Understanding the Economics of Microbial Threats Proceedings of a Workshop (2018) / Chapter Skim
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4 The Economics and Modeling of Emerging Infectious Diseases and Biological Risks
4 The Economics and Modeling of Emerging Infectious Diseases and Biological Risks
Pages 29-46
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From page 29... ...
Carlos Castillo-Chavez, professor of mathematical biology at Arizona State University, then presented on an epidemiological-economic model that explicitly incorporates human behavioral responses influenced by infectious disease outbreaks. Thomas Inglesby, director of the Center for Health Security of the Johns Hopkins Bloomberg School of Public Health, concluded the session with a presentation on infections that have the potential to cause significant harm to the global economy and international security.
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. Economic Modeling for Influenza Pandemic Meltzer highlighted the potential for economic modeling to guide preparedness efforts against pandemic influenza, as it can provide information that can be useful when planning for rationing, shortages, and prioritization of interventions during an epidemic.
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health care system to use additional mechanical ventilators during a large-scale public health emergency," Disaster Medicine and Public Health Preparedness, volume 9, issue 6, pages 634–641, reproduced with permission.
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ASSESSING ECONOMIC VULNERABILITY TO EMERGING INFECTIOUS DISEASE OUTBREAKS Anas El Turabi, Frank Knox fellow in health policy at Harvard University, stated that economic analysis can take two forms: the "snow-globe" approach and the "empiricist" approach. The snow-globe method attempts to build mathematical models of the world in its current state, which are then "shaken" to hypothesize the consequence of a given scenario.
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According to El Turabi, this economic impact, particularly from social responses, is often the forgotten dimension of analysis related to emerging outbreaks. El Turabi noted that different factors might affect a country's economic vulnerability to an infectious disease event.
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The difference in fear induced by the visible hemorrhagic condition of Ebola versus apathy from the flulike symptoms or neurological complications experienced with Zika is a key qualitative factor in comparing the two diseases, he said. El Turabi noted that the different characteristics of Ebola and Zika explain the different behavioral responses and economic impacts generated by these diseases.
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Finally, El Turabi concluded that better postevent analysis and data collection are needed to calibrate and refine predictive models. EPIDEMIC RISK MODELING: MEASURING THE EFFECT OF AVERSION BEHAVIOR AND CASCADING SOCIAL RESPONSES Carlos Castillo-Chavez, professor of mathematical biology at Arizona State University, presented on epidemic risk models that incorporate human behavioral responses.
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. According to Castillo-Chavez, accounting for human behavior is challenging when modeling a complex adaptive system of human disease dynamics,3 as the model must consider human decision making, disease transmission, and disease prevalence (see Figure 4-3)
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He noted that unlike traditional nonlinear contact models, this model focuses on trade-offs not based explicitly on the basic reproductive number of the disease, R0.5 To Castillo-Chavez, R0 implicitly includes disease-free behavior and confounds biological aspects of the pathogen with social aspects of adaptive human response to disease risk; thus, it may not reliably guide postoutbreak disease management. Castillo-Chavez highlighted how the results of this model reveal that adaptive human behavior can have a significant effect on disease dynamics (see Figure 4-4)
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The solid curve represents the results of the simulation where human behavior responds to disease states. The dashed line represents an ex post analysis of an outbreak's R0 based on the SIR model.
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He added that scientists have helped drive global concern or action on other widely accepted global catastrophic risks, such as nuclear weapons, climate change, and artificial intelligence, and could see the same happening for GCBRs. A Retrospective Look at Global Catastrophic Biological Risks Inglesby provided three examples of GCBRs.
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Future Global Catastrophic Biological Risks Looking into the future, Inglesby described the characteristics of potential pandemic pathogens. Based on a poll of experts in the field, the highest risk for a future pandemic will likely be from a respiratory RNA virus, with characteristics such as segmented genome, cytoplasmic replication, small genome host size, high host viremia, and zoonotic relationships (Adalja et al., 2018)
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In her view, she noted that there was a need for the following: • Accounting for significant variability and uncertainty in pandemic preparedness planning; • Undertaking post-hoc analyses of outbreaks and investing in under standing social responses to gain a more comprehensive view on the economic consequences of outbreaks; • Explicitly incorporating adaptive human behavioral responses in economic and disease modeling as they can change the course of epidemics; and • Performing more economic analyses on GCBRs because of their potential effect on governance, international relations, and society. The discussion with the audience began with a focus on human behavioral responses to infectious disease outbreaks.
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Katharina Hauck, senior lecturer in health economics from the Imperial College London, asked Castillo-Chavez about the extent to which adaptive human behavior can reduce the threat of pandemics during the eradication and elimination stages. She noted that individuals might demand less prevention as prevalence declines, making eradication difficult.
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He also cautioned that human behaviors change quickly and modeling human behavior produces great variability, so models may not be able to provide public health officials with an estimate of an outbreak's magnitude without a great deal of variability. Castillo-Chavez also commented on Duchin's question, illustrating two examples of behavioral responses related to the contagion effect.
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He reiterated that models are not meant to provide accurate predictions of the future, but rather to describe the relationships and "levers," or potential response actions, that influence the disease and human behaviors. El Turabi highlighted methodological practice from CDC and the United Nations Children's Fund that provides near real-time opinion polling in emergency outbreak scenarios for making decisions in the field.
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ECONOMICS AND MODELING OF EMERGING INFECTIOUS DISEASES 45 acteristics of those receiving vaccination. School closure analysis is similarly limited by the lack of a central registry of such events at the national or even state levels, so researchers rely on social media for data.
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