Changes in Physical Activity and Sedentary Behavior in Chinese Young Adults during the COVID-19 Pandemic: A Repeated-Measure Study throughout One Year.

Though we know physical activity (PA) decreased while sedentary behavior (SB) increased compared to that before the COVID-19 pandemic, little is known about subsequent changes in PA and SB throughout one year in the post-pandemic era. This study aimed to examine the changes in PA and SB in a sample of Chinese young adults using a four-wave repeated-measure design during the pandemic. A total of 411 participants provided self-reported data of sociodemographic characteristics (e.g., sex, age), PA, and SB. Nonparametric tests and generalized estimating equations were conducted. Results revealed significant changes in moderate to vigorous PA (MVPA), light PA (LPA), and SB. The MVPA of Wave 1, 2, and 3 was significantly less than that of Wave 4 (p < 0.001); the LPA of Wave 1 and 2 was significantly less than that of Wave 4; the SB of Wave 1 was significantly more than that of Wave 4 (p < 0.05). Being female was the only predictor of changes in MVPA (Beta = -0.311, p< 0.001). Being female (Beta = 0.115, p = 0.003) and perceived family affluence (Beta = -0.059, p< 0.001) were predictors of changes in SB. As such, PA was less, while SB was more during the early stages of the pandemic. With the progress of the pandemic stages, health behaviors in young adults have been gradually improved. Sex and perceived family affluence were two important factors in predicting health behaviors. Our results can inform efficient policies or interventions in the COVID-19 era and future similar public health events.

Social Behaviors Associated With a Positive COVID-19 Test Result.

Objective To compare the social behaviors of individuals who were tested positive for COVID-19 relative to non-infected individuals.   Methods We sent COVID positive cases and age/gender-matched controls a survey regarding their social behaviors via MyChart (online patient portal). We called cases if they did not complete the electronic survey within two days. Data were collected from May to June 2020. Survey responses for cases without close contact and controls were compared using Pearson chi-square or Fisher's exact tests as appropriate.   Results A total of 339 participants completed the survey (113 cases, 226 controls); 45 (40%) cases had known contact with COVID-19. Cases were more likely to have recently traveled (4% vs. 0%, p = 0.01) or to work outside the home (40% vs. 25%, p = 0.02). There was no difference in the rates of attending private or public gatherings, mask/glove use, hand-washing, cleaning surfaces, and cleaning mail/groceries between cases and controls.   Conclusions Sixty percent of cases had no known contact with COVID-19, indicating ongoing community transmission and underlining the importance of contact tracing. The greater percentage of cases who work outside the home provides further evidence for social distancing and remote telework when possible.

A dynamical framework for modeling fear of infection and frustration with social distancing in COVID-19 spread.

We introduce a novel modeling framework for incorporating fear of infection and frustration with social distancing into disease dynamics. We show that the resulting SEIR behavior-perception model has three principal modes of qualitative behavior-no outbreak, controlled outbreak, and uncontrolled outbreak. We also demonstrate that the model can produce transient and sustained waves of infection consistent with secondary outbreaks. We fit the model to cumulative COVID-19 case and mortality data from several regions. Our analysis suggests that regions which experience a significant decline after the first wave of infection, such as Canada and Israel, are more likely to contain secondary waves of infection, whereas regions which only achieve moderate success in mitigating the disease's spread initially, such as the United States, are likely to experience substantial secondary waves or uncontrolled outbreaks.

COVID-19 Symptom-Related Google Searches and Local COVID-19 Incidence in Spain: Correlational Study.

BACKGROUND: COVID-19 is one of the biggest pandemics in human history, along with other disease pandemics, such as the H1N1 influenza A, bubonic plague, and smallpox pandemics. This study is a small contribution that tries to find contrasted formulas to alleviate global suffering and guarantee a more manageable future. OBJECTIVE: In this study, a statistical approach was proposed to study the correlation between the incidence of COVID-19 in Spain and search data provided by Google Trends. METHODS: We assessed the linear correlation between Google Trends search data and the data provided by the National Center of Epidemiology in Spain-which is dependent on the Instituto de Salud Carlos III-regarding the number of COVID-19 cases reported with a certain time lag. These data enabled the identification of anticipatory patterns. RESULTS: In response to the ongoing outbreak, our results demonstrate that by using our correlation test, the evolution of the COVID-19 pandemic can be predicted in Spain up to 11 days in advance. CONCLUSIONS: During the epidemic, Google Trends offers the possibility to preempt health care decisions in real time by tracking people's concerns through their search patterns. This can be of great help given the critical, if not dramatic need for complementary monitoring approaches that work on a population level and inform public health decisions in real time. This study of Google search patterns, which was motivated by the fears of individuals in the face of a pandemic, can be useful in anticipating the development of the pandemic.

The Unaddressed Behavioral Health Aspect During the Coronavirus Pandemic.

The 2019 novel coronavirus (2019-nCoV) pneumonia has been declared a pandemic, citing more than 118,000 cases of the coronavirus illness in more than 110 countries and territories around the world. Public health emergencies have been demonstrated to have an impact on the behavioral health of the affected population as they may experience fear, anxiety, anger and post-traumatic stress disorder as consequences of their experiences. These effects may persist among affected individuals long after the outbreak has been controlled. To date, data on the behavioral distress and psychiatric morbidity of those suspected or diagnosed with the 2019-nCoV and their treating health professionals are lacking. Although the Centers for Disease Control and Prevention (CDC) has outlined some behavioral health guide for affected individuals, how best to respond to psychological challenges during the crisis is not known. There is an urgent need to provide robust and timely psychosocial support in the face of such an outbreak.

Focus on Mental Health During the Coronavirus (COVID-19) Pandemic: Applying Learnings from the Past Outbreaks.

The 2019 novel coronavirus (COVID-19) has gained global attention after it originated from China at the end of 2019, and later turned into pandemic as it affected about 118,000 in 114 countries by March 11, 2020. By March 13, 2020, it was declared a national emergency in the United States as the number of COVID-19 cases, and the death toll rose exponentially. To contain the spread of the disease, the world scientist community came together. However, the unpreparedness of the nations, even with the advanced medical sciences and resources, has failed to address the mental health aspect amongst the public, as all efforts are focused on understanding the epidemiology, clinical features, transmission patterns, and management of COVID-19 pneumonia. Our efforts in this review are to evaluate and study similar outbreaks from the past to understand its adverse impact on mental health, implement adequate steps to tackle and provide a background to physicians and healthcare workers at the time of such outbreaks to apply psychological first aid.