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.

The costs and benefits of primary prevention of zoonotic pandemics.

The lives lost and economic costs of viral zoonotic pandemics have steadily increased over the past century. Prominent policymakers have promoted plans that argue the best ways to address future pandemic catastrophes should entail, "detecting and containing emerging zoonotic threats." In other words, we should take actions only after humans get sick. We sharply disagree. Humans have extensive contact with wildlife known to harbor vast numbers of viruses, many of which have not yet spilled into humans. We compute the annualized damages from emerging viral zoonoses. We explore three practical actions to minimize the impact of future pandemics: better surveillance of pathogen spillover and development of global databases of virus genomics and serology, better management of wildlife trade, and substantial reduction of deforestation. We find that these primary pandemic prevention actions cost less than 1/20th the value of lives lost each year to emerging viral zoonoses and have substantial cobenefits.

Wild animal and zoonotic disease risk management and regulation in China: Examining gaps and One Health opportunities in scope, mandates, and monitoring systems.

Emerging diseases of zoonotic origin such as COVID-19 are a continuing public health threat in China that lead to a significant socioeconomic burden. This study reviewed the current laws and regulations, government reports and policy documents, and existing literature on zoonotic disease preparedness and prevention across the forestry, agriculture, and public health authorities in China, to articulate the current landscape of potential risks, existing mandates, and gaps. A total of 55 known zoonotic diseases (59 pathogens) are routinely monitored under a multi-sectoral system among humans and domestic and wild animals in China. These diseases have been detected in wild mammals, birds, reptiles, amphibians, and fish or other aquatic animals, the majority of which are transmitted between humans and animals via direct or indirect contact and vectors. However, this current monitoring system covers a limited scope of disease threats and animal host species, warranting expanded review for sources of disease and pathogen with zoonotic potential. In addition, the governance of wild animal protection and utilization and limited knowledge about wild animal trade value chains present challenges for zoonotic disease risk assessment and monitoring, and affect the completeness of mandates and enforcement. A coordinated and collaborative mechanism among different departments is required for the effective monitoring and management of disease emergence and transmission risks in the animal value chains. Moreover, pathogen surveillance among wild animal hosts and human populations outside of the routine monitoring system will fill the data gaps and improve our understanding of future emerging zoonotic threats to achieve disease prevention. The findings and recommendations will advance One Health collaboration across government and non-government stakeholders to optimize monitoring and surveillance, risk management, and emergency responses to known and novel zoonotic threats, and support COVID-19 recovery efforts.

A COVID-19 Risk Assessment for the US Labor Force.

The consequences of COVID-19 infection varies substantially based on individual social risk factors and predisposing health conditions. Understanding this variability may be critical for targeting COVID-19 control measures, resources and policies, including efforts to return people back to the workplace. We compiled individual level data from the National Health Information Survey and Quarterly Census of Earnings and Wages to estimate the number of at-risk workers for each US county and industry, accounting for both social and health risks. Nearly 80% of all workers have at least one health risk and 11% are over 60 with an additional health risk. We document important variation in the at-risk population across states, counties, and industries that could provide a strategic underpinning to a staged return to work.

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.

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.

Economic growth, urbanization, globalization, and the risks of emerging infectious diseases in China: A review.

Three interrelated world trends may be exacerbating emerging zoonotic risks: income growth, urbanization, and globalization. Income growth is associated with rising animal protein consumption in developing countries, which increases the conversion of wild lands to livestock production, and hence the probability of zoonotic emergence. Urbanization implies the greater concentration and connectedness of people, which increases the speed at which new infections are spread. Globalization-the closer integration of the world economy-has facilitated pathogen spread among countries through the growth of trade and travel. High-risk areas for the emergence and spread of infectious disease are where these three trends intersect with predisposing socioecological conditions including the presence of wild disease reservoirs, agricultural practices that increase contact between wildlife and livestock, and cultural practices that increase contact between humans, wildlife, and livestock. Such an intersection occurs in China, which has been a "cradle" of zoonoses from the Black Death to avian influenza and SARS. Disease management in China is thus critical to the mitigation of global zoonotic risks.

Evolutionary Dynamics and Global Diversity of Influenza A Virus.

UNLABELLED: The increasing number of zoonotic infections caused by influenza A virus (IAV) subtypes of avian origin (e.g., H5N1 and H7N9) in recent years underscores the need to better understand the factors driving IAV evolution and diversity. To evaluate the current feasibility of global analyses to contribute to this aim, we evaluated information in the public domain to explore IAV evolutionary dynamics, including nucleotide substitution rates and selection pressures, using 14 IAV subtypes in 32 different countries over a 12-year period (2000 to 2011). Using geospatial information from 39,785 IAV strains, we examined associations between subtype diversity and socioeconomic, biodiversity, and agricultural indices. Our analyses showed that nucleotide substitution rates for 11 of the 14 evaluated subtypes tended to be higher in Asian countries, particularly in East Asia, than in Canada and the United States. Similarly, at a regional level, subtypes H5N1, H5N2, and H6N2 exhibited significantly higher substitution rates in East Asia than in North America. In contrast, the selection pressures (measured as ratios of nonsynonymous to synonymous evolutionary changes [dN/dS ratios]) acting on individual subtypes showed little geographic variation. We found that the strongest predictors for the detected subtype diversity at the country level were reporting effort (i.e., total number of strains reported) and health care spending (an indicator of economic development). Our analyses also identified major global gaps in IAV reporting (including a lack of sequences submitted from large portions of Africa and South America and a lack of geolocation information) and in broad subtype testing which, until addressed, will continue to hinder efforts to track the evolution and diversity of IAV around the world. IMPORTANCE: In recent years, an increasing number of influenza A virus (IAV) subtypes, including H5N1, H7N9, and H10N8, have been detected in humans. High fatality rates have led to an increased urgency to better understand where and how novel pathogenic influenza virus strains emerge. Our findings showed that mutational rates of 11 commonly encountered subtypes were higher in East Asian countries than in North America, suggesting that there may be a greater risk for the emergence of novel pathogenic strains in East Asia. In assessing the potential drivers of IAV subtype diversity, our analyses confirmed that reporting effort and health care spending were the best predictors of the observed subtype diversity at the country level. These findings underscore the need to increase sampling and reporting efforts for all subtypes in many undersampled countries throughout the world.

Global avian influenza surveillance in wild birds: a strategy to capture viral diversity.

Wild birds play a major role in the evolution, maintenance, and spread of avian influenza viruses. However, surveillance for these viruses in wild birds is sporadic, geographically biased, and often limited to the last outbreak virus. To identify opportunities to optimize wild bird surveillance for understanding viral diversity, we reviewed responses to a World Organisation for Animal Health-administered survey, government reports to this organization, articles on Web of Knowledge, and the Influenza Research Database. At least 119 countries conducted avian influenza virus surveillance in wild birds during 2008-2013, but coordination and standardization was lacking among surveillance efforts, and most focused on limited subsets of influenza viruses. Given high financial and public health burdens of recent avian influenza outbreaks, we call for sustained, cost-effective investments in locations with high avian influenza diversity in wild birds and efforts to promote standardized sampling, testing, and reporting methods, including full-genome sequencing and sharing of isolates with the scientific community.

Integrating invasion and disease in the risk assessment of live bird trade.

AIM: International trade in plants and animals generates significant economic benefits. It also leads to substantial unintended impacts when introduced species become invasive, causing environmental disturbance or transmitting diseases that affect people, livestock, other wildlife or the environment. Policy responses are usually only implemented after these species become established and damages are already incurred. International agreements to control trade are likewise usually based on selection of species with known impacts. We aim to further develop quantitative invasive species risk assessment for bird imports and extend the tool to explicitly address disease threats. LOCATION: United States of America. METHODS: We use a two-step approach for rapid risk assessment based on the expected biological risks due to both the environmental and health impact of a potentially invasive wildlife species in trade. We assess establishment probability based on a model informed by historical observations and then construct a model of emerging infectious disease threat based on economic and ecological characteristics of the exporting country. RESULTS: We illustrate how our rapid assessment tool can be used to identify high-priority species for regulation based on a combination of the threat they pose for becoming established and vectoring emerging infectious diseases. MAIN CONCLUSIONS: Our approach can be executed for a species in a matter of days and is nested in an economic decision-making framework for determining whether the biological risk is justified by trade benefits.

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.

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.

A strategy to estimate unknown viral diversity in mammals.

UNLABELLED: The majority of emerging zoonoses originate in wildlife, and many are caused by viruses. However, there are no rigorous estimates of total viral diversity (here termed "virodiversity") for any wildlife species, despite the utility of this to future surveillance and control of emerging zoonoses. In this case study, we repeatedly sampled a mammalian wildlife host known to harbor emerging zoonotic pathogens (the Indian Flying Fox, Pteropus giganteus) and used PCR with degenerate viral family-level primers to discover and analyze the occurrence patterns of 55 viruses from nine viral families. We then adapted statistical techniques used to estimate biodiversity in vertebrates and plants and estimated the total viral richness of these nine families in P. giganteus to be 58 viruses. Our analyses demonstrate proof-of-concept of a strategy for estimating viral richness and provide the first statistically supported estimate of the number of undiscovered viruses in a mammalian host. We used a simple extrapolation to estimate that there are a minimum of 320,000 mammalian viruses awaiting discovery within these nine families, assuming all species harbor a similar number of viruses, with minimal turnover between host species. We estimate the cost of discovering these viruses to be ~$6.3 billion (or ~$1.4 billion for 85% of the total diversity), which if annualized over a 10-year study time frame would represent a small fraction of the cost of many pandemic zoonoses. IMPORTANCE: Recent years have seen a dramatic increase in viral discovery efforts. However, most lack rigorous systematic design, which limits our ability to understand viral diversity and its ecological drivers and reduces their value to public health intervention. Here, we present a new framework for the discovery of novel viruses in wildlife and use it to make the first-ever estimate of the number of viruses that exist in a mammalian host. As pathogens continue to emerge from wildlife, this estimate allows us to put preliminary bounds around the potential size of the total zoonotic pool and facilitates a better understanding of where best to allocate resources for the subsequent discovery of global viral diversity.

Quantifying trends in disease impact to produce a consistent and reproducible definition of an emerging infectious disease.

The proper allocation of public health resources for research and control requires quantification of both a disease's current burden and the trend in its impact. Infectious diseases that have been labeled as "emerging infectious diseases" (EIDs) have received heightened scientific and public attention and resources. However, the label 'emerging' is rarely backed by quantitative analysis and is often used subjectively. This can lead to over-allocation of resources to diseases that are incorrectly labelled "emerging," and insufficient allocation of resources to diseases for which evidence of an increasing or high sustained impact is strong. We suggest a simple quantitative approach, segmented regression, to characterize the trends and emergence of diseases. Segmented regression identifies one or more trends in a time series and determines the most statistically parsimonious split(s) (or joinpoints) in the time series. These joinpoints in the time series indicate time points when a change in trend occurred and may identify periods in which drivers of disease impact change. We illustrate the method by analyzing temporal patterns in incidence data for twelve diseases. This approach provides a way to classify a disease as currently emerging, re-emerging, receding, or stable based on temporal trends, as well as to pinpoint the time when the change in these trends happened. We argue that quantitative approaches to defining emergence based on the trend in impact of a disease can, with appropriate context, be used to prioritize resources for research and control. Implementing this more rigorous definition of an EID will require buy-in and enforcement from scientists, policy makers, peer reviewers and journal editors, but has the potential to improve resource allocation for global health.

Pathogens, pests, and economics: drivers of honey bee colony declines and losses.

The Western honey bee (Apis mellifera) is responsible for ecosystem services (pollination) worth US$215 billion annually worldwide and the number of managed colonies has increased 45% since 1961. However, in Europe and the U.S., two distinct phenomena; long-term declines in colony numbers and increasing annual colony losses, have led to significant interest in their causes and environmental implications. The most important drivers of a long-term decline in colony numbers appear to be socioeconomic and political pressure on honey production. In contrast, annual colony losses seem to be driven mainly by the spread of introduced pathogens and pests, and management problems due to a long-term intensification of production and the transition from large numbers of small apiaries to fewer, larger operations. We conclude that, while other causal hypotheses have received substantial interest, the role of pests, pathogens, and management issues requires increased attention.