Global impacts of Covid-19 on lifestyles and health and preparation preferences: an international survey of 30 countries

Background: The health area being greatest impacted by coronavirus disease 2019 (COVID-19) and residents' perspective to better prepare for future pandemic remain unknown. We aimed to assess and make cross-country and cross-region comparisons of the global impacts of COVID-19 and preparation preferences of pandemic. Methods: We recruited adults in 30 countries covering all World Health Organization (WHO) regions from July 2020 to August 2021. 5 Likert-point scales were used to measure their perceived change in 32 aspects due to COVID-19 (-2 = substantially reduced to 2 = substantially increased) and perceived importance of 13 preparations (1 = not important to 5 = extremely important). Samples were stratified by age and gender in the corresponding countries. Multidimensional preference analysis displays disparities between 30 countries, WHO regions, economic development levels, and COVID-19 severity levels. Results: 16 512 adults participated, with 10 351 females. Among 32 aspects of impact, the most affected were having a meal at home (mean (m) = 0.84, standard error (SE) = 0.01), cooking at home (m = 0.78, SE = 0.01), social activities (m = -0.68, SE = 0.01), duration of screen time (m = 0.67, SE = 0.01), and duration of sitting (m = 0.59, SE = 0.01). Alcohol (m = -0.36, SE = 0.01) and tobacco (m = -0.38, SE = 0.01) consumption declined moderately. Among 13 preparations, respondents rated medicine delivery (m = 3.50, SE = 0.01), getting prescribed medicine in a hospital visit / follow-up in a community pharmacy (m = 3.37, SE = 0.01), and online shopping (m = 3.33, SE = 0.02) as the most important. The multidimensional preference analysis showed the European Region, Region of the Americas, Western Pacific Region and countries with a high-income level or medium to high COVID-19 severity were more adversely impacted on sitting and screen time duration and social activities, whereas other regions and countries experienced more cooking and eating at home. Countries with a high-income level or medium to high COVID-19 severity reported higher perceived mental burden and emotional distress. Except for low- and lower-middle-income countries, medicine delivery was always prioritised. Conclusions: Global increasing sitting and screen time and limiting social activities deserve as much attention as mental health. Besides, the pandemic has ushered in a notable enhancement in lifestyle of home cooking and eating, while simultaneously reducing the consumption of tobacco and alcohol. A health care system and technological infrastructure that facilitate medicine delivery, medicine prescription, and online shopping are priorities for coping with future pandemics

Literacy critical to heart failure management: a scoping review.

Heart failure is a complex clinical syndrome most commonly encountered among older adults. This complex clinical syndrome is associated with poor health outcomes such as frequent admissions and mortality. These adverse outcomes are commonly associated with poor self-care and lower health literacy. Literacy is a combination of knowledge and skills and often reflected by appropriate interaction with the community, while health literacy is the cognitive and social skills reflected by accessing and comprehending health information and making appropriate health decisions. These decisions are common and challenging to patients with heart failure. Poor outcomes are said to be reduced by adequate self-care, which is associated with health literacy among heart failure patients. Better self-care was also shown to be associated with self-efficacy and self-confidence that were in turn associated with health literacy. Hence, enhancing health literacy among patient with heart failure is critical to enable them to increase control over their disease by better understanding and participating in health care, while being empowered to take part in designing health care services and even tailoring research to serve their needs and consequently improve outcome at the individual and community level. In clinical practice, assessing health literacy, measuring health literacy, and identifying patients at risk of low nutrition literacy is important to enhance health literacy and health outcomes. Hence, developing reliable and valid methods and tools for assessment and developing tailored and targeted interventions is of critical importance

New approach to intersection modeling - FLINT

The Florida Department of Transportation has developed a new carbon monoxide intersection model, called FLINT. FLINT is a user-friendly model using radically new ideas for emission allocation, traffic movement and dispersion. Preliminary testing has shown it to be more accurate than existing models. Further testing on databases will better determine FLINT\u27s accuracy and merit compared to other models

Queueing algorithm for calculating idling emissions in FLINT - The FLorida INTersection air quality model

The theoretical development of the queueing model used in the FLINT (FLorida INTersection) air quality model is described. FLINT is an area source model used to predict carbon monoxide concentrations for undersaturated and oversaturated traffic conditions at signalized intersections. In the FLINT model, deterministic queueing is used to estimate the queue length for cases of undersaturated conditions. In oversaturated cases, a cycle failure method has been developed to estimate queue length. In addition, a new concept is presented for calculating idling time for each vehicle\u27s position in the queue during both the red and the green phases of the traffic signal cycle. A limited set of undersaturated cases from monitoring data in Melrose Park, Illinois, was used to compare the predicted queue lengths with the measured queue lengths for several air quality models. It was found that FLINT predicted the queue length within one vehicle of the observed queue length. The same cases were tested using CAL3QHC, TEXIN2 intersection air quality models, and the American Automobile Manufacturers Association (AAMA) simulation model. It was found that predictions of the AAMA and the FLINT models were very close to the measured queue lengths in cases of undersaturated conditions. Moreover, although the FLINT and the AAMA models use a different approach to estimate queue length, their predicted queue lengths were very close in oversaturated cases. However, the predicted queue lengths of CAL3QHC were too long for oversaturated cases

Traffic operations during Electronic Toll Collection: Case study of the Holland East Plaza

The toll plaza model or TPModel is a macroscopic analytical queuing model, developed for estimating the rush hour delay at toll collection facilities. TPModel can be used to compare the performance of a plaza under different lane configurations. A delay sensitivity analysis was performed on each of the model\u27s variable. TPModel estimated increasing delay with increasing approach traffic rush hour volumes. TPModel also estimated smaller plaza delays as the service rate for the various services increased

Applications of queuing models to Electronic Toll Collection

Electronic Toll Collection (ETC) via Automatic Vehicle Identification (AVI) technology has significantly altered traffic operations during toll collection. In particular, the value of the average processing rate of a lane providing both ETC service as well as a traditional service, fluctuates over the rush hour between the average value of the processing rate of the traditional service and the capacity of the ETC service. This study develops a queuing model to address the changing processing rates for the different mixed lanes. The model is applied to the westbound 9-lane portion of the Holland East Plaza in Orlando, Florida. Data is evaluated for 6 different rush hours that include 3 different configuration patterns implemented over a period of 3 years. In the first configuration, only the traditional toll collection services are provided. In another configuration, all traditional lanes become mixed to include ETC except for the center lane, which becomes a lane dedicated solely to ETC service. In a final configuration, two lanes become dedicated to ETC service. A calibration factor between 1.15 and 1.19 corrects the predicted delay. A plaza delay sensitivity analysis is performed on each of the model\u27s input variables

Modeling traffic operations at electronic toll collection and traffic management systems

Automatic Vehicle Identification (AVI) technology is one possible solution to traffic congestion at existing transportation facilities. This paper presents a mathematical model of traffic conditions for toll plaza facilities that includes AVI toll collection services among other conventional services. Three types of services are available: manual toll service, in which transactions are handled by a toll collector, automatic toll service, in which coin machines are utilized, and AVI toll collection service. In addition, mixed lanes, which provide more than one of the above services, are considered by the model. For a given rush hour, queue lengths and delays can be calculated for different toll plaza configurations. Comparison of their performance may aid operators in the management of the lane configurations until all users of the facility become AVI patrons. © 1997 Elsevier Science Ltd

<title>Application of queuing models to electronic toll collection</title>

Electronic Toll Collection (ETC) via Automatic Vehicle Identification (AVI) technology has significantly altered traffic operations during toll collection. In particular, the value of the average processing rate of a lane providing both ETC service as well as a traditional service, fluctuates over the rush hour between the average value of the processing rate of the traditional service and the capacity of the ETC service. This study develops a queuing model to address the changing processing rates for the different mixed lanes. The model is applied to the westbound 9-lane portion of the Holland East Plaza in Orlando, Florida. Data is evaluated for 6 different rush hours that include 3 different configuration patterns implemented over a period of 3 years. In the first configuration, only the traditional toll collection services are provided. In another configuration, all traditional lanes become mixed to include ETC except for the center lane, which becomes a lane dedicated solely to ETC service. In a final configuration, two lanes become dedicated to ETC service. A calibration factor between 1.15 and 1.19 corrects the predicted delay. A plaza delay sensitivity analysis is performed on each of the model\u27s input variables