Literature DB >> 20161493

Intervention strategies for an influenza pandemic taking into account secondary bacterial infections.

Andreas Handel1, Ira M Longini, Rustom Antia.   

Abstract

Influenza infections often predispose individuals to consecutive bacterial infections. Both during seasonal and pandemic influenza outbreaks, morbidity and mortality due to secondary bacterial infections can be substantial. With the help of a mathematical model, we investigate the potential impact of such bacterial infections during an influenza pandemic, and we analyze how antiviral and antibacterial treatment or prophylaxis affect morbidity and mortality. We consider different scenarios for the spread of bacteria, the emergence of antiviral resistance, and different levels of severity for influenza infections (1918-like and 2009-like). We find that while antibacterial intervention strategies are unlikely to play an important role in reducing the overall number of cases, such interventions can lead to a significant reduction in mortality and in the number of bacterial infections. Antibacterial interventions become even more important if one considers the--very likely--scenario that during a pandemic outbreak, influenza strains resistant to antivirals emerge. Overall, our study suggests that pandemic preparedness plans should consider intervention strategies based on antibacterial treatment or prophylaxis through drugs or vaccines as part of the overall control strategy. A major caveat for our results is the lack of data that would allow precise estimation of many of the model parameters. As our results show, this leads to very large uncertainty in model outcomes. As we discuss, precise assessment of the impact of antibacterial strategies during an influenza pandemic will require the collection of further data to better estimate key parameters, especially those related to the bacterial infections and the impact of antibacterial intervention strategies.

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Year:  2009        PMID: 20161493      PMCID: PMC2796779          DOI: 10.1016/j.epidem.2009.09.001

Source DB:  PubMed          Journal:  Epidemics        ISSN: 1878-0067            Impact factor:   4.396


  91 in total

1.  Destabilization of epidemic models with the inclusion of realistic distributions of infectious periods.

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2.  Antibiotics in pandemic flu.

Authors:  Marc J M Bonten; Jan M Prins
Journal:  BMJ       Date:  2006-02-04

Review 3.  Oxazolidinone antibiotics.

Authors:  D J Diekema; R N Jones
Journal:  Lancet       Date:  2001-12-08       Impact factor: 79.321

4.  Role of neuraminidase in lethal synergism between influenza virus and Streptococcus pneumoniae.

Authors:  Jonathan A McCullers; Kimberly C Bartmess
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5.  Dispersal of Staphylococcus aureus into the air associated with a rhinovirus infection.

Authors:  Stefano Bassetti; Werner E Bischoff; Mark Walter; Barbara A Bassetti-Wyss; Lori Mason; Beth A Reboussin; Ralph B D'Agostino; Jack M Gwaltney; Michael A Pfaller; Robert J Sherertz
Journal:  Infect Control Hosp Epidemiol       Date:  2005-02       Impact factor: 3.254

6.  Effect of antiviral treatment on the outcome of secondary bacterial pneumonia after influenza.

Authors:  Jonathan A McCullers
Journal:  J Infect Dis       Date:  2004-06-30       Impact factor: 5.226

7.  H1N1 2009 influenza virus infection during pregnancy in the USA.

Authors:  Denise J Jamieson; Margaret A Honein; Sonja A Rasmussen; Jennifer L Williams; David L Swerdlow; Matthew S Biggerstaff; Stephen Lindstrom; Janice K Louie; Cara M Christ; Susan R Bohm; Vincent P Fonseca; Kathleen A Ritger; Daniel J Kuhles; Paula Eggers; Hollianne Bruce; Heidi A Davidson; Emily Lutterloh; Meghan L Harris; Colleen Burke; Noelle Cocoros; Lyn Finelli; Kitty F MacFarlane; Bo Shu; Sonja J Olsen
Journal:  Lancet       Date:  2009-07-28       Impact factor: 79.321

8.  Antiviral prophylaxis during pandemic influenza may increase drug resistance.

Authors:  Martin Eichner; Markus Schwehm; Hans-Peter Duerr; Mark Witschi; Daniel Koch; Stefan O Brockmann; Beatriz Vidondo
Journal:  BMC Infect Dis       Date:  2009-01-20       Impact factor: 3.090

9.  Time from illness onset to death, 1918 influenza and pneumococcal pneumonia.

Authors:  Keith P Klugman; Christina Mills Astley; Marc Lipsitch
Journal:  Emerg Infect Dis       Date:  2009-02       Impact factor: 6.883

10.  Bacterial pneumonia and pandemic influenza planning.

Authors:  Ravindra K Gupta; Robert George; Jonathan S Nguyen-Van-Tam
Journal:  Emerg Infect Dis       Date:  2008-08       Impact factor: 6.883

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  15 in total

Review 1.  Crossing the scale from within-host infection dynamics to between-host transmission fitness: a discussion of current assumptions and knowledge.

Authors:  Andreas Handel; Pejman Rohani
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2015-08-19       Impact factor: 6.237

2.  Prevalence of high-risk indications for influenza vaccine varies by age, race, and income.

Authors:  Richard K Zimmerman; Diane S Lauderdale; Sylvia M Tan; Diane K Wagener
Journal:  Vaccine       Date:  2010-07-30       Impact factor: 3.641

3.  Two resource distribution strategies for dynamic mitigation of influenza pandemics.

Authors:  Andrés Uribe-Sánchez; Alex Savachkin
Journal:  J Multidiscip Healthc       Date:  2010-07-07

4.  Disaster and Pandemic Management Using Machine Learning: A Survey.

Authors:  Vinay Chamola; Vikas Hassija; Sakshi Gupta; Adit Goyal; Mohsen Guizani; Biplab Sikdar
Journal:  IEEE Internet Things J       Date:  2020-12-15       Impact factor: 10.238

5.  Can interactions between timing of vaccine-altered influenza pandemic waves and seasonality in influenza complications lead to more severe outcomes?

Authors:  Utkarsh J Dang; Chris T Bauch
Journal:  PLoS One       Date:  2011-08-23       Impact factor: 3.240

6.  A review of mathematical models of influenza A infections within a host or cell culture: lessons learned and challenges ahead.

Authors:  Catherine A A Beauchemin; Andreas Handel
Journal:  BMC Public Health       Date:  2011-02-25       Impact factor: 3.295

7.  Modeling the potential impact of host population survival on the evolution of M. tuberculosis latency.

Authors:  Nibiao Zheng; Christopher C Whalen; Andreas Handel
Journal:  PLoS One       Date:  2014-08-26       Impact factor: 3.240

8.  An agent-based model simulation of influenza interactions at the host level: insight into the influenza-related burden of pneumococcal infections.

Authors:  Hélène Arduin; Matthieu Domenech de Cellès; Didier Guillemot; Laurence Watier; Lulla Opatowski
Journal:  BMC Infect Dis       Date:  2017-06-02       Impact factor: 3.090

Review 9.  Influenza interaction with cocirculating pathogens and its impact on surveillance, pathogenesis, and epidemic profile: A key role for mathematical modelling.

Authors:  Lulla Opatowski; Marc Baguelin; Rosalind M Eggo
Journal:  PLoS Pathog       Date:  2018-02-15       Impact factor: 6.823

10.  Predictive and Reactive Distribution of Vaccines and Antivirals during Cross-Regional Pandemic Outbreaks.

Authors:  Andrés Uribe-Sánchez; Alex Savachkin
Journal:  Influenza Res Treat       Date:  2011-06-05
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