same for April (OR 1.12, 95% CI 1.05, 1.21), March (OR 1.05, 95% CI 1.00, 1.11) and May (OR 1.07, 95% CI 1.00, 1.14). A reduction of MS births was found in November (OR 0.96, 95% CI 0.93, 0.99). The month and the season of birth are significantly associated with MS births.
    MeSH term(s) Humans ; Multiple Sclerosis/epidemiology ; Multivariate Analysis ; Odds Ratio ; Risk Factors ; Seasons
    Language English
    Publishing date 2019-05-04
    Publishing country Germany
    Document type Journal Article ; Meta-Analysis ; Review ; Systematic Review
    ZDB-ID 187050-6
    ISSN 1432-1459 ; 0340-5354 ; 0012-1037 ; 0939-1517 ; 1619-800X
    ISSN (online) 1432-1459
    ISSN 0340-5354 ; 0012-1037 ; 0939-1517 ; 1619-800X
    DOI 10.1007/s00415-019-09346-5
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  7. Article ; Online: Air quality and meteorological patterns of an early spring heatwave event in an industrialized area of Attica, Greece.

    Mavrakis, Anastasios / Kapsali, Athanasia / Tsiros, Ioannis X / Pantavou, Katerina

    Euro-Mediterranean journal for environmental integration

    2021  Volume 6, Issue 1, Page(s) 25

    Abstract: Heatwaves-excessively hot ambient conditions that are considered a serious threat to human health-are often associated with poor air quality. The aim of this study was to examine the impact of an early heatwave episode in an industrialized plain in the ... ...

    Abstract Heatwaves-excessively hot ambient conditions that are considered a serious threat to human health-are often associated with poor air quality. The aim of this study was to examine the impact of an early heatwave episode in an industrialized plain in the eastern Mediterranean region (Thriasio, Greece) on human thermal discomfort and urban air quality. The heatwave occurred in mid (15-20) May 2020, shortly after some of the restrictions that were improsed to halt the spread of coronavirus disease 2019 (COVID-19) in Greece were lifted (on 4 May). The discomfort index (DI) and the daily air quality index (DAQI) were calculated on an hourly basis throughout spring 2020 (March, April, May) using data from two stations that measure meteorological parameters and air pollutant concentrations in the Thriasio Plain. The analysis showed that the air temperature increased during 7-17 May to levels that were more than 10 °C above the monthly average value (25.8 °C). The maximum measured air temperature was 38 °C (on 17 May). The results showed a high level of thermal discomfort. The DI exceeded the threshold of 24 °C for several hours during 13-20 May. Increased air pollution levels were also identified. The average DAQI was estimated as 0.83 ± 0.1 and 1.14 ± 0.2 at two monitoring stations in the region of interest during the heatwave. Particulate matter (diameter < 10 μm) appeared to contribute significantly to the poor air quality. Significant correlations between the air temperature, DI, and AQSI were also identified.
    Language English
    Publishing date 2021-01-25
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2843155-8
    ISSN 2365-7448 ; 2365-6433
    ISSN (online) 2365-7448
    ISSN 2365-6433
    DOI 10.1007/s41207-020-00237-0
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  8. Article ; Online: Mortality attributable to seasonal influenza in Greece, 2013 to 2017: variation by type/subtype and age, and a possible harvesting effect.

    Lytras, Theodore / Pantavou, Katerina / Mouratidou, Elisavet / Tsiodras, Sotirios

    Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin

    2019  Volume 24, Issue 14

    Abstract: IntroductionEstimating the contribution of influenza to excess mortality in the population presents substantial methodological challenges.AimIn a modelling study we combined environmental, epidemiological and laboratory surveillance data to estimate ... ...

    Abstract IntroductionEstimating the contribution of influenza to excess mortality in the population presents substantial methodological challenges.AimIn a modelling study we combined environmental, epidemiological and laboratory surveillance data to estimate influenza-attributable mortality in Greece, over four seasons (2013/14 to 2016/17), specifically addressing the lag dimension and the confounding effect of temperature.MethodsAssociations of influenza type/subtype-specific incidence proxies and of daily mean temperature with mortality were estimated with a distributed-lag nonlinear model with 30 days of maximum lag, separately by age group (all ages, 15-64 and ≥ 65 years old). Total and weekly deaths attributable to influenza and cold temperatures were calculated.ResultsOverall influenza-attributable mortality was 23.6 deaths per 100,000 population per year (95% confidence interval (CI): 17.8 to 29.2), and varied greatly between seasons, by influenza type/subtype and by age group, with the vast majority occurring in persons aged ≥ 65 years. Most deaths were attributable to A(H3N2), followed by influenza B. During periods of A(H1N1)pdm09 circulation, weekly attributable mortality to this subtype among people ≥ 65 years old increased rapidly at first, but then fell to zero and even negative, suggesting a mortality displacement (harvesting) effect. Mortality attributable to cold temperatures was much higher than that attributable to influenza.ConclusionsStudies of influenza-attributable mortality need to consider distributed-lag effects, stratify by age group and adjust both for circulating influenza virus types/subtypes and daily mean temperatures, in order to produce reliable estimates. Our approach addresses these issues, is readily applicable in the context of influenza surveillance, and can be useful for other countries.
    MeSH term(s) Adolescent ; Adult ; Age Distribution ; Aged ; Algorithms ; Greece/epidemiology ; Humans ; Influenza A Virus, H1N1 Subtype ; Influenza A Virus, H3N2 Subtype ; Influenza A virus ; Influenza B virus ; Influenza, Human/diagnosis ; Influenza, Human/epidemiology ; Influenza, Human/mortality ; Male ; Middle Aged ; Models, Statistical ; Models, Theoretical ; Seasons ; Sentinel Surveillance
    Language English
    Publishing date 2019-04-04
    Publishing country Sweden
    Document type Journal Article
    ZDB-ID 1338803-4
    ISSN 1560-7917 ; 1025-496X
    ISSN (online) 1560-7917
    ISSN 1025-496X
    DOI 10.2807/1560-7917.ES.2019.24.14.1800118
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  9. Article ; Online: Trends of Online Search of COVID-19 Related Terms in Cyprus.

    Anastasiou, Marios / Pantavou, Katerina / Yiallourou, Anneza / Bonovas, Stefanos / Nikolopoulos, Georgios K

    Epidemiolgia (Basel, Switzerland)

    2021  Volume 2, Issue 1, Page(s) 36–45

    Abstract: Knowledge of trends in web searches provides useful information for various purposes, including responses to public health emergencies. This work aims to analyze the popularity of internet search queries for Coronavirus Disease 2019 (COVID-19) and COVID- ... ...

    Abstract Knowledge of trends in web searches provides useful information for various purposes, including responses to public health emergencies. This work aims to analyze the popularity of internet search queries for Coronavirus Disease 2019 (COVID-19) and COVID-19 symptoms in Cyprus. Query data for the term Coronavirus were retrieved from Google Trends website between 19 January and 30 June 2020. The study focused on Cyprus and the four most populated cities: Nicosia, Limassol, Larnaca, and Paphos. COVID-19 symptoms including fever, cough, sore throat, shortness of breath, and myalgia were considered in the analysis. Daily and weekly search volumes were described, and their correlation with the evolution of the COVID-19 pandemic and important announcements or events were examined. Three periods of interest peaks were identified in Cyprus. The highest interest in COVID-19-related terms was found in the city of Paphos. The most popular symptoms were fever and cough, and the symptom with the highest increase in popularity was myalgia. At the beginning of the pandemic, the search volume of COVID-19 grew substantially when governments, major organizations, and high-profile figures, globally and locally, made important announcements regarding COVID-19. Health authorities in Cyprus and elsewhere could benefit from constantly monitoring the online interest of the population in order to get timely information that could be used in public health planning and response.
    Language English
    Publishing date 2021-01-20
    Publishing country Switzerland
    Document type Journal Article
    ISSN 2673-3986
    ISSN (online) 2673-3986
    DOI 10.3390/epidemiologia2010004
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  10. Article: Data on verbal expressions for thermal sensation and comfort in the Greek language

    Pantavou, Katerina / Koletsis, Ioannis / Lykoudis, Spyridon / Melas, Emmanouil / Nikolopoulou, Marialena / Tsiros, Ioannis X.

    Data in Brief. 2020 Aug., v. 31

    2020  

    Abstract: This article presents data collected during a web-based survey on expressions used to describe thermal sensation and comfort in the Greek language. The survey used a structured questionnaire and delivered through Google Forms. The survey was promoted ... ...

    Abstract This article presents data collected during a web-based survey on expressions used to describe thermal sensation and comfort in the Greek language. The survey used a structured questionnaire and delivered through Google Forms. The survey was promoted through social networks and conducted in spring 2019. The data presented herein comprise of the participants’ responses to the questionnaire. A total of 359 questionnaires were completed. The participants were Greek speakers, older than 12, with at least a basic knowledge of the English language. The participants were asked to: (a) select the most appropriate translation, from English to Greek, of the nine-point ISO 10551 scale of perceptual judgment on personal thermal state, (b) formulate five, seven and nine-point thermal sensation scales, (c) report the category of the thermal sensation scale that signifies thermal comfort and (d) to assess the relative distances between the thermal sensation categories of the five, seven and nine-point thermal sensation scales. For the translation of the ISO 10551, the respondents were allowed to choose from a list of 30 Greek wordings. The data have been analysed in the research article entitled “Native influences on the construction of thermal sensation scales” [1].
    Keywords Internet ; questionnaires ; sensation ; spring ; surveys
    Language English
    Dates of publication 2020-08
    Publishing place Elsevier Inc.
    Document type Article
    ZDB-ID 2786545-9
    ISSN 2352-3409
    ISSN 2352-3409
    DOI 10.1016/j.dib.2020.105807
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