Valuing bioeconomic impacts of regulation on nutrient loads mediated by invasive mussels in Lake Michigan.

Current calls to correct the perturbed ecosystems and nutrient imbalances of the Laurentian Great Lakes focus on setting target nutrient levels that will be met by environmental and economic regulations to reduce the flow of excess nutrients into the lakes. While these standard types of regulations have been successful in the past, it is unclear whether they will achieve similar ecological and economic successes now amid possible ecosystem regime shifts triggered by invasive mussels. We compute the bioeconomic costs and benefits of hypothetical regulations designed to target nutrient loads in present-day Lake Michigan through agricultural operations, which are known to be nonpoint source polluters of the aquatic ecosystem network. Our results show how reducing nutrient loads may exacerbate spatially disparate ecosystem issues that generate overall economic losses. Conversely, and counterintuitively, allowing for more nutrient loading could generate economic gains over our assessment timeframe. We determine that implementation of standard nutrient target policies are costly and likely inadequate for current dreissenid-affected aquatic ecosystems experiencing nutrient imbalances because they disregard the interactive role of invasive mussels in nutrient cycling.

Physical distancing versus testing with self-isolation for controlling an emerging epidemic.

Two distinct strategies for controlling an emerging epidemic are physical distancing and regular testing with self-isolation. These strategies are especially important before effective vaccines or treatments become widely available. The testing strategy has been promoted frequently but used less often than physical distancing to mitigate COVID-19. We compared the performance of these strategies in an integrated epidemiological and economic model that includes a simple representation of transmission by "superspreading," wherein a relatively small fraction of infected individuals cause a large share of infections. We examined the economic benefits of distancing and testing over a wide range of conditions, including variations in the transmissibility and lethality of the disease meant to encompass the most prominent variants of COVID-19 encountered so far. In a head-to-head comparison using our primary parameter values, both with and without superspreading and a declining marginal value of mortality risk reductions, an optimized testing strategy outperformed an optimized distancing strategy. In a Monte Carlo uncertainty analysis, an optimized policy that combined the two strategies performed better than either one alone in more than 25% of random parameter draws. Insofar as diagnostic tests are sensitive to viral loads, and individuals with high viral loads are more likely to contribute to superspreading events, superspreading enhances the relative performance of testing over distancing in our model. Both strategies performed best at moderate levels of transmissibility, somewhat lower than the transmissibility of the ancestral strain of SARS-CoV-2.

Challenges of integrating economics into epidemiological analysis of and policy responses to emerging infectious diseases.

COVID-19 has shown that the consequences of a pandemic are wider-reaching than cases and deaths. Morbidity and mortality are important direct costs, but infectious diseases generate other direct and indirect benefits and costs as the economy responds to these shocks: some people lose, others gain and people modify their behaviours in ways that redistribute these benefits and costs. These additional effects feedback on health outcomes to create a complicated interdependent system of health and non-health outcomes. As a result, interventions primarily intended to reduce the burden of disease can have wider societal and economic effects and more complicated and unintended, but possibly not anticipable, system-level influences on the epidemiological dynamics themselves. Capturing these effects requires a systems approach that encompasses more direct health outcomes. Towards this end, in this article we discuss the importance of integrating epidemiology and economic models, setting out the key challenges which such a merging of epidemiology and economics presents. We conclude that understanding people's behaviour in the context of interventions is key to developing a more complete and integrated economic-epidemiological approach; and a wider perspective on the benefits and costs of interventions (and who these fall upon) will help society better understand how to respond to future pandemics.

Investing to Both Prevent and Prepare for COVID-XX.

One cause of the high rate of COVID-19 cases in the USA is thought to be insufficient prior capital investment in national health programs to preemptively reduce the likelihood of an outbreak and in national capacity to reduce the severity of any outbreak that does occur. We analyze the choice of capital investments (e.g. testing capacity, stockpiles of PPE, and information sharing capacity) and find the economically efficient capital stock associated with mitigating pandemic risk should be dramatically expanded. Policymakers who fail to invest in public health forgo significant expected cost savings from being prepared.

Non-stationary and interactive effects of climate and competition on pink salmon productivity.

Pacific salmon (Oncorhynchus spp.) are exposed to increased environmental change and multiple human stressors. To anticipate future impacts of global change and to improve sustainable resource management, it is critical to understand how wild salmon populations respond to stressors associated with human-caused changes such as climate warming and ocean acidification, as well as competition in the ocean, which is intensified by the large-scale production and release of hatchery reared salmon. Pink salmon (O. gorbuscha) are a keystone species in the North Pacific Ocean and support highly valuable commercial fisheries. We investigated the joint effects of changes in ocean conditions and salmon abundances on the productivity of wild pink salmon. Our analysis focused on Prince William Sound in Alaska, because the region accounts for ~50% of the global production of hatchery pink salmon with local hatcheries releasing 600-700 million pink salmon fry annually. Using 60 years of data on wild pink salmon abundances, hatchery releases, and ecological conditions in the ocean, we find evidence that hatchery pink salmon releases negatively affect wild pink salmon productivity, likely through competition between wild and hatchery juveniles in nearshore marine habitats. We find no evidence for effects of ocean acidification on pink salmon productivity. However, a change in the leading mode of North Pacific climate in 1988-1989 weakened the temperature-productivity relationship and altered the strength of intraspecific density dependence. Therefore, our results suggest non-stationary (i.e., time varying) and interactive effects of ocean climate and competition on pink salmon productivity. Our findings further highlight the need for salmon management to consider potential adverse effects of large-scale hatchery production within the context of ocean change.

Emphasize personal health benefits to boost COVID-19 vaccination rates.

The rapid development of COVID-19 vaccines is a tremendous scientific response to the current global pandemic. However, vaccines per se do not save lives and restart economies. Their success depends on the number of people getting vaccinated. We used a survey experiment to examine the impact on vaccine intentions of a variety of public health messages identified as particularly promising: three messages that emphasize different benefits from the vaccines (personal health, the health of others, and the recovery of local and national economies) and one message that emphasizes vaccine safety. Because people will likely be exposed to multiple messages in the real world, we also examined the effect of these messages in combination. Based on a nationally quota representative sample of 3,048 adults in the United States, our findings suggest that several forms of public messages can increase vaccine intentions, but messaging that emphasizes personal health benefits had the largest impact.

Hesitancy Toward a COVID-19 Vaccine.

The scientific community has come together in a mass mobilization to combat the public health risks of COVID-19, including efforts to develop a vaccine. However, the success of any vaccine depends on the share of the population that gets vaccinated. We designed a survey experiment in which a nationally representative sample of 3,133 adults in the USA stated their intentions to vaccinate themselves and their children for COVID-19. The factors that we varied across treatments were: the stated severity and infectiousness of COVID-19 and the stated source of the risk information (White House or the Centers for Disease Control). We find that 20% of people in the USA intend to decline the vaccine. We find no statistically significant effect on vaccine intentions from the severity of COVID-19. In contrast, we find that the degree of infectiousness of the coronavirus influences vaccine intentions and that inconsistent risk messages from public health experts and elected officials may reduce vaccine uptake. However, the most important determinants of COVID-19 vaccine hesitancy seem to be distrust of the vaccine safety (including uncertainty due to vaccine novelty), as well as general vaccine avoidance, as implied by not having had a flu shot in the last two years.

Effects of Physical Distancing to Control COVID-19 on Public Health, the Economy, and the Environment.

Physical distancing measures are important tools to control disease spread, especially in the absence of treatments and vaccines. While distancing measures can safeguard public health, they also can profoundly impact the economy and may have important indirect effects on the environment. The extent to which physical distancing measures should be applied therefore depends on the trade-offs between their health benefits and their economic costs. We develop an epidemiological-economic model to examine the optimal duration and intensity of physical distancing measures aimed to control the spread of COVID-19. In an application to the United States, our model considers the trade-off between the lives saved by physical distancing-both directly from stemming the spread of the virus and indirectly from reductions in air pollution during the period of physical distancing-and the short- and long-run economic costs that ensue from such measures. We examine the effect of air pollution co-benefits on the optimal physical distancing policy and conduct sensitivity analyses to gauge the influence of several key parameters and uncertain model assumptions. Using recent estimates of the association between airborne particulate matter and the virulence of COVID-19, we find that accounting for air pollution co-benefits can significantly increase the intensity and duration of the optimal physical distancing policy. To conclude, we broaden our discussion to consider the possibility of durable changes in peoples' behavior that could alter local markets, the global economy, and our relationship to nature for years to come.

Catastrophic Risk: Waking Up to the Reality of a Pandemic?

Will a major shock awaken the US citizens to the threat of catastrophic pandemic risk? Using a natural experiment administered both before and after the 2014 West African Ebola Outbreak, our evidence suggests "no." Our results show that prior to the Ebola scare, the US citizens were relatively complacent and placed a low relative priority on public spending to prepare for a pandemic disease outbreak relative to an environmental disaster risk (e.g., Fukushima) or a terrorist attack (e.g., 9/11). After the Ebola scare, the average citizen did not over-react to the risk. This flat reaction was unexpected given the well-known availability heuristic-people tend to over-weigh judgments of events more heavily toward more recent information. In contrast, the average citizen continued to value pandemic risk less relative to terrorism or environmental risk.

Chronic wasting disease undermines efforts to control the spread of brucellosis in the Greater Yellowstone Ecosystem.

Wildlife diseases pose a substantial threat to the provisioning of ecosystem services. We use a novel modeling approach to study the potential loss of these services through the imminent introduction of chronic wasting disease (CWD) to elk populations in the Greater Yellowstone Ecosystem (GYE). A specific concern is that concentrating elk at feedgrounds may exacerbate the spread of CWD, whereas eliminating feedgrounds may increase the number of elk on private ranchlands and the transmission of a second disease, brucellosis, from elk to cattle. To evaluate the consequences of management strategies given the threat of two concurrent wildlife diseases, we develop a spatiotemporal bioeconomic model. GPS data from elk and landscape attributes are used to predict migratory behavior and population densities with and without supplementary feeding. We use a 4,800 km2 area around Pinedale, Wyoming containing four existing feedgrounds as a case study. For this area, we simulate welfare estimates under a variety of management strategies. Our results indicate that continuing to feed elk could result in substantial welfare losses for the case-study region. Therefore, to maximize the present value of economic net benefits generated by the local elk population upon CWD's arrival in the region, wildlife managers may wish to consider discontinuing elk feedgrounds while simultaneously developing new methods to mitigate the financial impact to ranchers of possible brucellosis transmission to livestock. More generally, our methods can be used to weigh the costs and benefits of human-wildlife interactions in the presence of multiple disease risks.

The Economic Case for a Pandemic Fund.

The rapid urban spread of Ebola virus in West Africa in 2014 and consequent breakdown of control measures led to a significant economic impact as well as the burden on public health and wellbeing. The US government appropriated $5.4 Billion for FY2015 and WHO proposed a $100 Million emergency fund largely to curtail the threat of future outbreaks. Using epidemiological analyses and economic modeling, we propose that the best use of these and similar funds would be to serve as global insurance against the continued threat of emerging infectious diseases. An effective strategy would involve the initial investment in strengthening mobile and adaptable capacity to deal with the threat and reality of disease emergence, coupled with repeated investment to maintain what is effectively a 'national guard' for pandemic prevention and response. This investment would create a capital stock that could also provide access to safe treatment during and between crises in developing countries, lowering risk to developed countries.

Managing Wildlife Faced with Pathogen Risks Involving Multi-Stable Outcomes.

Most models designed to understand how to manage infected wildlife systems with bioeconomic multi-stability take the initial conditions as given, thereby treating pathogen invasion as unanticipated. We examine how ex ante management is an opportunity to influence the ex post conditions, which in turn affect the ex post optimal outcome. To capture these ex ante management choices, we extend the Poisson "collapse" model of Reed and Heras (Bull Math Biol 54:185-207, 1992) to allow for endogenous initial conditions and ex post multi-stability. We account for two uncertain processes: the introduction and establishment of the pathogen. Introduction is conditional on anthropogenic investments in prevention, and both random processes are conditional on how we manage the native population to provide natural prevention of invasion and natural insurance against establishment placing the system in an undesirable basin of attraction. We find that both multi-stability of the invaded system and these uncertainty processes can create economic non-convexities that yield multiple candidate solutions to the ex ante optimization problem. Additionally, we illustrate how the nature of natural protection against introduction and establishment risks can play an important role in the allocation of anthropogenic investments.

Impacts of Pathogen Introduction Risk on Importer Behavior and Gains from Trade in the Livestock Industry.

Trade eliminates geographic barriers, allowing for novel exchange of goods and services, but also creates pathways for the unintentional spread of infectious pathogens such as foot and mouth disease. In the absence of trade regulation, a producer's choice of import origin depends on relative prices and costs associated with trading partners. This paper develops a framework for exploring importer behavior in a non-regulated economy, allowing for price and risk heterogeneity among potential import sources. In the model, importers determine the risk of introducing foot and mouth disease to home soil and choose import volumes using risk and market data. When importers consider the possibility of unreported or undetected outbreaks, they choose to import from multiple sources to minimize risk and simultaneously create gains from trade over the regulated outcome. Our results have implications for the development of import and inspection policies that could be specifically designed to target highest risk imports of livestock.

Cross-jurisdictional management of a trophy-hunted species.

Gray wolves (Canis lupus) are managed for competing uses in the Greater Yellowstone Ecosystem (GYE). Tourism benefits Yellowstone National Park (YNP) visitors while trophy hunting benefits hunters outside of the park. We investigate the policy scope of gray wolf management across jurisdictional boundaries by incorporating three foundations of the behavioral ecology of wolves: refuge-seeking behavior, optimal foraging group size and territoriality. Tradeoffs between and within consumptive and non-consumptive human benefits and wolf population fitness and life history indicators are quantified as a set of elasticities, providing clear implications to resource managers. Our approach highlights that hunting intensity affects the provision of consumptive and non-consumptive human benefits across jurisdictional boundaries and ought to be managed accordingly. We also show that population levels are an incomplete indicator of species fitness, which may depend on how hunting policies impact underlying group ecology. Our findings suggest traditional optimization approaches to wildlife management may lead to suboptimal policy recommendations when the boundaries on the natural system are oversimplified. Highlighting the human element of wildlife management, we show that understanding tourist and hunter responses to wildlife population abundances is critical to balancing provision of consumptive and non-consumptive human uses.

Managing dynamic epidemiological risks through trade.

There is growing concern that trade, by connecting geographically isolated regions, unintentionally facilitates the spread of invasive pathogens and pests - forms of biological pollution that pose significant risks to ecosystem and human health. We use a bioeconomic framework to examine whether trade always increases private risks, focusing specifically on pathogen risks from live animal trade. When the pathogens have already established and traders bear some private risk, we find two results that run counter to the conventional wisdom on trade. First, uncertainty about the disease status of individual animals held in inventory may increase the incentives to trade relative to the disease-free case. Second, trade may facilitate reduced long-run disease prevalence among buyers. These results arise because disease risks are endogenous due to dynamic feedback processes involving valuable inventories, and markets facilitate the management of private risks that producers face with or without trade.

Managing the Endogenous Risk of Disease Outbreaks with Non-Constant Background Risk.

There is a growing concern that risks of disease outbreak and pandemics are increasing over time. We consider optimal investments in prevention before an outbreak using an endogenous risk approach within an optimal control setting. Using the threat of pandemic influenza as an illustrative example, we demonstrate that prevention expenditures are relatively small in comparison to the potential losses facing the USA, and these expenditures need to be flexible and responsive to changes in background risk. Failure to adjust these expenditures to changes in background risk poses a significant threat to social welfare into the future.

Economic optimization of a global strategy to address the pandemic threat.

Emerging pandemics threaten global health and economies and are increasing in frequency. Globally coordinated strategies to combat pandemics, similar to current strategies that address climate change, are largely adaptive, in that they attempt to reduce the impact of a pathogen after it has emerged. However, like climate change, mitigation strategies have been developed that include programs to reduce the underlying drivers of pandemics, particularly animal-to-human disease transmission. Here, we use real options economic modeling of current globally coordinated adaptation strategies for pandemic prevention. We show that they would be optimally implemented within 27 y to reduce the annual rise of emerging infectious disease events by 50% at an estimated one-time cost of approximately $343.7 billion. We then analyze World Bank data on multilateral "One Health" pandemic mitigation programs. We find that, because most pandemics have animal origins, mitigation is a more cost-effective policy than business-as-usual adaptation programs, saving between $344.0.7 billion and $360.3 billion over the next 100 y if implemented today. We conclude that globally coordinated pandemic prevention policies need to be enacted urgently to be optimally effective and that strategies to mitigate pandemics by reducing the impact of their underlying drivers are likely to be more effective than business as usual.

Complementarity in the provision of ecosystem services reduces the cost of mitigating amplified natural disturbance events.

Climate change has been implicated as a root cause of the recent surge in natural disturbance events such as storms, wildfires, and insect outbreaks. This climate-based surge has led to a greater focus on disturbance-mitigating benefits of ecosystem management. Quantifying these benefits requires knowledge of the relationship between natural and anthropogenic disturbances, which is lacking at the temporal and spatial scales needed to inform ecosystem-based management. This study investigates a specific relationship between timber harvesting and climate-amplified outbreaks of mountain pine beetle. If harvesting is located to mitigate long-distance insect dispersal, there is potential for a win-win outcome in which both timber production and forest conservation can be increased. This spatially targeted harvesting strategy lowers the cost of providing disturbance-mitigating ecosystem services, because valuable timber products are also produced. Mitigating long-distance dispersal also produces net gains in forest conservation across various stakeholder groups. These results speak to ongoing federal efforts to encourage forest vegetation removal on public forestlands to improve forest health. These efforts will lower the cost of responding to climate-amplified natural disturbance events but only if vegetation removal efforts are spatially located to reduce disturbance risk. Otherwise, efforts to improve forest health may be converting forest conservation services to timber services.

Merging economics and epidemiology to improve the prediction and management of infectious disease.

Mathematical epidemiology, one of the oldest and richest areas in mathematical biology, has significantly enhanced our understanding of how pathogens emerge, evolve, and spread. Classical epidemiological models, the standard for predicting and managing the spread of infectious disease, assume that contacts between susceptible and infectious individuals depend on their relative frequency in the population. The behavioral factors that underpin contact rates are not generally addressed. There is, however, an emerging a class of models that addresses the feedbacks between infectious disease dynamics and the behavioral decisions driving host contact. Referred to as "economic epidemiology" or "epidemiological economics," the approach explores the determinants of decisions about the number and type of contacts made by individuals, using insights and methods from economics. We show how the approach has the potential both to improve predictions of the course of infectious disease, and to support development of novel approaches to infectious disease management.