The elicitation of autologous neutralizing responses by immunization with HIV-1 envelope (Env) trimers conformationally stabilized in a prefusion closed state has generated considerable interest in the HIV-1 vaccine field. However, soluble prefusion closed Env trimers have been produced from only a handful of HIV-1 strains, limiting their utility as vaccine antigens and B cell probes. Here, we report the engineering from 81 HIV-1 strains of soluble, fully cleaved, prefusion Env trimers with appropriate antigenicity. We used a 96-well expression-screening format to assess the ability of artificial disulfides and Ile559Pro substitution (DS-SOSIP) to produce soluble cleaved-Env trimers; from 180 Env strains, 20 yielded prefusion closed trimers. We also created chimeras, by utilizing structure-based design to incorporate select regions from the well-behaved BG505 strain; from 180 Env strains, 78 DS-SOSIP-stabilized chimeras, including 61 additional strains, yielded prefusion closed trimers. Structure-based design thus enables the production of prefusion closed HIV-1-Env trimers from dozens of diverse strains.

We study the factors associated with compliance with social-distancing regulations using a unique dataset on the behaviour of Ontarians during the COVID-19 pandemic. To start, we build a simple theoretical model of social distancing in order to understand how some individual and community-level factors influence compliance. We test our model's predictions by designing and conducting a survey on Ontarians in which we elicit their degree of compliance with current distancing regulations as well as proposed regulations that impose different fine levels on violators or grant wage subsidies to encourage staying at home. In line with the model's predictions, we show that variables related to one's risk of infection (e.g., health status, age, necessity of working outside the home, regional COVID-19 cases) are significant predictors of compliance as are gender, political beliefs, risk and time preferences. Furthermore, we demonstrate that fines and wage subsidies can be powerful policy tools for promoting full compliance with regulations.

We study the factors associated with compliance with social-distancing regulations using a unique dataset on the behaviour of Ontarians during the COVID-19 pandemic. To start, we build a simple theoretical model of social distancing in order to understand how some individual and community-level factors influence compliance. We test our model's predictions by designing and conducting a survey on Ontarians in which we elicit their degree of compliance with current distancing regulations as well as proposed regulations that impose different fine levels on violators or grant wage subsidies to encourage staying at home. In line with the model's predictions, we show that variables related to one's risk of infection (e.g., health status, age, necessity of working outside the home, regional COVID-19 cases) are significant predictors of compliance as are gender, political beliefs, risk and time preferences. Furthermore, we demonstrate that fines and wage subsidies can be powerful policy tools for promoting full compliance with regulations.

No abstract