Modeling Uncertainties in Workforce Disruptions from Influenza Pandemics Using Dynamic Input‐Output Analysis

Influenza pandemic is a serious disaster that can pose significant disruptions to the workforce and associated economic sectors. This article examines the impact of influenza pandemic on workforce availability within an interdependent set of economic sectors. We introduce a simulation model based on the dynamic input‐output model to capture the propagation of pandemic consequences through the National Capital Region (NCR). The analysis conducted in this article is based on the 2009 H1N1 pandemic data. Two metrics were used to assess the impacts of the influenza pandemic on the economic sectors: (i) inoperability, which measures the percentage gap between the as‐planned output and the actual output of a sector, and (ii) economic loss, which quantifies the associated monetary value of the degraded output. The inoperability and economic loss metrics generate two different rankings of the critical economic sectors. Results show that most of the critical sectors in terms of inoperability are sectors that are related to hospitals and health‐care providers. On the other hand, most of the sectors that are critically ranked in terms of economic loss are sectors with significant total production outputs in the NCR such as federal government agencies. Therefore, policy recommendations relating to potential mitigation and recovery strategies should take into account the balance between the inoperability and economic loss metrics.     

Risk‐Based Input‐Output Analysis of Influenza Epidemic Consequences on Interdependent Workforce Sectors

Outbreaks of contagious diseases underscore the ever‐looming threat of new epidemics. Compared to other disasters that inflict physical damage to infrastructure systems, epidemics can have more devastating and prolonged impacts on the population. This article investigates the interdependent economic and productivity risks resulting from epidemic‐induced workforce absenteeism. In particular, we develop a dynamic input‐output model capable of generating sector‐disaggregated economic losses based on different magnitudes of workforce disruptions. An ex post analysis of the 2009 H1N1 pandemic in the national capital region (NCR) reveals the distribution of consequences across different economic sectors. Consequences are categorized into two metrics: (i) economic loss, which measures the magnitude of monetary losses incurred in each sector, and (ii) inoperability, which measures the normalized monetary losses incurred in each sector relative to the total economic output of that sector. For a simulated mild pandemic scenario in NCR, two distinct rankings are generated using the economic loss and inoperability metrics. Results indicate that the majority of the critical sectors ranked according to the economic loss metric comprise of sectors that contribute the most to the NCR's gross domestic product (e.g., federal government enterprises). In contrast, the majority of the critical sectors generated by the inoperability metric include sectors that are involved with epidemic management (e.g., hospitals). Hence, prioritizing sectors for recovery necessitates consideration of the balance between economic loss, inoperability, and other objectives. Although applied specifically to the NCR, the proposed methodology can be customized for other regions.     

International Trade Inoperability Input-Output Model (IT-IIM): Theory and Application

The inoperability input-output model (IIM) has been used for analyzing disruptions due to man-made or natural disasters that can adversely affect the operation of economic systems or critical infrastructures. Taking economic perturbation for each sector as inputs, the IIM provides the degree of economic production impacts on all industry sectors as the outputs for the model. The current version of the IIM does not provide a separate analysis for the international trade component of the inoperability. If an important port of entry (e.g., Port of Los Angeles) is disrupted, then international trade inoperability becomes a highly relevant subject for analysis. To complement the current IIM, this article develops the International Trade-IIM (IT-IIM). The IT-IIM investigates the resulting international trade inoperability for all industry sectors resulting from disruptions to a major port of entry. Similar to traditional IIM analysis, the inoperability metrics that the IT-IIM provides can be used to prioritize economic sectors based on the losses they could potentially incur. The IT-IIM is used to analyze two types of direct perturbations: (1) the reduced capacity of ports of entry, including harbors and airports (e.g., a shutdown of any port of entry); and (2) restrictions on commercial goods that foreign countries trade with the base nation (e.g., embargo).     

Multiobjective Prioritization Methodology and Decision Support System for Evaluating Inventory Enhancement Strategies for Disrupted Interdependent Sectors

Disruptions in the production of commodities and services resulting from disasters influence the vital functions of infrastructure and economic sectors within a region. The interdependencies inherent among these sectors trigger the faster propagation of disaster consequences that are often associated with a wider range of inoperability and amplified losses. This article evaluates the impact of inventory‐enhanced policies for disrupted interdependent sectors to improve the disaster preparedness capability of dynamic inoperability input‐output models (DIIM). In this article, we develop the dynamic cross‐prioritization plot (DCPP)—a prioritization methodology capable of identifying and dynamically updating the critical sectors based on preference assignments to different objectives. The DCPP integrates the risk assessment metrics (e.g., economic loss and inoperability), which are independently analyzed in the DIIM. We develop a computer‐based DCPP tool to determine the priority for inventory enhancement with user preference and resource availability as new dimensions. A baseline inventory case for the state of Virginia revealed a high concentration of (i) manufacturing sectors under the inoperability objective and (ii) service sectors under the economic loss objective. Simulation of enhanced inventory policies for selected critical manufacturing sectors has reduced the recovery period by approximately four days and the expected total economic loss by $33 million. Although the article focuses on enhancing inventory levels in manufacturing sectors, complementary analysis is recommended to manage the resilience of the service sectors. The flexibility of the proposed DCPP as a decision support tool can also be extended to accommodate analysis in other regions and disaster scenarios.     

A Risk‐Based Approach for Identifying Key Economic and Infrastructure Systems

This article introduces approaches for identifying key interdependent infrastructure sectors based on the inventory dynamic inoperability input‐output model, which integrates an inventory model and a risk‐based interdependency model. An identification of such key sectors narrows a policymaker's focus on sectors providing most impact and receiving most impact from inventory‐caused delays in inoperability resulting from disruptive events. A case study illustrates the practical insights of the key sector approaches derived from a value of workforce‐centered production inoperability from Bureau of Economic Analysis data.     

基于ITIM模型的政治争端事件对产业经济系统的影响评估

本文在考虑事件恢复期的情景下,扩展了Jung^[7]的针对进出口国际贸易的非正常投入产出模型。将2012年中日"钓鱼岛事件"视为一类政治争端事件,在几个假设前提下,评估该事件给中国的产业经济系统带来的间接经济损失,并筛选出对该事件较为敏感的产业。结果表明:"钓鱼岛事件"严重影响了中日贸易,2012年中日进出口贸易总额同比减少134.3716亿美元,考虑到产业经济系统内部的技术经济关联性,估算出"钓鱼岛事件"带来的静态间接经济损失区间为;然后假设"钓鱼岛事件"在1年、2年、3年、5年、10年和15年内得以解决,分别计算了该事件带来的间接经济损失区间;筛选出了"钓鱼岛事件"的高敏感行业:通用、专用设备制造业、电气机械及器材制造业、化学工业、金属冶炼及压延加工业和金属制品业等。最后提出了相应的政策建议。本文的研究方法可为类似事件的损失评估提供借鉴,研究结果可为政府、行业管理部门和相关企业提供参考。     

A Framework for Linking Cybersecurity Metrics to the Modeling of Macroeconomic Interdependencies

Hierarchical decision making is a multidimensional process involving management of multiple objectives (with associated metrics and tradeoffs in terms of costs, benefits, and risks), which span various levels of a large-scale system. The nation is a hierarchical system as it consists multiple classes of decisionmakers and stakeholders ranging from national policymakers to operators of specific critical infrastructure subsystems. Critical infrastructures (e.g., transportation, telecommunications, power, banking, etc.) are highly complex and interconnected. These interconnections take the form of flows of information, shared security, and physical flows of commodities, among others. In recent years, economic and infrastructure sectors have become increasingly dependent on networked information systems for efficient operations and timely delivery of products and services. In order to ensure the stability, sustainability, and operability of our critical economic and infrastructure sectors, it is imperative to understand their inherent physical and economic linkages, in addition to their cyber interdependencies. An interdependency model based on a transformation of the Leontief input-output (I-O) model can be used for modeling: (1) the steady-state economic effects triggered by a consumption shift in a given sector (or set of sectors); and (2) the resulting ripple effects to other sectors. The inoperability metric is calculated for each sector; this is achieved by converting the economic impact (typically in monetary units) into a percentage value relative to the size of the sector. Disruptive events such as terrorist attacks, natural disasters, and large-scale accidents have historically shown cascading effects on both consumption and production. Hence, a dynamic model extension is necessary to demonstrate the interplay between combined demand and supply effects. The result is a foundational framework for modeling cybersecurity scenarios for the oil and gas sector. A hypothetical case study examines a cyber attack that causes a 5-week shortfall in the crude oil supply in the Gulf Coast area.     

An Adaptive Regional Input-Output Model and its Application to the Assessment of the Economic Cost of Katrina

This article proposes a new modeling framework to investigate the consequences of natural disasters and the following reconstruction phase. Based on input-output tables, its originalities are (1) the taking into account of sector production capacities and of both forward and backward propagations within the economic system; and (2) the introduction of adaptive behaviors. The model is used to simulate the response of the economy of Louisiana to the landfall of Katrina. The model is found consistent with available data, and provides two important insights. First, economic processes exacerbate direct losses, and total costs are estimated at $149 billion, for direct losses equal to $107 billion. When exploring the impacts of other possible disasters, it is found that total losses due to a disaster affecting Louisiana increase nonlinearly with respect to direct losses when the latter exceed $50 billion. When direct losses exceed $200 billion, for instance, total losses are twice as large as direct losses. For risk management, therefore, direct losses are insufficient measures of disaster consequences. Second, positive and negative backward propagation mechanisms are essential for the assessment of disaster consequences, and the taking into account of production capacities is necessary to avoid overestimating the positive effects of reconstruction. A systematic sensitivity analysis shows that, among all parameters, the overproduction capacity in the construction sector and the adaptation characteristic time are the most important.     

Total Economic Consequences of an Influenza Outbreak in the United States

Pandemic influenza represents a serious threat not only to the population of the United States, but also to its economy. In this study, we analyze the total economic consequences of potential influenza outbreaks in the United States for four cases based on the distinctions between disease severity and the presence/absence of vaccinations. The analysis is based on data and parameters on influenza obtained from the Centers for Disease Control and the general literature. A state‐of‐the‐art economic impact modeling approach, computable general equilibrium, is applied to analyze a wide range of potential impacts stemming from the outbreaks. This study examines the economic impacts from changes in medical expenditures and workforce participation, and also takes into consideration different types of avoidance behavior and resilience actions not previously fully studied. Our results indicate that, in the absence of avoidance and resilience effects, a pandemic influenza outbreak could result in a loss in U.S. GDP of $25.4 billion, but that vaccination could reduce the losses to $19.9 billion. When behavioral and resilience factors are taken into account, a pandemic influenza outbreak could result in GDP losses of $45.3 billion without vaccination and $34.4 billion with vaccination. These results indicate the importance of including a broader set of causal factors to achieve more accurate estimates of the total economic impacts of not just pandemic influenza but biothreats in general. The results also highlight a number of actionable items that government policymakers and public health officials can use to help reduce potential economic losses from the outbreaks.     

实施建筑节能标准的宏观经济和环境影响测算模型研究

本文首先对实施建筑节能标准的主要经济和环境影响方面进行系统分析,然后对投入产出局部闭模型进行了改进,并结合数量经济和静态比较的方法,创建了实施建筑节能标准的宏观经济和环境影响测算模型。该模型可以从6个主要方面详细测算实施建筑节能标准对各个产业部门的直接经济影响、直接环境影响、完全经济影响和对GDP的总影响。模型测算结果表明,建筑节能的节能和减排效果显著,同时对GDP有小幅的拉动作用,随着建筑节能标准实施率的增加,它对GDP的拉动强度呈先增后减的趋势。最后根据对测算结果的分析,提出推广实施建筑节能标准的具体方法建议。     

Computational Comparison Studies of Quadratic Assignment Like Formulations for the In Silico Sequence Selection Problem in De Novo Protein Design

In this paper an O(n²) mathematical formulation for in silico sequence selection in de novo protein design proposed by Klepeis et al. (2003, 2004), in which the number of additional variables and linear constraints scales with the square of the number of binary variables, is compared to three O(n) formulations. It is found that the O(n²) formulation is superior to the O(n) formulations on most sequence search spaces. The superiority of the O(n²) formulation is due to the reformulation linearization techniques (RLTs), since the O(n²) formulation without RLTs is found to be computationally less efficient than the O(n) formulations. In addition, new algorithmic enhancing components of RLTs with inequality constraints, triangle inequalities, and Dead-End Elimination (DEE) type preprocessing are added to the O(n²) formulation. The current best O(n²) formulation, which is the original formulation from Klepeis et al. (2003, 2004) plus DEE type preprocessing, is proposed for in silico sequence search. For a test problem with a search space of 3.4×10⁴⁵ sequences, this new improved model is able to reduce the required CPU time by 67%.     

On the Local Sensitivity Analysis of the Inoperability Input‐Output Model

Natural and man‐made disasters are currently a source of major concern for contemporary societies. In order to understand their economic impacts, the inoperability input‐output model has recently gained recognition among scholars. In a recent paper, Percoco (2006) has proposed an extension of the model to map the technologically most important sectors through so‐called fields of influence. In the present note we aim to show that this importance measure also has a clear connection with local sensitivity analysis theory.     

Largest area convex hull of imprecise data based on axis-aligned squares

In recent years, more and more algorithms related to imprecise data have been proposed. Specifically, some algorithms on computing the maximum area convex hull are designed recently when the imprecise data are modeled as non-overlapping axis-aligned squares or as equal size squares. The time complexity of the best known algorithm based on non-overlapping axis-aligned squares is O(n ⁷). If the squares have equal size and can overlap, the time complexity of the best known algorithm is O(n ⁵). In this paper, we improve the former from O(n ⁷) to O(n ⁵) and improve the latter from O(n ⁵) to O(n ²). These results are obtained by exploiting the non-trivial geometric properties of the problems.     

The Management of Redundancies in Europe: The Case of Great Britain

The paper presents the findings of a comparative and interdisciplinary legal and economic study on managing labour redundancies in seven EU member countries. It is structured for immediate comparability between the systems examined. The introductory section contains an account of the evolution of the British labour market, with special reference to redundancy trends, the features of the programmes for managing redundancies, the roles of firms and the ‘external environment’ in handling workforce adjustments. The second section presents a map of policies that work to prevent labour redundancies (preventive measures) such as flexibility, training etc. Next, the instruments for handling temporary labour redundancies (retentive measures) are examined (e.g. short-time working, temporary layoffs etc.). The following section is devoted to instruments and programmes involved in the management of permanent labour redundancies (expulsive measures), e.g. collective dismissals, severance pay etc. The final section provides an overall assessment of the British system for managing labour redundancies, and briefly discusses the national debate on the prospects for reform, in light of the principles and policies of convergence set forth by the European Union.     

The Management of Redundancies in Europe: The Case of Spain

The paper presents the findings of a comparative and interdisciplinary legal and economic study on managing labour redundancies in seven EU member countries. It is structured for comparability between the systems examined. The introductory section contains an account of the evolution of the Spanish labour market, with special reference to redundancy trends, of the features of the programmes for managing redundancies, of the roles of forms and the ‘external environment’ in handling workforce adjustments. The second section presents a map of policies that work to prevent labour redundancies (preventive measures) such as flexibility, training etc. Next, the instruments for handling temporary labour redundancies (retentive measures) are examined (e.g. short-time working, temporary layoffs etc.) The following section is devoted to instruments and programmes involved in the management of permanent labour redundancies (expulsive measures), e.g. collective dismissals, severance pay etc. The final section provides and overall assessment of the Spanish system for managing labour redundancies, and briefly discusses the national debate on the prospects for reform, in light of the principles and policies of convergence set forth by the European Union.     

The Management of Redundancies in Europe: The Case of Denmark

The paper presents the findings of comparative and interdisciplinary legal and economic study on managing labour redundancies in seven EU member countries. It is structured for comparability between the systems examined. The introductory section contains an account of the evolution of the Danish labour market, with special reference to redundancy trends, of the features of the programmes for managing redundancies, of the roles of firms and the ‘external environment’ in handling workforce adjustments. The second section presents a map of policies that work to prevent labour redundancies (preventive measures) such as flexibility, training etc. Next, the instruments for handling temporary labour redundancies (retentive measures) are examined (e.g. short-time working, temporary layoffs etc.). The following section is devoted to instruments and programmes involved in the management of permanent labour redundancies (expulsive measures), e.g. collective dismissals, severance pay etc. The final section provides an overall assessment of the Danish system for managing labour redundancies, and briefly discusses the national debate on the prospects for reform, in light of the principles and policies of convergence set forth by the European Union.     

Evaluation of the Productivity Decrease Risk Due to a Future Increase in Tropical Cyclone Intensity in Japan

A number of scientists have recently conducted research that shows that tropical cyclone intensity is likely to increase in the future. This would result in an increase in the damage along with a decrease in economic productivity due to precautionary cessation of the economic activity of the affected areas during the passage of the cyclone. The economic effect of this stop in economic activity is a phenomenon that has not received much attention in the past, and the cumulative effect that it can have on the Japanese economy over the next 75 years has never been evaluated. The starting point for the evaluation of the economic risks is the change in the patterns of tropical cyclone intensity suggested by Knutson and Tuleya.⁽ 1 ⁾ The results obtained show how a significant decrease in the overall productivity of the country could be expected, which could lower GDP by between 6% and 13% by 2085.     

The Management of Redundancies in Europe: The Case of the Netherlands

The paper presents the findings of comparative and interdisciplinary legal and economic study on managing labour redundancies in seven EU member countries. It is structured for comparability between the systems examined. The introductory section contains an account of the evolution of the Dutch labour market, with special reference to redundancy trends, of the features of the programmes for managing redundancies, of the roles of firms and the ‘external environment’ in handling workforce adjustments. The second section presents a map of policies that work to prevent labour redundancies (preventive measures) such as flexibility, training etc. Next, the instruments for handling temporary labour redundancies (retentive measures) are examined (e.g. short-time working, temporary layoffs etc.). The following section is devoted to instruments and programmes involved in the management of permanent labour redundancies (expulsive measures), e.g. collective dismissals, severance pay etc. The final section provides an overall assessment of the Dutch system for managing labour redundancies, and briefly discusses the national debate on the prospects for reform, in light of the principles and policies of convergence set forth by the European Union.     

Risk of Fetal Mortality After Exposure to Listeria monocytogenes Based on Dose-Response Data from Pregnant Guinea Pigs and Primates

One‐third of the annual cases of listeriosis in the United States occur during pregnancy and can lead to miscarriage or stillbirth, premature delivery, or infection of the newborn. Previous risk assessments completed by the Food and Drug Administration/the Food Safety Inspection Service of the U.S. Department of Agriculture/the Centers for Disease Control and Prevention (FDA/USDA/CDC)^{( 1 )} and Food and Agricultural Organization/the World Health Organization (FAO/WHO)^{( 2 )} were based on dose‐response data from mice. Recent animal studies using nonhuman primates^{( 3 , 4 )} and guinea pigs^{( 5 )} have both estimated LD₅₀s of approximately 10⁷ Listeria monocytogenes colony forming units (cfu). The FAO/WHO^{( 2 )} estimated a human LD₅₀ of 1.9 × 10⁶ cfu based on data from a pregnant woman consuming contaminated soft cheese. We reevaluated risk based on dose‐response curves from pregnant rhesus monkeys and guinea pigs. Using standard risk assessment methodology including hazard identification, exposure assessment, hazard characterization, and risk characterization, risk was calculated based on the new dose‐response information. To compare models, we looked at mortality rate per serving at predicted doses ranging from 10^?4 to 10¹² L. monocytogenes cfu. Based on a serving of 10⁶ L. monocytogenes cfu, the primate model predicts a death rate of 5.9 × 10^?1 compared to the FDA/USDA/CDC (fig. IV‐12)^{( 1 )} predicted rate of 1.3 × 10^?7. Based on the guinea pig and primate models, the mortality rate calculated by the FDA/USDA/CDC^{( 1 )} is underestimated for this susceptible population.     

The Management of Redundancies in Europe: The Case of Germany

The paper presents the findings of comparative and interdisciplinary legal and economic study on managing labour redundancies in seven EU member countries. It is structured for immediate comparability between the systems examined. The introductory section contains an account of the evolution of the German labour market, with special reference to redundancy trends, of the features of the programmes for managing redundancies, of the roles of firms and the ‘external environment’ in handling workforce adjustments. The second section presents a map of policies that work to prevent labour redundancies (preventive measures) such as flexibility, training etc. Next, the instruments for handling temporary labour redundancies (retentive measures) are examined (e.g. short-time working, temporary layoffs etc.). The following section is devoted to instruments and programmes involved in the management of permanent labour redundancies (expulsive measures), e.g. collective dismissals, severance pay etc. The final section provides an overall assessment of the German system for managing labour redundancies, and briefly discusses the national debate on the prospects for reform, in light of the principles and policies of convergence set forth by the European Commission.