Richard T. Carson

The COVID-19 pandemic brought the need to quickly deploy non-pharmaceutical measures like facemasks to reduce transmission rates into sharp focus. Factors influencing this behavior are examined through the classic attitude–behavior lens of Fishbein and Ajzen [Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley] cast in the language of property rights and social norms. Behavior is operationalized as wearing a facemask (or not) and attitude in terms of supporting a mandatory mask mandate. This yields targetable segments of the population as they are referred to in a marketing context: wearing/supporting, wearing/not supporting, not wearing/supporting, not wearing/not supporting [Kim, D, RT Carson, D Whittington and WM Hanemann (2022). Support for regulation versus compliance: Face masks during COVID-19. Public Health in Practice, 5, 100324]. Membership in each segment is predicted using a generalized structural equation modelling (GSEM) approach focused on three broad factors. The first includes political and demographic variables, which represent exogenous taste parameters. The second is a set of knowledge variables characterizing the COVID-19 information a person possesses. These are potentially influenceable by health officials. The third relates to risk cast in the form of knowing someone who had tested positive for COVID-19, been hospitalized or died from it. The GSEM results paint a rich picture of how our factor sets interact with the four targetable segments of the population in a critical situation where high but not perfect compliance is needed.

Science funding agencies such as the NIH, NSF, and their counterparts around the world are often criticized for being too conservative, funding incremental innovations over more radical but riskier projects. One explanation for their conservatism is the way the agencies use peer review of scientific proposals. Peer review is the cornerstone of research allocation decisions, but agencies typically base decisions on a simple average of peer review scores. More novel ideas are less likely to gain consistently high ratings across evaluators and are less likely to be funded. Using a discrete choice experiment conducted with a large sample of active biomedical researchers, we find that—in contrast to funding agencies—scientists systematically prefer to fund projects with more reviewer dissensus. Rather than purely focusing on the first moment of the distribution of reviewer scores, they also value the second moment. Further, scientists with the greatest domain expertise on a proposal are more enthusiastic about dissensus, and while appetite for dissensus shrinks as budgets become tighter, it does not disappear completely. Applying our estimates to prior studies mimicking NIH’s review process shows that incorporating expert scientists’ preferences for dissensus would change marginal funding decisions for ten percent of projects worth billions of dollars per year. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

This compendium is a product of the Commission’s Green Recovery Task Force, a group of world-renowned economists, academics, environmentalists, and private sector experts convened to discuss and provide recommendations on how to build economic resilience and reduce inequality as we recover from the COVID-19 pandemic and work towards a more equitable, sustainable, and inclusive future.

Objective To determine the relative importance members of the US public place on different patient attributes in triage decisions about who should receive the last available intensive care unit (ICU) bed. Methods A discrete choice experiment was conducted with a nationally representative sample of 2000 respondents from the YouGov internet panel of US households. Respondents chose which of three hypothetical patients with COVID-19 should receive an ICU bed if only one were available. The three patients differed in age, gender, Alzheimer’s-like disability and probability of survival if the patient received the ICU bed. An experimental design varied the values of the four attributes of the three hypothetical patients with COVID-19 that a respondent saw in four choice tasks. Results The most important patient attribute to respondents was the probability the patient survives COVID-19 if they get the ICU bed (OR CI: 4.41 to 6.91). There was heterogeneity among different age groups of respondents about how much age of the patient mattered. Respondents under 30 years of age were more likely to choose young patients and old patients, and less likely to select patients aged 40–60 years old. For respondents in the age group 30–49 years old, as the age of the patient declined, their preference for saving the patient declined modestly in a linear fashion. Conclusions Respondents favoured giving the last ICU bed available to the patient with the highest probability of surviving COVID-19. Public opinion suggests a simple guideline for physician choices based on likelihood of survival as opposed to the number of life-years saved. There was heterogeneity among respondents of different age groups for allocating the last ICU bed, as well as to the importance of the patient having an Alzheimer’s-like disability (where religion of the respondent is important) and the gender of the patient (where the gender and racial identity are important).

We estimate the U.S. temperature response profile (TRP) for COVID-19 and show it is highly sensitive to temperature variation. Replacing the erratic daily death counts U.S. states initially reported with counts based on death certificate date, we build a week-ahead statistical forecasting model that explains most of their daily variation (R² = 0.97) and isolates COVID-19’s TRP (p < 0.001). These counts, normalized at 31 °C (U.S. mid-summer average), scale up to 160% at 5 °C in the static case where the infection pool is held constant. Positive case counts are substantially more temperature sensitive. When temperatures are declining, dynamic feedback through a growing infection pool can substantially amplify these temperature effects. Our estimated TRP can be incorporated into COVID-related planning exercises and used as an input to SEIR models employed for longer run forecasting. For the former, we show how our TRP is predictive of the realized pattern of growth rates in per capita positive cases across states five months after the end of our sample period. For the latter, we show the variation in herd immunity levels implied by temperature-driven, time-varying R₀series for the Alpha and Delta variants of COVID-19 for several representative states.

We estimate the U.S. temperature response curve for COVID-19 and show transmission is highly sensitive to temperature variation despite summer outbreaks widely assumed to show otherwise. By largely replacing the daily death counts states initially reported with counts based on death certificate date, we build a week-ahead statistical forecasting model that explains most of the daily variation (R ² = 0.97) and isolates COVID-19’s temperature response profile (p < 0.001). These counts normalized at 31°C (U.S. mid-summer average) scale up to nearly 160% at 5°C. Positive cases are more temperature sensitive, scaling up to almost 400% between 31°C and 5°C. Dynamic feedback amplifies these effects, suggesting that cooling temperatures are likely to the substantially increase COVID-19 transmission. Article Summary Line: COVID-19’s temperature response profile is reliably estimated using re-assembled state-reported data and suggests the onset of cold weather will amplify its spread.

We measure the value placed by the American public on ensuring the continued existence of the traditional Hopi culture and way of life at the Hopi Reservation in Arizona. The Hopi are the oldest living culture in the United States. The continued existence of the Reservation is threatened by depletion of the groundwater resource underlying the reservation. In the future, without a new source of water, the Hopi will run out of water to support the villages and continue their traditional Hopi agricultural practices. Many Hopi will have to move off the Reservation and give up their traditional culture and way of life. The Reservation will no longer serve as a permanent home for the Hopi Tribe. An expensive pipeline would be required to convey a new source of water to the Reservation, for which the Federal government might pay. The question is: would the expenditure by the federal government to convey water that would ensure the continued existence of the traditional Hopi culture at the Hopi Reservation be justified by the existence value of that culture to the American people? This paper describes the results of a study undertaken to measure that existence value. We show that a simple stated preference design, using only a single monetary amount, is sufficient to provide a bound.