Perceptions about infodemic in the context of a syndemic from an extension course

In 2020, we live in obscure times of a health crisis due to the Sars-CoV-2 syndemic that opened up perverse social inequality and the inability to provide all basic public services with the legitimation of necropolitics and nefarious arguments. There was also a vertiginous growth of information, which was transmitted mainly by social media, with a global reach and which was not always accurate. In the midst of this scenario, an extension course was promoted in order to facilitate the dialogue and exchange of knowledge between the community and the university, thus overcoming the discourse of academic hegemony and replacing it with the idea of an alliance with movements, sectors and social organizations. In this work, the speeches of the course participants in relation to the texts produced during the course were analyzed, taking as a pillar the content analysis of Bardin (2002). Participants pondered, among other aspects, about underreporting, social inequality and the search for reliable information. We conclude with the understanding of the importance of facing the verb to hope as an imperative;not as a way to conform, but to resist and try to seek solutions together. © 2022, Brazilian Institute for Information in Science and Technology. All rights reserved.

Negative Air Pressure Isolation Room for COVID-19 Patients in the Philippines: A Simulation of the Proposed Design using SolidWorks

Since the start of the 2019 pandemic, medical staff and non-medical staff are fighting on the front line in all hospitals worldwide. However, the possibility of healthcare workers' scarcity due to the increasing medical infection rate is ignored in many recent studies. To prevent such things to happen, the installation of a negative air pressure isolation room is proposed to Norzagaray Municipal Hospital (NMH). Primary parameters such as filtration, pressure management, and dilution ventilation were investigated in SOLIDWORKS simulation software by removing one parameter per simulation. Two existing schemes were simulated, and the primary parameters present were evaluated. Three ventilation design set-ups were designed and the effects of the varying placements of the primary parameters to the airflow pattern in a negative air pressure isolation room were determined. Cost-benefit analysis (CBA) was conducted to determine if the cost of installing the negative air pressure room outweighs its benefit. The set-up where the High efficiency particulate air (HEPA) machine is inside the room is proposed to NMH as this abides by the Department of Health (DOH) memorandum and standards on Airborne Infection Isolation Rooms (AIIRs) and is the most effective of the three set-ups. Results show that filtration filters the infectious particles, pressure management manages the proper airflow direction, and dilution ventilation makes sure there are enough air changes per hour to filter a percentage of infectious particles. In the existing schemes, all the primary parameters were used to contain the infectious particles in the room, however, the effectivity of the filtration also depends on the location of the patient, supply, and exhaust. The most significant effect of the varying placements of the primary parameters can be seen in filtration as only the set-up where the HEPA machine is inside the room was able to filter 100% of the infectious particles. It is also the most profitable ventilation design set-up with a 2.08 CBA ratio and has the least payback period of 5.8 months. © 2021 IEEE.

Impacts of COVID-19 Pandemic Crisis in the Transportation Sector: A Classification Analysis in Regard with Preferred Modes of Transportation Using Random Forest Algorithm

The study observes the Pandemic Crisis (Covid 19) that resulted in impacts on the Transportation category in the area National Capital Region. Public transportation is an important aspect of human's ability to travel to different places whether its personal or business purpose, it's a part of life that people take for granted and can't be taken away easily. But due to the pandemic era, people have been careful in their choices, which resulted in the change standard when it comes to public transportation choices. With that said, to understand and observe these impacts, a scenario must be made such as before and after the pandemic designed as an environment for the study to take root. The study has used machine learning called Random Forest Algorithm with the used several parameters to create a prediction model. As for the method in gathering data, a survey of Google Form is utilized to gather 200 participants of the National Capital Region with varying parameters for their choice of public transportation. The machine algorithm has shown satisfactory accuracy of 89.88% and 88.88%. As an important note, it is observed that travel expense has more impact on public transportation choices than other parameters. The Random Forest Algorithm has been utilized in creating classification types of models and can help future researchers improve the machine learning approach. © 2021 IEEE.

Construction Labor Productivity in Construction Sites during the COVID-19 Pandemic Using Relative Importance Index (RII)

The construction industry is heavily reliant on the production of laborers, and construction labor costs share a big part in the total cost of the projects. Due to the emergence of the COVID-19, the construction industry has been experiencing restrictions and limitations in their project sites, affecting labor productivity. This paper aims to determine which factors are critical in influencing Construction Labor Productivity in the National Capital Region (NCR) in the Philippines during the COVID-19 pandemic by obtaining each of the critical factors' respective relative importance index. In order to achieve the study's objective, the researchers asked experts under the category AAAA companies who have a site and managerial experience during the pandemic to participate in an online questionnaire survey. 34 factors were considered for this study and categorized into four groups: (1) Human/labor;(2) Management;(3) Technological;and (4) COVID-19. The findings of the study were able to identify the 10 significant factors affecting labor productivity during the pandemic: (1) Laborer's Experience and Skill;(2) Availability of Materials;(3) Clarity of Instructions and Daily Task Assignments;(4) Coordination among Level Design Disciplines;(5) Shortage of Laborers, Construction Method;(6) Prolonged Delivery Period, Limited Number of Work Personnel Per Zone, Leadership of Construction Management;(7) Clarity of the Drawings and Specifications;(8) Communication among Laborers, Rework;(9) Social Distancing, Laborer's Absenteeism;and (10) Availability of Personal Protective Equipment. The study can guide construction firms for efficient management of laborers during a pandemic to improve construction labor productivity and accomplish a cost-effective project. © 2021 IEEE.

Household Awareness and Participation on Waste Disposal: An Effective Solid Waste Management Amidst COVID-19 Pandemic

This research aims to determine the demographics that affect the solid waste management behavior in San Martin Subdivision in Angono, Rizal, conducted during the time of pandemic. This aims to improve sustainability and help create programs that will improve the participation of the households towards positive waste management. Currently, there are limited studies involving waste management, especially in developing countries like the Philippines, where waste management problems are more prevalent, adding more solid wastes during the pandemic period. This will help developing countries improve their waste management system as it will open areas for research and development. The researchers seek through the study of the demographics that affects the attitude, knowledge, and practices of the households to create a more targeted solution for the area. Online questionnaires were distributed to the respondents and were analyzed using the Kruskal-Wallis test. The findings revealed the relevant demographics in the target area and created a conceptual framework that the administrators can adopt. For the knowledge, attitude, and practice of the households, the income of the family showed significance. The other significant demographics were the household size for the attitude section;educational attainment for the knowledge section;and all the demographics for the practice section. Knowing this relevance, the community can create policies that are catered more to the effective group equating to greater chance of success in the implementation. The significance of the study is that the household wastes comprise of more than half of the waste generation of the Philippines hence, targeting this sector of the society will greatly impact the solid waste problem in the country. © 2021 IEEE.