Beyond Ebola: lessons to mitigate future pandemics

Castillo‐Chavez, Carlos; Curtiss, Roy; Daszak, Peter; Levin, Simon A.; Patterson-Lomba, Oscar; Perrings, Charles; Poste, George; Towers, Sherry

doi:10.1016/s2214-109x(15)00068-6

Cited by 48 publications

(45 citation statements)

References 11 publications

(14 reference statements)

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“…Global security is threated from pandemics, in terms of lives and economic stability (Maurice, 2016). Pandemics are no longer simply the domain of public health and clinical medicine, but are a social issue, a development issue, and a global security issue (Castillo-Chavez et al, 2015). The commission on a Global Health Risk Framework for the Future (GHRF) published a book at the beginning of 2016 under the title: "The Neglected Dimension of Global Security -A Framework to Counter Infectious Diseases Crises".…”

Section: Security Impactsmentioning

confidence: 99%

The Pandemic and its Impacts

Qiu

Rutherford

Mao

et al. 2017

hcs

216

132

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The Pandemic has a long history, but the term itself is yet to be defined by many medical texts. There have been a number of significant pandemics recorded in human history where pandemic related crises have caused enormous negative impacts on health, economies, and even national security globally. This article will explore the literature for the concept and history of pandemics, providing a summary of key features with consequent discussion on the negative impacts on health, economy, social and global security yielded by pandemics and disease outbreaks.

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Section: Security Impactsmentioning

confidence: 99%

The Pandemic and its Impacts

Qiu

Rutherford

Mao

et al. 2017

hcs

216

132

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“…This, in turn, facilitates disease transmissions within herds and between livestock and humans by increasing livestock population and density [3]. Therefore, the potential emergence of zoonoses from livestock population should not be underestimated [13,14]. In 2003, there was an outbreak of a highly pathogenic avian influenza A subtype H7N7 in humans linked to multiple commercial poultry farms in the Netherlands [15].…”

Section: Introductionmentioning

confidence: 99%

Virus Metagenomics in Farm Animals: A Systematic Review

Kwok

Nieuwenhuijse

Phan

et al. 2020

Viruses

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A majority of emerging infectious diseases are of zoonotic origin. Metagenomic Next-Generation Sequencing (mNGS) has been employed to identify uncommon and novel infectious etiologies and characterize virus diversity in human, animal, and environmental samples. Here, we systematically reviewed studies that performed viral mNGS in common livestock (cattle, small ruminants, poultry, and pigs). We identified 2481 records and 120 records were ultimately included after a first and second screening. Pigs were the most frequently studied livestock and the virus diversity found in samples from poultry was the highest. Known animal viruses, zoonotic viruses, and novel viruses were reported in available literature, demonstrating the capacity of mNGS to identify both known and novel viruses. However, the coverage of metagenomic studies was patchy, with few data on the virome of small ruminants and respiratory virome of studied livestock. Essential metadata such as age of livestock and farm types were rarely mentioned in available literature, and only 10.8% of the datasets were publicly available. Developing a deeper understanding of livestock virome is crucial for detection of potential zoonotic and animal pathogens and One Health preparedness. Metagenomic studies can provide this background but only when combined with essential metadata and following the "FAIR" (Findable, Accessible, Interoperable, and Reusable) data principles.Viruses 2020, 12, 107 2 of 22 flocks and wild birds, suggesting that pre-existing biosecurity measurements could not keep up with the rate of livestock intensification [16]. In 2007-2010, a large-scale Q fever outbreak was reported in the Netherlands, affecting more than 3500 human cases and resulting in a huge economic loss [17,18]. A steep increase in the number of goat farms most likely was the driver for the increased prevalence of Coxiella burnetii infections, with animal abortion waves that had gone unnoticed. The policy of voluntary reporting abortion outbreaks to the Animal Health Service hindered the timely detection of the circulation of Q fever, and therefore early interventions. These examples indicate that zoonotic risks in the livestock industry should be carefully managed and adapted to livestock intensification. The One Health approach has been coined for advocating collaboration between multiple stakeholders including veterinarians, clinicians, epidemiologists, virologists, microbiologists, ecologists, and policy makers to prevent and control EIDs through the human-animal-environment interface [19]. Surveillance of livestock and the surrounding environment is a hallmark of early detection but is currently targeted to known risks.Advances in Next-Generation Sequencing (NGS) technologies and rapid development of bioinformatics and computational tools offer new opportunities for EID surveillance in quality and in scale. Particularly, metagenomic NGS (mNGS) allows unbiased detection of all microbes and viruses in a sample, showing potential for timely detection of rare or novel infectio...

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“…L essons learned from the HIV pandemic, 2003 severe acute respiratory syndrome (SARS) epidemic, the 2009 H1N1 influenza pandemic, the 2014 Ebola outbreak in West Africa, and the ongoing Zika outbreaks in the Americas can be framed under a public health policy model that responds after the fact, most often via the reallocation of resources from one disease control effort to the new pressing one. The operating models of preparedness and response are ill-equipped to prevent or ameliorate disease emergence or reemergence, at global scales (1). Epidemiological challenges that are a threat to the economic stability of many regions of the world, particularly those depending on travel and trade (2), remain at the forefront of the Global Commons.…”

mentioning

confidence: 99%

“…Our experience with an H1N1 influenza pandemic crisscrossing the world in the months during 2009 to 2010; the 2014 Ebola outbreaks, limited to regions of West Africa lacking appropriate medical facilities, health infrastructure, and sufficient levels of preparedness and education; and the expanding Zika outbreaks, moving expeditiously across suitable habitats to Aedes aegypti, provide opportunities to quantify the impact of disease emergence or reemergence on the decisions that individuals take in response to real or perceived disease risks (5)(6)(7). The case of SARS 2003 (8), the efforts to reduce the burden of H1N1 influenza cases in 2009 (5,7,9,10), and the challenges faced in reducing the number of Ebola cases in 2014 (1,11) are but three recent scenarios that required a timely global response. Studies addressing the impact of centralized sources of information (12), the impact of information along social connections (9,13,14), or the role of past disease outbreak experiences (15,16) on the risk-aversion decisions that individuals undertake may help identify and quantify the role of human responses to disease dynamics while recognizing the importance of assessing the timing of disease emergence and reemergence; the coevolving human responses to disease dynamics are prototypical of the feedbacks that define complex adaptive systems.…”

mentioning

confidence: 99%

Perspectives on the role of mobility, behavior, and time scales in the spread of diseases

Castillo‐Chavez

Bichara

Morin

2016

Proc. Natl. Acad. Sci. U.S.A.

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The dynamics, control, and evolution of communicable and vectorborne diseases are intimately connected to the joint dynamics of epidemiological, behavioral, and mobility processes that operate across multiple spatial, temporal, and organizational scales. The identification of a theoretical explanatory framework that accounts for the pattern regularity exhibited by a large number of host-parasite systems, including those sustained by host-vector epidemiological dynamics, is but one of the challenges facing the coevolving fields of computational, evolutionary, and theoretical epidemiology. Host-parasite epidemiological patterns, including epidemic outbreaks and endemic recurrent dynamics, are characteristic to well-identified regions of the world; the result of processes and constraints such as strain competition, host and vector mobility, and population structure operating over multiple scales in response to recurrent disturbances (like El Niño) and climatological and environmental perturbations over thousands of years. It is therefore important to identify and quantify the processes responsible for observed epidemiological macroscopic patterns: the result of individual interactions in changing social and ecological landscapes. In this perspective, we touch on some of the issues calling for the identification of an encompassing theoretical explanatory framework by identifying some of the limitations of existing theory, in the context of particular epidemiological systems. Fostering the reenergizing of research that aims at disentangling the role of epidemiological and socioeconomic forces on disease dynamics, better understood as complex adaptive systems, is a key aim of this perspective.infectious disease | risk | complex adaptive systems | mobility | behavior

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Beyond Ebola: lessons to mitigate future pandemics

Cited by 48 publications

References 11 publications

The Pandemic and its Impacts

The Pandemic and its Impacts

Virus Metagenomics in Farm Animals: A Systematic Review

Perspectives on the role of mobility, behavior, and time scales in the spread of diseases

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