Increased #frequency of #travel in the presence of cross-immunity may act to decrease the #chance of a #global #pandemic (Philos Transact Roy Soc B., abstract)

[Source: US National Library of Medicine, full page: (LINK). Abstract, edited.]

Philos Trans R Soc Lond B Biol Sci. 2019 Jun 24;374(1775):20180274. doi: 10.1098/rstb.2018.0274.

Increased frequency of travel in the presence of cross-immunity may act to decrease the chance of a global pandemic.

Thompson RN1,2,3, Thompson CP2, Pelerman O4, Gupta S2, Obolski U2,5,6.

Author information: 1 Mathematical Institute, University of Oxford , Andrew Wiles Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG , UK. 2 Department of Zoology, University of Oxford , South Parks Road, Oxford OX1 3PS , UK.
3 Christ Church, University of Oxford , St Aldate’s, Oxford OX1 1DP , UK. 4 The Chaim Rosenberg School of Jewish Studies, Tel Aviv University , Tel Aviv 69978 , Israel. 5 School of Public Health , Tel Aviv University, Tel Aviv , Israel. 6 Porter School of the Environment and Earth Sciences, Tel Aviv University , Israel.

 

Abstract

The high frequency of modern travel has led to concerns about a devastating pandemic since a lethal pathogen strain could spread worldwide quickly. Many historical pandemics have arisen following pathogen evolution to a more virulent form. However, some pathogen strains invoke immune responses that provide partial cross-immunity against infection with related strains. Here, we consider a mathematical model of successive outbreaks of two strains-a low virulence (LV) strain outbreak followed by a high virulence (HV) strain outbreak. Under these circumstances, we investigate the impacts of varying travel rates and cross-immunity on the probability that a major epidemic of the HV strain occurs, and the size of that outbreak. Frequent travel between subpopulations can lead to widespread immunity to the HV strain, driven by exposure to the LV strain. As a result, major epidemics of the HV strain are less likely, and can potentially be smaller, with more connected subpopulations. Cross-immunity may be a factor contributing to the absence of a global pandemic as severe as the 1918 influenza pandemic in the century since. This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’. This issue is linked with the subsequent theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’.

KEYWORDS: antigenic variation; cross-immunity; major epidemic; mathematical modelling; pathogen diversity

PMID: 31056047 DOI: 10.1098/rstb.2018.0274

Keywords: Emerging diseases; Infectious Diseases; Pandemic Influenza, Mathematical models.

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One #model to rule them all? Modelling #approaches across #OneHealth for #human, #animal and #plant #epidemics (Philos Transact Roy Soc B., abstract)

[Source: US National Library of Medicine, full page: (LINK). Abstract, edited.]

Philos Trans R Soc Lond B Biol Sci. 2019 Jun 24;374(1775):20180255. doi: 10.1098/rstb.2018.0255.

One model to rule them all? Modelling approaches across OneHealth for human, animal and plant epidemics.

Kleczkowski A1, Hoyle A2, McMenemy P2.

Author information: 1 Department of Mathematics and Statistics, University of Strathclyde , Glasgow G1 1XH , UK. 2 Computing Science and Mathematics, University of Stirling , Stirling FK9 4LA , UK.

 

Abstract

One hundred years after the 1918 influenza outbreak, are we ready for the next pandemic? This paper addresses the need to identify and develop collaborative, interdisciplinary and cross-sectoral approaches to modelling of infectious diseases including the fields of not only human and veterinary medicine, but also plant epidemiology. Firstly, the paper explains the concepts on which the most common epidemiological modelling approaches are based, namely the division of a host population into susceptible, infected and removed (SIR) classes and the proportionality of the infection rate to the size of the susceptible and infected populations. It then demonstrates how these simple concepts have been developed into a vast and successful modelling framework that has been used in predicting and controlling disease outbreaks for over 100 years. Secondly, it considers the compartmental models based on the SIR paradigm within the broader concept of a ‘disease tetrahedron’ (comprising host, pathogen, environment and man) and uses it to review the similarities and differences among the fields comprising the ‘OneHealth’ approach. Finally, the paper advocates interactions between all fields and explores the future challenges facing modellers. This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’. This issue is linked with the subsequent theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’.

KEYWORDS: OneHealth; bio-economic models; compartmental models; epidemiological data; infectious disease; plant pathogens

PMID: 31056049 DOI: 10.1098/rstb.2018.0255

Keywords: Infectious Diseases; Emerging Diseases; Pandemic Influenza; Mathematical models.

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#Detection, #forecasting and #control of #infectious #disease #epidemics: modelling #outbreaks in #humans, #animals and #plants (Philos Transact Roy Soc B., abstract)

[Source: US National Library of Medicine, full page: (LINK). Abstract, edited.]

Philos Trans R Soc Lond B Biol Sci. 2019 Jun 24;374(1775):20190038. doi: 10.1098/rstb.2019.0038.

Detection, forecasting and control of infectious disease epidemics: modelling outbreaks in humans, animals and plants.

Thompson RN1,2,3, Brooks-Pollock E4,5.

Author information: 1 Mathematical Institute, University of Oxford , Andrew Wiles Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG , UK. 2 Department of Zoology, University of Oxford , Peter Medawar Building, South Parks Road, Oxford OX1 3SY , UK. 3 Christ Church, University of Oxford , St Aldates, Oxford OX1 1DP , UK. 4 Bristol Veterinary School, University of Bristol , Langford BS40 5DU , UK. 5 National Institute for Health Research, Health Protection Research Unit in Evaluation of Interventions, Bristol Medical School , Bristol BS8 2BN , UK.

 

Abstract

The 1918 influenza pandemic is one of the most devastating infectious disease epidemics on record, having caused approximately 50 million deaths worldwide. Control measures, including prohibiting non-essential gatherings as well as closing cinemas and music halls, were applied with varying success and limited knowledge of transmission dynamics. One hundred years later, following developments in the field of mathematical epidemiology, models are increasingly used to guide decision-making and devise appropriate interventions that mitigate the impacts of epidemics. Epidemiological models have been used as decision-making tools during outbreaks in human, animal and plant populations. However, as the subject has developed, human, animal and plant disease modelling have diverged. Approaches have been developed independently for pathogens of each host type, often despite similarities between the models used in these complementary fields. With the increased importance of a One Health approach that unifies human, animal and plant health, we argue that more inter-disciplinary collaboration would enhance each of the related disciplines. This pair of theme issues presents research articles written by human, animal and plant disease modellers. In this introductory article, we compare the questions pertinent to, and approaches used by, epidemiological modellers of human, animal and plant pathogens, and summarize the articles in these theme issues. We encourage future collaboration that transcends disciplinary boundaries and links the closely related areas of human, animal and plant disease epidemic modelling. This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’. This issue is linked with the subsequent theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’.

KEYWORDS: animal disease; human disease; mathematical modelling; one health; plant disease; public health

PMID: 31056051 DOI: 10.1098/rstb.2019.0038

Keywords: Infectious Diseases; Emerging Diseases; Pandemic Influenza; Mathematical models.

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Towards high quality RT #WGS during #outbreaks using #Usutu virus as example (Infect Genet Evol., abstract)

[Source: US National Library of Medicine, full page: (LINK). Abstract, edited.]

Infect Genet Evol. 2019 Apr 20. pii: S1567-1348(19)30056-5. doi: 10.1016/j.meegid.2019.04.015. [Epub ahead of print]

Towards high quality real-time whole genome sequencing during outbreaks using Usutu virus as example.

Oude Munnink BB1, Kik M2, de Bruijn ND3, Kohl R1, van der Linden A1, Reusken CBEM1, Koopmans M4.

Author information: 1 ErasmusMC, Department of Viroscience, WHO Collaborating Centre for Arbovirus and Viral Hemorrhagic Fever Reference and Research, Rotterdam, the Netherlands. 2 Veterinary Pathology Centre, University of Utrecht, the Netherlands. 3 GD Animal Health, Deventer, the Netherlands. 4 ErasmusMC, Department of Viroscience, WHO Collaborating Centre for Arbovirus and Viral Hemorrhagic Fever Reference and Research, Rotterdam, the Netherlands. Electronic address: m.koopmans@erasmusmc.nl.

 

Abstract

Recently, protocols for amplicon based whole genome sequencing using Nanopore technology have been described for Ebola virus, Zika virus, yellow fever virus and West Nile virus. However, there is some debate regarding reliability of sequencing using this technology, which is important for applications beyond diagnosis such as linking lineages to outbreaks, tracking transmission pathways and pockets of circulation, or mapping specific markers. To our knowledge, no in depth analyses of the required read coverage to compensate for the error profile in Nanopore sequencing have been described. Here, we describe the validation of a protocol for whole genome sequencing of USUV using Nanopore sequencing by direct comparison to Illumina sequencing. To that point we selected brain tissue samples with high viral loads, typical for birds which died from USUV infection. We conclude that the low-cost MinION Nanopore sequencing platform can be used for characterization and tracking of Usutu virus outbreaks.

Copyright © 2018. Published by Elsevier B.V.

KEYWORDS: Arboviruses; Nanopore; Sequencing; USUV

PMID: 31014969 DOI: 10.1016/j.meegid.2019.04.015

Keywords: Emerging diseases; Infectious Diseases; Diagnostic tests; Usutu virus.

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Emerging #Infectious #Diseases and #Antimicrobial #Resistance (#EIDAR) (Mil Med., abstract)

[Source: US National Library of Medicine, full page: (LINK). Abstract, edited.]

Mil Med. 2019 Apr 20. pii: usz081. doi: 10.1093/milmed/usz081. [Epub ahead of print]

Emerging Infectious Diseases and Antimicrobial Resistance (EIDAR).

Lanteri C1, Mende K1,2,3, Kortepeter M4,5.

Author information: 1 Infectious Disease Clinical Research Program, Preventive Medicine and Biostatistics Department, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Road, Bethesda, MD 20814. 2 Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., 6720A Rockledge Drive, Bethesda, MD 20817. 3 Brooke Army Military Center, 3551 Roger Brooke Drive, JBSA Fort Sam Houston, TX 78234. 4 University of Nebraska Medical Center College of Public Health, 984355 Medical Center, Omaha, NB 68198. 5 Departments of Medicine and Preventive Medicine, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Road Bethesda, MD 20814.

 

Abstract

INTRODUCTION:

The Infectious Disease Clinical Research Program’s (IDCRP) Emerging Infectious Diseases and Antimicrobial Resistance (EIDAR) Research Area is a Department of Defense (DoD) clinical research capability that is responsive and adaptive to emerging infectious disease (EID) threats to US military readiness. Among active-duty and other Military Health System (MHS) beneficiaries, EIDAR research is largely focused on evaluating the incidence, risk factors, and acute- and long-term health effects of military-relevant EIDs, especially those caused by high-consequence pathogens or are responsible for outbreaks among US military populations. The EIDAR efforts also address Force Health Protection concerns associated with antimicrobial resistance and antimicrobial stewardship practices within the MHS.

METHODS:

The EIDAR studies utilize the approach of: (1) Preparing for emergent conditions to systematically collect clinical specimens and data and conduct clinical trials to assist the military with a scientifically appropriate response; and (2) Evaluating burden of emergent military-relevant infectious diseases and assessing risks for exposure and development of post-infectious complications and overall impact on military readiness.

RESULTS:

In response to the Ebola virus epidemic in West Africa, the IDCRP partnered with the National Institutes of Health in developing a multicenter, randomized safety and efficacy study of investigational therapeutics in Ebola patients. Subsequently, the EIDAR team developed a protocol to serve as a contingency plan (EpICC-EID) to allow clinical research activities to occur during future outbreaks of viral hemorrhagic fever and severe acute respiratory infections among MHS patients. The EIDAR portfolio recently expanded to include studies to understand exposure risks and impact on military readiness for a diversity of EIDs, such as seroincidence of non-Lyme disease borreliosis and Coccidioides fungal infections among high-risk military populations. The team also launched a new prospective study in response to the recent Zika epidemic to conduct surveillance for Zika and other related viruses among MHS beneficiaries in Puerto Rico. Another new study will prospectively follow U.S. Marines via an online health assessment survey to assess long-term health effects following the largest DoD Shiga Toxin-Producing Escherichia coli outbreak at the U.S. Marine Corps Recruit Depot-San Diego. In cooperation with the Trauma-Related Infections Research Area, the EIDAR Research Area is also involved with the Multidrug-Resistant and Virulent Organisms Trauma Infections Initiative, which is a collaborative effort across DoD laboratories to characterize bacterial and fungal isolates infecting combat-related extremity wounds and link lab findings to clinical outcomes. Furthermore, the EIDAR team has developed an Antimicrobial Resistance and Stewardship Collaborative Clinical Research Consortium, comprised of Infectious Disease and Pharmacy specialists.

CONCLUSIONS:

The EIDAR Research Area is responsive to military-relevant infectious disease threats that are also frequently global public health concerns. Several new EIDAR efforts are underway that will provide Combatant Command Surgeons, Infectious Diseases Service Chiefs, and other Force Health Protection stakeholders with epidemiological information to mitigate the impact of EIDs and antimicrobial resistance on the health of U.S. military service members and their dependents.

Published by Oxford University Press on behalf of the Association of Military Surgeons of the United States 2019. This work is written by (a) US Government employee(s) and is in the public domain in the US.

KEYWORDS: emerging infectious diseases; multidrug resistance

PMID: 31004432 DOI: 10.1093/milmed/usz081

Keywords: Infectious Diseases; Emerging Diseases; USA; Military Health Services.

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#Infectious Disease #Threats in the 21rst Century: Strengthening the #Global #Response (Front Immunol., abstract)

[Source: US National Library of Medicine, full page: (LINK). Abstract, edited.]

Front Immunol. 2019 Mar 28;10:549. doi: 10.3389/fimmu.2019.00549. eCollection 2019.

Infectious Disease Threats in the Twenty-First Century: Strengthening the Global Response.

Bloom DE1, Cadarette D1.

Author information: 1 Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA, United States.

 

Abstract

The world has developed an elaborate global health system as a bulwark against known and unknown infectious disease threats. The system consists of various formal and informal networks of organizations that serve different stakeholders; have varying goals, modalities, resources, and accountability; operate at different regional levels (i.e., local, national, regional, or global); and cut across the public, private-for-profit, and private-not-for-profit sectors. The evolving global health system has done much to protect and promote human health. However, the world continues to be confronted by longstanding, emerging, and reemerging infectious disease threats. These threats differ widely in terms of severity and probability. They also have varying consequences for morbidity and mortality, as well as for a complex set of social and economic outcomes. To various degrees, they are also amenable to alternative responses, ranging from clean water provision to regulation to biomedical countermeasures. Whether the global health system as currently constituted can provide effective protection against a dynamic array of infectious disease threats has been called into question by recent outbreaks of Ebola, Zika, dengue, Middle East respiratory syndrome, severe acute respiratory syndrome, and influenza and by the looming threat of rising antimicrobial resistance. The concern is magnified by rapid population growth in areas with weak health systems, urbanization, globalization, climate change, civil conflict, and the changing nature of pathogen transmission between human and animal populations. There is also potential for human-originated outbreaks emanating from laboratory accidents or intentional biological attacks. This paper discusses these issues, along with the need for a (possibly self-standing) multi-disciplinary Global Technical Council on Infectious Disease Threats to address emerging global challenges with regard to infectious disease and associated social and economic risks. This Council would strengthen the global health system by improving collaboration and coordination across organizations (e.g., the WHO, Gavi, CEPI, national centers for disease control, pharmaceutical manufacturers, etc.); filling in knowledge gaps with respect to (for example) infectious disease surveillance, research and development needs, financing models, supply chain logistics, and the social and economic impacts of potential threats; and making high-level, evidence-based recommendations for managing global risks associated with infectious disease.

KEYWORDS: antimicrobial resistance (AMR); epidemic; global health; global health systems; infectious disease; outbreak; pandemic; pandemic preparedness and response

PMID: 30984169 PMCID: PMC6447676 DOI: 10.3389/fimmu.2019.00549

Keywords: Infectious Diseases; Emerging Diseases; Global Health.

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#Policy and #Science for #GlobalHealth #Security: Shaping the Course of #International Health (Trop Med Infect Dis., abstract)

[Source: US National Library of Medicine, full page: (LINK). Abstract, edited.]

Trop Med Infect Dis. 2019 Apr 10;4(2). pii: E60. doi: 10.3390/tropicalmed4020060.

Policy and Science for Global Health Security: Shaping the Course of International Health.

Berger KM1, Wood JLN2, Jenkins B3,4, Olsen J5, Morse SS6, Gresham L7, Root JJ8, Rush M9, Pigott D10,11, Winkleman T12, Moore M13, Gillespie TR14,15, Nuzzo JB16, Han BA17, Olinger P18, Karesh WB19, Mills JN20, Annelli JF21, Barnabei J22, Lucey D23, Hayman DTS24.

Author information: 1 Gryphon Scientific, LLC, 6930 Carroll Avenue, Suite 810, Takoma Park, MD 20912, USA. kberger@gryphonscientific.com. 2 Disease Dynamics Unit, Department of Veterinary Medicine, University of Cambridge, Madingley Road, Cambridge CB3 0ES, UK. jlnw2@cam.ac.uk. 3 Brookings Institution, 1775 Massachusetts Avenue NW, Washington, DC 20036, USA. bonniedjenkins@gmail.com. 4 Women of Color Advancing Peace, Security and Conflict Transformation, 3695 Ketchum Court, Woodbridge, VA 22193, USA. bonniedjenkins@gmail.com. 5 Rosalynn Carter Institute for Caregiving, Georgia Southwestern State University, 800 GSW State University Drive, Americus, GA 31709, USA. jenolsen.drph@gmail.com. 6 Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 West 168th St., New York, NY 10032, USA. ssm20@cumc.columbia.edu. 7 Ending Pandemics and San Diego State University, San Diego, CA 92182, USA. lgresham@sdsu.edu. 8 U.S. Department of Agriculture, National Wildlife Research Center, Fort Collins, CO 80521, USA. Jeff.Root@aphis.usda.gov. 9 Gryphon Scientific, LLC, 6930 Carroll Avenue, Suite 810, Takoma Park, MD 20912, USA. margaret@gryphonscientific.com. 10 Institute for Health Metrics and Evaluation, Department of Health Metrics Sciences, University of Washington, 2301 Fifth Avenue, Suite 600, Seattle, WA 98121, USA. pigottdm@uw.edu. 11 Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK. pigottdm@uw.edu. 12 Next Generation Global Health Security Network, Washington, DC 20001, USA. t.winkleman.dvm@gmail.com. 13 RAND Corporation, 1200 South Hayes St., Arlington, VA 22202, USA. 14 Population Biology, Ecology, and Evolution Program, Emory University, Atlanta, GA 30322, USA. thomas.gillespie@emory.edu. 15 Department of Environmental Health, Rollins School of Public Health, 1518 Clifton Road, Atlanta, GA 30322, USA. thomas.gillespie@emory.edu. 16 Center for Health Security, Johns Hopkins University School of Public Health, Pratt Street, Baltimore, MD 21202, USA. jnuzzo1@jhu.edu. 17 Cary Institute of Ecosystem Studies, Box AB Millbrook, NY 12545, USA. hanb@caryinstitute.org. 18 Environmental, Health and Safety Office (EHSO), Emory University, 1762 Clifton Rd., Suite 1200, Atlanta, GA 30322, USA. patty.olinger@emory.edu. 19 EcoHealth Alliance, 460 West 34th Street, New York, NY 10001, USA. karesh@ecohealthalliance.org. 20 Population Biology, Ecology, and Evolution Program, Emory University, Atlanta, GA 30322, USA. wildlifedisease@gmail.com. 21 Practical One Health Solutions, LLC, New Market, MD 21774, USA. pohsolutions@gmail.com. 22 Plum Island Animal Disease Center, Department of Homeland Security, Greenport, NY 11944, USA. jbarnabei87@gmail.com. 23 Department of Medicine Infectious Disease, Georgetown University, 600 New Jersey Avenue, NW Washington, DC 20001, USA. daniel.lucey8@gmail.com. 24 EpiLab, Infectious Disease Research Centre, School of Veterinary Science, Massey University, Private Bag, 11 222, Palmerston North 4442, New Zealand. d.t.s.hayman@massey.ac.nz.

 

Abstract

The global burden of infectious diseases and the increased attention to natural, accidental, and deliberate biological threats has resulted in significant investment in infectious disease research. Translating the results of these studies to inform prevention, detection, and response efforts often can be challenging, especially if prior relationships and communications have not been established with decision-makers. Whatever scientific information is shared with decision-makers before, during, and after public health emergencies is highly dependent on the individuals or organizations who are communicating with policy-makers. This article briefly describes the landscape of stakeholders involved in information-sharing before and during emergencies. We identify critical gaps in translation of scientific expertise and results, and biosafety and biosecurity measures to public health policy and practice with a focus on One Health and zoonotic diseases. Finally, we conclude by exploring ways of improving communication and funding, both of which help to address the identified gaps. By leveraging existing scientific information (from both the natural and social sciences) in the public health decision-making process, large-scale outbreaks may be averted even in low-income countries.

KEYWORDS: Ebola virus; One Health; emerging infectious diseases; zoonoses

PMID: 30974815 DOI: 10.3390/tropicalmed4020060

Keywords: Global Health; Infectious Diseases; Emerging Diseases; Pandemic Preparedness.

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