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      Assessing global preparedness for the next pandemic: development and application of an Epidemic Preparedness Index

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          Abstract

          Introduction

          Robust metrics for national-level preparedness are critical for assessing global resilience to epidemic and pandemic outbreaks. However, existing preparedness assessments focus primarily on public health systems or specific legislative frameworks, and do not measure other essential capacities that enable and support public health preparedness and response.

          Methods

          We developed an Epidemic Preparedness Index (EPI) to assess national-level preparedness. The EPI is global, covering 188 countries. It consists of five subindices measuring each country’s economic resources, public health communications, infrastructure, public health systems and institutional capacity. To evaluate the construct validity of the EPI, we tested its correlation with proxy measures for preparedness and response capacity, including the timeliness of outbreak detection and reporting, as well as vaccination rates during the 2009 H1N1 influenza pandemic.

          Results

          The most prepared countries were concentrated in Europe and North America, while the least prepared countries clustered in Central and West Africa and Southeast Asia. Better prepared countries were found to report infectious disease outbreaks more quickly and to have vaccinated a larger proportion of their population during the 2009 pandemic.

          Conclusion

          The EPI measures a country’s capacity to detect and respond to infectious disease events. Existing tools, such as the Joint External Evaluation (JEE), have been designed to measure preparedness within a country over time. The EPI complements the JEE by providing a holistic view of preparedness and is constructed to support comparative risk assessment between countries. The index can be updated rapidly to generate global estimates of pandemic preparedness that can inform strategy and resource allocation.

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          Most cited references13

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          Crisis and emergency risk communication as an integrative model.

          This article describes a model of communication known as crisis and emergency risk communication (CERC). The model is outlined as a merger of many traditional notions of health and risk communication with work in crisis and disaster communication. The specific kinds of communication activities that should be called for at various stages of disaster or crisis development are outlined. Although crises are by definition uncertain, equivocal, and often chaotic situations, the CERC model is presented as a tool health communicators can use to help manage these complex events.
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            Real-time numerical forecast of global epidemic spreading: case study of 2009 A/H1N1pdm

            Background Mathematical and computational models for infectious diseases are increasingly used to support public-health decisions; however, their reliability is currently under debate. Real-time forecasts of epidemic spread using data-driven models have been hindered by the technical challenges posed by parameter estimation and validation. Data gathered for the 2009 H1N1 influenza crisis represent an unprecedented opportunity to validate real-time model predictions and define the main success criteria for different approaches. Methods We used the Global Epidemic and Mobility Model to generate stochastic simulations of epidemic spread worldwide, yielding (among other measures) the incidence and seeding events at a daily resolution for 3,362 subpopulations in 220 countries. Using a Monte Carlo Maximum Likelihood analysis, the model provided an estimate of the seasonal transmission potential during the early phase of the H1N1 pandemic and generated ensemble forecasts for the activity peaks in the northern hemisphere in the fall/winter wave. These results were validated against the real-life surveillance data collected in 48 countries, and their robustness assessed by focusing on 1) the peak timing of the pandemic; 2) the level of spatial resolution allowed by the model; and 3) the clinical attack rate and the effectiveness of the vaccine. In addition, we studied the effect of data incompleteness on the prediction reliability. Results Real-time predictions of the peak timing are found to be in good agreement with the empirical data, showing strong robustness to data that may not be accessible in real time (such as pre-exposure immunity and adherence to vaccination campaigns), but that affect the predictions for the attack rates. The timing and spatial unfolding of the pandemic are critically sensitive to the level of mobility data integrated into the model. Conclusions Our results show that large-scale models can be used to provide valuable real-time forecasts of influenza spreading, but they require high-performance computing. The quality of the forecast depends on the level of data integration, thus stressing the need for high-quality data in population-based models, and of progressive updates of validated available empirical knowledge to inform these models.
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              Environmental and social influences on emerging infectious diseases: past, present and future.

              During the processes of human population dispersal around the world over the past 50 000-100 000 years, along with associated cultural evolution and inter-population contact and conflict, there have been several major transitions in the relationships of Homo sapiens with the natural world, animate and inanimate. Each of these transitions has resulted in the emergence of new or unfamiliar infectious diseases. The three great historical transitions since the initial advent of agriculture and livestock herding, from ca. 10 000 years ago, occurred when: (i) early agrarian-based settlements enabled sylvatic enzootic microbes to make contact with Homo sapiens; (ii) early Eurasian civilizations (such as the Greek and Roman empires, China and south Asia) came into military and commercial contact, ca. 3000-2000 years ago, swapping their dominant infections; and (iii) European expansionism, over the past five centuries, caused the transoceanic spread of often lethal infectious diseases. This latter transition is best known in relation to the conquest of the Americas by Spanish conquistadores, when the inadvertent spread of measles, smallpox and influenza devastated the Amerindian populations.Today, we are living through the fourth of these great transitional periods. The contemporary spread and increased lability of various infectious diseases, new and old, reflect the combined and increasingly widespread impacts of demographic, environmental, behavioural, technological and other rapid changes in human ecology. Modern clinical medicine has, via blood transfusion, organ transplantation, and the use of hypodermic syringes, created new opportunities for microbes. These have contributed to the rising iatrogenic problems of hepatitis C, HIV/AIDS and several other viral infections. Meanwhile, the injudicious use of antibiotics has been a rare instance of human action actually increasing 'biodiversity'. Another aspect of this fourth transition is that modern hyper-hygienic living restricts microbial exposure in early life. This, in the 1950s, may have contributed to an epidemic of more serious, disabling, poliomyelitis, affecting older children than those affected in earlier, more endemic decades. As with previous human-microbe transitions, a new equilibrial state may lie ahead. However, it certainly will not entail a world free of infectious diseases. Any mature, sustainable, human ecology must come to terms with both the need for, and the needs of, the microbial species that help to make up the interdependent system of life on Earth. Humans and microbes are not "at war"; rather, both parties are engaged in amoral, self-interested, coevolutionary struggle. We need to understand better, and therefore anticipate, the dynamics of that process.
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                Author and article information

                Journal
                BMJ Glob Health
                BMJ Glob Health
                bmjgh
                bmjgh
                BMJ Global Health
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2059-7908
                2019
                29 January 2019
                : 4
                : 1
                : e001157
                Affiliations
                [1] Metabiota , San Francisco, California, USA
                Author notes
                [Correspondence to ] Dr Ben Oppenheim; boppenheim@ 123456metabiota.com
                Author information
                http://orcid.org/0000-0003-1487-3534
                Article
                bmjgh-2018-001157
                10.1136/bmjgh-2018-001157
                6352812
                30775006
                534d5928-30b8-4bf8-a6a5-6980251cbd24
                © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 06 September 2018
                : 24 November 2018
                : 03 December 2018
                Categories
                Research
                1506
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                health systems,public health,epidemics
                health systems, public health, epidemics

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