Community- Versus Health Care Organization-Based Approaches to Expanding At-Home COVID-19 Testing in Black and Latino Communities, New Jersey, 2021.

At-home COVID-19 testing offers convenience and safety advantages. We evaluated at-home testing in Black and Latino communities through an intervention comparing community-based organization (CBO) and health care organization (HCO) outreach. From May through December 2021, 1100 participants were recruited, 94% through CBOs. The odds of COVID-19 test requests and completions were significantly higher in the HCO arm. The results showed disparities in test requests and completions related to age, race, language, insurance, comorbidities, and pandemic-related challenges. Despite the popularity of at-home testing, barriers exist in underresourced communities. (Am J Public Health. 2022;112(S9):S918-S922. https://doi.org/10.2105/AJPH.2022.306989).

Research Note: Intergenerational Transmission Is Not Sufficient for Positive Long-Term Population Growth.

All leading long-term global population projections agree on continuing fertility decline, resulting in a rate of population size growth that will continue to decline toward zero and would eventually turn negative. However, scholarly and popular arguments have suggested that because fertility transmits intergenerationally (i.e., higher fertility parents tend to have higher fertility children) and is heterogeneous within a population, long-term population growth must eventually be positive, as high-fertility groups come to dominate the population. In this research note, we show that intergenerational transmission of fertility is not sufficient for positive long-term population growth, for empirical and theoretical reasons. First, because transmission is imperfect, the combination of transmission rates and fertility rates may be quantitatively insufficient for long-term population growth: higher fertility parents may nevertheless produce too few children who retain higher fertility preferences. Second, today even higher fertility subpopulations show declining fertility rates, which may eventually fall below replacement (and in some populations already are). Therefore, although different models of fertility transmission across generations reach different conclusions, depopulation is likely under any model if, in the future, even higher fertility subpopulations prefer and achieve below-replacement fertility. These results highlight the plausibility of long-term global depopulation and the importance of understanding the possible consequences of depopulation.

Population ethics and the prospects for fertility policy as climate mitigation policy.

What are the prospects for using population policy as tool to reduce carbon emissions? In this paper, we review evidence from population science, in order to inform debates in population ethics that, so far, have largely taken place within the academic philosophy literature. In particular, we ask whether fertility policy is likely to have a large effect on carbon emissions, and therefore on temperature change. Our answer is no. Prospects for a policy of fertility-reduction-as-climate-mitigation are limited by population momentum, a demographic factor that limits possible variation in the size of the population, even if fertility rates change very quickly. In particular, a hypothetical policy that instantaneously changed fertility and mortality rates to replacement levels would nevertheless result in a population of over 9 billion people in 2060. We use a leading climate-economy model to project the consequence of such a hypothetical policy for climate change. As a standalone mitigation policy, such a hypothetical change in the size of the future population - much too large to be implementable by any foreseeable government program - would reduce peak temperature change only to 6.4°C, relative to 7.1°C under the most likely population path. Therefore, fertility reduction is unlikely to be an adequate core approach to climate mitigation.

Impact of population growth and population ethics on climate change mitigation policy.

Future population growth is uncertain and matters for climate policy: higher growth entails more emissions and means more people will be vulnerable to climate-related impacts. We show that how future population is valued importantly determines mitigation decisions. Using the Dynamic Integrated Climate-Economy model, we explore two approaches to valuing population: a discounted version of total utilitarianism (TU), which considers total wellbeing and is standard in social cost of carbon dioxide (SCC) models, and of average utilitarianism (AU), which ignores population size and sums only each time period's discounted average wellbeing. Under both approaches, as population increases the SCC increases, but optimal peak temperature decreases. The effect is larger under TU, because it responds to the fact that a larger population means climate change hurts more people: for example, in 2025, assuming the United Nations (UN)-high rather than UN-low population scenario entails an increase in the SCC of 85% under TU vs. 5% under AU. The difference in the SCC between the two population scenarios under TU is comparable to commonly debated decisions regarding time discounting. Additionally, we estimate the avoided mitigation costs implied by plausible reductions in population growth, finding that large near-term savings ($billions annually) occur under TU; savings under AU emerge in the more distant future. These savings are larger than spending shortfalls for human development policies that may lower fertility. Finally, we show that whether lowering population growth entails overall improvements in wellbeing-rather than merely cost savings-again depends on the ethical approach to valuing population.

Optimal Climate Policy and the Future of World Economic Development.

How much should the present generations sacrifice to reduce emissions today, in order to reduce the future harms of climate change? Within climate economics, debate on this question has been focused on so-called "ethical parameters" of social time preference and inequality aversion. We show that optimal climate policy similarly importantly depends on the future of the developing world. In particular, although global poverty is falling and the economic lives of the poor are improving worldwide, leading models of climate economics may be too optimistic about two central predictions: future population growth in poor countries, and future convergence in total factor productivity (TFP). We report results of small modifications to a standard model: under plausible scenarios for high future population growth (especially in sub-Saharan Africa) and for low future TFP convergence, we find that optimal near-term carbon taxes could be substantially larger.

Inequality, climate impacts on the future poor, and carbon prices.

Integrated assessment models of climate and the economy provide estimates of the social cost of carbon and inform climate policy. We create a variant of the Regional Integrated model of Climate and the Economy (RICE)-a regionally disaggregated version of the Dynamic Integrated model of Climate and the Economy (DICE)-in which we introduce a more fine-grained representation of economic inequalities within the model's regions. This allows us to model the common observation that climate change impacts are not evenly distributed within regions and that poorer people are more vulnerable than the rest of the population. Our results suggest that this is important to the social cost of carbon-as significant, potentially, for the optimal carbon price as the debate between Stern and Nordhaus on discounting.

Animal welfare: Methods to improve policy and practice.

New methods are emerging to quantify human and animal welfare on a common scale, creating new tools for policy.

Repugnant Conclusions.

The population ethics literature has long focused on attempts to avoid the repugnant conclusion. We show that a large set of social orderings that are conventionally understood to escape the repugnant conclusion do not in fact avoid it in all instances. As we demonstrate, prior results depend on formal definitions of the repugnant conclusion that exclude some repugnant cases, for reasons inessential to any "repugnance" (or other meaningful normative properties) of the repugnant conclusion. In particular, the literature traditionally formalizes the repugnant conclusion to exclude cases that include an unaffected sub-population. We relax this normatively irrelevant exclusion, and others. Using several more inclusive formalizations of the repugnant conclusion, we then prove that any plausible social ordering implies some instance of the repugnant conclusion. This understanding - that it is impossible to avoid all instances of the repugnant conclusion - is broader than the traditional understanding in the literature that the repugnant conclusion can only be escaped at unappealing theoretical costs. Therefore, the repugnant conclusion provides no methodological guidance for theory or policy-making, because it does not discriminate among candidate social orderings. So escaping the repugnant conclusion should not be a core goal of the population ethics literature.

Broad cross-national public support for accelerated COVID-19 vaccine trial designs.

A vaccine for COVID-19 is urgently needed. Several vaccine trial designs may significantly accelerate vaccine testing and approval, but also increase risks to human subjects. Concerns about whether the public would see such designs as ethical represent an important roadblock to their implementation; accordingly, both the World Health Organization and numerous scholars have called for consulting the public regarding them. We answered these calls by conducting a cross-national survey (n = 5920) in Australia, Canada, Hong Kong, New Zealand, South Africa, Singapore, the United Kingdom, and the United States. The survey explained key differences between traditional vaccine trials and two accelerated designs: a challenge trial or a trial integrating a Phase II safety and immunogenicity trial into a larger Phase III efficacy trial. Respondents' answers to comprehension questions indicate that they largely understood the key differences and ethical trade-offs between the designs from our descriptions. We asked respondents whether they would prefer scientists to conduct traditional trials or one of these two accelerated designs. We found broad majorities prefer for scientists to conduct challenge trials (75%) and integrated trials (63%) over standard trials. Even as respondents acknowledged the risks, they perceived both accelerated trials as similarly ethical to standard trial designs. This high support is consistent across every geography and demographic subgroup we examined, including vulnerable populations. These findings may help assuage some of the concerns surrounding accelerated designs.

Utilitarian benchmarks for emissions and pledges promote equity, climate and development.

Tools are needed to benchmark carbon emissions and pledges against criteria of equity and fairness. However, standard economic approaches, which use a transparent optimization framework, ignore equity. Models that do include equity benchmarks exist, but often use opaque methodologies. Here we propose a utilitarian benchmark computed in a transparent optimization framework, which could usefully inform the equity benchmark debate. Implementing the utilitarian benchmark, which we see as ethically minimal and conceptually parsimonious, in two leading climate-economy models allows for calculation of the optimal allocation of future emissions. We compare this optimum with historical emissions and initial nationally determined contributions. Compared with cost minimization, utilitarian optimization features better outcomes for human development, equity and the climate. Peak temperature is lower under utilitarianism because it reduces the human development cost of global mitigation. Utilitarianism therefore is a promising inclusion to a set of benchmarks for future explorations of climate equity.

Valuing Health Impacts In Climate Policy: Ethical Issues And Economic Challenges.

Deciding which climate policies to enact, and where and when to enact them, requires weighing their costs against the expected benefits. A key challenge in climate policy is how to value health impacts, which are likely to be large and varied, considering that they will accrue over long time horizons (centuries), will occur throughout the world, and will be distributed unevenly within countries depending in part on socioeconomic status. These features raise a number of important economic and ethical issues including how to value human life in different countries at different levels of development, how to value future people, and how much priority to give the poor and disadvantaged. In this article we review each of these issues, describe different approaches for addressing them in quantitative climate policy analysis, and show how their treatment can dramatically change what should be done about climate change. Finally, we use the social cost of carbon, which reflects the cost of adding carbon emissions to the atmosphere, as an example of how analysis of climate impacts is sensitive to ethical assumptions. We consider $20 a reasonable lower bound for the social cost of carbon, but we show that a much higher value is warranted given a strong concern for equity within and across generations.

The impact of human health co-benefits on evaluations of global climate policy.

The health co-benefits of CO2 mitigation can provide a strong incentive for climate policy through reductions in air pollutant emissions that occur when targeting shared sources. However, reducing air pollutant emissions may also have an important co-harm, as the aerosols they form produce net cooling overall. Nevertheless, aerosol impacts have not been fully incorporated into cost-benefit modeling that estimates how much the world should optimally mitigate. Here we find that when both co-benefits and co-harms are taken fully into account, optimal climate policy results in immediate net benefits globally, overturning previous findings from cost-benefit models that omit these effects. The global health benefits from climate policy could reach trillions of dollars annually, but will importantly depend on the air quality policies that nations adopt independently of climate change. Depending on how society values better health, economically optimal levels of mitigation may be consistent with a target of 2 °C or lower.

The comparative importance for optimal climate policy of discounting, inequalities and catastrophes.

Integrated assessment models (IAMs) of climate and the economy provide estimates of the social cost of carbon and inform climate policy. With the Nested Inequalities Climate Economy model (NICE) (Dennig et al. PNAS 112:15,827-15,832, 2015), which is based on Nordhaus's Regional Integrated Model of Climate and the Economy (RICE), but also includes inequalities within regions, we investigate the comparative importance of several factors-namely, time preference, inequality aversion, intraregional inequalities in the distribution of both damage and mitigation cost and the damage function. We do so by computing optimal carbon price trajectories that arise from the wide variety of combinations that are possible given the prevailing range of disagreement over each factor. This provides answers to a number of questions, including Thomas Schelling's conjecture that properly accounting for inequalities could lead the inequality aversion parameter to have an effect opposite to what is suggested by the Ramsey equation.