ABSTRACT
COVID-19 raises attention to epidemic transmission in various places. This study analyzes the transmission risks associated with human activity places at multiple scales, including different types of settlements and eleven types of specific establishments (restaurants, bars, etc.), using COVID-19 data in 906 urban areas across four continents. Through a difference-in-difference approach, we identify the causal effects of activities at various places on epidemic transmission. We find that at the micro-scale, though the transmission risks at different establishments differ across countries, sports, entertainment, and catering establishments are generally more infectious. At the macro-scale, contradicting common beliefs, it is consistent across countries that transmission does not increase with settlement size and density. It is also consistent that specific establishments play a lesser role in transmission in larger settlements, suggesting more transmission happening elsewhere. These findings contribute to building a system of knowledge on the linkage between places, human activities, and disease transmission.
ABSTRACT
People living with HIV (PLWH), if infected with Coronavirus Disease 2019 (COVID-19), had an increased risk of mortality compared to people without HIV infection. They are considered as a priority group to receive COVID-19 vaccination. This cross-sectional online survey investigated the prevalence of and factors associated with COVID-19 vaccination uptake among 2740 PLWH aged 18–65 years in eight Chinese metropolitan cities between January and February 2021. As validated by requesting participants to send an image of receipt hiding personal identification, 6.2% of PLWH had taken up COVID-19 vaccination. Participants living in cities where individuals could make an appointment to receive COVID-19 vaccination reported significantly higher uptake than those living in cities without such allowance (11.0 vs. 2.9%, p < 0.001). Being a member of priority groups to receive vaccination, concerning about the side effects of COVID-19 vaccination and its interaction with HIV treatment, and exposing to information on the Internet/social media supporting PLWH to receive COVID-19 vaccination were significantly associated with COVID-19 vaccination uptake in both groups of participants. Receiving advice from the staff of community-based organizations supporting COVID-19 vaccination was associated with higher uptake among participants living in cities where individuals could make an appointment to receive such vaccination, while a shortage in COVID-19 vaccine supply was associated with a lower uptake among participants living in other cities. Our findings presented a snapshot of COVID-19 vaccination uptake among PLWH in the early phase of vaccine rollout in China. It provided a knowledge basis to formulate interventions promoting COVID-19 vaccination for PLWH.
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The explosive spread of false news on social media has severely affected many areas such as news ecosystems, politics, economics, and public trust, especially amid the COVID-19 infodemic. Machine intelligence has met with limited success in detecting and curbing false news. Human knowledge and intelligence hold great potential to complement machine-based methods. Yet they are largely underexplored in current false news detection research, especially in terms of how to efficiently utilize such information. We observe that the crowd contributes to the challenging task of assessing the veracity of news by posting responses or reporting. We propose combining these two types of scalable crowd judgments with machine intelligence to tackle the false news crisis. Specifically, we design a novel framework called CAND, which first extracts relevant human and machine judgments from data sources including news features and scalable crowd intelligence. The extracted information is then aggregated by an unsupervised Bayesian aggregation model. Evaluation based on Weibo and Twitter datasets demonstrates the effectiveness of crowd intelligence and the superior performance of the proposed framework in comparison with the benchmark methods. The results also generate many valuable insights, such as the complementary value of human and machine intelligence, the possibility of using human intelligence for early detection, and the robustness of our approach to intentional manipulation. This research significantly contributes to relevant literature on false news detection and crowd intelligence. In practice, our proposed framework serves as a feasible and effective approach for false news detection. [ FROM AUTHOR] Copyright of MIS Quarterly is the property of MIS Quarterly and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
COVID-19 raises attention to epistemological risks related to everyday human activities. Our work quantifies infection transmission risks at different human activity places, including different types of settlements at macro-scale and establishments (restaurants, bars, etc.) at micro-scale, using evidences from COVID-19 in 906 urban areas across four continents. Relatively stable rules of how infection risks are distributed across human settlements and establishments are found. At micro-scale, the infection transmission risks at various establishments differ across countries, but generally, physical activity, entertainment and catering establishments lead to more infections than other activity places. At macro-scale, contrary to common beliefs, we find consistent pattern that transmission does not increase with settlement size and density. When considering interaction between the two scales, there is also consistent pattern that a smaller proportion of infections take place at specific establishments in larger settlements, suggesting that general public spaces such as streets play a greater role in transmission due to longer trips. Though with limitations, our work provides the first steps towards a system of knowledge on the linkage between places, human activities and disease transmission.
Subject(s)
COVID-19ABSTRACT
The efficacy of government interventions in epidemic has become a hot subject since the onset of COVID-19. There is however much variation in the results quantifying the effects of interventions, which is partly related to the varying modelling approaches employed by existing studies. This paper therefore aims to examine how the choice of modelling approach would affect the estimation results of intervention effects, by experimenting with different modelling approaches on a same data set composed of the 500 most affected U.S. counties. We compare the most frequently used methods from the two classes of modelling approaches, which are Bayesian hierarchical model from the class of computational approach and difference-in-difference from the class of natural experimental approach. We find that computational methods are likely to produce larger estimates of intervention effects due to simultaneous voluntary behavioral changes. In contrast, natural experimental methods are more likely to extract the true effect of interventions. Among different difference-in-difference estimators, the two-way fixed effect estimator seems to be an efficient one. Our work can inform the methodological choice of future research on this topic, as well as more robust re-interpretation of existing works, to facilitate both future epidemic response plans and the science of public health.
Subject(s)
COVID-19ABSTRACT
OBJECTIVE To assess the efficacy and safety of tenecteplase in patients with pulmonary embolism (PE). METHODS We completed the literature search on May 31, 2021 using PubMed, EMBASE and the Web of Science. Analyses were conducted according to PE risk stratification, study design and duration of follow-up. The pooled risk ratios (RRs) and its 95% confident intervals (CIs) for death and major bleeding were calculated using a random-effect model. RESULTS A total of six studies, with four randomized controlled trials (RCTs) and two cohort studies, were included in this study out of the 160 studies retrieved. For patients with high-risk PE, tenecteplase increased 30-day survival rate (16% vs 6%; P=0.005) and did not increase the incidence of bleeding (6% vs 5%; P=0.73). For patients with intermediate-risk PE, four RCTs suggested that tenecteplase reduced right ventricular insufficiency at 24h early in the onset and the incidence of hemodynamic failure without affecting mortality in a short/long-term [<30 days RR=0.83, 95% CI (0.47, 1.46);≥30 days RR=1.04, 95% CI (0.88, 1.22)]. However, tenecteplase was associated with high bleeding risk [<30 days RR=1.79, 95% CI (1.61, 2.00); ≥30 days RR=1.28, 95% CI (0.62, 2.64)]. CONCLUSIONS Tenecteplase may represent a promising candidate for patients with intermediate/high risk PE. Furthermore, tenecteplase may be preferable in the COVID-19 pandemic due to its all-at-once administration.
Subject(s)
Pulmonary Embolism , Renal Insufficiency , COVID-19 , Addison DiseaseABSTRACT
Places are fundamental factors in the spread of epidemics, as they are where people agglomerate and interact. This paper explores how different types of places--activity spaces at micro-level and human settlements at macro-level--impact the transmission of infections using evidences from COVID-19. We examine eleven types of activity spaces and find heterogeneous impacts across countries, yet we also find that non-essential activity spaces tend to have larger impacts than essential ones. Contrary to common beliefs, settlement size and density are not positively associated with reproduction numbers. Further, the impacts of closing activity spaces vary with settlement types and are consistently lower in larger settlements in all sample countries, suggesting more complex pattern of virus transmission in large settlements. This work takes first steps in systematically evaluating the epistemological risks of places at multiple scales, which contributes to knowledge in urban resilience, health and livability. TeaserActivity spaces and human settlement characteristics impact the spread of epidemics in multiple ways and should be considered in policy making.
Subject(s)
COVID-19ABSTRACT
Reduced mobility and less anthropogenic activity under special case circumstances over various parts of the world have pronounced effects on air quality. The objective of this study is to investigate the impact of reduced anthropogenic activity on air quality in the mega city of Shanghai, China. Observations from the highly sophisticated multi-axis differential optical absorption spectroscope (MAX-DOAS) instrument were used for nitrogen dioxide (NO2) and formaldehyde (HCHO) column densities. In situ measurements for NO2, ozone (O3), particulate matter (PM2.5) and the air quality index (AQI) were also used. The concentration of trace gases in the atmosphere reduces significantly during annual Spring Festival holidays, whereby mobility is reduced and anthropogenic activities come to a halt. The COVID-19 lockdown during 2020 resulted in a considerable drop in vertical column densities (VCDs) of HCHO and NO2 during lockdown Level-1, which refers to strict lockdown, i.e., strict measures taken to reduce mobility (43% for NO2;24% for HCHO), and lockdown Level-2, which refers to relaxed lockdown, i.e., when the mobility restrictions were relaxed somehow (20% for NO2;22% for HCHO), compared with pre-lockdown days, as measured by the MAX-DOAS instrument. However, for 2019, a reduction in VCDs was found only during Level-1 (24% for NO2;6.62% for HCHO), when the Spring Festival happened. The weekly cycle for NO2 and HCHO depicts no significant effect of weekends on the lockdown. After the start of the Spring Festival, the VCDs of NO2 and HCHO showed a decline for 2019 as well as 2020. Backward trajectories calculated using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model indicated more air masses coming from the sea after the Spring Festival for 2019 and 2020, implying that a low pollutant load was carried by them. No impact of anthropogenic activity was found on O3 concentration. The results indicate that the ratio of HCHO to NO2 (RFN) fell in the volatile organic compound (VOC)-limited regime.
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Background: An increased risk of venous thromboembolism (VTE) in patients with coronavirus disease 2019 (COVID-19) has been reported. We performed a meta-analysis to evaluate the prevalence of VTE in COVID-19 patients.Methods: The PubMed and Embase databases were searched for studies reporting VTE in COVID-19 patients up to June 27, 2020. The selected studies were predefined into the “suspected screening group” and the “routine screening group.” The VTE prevalence was calculated using random-effect models.Results: We selected 20 studies including a total of 2763 COVID-19 patients. In 2203 COVID-19 patients from the suspected screening group, the pool VTE incidence was 15.2% (95% confidence interval [CI]: 10.5–21.6%). In 560 COVID-19 patients from the routine screening group, the VTE prevalence was 40.8% (95% CI: 20.6–64.7%). Furthermore, the VTE incidence of critically ill COVID-19 patients from the two groups was 19.6% and 61.4%, respectively, which indicates that critically ill COVID-19 patients were more susceptible to VTE.Conclusions: A high incidence of VTE was observed in COVID-19 patients, especially in severe cases. The incidence of VTE in COVID-19 patients from the routine screening group was higher than that in patients from the suspected screening group. This indicates that a lower threshold of suspicion to perform VTE imaging tests may be reasonable and there is an urgent need to adapt a regular screening strategy for VTE.