COVID-19 Prevention Measures Targeting Homeless People in Japan: A Cross-sectional Study.
Kashiko FujiiPublished in: Social work in public health (2022)
Reports worldwide have shown that COVID-19 has impacted vulnerable populations, including homeless populations. The rate of the COVID-19 infection among the homeless populations is still unknown in most countries due to these individuals being scattered inconsistently throughout urban areas; however, surveys have been conducted in some shelters and in areas outside of Japan. Further, psychological impacts associated with COVID-19 infection, such as stress and anxiety or preventive procedures to protect yourself from infection, have also not been well studied among homeless populations. This study analyzes the demographic characteristics of the homeless population, their anxieties about COVID-19, and whether the author's weekly announcements related to COVID-19 are beneficial to them. A cross-sectional mixed methods study was conducted in a Japanese city from October 2020 to February 2021. Data regarding socio-demographic characteristics, individuals' experiences of homelessness, and perceptions of COVID-19 were gathered via interviews and examined using quantitative and qualitative methods. 71.1% and 44.2% of the respondents expressed no history of previous diseases and having anxiety due to COVID-19 respectively. Data indicated that they associated COVID-19 with death and serious physical harm. Additionally, 78.6% found the health announcements to be helpful and took preventive measures. Homeless people do not visit doctors, except when experiencing unbearable pain. Therefore, it is necessary to continuously provide comprehensive support for Japan's homeless population.
Keyphrases
- coronavirus disease
- sars cov
- mental illness
- mental health
- respiratory syndrome coronavirus
- public health
- physical activity
- electronic health record
- primary care
- systematic review
- emergency department
- machine learning
- big data
- drug delivery
- risk assessment
- spinal cord injury
- social media
- climate change
- artificial intelligence