Impact of Human Mobility on COVID-19 Transmission According to Mobility Distance, Location, and Demographic Factors in the Greater Bay Area of China: Population-Based Study.

BACKGROUND: Mobility restriction was one of the primary measures used to restrain the spread of COVID-19 globally. Governments implemented and relaxed various mobility restriction measures in the absence of evidence for almost 3 years, which caused severe adverse outcomes in terms of health, society, and economy. OBJECTIVE: This study aimed to quantify the impact of mobility reduction on COVID-19 transmission according to mobility distance, location, and demographic factors in order to identify hotspots of transmission and guide public health policies. METHODS: Large volumes of anonymized aggregated mobile phone position data between January 1 and February 24, 2020, were collected for 9 megacities in the Greater Bay Area, China. A generalized linear model (GLM) was established to test the association between mobility volume (number of trips) and COVID-19 transmission. Subgroup analysis was also performed for sex, age, travel location, and travel distance. Statistical interaction terms were included in a variety of models that express different relations between involved variables. RESULTS: The GLM analysis demonstrated a significant association between the COVID-19 growth rate ratio (GR) and mobility volume. A stratification analysis revealed a higher effect of mobility volume on the COVID-19 GR among people aged 50-59 years (GR decrease of 13.17% per 10% reduction in mobility volume; P<.001) than among other age groups (GR decreases of 7.80%, 10.43%, 7.48%, 8.01%, and 10.43% for those aged ≤18, 19-29, 30-39, 40-49, and ≥60 years, respectively; P=.02 for the interaction). The impact of mobility reduction on COVID-19 transmission was higher for transit stations and shopping areas (instantaneous reproduction number [Rt] decreases of 0.67 and 0.53 per 10% reduction in mobility volume, respectively) than for workplaces, schools, recreation areas, and other locations (Rt decreases of 0.30, 0.37, 0.44, and 0.32, respectively; P=.02 for the interaction). The association between mobility volume reduction and COVID-19 transmission was lower with decreasing mobility distance as there was a significant interaction between mobility volume and mobility distance with regard to Rt (P<.001 for the interaction). Specifically, the percentage decreases in Rt per 10% reduction in mobility volume were 11.97% when mobility distance increased by 10% (Spring Festival), 6.74% when mobility distance remained unchanged, and 1.52% when mobility distance declined by 10%. CONCLUSIONS: The association between mobility reduction and COVID-19 transmission significantly varied according to mobility distance, location, and age. The substantially higher impact of mobility volume on COVID-19 transmission for longer travel distance, certain age groups, and specific travel locations highlights the potential to optimize the effectiveness of mobility restriction strategies. The results from our study demonstrate the power of having a mobility network using mobile phone data for surveillance that can monitor movement at a detailed level to measure the potential impacts of future pandemics.

Adoption of Preventive Measures During the Very Early Phase of the COVID-19 Outbreak in China: National Cross-sectional Survey Study.

BACKGROUND: The outbreak of COVID-19 in China occurred around the Chinese New Year (January 25, 2020), and infections decreased continuously afterward. General adoption of preventive measures during the Chinese New Year period was crucial in driving the decline. It is imperative to investigate preventive behaviors among Chinese university students, who could have spread COVID-19 when travelling home during the Chinese New Year break. OBJECTIVE: In this study, we investigated levels of COVID-19-related personal measures undertaken during the 7-day Chinese New Year holidays by university students in China, and associated COVID-19-related cognitive factors. METHODS: A cross-sectional anonymous web-based survey was conducted during the period from February 1 to 10, 2020. Data from 23,863 students (from 26 universities, 16 cities, 13 provincial-level regions) about personal measures (frequent face-mask wearing, frequent handwashing, frequent home staying, and an indicator that combined the 3 behaviors) were analyzed (overall response rate 70%). Multilevel multiple logistic regression analysis was performed. RESULTS: Only 28.0% of respondents (6684/23,863) had left home for >4 hours, and 49.3% (11,757/23,863) had never left home during the 7-day Chinese New Year period; 79.7% (19,026/23,863) always used face-masks in public areas. The frequency of handwashing with soap was relatively low (6424/23,863, 26.9% for >5 times/day); 72.4% (17,282/23,863) had frequently undertaken ≥2 of these 3 measures. COVID-19-related cognitive factors (perceptions on modes of transmission, permanent bodily damage, efficacy of personal or governmental preventive measures, nonavailability of vaccines and treatments) were significantly associated with preventive measures. Associations with frequent face-mask wearing were stronger than those with frequent home staying. CONCLUSIONS: University students had strong behavioral responses during the very early phase of the COVID-19 outbreak. Levels of personal prevention, especially frequent home staying and face-mask wearing, were high. Health promotion may modify cognitive factors. Some structural factors (eg, social distancing policy) might explain why the frequency of home staying was higher than that of handwashing. Other populations might have behaved similarly; however, such data were not available to us.

Factors Influencing Depression and Mental Distress Related to COVID-19 Among University Students in China: Online Cross-sectional Mediation Study.

BACKGROUND: The COVID-19 epidemic may elevate mental distress and depressive symptoms in various populations in China. OBJECTIVE: This study investigates the levels of depression and mental distress due to COVID-19, and the associations between cognitive, behavioral, and psychosocial factors, and depression and mental distress due to COVID-19 among university students in China. METHODS: A large-scale online cross-sectional study (16 cities in 13 provinces) was conducted among university students from February 1 to 10, 2020, in China; 23,863 valid questionnaires were returned. The Patient Health Questionnaire-9 was used to assess depression. Structural equation modeling was performed to test mediation and suppression effects. RESULTS: Of the 23,863 participants, 47.1% (n=11,235) reported high or very high levels of one or more types of mental distress due to COVID-19; 39.1% (n=9326) showed mild to severe depression. Mental distress due to COVID-19 was positively associated with depression. All but one factor (perceived infection risks, perceived chance of controlling the epidemic, staying at home, contacted people from Wuhan, and perceived discrimination) were significantly associated with mental distress due to COVID-19 and depression. Mental distress due to COVID-19 partially mediated and suppressed the associations between some of the studied factors and depression (effect size of 6.0%-79.5%). CONCLUSIONS: Both mental distress due to COVID-19 and depression were prevalent among university students in China; the former may have increased the prevalence of the latter. The studied cognitive, behavioral, and psychosocial factors related to COVID-19 may directly or indirectly (via mental distress due to COVID-19) affect depression. Interventions to modify such factors may reduce mental distress and depressive symptoms during the COVID-19 epidemic.

Notes from the Field: Effectiveness of Prevention and Control Measures for Imported COVID-19 in Guangming District of Shenzhen.

Novel coronavirus disease 2019 (COVID-19) was present in most provinces of China after January 2020. We implemented a surveillance and screening strategy that included early detection of laboratory-confirmed COVID-19 cases and people who were exposed to the disease in Guangming District of Shenzhen. Separate targeted treatment and management strategies were applied to confirmed and suspected cases. From January 23 to March 13, 2020, we found 12 suspected cases, and 11 were confirmed as positive. Although eight of the 11 confirmed cases were family-aggregated, they were all imported cases with common exposure, which did not further cause local community transmission, and no medical staff were infected. After February 14, when the last case was confirmed, there were no newly confirmed cases for 28 consecutive days under the strict outbreak control. The targeted and whole-society involved prevention and control measures prevented the spread of the disease in a very short time and provided a strong guarantee for the orderly recovery of returning to work and social activities.

The unique features of SARS-CoV-2 transmission: Comparison with SARS-CoV, MERS-CoV and 2009 H1N1 pandemic influenza virus.

From 2002 to 2019, three deadly human coronaviruses (hCoVs), severe acute respiratory syndrome coronavirus (SARS-CoV), Middle Eastern respiratory syndrome coronavirus (MERS-CoV) and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) emerged to produce outbreaks of SARS, MERS and coronavirus disease 2019 (Covid-19), respectively. All three hCoVs are members of the Betacoronavirus genus in the subfamily Orthocoronavirinae and share many similarities in virology and epidemiology. However, the pattern and scale of Covid-19 global spread is similar to 2009 pandemic H1N1 influenza (H1N1pdm09), rather than SARS or MERS. Covid-19 exhibits high viral shedding in the upper respiratory tract at an early stage of infection, and has a high proportion of transmission competent individuals that are pre-symptomatic, asymptomatic and mildly symptomatic, characteristics seen in H1N1pdm09 but not in SARS or MERS. These two traits of Covid-19 and H1N1pdm09 result in reduced efficiency in identification of transmission sources by symptomatic screening and play important roles in their ability to spread unchecked to cause pandemics. To overcome these attributes of Covid-19 in community transmission, identifying the transmission source by testing for virus shedding and interrupting chains of transmission by social distancing and public masking are required.

Effects of human mobility restrictions on the spread of COVID-19 in Shenzhen, China: a modelling study using mobile phone data.

Background: Restricting human mobility is an effective strategy used to control disease spread. However, whether mobility restriction is a proportional response to control the ongoing COVID-19 pandemic is unclear. We aimed to develop a model that can quantify the potential effects of various intracity mobility restrictions on the spread of COVID-19. Methods: In this modelling study, we used anonymous and aggregated mobile phone sightings data to build a susceptible-exposed-infectious-recovered transmission model for COVID-19 based on the city of Shenzhen, China. We simulated how disease spread changed when we varied the type and magnitude of mobility restrictions in different transmission scenarios, with variables such as the basic reproductive number (R 0), length of infectious period, and the number of initial cases. Findings: 331 COVID-19 cases distributed across the ten regions of Shenzhen were reported on Feb 7, 2020. In our basic scenario (R 0 of 2·68), mobility reduction of 20-60% within the city had a notable effect on controlling COVID-19 spread: a flattening of the peak number of cases by 33% (95% UI 21-42) and delay to the peak number by 2 weeks with a 20% restriction, 66% (48-75) reduction and 4 week delay with a 40% restriction, and 91% (79-95) reduction and 14 week delay with a 60% restriction. The effects of mobility restriction were increased when combined with reductions of 25% or 50% in transmissibility of the virus. In specific analyses of mobility restrictions for individuals with symptomatic infections and for high-risk regions, these measures also had substantial effects on reducing the spread of COVID-19. For example, the peak of the epidemic was delayed by 2 weeks if the proportion of individuals with symptomatic infections who could move freely was maintained at 20%, and by 4 weeks if two high-risk regions were locked down. The simulation results were also affected by various transmission parameters. Interpretation: Our model shows the effects of various types and magnitudes of mobility restrictions on controlling COVID-19 outbreaks at the city level in Shenzhen, China. The model could help policy makers to establish the optimal combinations of mobility restrictions during the COVID-19 pandemic, especially to assess the potential positive effects of mobility restriction on public health in view of the potential negative economic and societal effects. Funding: Guangdong Medical Science Fund, and National Natural Science Foundation of China.

Negative cognitive and psychological correlates of mandatory quarantine during the initial COVID-19 outbreak in China.

Quarantine plays a key role in controlling the pandemic of 2019 coronavirus disease (COVID-19). This study investigated (a) the associations between mandatory quarantine status and negative cognitions (perceived discrimination because of COVID-19 and perceived risk of COVID-19 infection)/mental health status (emotional distress because of COVID-19, probable depression, and self-harm/suicidal ideation), (b) the associations between the negative cognitions and mental health status, and (c) potential mediations between quarantined status and probable depression and self-harm/suicidal ideation via COVID-19-related negative cognitions/emotional distress. An online cross-sectional survey was conducted among 24,378 students of 26 universities in 16 Chinese cities (February 1-10, 2020). Correlation coefficients, odds ratios (OR), structural equation modeling, and other statistics were used for data analysis. Mandatory quarantined status was significantly and positively associated with perceived discrimination (Cohen's d = 0.62), perceived high/very high risk of infection (OR = 1.61), emotional distress (Cohen's d = 0.46), probable depression (OR = 2.54), and self-harm/suicidal ideation (OR = 4.98). Perceived discrimination was moderately and positively associated with emotional distress (Spearman correlation = 0.44). Associations between perceived risk of infection and mental health variables were significant but relatively weak. Cross-sectional mediation models showed good model fit, but the overall indirect paths via COVID-19-related negative cognitions/emotional distress only accounted for 12-15% of the total effects between quarantined status and probable depression and self-harm/suicidal ideation. In conclusion, quarantined participants were more likely than others to perceive discrimination and exhibit mental distress. It is important to integrate mental health care into the planning and implementation of quarantine measures. Future longitudinal studies to explore mechanisms underlying the mental health impact of quarantines are warranted. (PsycInfo Database Record (c) 2020 APA, all rights reserved).