ABSTRACT
Background: Clinical studies suggest that warmer climates slow the spread of viral infections. In addition, exposure to cold weakens human immunity. Aim: This study describes the relationship between meteorological indicators, the number of cases, and mortality in patients with confirmed coronavirus disease 2019 (COVID-19). Patients and Methods: This was a retrospective observational study. Adult patients who presented to the emergency department with confirmed COVID-19 were included in the study. Meteorological data [mean temperature, minimum (min) temperature, maximum (max) temperature, relative humidity, and wind speed] for the city of Istanbul were collected from the Istanbul Meteorology 1st Regional Directorate. Results: The study population consisted of 169,058 patients. The highest number of patients were admitted in December (n = 21,610) and the highest number of deaths (n = 46) occurred in November. In a correlation analysis, a statistically significant, negative correlation was found between the number of COVID-19 patients and mean temperature (rho = -0.734, P < 0.001), max temperature (rho = -0.696, P < 0.001) or min temperature (rho = -0.748, P < 0.001). Besides, the total number of patients correlated significantly and positively with the mean relative humidity (rho = 0.399 and P = 0.012). The correlation analysis also showed a significant negative relationship between the mean, maximum, and min temperatures and the number of deaths and mortality. Conclusion: Our results indicate an increased number of COVID-19 cases during the 39-week study period when the mean, max, and min temperatures were consistently low and the mean relative humidity was consistently high.
Subject(s)
COVID-19 , Adult , Humans , COVID-19/epidemiology , Meteorological Concepts , Temperature , Retrospective Studies , Cold TemperatureABSTRACT
This study integrated dynamic models and statistical methods to design a novel macroanalysis approach to judge the climate impacts. First, the incidence difference across Köppen-Geiger climate regions was used to determine the four risk areas. Then, the effective influence of climate factors was proved according to the non-climate factors' non-difference among the risk areas, multi-source non-major component data assisting the proof. It is found that cold steppe arid climates and wet temperate climates are more likely to transmit SARS-CoV-2 among human beings. Although the results verified that the global optimum temperature was around 10 °C, and the average humidity was 71%, there was evident heterogeneity among different climate risk areas. The first-grade and fourth-grade risk regions in the Northern Hemisphere and fourth-grade risk regions in the Southern Hemisphere are more sensitive to temperature. However, the third-grade risk region in the Southern Hemisphere is more sensitive to relative humidity. The Southern Hemisphere's third-grade and fourth-grade risk regions are more sensitive to precipitation.
Subject(s)
COVID-19 , Humans , Pandemics , SARS-CoV-2 , Climate , TemperatureABSTRACT
The stability of SARS-CoV-2 for varying periods on a wide range of inanimate surfaces has raised concerns about surface transmission; however, there is still no evidence to confirm this route. In the present review, three variables affecting virus stability, namely temperature, relative humidity (RH), and initial virus titer, were considered from different experimental studies. The stability of SARS-CoV-2 on the surfaces of six different contact materials, namely plastic, metal, glass, protective equipment, paper, and fabric, and the factors affecting half-life period was systematically reviewed. The results showed that the half-life of SARS-CoV-2 on different contact materials was generally 2-10 h, up to 5 d, and as short as 30 min at 22 °C, whereas the half-life of SARS-CoV-2 on non-porous surfaces was generally 5-9 h d, up to 3 d, and as short as 4 min at 22 â. The half-life on porous surfaces was generally 1-5 h, up to 2 d, and as short as 13 min at 22 °C. Therefore, the half-life period of SARS-CoV-2 on non-porous surfaces is longer than that on porous surfaces, and thehalf-life of the virus decreases with increasing temperature, whereas RH produces a stable negative inhibitory effect only in a specific humidity range. Various disinfection precautions can be implemented in daily life depending on the stability of SARS-CoV-2 on different surfaces to interrupt virus transmission, prevent COVID-19 infections, and avoid over-disinfection. Owing to the more stringent control of conditions in laboratory studies and the lack of evidence of transmission through surfaces in the real world, it is difficult to provide strong evidence for the efficiency of transmission of the contaminant from the surface to the human body. Therefore, we suggest that future research should focus on exploring the systematic study of the entire transmission process of the virus, which will provide a theoretical basis for optimizing global outbreak prevention and control measures.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Temperature , Textiles , DisinfectionABSTRACT
Using the example of the city of São Paulo (Brazil), in this paper, we analyze the temporal relation between human mobility and meteorological variables with the number of infected individuals by the COVID-19 disease. For the temporal relation, we use the significant values of distance correlation t0(DC), which is a recently proposed quantity capable of detecting nonlinear correlations between time series. The analyzed period was from February 26, 2020 to June 28, 2020. Fewer movements in recreation and transit stations and the increase in the maximal temperature have strong correlations with the number of newly infected cases occurring 17 days after. Furthermore, more significant changes in grocery and pharmacy, parks, and recreation and sudden changes in the maximal pressure occurring 10 and 11 days before the disease begins are also correlated with it. Scanning the whole period of the data, not only the early stage of the disease, we observe that changes in human mobility also primarily affect the disease for 0-19 days after. In other words, our results demonstrate the crucial role of the municipal decree declaring an emergency in the city to influence the number of infected individuals.
Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , Brazil/epidemiology , Cities/epidemiology , Temperature , Time FactorsABSTRACT
BACKGROUND: Thermal inactivation is a conventional and effective method of eliminating the infectivity of pathogens from specimens in clinical and biological laboratories, and reducing the risk of occupational exposure and environmental contamination. During the COVID-19 pandemic, specimens from patients and potentially infected individuals were heat treated and processed under BSL-2 conditions in a safe, cost-effective, and timely manner. The temperature and duration of heat treatment are optimized and standardized in the protocol according to the susceptibility of the pathogen and the impact on the integrity of the specimens, but the heating device is often undefined. Devices and medium transferring the thermal energy vary in heating rate, specific heat capacity, and conductivity, resulting in variations in efficiency and inactivation outcome that may compromise biosafety and downstream biological assays. METHODS: We evaluated the water bath and hot air oven in terms of pathogen inactivation efficiency, which are the most commonly used inactivation devices in hospitals and biological laboratories. By evaluating the temperature equilibrium and viral titer elimination under various conditions, we studied the devices and their inactivation outcomes under identical treatment protocol, and to analyzed the factors, such as energy conductivity, specific heat capacity, and heating rate, underlying the inactivation efficiencies. RESULTS: We compared thermal inactivation of coronavirus using different devices, and have found that the water bath was more efficient at reducing infectivity, with higher heat transfer and thermal equilibration than a forced hot air oven. In addition to the efficiency, the water bath showed relative consistency in temperature equilibration of samples of different volumes, reduced the need for prolonged heating, and eliminated the risk of pathogen spread by forced airflow. CONCLUSIONS: Our data support the proposal to define the heating device in the thermal inactivation protocol and in the specimen management policy.
Subject(s)
COVID-19 , Humans , COVID-19/prevention & control , Pandemics/prevention & control , Hot Temperature , Temperature , WaterABSTRACT
Since the advent of coronavirus disease 2019 (COVID-19), healthcare workers (HCWs) wearing personal protective equipment (PPE) has become a common phenomenon. COVID-19 outbreaks overlap with heat waves, and healthcare workers must unfortunately wear PPE during hot weather and experience excessive heat stress. Healthcare workers are at risk of developing heat-related health problems during hot periods in South China. The investigation of thermal response to heat stress among HCWs when they do not wear PPE and when they finish work wearing PPE, and the impact of PPE use on HCWs' physical health were conducted. The field survey were conducted in Guangzhou, including 11 districts. In this survey, HCWs were invited to answer a questionnaire about their heat perception in the thermal environment around them. Most HCWs experienced discomfort in their back, head, face, etc., and nearly 80% of HCWs experienced "profuse sweating." Up to 96.81% of HCWs felt "hot" or "very hot." The air temperature had a significant impact on thermal comfort. Healthcare workers' whole thermal sensation and local thermal sensation were increased significantly by wearing PPE and their thermal sensation vote (TSV) tended towards "very hot." The adaptive ability of the healthcare workers would decreased while wearing PPE. In addition, the accept range of the air temperature (T a) were determined in this investigation. Graphical Abstract.
Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , COVID-19/prevention & control , Personal Protective Equipment , Health Personnel , Temperature , Heat-Shock ResponseABSTRACT
This paper presents the numerical results of particle propagation in open space, taking into account the temperature of the human body and the surface of the ground. And also, the settling of particles or droplets under the action of gravitational force and transport in the open air is taken into account, taking into account the temperature during the process of breathing and sneezing or coughing. The temperature of the body and the surface of the ground, different rates of particle emission from the mouth, such as breathing and coughing or sneezing, are numerically investigated. The effect of temperature, cross-inlet wind, and the velocity of particle ejection from a person's mouth on social distancing is being investigated using a numerical calculation. The variable temperature of the human body forms a thermal plume, which affects the increase in the trajectory of the particle propagation, taking into account the lateral air flow. The thermal plume affects the particles in the breathing zone and spreads the particles over long distances in the direction of the airflow. The result of this work shows that in open space, taking into account the temperature of the body and the surface of the ground, a 2-m social distance may be insufficient for the process of sneezing and social distance must be observed depending on the breathing mode.
Subject(s)
Human Body , Wind , Humans , Temperature , Particle Size , Physical Distancing , Respiratory Aerosols and Droplets , SneezingABSTRACT
Surfaces contaminated with infectious SARS-CoV-2 particles have the potential to cause human infection and any increase in surface survivability of a SARS-CoV-2 variant may increase its prevalence over other variants. This study investigated whether there were differences in surface persistence between Delta and Omicron variants leading to Omicron's dominance globally. Stainless steel coupons were inoculated with suspensions of either Delta or Omicron variant and exposed to typical environmental conditions within a containment level 3 laboratory. Coupons were recovered at different timepoints and enumerated using plaque assay. Both variants were recoverable for >48 h on the coupons. Omicron showed a greater reduction of viability after 48 h compared to Delta with a 20-fold decrease versus 15-fold respectively, but this difference was not statistically significant (p = 0.424). These results indicate that Omicron's surface persistence is unlikely to contribute to it becoming the dominant variant over Delta.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , Temperature , Biological AssayABSTRACT
The increase in using antibiotics, especially Azithromycin have increased steadily since the beginning of COVID19 pandemic. This increase has led to its presence in water systems which consequently led to its presence upon using this water for irrigation. The aim of the present work is to study the impact of irrigation using Azithromycin containing water on soil microbial community and its catabolic activity in the presence of phenolic wastes as compost. Wild berry, red grapes, pomegranate, and spent tea waste were added to soil and the degradation was monitored after 5 and 7 days at ambient and high temperatures. The results obtained show that at 30 °C, soil microbial community collectively was able to degrade Azithromycin, while at 40 °C, addition of spent tea as compost was needed to reach higher degradation. To ensure that the degradation was biotic and depended on degradation by indigenous microflora, a 25 kGy irradiation dose was used to kill the microorganisms in the soil and this was used as negative control. The residual antibiotic was assayed using UV spectroscopy and High Performance Liquid Chromatography (HPLC). Indication of Azithromycin presence was studied using Fourier Transform Infrared Spectroscopy (FTIR) peaks and the same pattern was obtained using the 3 used detection methods, the ability to assign the peaks even in the presence of soil and not to have any overlaps, gives the chance to study this result in depth to prepare IR based sensor for quick sensing of antibiotic in environmental samples.
Subject(s)
COVID-19 , Microbiota , Soil Pollutants , Humans , Azithromycin/pharmacology , Azithromycin/analysis , Anti-Bacterial Agents/pharmacology , Anti-Bacterial Agents/analysis , Temperature , Soil/chemistry , COVID-19 Drug Treatment , Biodegradation, Environmental , Phenols/analysis , Water , Tea , Soil Microbiology , Soil Pollutants/metabolismABSTRACT
There have been a prolonged lockdown period and reduction in human activities in most of the major cities in the world during the Covid-19 pandemic period between the early 2020 and the late 2021. Such a reduction in human activities was believed to have influenced pollution levels and land surface temperatures (LST) in urban areas. This paper describes the variations in LSTs before, during and after the Covid-19 lockdown in Ho Chi Minh City in southern Vietnam, which is the economic hub of the country. For this purpose, Landsat-8 OLI and TIRS images acquired between 2015 and 2022 were used. It is observed that there was a significant reduction of 1 to 1.8 °C in LST in open areas, excepting impervious surfaces and built-up areas, during the strict lockdown period in Ho Chi Minh City, and an increase in LST since then. The observed reduction in LST during the lockdown period in Ho Chi Minh City is in agreement with the reduction in greenhouses gases during the same period in recent studies. Human mobility and industrial activities have been restored in November 2021 in the study area which would explain the regain in LST in the post-lockdown period.
Subject(s)
COVID-19 , Hot Temperature , Humans , Cities , Temperature , Vietnam , Pandemics , Environmental Monitoring/methods , Communicable Disease Control , UrbanizationABSTRACT
When the external conditions change, such as the temperature or the pressure, the multi-component system sometimes separates into several phases with different components and structures, which is called phase separation. Increasing studies have shown that cells condense related biomolecules into independent compartments in order to carry out orderly and efficient biological reactions with the help of phase separation. Biomolecular condensates formed by phase separation play a significant role in a variety of cellular processes, including the control of signal transduction, the regulation of gene expression, and the stress response. In recent years, many phase separation events have been discovered in the immune response process. In this review, we provided a comprehensive and detailed overview of the role and mechanism of phase separation in the innate and adaptive immune responses, which will help the readers to appreciate the advance and importance of this field.
Subject(s)
Biomolecular Condensates , Immune System , TemperatureABSTRACT
During the coronavirus 2019 (COVID-19) pandemic, the implementation of non-contact infrared thermometry (NCIT) became an increasingly popular method of screening body temperature. However, data on the accuracy of these devices and the standardisation of their use are limited. In the current study, the body temperature of non-febrile volunteers was measured using infrared (IR) thermography, IR tympanic thermometry and IR gun thermometry at different facial feature locations and distances and compared with SpotOn core-body temperature. Poor agreement was found between all IR devices and SpotOn measurements (intra-class correlation coefficient <0.8). Bland-Alman analysis showed the narrowest limits of agreement with the IR gun at 3 cm from the forehead (bias = 0.19°C, limits of agreement (LOA): -0.58°C to 0.97°C) and widest with the IR gun at the nose (bias = 1.40°C, LOA: -1.15°C to 3.94°C). Thus, our findings challenge the established use of IR thermometry devices within hospital settings without adequate standard operating procedures to reduce operator error.
Subject(s)
COVID-19 , Thermometry , Humans , Body Temperature , Temperature , Thermometry/methods , COVID-19/diagnosis , VolunteersABSTRACT
COVID-19 has been pandemic since 2020 with persistent generation of new variants. Cellular receptor for SARS-CoV-2 is angiotensin-converting enzyme 2 (ACE2), where transmembrane serine protease-2 (TMPRSS2) is essential for viral internalization. We recently reported abundant expression of ACE2 and TMPRSS2 in the oral cavity of humans and mice. Therefore, oral cavity may work for COVID-19 infection gates. Here we undertook to evaluate whether vaccination in the tongue harbors any merit in comparison to subcutaneous injection. Low-temperature plasma (LTP) is the fourth physical state of matters with ionization above gas but at body temperature. LTP provides complex chemistry, eventually supplying oxidative and/or nitrosative stress on the interface. LTP-associated cellular death has been reported to cause apoptosis and/or ferroptosis. However, there is few data available on immunogenicity retention after LTP exposure. We therefore studied the effect of LTP exposure after the injection of keyhole limpet hemocyanin (KLH) or spike 2 protein of SARS-CoV-2 to the tongue of six-week-old male BALB/c mice, compared to subcutaneous vaccination. Whereas LTP did not change the expression of ACE2 and TMPRSS2 in the tongue, repeated LTP exposure after tongue vaccination significantly promoted systemic and specific IgM production at day 11. In contrast, repeated LTP exposure after subcutaneous vaccination of KLH decreased systemic IgM production. Of note, tongue injection produced significantly higher titer of IgM and IgG in the case of KLH. In conclusion, LTP significantly reinforced humoral immunity by IgM after tongue injection. Vaccination to the tongue can be a novel strategy to acquire immediate immunity.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Male , Animals , Mice , SARS-CoV-2/metabolism , Angiotensin-Converting Enzyme 2 , Spike Glycoprotein, Coronavirus/metabolism , Temperature , Tongue/metabolism , Immunoglobulin MABSTRACT
The Central African Region is an agricultural and fishing-based economy, with 40% of the population living in rural communities. The negative impacts of climate change have caused economic/health-related adverse impacts and food insecurity. This original article aims to research four key themes: (i) acute food insecurity (AFI); (ii) childhood malnutrition and mortality; (iii) infectious disease burden; and (iv) drought and mean temperature projections throughout the twenty-first century. Food insecurity was mapped in Central Africa based on the Integrated Food Security Phase Classification (IPC) for AFI. The global hunger index (GHI) was presented along with the proportion of children with undernourishment, stunting, wasting, and mortality. Data for infectious disease burden was computed by assessing the adjusted rate of change (AROC) of mortality due to diarrhea among children and the burden of death rates due to pneumonia across all age groups. Finally, the mean drought index was computed through the year 2100. This population-based study identifies high levels of hunger across a majority of the countries, with the mean drought index suggesting extreme ends of wet and dry days and an overall rise of 1-3 °C. This study is a source of evidence for stakeholders, policymakers, and the population residing in Central Africa.
Subject(s)
Communicable Diseases , Malnutrition , Humans , Child , Droughts , Temperature , Food Supply , Malnutrition/epidemiology , Food Insecurity , Africa, Central/epidemiologyABSTRACT
Messenger RNA (mRNA) lipid nanoparticles (LNPs) have emerged at the forefront during the COVID-19 vaccination campaign. Despite their tremendous success, mRNA vaccines currently require storage at deep freeze temperatures which complicates their storage and distribution, and ultimately leads to lower accessibility to low- and middle-income countries. To elaborate on this challenge, we investigated freeze-drying as a method to enable storage of mRNA LNPs at room- and even higher temperatures. More specifically, we explored a novel continuous freeze-drying technique based on spin-freezing, which has several advantages compared to classical batch freeze-drying including a much shorter drying time and improved process and product quality controlling. Here, we give insight into the variables that play a role during freeze-drying by evaluating the impact of the buffer and mRNA LNP formulation (ionizable lipid to mRNA weight ratio) on properties such as size, morphology and mRNA encapsulation. We found that a sufficiently high ionizable lipid to mRNA weight ratio was necessary to prevent leakage of mRNA during freeze-drying and that phosphate and Tris, but not PBS, were appropriate buffers for lyophilization of mRNA LNPs. We also studied the stability of optimally lyophilized mRNA LNPs at 4 °C, 22 °C, and 37 °C and found that transfection properties of lyophilized mRNA LNPs were maintained during at least 12 weeks. To our knowledge, this is the first study that demonstrates that optimally lyophilized mRNA LNPs can be safely stored at higher temperatures for months without losing their transfection properties.
Subject(s)
COVID-19 , Nanoparticles , Humans , Temperature , RNA, Messenger , COVID-19 Vaccines , Freeze Drying/methods , LipidsABSTRACT
A healthy and safe indoor environment is an important part of containing the coronavirus disease 2019 (COVID-19) pandemic. Therefore, this work presents a real-time Internet of things (IoT) software architecture to automatically calculate and visualize a COVID-19 aerosol transmission risk estimation. This risk estimation is based on indoor climate sensor data, such as carbon dioxide (CO2) and temperature, which is fed into Streaming MASSIF, a semantic stream processing platform, to perform the computations. The results are visualized on a dynamic dashboard that automatically suggests appropriate visualizations based on the semantics of the data. To evaluate the complete architecture, the indoor climate during the student examination periods of January 2020 (pre-COVID) and January 2021 (mid-COVID) was analyzed. When compared to each other, we observe that the COVID-19 measures in 2021 resulted in a safer indoor environment.
Subject(s)
Air Pollution, Indoor , COVID-19 , Humans , Air Pollution, Indoor/analysis , Respiratory Aerosols and Droplets , Software , TemperatureABSTRACT
With the outbreak of COVID-19, epidemic prevention has become a way to prevent the spread of epidemics. Many public places, such as hospitals, schools, and office places, require disinfection and temperature measurement. To implement epidemic prevention systems and reduce the risk of infection, it is a recent trend to measure body temperature through non-contact sensing systems with thermal imaging cameras. Compared to fingerprints and irises, face recognition is accurate and does not require close contact, which significantly reduces the risk of infection. However, masks block most facial features, resulting in the low accuracy of face recognition systems. This work combines masked face recognition with a thermal imaging camera for use as an automated attendance system. It can record body temperature and recognize the person at the same time. Through the designed UI system, we can search the attendance information of each person. We not only provide the design method based on convolutional neural networks (CNNs), but also provide the complete embedded system as a real demonstration and achieve a 94.1% accuracy rate of masked face recognition in the real world. With the face recognition system combined with a thermal imaging camera, the purpose of screening body temperature when checking in at work can be achieved.
Subject(s)
COVID-19 , Facial Recognition , Humans , Body Temperature , Temperature , COVID-19/diagnosis , Neural Networks, ComputerABSTRACT
In urban areas, industrial and human activities are the prime cause that exacerbates the heating effects, also called the urban heat island (UHI) effect. The land surface temperature (LST), normalized difference vegetation index (NDVI), and the proportion of vegetation (Pv) are indicators of measurement of the heating/urbanization effects. In the present work, we investigated the impact of the COVID-19 lockdown, i.e., restricted human activities. We used Landsat-8 OLI/TIRS (level 1) data to investigate spatial and temporal heterogeneity changes in these urbanization indicators during full and partial lockdown periods in 2020 and 2021, with 2019 as the base year. We have selected three cities in India's eastern coal mining belt, Bokaro, Dhanbad, and Ranchi, for the study. Results showed a significant decrease in LST values over all sites, with a maximum reduction over mining sites, i.e., Bokaro and Dhanbad. The LST value decreased by about 13-19% during the lockdown period. Vegetation indices (i.e., NDVI and Pv) showed a substantial increase of about 15% overall sites. With decreased LST values and increased NDVI values, these quantities' correlations became more negative during the lockdown period. More positive changes are noticed over mining sites than non/less mining sites. This indirectly indicates the reduction in the heat-absorbing particles in the environment and surface of these sites, a possible cause for the reduction in LST values substantially. Reduction in coal particles at the land and vegetation surface likely contributed to decreased LST and enhanced vegetation indices. To check the statistical significance of changes in the UHI indicators in the lockdown period, statistical tests (ANOVA and Tukey's test) are performed. Results indicate that most of the case changes have been significant. The study's finding suggests the lockdown's positive impact on the heating/UHI effects. It emphasizes the need for planned lockdowns as city mitigation strategies to overcome pollution and environmental issues.
Subject(s)
COVID-19 , Hot Temperature , Humans , Temperature , Cities , Environmental Monitoring/methods , COVID-19/epidemiology , Communicable Disease Control , UrbanizationABSTRACT
Non-contact temperature measurement of persons during an epidemic is the most preferred measurement option because of the safety of personnel and minimal possibility of spreading infection. The use of infrared (IR) sensors to monitor building entrances for infected persons has seen a major boom between 2020 and 2022 due to the COVID-19 epidemic, but with questionable results. This article does not deal with the precise determination of the temperature of an individual person but focuses on the possibility of using infrared cameras for monitoring the health of the population. The aim is to use large amounts of infrared data from many locations to provide information to epidemiologists so they can have better information about potential outbreaks. This paper focuses on the long-term monitoring of the temperature of passing persons inside public buildings and the search for the most appropriate tools for this purpose and is intended as the first step towards creating a useful tool for epidemiologists. As a classical approach, the identification of persons based on their characteristic temperature values over time throughout the day is used. These results are compared with the results of a method using artificial intelligence (AI) to evaluate temperature from simultaneously acquired infrared images. The advantages and disadvantages of both methods are discussed.
Subject(s)
Artificial Intelligence , COVID-19 , Humans , COVID-19/epidemiology , Thermography/methods , Body Temperature , Temperature , Infrared RaysABSTRACT
Wearable sensors and machine learning algorithms are widely used for predicting an individual's thermal sensation. However, most of the studies are limited to controlled laboratory experiments with inconvenient wearable sensors without considering the dynamic behavior of ambient conditions. In this study, we focused on predicting individual dynamic thermal sensation based on physiological and psychological data. We designed a smart face mask that can measure skin temperature (SKT) and exhaled breath temperature (EBT) and is powered by a rechargeable battery. Real-time human experiments were performed in a subway cabin with twenty male students under natural conditions. The data were collected using a smartphone application, and we created features using the wavelet decomposition technique. The bagged tree algorithm was selected to train the individual model, which showed an overall accuracy and f-1 score of 98.14% and 96.33%, respectively. An individual's thermal sensation was significantly correlated with SKT, EBT, and associated features.