Mechanistic #Modelling of Multiple #Waves in an #Influenza #Epidemic or #Pandemic (J Theor Biol., abstract)

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

J Theor Biol. 2019 Nov 4:110070. doi: 10.1016/j.jtbi.2019.110070. [Epub ahead of print]

Mechanistic Modelling of Multiple Waves in an Influenza Epidemic or Pandemic.

Xu B1, Cai J2, He D3, Chowell G4, Xu B5.

Author information: 1 Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China; Joint Center for Global Change Studies, Beijing 100875, China. Electronic address: xu-b15@mails.tsinghua.edu.cn. 2 Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China; Joint Center for Global Change Studies, Beijing 100875, China. Electronic address: cai-j12@mails.tsinghua.edu.cn. 3 Department of Applied Mathematics, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong (SAR), China. Electronic address: daihai.he@polyu.edu.hk. 4 Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia 30303, United States; Division of Inwternational Epidemiology and Population Studies, Fogarty International Center, National Institute of Health, Bethesda, Maryland 20892, United States. Electronic address: gchowell@gsu.edu. 5 Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China; Joint Center for Global Change Studies, Beijing 100875, China. Electronic address: bingxu@tsinghua.edu.cn.

 

Abstract

Multiple-wave outbreaks have been documented for influenza pandemics particularly in the temperate zone, and occasionally for seasonal influenza epidemics in the tropical zone. The mechanisms shaping multiple-wave influenza outbreaks are diverse but are yet to be summarized in a systematic fashion. For this purpose, we described 12 distinct mechanistic models, among which five models were proposed for the first time, that support two waves of infection in a single influenza season, and classified them into five categories according to heterogeneities in host, pathogen, space, time and their combinations, respectively. To quantify the number of infection waves, we proposed three metrics that provide robust and intuitive results for real epidemics. Further, we performed sensitivity analyses on key parameters in each model and found that reducing the basic reproduction number or the transmission rate, limiting the addition of susceptible people who are to get the primary infection to infected areas, and limiting the probability of replenishment of people who are to be reinfected in the short term, could decrease the number of infection waves and clinical attack rate. Finally, we introduced a modelling framework to infer the mechanisms driving two-wave outbreaks. A better understanding of two-wave mechanisms could guide public health authorities to develop and implement preparedness plans and deploy control strategies.

Copyright © 2019. Published by Elsevier Ltd.

KEYWORDS: Influenza outbreak; Mechanistic model; Modelling framework; Multiple waves; Number of infection waves

PMID: 31697940 DOI: 10.1016/j.jtbi.2019.110070

Keywords: Influenza A; Pandemic influenza; Mathematical models.

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#NewYork State #Emergency #Preparedness and Response to #Influenza #Pandemics 1918-2018 (Trop Med Infect Dis., abstract)

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

Trop Med Infect Dis. 2019 Oct 30;4(4). pii: E132. doi: 10.3390/tropicalmed4040132.

New York State Emergency Preparedness and Response to Influenza Pandemics 1918-2018.

Escuyer KL1, E Fuschino M2, St George K3.

Author information: 1 Laboratory of Viral Diseases, Wadsworth Center, New York State Department of Health, Albany, NY 12208, USA. Kay.Escuyer@health.ny.gov. 2 Laboratory of Viral Diseases, Wadsworth Center, New York State Department of Health, Albany, NY 12208, USA. Meghan.Fuschino@health.ny.gov. 3 Laboratory of Viral Diseases, Wadsworth Center, New York State Department of Health, Albany, NY 12208, USA. Kirsten.St.George@health.ny.gov.

 

Abstract

Emergency health preparedness and response efforts are a necessity in order to safeguard the public against major events, such as influenza pandemics. Since posting warnings of the epidemic influenza in 1918, to the mass media communications available a century later, state, national and global public health agencies have developed sophisticated networks, tools, detection methods, and preparedness plans. These progressive measures guide health departments and clinical providers, track patient specimens and test reports, monitor the spread of disease, and evaluate the most threatening influenza strains by means of risk assessment, to be able to respond readily to a pandemic. Surge drills and staff training were key aspects for New York State preparedness and response to the 2009 influenza pandemic, and the re-evaluation of preparedness plans is recommended to ensure readiness to address the emergence and spread of a future novel virulent influenza strain.

KEYWORDS: emergency preparedness; incident management system; influenza pandemic; just-in-time training; surge support

PMID: 31671539 DOI: 10.3390/tropicalmed4040132

Keywords: Pandemic preparedness; Pandemic Influenza; New York; USA.

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Preparing intensive care for the next #pandemic #influenza (Crit Care, abstract)

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

Crit Care. 2019 Oct 30;23(1):337. doi: 10.1186/s13054-019-2616-1.

Preparing intensive care for the next pandemic influenza.

Kain T1, Fowler R2,3.

Author information: 1 Department of Critical Care, University of Toronto, Toronto, ON, Canada. 2 Department of Critical Care, University of Toronto, Toronto, ON, Canada. rob.fowler@sunnybrook.ca. 3 Sunnybrook Health Sciences Centre, Room D478, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada. rob.fowler@sunnybrook.ca.

 

Abstract

Few viruses have shaped the course of human history more than influenza viruses. A century since the 1918-1919 Spanish influenza pandemic-the largest and deadliest influenza pandemic in recorded history-we have learned much about pandemic influenza and the origins of antigenic drift among influenza A viruses. Despite this knowledge, we remain largely underprepared for when the next major pandemic occurs.While emergency departments are likely to care for the first cases of pandemic influenza, intensive care units (ICUs) will certainly see the sickest and will likely have the most complex issues regarding resource allocation. Intensivists must therefore be prepared for the next pandemic influenza virus. Preparation requires multiple steps, including careful surveillance for new pandemics, a scalable response system to respond to surge capacity, vaccine production mechanisms, coordinated communication strategies, and stream-lined research plans for timely initiation during a pandemic. Conservative models of a large-scale influenza pandemic predict more than 170% utilization of ICU-level resources. When faced with pandemic influenza, ICUs must have a strategy for resource allocation as strain increases on the system.There are several current threats, including avian influenza A(H5N1) and A(H7N9) viruses. As humans continue to live in closer proximity to each other, travel more extensively, and interact with greater numbers of birds and livestock, the risk of emergence of the next pandemic influenza virus mounts. Now is the time to prepare and coordinate local, national, and global efforts.

KEYWORDS: Health care worker safety; Highly pathogenic avian influenza; Human; Influenza; Intensive care; Pandemic; Preparation; Research; Resource allocation; Triage

PMID: 31665057 DOI: 10.1186/s13054-019-2616-1

Keywords: Pandemic influenza; Pandemic preparedness; Intensive care.

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#Oseltamivir Is Effective against 1918 #Influenza Virus Infection of #Macaques but Vulnerable to Escape (mBio, abstract)

[Source: mBio, full page: (LINK). Abstract, edited.]

Oseltamivir Is Effective against 1918 Influenza Virus Infection of Macaques but Vulnerable to Escape

Friederike Feldmann, Darwyn Kobasa, Carissa Embury-Hyatt, Allen Grolla, Tracy Taylor, Maki Kiso, Satoshi Kakugawa, Jason Gren, Steven M. Jones, Yoshihiro Kawaoka, Heinz Feldmann

Diane E. Griffin, Editor

DOI: 10.1128/mBio.02059-19

 

ABSTRACT

The 1918 influenza virus, subtype H1N1, was the causative agent of the most devastating pandemic in the history of infectious diseases. In vitro studies have confirmed that extreme virulence is an inherent property of this virus. Here, we utilized the macaque model for evaluating the efficacy of oseltamivir phosphate against the fully reconstructed 1918 influenza virus in a highly susceptible and relevant disease model. Our findings demonstrate that oseltamivir phosphate is effective in preventing severe disease in macaques but vulnerable to virus escape through emergence of resistant mutants, especially if given in a treatment regimen. Nevertheless, we conclude that oseltamivir would be highly beneficial to reduce the morbidity and mortality rates caused by a highly pathogenic influenza virus although it would be predicted that resistance would likely emerge with sustained use of the drug.

 

IMPORTANCE

Oseltamivir phosphate is used as a first line of defense in the event of an influenza pandemic prior to vaccine administration. Treatment failure through selection and replication of drug-resistant viruses is a known complication in the field and was also demonstrated in our study with spread of resistant 1918 influenza virus in multiple respiratory tissues. This emphasizes the importance of early treatment and the possibility that noncompliance may exacerbate treatment effectiveness. It also demonstrates the importance of implementing combination therapy and vaccination strategies as soon as possible in a pandemic situation.

Keywords: Antivirals; Drugs Resistance; Oseltamivir; Animal models; H1N1; Pandemic Influenza; Spanish flu.

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Higher #frequency of #hospitalization but lower relative #mortality for #pandemic #influenza in people with type 2 #diabetes (J Intern Med., abstract)

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

J Intern Med. 2019 Oct 6. doi: 10.1111/joim.12984. [Epub ahead of print]

Higher frequency of hospitalization but lower relative mortality for pandemic influenza in people with type 2 diabetes.

Ruiz PL1,2,3, Bakken IJ4, Håberg SE4, Tapia G1, Hauge SH5, Birkeland KI3,6, Gulseth HL1,2, Stene LC1.

Author information: 1 Department of Chronic Diseases and Ageing, Norwegian Institute of Public Health, Oslo, Norway. 2 Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway. 3 Institute of Clinical Medicine, University of Oslo, Oslo, Norway. 4 Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway. 5 Department of Influenza, Norwegian Institute of Public Health, Oslo, Norway. 6 Department of Transplantation Medicine, Oslo University Hospital, Oslo, Norway.

 

Abstract

BACKGROUND:

There is limited evidence linking type 2 diabetes (T2D) to influenza-related complications.

OBJECTIVES:

To test a set of research questions relating to pandemic influenza vaccination, hospitalization and mortality in people with and without T2D.

METHODS:

In this population-based cohort study, we linked individual-level data from several national registers for all Norwegian residents aged 30 years or older as of January 2009. People with or without T2D at baseline (n=2,992,228) were followed until December 2013. We used Cox regression to estimate adjusted hazard ratios (aHRs).

RESULTS:

Pandemic influenza hospitalization was more common in individuals with T2D (aHR=2.46, 95%CI 2.04-2.98). The mortality hazard ratio associated with hospitalization for pandemic influenza was lower in people with T2D (aHR=1.82, 95%CI 1.21-2.74) than in those without T2D (aHR=3.89, 95%CI 3.27-4.62). The same pattern was observed when restricting to 90 days mortality (aHR=3.89, 95%CI 1.25-12.06 among those with T2D and aHR=10.79, 95%CI 7.23-16.10 among those without T2D). The rate of hospitalization for pandemic influenza was 78% lower in those vaccinated compared to non-vaccinated among people with T2D (aHR=0.22, 95% CI 0.11-0.39), while the corresponding estimate for those without T2D was 59% lower (aHR=0.41, 95%CI 0.33-0.52). Mortality was 25% lower in those vaccinated compared to non-vaccinated among people with T2D (aHR=0.75, 95% CI 0.73-0.77), while the corresponding estimate for those without T2D was 9% (aHR=0.91, 95%CI 0.90-0.92).

CONCLUSIONS:

There may have been a lower threshold for pandemic influenza hospitalization for people with T2D, rather than more severe influenza infection. Our combined results support the importance of influenza vaccination among people with T2D, especially during pandemics.

© 2019 The Association for the Publication of the Journal of Internal Medicine.

KEYWORDS: Diabetes Mellitus; Influenza; Mortality; Type 2; Vaccination; human

PMID: 31587396 DOI: 10.1111/joim.12984

Keywords: Pandemic Influenza; H1N1pdm09; Norway; Diabetes.

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MDCK-B4GalNT2 cells disclose a α2,3-sialic acid requirement for the 2009 #pandemic #H1N1 A/California/04/2009 and NA aid entry of A/WSN/33 (Emerg Microbes Infect., abstract)

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

Emerg Microbes Infect. 2019;8(1):1428-1437. doi: 10.1080/22221751.2019.1665971.

MDCK-B4GalNT2 cells disclose a α2,3-sialic acid requirement for the 2009 pandemic H1N1 A/California/04/2009 and NA aid entry of A/WSN/33.

Wong HH1,2, Fung K1, Nicholls JM1.

Author information: 1 Department of Pathology, University of Hong Kong , Hong Kong. 2 HKU-Pasteur Research Pole, University of Hong Kong , Hong Kong.

 

Abstract

Switching of receptor binding preference has been widely considered as one of the necessary mutations for avian influenza viruses, enabling efficient transmissions between human hosts. By stably overexpressing B4GalNT2 gene in MDCK cells, surface α2,3-siallylactose receptors were modified without affecting α2,6-receptor expression. The cell line MDCK-B4GalNT2 was used as a tool to screen for α2,3-receptor requirements in a panel of influenza viruses with previously characterized glycan array data. Infection of viruses with α2,3-receptor binding capability was inhibited in MDCK-B4GalNT2 cells, with the exception of A/WSN/33 (WSN). Infection with the 2009 pandemic H1N1 strains, A/California/04/2009 (Cal04) and A/Hong Kong/415742/2009 (HK09), despite showing α2,6-receptor binding, was also found to be inhibited. Further investigation showed that viral inhibition was due to a reduction in viral entry rate and viral attachment. Recombinant WSN virus with the neuraminidase (NA) gene swapped to A/Puerto Rico/8/1934 (PR8) and Cal04 resulted in a significant viral inhibition in MDCK-B4GalNT2 cells. With oseltamivir, the NA active site was found to be important for the replication results of WSN, but not Cal04.

KEYWORDS: B4GalNT2; Influenza; MDCK; Madin-Darby Canine Kidney cell; Sda; receptor; sialic acid; β-1,4-N-Acetyl-Galactosaminyltransferase 2

PMID: 31560252 DOI: 10.1080/22221751.2019.1665971

Keywords: Pandemic Influenza; Seasonal Influenza; H1N1; H1N1pdm09; Viral pathogenesis.

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#Medical #Outcomes in Women Who Became #Pregnant after #Vaccination with a #VLP Experimental #Vaccine against #Influenza A (#H1N1) 2009 Virus Tested during 2009 #Pandemic Outbreak (Viruses, abstract)

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

Viruses. 2019 Sep 17;11(9). pii: E868. doi: 10.3390/v11090868.

Medical Outcomes in Women Who Became Pregnant after Vaccination with a Virus-Like Particle Experimental Vaccine against Influenza A (H1N1) 2009 Virus Tested during 2009 Pandemic Outbreak.

Cérbulo-Vázquez A1, Arriaga-Pizano L2, Cruz-Cureño G3, Boscó-Gárate I4, Ferat-Osorio E5, Pastelin-Palacios R6, Figueroa-Damian R7, Castro-Eguiluz D8, Mancilla-Ramirez J9, Isibasi A10, López-Macías C11,12,13.

Author information: 1 Facultad de Medicina, Plan de Estudios Combinados en Medicina (MD, PhD Program), Universidad Nacional Autónoma de México, Mexico City CP 04510, Mexico. cerbulo@unam.mx. 2 Unidad de Investigación Médica en Inmunoquímica, Hospital de Especialidades del Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social (IMSS), Mexico City CP 06720, Mexico. landapi@hotmail.com. 3 Escuela Nacional de Ciencias Biológicas, Programa de Inmunología, Instituto Politécnico Nacional, Mexico City CP 11340, Mexico. gabrielacruz30@gmail.com. 4 Unidad de Investigación Médica en Inmunoquímica, Hospital de Especialidades del Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social (IMSS), Mexico City CP 06720, Mexico. ibosco45@hotmail.com. 5 Servicio de Cirugía Gastrointestinal, Unidad Médica de Alta Especialidad, Hospital de Especialidades Dr Bernardo Sepúlveda Gutiérrez, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social (IMSS), Mexico City CP 06720, Mexico. eduardoferat@prodigy.net.mx. 6 Departamento de Biología, Facultad de Química, Universidad Nacional Autónoma de México, Mexico City CP 04510, Mexico. rodolfop@unam.mx. 7 Departamento de Infectología, Instituto Nacional de Perinatología, Mexico City CP 11000, Mexico. rfd6102@yahoo.com.mx. 8 Consejo Nacional de Ciencia y Tecnología (CONACYT)- Departamento de Investigación Clínica, Instituto Nacional de Cancerología, Mexico City CP 14080, Mexico. angeldenisse@gmail.com. 9 Escuela Superior de Medicina, Instituto Politécnico Nacional; Hospital de la Mujer, Secretaria de Sauld, Mexico City CP 11340, Mexico. javiermancilla@hotmail.com. 10 Unidad de Investigación Médica en Inmunoquímica, Hospital de Especialidades del Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social (IMSS), Mexico City CP 06720, Mexico. isibasi@prodigy.net.mx. 11 Unidad de Investigación Médica en Inmunoquímica, Hospital de Especialidades del Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social (IMSS), Mexico City CP 06720, Mexico. constantino@sminmunologia.mx. 12 Visiting Professor of Immunology, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7LF, UK. constantino@sminmunologia.mx. 13 Mexican Translational Immunology Research Group, Federation of Clinical Immunology Societies Centers of Excellence, National Autonomous University of Mexico, Mexico City 04510, Mexico. constantino@sminmunologia.mx.

 

Abstract

The clinical effects and immunological response to the influenza vaccine in women who later become pregnant remain to be thoroughly studied. Here, we report the medical outcomes of 40 women volunteers who became pregnant after vaccination with an experimental virus-like particle (VLP) vaccine against pandemic influenza A(H1N1)2009 (influenza A(H1N1)pdm09) and their infants. When included in the VLP vaccine trial, none of the women were pregnant and were randomly assigned to one of the following groups: (1) placebo, (2) 15 μg dose of VLP vaccine, or (3) 45 μg dose of VLP vaccine. These 40 women reported becoming pregnant during the follow-up phase after receiving the placebo or VLP vaccine. Women were monitored throughout pregnancy and their infants were monitored until one year after birth. Antibody titers against VLP were measured in the mothers and infants at delivery and at six months and one year after birth. The incidence of preeclampsia, fetal death, preterm delivery, and premature rupture of membranes was similar among groups. All vaccinated women and their infants elicited antibody titers (≥1:40). Women vaccinated prior to pregnancy had no adverse events that were different from the nonvaccinated population. Even though this study is limited by the sample size, the results suggest that the anti-influenza A(H1N1)pdm09 VLP experimental vaccine applied before pregnancy is safe for both mothers and their infants.

KEYWORDS: antibody titers; influenza A(H1N1)pdm09; pregnant women; vaccination; virus-like particle

PMID: 31533277 DOI: 10.3390/v11090868

Keywords: Pandemic Influenza; H1N1pdm09; Vaccines; Pregnancy.

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