Using social media data to assess the impact of COVID-19 on mental health in China.

BACKGROUND: The outbreak and rapid spread of coronavirus disease 2019 (COVID-19) not only caused an adverse impact on physical health, but also brought about mental health problems among the public. METHODS: To assess the causal impact of COVID-19 on psychological changes in China, we constructed a city-level panel data set based on the expressed sentiment in the contents of 13 million geotagged tweets on Sina Weibo, the Chinese largest microblog platform. RESULTS: Applying a difference-in-differences approach, we found a significant deterioration in mental health status after the occurrence of COVID-19. We also observed that this psychological effect faded out over time during our study period and was more pronounced among women, teenagers and older adults. The mental health impact was more likely to be observed in cities with low levels of initial mental health status, economic development, medical resources and social security. CONCLUSIONS: Our findings may assist in the understanding of mental health impact of COVID-19 and yield useful insights into how to make effective psychological interventions in this kind of sudden public health event.

Effect of the Announcement of Human-to-Human Transmission on Telemedicine Services in China During COVID-19.

OBJECTIVES: Telemedicine enables patients to communicate with physicians effectively, especially during the coronavirus disease (COVID-19) pandemic. However, few studies have explored the use of online health care platforms for a comprehensive range of specialties during the COVID-19 pandemic. This study aimed to investigate how telemedicine services were affected by the announcement of human-to-human transmission in China. METHODS: Telemedicine data from haodf.com in China were collected. A difference-in-differences analysis compared the number of telemedicine use and the number of active online physicians for different specialties in 2020 with the numbers in 2019, before and after the announcement of human-to-human transmission. RESULTS: Data from 2 473 734 telemedicine use during the same calendar time in 2020 and 2019 were collected. Telemedicine use in 2020 increased by 349.9% after the announcement of human-to-human transmission in China, and the number of active online physicians increased by 23.2%. The difference-in-differences analysis indicated that the announcement had statistically significant positive effects on the numbers of telemedicine use for almost all specialties, except cosmetic dermatology, pathology, occupational diseases, sports medicine, burn, medical imaging, and interventional medicine. CONCLUSION: Telemedicine services increased significantly after the announcement of human-to-human transmission of COVID-19. Online activities of most specialties increased, except where providers had to conduct in-person testing and provide bedside therapies.

Exposure-lag-response associations between weather conditions and ankylosing spondylitis: a time series study.

BACKGROUND: Patients with ankylosing spondylitis (AS) have reported that their pain becomes worse when the local weather changes. However, there is limited evidence verifying the short-term associations between meteorological factors and outpatient visits for patients with AS. Therefore, this study evaluates this possible association. METHODS: Meteorological data and data on daily AS outpatient visits to a general hospital in Hefei, China, from 2014 to 2019 were collected and analysed. Distributed lag nonlinear models and Poisson regression models were employed to determine the association between weather conditions and outpatient visits; the results were also stratified by gender and age. RESULTS: High relative humidity is significantly associated with all patient visits in lag 1 (RR = 1.113, 95% CI 1.021 to 1.213) and lag 7 days (RR = 1.115, 95% CI 1.014 to 1.227). A low relative risk to the nadir is observed in lag 4 days (RR = 0.920, 95% CI 0.862 to 0.983). Male and young patients (< 65 years) are more vulnerable to damp weather, and elderly people (≥ 65 years) are significantly affected by high temperatures in lag 7 days (RR = 3.004, 95% CI 1.201 to 7.510). CONCLUSIONS: Our findings suggest a potential relationship between exposure to weather conditions and increased risk of AS outpatient visits. These results can aid hospitals in preparing for and managing hospital visits by AS patients when the local weather conditions change.

The moderating effect of solar radiation on the association between human mobility and COVID-19 infection in Europe.

The novel coronavirus disease 2019 (COVID-19) has caused a global pandemic. Some studies have suggested a negative association between sunlight intensity and COVID-19 infection, alluding to the belief that it might be safe to go out on sunny days. This paper examined whether solar radiation mitigated the association between human mobility and COVID-19 infection in Europe using a dynamic panel data model to investigate the effect of human mobility, solar radiation, and their interaction on COVID-19 infection. The results revealed that outgoing mobility was positively correlated and solar radiation was negatively correlated with COVID-19 infection at lag levels of 1, 2, and 3 weeks. The coefficients of the interaction items indicated that solar radiation negatively moderated the relationship between outgoing mobility and the number of daily new confirmed cases at 2- and 3-week lag levels. However, the moderating effect was limited and unable to eliminate the positive effect of outgoing mobility on COVID-19 infection. Thus, these results suggested that solar radiation only weakly mitigated the relationship between human mobility and COVID-19 infection, providing policy implications that mobility should still be restricted on sunny days during the COVID-19 pandemic.

Mediation by human mobility of the association between temperature and COVID-19 transmission rate.

The coronavirus disease 2019 (COVID-19) pandemic is a major threat to global health. Relevant studies have shown that ambient temperature may influence the spread of novel coronavirus. However, the effect of ambient temperature on COVID-19 remains controversial. Human mobility is also closely related to the pandemic of COVID-19, which could be affected by temperature at the same time. The purpose of this study is to explore the underlying mechanism of the association of temperature with COVID-19 transmission rate by linking human mobility. The effective reproductive number, meteorological conditions and human mobility data in 47 countries are collected. Panel data models with fixed effects are used to analyze the association of ambient temperature with COVID-19 transmission rate, and the mediation by human mobility. Our results show that there is a negative relationship between temperature and COVID-19 transmission rate. We also observe that temperature is positively associated with human mobility and human mobility is positively related to COVID-19 transmission rate. Thus, the suppression effect (also known as the inconsistent mediation effect) of human mobility is confirmed, which remains robust when different lag structures are used. These findings provide evidence that temperature can influence the spread of COVID-19 by affecting human mobility. Therefore, although temperature is negatively related to COVID-19 transmission rate, governments and the public should pay more attention to control measures since people are more likely to go out when temperature rising. Our results could partially explain the reason why COVID-19 is not prevented by warm weather in some countries.

The mediating effect of air quality on the association between human mobility and COVID-19 infection in China.

BACKGROUND: Previous studies have found that human mobility restrictions could not only prevent the spread of COVID-19, but also improve the air quality because of the reduction of industrial production, transportation and traffic. It is noteworthy that air quality is also closely related to the risk of COVID-19 infection. Therefore, we aimed to assess the mediating role of air quality on the association between human mobility and the infection caused by this novel coronavirus. METHODS: We collected daily confirmed cases, human mobility data, air quality data and meteorological variables in 120 cities from China between January 23, 2020 and February 29, 2020. We applied the generalized additive model to examine the association of human mobility index with COVID-19 confirmed cases, and to assess the mediating effects of air quality index and each pollutant. RESULTS: We observed a significant positive relationship between human mobility index and the daily counts of COVID-19 confirmed cases. A unit increase in human mobility index (lag0-14) was associated with a 6.45% increase in daily COVID-19 confirmed cases, and air quality index significantly mediated 19.47% of this association. We also observed a positive relationship between human mobility index and air quality index. In the pollutant level analyses, we found significant mediating effects of PM2.5, PM10, and NO2. CONCLUSIONS: Our study suggests that limiting human movements could reduce COVID-19 cases by improving air quality besides decreasing social contact.

Association between short-term exposure to air pollution and COVID-19 infection: Evidence from China.

The novel coronavirus pneumonia, namely COVID-19, has become a global public health problem. Previous studies have found that air pollution is a risk factor for respiratory infection by carrying microorganisms and affecting body's immunity. This study aimed to explore the relationship between ambient air pollutants and the infection caused by the novel coronavirus. Daily confirmed cases, air pollution concentration and meteorological variables in 120 cities were obtained from January 23, 2020 to February 29, 2020 in China. We applied a generalized additive model to investigate the associations of six air pollutants (PM2.5, PM10, SO2, CO, NO2 and O3) with COVID-19 confirmed cases. We observed significantly positive associations of PM2.5, PM10, NO2 and O3 in the last two weeks with newly COVID-19 confirmed cases. A 10-µg/m3 increase (lag0-14) in PM2.5, PM10, NO2, and O3 was associated with a 2.24% (95% CI: 1.02 to 3.46), 1.76% (95% CI: 0.89 to 2.63), 6.94% (95% CI: 2.38 to 11.51), and 4.76% (95% CI: 1.99 to 7.52) increase in the daily counts of confirmed cases, respectively. However, a 10-µg/m3 increase (lag0-14) in SO2 was associated with a 7.79% decrease (95% CI: -14.57 to -1.01) in COVID-19 confirmed cases. Our results indicate that there is a significant relationship between air pollution and COVID-19 infection, which could partially explain the effect of national lockdown and provide implications for the control and prevention of this novel disease.