RESUMO
After the outbreak of COVID-19, the interaction of infectious disease systems and social systems has challenged traditional infectious disease modeling methods. Starting from the research purpose and data, researchers improved the structure and data of the compartment model or used agents and artificial intelligence based models to solve epidemiological problems. In terms of modeling methods, the researchers use compartment subdivision, dynamic parameters, agent-based model methods, and artificial intelligence related methods. In terms of factors studied, the researchers studied 6 categories: human mobility, nonpharmaceutical interventions (NPIs), ages, medical resources, human response, and vaccine. The researchers completed the study of factors through modeling methods to quantitatively analyze the impact of social systems and put forward their suggestions for the future transmission status of infectious diseases and prevention and control strategies. This review started with a research structure of research purpose, factor, data, model, and conclusion. Focusing on the post-COVID-19 infectious disease prediction simulation research, this study summarized various improvement methods and analyzes matching improvements for various specific research purposes.
RESUMO
Antiseptic polymer gel-surfactant complexes were prepared by incorporating the low-molecular-weight cationic disinfectant cetylpyridinium chloride into the oppositely charged, slightly cross-linked polymer matrices. Three types of polymers were used: copolymers of acrylamide and sodium 2-acrylamido-2-methylpropane sulfonate; copolymers of acrylamide and sodium methacrylate; copolymers of vinylpyrrolidone and sodium methacrylate. It was shown that the rate of the release of the cationic disinfectant from the oppositely charged polymer gels could be tuned in a fairly broad range by varying the concentration of the disinfectant, the degree of swelling, and degree of cross-linking of the gel and the content/type of anionic repeat units in the polymer matrix. Polymer-surfactant complexes were demonstrated to reduce SARS-CoV-2 titer by seven orders of magnitude in as little as 5 s. The complexes retained strong virucidal activity against SARS-CoV-2 for at least one week.
RESUMO
The virucidal activity of a series of cationic surfactants differing in the length and number of hydrophobic tails (at the same hydrophilic head) and the structure of the hydrophilic head (at the same length of the hydrophobic n-alkyl tail) was compared. It was shown that an increase in the length and number of hydrophobic tails, as well as the presence of a benzene ring in the surfactant molecule, enhance the virucidal activity of the surfactant against SARS-CoV-2. This may be due to the more pronounced ability of such surfactants to penetrate and destroy the phospholipid membrane of the virus. Among the cationic surfactants studied, didodecyldimethylammonium bromide was shown to be the most efficient as a disinfectant, its 50% effective concentration (EC50) being equal to 0.016 mM. Two surfactants (didodecyldimethylammonium bromide and benzalkonium chloride) can deactivate SARS-CoV-2 in as little as 5 s.