The Importance of Behavioral and Native Factors on COVID-19 Infection and Severity: Insights from a Preliminary Cross-Sectional Study.

The COVID-19 pandemic has had a major impact on a global scale. Understanding the innate and lifestyle-related factors influencing the rate and severity of COVID-19 is important for making evidence-based recommendations. This cross-sectional study aims at establishing a potential relationship between human characteristics and vulnerability/resistance to SARS-CoV-2. We hypothesize that the impact of the virus is not the same due to cultural and ethnic differences. A cross-sectional study was performed using an online questionnaire. The methodology included the development of a multi-language survey, expert evaluation, and data analysis. Data were collected using a 13-item pre-tested questionnaire based on a literature review between 9 December 2020 and 21 July 2021. Data were statistically analyzed using logistic regression. For a total of 1125 respondents, 332 (29.5%) were COVID-19 positive; among them, 130 (11.5%) required home-based treatment, and 14 (1.2%) intensive care. The significant and most influential factors on infection included age, physical activity, and health status (p < 0.05), i.e., better physical activity and better health status significantly reduced the possibility of infection, while older age significantly increased it. The severity of infection was negatively associated with the acceptance (adherence and respect) of preventive measures and positively associated with tobacco (p < 0.05), i.e., smoking regularly significantly increases the severity of COVID-19 infection. This suggests the importance of behavioral factors compared to innate ones. Apparently, individual behavior is mainly responsible for the spread of the virus. Therefore, adopting a healthy lifestyle and scrupulously observing preventive measures, including vaccination, would greatly limit the probability of infection and prevent the development of severe COVID-19.

Micro-Fabricated RTD Based Sensor for Breathing Analysis and Monitoring.

The design, micro-fabrication, and characterization of a resistance temperature detector (RTD) based micro sensor for minimally invasive breathing analysis and monitoring is presented. Experimental results demonstrate that the change in air temperature while inhaling and exhaling can be transduced into a time varying electrical signal, which is subsequently used to determine the breathing frequency (respiratory rate). The RTD is placed into a Wheatstone bridge to simultaneously reduce the sensor's output noise and improve overall system accuracy. The proposed design could potentially aid health care providers in the determination of respiratory rates, which is of critical importance during the current COVID-19 pandemic.