Social Connectedness, Physical Distancing, and Anxiety in Complying with Shelter-In-Place Orders and Advisories during the Once-In-A-Century COVID-19 Pandemic in the US: A Study of Social Media and Internet Users.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease (COVID-19), was first identified in Wuhan, China, in December 2019. As of 20 October 2020, the virus had infected 8,202,552 people, with 220,061 deaths in US, and in countries around the world, over 38 million people have become infected and over one million have died. The virus usually spreads via respiratory droplets from an infected person. At the time of compiling this paper, while countries around the world are still striving to find a "pharmaceutical intervention (PI)", including treatments and vaccines, they are left with only "non-pharmaceutical interventions (NPIs)", such as physical distancing, wearing masks, and maintaining personal hygiene. In the US, all 50 states, the District of Columbia, and five US territories issued mandatory stay-at-home orders between March 1 and 31 May 2020 to lower the risk of virus transmission. This study empirically examined how social connectedness and anxiety interact with shelter-in-place compliance and advisories during the pandemic. The study collected information from 494 adults using an online survey during April and July 2020.

Factors Contributing to SARS-CoV-2 Vaccine Hesitancy of Hispanic Population in Rio Grande Valley.

Hispanic communities have been disproportionately affected by economic disparities. These inequalities have put Hispanics at an increased risk for preventable health conditions. In addition, the CDC reports Hispanics to have 1.5× COVID-19 infection rates and low vaccination rates. This study aims to identify the driving factors for COVID-19 vaccine hesitancy of Hispanic survey participants in the Rio Grande Valley. Our analysis used machine learning methods to identify significant associations between medical, economic, and social factors impacting the uptake and willingness to receive the COVID-19 vaccine. A combination of three classification methods (i.e., logistic regression, decision trees, and support vector machines) was used to classify observations based on the value of the targeted responses received and extract a robust subset of factors. Our analysis revealed different medical, economic, and social associations that correlate to other target population groups (i.e., males and females). According to the analysis performed on males, the Matthews correlation coefficient (MCC) value was 0.972. An MCC score of 0.805 was achieved by analyzing females, while the analysis of males and females achieved 0.797. Specifically, several medical, economic factors, and sociodemographic characteristics are more prevalent in vaccine-hesitant groups, such as asthma, hypertension, mental health problems, financial strain due to COVID-19, gender, lack of health insurance plans, and limited test availability.