ABSTRACT
Chapter 1:An Equilibrium Model of Traffic Accidents: from the Peltzman Effect on Autonomous Cars We propose a population game to analyze drivers' driving behavior. Each driver interacts with a myriad of other drivers in a strategic substitute fashion, namely other drivers' reckless behavior encourages me to drive more carefully. We establish a set of reasonable assumptions, under which this game admits a unique Nash Equilibrium. This allows us to analyze the question that Peltzman (1975) raised: If the driving environment improves, drivers respond by driving more incautiously. Can this reaction lead to more auto accidents? To this end, we derive a sufficient condition that rules out this possibility. We then justify this sufficient condition using an empirical regularity we discover from data regarding mutual accidents between different groups of drivers. Throughout the analysis, we provide a definition of potential games for a continuum of players, where the interaction term depends also on their types. Also, the comparative statics result we produced, can be applied to a range of games with strategic substitutesChapter 2: Information Asymmetry in an Epidemic: A Game Theoretical Analysis of Communication Failure In an epidemic, individuals reduce social activities to protect themselves from getting infected. This also protects others from potential infections, but utility-maximizing individuals do not consider this spillover effect. Consequently, individuals choose a social activity that is higher than the regulator's preferred social optimum. When facing a novel disease such as COVID-19, the public often lacks knowledge of certain disease attributes such as the pass-through rate, the mortality rate, the number of current infections, etc. On the other hand, the regulator is often better informed. We build a game theoretic model to study how the regulator strategically communicates to the public, in the presence of misaligned incentives caused by the spillover effect. When the public uncertainty is large and the disease reproduction rate is high, the regulator loses credibility, and cannot reveal any information to the public. Communication failure can lead to the public under (or over) reactions. Compartmental models that overlook this information friction can significantly under-estimate the future infection rate. (PsycInfo Database Record (c) 2022 APA, all rights reserved)
ABSTRACT
Chapter 1:An Equilibrium Model of Traffic Accidents: from the Peltzman Effect on Autonomous Cars We propose a population game to analyze drivers' driving behavior. Each driver interacts with a myriad of other drivers in a strategic substitute fashion, namely other drivers' reckless behavior encourages me to drive more carefully. We establish a set of reasonable assumptions, under which this game admits a unique Nash Equilibrium. This allows us to analyze the question that Peltzman (1975) raised: If the driving environment improves, drivers respond by driving more incautiously. Can this reaction lead to more auto accidents? To this end, we derive a sufficient condition that rules out this possibility. We then justify this sufficient condition using an empirical regularity we discover from data regarding mutual accidents between different groups of drivers. Throughout the analysis, we provide a definition of potential games for a continuum of players, where the interaction term depends also on their types. Also, the comparative statics result we produced, can be applied to a range of games with strategic substitutesChapter 2: Information Asymmetry in an Epidemic: A Game Theoretical Analysis of Communication Failure In an epidemic, individuals reduce social activities to protect themselves from getting infected. This also protects others from potential infections, but utility-maximizing individuals do not consider this spillover effect. Consequently, individuals choose a social activity that is higher than the regulator's preferred social optimum. When facing a novel disease such as COVID-19, the public often lacks knowledge of certain disease attributes such as the pass-through rate, the mortality rate, the number of current infections, etc. On the other hand, the regulator is often better informed. We build a game theoretic model to study how the regulator strategically communicates to the public, in the presence of misaligned incentives caused by the spillover effect. When the public uncertainty is large and the disease reproduction rate is high, the regulator loses credibility, and cannot reveal any information to the public. Communication failure can lead to the public under (or over) reactions. Compartmental models that overlook this information friction can significantly under-estimate the future infection rate. (PsycInfo Database Record (c) 2022 APA, all rights reserved)
ABSTRACT
Xiyanping (XYP) is a Chinese herbal medicine used in the clinic to treat respiratory infection and pneumonia. Recent evidence identified XYP as a potential inhibitor of severe acute respiratory syndrome coronavirus 2, implying XYP as a possible treatment for the coronavirus disease 2019 (COVID-19). Here, we conducted a prospective, multicenter, open-label and randomized controlled trial to evaluate the safety and effectiveness of XYP injection in patients with mild to moderate COVID-19. We consecutively recruited 130 COVID-19 patients with mild to moderate symptoms from five study sites, and randomized them in 1:1 ratio to receive XYP injection in combination with standard therapy or receive standard supportive therapy alone. We found that XYP injection significantly reduced the time to cough relief, fever resolution and virus clearance. Less patients receiving XYP injection experienced disease progression to the severe stage during the treatment process. No severe adverse events were reported during the study. Taken together, XYP injection is safe and effective in improving the recovery of patients with mild to moderate COVID-19. However, further studies are warranted to evaluate the efficacy of XYP in an expanded cohort comprising COVID-19 patients at different disease stages.