Mendeley | Further Information

{"title"=>"Influenza interaction with cocirculating pathogens and its impact on surveillance, pathogenesis, and epidemic profile: A key role for mathematical modelling", "type"=>"generic", "authors"=>[{"first_name"=>"Lulla", "last_name"=>"Opatowski", "scopus_author_id"=>"24923054200"}, {"first_name"=>"Marc", "last_name"=>"Baguelin", "scopus_author_id"=>"16309167900"}, {"first_name"=>"Rosalind M.", "last_name"=>"Eggo", "scopus_author_id"=>"36113351400"}], "year"=>2018, "source"=>"PLoS Pathogens", "identifiers"=>{"issn"=>"15537374", "doi"=>"10.1371/journal.ppat.1006770", "sgr"=>"85042698104", "scopus"=>"2-s2.0-85042698104", "isbn"=>"1111111111", "pmid"=>"29447284", "pui"=>"620981837"}, "id"=>"88e19522-8254-3e94-8db6-0eb03dbd0ee5", "abstract"=>"Evidence is mounting that influenza virus, a major contributor to the global disease burden, interacts with other pathogens infecting the human respiratory tract. Taking into account interactions with other pathogens may be critical to determining the real influenza burden and the full impact of public health policies targeting influenza. That necessity is particularly true for mathematical modeling studies, which have become critical in public health decision-making, despite their usually focusing on lone influenza virus acquisition and infection, thereby making broad oversimplifications regarding pathogen ecology. Herein, we review evidence of influenza virus interaction with bacteria and viruses, and the modeling studies that incorporated some of these. Despite the many studies examining possible associations between influenza and Streptococcus pneumoniae, Staphylococcus aureus, Haemophilus influenzae, Neisseria meningitides, respiratory syncytial virus, human rhinoviruses, human parainfluenza viruses, etc., very few mathematical models have integrated other pathogens alongside influenza. A notable exception is the recent modeling of the pneumococcus-influenza interaction, which highlighted potential influenza-related increased pneumococcal transmission and pathogenicity. That example demonstrates the power of dynamic modeling as an approach to test biological hypotheses concerning interaction mechanisms and estimate the strength of those interactions. We explore how different interference mechanisms may lead to unexpected incidence trends and misinterpretations. Using simple transmission models, we illustrate how existing interactions might impact public health surveillance systems and demonstrate that the development of multipathogen models is essential to assess the true public health burden of influenza, and help improve planning and evaluation of control measures. Finally, we identify the public health needs, surveillance, modeling and biological challenges, and propose avenues of research for the coming years.", "link"=>"http://www.mendeley.com/research/influenza-interaction-cocirculating-pathogens-impact-surveillance-pathogenesis-epidemic-profile-key", "reader_count"=>30, "reader_count_by_academic_status"=>{"Librarian"=>1, "Researcher"=>14, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>8, "Student > Postgraduate"=>1, "Other"=>3, "Professor"=>1}, "reader_count_by_user_role"=>{"Librarian"=>1, "Researcher"=>14, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>8, "Student > Postgraduate"=>1, "Other"=>3, "Professor"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>3, "Environmental Science"=>2, "Biochemistry, Genetics and Molecular Biology"=>3, "Mathematics"=>6, "Medicine and Dentistry"=>5, "Agricultural and Biological Sciences"=>7, "Arts and Humanities"=>1, "Computer Science"=>1, "Immunology and Microbiology"=>2}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>5}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>7}, "Computer Science"=>{"Computer Science"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>3}, "Mathematics"=>{"Mathematics"=>6}, "Unspecified"=>{"Unspecified"=>3}, "Environmental Science"=>{"Environmental Science"=>2}, "Arts and Humanities"=>{"Arts and Humanities"=>1}}, "group_count"=>0}

CrossRef

• http://doi.org/10.1098/rsos.190305
• http://doi.org/10.1007/s11908-020-0711-8
• http://doi.org/10.1186/s12859-019-2793-6
• http://doi.org/10.1186/s12889-020-09145-y
• http://doi.org/10.1371/journal.pcbi.1008301
• http://doi.org/10.1111/irv.12666
• http://doi.org/10.1371/journal.pntd.0009208
• http://doi.org/10.1128/JVI.00881-18
• http://doi.org/10.1186/s12889-019-7414-9
• http://doi.org/10.1073/pnas.1911083116
• http://doi.org/10.1016/j.rinp.2021.104070
• http://doi.org/10.1099/jgv.0.001104
• http://doi.org/10.3389/fimmu.2018.02700
• http://doi.org/10.1016/j.intimp.2019.106032
• http://doi.org/10.1371/journal.pmed.1002829
• http://doi.org/10.1371/journal.pcbi.1006211
• http://doi.org/10.3390/vaccines7040168

Scopus | Further Information

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Twitter

• {"id"=>"1302624192446304261", "text"=>"@BrianRWasik @EllenFoxman Nice paper. https://t.co/htxCPsAV4D we wrote a review on this a couple of years ago about… https://t.co/DebNB5XEYZ", "created_at"=>"2020-09-06T15:06:23Z", "user"=>"rozeggo", "user_name"=>"Dr Roz Eggo", "user_profile_image"=>"http://pbs.twimg.com/profile_images/1226107270418882562/nZQMVzDH_normal.jpg"}
• {"id"=>"1329092378695614466", "text"=>"@nir_ @OmerUnveiled ????? ??: https://t.co/QmCIp42Rue", "created_at"=>"2020-11-18T16:01:31Z", "user"=>"SternShahar", "user_name"=>"Shahar Stern", "user_profile_image"=>"http://pbs.twimg.com/profile_images/1285802111813509120/yrvouljs_normal.jpg"}
• {"id"=>"1351956945125707782", "text"=>"@MLhNevB6siYaB5Z @GrimBeholder ??? ?? ?????. ???? ??????? ??? ??????.\n??????, ?????? ?????? ??? ????:\nhttps://t.co/QmCIp4ksSO", "created_at"=>"2021-01-20T18:17:08Z", "user"=>"SternShahar", "user_name"=>"Shahar Stern", "user_profile_image"=>"http://pbs.twimg.com/profile_images/1285802111813509120/yrvouljs_normal.jpg"}

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