Epidemiological characteristics of patients from fever clinics during the COVID-19 epidemic in 2022 in Shanghai, China.

An outbreak of COVID-19 in Shanghai, China, in March 2022 was caused by the Omicron variant. The epidemic lasted for more than 3 months, and the cumulative number of infected people reached 626,000. We investigated the impact of clinical factors on disease outcomes in patients with COVID-19. Using a case-control study design, we examined cases from fever clinics with confirmed Omicron variant infection, analyzed their population and laboratory diagnostic characteristics, and provided theoretical support for subsequent epidemic prevention and control. Logistic regression was used to identify factors associated with infection with the Omicron variant. The results of this study show that the COVID-19 vaccine can protect against infection with the Omicron variant, and more than 50% of infected people had not been vaccinated. Compared with the epidemic in Wuhan 2 years ago, most of the patients in the hospital in the Shanghai epidemic had underlying diseases (P = 0.006). A comparison of patients infected with the Omicron variant in Shanghai and patients with other respiratory tract infections showed no significant difference in the levels of neutrophils, lymphocytes, eosinophils, white blood cells, hemoglobin, or platelets (P > 0.05). People over 60 years old and those with underlying diseases were at risk for pneumonia (OR = 14.62 (5.49-38.92), P < 0.001; OR = 5.29 (2.58-10.85), P < 0.001, respectively), but vaccination was a protective factor (OR = 0.24 (0.12-0.49), P < 0.001). In summary, vaccination has a potential effect on infection with Omicron variant strains and provides protection against pneumonia. The severity of illness caused by the Omicron variant in 2022 was significantly lower than that of the original SARS-CoV-2 variant from two years previously.

Sustainable development and health assessment model of higher education in India: A mathematical modeling approach.

The Coronavirus Disease 2019 has resulted in a transition from physical education to online learning, leading to a collapse of the established educational order and a wisdom test for the education governance system. As a country seriously affected by the pandemic, the health of the Indian higher education system urgently requires assessment to achieve sustainable development and maximize educational externalities. This research systematically proposes a health assessment model from four perspectives, including educational volume, efficiency, equality, and sustainability, by employing the Technique for Order Preference by Similarity to an Ideal Solution Model, Principal Component Analysis, DEA-Tobit Model, and Augmented Solow Model. Empirical results demonstrate that India has high efficiency and an absolute health score in the higher education system through multiple comparisons between India and the other selected countries while having certain deficiencies in equality and sustainability. Additionally, single-target and multiple-target path are simultaneously proposed to enhance the Indian current education system. The multiple-target approach of the India-China-Japan-Europe-USA process is more feasible to achieve sustainable development, which would improve the overall health score from .351 to .716. This finding also reveals that the changes are relatively complex and would take 91.5 years considering the relationship between economic growth rates and crucial indicators. Four targeted policies are suggested for each catching-up period, including expanding and increasing the social funding sources, striving for government expenditure support to improve infrastructures, imposing gender equality in education, and accelerating the construction of high-quality teachers.