The Day-Ahead Forecasting of the Passenger Occupancy in Public Transportation by Using Machine Learning

Public transport is one of the main infrastructures of a sustainable city. For this reason, there are many studies on public transportation which mostly answer the question of “when my next bus will arrive?”. However now when the public is under the restrictions of the Covid-19 pandemic and learning to live with new social rules such as “social distance” a new yet crucial question arise on public transportation: “how crowded my next bus will be?” To prevent the crowdedness in public transportation the traffic regulators need to forecast the number of passengers the day ahead. In this study, in cooperation with Synteda, we suggest a machine learning algorithm that forecasts the occupancy in a bus or tram the day ahead for each stop for a route. The input data is past passenger travel data provided by the Västtrafik AB which is the public transportation company in Gothenburg, Sweden. The hourly data for the precipitation and temperature also has been added to the forecasting method;the database of precipitation and temperature is obtained by the SMHI, Swedish Meteorological and Hydrological Institute. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

Examining the effects of the COVID-19 pandemic on community engagement for people with mobility disabilities.

BACKGROUND: The COVID-19 pandemic and subsequent mandates upended community participation in the United States. People with disabilities were often more vulnerable to the adverse effects of the pandemic. Some areas of community participation affected for this population include employment, access to transportation, and social engagement and connection to others. OBJECTIVES: The purpose of this study was to explore the effects of the COVID-19 pandemic for people with mobility disabilities across a variety of topics related to community engagement including social interactions with family and friends, and access to caregivers, groceries, transportation, and employment. METHODS: A survey was administered to participants with mobility disabilities (N = 39). Participants were asked to elaborate on topic areas that they identified as being affected by the COVID-19 pandemic. Data analysis included descriptive statistics and a content analysis in search of themes from open-ended responses. RESULTS: Results indicate that access to family and friends was the most negatively affected topic related to participation, followed by access to food and groceries, transportation, employment, living independently, caring for others, and participating in the community in general. In response to these pandemic-related challenges, participants reported utilizing technology to connect with others and to get essential items delivered. CONCLUSIONS: Findings from this rapid research emphasize the need for emergency preparedness strategies, accessible and reliable resources related to technology use (e.g., Internet), and continued access to services for people with disabilities to maintain various aspects of community participation throughout the COVID-19 pandemic and in the future.

Effects of an Online Community Intervention on Taiwanese Sugar Intake Behavior

Sugar intake has increasingly been a threat because of its association with chronic diseases such as diabetes. During the ongoing Covid-19 pandemic, people have stayed indoors with minimal activities, leading to unhealthy eating habits and weight gain. However, through health-promotion education, these threats could be managed. This study focused on an online heath nutrition program for sugar reduction, with an aim of developing an online training program for reducing sugar intake. Data were collected from 100 participants belonging to a Facebook community in Taiwan. They performed activities guided by research's daily lesson plans for a maximum of 10 minutes per day for three weeks. Online questionnaires were used for the pretest and posttest. Findings revealed significant differences in health knowledge (t(99) = -8.27, p < .001), attitude (t(99) = -8.98, p < .001), self-efficacy (t(99) = -10.14, p < .001), and perceived healthy behavior (t(99) = -12.40, p < .001), with their posttest scores being higher than their pretest scores. These findings imply that online training on Facebook is an effective educational tool during the Covid-19 pandemic. Therefore, this study contributes to behavioral science knowledge by revealing Facebook as a facilitating and training platform for promoting healthy behavior, and access to information on reduction of sugar intake during pandemic. Furthermore, these findings could be used as empirical evidence of the possibility of implementing online nutrition programs for the teaching and training of online communities.

COVID-19 pandemic highlights the need to reconsider psychiatry training of Indian medical graduate

In the middle of COVID-19 crisis in India and the psychological impact on millions of peoples, is it time to reconsider psychiatry training for Indian medical graduate under the new competency-based curriculum? India has one of the highest numbers of medical colleges in the world and also has over a million doctors, including MBBS graduates working at the primary health-care centers who are important pillars for health-care delivery. In a major drawback that also plagued the earlier curriculum, the new competency-based curriculum has not incorporated a single mandatory skill in psychiatry which a medical trainee has to demonstrate to become doctor. Mental health and the COVID-19 pandemic are interlinked in a complex manner. Hence, millions are likely to have mental health consequences. With no skill required in psychiatry as a must for a medical trainee to become an MBBS doctor, the mental health services during or aftermath of a disaster are severely compromised and need urgent reconsideration under the new curriculum.

Working in a bubble: How can businesses reopen while limiting the risk of COVID-19 outbreaks?: CMAJ

The coronavirus disease 2019 (COVID-19) pandemic has required governments around the world to institute severe physical-distancing measures to reduce the spread of the virus in order to protect public health and ensure health care system capacity. Mitigation measures in many countries, including Canada, have incorporated the temporary closure of nonessential businesses, which has led to bleak employment and economic outlooks. Essential businesses that were allowed to remain open have, in many cases, led to the ongoing spread of the pandemic. Factories with employees working in close proximity have been particularly affected, not only putting the health and safety of the workforce at risk, but also negatively affecting supply chains and downstream businesses. As we begin to gradually relax the public health measures that have been implemented to slow the spread of COVID-19 in Canada, it is essential to consider how to limit the risk of the disease in the workplace.

Transcriptional and proteomic insights into the host response in fatal COVID-19 cases.

Coronavirus disease 2019 (COVID-19), the global pandemic caused by SARS-CoV-2, has resulted thus far in greater than 933,000 deaths worldwide; yet disease pathogenesis remains unclear. Clinical and immunological features of patients with COVID-19 have highlighted a potential role for changes in immune activity in regulating disease severity. However, little is known about the responses in human lung tissue, the primary site of infection. Here we show that pathways related to neutrophil activation and pulmonary fibrosis are among the major up-regulated transcriptional signatures in lung tissue obtained from patients who died of COVID-19 in Wuhan, China. Strikingly, the viral burden was low in all samples, which suggests that the patient deaths may be related to the host response rather than an active fulminant infection. Examination of the colonic transcriptome of these patients suggested that SARS-CoV-2 impacted host responses even at a site with no obvious pathogenesis. Further proteomics analysis validated our transcriptome findings and identified several key proteins, such as the SARS-CoV-2 entry-associated protease cathepsins B and L and the inflammatory response modulator S100A8/A9, that are highly expressed in fatal cases, revealing potential drug targets for COVID-19.