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Cataract is the first cause of blindness and the major cause of visual impairment worldwide. Under conditions of global warming, researchers have begun to give attention to the influence of increasing temperature on cataract patients. Our paper aimed to investigate the association between extreme heat and hospital admissions for cataract in Hefei, China. Based on data from the New Rural Cooperative Medical System and National Meteorological Information Center, we used a generalized additive model and a distributed lag nonlinear model to examine the relationship between extreme heat and hospitalizations for cataract, with consideration of cumulative and lagged effects. When current mean temperature was above 28 °C, each 1 °C rise was associated with a 4% decrease in the number of cataract admissions (RR = 0.96, 95% CI = 0.94–0.98). The cumulative relative risk over 11 days of lag was the lowest, which indicated that every 1 °C increase in mean temperature above 28 °C was associated with a 19% decrease in the number of hospital admissions for cataract (RR = 0.81, 95% CI = 0.75–0.88). In subgroup analyses, the negative association between extreme heat and hospital admissions for cataract was stronger among patients who were not admitted to provincial-level hospitals. In conclusion, this paper found that extreme heat was negatively associated with cataract hospitalizations in Hefei, providing useful information for hospitals and policymakers. Electronic supplementary material The online version of this article (10.1007/s11356-020-10402-1) contains supplementary material, which is available to authorized users.

With the popularization of computers and the development of information engineering, the emergence of search engines makes it possible to get the information needed from big data quickly and efficiently. However, in recent years, a multiplicity of new viruses have been propagated by search engines. Many researchers choose to cut off the source of virus propagation, ignoring the virus immunization strategy based on the search engine. In this paper, we analyze the impact of search engines on virus propagation. First, considering the immune effect and cost, two kinds of immune mechanisms based on the search engine that have greater practicability are defined. Second, immune mechanisms based on the search engine are theoretically analyzed by the iteration method and the dynamic method. The results show that this immunization strategy can slow down or eliminate the propagation of a virus to a certain extent. Third, three real social network data sets are used to simulate and analyze the immune mechanism. We find that when the proportion of nodes being infected and the proportion of infected nodes being identified by the search engine satisfy a certain relationship, our immune mechanism can inhibit the spread of viruses, which confirms our theoretical analysis results.

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., Graphical abstract Image 1, Highlights • There was a positive relationship between human mobility and COVID-19 infection. • Human mobility was positively associated with the air quality index. • Air quality index partially mediated the association of human mobility with COVID-19 infection. • We also observed the significant mediating effects of PM2.5, PM10, and NO2.

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. National Natural Science Foundation of China

Plaque rupture or erosion represents a major cause of stroke and the acute coronary syndrome. Information on plaque morphology and composition is essential to identify patients at increased risk for acute cardio- and cerebrovascular events, and may play a key role in individualizing therapeutic strategies and monitoring the effect of interventions. The rapidly emerging field of MR and targeted molecular MRI allows to qualitatively and quantitatively characterize plaque features. We aimed to review the literature regarding the current most promising advanced techniques to image vulnerable atherosclerotic plaques.