Spread Of COVID-19 Research Articles

Zombie firms and resource allocation: research trends and developments during the spread of COVID-19 1

ABSTRACT We identify so-called “zombie firms,” which survive with banks’ and governments’ support despite performing poorly without the prospect of recovery, using firms’ financial data. We set the criteria of the zombie firms by arranging methodologies proposed by the existing studies. It mainly focuses on Japan after the collapse of its bubble economy, European countries after the global financial crisis and the sovereign debt crises, China under debt expansion, and developed countries during the spread of COVID-19. The analysis shows that the number of zombie firms surged after the collapse of the bubble economy in the early 1990s in Japan. At least based on the currently available data in fiscal 2020 after the spread of COVID-19, we do not detect a problematic growth in the number of zombie firms as in the 1990s.

Differences in emergency hospitalization trauma patients during and after the COVID-19 pandemic.

The spread of COVID-19 has a huge impact on the medical system, affecting the normal order of routine patients, especially obvious effect on the Shenzhen Third People's Hospital as the designated hospital for COVID-19 patients. After the epidemic was loosened in early December 2022, the normal medical order gradually restored in China. How much was the impact on the admission and treatment of emergency trauma patients during and after the epidemic? This study aims to compare the differences between trauma patients admitted to the emergency department during and after the COVID-19 pandemic. The study included all trauma patients admitted through the emergency department from January 2020 to March 2024. Clinical data were collected, and a retrospective comparative analysis was performed on the characteristics of the two groups of trauma patients during and after the pandemic, including gender, age, average length of hospital stay, proportions of admissions to various departments, proportions of severe cases, proportions of surgical patients, and mortality rates, using statistical methods for analysis. The proportion of male patients during the pandemic (69.98%) was higher than after the pandemic (67.01%). The proportion of patients under 60 years of age during the pandemic was higher than that after the pandemic. There was no significant difference in the average hospital stay between patients during and after the pandemic (P>0.05). Comparisons between the two groups in terms of admissions to departments such as otolaryngology, hepatobiliary surgery, hepatic surgery, orthopedics, urology, neurosurgery, gastroenterology surgery, thoracic surgery, ophthalmology and intensive care unit showed no significant differences (P>0.05). The proportion of surgical patients during the pandemic (75.09%) was higher than after the pandemic (69.53%). The mortality rate during the pandemic (0.13%) was lower than after the pandemic (2.45%). The COVID-19 pandemic has impacted trauma patients admitted through the emergency department, with increases in the proportion of male and younger patients, surgical cases, and a decrease in mortality rates during the pandemic.

Modeling the impacts of governmental and human responses on COVID-19 spread using statistical machine learning

ABSTRACT Understanding the impacts of governmental and human responses on the pandemic control is imperative for forecasting pandemic spread under various responsive scenarios and guiding localized interventions before pharmaceutical interventions are available. This study analyzed multiple data sets, including social media, mobility, policy evaluations, and COVID-19 infection reports, to delineate the interactions between governmental and human responses and COVID-19 spread in the United States in 2020 when vaccinations were unavailable. The contributions are (1) uncovering the spatiotemporal variations in governmental and human responses during COVID-19; (2) developing a statistical machine learning algorithm that incorporates spatiotemporal dependencies and temporal lag effects to model the relationships between governmental and human responses and the pandemic spread; (3) dissecting the impacts of human responses on the pandemic across space and time. Results reveal that the determinants of COVID-19 health impacts transitioned from human mobility during the initial outbreak phase to both human mobility and stay-at-home policies during the rapid spread phase, and ultimately to the compound of human mobility, stay-at-home policies and the public awareness in the full-blown phase. These findings furnish guidance for policymakers in implementing adaptive and phased strategies.

Barriers and facilitators of compliance with infection prevention and control measures during the COVID-19 pandemic in health facilities in Kampala city, Uganda.

During the COVID-19 pandemic, Infection Prevention and Control (IPC) was crucial to reduce the spread of the virus in health facilities. This study explored the barriers and facilitators of IPC compliance among healthcare workers (HCWs) during the COVID-19 pandemic in Kampala City, Uganda. Key informant interviews were conducted with 14 participants in 12 health facilities located in Nakawa division, Kampala City. Of these facilities, 3 were government-owned, and 9 were private not-for-profit. Each health facility's participant was either the IPC focal person or a HCW knowledgeable about the IPC measures implemented there. Transcripts were coded using a newly generated codebook in Atlas.ti version 9, and thematic analysis was carried out to analyze the study findings. Participants identified the fear of contracting the virus as one of the primary facilitators for IPC compliance among HCWs during the COVID-19 pandemic. They explained that the sustainability of IPC measures in health facilities was partly due to HCWs' belief that they served as role models in the community for observing and implementing health-related behaviors, especially regarding COVID-19. Among the barriers, participants mentioned that not all HCWs got the opportunity to be trained on COVID-19 IPC. Only HCWs working in high-risk departments for COVID-19 such as triage or Intensive Care Units were prioritized. However, regardless of the department, all HCWs were exposed to potential COVID-19 patients, and the high workload led them to sometimes skip the required IPC measures. This study found that addressing the spread of COVID-19 among HCWs necessitated a comprehensive approach to IPC in health facilities. This approach should encompass capacity building, as well as provision of necessary supplies. In addition, HCWs, the hospital management and government have a role to play to ensure that IPC is fully implemented in the case of future related outbreaks.

Public Trust in Covid-19 Tracking Technology: A Survey of Attitudes About Hong Kong’s LeaveHomeSafe Mobile App

AbstractThe effectiveness of governments in addressing the Covid-19 pandemic has been analyzed through numerous perspectives, including state authority, capacity, and legitimacy. In Hong Kong, incumbent political tensions and lack of trust in government potentially weakened public support for official Covid-19 mitigation measures, which included a government-mandated mobile application to monitor personal movements and contacts. This episode invites academic inquiry about public trust in policies and associated technology. Based on a 2022 survey of more than 5,000 residents, this study finds that support for Hong Kong’s LeaveHomeSafe application is associated with, among other factors, a predisposition to cooperate with government in sharing personal data. Several control variables, including age, social media use, and vaccination status, are also associated with support for the application. Trust in policies that use technology and data, and agreement that the government was effective in managing the spread of Covid-19, do not significantly associate with public support for the application. This study deepens scholarly understandings about the distinction between public trust in government and public trust in government technology, a topic of recent interest in the context of smart cities and rapid advancements in artificial intelligence.

Fractal-Fractional Modeling of the Covid-19 Spread with Deterministic and Stochastic Approaches

Fractal-Fractional Modeling of the Covid-19 Spread with Deterministic and Stochastic Approaches

Personality and grocery hoarding during a pandemic

This study investigates the relationship between personality traits and grocery hoarding. Data were obtained from a representative sample of the U.S. population (N = 1,149) through a web-based survey conducted during the early stages of the Covid-19 pandemic. Grocery hoarding was assessed as a dichotomous variable, capturing whether respondents stocked up on food or daily necessities beyond their usual purchases during the initial spread of Covid-19. Personality traits were measured using the Big Five Inventory (BFI-10). An independent t-test showed that individuals who engaged in grocery hoarding exhibited higher levels of Extraversion and Agreeableness compared to those who did not. Logistic regression analysis revealed that in the initial step, higher levels of Neuroticism, Extraversion, and Agreeableness significantly predicted grocery hoarding. However, after controlling for age, gender, and residential area, only Neuroticism and Agreeableness remained significant predictors, while Extraversion lost its effect. These findings suggest that grocery hoarding during the early stages of Covid-19 in the U.S. was associated with higher levels of Neuroticism and Agreeableness. The results align with some previous research but diverge from others, highlighting the need for further investigation into the role of personality traits in hoarding behaviors during crises.

Discovering Hidden Pattern in COVID-19 Prevention through Exit-Entry Permit Letter (SIKM) System using Geospatial Analysis

Abstract COVID-19 was declared as a global pandemic in 2020, and described as a highly contagious virus that spreads through direct contact. Almost all countries affected by COVID-19 implement various steps to prevent its spread, one of which is lockdown, described as a prohibition of human movement outside the home. Jakarta, the capital city of Indonesia with a population of 10,609,681, implements restrictions on human movement entering and leaving of the city using the Exit-Entry Permit Letter (SIKM) system to prevent the spread of COVID-19. Lockdown does not chosen as option to prevent the spread of COVID-19 in Jakarta due to the consideration of its large population, which could have significant economic impacts on the community. Meanwhile, the SIKM system is designed to restrict the mobility of people entering and leaving Jakarta in order to control the spread of COVID-19, with the hope of minimizing significant impacts on the community’s economy. The aim of this research is to discover hidden patterns in human movement entering Jakarta through the SIKM system, utilizing geospatial analysis with Geographic Information System (GIS). The results of this research indicate that the central business district, known as the ‘Golden Triangle’ of Jakarta, emerges as the area with an economic activity zone with the densest hotspot as the primary destination for people during the implementation of the SIKM system. Furthermore, the hidden pattern of Jakarta’s spatial plan indicates that in general the economic activity tend to located in Central Jakarta, meanwhile the residence is tend to located around the borders of Jakarta. Therefore, with the geospatial analysis, hidden patterns of human movement during COVID-19 through the SIKM system can be identified for decision support system for Jakarta government.

A study on the fractional-order COVID-19 SEIQR model and parameter analysis using homotopy perturbation method

In this article, we present a fractional-order susceptible-exposed-infected-quarantine-recovered (SEIQR) model to analyze the dynamics of the COVID-19 pandemic. The model includes susceptible (S), exposed (E), infected (I), quarantined (Q), and recovered (R) populations and uses a fractional-order differential equation to provide a further accurate representation of the disease's progression. We employ the homotopy perturbation method (HPM) to derive analytical solutions and the Runge-Kutta fourth-order (RK4) method to obtain numerical solutions. The results indicate that the fractional-order model, particularly for a fractional parameter α = 0.40, provides better accuracy and stability compared to the classical integer-order model. This study highlights the importance of fractional-order modeling in understanding the spread of COVID-19 and suggests its potential application in predicting and controlling future epidemics.

Reassessing the information transmission and pricing influence of Shanghai crude oil futures: A time-varying perspective

The Shanghai crude oil futures market, known as INE, has achieved significant success in trading volume and is increasingly recognized as a nascent crucial oil futures contract. As INE aims to serve as a pivotal global pricing reference, evaluating the dynamic characteristics of its pricing capability is essential for comprehending the evolving market landscape. This study initiates with foundational insights from a time-varying perspective. We uncover the time-varying information transmission of INE within the crude oil futures system and reveal its time-varying predictive causality on crude oil spot prices. The empirical findings yield several significant observations. Firstly, the Shanghai crude oil futures consistently functioned as the net receiver of price information transmission from mainstream international crude oil futures. Secondly, during the initial months of post-INE listing, and amid the global spread of COVID-19, Shanghai crude oil futures displayed less information received. Thirdly, the significant predictive causal influence of INE on the crude oil spot markets is predominantly observed to be valid post-2021, with its predictive capabilities exhibiting an ongoing enhancement. Our findings indicate that INE is gradually solidifying and strengthening its role as an influential player in the global crude oil market as it matures.

PIV Experimental Study of Airflow Structures in a Multi-Slot Ventilation Enclosure with Opposed Jets

The airflow structure of enclosures directly affects the spread of COVID-19 and is also closely related to indoor air quality, the thermal comfort of personnel, and buildings’ energy consumption. A large number of studies on airflow field under mixing and displacement ventilation with a single air inlet in rectangular rooms have been conducted; however, to the best of the authors’ knowledge, only a limited number of studies have dealt with airflow structures in a multi-slot ventilation enclosure with opposed jets. Therefore, this paper uses PIV to study the velocity, turbulence information, and entropy of an unstable airflow field in a multi-slot ventilation enclosure with opposed jets under isothermal and non-isothermal conditions. This paper also presents, due to the collision of the jets to form two large-scale eddies, the airflow field structure being unstable. In the region without air supply inlets and exhaust outlets, a large-scale vortex is formed in the airflow field, resulting in the high information entropy of the flow field. The thermal plume suppresses the large-scale flow field structure and increases the small-scale flow field structure.

From ride hailing to food hailing: Understanding on-demand food delivery through platform urbanism and urban policy in Canadian cities

ABSTRACT This paper examines the pivot that took place during the COVID-19 pandemic from ride hailing to food hailing. In 2020, the global spread of COVID-19 challenged urban life, raising questions about the prospects for digital mobility platforms. Pandemic restrictions resulted in dramatic changes in mobility patterns globally, including significant declines in demand for ride hailing. Concurrently, with restaurants closed to indoor and outdoor dining for extended periods in many cities around the world, restaurateurs worked diligently to adjust their business models. During the early days of the COVID-19 lockdown, ride hailing firms such as Uber shifted their efforts from moving people to moving food and other goods. With a particular focus on Canada, we document this pivot and analyze its significance using evidence from case studies and interviews with multiple actors involved in the food and platform delivery ecosystem in major North American cities. We discovered both mutually beneficial and friction-filled relationships in the business, social and organizational logistics of digital food delivery. These results have implications for theories of platform urbanism and urban policy including highlighting new forms of competition that prioritize the role of urban infrastructure for creating value for platform firms.

Assessment of dental clinics’ infection control function using a checklist during the COVID-19 pandemic

IntroductionThe heightened risk of COVID-19 transmission during dental procedures has been a major concern in dentistry. To curb the spread of the virus, breaking the chain of transmission is paramount. This study aimed to assess infection control function in dental clinics using a supervisory checklist developed specifically during the COVID-19 pandemic.MethodIn April 2020, Alborz University of Medical Sciences introduced a 46-item checklist to guide infection control. Regular inspections of clinics began in June 2020 and continued every 6 months. Inspectors, accompanied by either the clinic manager or the infection control team, completed the checklist to evaluate protocol adherence. This retrospective cross-sectional study presents findings from the initial round of inspections.ResultsClinics were categorized as adherent or non-adherent based on achieving at least 50% of the total checklist score. Of the 76 clinics evaluated, 66 (86.8%) met the adherence criteria. The highest compliance was observed in question 12 (separation of employee and patient restrooms), with 81.6% adherence. The lowest compliance was in question 31 (use of disposable waterproof shoe covers), with only 26.3% adherence.ConclusionOver 80% of dental clinics demonstrated satisfactory adherence to COVID-19 infection control protocols. However, to further mitigate the spread of COVID-19, particularly its more contagious variants, enhancing compliance across all infection control measures remains essential.

The image of COVID-19 in the Russian linguistic consciousness

INTRODUCTION. The widespread spread of COVID-19 in Russia could not but affect the Russian linguistic consciousness, in which the associative thesaurus of the 21st century pandemic is being formed to one degree or another. Russian-language information resources are full of information about the new virus and the need for vaccination against it. These topics are actively discussed by the entire Russian-speaking population. The aim is to explore the image of COVID-19 in the Russian linguistic consciousness in the aspect of syntagmatic, paradigmatic and thematic associative thesaurus in two time periods: May–June 2020 and May–June 2021.MATERIALS AND METHODS. The research material is the National Russian Language Corps, social network’s hashtags, printed and electronic content « Rossiyskaya Gazeta and RBC newspapers. The associative experiment method is used to identify syntagmatic and paradigmatic reactions and thematic groups.RESULTS AND DISCUSSION. The analysis is an attempt to demonstrate the formation state of the concept of COVID-19 in the linguistic consciousness of Russians. The subject of the study was the syntactic function of the COVID-19 lexeme and the results of an associative experiment.CONCLUSION. The syntactic function of the COVID-19 lexeme, its lexical compatibility and connotation have been identified. It has been established that the perception of the COVID-19 epidemic in the linguistic consciousness is assessed as a typical characteristic of modernity and is recognized as part of reality along with the problems of global changes in ecology and climate and exists along with such concepts as globalization, digitalization and convergence.

A Novel Fractional Model Combined with Numerical Simulation to Examine the Impact of Lockdown on COVID-19 Spread

One of the best procedures for preventing the spread of the coronavirus is a lockdown, if it is implemented correctly. In order to assess how well lockdowns prevent the virus’s propagation, this paper presents a fractional-order mathematical model constructed by the proportional-Caputo operator. This model consists of five nonlinear fractional-order differential equations. The solution’s existence and uniqueness are investigated using the Schauder and Banach fixed-point theorems. Also, this study produces a stability analysis utilizing Ulam–Hyers and modified Ulam–Hyers criteria. Furthermore, the Adams–Bashforth–Moulton approach is used to implement numerical simulations that show how the model behaves with different parameter combinations and to validate the theoretical results.

Depression, Anxiety, Stress and Its Association with Coping Strategies among Malaysian University Students

Malaysia is one of the countries transitioning from the pandemic phase to an endemic phase of Covid-19. The spread of Covid-19 had a significant impact on university students, affecting their mental health just as it did for many others. This study investigates depression, anxiety, and stress symptom levels among Malaysian university students and the coping strategies used to prevent or reduce these psychological distress symptoms. A web-based questionnaire was developed using Google Forms to collect data from students who were selected non-randomly from three public universities and one from a private university in Malaysia. Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and Perceived Stress Scales-10 (PSS-10) were used for measuring depression, anxiety, and stress respectively. The coping strategies were measured using five strategies: seeking social support for emotional reasons, seeking social support for instrumental reasons, acceptance, mental disengagement, and humanitarian. The study findings indicated that 60.7% had depression symptoms, 30.4% had anxiety symptoms, and 86.3% had stress symptoms at moderate-to-severe levels. Acceptance was the most preferred coping strategy among the students while seeking social support for instrumental reasons was the least preferred coping strategy. Students with severe depression levels used mental disengagement coping strategies more than those with mild symptoms. Mental disengagement coping strategy was associated with severe anxiety symptoms compared to mild and minimal symptoms. Seeking social support for emotional reasons was also associated with moderate anxiety symptoms compared to mild anxiety symptoms.

The effects of COVID-19 lockdown and reopening on rest-activity rhythms in Singaporean working adults: A longitudinal age group comparison study

Study objectivesCOVID-19 mobility restrictions disrupted daily rhythms worldwide, but how this rhythm disruption differs across age groups is unclear. We examined the course of age-related differences in trajectories of rest-activity rhythm during the COVID-19 pandemic lockdown and reopening in Singapore. We also evaluated the association of these patterns with mental well-being. Methods24-hour step count data (Fitbit) were obtained from 617 younger (age range: 21-40) and 602 older adults (age range: 55-70) from January 2020 (baseline) through lockdown (April 2020) and reopening periods until August 2021. Nonparametric rest-activity rhythm metrics: interdaily stability, intradaily variability and most active 10-hour period (M10) were computed. Longitudinal changes in rest-activity rhythm, age-related differences in changes, and the associations between mental well-being and these changes were assessed using nonlinear latent-growth models. ResultsIn younger adults, mobility restrictions during lockdown caused significant decline in interdaily stability and M10, alongside significant increase in intradaily variability. However, in older adults, changes were confined to increased intradaily variability and decreased M10. Older adults also showed less change in intradaily variability and M10 compared to younger adults. Gradual recovery of rest-activity rhythm metrics during reopening was observed, with interdaily stability and M10 remaining lower after 15months post-lockdown. In younger but not older adults, a larger decline in interdaily stability was associated with poorer mental well-being 15months post-lockdown. ConclusionYounger adults appear more vulnerable than older adults to mobility restrictions as reflected in their rest-activity rhythm metrics. A significant disruption of daily routine may have long-lasting effects on younger adults’ mental well-being. Statement of significanceAlthough stringent mobility restrictions imposed to curb the spread of COVID-19 were imposed primarily to protect older adults, we found that younger adults were more vulnerable to rhythm disruption arising from mobility restrictions. Disrupted rhythm stability was associated with poorer mental well-being 15months after the lockdown ended in younger but not older adults. These asymmetric long-term effects on mental health on younger relative to older adults should be kept in mind when planning for large-scale catastrophes linked to mobility restrictions.

Analysis of the Effect of Novel Coronavirus 2019 (Covid-19) Spreading Toward Sharia Stock Market in Indonesia

The purpose of this research is to identify and analyze the influence of the spread of Novel Coronavirus 2019 (Covid-19), the policies of Indonesian Government during pandemic (i.e. work from home, large-scale social restrictions (PSBB) and community activities restriction enforcement (PPKM), the movement of FTSE 100 and Nasdaq Composite indexes on Islamic stock market in Indonesia (represented by the Indonesian Sharia Stock Index). This study utilizes the Vector Error Correction Model (VECM), Impulse Response Function (IRF), and Forecast Error Correction Model (FEVD) approach, with the range data from September 2019 to November 2022. The results of this research indicates that the VECM test showed that Covid-19 case in Indonesia and the movement of FTSE 100 had a significant positive effect on ISSI in the long term. Meanwhile, in the short term, Covid-19 case in Indonesia and government policies have had a significant negative effect on ISSI. In the IRF test, this shows that the Covid-19 case in Indonesia and government policies during pandemic have had a significant negative effect on ISSI. Conversely, the movement of the FTSE 100 and Nasdaq Composite Index has a significant positive effect on ISSI. In the FEVD test, it can be seen that the biggest contribution to ISSI shock movement was the shock itself of 85.24% and was followed by government policies, the Covid-19 case, FTSE 100 and Nasdaq. This investigation use three variables in order to search the effect of these factors on the movement of sharia stock market in Indonesia. The stock market represented by Indonesian Sharia Stock Index (ISSI).

Determining the risk level of covid-19 infection of medical workers

Introduction. The primary task in assessing the probable risk of infection is to identify potential threats to the health and well-being of the population, determine the risks associated with the occupational activities of workers in various fields, including medical workers of various specialties, as well as analyze the effectiveness of measures already implemented to prevent them. Materials and methods. An analysis of literature data in the Russian and English-language segments, own and dissertation research was carried out, significant factors in the spread of COVID-19 for medical workers of different specialties were identified. Results. Based on the results of own research, the most significant risk factor in the spread of COVID-19 for medical workers was identified – failure to maintain a social distance of 1.5 meters (49.5%). An assessment was made of the level of probable risk of COVID-19 infection in the workplace for medical workers. The majority estimated the probable risk of infection at 1–2 points, which is moderate or low. Doctors – epidemiologists: about 48% of respondents spend more than 5 hours in the outbreak; 55.0% maintain a social distance of 1–1.5 meters; 65.0% of respondents visit 1–2 centers per day. General practitioners: 42.6% have contact with 5 or fewer patients; 29.5% maintain a social distance of 1–1.5 meters and 42.6% of respondents spend 5-10 minutes per patient. Limitations. To implement this study, the required number of respondents was calculated using the method proposed by Viechtbauer W. et al. (2015). In this case, a 95% confidence interval and an expected response rate of 0.05 were set. According to the results obtained, at least ninety two people should take part in the study, which is a sufficient reference sample. Conclusion. According to epidemiologists, the most significant factor in the spread of COVID-19 was failure to maintain a social distance of 1.5 meters and the failure to use masks when working with patients sick with the new coronavirus infection. According to general practitioners, the key factors in the spread of COVID-19 were the number of contacts with patients, the number of epicenters of infection visited, the length of the doctor’s stay at the site of the disease, as well as the distance during contact with the patient.

Effectiveness of Aerosol Filtration by Mechanical Filter, Electrostatic Filter, and Electrostatic Filter with Heat Moisture Exchanger in Healthy Volunteers Nebulized with Normal Saline: A Randomized Crossover Trial

Background: The COVID-19 outbreak in Thailand has raised concerns that aerosol generated from the nebulizer might be contaminated with SARS-CoV-2. To prevent this, various types of viral filters might be useful in decreasing the spread of COVID-19. Objective: To compare the effectiveness of mechanical filter, electrostatic filter, and electrostatic filter with heat moisture exchanger (HME) to no filter in filtration nebulized normal saline solution (NSS). Materials and Methods: The present study was a randomized, single-blind crossover trial. Forty-eight healthy volunteers were given nebulized NSS via the mouthpiece. At the end of the system, a filter or no filter was attached according to the randomization series. The primary outcome was the number of particles per cubic foot measured at two locations, distal to the filter, which is referred to as ‘near distant’ and 180 centimeters away from the system, which is referred to as ‘far distant’ during nebulization. The measurement was recorded every minute from the beginning of nebulization until the fifth minute. Results: Forty-eight healthy volunteers were studied with four types of filtration methods. The number of particles per cubic foot was compared by intervention using a multi-level mixed effect linear regression, a statistical method that accounted for the repeated measurements within each participant. The highest number of particles was measured at the near distant in no filter group, with a mean of 188,034 particles per cubic feet and a maximum of 370,816 particles per cubic feet and lowest number was measured at the far distant in mechanical filter group with a mean of 199 per cubic feet and a maximum of 316 particles per cubic feet. The ranking of the number of particles from the highest to the lowest were no filter, electrostatic filter, electrostatic filter with HME, and mechanical filter. Each type of filter significantly decreased the number of particles compared to no filter usage (p<0.001). However, no significant difference was found among each type of filter. Conclusion: Mechanical filter, electrostatic filter, and electrostatic with HME lessened the number of particle dispersion into the environment compared with no filter attached to the nebulization equipment.