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Lipsitch M, Bassett MT, Brownstein JS, Elliott P, Eyre D, Grabowski MK, Hay JA, Johansson MA, Kissler SM, Larremore DB, Layden JE, Lessler J, Lynfield R, MacCannell D, Madoff LC, Metcalf CJE, Meyers LA, Ofori SK, Quinn C, Bento AI, Reich NG, Riley S, Rosenfeld R, Samore MH, Sampath R, Slayton RB, Swerdlow DL, Truelove S, Varma JK, Grad YH. Infectious disease surveillance needs for the United States: lessons from Covid-19. Front Public Health 2024; 12:1408193. [PMID: 39076420 PMCID: PMC11285106 DOI: 10.3389/fpubh.2024.1408193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Accepted: 06/18/2024] [Indexed: 07/31/2024] Open
Abstract
The COVID-19 pandemic has highlighted the need to upgrade systems for infectious disease surveillance and forecasting and modeling of the spread of infection, both of which inform evidence-based public health guidance and policies. Here, we discuss requirements for an effective surveillance system to support decision making during a pandemic, drawing on the lessons of COVID-19 in the U.S., while looking to jurisdictions in the U.S. and beyond to learn lessons about the value of specific data types. In this report, we define the range of decisions for which surveillance data are required, the data elements needed to inform these decisions and to calibrate inputs and outputs of transmission-dynamic models, and the types of data needed to inform decisions by state, territorial, local, and tribal health authorities. We define actions needed to ensure that such data will be available and consider the contribution of such efforts to improving health equity.
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Affiliation(s)
- Marc Lipsitch
- Center for Forecasting and Outbreak Analytics, US Centers for Disease Control and Prevention, Atlanta, GA, United States
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, United States
| | - Mary T. Bassett
- François-Xavier Bagnoud Center for Health and Human Rights, Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, Boston, MA, United States
| | - John S. Brownstein
- Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Paul Elliott
- Department of Epidemiology and Public Health Medicine, Imperial College London, London, United Kingdom
| | - David Eyre
- Big Data Institute, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - M. Kate Grabowski
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
| | - James A. Hay
- Big Data Institute, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Michael A. Johansson
- Division of Vector-Borne Diseases, US Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Stephen M. Kissler
- Department of Computer Science, University of Colorado Boulder, Boulder, CO, United States
| | - Daniel B. Larremore
- Department of Computer Science, University of Colorado Boulder, Boulder, CO, United States
- BioFrontiers Institute, University of Colorado Boulder, Boulder, CO, United States
| | - Jennifer E. Layden
- Office of Public Health Data, Surveillance, and Technology, US Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Justin Lessler
- Department of Epidemiology, UNC Gillings School of Public Health, Chapel Hill, NC, United States
| | - Ruth Lynfield
- Minnesota Department of Health, Minneapolis, MN, United States
| | - Duncan MacCannell
- US Centers for Disease Control and Prevention, Office of Advanced Molecular Detection, Atlanta, GA, United States
| | | | - C. Jessica E. Metcalf
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, United States
| | - Lauren A. Meyers
- Department of Integrative Biology, University of Texas at Austin, Austin, TX, United States
| | - Sylvia K. Ofori
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, United States
| | - Celia Quinn
- Division of Disease Control, New York City Department of Health and Mental Hygiene, New York City, NY, United States
| | - Ana I. Bento
- Department of Public and Ecosystem Health, College of Veterinary Medicine, Cornell University, Ithaca, NY, United States
| | - Nicholas G. Reich
- Departments of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA, United States
| | - Steven Riley
- United Kingdom Health Security Agency, London, United Kingdom
| | - Roni Rosenfeld
- Departments of Computer Science and Computational Biology, Carnegie Melon University, Pittsburgh, PA, United States
| | - Matthew H. Samore
- Division of Epidemiology, Department of Medicine, University of Utah, Salt Lake City, UT, United States
| | | | - Rachel B. Slayton
- Division of Healthcare Quality Promotion, US Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - David L. Swerdlow
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, United States
| | - Shaun Truelove
- Department of Epidemiology, UNC Gillings School of Public Health, Chapel Hill, NC, United States
| | - Jay K. Varma
- SIGA Technologies, New York City, NY, United States
| | - Yonatan H. Grad
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, United States
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Eames KTD, Tang ML, Hill EM, Tildesley MJ, Read JM, Keeling MJ, Gog JR. Coughs, colds and "freshers' flu" survey in the University of Cambridge, 2007-2008. Epidemics 2023; 42:100659. [PMID: 36758342 DOI: 10.1016/j.epidem.2022.100659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 11/06/2022] [Accepted: 12/06/2022] [Indexed: 12/24/2022] Open
Abstract
Universities provide many opportunities for the spread of infectious respiratory illnesses. Students are brought together into close proximity from all across the world and interact with one another in their accommodation, through lectures and small group teaching and in social settings. The COVID-19 global pandemic has highlighted the need for sufficient data to help determine which of these factors are important for infectious disease transmission in universities and hence control university morbidity as well as community spillover. We describe the data from a previously unpublished self-reported university survey of coughs, colds and influenza-like symptoms collected in Cambridge, UK, during winter 2007-2008. The online survey collected information on symptoms and socio-demographic, academic and lifestyle factors. There were 1076 responses, 97% from University of Cambridge students (5.7% of the total university student population), 3% from staff and <1% from other participants, reporting onset of symptoms between September 2007 and March 2008. Undergraduates are seen to report symptoms earlier in the term than postgraduates; differences in reported date of symptoms are also seen between subjects and accommodation types, although these descriptive results could be confounded by survey biases. Despite the historical and exploratory nature of the study, this is one of few recent detailed datasets of influenza-like infection in a university context and is especially valuable to share now to improve understanding of potential transmission dynamics in universities during the current COVID-19 pandemic.
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Affiliation(s)
- Ken T D Eames
- Department of Applied Mathematics and Theoretical Physics, Centre for Mathematical Sciences, University of Cambridge, Cambridge, CB3 0WA, UK
| | - Maria L Tang
- Department of Applied Mathematics and Theoretical Physics, Centre for Mathematical Sciences, University of Cambridge, Cambridge, CB3 0WA, UK; Joint UNIversities Pandemic and Epidemiological Research, UK(1).
| | - Edward M Hill
- Joint UNIversities Pandemic and Epidemiological Research, UK(1); The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, CV4 7AL, UK
| | - Michael J Tildesley
- Joint UNIversities Pandemic and Epidemiological Research, UK(1); The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, CV4 7AL, UK
| | - Jonathan M Read
- Joint UNIversities Pandemic and Epidemiological Research, UK(1); Lancaster Medical School, Lancaster University, Lancaster, UK
| | - Matt J Keeling
- Joint UNIversities Pandemic and Epidemiological Research, UK(1); The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, CV4 7AL, UK
| | - Julia R Gog
- Department of Applied Mathematics and Theoretical Physics, Centre for Mathematical Sciences, University of Cambridge, Cambridge, CB3 0WA, UK; Joint UNIversities Pandemic and Epidemiological Research, UK(1).
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Zhou Y, Li R, Shen L. Targeting COVID-19 vaccine-hesitancy in college students: An audience-centered approach. JOURNAL OF AMERICAN COLLEGE HEALTH : J OF ACH 2023:1-10. [PMID: 36853986 DOI: 10.1080/07448481.2023.2180988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 12/27/2022] [Accepted: 02/10/2023] [Indexed: 06/18/2023]
Abstract
Objective: The study tested potential factors that differentiated the COVID-19 vaccine-hesitant and -inclined college students and, based on these factors, identified subgroups of the vaccine-hesitant students. Participants: Participants were 1,183 U.S. college students attending four-year universities or community colleges recruited through Qualtrics between January 25 and March 3, 2021. Methods: Participants completed an online survey assessing their COVID-19 vaccination intention, perceived risks of COVID-19 and the COVID-19 vaccines, efficacy beliefs regarding COVID-19 and the COVID-19 vaccines, and emotions toward taking the COVID-19 vaccines. Results: Vaccine-hesitant and -inclined college students varied in their emotions, risk perceptions, and efficacy beliefs regarding the virus and the vaccines. Using these factors as indicators, vaccine-hesitant college students were classified into five latent subgroups with distinct characteristics. Conclusions: In identifying subgroups of the vaccine-hesitant college students, the study has important insights to offer regarding the design of vaccine-promotion messaging strategies targeting the college student population.
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Affiliation(s)
- Yanmengqian Zhou
- Department of Communication Studies, Louisiana State University, Baton Rouge, Louisiana, USA
| | - Ruobing Li
- School of Communication & Journalism, Stony Brook University, Stony Brook, New York, USA
| | - Lijiang Shen
- Department of Communication Arts & Sciences, Pennsylvania State University, University Park, Pennsylvania, USA
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Moreland S, Zviedrite N, Ahmed F, Uzicanin A. COVID-19 prevention at institutions of higher education, United States, 2020-2021: implementation of nonpharmaceutical interventions. BMC Public Health 2023; 23:164. [PMID: 36694136 PMCID: PMC9872740 DOI: 10.1186/s12889-023-15079-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 01/17/2023] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND In early 2020, following the start of the coronavirus disease 2019 (COVID-19) pandemic, institutions of higher education (IHEs) across the United States rapidly pivoted to online learning to reduce the risk of on-campus virus transmission. We explored IHEs' use of this and other nonpharmaceutical interventions (NPIs) during the subsequent pandemic-affected academic year 2020-2021. METHODS From December 2020 to June 2021, we collected publicly available data from official webpages of 847 IHEs, including all public (n = 547) and a stratified random sample of private four-year institutions (n = 300). Abstracted data included NPIs deployed during the academic year such as changes to the calendar, learning environment, housing, common areas, and dining; COVID-19 testing; and facemask protocols. We performed weighted analysis to assess congruence with the October 29, 2020, US Centers for Disease Control and Prevention (CDC) guidance for IHEs. For IHEs offering ≥50% of courses in person, we used weighted multivariable linear regression to explore the association between IHE characteristics and the summated number of implemented NPIs. RESULTS Overall, 20% of IHEs implemented all CDC-recommended NPIs. The most frequently utilized NPI was learning environment changes (91%), practiced as one or more of the following modalities: distance or hybrid learning opportunities (98%), 6-ft spacing (60%), and reduced class sizes (51%). Additionally, 88% of IHEs specified facemask protocols, 78% physically changed common areas, and 67% offered COVID-19 testing. Among the 33% of IHEs offering ≥50% of courses in person, having < 1000 students was associated with having implemented fewer NPIs than IHEs with ≥1000 students. CONCLUSIONS Only 1 in 5 IHEs implemented all CDC recommendations, while a majority implemented a subset, most commonly changes to the classroom, facemask protocols, and COVID-19 testing. IHE enrollment size and location were associated with degree of NPI implementation. Additional research is needed to assess adherence to NPI implementation in IHE settings.
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Affiliation(s)
- Sarah Moreland
- grid.416738.f0000 0001 2163 0069Centers for Disease Control and Prevention, 1600 Clifton Rd NE, Atlanta, GA 30329 USA ,grid.410547.30000 0001 1013 9784Oak Ridge Institute for Science and Education, 1299 Bethel Valley Rd, Oak Ridge, TN 37830 USA
| | - Nicole Zviedrite
- Centers for Disease Control and Prevention, 1600 Clifton Rd NE, Atlanta, GA, 30329, USA.
| | - Faruque Ahmed
- grid.416738.f0000 0001 2163 0069Centers for Disease Control and Prevention, 1600 Clifton Rd NE, Atlanta, GA 30329 USA
| | - Amra Uzicanin
- grid.416738.f0000 0001 2163 0069Centers for Disease Control and Prevention, 1600 Clifton Rd NE, Atlanta, GA 30329 USA
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Akhter S, Robbins M, Curtis P, Hinshaw B, Wells EM. Online survey of university students' perception, awareness and adherence to COVID-19 prevention measures. BMC Public Health 2022; 22:964. [PMID: 35562731 PMCID: PMC9103602 DOI: 10.1186/s12889-022-13356-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 04/29/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Determining factors correlated with protective measures against COVID-19 is important to improve public health response. This study describes student opinions related to university COVID-19 preventive measures. METHODS In fall 2020, 643 US university students completed an online survey on perception, awareness, and adherence to COVID-19 preventive measures. Outcomes included protocol effectiveness (self or others), protocol adherence (self or others), consequences of protocol violation, knowledge of violations, and level of concern for COVID-19. Multiple linear regression models determined correlates of outcome variables. Covariates included gender, race, residence, area of study, class, and knowledge of someone with a positive COVID-19 test. RESULTS Overall, students agreed with protective measures (equivalent to higher scores). In adjusted linear models, females (versus males) had significantly higher scores for protocol effectiveness (self) (p < 0.001), consequences of protocol violation (p = 0.005), and concern about COVID-19 (p < 0.001). Asian/Pacific Islander (versus white) had significantly higher scores for protocol effectiveness (self) (p < 0.001), consequences of protocol violation (p = 0.008), and concern about COVID-19 (p = 0.001). Graduate students (versus freshman) had higher scores for protocol effectiveness (self) (p < 0.001), protocol adherence (self) (p = 0.004) and concern about COVID-19 (p < 0.001). In contrast, participants who had a positive COVID-19 test had significantly lower scores for protocol effectiveness (self) (p = 0.02), protocol adherence (self) (p = 0.004), and consequences of protocol violation (p = 0.008). CONCLUSION Overall, females, Asian/Pacific Islanders, and graduate students were more likely to agree with or adhere to COVID-19 prevention guidelines but those who tested positive for COVID-19 were less likely to do so. These results may inform future prevention efforts.
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Affiliation(s)
- Salma Akhter
- grid.169077.e0000 0004 1937 2197School of Health Sciences, Purdue University, West Lafayette, IN USA
| | - Meredith Robbins
- grid.169077.e0000 0004 1937 2197School of Health Sciences, Purdue University, West Lafayette, IN USA
| | - Perry Curtis
- grid.169077.e0000 0004 1937 2197School of Health Sciences, Purdue University, West Lafayette, IN USA
| | - Belle Hinshaw
- grid.169077.e0000 0004 1937 2197School of Health Sciences, Purdue University, West Lafayette, IN USA
| | - Ellen M. Wells
- grid.169077.e0000 0004 1937 2197School of Health Sciences, Purdue University, West Lafayette, IN USA ,grid.169077.e0000 0004 1937 2197Department of Public Health, Purdue University, West Lafayette, IN USA
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Mitra S, Anand U, Sanyal R, Jha NK, Behl T, Mundhra A, Ghosh A, Radha, Kumar M, Proćków J, Dey A. Neoechinulins: Molecular, cellular, and functional attributes as promising therapeutics against cancer and other human diseases. Biomed Pharmacother 2021; 145:112378. [PMID: 34741824 DOI: 10.1016/j.biopha.2021.112378] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 10/23/2021] [Accepted: 10/25/2021] [Indexed: 12/21/2022] Open
Abstract
Neoechinulins are fungal and plant-derived chemicals extracted from Microsporum sp., Eurotium rubrum, Aspergillus sp., etc. Two analogues of neoechinulin, i.e., A and B, exerted extensive pharmacological properties described in this review. Neoechinulin is an indole alkaloid and has a double bond between C8/C9, which tends to contribute to its cytoprotective nature. Neoechinulin A exhibits protection to PC12 cells against nitrosative stress via increasing NAD(P)H reserve capacity and decreasing cellular GSH levels. It also confers protection via rescuing PC12 cells from rotenone-induced stress by lowering LDH leakage. This compound has great positive potential against neurodegenerative diseases by inhibiting SIN-1 induced cell death in neuronal cells. Together with these, neoechinulin A tends to inhibit Aβ42-induced microglial activation and confers protection against neuroinflammation. Alongside, it also inhibits cervical cancer cells by caspase-dependent apoptosis and via upregulation of apoptosis inducing genes like Bax, it suppresses LPS-induced inflammation in RAW264.7 macrophages and acts as an antidepressant. Whereas, another analogue, Neoechinulin B tends to interfere with the cellular mechanism thereby, inhibiting the entry of influenza A virus and it targets Liver X receptor (LXR) and decreases the infection rate of Hepatitis C. The present review describes the pharmaceutical properties of neoechinulins with notes on their molecular, cellular, and functional basis and their therapeutic properties.
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Affiliation(s)
- Sicon Mitra
- Department of Biotechnology, School of Engineering & Technology, Sharda University, Greater Noida 201310, Uttar Pradesh, India
| | - Uttpal Anand
- Department of Life Sciences, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
| | - Rupa Sanyal
- Department of Botany, Bhairab Ganguly College (affiliated to West Bengal State University), Feeder Road, Belghoria, Kolkata 700056, West Bengal, India
| | - Niraj Kumar Jha
- Department of Biotechnology, School of Engineering & Technology, Sharda University, Greater Noida 201310, Uttar Pradesh, India
| | - Tapan Behl
- Chitkara College of Pharmacy, Chitkara University, Punjab 140401, India
| | - Avinash Mundhra
- Department of Botany, Rishi Bankim Chandra College (Affiliated to the West Bengal State University), East Kantalpara, North 24 Parganas, Naihati 743165, West Bengal, India
| | - Arabinda Ghosh
- Department of Botany, Gauhati University, Guwahati, Assam 781014, India
| | - Radha
- School of Biological and Environmental Sciences, Shoolini University of Biotechnology and Management Sciences, Solan, Himachal Pradesh 173229, India
| | - Manoj Kumar
- Chemical and Biochemical Processing Division, ICAR - Central Institute for Research on Cotton Technology, Mumbai 400019, Maharashtra, India
| | - Jarosław Proćków
- Department of Plant Biology, Institute of Environmental Biology, Wrocław University of Environmental and Life Sciences, Kożuchowska 5b, 51-631 Wrocław, Poland.
| | - Abhijit Dey
- Department of Life Sciences, Presidency University, 86/1 College Street, Kolkata, 700073, West Bengal, India.
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Lopman B, Liu CY, Le Guillou A, Handel A, Lash TL, Isakov AP, Jenness SM. A modeling study to inform screening and testing interventions for the control of SARS-CoV-2 on university campuses. Sci Rep 2021; 11:5900. [PMID: 33723312 PMCID: PMC7960702 DOI: 10.1038/s41598-021-85252-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 02/22/2021] [Indexed: 12/16/2022] Open
Abstract
University administrators face decisions about how to safely return and maintain students, staff and faculty on campus throughout the 2020-21 school year. We developed a susceptible-exposed-infectious-recovered (SEIR) deterministic compartmental transmission model of SARS-CoV-2 among university students, staff, and faculty. Our goals were to inform planning at our own university, Emory University, a medium-sized university with around 15,000 students and 15,000 faculty and staff, and to provide a flexible modeling framework to inform the planning efforts at similar academic institutions. Control strategies of isolation and quarantine are initiated by screening (regardless of symptoms) or testing (of symptomatic individuals). We explored a range of screening and testing frequencies and performed a probabilistic sensitivity analysis. We found that among students, monthly and weekly screening can reduce cumulative incidence by 59% and 87%, respectively, while testing with a 2-, 4- and 7-day delay between onset of infectiousness and testing results in an 84%, 74% and 55% reduction in cumulative incidence. Smaller reductions were observed among staff and faculty. Community-introduction of SARS-CoV-2 onto campus may be controlled with testing, isolation, contract tracing and quarantine. Screening would need to be performed at least weekly to have substantial reductions beyond disease surveillance. This model can also inform resource requirements of diagnostic capacity and isolation/quarantine facilities associated with different strategies.
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Affiliation(s)
- Ben Lopman
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA
| | - Carol Y Liu
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA.
| | - Adrien Le Guillou
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA
- Department of Research and Public Health, Reims Teaching Hospitals, Robert Debré Hospital, Reims, France
| | - Andreas Handel
- College of Public Health, University of Georgia, Athens, GA, 30602, USA
| | - Timothy L Lash
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA
| | | | - Samuel M Jenness
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA
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Quiroz Flores A, Liza F, Quteineh H, Czarnecka B. Variation in the timing of Covid-19 communication across universities in the UK. PLoS One 2021; 16:e0246391. [PMID: 33592014 PMCID: PMC7886223 DOI: 10.1371/journal.pone.0246391] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 01/17/2021] [Indexed: 11/19/2022] Open
Abstract
During the Covid-19 pandemic, universities in the UK used social media to raise awareness and provide guidance and advice about the disease to students and staff. We explain why some universities used social media to communicate with stakeholders sooner than others. To do so, we identified the date of the first Covid-19 related tweet posted by each university in the country and used survival models to estimate the effect of university-specific characteristics on the timing of these messages. In order to confirm our results, we supplemented our analysis with a study of the introduction of coronavirus-related university webpages. We find that universities with large numbers of students are more likely to use social media and the web to speak about the pandemic sooner than institutions with fewer students. Universities with large financial resources are also more likely to tweet sooner, but they do not introduce Covid-19 webpages faster than other universities. We also find evidence of a strong process of emulation, whereby universities are more likely to post a coronavirus-related tweet or webpage if other universities have already done so.
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Affiliation(s)
- Alejandro Quiroz Flores
- Business and Local Government Data Research Centre, University of Essex, Colchester, Essex, United Kingdom
- Department of Government, University of Essex, Colchester, Essex, United Kingdom
- Institute for Analytics and Data Science, University of Essex, Colchester, Essex, United Kingdom
| | - Farhana Liza
- Business and Local Government Data Research Centre, University of Essex, Colchester, Essex, United Kingdom
| | - Husam Quteineh
- Business and Local Government Data Research Centre, University of Essex, Colchester, Essex, United Kingdom
| | - Barbara Czarnecka
- Division of Management, Marketing and People, Business School, London South Bank University, London, United Kingdom
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Oliver AP, Ford MA, Bass MA, Barnard M. College Students’ Knowledge, Attitudes, and Beliefs about the 2017–2018 H3N2 Influenza Virus and Vaccination. South Med J 2020; 113:524-530. [DOI: 10.14423/smj.0000000000001155] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Abstract
Previous research on respiratory infection transmission among university students has primarily focused on influenza. In this study, we explore potential transmission events for multiple respiratory pathogens in a social contact network of university students. University students residing in on-campus housing (n = 590) were followed for the development of influenza-like illness for 10-weeks during the 2012-13 influenza season. A contact network was built using weekly self-reported contacts, class schedules, and housing information. We considered a transmission event to have occurred if students were positive for the same pathogen and had a network connection within a 14-day period. Transmitters were individuals who had onset date prior to their infected social contact. Throat and nasal samples were analysed for multiple viruses by RT-PCR. Five viruses were involved in 18 transmission events (influenza A, parainfluenza virus 3, rhinovirus, coronavirus NL63, respiratory syncytial virus). Transmitters had higher numbers of co-infections (67%). Identified transmission events had contacts reported in small classes (33%), dormitory common areas (22%) and dormitory rooms (17%). These results suggest that targeting person-to-person interactions, through measures such as isolation and quarantine, could reduce transmission of respiratory infections on campus.
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Model-Based Recursive Partitioning of Patients' Return Visits to Multispecialty Clinic During the 2009 H1N1 Pandemic Influenza (pH1N1). Online J Public Health Inform 2020; 12:e4. [PMID: 32577153 DOI: 10.5210/ojphi.v12i1.10576] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Background During the 2009 H1N1 influenza pandemic (pH1N1), the proportion of outpatient visits to emergency departments, clinics and hospitals became elevated especially during the early months of the pandemic due to surges in sick, 'worried well' or returning patients seeking care. We determined the prevalence of return visits to a multispecialty clinic during the 2009 H1N1 influenza pandemic and identify subgroups at risk for return visits using model-based recursive partitioning technique. Methods This study was a retrospective analysis of ILI-related medical care visits to multispecialty clinic in Houston, Texas obtained as part of the Houston Health Department Influenza Sentinel Surveillance Project (ISSP) during the 2009 H1N1 pandemic influenza (April 2009 - March 2010). The data comprised of 2680 individuals who made a total of 2960 clinic visits. Return visit was defined as any visit following the index visit after the wash-out phase prior to the study period. We applied nominal logistic regression and recursive partitioning models to determine the independent predictors and the response probabilities of return visits. The sensitivity and specificity of the outcomes probabilities were determined using receiver operating characteristic (ROC) curve. Results Overall, 4.56% (Prob. 0.0%-17.5%) of the cohort had return visits with significant variations observed attributed to age group (76.0%), type of vaccine received by patients (18.4%) and Influenza A (pH1N1) test result (5.6%). Patients in age group 0-4 years were 9 times (aOR: 8.77, 95%CI: 3.39-29.95, p<0.0001) more likely than those who were 50+ years to have return visits. Similarly, patients who received either seasonal flu (aOR: 1.59, 95% CI 1.01-2.50, p=0.047) or pH1N1 (aOR: 1.74, 95%CI: 1.09-2.75, p=0.022) vaccines were about twice more likely to have return visits compared to those with no vaccination history. Model-based recursive partitioning yielded 19 splits with patients in subgroup I (patients of age group 0-4 years, who tested positive for pH1N1, and received both seasonal flu and pH1N1 vaccines) having the highest risk of return visits (Prob.=17.5%). The area under the curve (AUC) for both return and non-return visits was 72.9%, indicating a fairly accurate classification of the two groups. Conclusions Return visits in our cohort were more prevalent among children and young adults, and those that received either seasonal flu or pH1N1 or both vaccines. Understanding the dynamics in care-seeking behavior during pandemic would assist policymakers with appropriate resource allocation, and in the design of initiatives aimed at mitigating surges and recurrent utilization of the healthcare system.
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Lipsitch M, Santillana M. Enhancing Situational Awareness to Prevent Infectious Disease Outbreaks from Becoming Catastrophic. Curr Top Microbiol Immunol 2019; 424:59-74. [DOI: 10.1007/82_2019_172] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
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13
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Hashmi S, D'Ambrosio L, Diamond DV, Jalali MS, Finkelstein SN, Larson RC. Preventive behaviors and perceptions of influenza vaccination among a university student population. J Public Health (Oxf) 2018; 38:739-745. [PMID: 28158761 DOI: 10.1093/pubmed/fdv189] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
| | - Lisa D'Ambrosio
- Institute for Data, Systems and Society, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - David V Diamond
- MIT Medical, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Mohammad S Jalali
- Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Stan N Finkelstein
- Institute for Data, Systems and Society, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Richard C Larson
- Institute for Data, Systems and Society, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
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14
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Lo C, Mertz D, Loeb M. Assessing the reporting quality of influenza outbreaks in the community. Influenza Other Respir Viruses 2017; 11:556-563. [PMID: 29054122 PMCID: PMC5705690 DOI: 10.1111/irv.12516] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/14/2017] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND High-quality reporting of outbreak characteristics is fundamental to understand the behaviour of various strains of influenza virus and the impact of outbreak management strategies. However, few studies have systematically evaluated the quality of outbreak reporting. OBJECTIVES To conduct a systematic analysis and assessment for reporting quality of influenza outbreaks based on a modified version of the STROBE statement, and to examine characteristics associated with reporting quality. METHODS A literature search was conducted across 3 online databases (PubMed, Web of Science, MEDLINE) for reports of influenza outbreaks (pandemic H1N1, avian, seasonal). The quality of reports meeting our eligibility criteria was assessed using the Modified STROBE criteria and assigned a score of 30. Mean differences (MD) and 95% confidence intervals (CI) were reported for comparisons of study characteristics. RESULTS Sixty-four outbreak reports were available for analyses. The average Modified STROBE score was 20/30. Peer-reviewed articles were associated with a better quality of reporting (MD 2.79, 95% CI 0.79-4.78). Likewise, reports from authors affiliated with public health agencies were associated with better quality than those from academic institutions (MD 1.65, 95% CI-0.27-3.56). CONCLUSIONS The development of explicit reporting guidelines specifically geared towards reporting of outbreak investigations proved to be useful. Providing information on patient characteristics, investigation details in introduction and results, as well as addressing limitations that could have biased the findings, were frequently missing in the published reports.
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Affiliation(s)
- Calvin Lo
- Department of Pathology and Molecular MedicineMcMaster UniversityHamiltonONCanada
| | - Dominik Mertz
- Department of Pathology and Molecular MedicineMcMaster UniversityHamiltonONCanada
- Department of MedicineMcMaster UniversityHamiltonONCanada
- Department of Health Research Methods, Evidence and ImpactMcMaster UniversityHamiltonONCanada
- Michael G. DeGroote Institute for Infectious Diseases ResearchMcMaster UniversityHamiltonONCanada
| | - Mark Loeb
- Department of Pathology and Molecular MedicineMcMaster UniversityHamiltonONCanada
- Department of Health Research Methods, Evidence and ImpactMcMaster UniversityHamiltonONCanada
- Michael G. DeGroote Institute for Infectious Diseases ResearchMcMaster UniversityHamiltonONCanada
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15
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Qualls N, Levitt A, Kanade N, Wright-Jegede N, Dopson S, Biggerstaff M, Reed C, Uzicanin A. Community Mitigation Guidelines to Prevent Pandemic Influenza - United States, 2017. MMWR Recomm Rep 2017. [PMID: 28426646 DOI: 10.15585/mmwr.rr6601a1externalicon] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/24/2023] Open
Abstract
When a novel influenza A virus with pandemic potential emerges, nonpharmaceutical interventions (NPIs) often are the most readily available interventions to help slow transmission of the virus in communities, which is especially important before a pandemic vaccine becomes widely available. NPIs, also known as community mitigation measures, are actions that persons and communities can take to help slow the spread of respiratory virus infections, including seasonal and pandemic influenza viruses.These guidelines replace the 2007 Interim Pre-pandemic Planning Guidance: Community Strategy for Pandemic Influenza Mitigation in the United States - Early, Targeted, Layered Use of Nonpharmaceutical Interventions (https://stacks.cdc.gov/view/cdc/11425). Several elements remain unchanged from the 2007 guidance, which described recommended NPIs and the supporting rationale and key concepts for the use of these interventions during influenza pandemics. NPIs can be phased in, or layered, on the basis of pandemic severity and local transmission patterns over time. Categories of NPIs include personal protective measures for everyday use (e.g., voluntary home isolation of ill persons, respiratory etiquette, and hand hygiene); personal protective measures reserved for influenza pandemics (e.g., voluntary home quarantine of exposed household members and use of face masks in community settings when ill); community measures aimed at increasing social distancing (e.g., school closures and dismissals, social distancing in workplaces, and postponing or cancelling mass gatherings); and environmental measures (e.g., routine cleaning of frequently touched surfaces).Several new elements have been incorporated into the 2017 guidelines. First, to support updated recommendations on the use of NPIs, the latest scientific evidence available since the influenza A (H1N1)pdm09 pandemic has been added. Second, a summary of lessons learned from the 2009 H1N1 pandemic response is presented to underscore the importance of broad and flexible prepandemic planning. Third, a new section on community engagement has been included to highlight that the timely and effective use of NPIs depends on community acceptance and active participation. Fourth, to provide new or updated pandemic assessment and planning tools, the novel influenza virus pandemic intervals tool, the Influenza Risk Assessment Tool, the Pandemic Severity Assessment Framework, and a set of prepandemic planning scenarios are described. Finally, to facilitate implementation of the updated guidelines and to assist states and localities with prepandemic planning and decision-making, this report links to six supplemental prepandemic NPI planning guides for different community settings that are available online (https://www.cdc.gov/nonpharmaceutical-interventions).
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Affiliation(s)
- Noreen Qualls
- Division of Global Migration and Quarantine, National Center for Emerging and Zoonotic Infectious Diseases, CDC, Atlanta, Georgia
| | | | - Neha Kanade
- Division of Global Migration and Quarantine, National Center for Emerging and Zoonotic Infectious Diseases, CDC, Atlanta, Georgia
- Eagle Medical Services, San Antonio, Texas
| | - Narue Wright-Jegede
- Division of Global Migration and Quarantine, National Center for Emerging and Zoonotic Infectious Diseases, CDC, Atlanta, Georgia
- Karna, Atlanta, Georgia
| | - Stephanie Dopson
- Division of State and Local Readiness, Office of Public Health Preparedness and Response, CDC, Atlanta, Georgia
| | - Matthew Biggerstaff
- Influenza Division, National Center for Immunization and Respiratory Diseases, CDC, Atlanta, Georgia
| | - Carrie Reed
- Influenza Division, National Center for Immunization and Respiratory Diseases, CDC, Atlanta, Georgia
| | - Amra Uzicanin
- Division of Global Migration and Quarantine, National Center for Emerging and Zoonotic Infectious Diseases, CDC, Atlanta, Georgia
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16
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Qualls N, Levitt A, Kanade N, Wright-Jegede N, Dopson S, Biggerstaff M, Reed C, Uzicanin A. Community Mitigation Guidelines to Prevent Pandemic Influenza - United States, 2017. MMWR Recomm Rep 2017; 66:1-34. [PMID: 28426646 PMCID: PMC5837128 DOI: 10.15585/mmwr.rr6601a1] [Citation(s) in RCA: 238] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
When a novel influenza A virus with pandemic potential emerges, nonpharmaceutical interventions (NPIs) often are the most readily available interventions to help slow transmission of the virus in communities, which is especially important before a pandemic vaccine becomes widely available. NPIs, also known as community mitigation measures, are actions that persons and communities can take to help slow the spread of respiratory virus infections, including seasonal and pandemic influenza viruses.These guidelines replace the 2007 Interim Pre-pandemic Planning Guidance: Community Strategy for Pandemic Influenza Mitigation in the United States - Early, Targeted, Layered Use of Nonpharmaceutical Interventions (https://stacks.cdc.gov/view/cdc/11425). Several elements remain unchanged from the 2007 guidance, which described recommended NPIs and the supporting rationale and key concepts for the use of these interventions during influenza pandemics. NPIs can be phased in, or layered, on the basis of pandemic severity and local transmission patterns over time. Categories of NPIs include personal protective measures for everyday use (e.g., voluntary home isolation of ill persons, respiratory etiquette, and hand hygiene); personal protective measures reserved for influenza pandemics (e.g., voluntary home quarantine of exposed household members and use of face masks in community settings when ill); community measures aimed at increasing social distancing (e.g., school closures and dismissals, social distancing in workplaces, and postponing or cancelling mass gatherings); and environmental measures (e.g., routine cleaning of frequently touched surfaces).Several new elements have been incorporated into the 2017 guidelines. First, to support updated recommendations on the use of NPIs, the latest scientific evidence available since the influenza A (H1N1)pdm09 pandemic has been added. Second, a summary of lessons learned from the 2009 H1N1 pandemic response is presented to underscore the importance of broad and flexible prepandemic planning. Third, a new section on community engagement has been included to highlight that the timely and effective use of NPIs depends on community acceptance and active participation. Fourth, to provide new or updated pandemic assessment and planning tools, the novel influenza virus pandemic intervals tool, the Influenza Risk Assessment Tool, the Pandemic Severity Assessment Framework, and a set of prepandemic planning scenarios are described. Finally, to facilitate implementation of the updated guidelines and to assist states and localities with prepandemic planning and decision-making, this report links to six supplemental prepandemic NPI planning guides for different community settings that are available online (https://www.cdc.gov/nonpharmaceutical-interventions).
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Affiliation(s)
- Noreen Qualls
- Division of Global Migration and Quarantine, National Center for Emerging and Zoonotic Infectious Diseases, CDC, Atlanta, Georgia
| | | | - Neha Kanade
- Division of Global Migration and Quarantine, National Center for Emerging and Zoonotic Infectious Diseases, CDC, Atlanta, Georgia.,Eagle Medical Services, San Antonio, Texas
| | - Narue Wright-Jegede
- Division of Global Migration and Quarantine, National Center for Emerging and Zoonotic Infectious Diseases, CDC, Atlanta, Georgia.,Karna, Atlanta, Georgia
| | - Stephanie Dopson
- Division of State and Local Readiness, Office of Public Health Preparedness and Response, CDC, Atlanta, Georgia
| | - Matthew Biggerstaff
- Influenza Division, National Center for Immunization and Respiratory Diseases, CDC, Atlanta, Georgia
| | - Carrie Reed
- Influenza Division, National Center for Immunization and Respiratory Diseases, CDC, Atlanta, Georgia
| | - Amra Uzicanin
- Division of Global Migration and Quarantine, National Center for Emerging and Zoonotic Infectious Diseases, CDC, Atlanta, Georgia
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17
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Mcbride WJH, Abhayaratna WP, Barr I, Booy R, Carapetis J, Carson S, De Looze F, Ellis-Pegler R, Heron L, Karrasch J, Marshall H, Mcvernon J, Nolan T, Rawlinson W, Reid J, Richmond P, Shakib S, Basser RL, Hartel GF, Lai MH, Rockman S, Greenberg ME. Efficacy of a trivalent influenza vaccine against seasonal strains and against 2009 pandemic H1N1: A randomized, placebo-controlled trial. Vaccine 2016; 34:4991-4997. [PMID: 27595443 DOI: 10.1016/j.vaccine.2016.08.038] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2016] [Revised: 07/31/2016] [Accepted: 08/11/2016] [Indexed: 11/18/2022]
Abstract
BACKGROUND Before pandemic H1N1 vaccines were available, the potential benefit of existing seasonal trivalent inactivated influenza vaccines (IIV3s) against influenza due to the 2009 pandemic H1N1 influenza strain was investigated, with conflicting results. This study assessed the efficacy of seasonal IIV3s against influenza due to 2008 and 2009 seasonal influenza strains and against the 2009 pandemic H1N1 strain. METHODS This observer-blind, randomized, placebo-controlled study enrolled adults aged 18-64years during 2008 and 2009 in Australia and New Zealand. Participants were randomized 2:1 to receive IIV3 or placebo. The primary objective was to demonstrate the efficacy of IIV3 against laboratory-confirmed influenza. Participants reporting an influenza-like illness during the period from 14days after vaccination until 30 November of each study year were tested for influenza by real-time reverse transcription polymerase chain reaction. RESULTS Over a study period of 2years, 15,044 participants were enrolled (mean age±standard deviation: 35.5±14.7years; 54.4% female). Vaccine efficacy of the 2008 and 2009 IIV3s against influenza due to any strain was 42% (95% confidence interval [CI]: 30%, 52%), whereas vaccine efficacy against influenza due to the vaccine-matched strains was 60% (95% CI: 44%, 72%). Vaccine efficacy of the 2009 IIV3 against influenza due to the 2009 pandemic H1N1 strain was 38% (95% CI: 19%, 53%). No vaccine-related deaths or serious adverse events were reported. Solicited local and systemic adverse events were more frequent in IIV3 recipients than placebo recipients (local: IIV3 74.6% vs placebo 20.4%, p<0.001; systemic: IIV3 46.6% vs placebo 39.1%, p<0.001). CONCLUSIONS The 2008 and 2009 IIV3s were efficacious against influenza due to seasonal influenza strains and the 2009 IIV3 demonstrated moderate efficacy against influenza due to the 2009 pandemic H1N1 strain. Funded by CSL Limited, ClinicalTrials.gov identifier NCT00562484.
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Affiliation(s)
- William J H Mcbride
- James Cook University, Cairns Hospital Clinical School, Cairns, Queensland 4870, Australia.
| | - Walter P Abhayaratna
- Academic Unit of Internal Medicine, Canberra Hospital, Woden, Australian Capital Territory 2606, Australia; ANU College of Medicine, Biology and Environment, Australian National University, Canberra, Australian Capital Territory 0200, Australia.
| | - Ian Barr
- World Health Organization Collaborating Centre for Reference and Research on Influenza, North Melbourne, Victoria 3051, Australia.
| | - Robert Booy
- National Centre for Immunisation Research and Surveillance of Vaccine Preventable Diseases, The University of Sydney and The Children's Hospital at Westmead, Westmead, New South Wales 2145, Australia.
| | - Jonathan Carapetis
- Menzies School of Health Research, Charles Darwin University, Darwin, Northern Territory 0810, Australia.
| | - Simon Carson
- Southern Clinical Trials Ltd, Christchurch 8013, New Zealand.
| | - Ferdinandus De Looze
- Trialworks Clinical Research Pty Ltd and Discipline of General Practice, School of Medicine, University of Queensland, Brisbane, Queensland 4067, Australia.
| | | | - Leon Heron
- National Centre for Immunisation Research and Surveillance of Vaccine Preventable Diseases, The University of Sydney and The Children's Hospital at Westmead, Westmead, New South Wales 2145, Australia.
| | - Jeff Karrasch
- Redcliffe Hospital, Redcliffe, Queensland 4020, Australia.
| | - Helen Marshall
- Vaccinology and Immunology Research Trials Unit (VIRTU), Women's and Children's Hospital, Robinson Research Institute and School of Medicine, University of Adelaide, Adelaide, South Australia 5006, Australia.
| | - Jodie Mcvernon
- Vaccine and Immunization Research Group, Melbourne School of Population and Global Health, University of Melbourne, and Murdoch Children's Research Institute, Parkville, Victoria 3052, Australia.
| | - Terry Nolan
- Vaccine and Immunization Research Group, Melbourne School of Population and Global Health, University of Melbourne, and Murdoch Children's Research Institute, Parkville, Victoria 3052, Australia.
| | - William Rawlinson
- South Eastern Sydney and Illawarra Area Health Service and University of New South Wales, Sydney, New South Wales 2052, Australia.
| | - Jim Reid
- Dunedin School of Medicine, University of Otago, Dunedin 9054, New Zealand.
| | - Peter Richmond
- University of Western Australia, School of Paediatrics and Child Health, Princess Margaret Hospital for Children, Perth, Western Australia 6872, Australia
| | - Sepehr Shakib
- Discipline of Pharmacology, School of Medical Sciences, University of Adelaide, Adelaide, South Australia 5001, Australia.
| | - Russell L Basser
- Clinical Research and Development, CSL Limited, Parkville, Victoria 3052, Australia.
| | - Gunter F Hartel
- Clinical Research and Development, CSL Limited, Parkville, Victoria 3052, Australia.
| | - Michael H Lai
- Clinical Research and Development, CSL Limited, Parkville, Victoria 3052, Australia.
| | - Steven Rockman
- Clinical Research and Development, CSL Limited, Parkville, Victoria 3052, Australia.
| | - Michael E Greenberg
- Clinical Research and Development, CSL Limited, Parkville, Victoria 3052, Australia.
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18
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Lipsitch M, Donnelly CA, Fraser C, Blake IM, Cori A, Dorigatti I, Ferguson NM, Garske T, Mills HL, Riley S, Van Kerkhove MD, Hernán MA. Potential Biases in Estimating Absolute and Relative Case-Fatality Risks during Outbreaks. PLoS Negl Trop Dis 2015; 9:e0003846. [PMID: 26181387 PMCID: PMC4504518 DOI: 10.1371/journal.pntd.0003846] [Citation(s) in RCA: 139] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Estimating the case-fatality risk (CFR)-the probability that a person dies from an infection given that they are a case-is a high priority in epidemiologic investigation of newly emerging infectious diseases and sometimes in new outbreaks of known infectious diseases. The data available to estimate the overall CFR are often gathered for other purposes (e.g., surveillance) in challenging circumstances. We describe two forms of bias that may affect the estimation of the overall CFR-preferential ascertainment of severe cases and bias from reporting delays-and review solutions that have been proposed and implemented in past epidemics. Also of interest is the estimation of the causal impact of specific interventions (e.g., hospitalization, or hospitalization at a particular hospital) on survival, which can be estimated as a relative CFR for two or more groups. When observational data are used for this purpose, three more sources of bias may arise: confounding, survivorship bias, and selection due to preferential inclusion in surveillance datasets of those who are hospitalized and/or die. We illustrate these biases and caution against causal interpretation of differential CFR among those receiving different interventions in observational datasets. Again, we discuss ways to reduce these biases, particularly by estimating outcomes in smaller but more systematically defined cohorts ascertained before the onset of symptoms, such as those identified by forward contact tracing. Finally, we discuss the circumstances in which these biases may affect non-causal interpretation of risk factors for death among cases.
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Affiliation(s)
- Marc Lipsitch
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
- * E-mail:
| | - Christl A. Donnelly
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Christophe Fraser
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Isobel M. Blake
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Anne Cori
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Ilaria Dorigatti
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Neil M. Ferguson
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Tini Garske
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Harriet L. Mills
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Steven Riley
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Maria D. Van Kerkhove
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
- Centre for Global Health, Institut Pasteur, Paris, France
| | - Miguel A. Hernán
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
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19
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Gambhir M, Bozio C, O'Hagan JJ, Uzicanin A, Johnson LE, Biggerstaff M, Swerdlow DL. Infectious disease modeling methods as tools for informing response to novel influenza viruses of unknown pandemic potential. Clin Infect Dis 2015; 60 Suppl 1:S11-9. [PMID: 25878297 DOI: 10.1093/cid/civ083] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The rising importance of infectious disease modeling makes this an appropriate time for a guide for public health practitioners tasked with preparing for, and responding to, an influenza pandemic. We list several questions that public health practitioners commonly ask about pandemic influenza and match these with analytical methods, giving details on when during a pandemic the methods can be used, how long it might take to implement them, and what data are required. Although software to perform these tasks is available, care needs to be taken to understand: (1) the type of data needed, (2) the implementation of the methods, and (3) the interpretation of results in terms of model uncertainty and sensitivity. Public health leaders can use this article to evaluate the modeling literature, determine which methods can provide appropriate evidence for decision-making, and to help them request modeling work from in-house teams or academic groups.
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Affiliation(s)
- Manoj Gambhir
- Epidemiological Modelling Unit, Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia Modeling Unit, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC) IHRC Inc
| | - Catherine Bozio
- Graduate Program in Epidemiology and Molecules to Mankind, Laney Graduate School, Emory University
| | - Justin J O'Hagan
- Modeling Unit, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC) IHRC Inc
| | - Amra Uzicanin
- Division of Global Migration and Quarantine, National Center for Emerging and Zoonotic Infectious Diseases
| | | | | | - David L Swerdlow
- Modeling Unit and Office of the Director, NCIRD, CDC, Atlanta, Georgia
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20
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Napoli C, Fabiani M, Rizzo C, Barral M, Oxford J, Cohen J, Niddam L, Goryński P, Pistol A, Lionis C, Briand S, Nicoll A, Penttinen P, Gauci C, Bounekkar A, Bonnevay S, Beresniak A. Assessment of human influenza pandemic scenarios in Europe. ACTA ACUST UNITED AC 2015; 20:29-38. [PMID: 25719965 DOI: 10.2807/1560-7917.es2015.20.7.21038] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- C Napoli
- Istituto Superiore di Sanita (ISS), Rome, Italy
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21
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Chen X, Si L, Liu D, Proksch P, Zhang L, Zhou D, Lin W. Neoechinulin B and its analogues as potential entry inhibitors of influenza viruses, targeting viral hemagglutinin. Eur J Med Chem 2015; 93:182-95. [PMID: 25681711 DOI: 10.1016/j.ejmech.2015.02.006] [Citation(s) in RCA: 80] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2014] [Revised: 02/01/2015] [Accepted: 02/04/2015] [Indexed: 11/16/2022]
Abstract
A class of prenylated indole diketopiperazine alkaloids including 15 new compounds namely rubrumlines A-O obtained from marine-derived fungus Eurotium rubrum, were tested against influenza A/WSN/33 virus. Neoechinulin B (18) exerted potent inhibition against H1N1 virus infected in MDCK cells, and is able to inhibit a panel of influenza virus strains including amantadine- and oseltamivir-resistant clinical isolates. Mechanism of action studies indicated that neoechinulin B binds to influenza envelope hemagglutinin, disrupting its interaction with the sialic acid receptor and the attachment of viruses to host cells. In addition, neoechinulin B was still efficient in inhibiting influenza A/WSN/33 virus propagation even after a fifth passage. The high potency and broad-spectrum activities against influenza viruses with less drug resistance make neoechinulin B as a new lead for the development of potential inhibitor of influenza viruses.
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Affiliation(s)
- Xueqing Chen
- State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, 38 Xueyuan Road, Beijing 100191, China
| | - Longlong Si
- State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, 38 Xueyuan Road, Beijing 100191, China
| | - Dong Liu
- State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, 38 Xueyuan Road, Beijing 100191, China
| | - Peter Proksch
- Institute für Pharmazeutische Biologie und Biotechnologie, Heinrich-Heine-Universität Düsseldorf, Universitätsstr. 1, Geb.26.23, 40225 Düsseldorf, Germany
| | - Lihe Zhang
- State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, 38 Xueyuan Road, Beijing 100191, China
| | - Demin Zhou
- State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, 38 Xueyuan Road, Beijing 100191, China.
| | - Wenhan Lin
- State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, 38 Xueyuan Road, Beijing 100191, China.
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22
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Li ZY, Chen JY, Zhang YL, Fu WM. Partial protection against 2009 pandemic influenza A (H1N1) of seasonal influenza vaccination and related regional factors: Updated systematic review and meta-analyses. Hum Vaccin Immunother 2015; 11:1337-44. [PMID: 25692308 PMCID: PMC4514212 DOI: 10.4161/21645515.2014.985495] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2014] [Revised: 09/29/2014] [Accepted: 10/07/2014] [Indexed: 01/02/2023] Open
Abstract
This updated systematic review and meta-analyses aims to systematically evaluate the cross-protection of seasonal influenza vaccines against the 2009 pandemic A (H1N1) influenza infection, and investigate the potential effect of the influenza strains circulating previous to the pandemic on the association between vaccine receipt and pandemic infection. In addition, subgroup analysis was performed based on the study locations and previous circulating influenza viruses. Relevant articles in English and Chinese from 2009 to October 2013 were systematically searched, and 21 eligible studies were included. For case-control studies, an insignificant 20% reduced risk for pandemic influenza infection based on combined national data (OR = 0.80; 95%CI: 0.60, 1.05) was calculated for people receiving seasonal influenza vaccination. However, for RCTs, an insignificant increase in the risk of seasonal influenza vaccines was observed (RR = 1.27; 95% CI: 0.46, 3.53). For the subgroup analysis, a significant 35% cross-protection was observed in the subgroup where influenza A outbreaks were detected before the 2009 pandemic. Moreover, the results indicated that seasonal influenza vaccination may reduce the risk of influenza-like illnesses (ILIs) (RR = 0.91; 95% CI: 0.84, 0.99). Our findings partially support the hypothesis that seasonal vaccines may offer moderate cross-protection for adults against laboratory-confirmed pandemic influenza A (H1N1) infection and ILIs. Further immunological studies are needed to understand the mechanism underlying these findings.
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Affiliation(s)
- Zhi-Yuan Li
- Guangzhou Institute of Advanced Technology; Chinese Academy of Sciences; Guangzhou, PR China
| | | | - Yan-Ling Zhang
- School of Medical Technology and Nursing; Shenzhen Polytechnic; Shenzhen, PR China
| | - Wei-Ming Fu
- Guangzhou Institute of Advanced Technology; Chinese Academy of Sciences; Guangzhou, PR China
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23
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Transmission characteristics of different students during a school outbreak of (H1N1) pdm09 influenza in China, 2009. Sci Rep 2014; 4:5982. [PMID: 25102240 PMCID: PMC4124738 DOI: 10.1038/srep05982] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2014] [Accepted: 07/17/2014] [Indexed: 11/25/2022] Open
Abstract
Many outbreaks of A(H1N1)pdm09 influenza have occurred in schools with a high population density. Containment of school outbreaks is predicted to help mitigate pandemic influenza. Understanding disease transmission characteristics within the school setting is critical to implementing effective control measures. Based on a school outbreak survey, we found almost all (93.7%) disease transmission occurred within a single grade, only 6.3% crossed grades. Transmissions originating from freshmen exhibited a star-shaped network; other grades exhibited branch- or line-shaped networks, indicating freshmen have higher activity and are more likely to cause infection. R0 for freshmen, calculated as 2.04, estimated as 2.76, was greater than for other grades (P < 0.01). Without intervention, the estimated number of cases was much greater when the outbreak was initiated by freshmen than by other grades. Furthermore, the estimated number of cases required to be under quarantine and isolation for freshmen was less than that of equivalent other grades. So we concluded that different grades have different transmission mode. Freshmen were the main facilitators of the spread of A(H1N1)pdm09 influenza during this school outbreak, so control measures (e.g. close contact isolation) priority used for freshmen would likely have effectively reduced spread of influenza in school settings.
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Evaluation of the spread of pandemic influenza A/H1N1 2009 among Japanese university students. Environ Health Prev Med 2014; 19:315-21. [PMID: 24993386 DOI: 10.1007/s12199-014-0396-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2014] [Accepted: 06/11/2014] [Indexed: 10/25/2022] Open
Abstract
The pandemic influenza A/H1N1 2009 virus is commonly known to affect younger individuals. Several epidemiological studies have clarified the epidemic features of university students in Japan. In this study, we reviewed these studies in Japan in comparison with reports from other countries. The average cumulative incidence rate among university students was 9.6 %, with the major symptoms being cough, sore throat, and rhinorrhea. These epidemiological features were similar between Japan and other countries. Attitudes and behaviors toward pandemic influenza control measures were different before and improved during and after the epidemic. These features were also similar to those in other countries. On the other hand, the epidemic spread through club activities or social events, and transmission was attenuated after temporary closure of such groups in Japan. This transmission pattern was inconsistent among countries, which may have been due to differences in lifestyle and cultural habits. Based on these results, infection control measures of pandemic influenza for university organizations in Japan should be considered.
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Skowronski DM, Hamelin ME, De Serres G, Janjua NZ, Li G, Sabaiduc S, Bouhy X, Couture C, Leung A, Kobasa D, Embury-Hyatt C, de Bruin E, Balshaw R, Lavigne S, Petric M, Koopmans M, Boivin G. Randomized controlled ferret study to assess the direct impact of 2008-09 trivalent inactivated influenza vaccine on A(H1N1)pdm09 disease risk. PLoS One 2014; 9:e86555. [PMID: 24475142 PMCID: PMC3903544 DOI: 10.1371/journal.pone.0086555] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2013] [Accepted: 12/17/2013] [Indexed: 12/29/2022] Open
Abstract
During spring-summer 2009, several observational studies from Canada showed increased risk of medically-attended, laboratory-confirmed A(H1N1)pdm09 illness among prior recipients of 2008-09 trivalent inactivated influenza vaccine (TIV). Explanatory hypotheses included direct and indirect vaccine effects. In a randomized placebo-controlled ferret study, we tested whether prior receipt of 2008-09 TIV may have directly influenced A(H1N1)pdm09 illness. Thirty-two ferrets (16/group) received 0.5 mL intra-muscular injections of the Canadian-manufactured, commercially-available, non-adjuvanted, split 2008-09 Fluviral or PBS placebo on days 0 and 28. On day 49 all animals were challenged (Ch0) with A(H1N1)pdm09. Four ferrets per group were randomly selected for sacrifice at day 5 post-challenge (Ch+5) and the rest followed until Ch+14. Sera were tested for antibody to vaccine antigens and A(H1N1)pdm09 by hemagglutination inhibition (HI), microneutralization (MN), nucleoprotein-based ELISA and HA1-based microarray assays. Clinical characteristics and nasal virus titers were recorded pre-challenge then post-challenge until sacrifice when lung virus titers, cytokines and inflammatory scores were determined. Baseline characteristics were similar between the two groups of influenza-naïve animals. Antibody rise to vaccine antigens was evident by ELISA and HA1-based microarray but not by HI or MN assays; virus challenge raised antibody to A(H1N1)pdm09 by all assays in both groups. Beginning at Ch+2, vaccinated animals experienced greater loss of appetite and weight than placebo animals, reaching the greatest between-group difference in weight loss relative to baseline at Ch+5 (7.4% vs. 5.2%; p = 0.01). At Ch+5 vaccinated animals had higher lung virus titers (log-mean 4.96 vs. 4.23pfu/mL, respectively; p = 0.01), lung inflammatory scores (5.8 vs. 2.1, respectively; p = 0.051) and cytokine levels (p>0.05). At Ch+14, both groups had recovered. Findings in influenza-naïve, systematically-infected ferrets may not replicate the human experience. While they cannot be considered conclusive to explain human observations, these ferret findings are consistent with direct, adverse effect of prior 2008-09 TIV receipt on A(H1N1)pdm09 illness. As such, they warrant further in-depth investigation and search for possible mechanistic explanations.
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Affiliation(s)
- Danuta M. Skowronski
- British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada
- University of British Columbia, Vancouver, British Columbia, Canada
| | - Marie-Eve Hamelin
- Centre Hospitalier Universitaire de Québec [University Hospital Centre of Québec], Québec, Canada
- Laval University, Québec, Canada
| | - Gaston De Serres
- Centre Hospitalier Universitaire de Québec [University Hospital Centre of Québec], Québec, Canada
- Laval University, Québec, Canada
- Institut National de Santé Publique du Québec [National Institute of Health of Québec], Québec, Canada
| | - Naveed Z. Janjua
- British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada
- University of British Columbia, Vancouver, British Columbia, Canada
| | - Guiyun Li
- British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada
| | - Suzana Sabaiduc
- British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada
- University of British Columbia, Vancouver, British Columbia, Canada
| | - Xavier Bouhy
- Centre Hospitalier Universitaire de Québec [University Hospital Centre of Québec], Québec, Canada
| | - Christian Couture
- Institut universitaire de cardiologie et pneumologie de Québec, Québec, Québec, Canada
| | - Anders Leung
- Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Darwyn Kobasa
- Public Health Agency of Canada, Winnipeg, Manitoba, Canada
- Department of Medical Microbiology, University of Manitoba, Winnipeg, Manitoba, Canada
| | | | - Erwin de Bruin
- Laboratory for Infectious Disease Research, Diagnostics and Screening, Centre for Infectious Disease Control (CIDC), Rijksinstituut voor Volksgezondheid en Milieu (RIVM) [National Institute of Public Health and the Environment], Bilthoven, The Netherlands
| | - Robert Balshaw
- British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada
- University of British Columbia, Vancouver, British Columbia, Canada
- Simon Fraser University, Burnaby, British Columbia, Canada
| | - Sophie Lavigne
- Institut universitaire de cardiologie et pneumologie de Québec, Québec, Québec, Canada
| | - Martin Petric
- British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada
- University of British Columbia, Vancouver, British Columbia, Canada
| | - Marion Koopmans
- Laboratory for Infectious Disease Research, Diagnostics and Screening, Centre for Infectious Disease Control (CIDC), Rijksinstituut voor Volksgezondheid en Milieu (RIVM) [National Institute of Public Health and the Environment], Bilthoven, The Netherlands
- Viroscience Department, Erasmus MC, Rotterdam, The Netherlands
| | - Guy Boivin
- Centre Hospitalier Universitaire de Québec [University Hospital Centre of Québec], Québec, Canada
- Laval University, Québec, Canada
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Lan YC, Su MC, Chen CH, Huang SH, Chen WL, Tien N, Lin CW. Epidemiology of pandemic influenza A/H1N1 virus during 2009-2010 in Taiwan. Virus Res 2013; 177:46-54. [PMID: 23886669 DOI: 10.1016/j.virusres.2013.07.007] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2013] [Revised: 06/14/2013] [Accepted: 07/11/2013] [Indexed: 11/15/2022]
Abstract
Outbreak of swine-origin influenza A/H1N1 virus (pdmH1N1) occurred in 2009. Taiwanese authorities implemented nationwide vaccinations with pdmH1N1-specific inactivated vaccine as of November 2009. This study evaluates prevalence, HA phylogenetic relationship, and transmission dynamic of influenza A and B viruses in Taiwan in 2009-2010. Respiratory tract specimens were analyzed for influenza A and B viruses. The pdmH1N1 peaked in November 2009, was predominant from August 2009 to January 2010, then sharply dropped in February 2010. Significant prevalence peaks of influenza B in April-June of 2010 and H3N2 virus in July and August were observed. Highest percentage of pdmH1N1- and H3N2-positive cases appeared among 11-15-year-olds; influenza B-positive cases were dominant among those 6-10 years old. Maximum likelihood phylogenetic trees showed 11 unique clusters of pdmH1N1, seasonal H3N2 influenza A and B viruses, as well as transmission clusters and mixed infections of influenza strains in Taiwan. The 2009 pdmH1N1 virus was predominant in Taiwan from August 2009 to January 2010; seasonal H3N2 influenza A and B viruses exhibited small prevalence peaks after nationwide vaccinations. Phylogenetic evidence indicated transmission clusters and multiple independent clades of co-circulating influenza A and B strains in Taiwan.
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Affiliation(s)
- Yu-Ching Lan
- Department of Health Risk Management, School of Public, China Medical University, Taichung, Taiwan
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Kushwaha AS, Teli P, Mahen A. Outbreak of Influenza (H1N1) amongst children in a residential school. Med J Armed Forces India 2013; 70:274-6. [PMID: 25378783 DOI: 10.1016/j.mjafi.2013.01.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2012] [Accepted: 01/01/2013] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND An outbreak of pandemic Influenza H1N1 occurred from 13 Feb to 20 Feb 2010 in a residential school at Belgaum, India. METHODS On report of sudden increase in number of students reporting sick with symptoms suggestive of flu like illness, an investigation was launched to detect the source of infection and to control the spread of infection amongst those not affected. Six random samples of throat from the initial cluster were collected and RT-PCR was done to confirm the diagnosis. The outbreak in this institution was effectively controlled by standard preventive & control measures in the absence of vaccine. RESULT In a school of 335 children, 96 cases of Influenza like illness possibly resulting from pH1N1 (2009) were reported with an attack rate of 28.6%. Out of a total of 96 cases reported, 73 (76%) were hospitalized and 23 treated as outdoor patients. Serogroup A of Influenza H1N1 pandemic was identified to be the agent responsible for this outbreak as 06 random samples drawn from initial cluster tested positive on RT-PCR. A visit to an exhibition in the city was possibly the source of exposure amongst the children. CONCLUSION An outbreak of Influenza H1N1 infection amongst students in a residential public School was found to be linked to a visit to an exhibition following which the secondary transmission led to further occurrence of cases.
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Affiliation(s)
- A S Kushwaha
- Classified Specialist (Community Medicine), ADH HQ 16 Corps, C/O 56 APO, India
| | - Prabhakar Teli
- Commanding Officer, Station Health Organization, Babina, India
| | - Ajoy Mahen
- Professor & Head, Department of Community Medicine, Armed Forces Medical College, Pune 40, India
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Enanoria WTA, Crawley AW, Tseng W, Furnish J, Balido J, Aragón TJ. The epidemiology and surveillance response to pandemic influenza A (H1N1) among local health departments in the San Francisco Bay Area. BMC Public Health 2013; 13:276. [PMID: 23530722 PMCID: PMC3681650 DOI: 10.1186/1471-2458-13-276] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2012] [Accepted: 03/07/2013] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Public health surveillance and epidemiologic investigations are critical public health functions for identifying threats to the health of a community. Very little is known about how these functions are conducted at the local level. The purpose of the Epidemiology Networks in Action (EpiNet) Study was to describe the epidemiology and surveillance response to the 2009 pandemic influenza A (H1N1) by city and county health departments in the San Francisco Bay Area in California. The study also documented lessons learned from the response in order to strengthen future public health preparedness and response planning efforts in the region. METHODS In order to characterize the epidemiology and surveillance response, we conducted key informant interviews with public health professionals from twelve local health departments in the San Francisco Bay Area. In order to contextualize aspects of organizational response and performance, we recruited two types of key informants: public health professionals who were involved with the epidemiology and surveillance response for each jurisdiction, as well as the health officer or his/her designee responsible for H1N1 response activities. Information about the organization, data sources for situation awareness, decision-making, and issues related to surge capacity, continuity of operations, and sustainability were collected during the key informant interviews. Content and interpretive analyses were conducted using ATLAS.ti software. RESULTS The study found that disease investigations were important in the first months of the pandemic, often requiring additional staff support and sometimes forcing other public health activities to be put on hold. We also found that while the Incident Command System (ICS) was used by all participating agencies to manage the response, the manner in which it was implemented and utilized varied. Each local health department (LHD) in the study collected epidemiologic data from a variety of sources, but only case reports (including hospitalized and fatal cases) and laboratory testing data were used by all organizations. While almost every LHD attempted to collect school absenteeism data, many respondents reported problems in collecting and analyzing these data. Laboratory capacity to test influenza specimens often aided an LHD's ability to conduct disease investigations and implement control measures, but the ability to test specimens varied across the region and even well-equipped laboratories exceeded their capacity. As a whole, the health jurisdictions in the region communicated regularly about key decision-making (continued on next page) (continued from previous page) related to the response, and prior regional collaboration on pandemic influenza planning helped to prepare the region for the novel H1N1 influenza pandemic. The study did find, however, that many respondents (including the majority of epidemiologists interviewed) desired an increase in regional communication about epidemiology and surveillance issues. CONCLUSION The study collected information about the epidemiology and surveillance response among LHDs in the San Francisco Bay Area that has implications for public health preparedness and emergency response training, public health best practices, regional public health collaboration, and a perceived need for information sharing.
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Affiliation(s)
- Wayne TA Enanoria
- Division of Epidemiology, University of California at Berkeley, Berkeley, California, USA
- Center for Infectious Diseases and Emergency Readiness, University of California at Berkeley, Berkeley, California, USA
| | - Adam W Crawley
- Center for Infectious Diseases and Emergency Readiness, University of California at Berkeley, Berkeley, California, USA
| | - Winston Tseng
- Health Research for Action, University of California at Berkeley, Berkeley, California, USA
| | - Jasmine Furnish
- Center for Infectious Diseases and Emergency Readiness, University of California at Berkeley, Berkeley, California, USA
| | - Jeannie Balido
- Center for Infectious Diseases and Emergency Readiness, University of California at Berkeley, Berkeley, California, USA
| | - Tomás J Aragón
- Division of Epidemiology, University of California at Berkeley, Berkeley, California, USA
- Center for Infectious Diseases and Emergency Readiness, University of California at Berkeley, Berkeley, California, USA
- , San Francisco Department of Public Health, San Francisco, California, USA
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Khaokham CB, Selent M, Loustalot FV, Zarecki SM, Harrington D, Hoke E, Faix DJ, Ortiguerra R, Alvarez B, Almond N, McMullen K, Cadwell B, Uyeki TM, Blair PJ, Waterman SH. Seroepidemiologic investigation of an outbreak of pandemic influenza A H1N1 2009 aboard a US Navy vessel--San Diego, 2009. Influenza Other Respir Viruses 2013; 7:791-8. [PMID: 23496798 PMCID: PMC5781214 DOI: 10.1111/irv.12100] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/03/2013] [Indexed: 11/28/2022] Open
Abstract
Background During summer 2009, a US Navy ship experienced an influenza‐like illness outbreak with 126 laboratory‐confirmed cases of pandemic influenza A (H1N1) 2009 virus among the approximately 2000‐person crew. Methods During September 24–October 9, 2009, a retrospective seroepidemiologic investigation was conducted to characterize the outbreak. We administered questionnaires, reviewed medical records, and collected post‐outbreak sera from systematically sampled crewmembers. We used real‐time reverse transcription‐PCR or microneutralization assays to detect evidence of H1N1 virus infection. Results Retrospective serologic data demonstrated that the overall H1N1 virus infection attack rate was 32%. Weighted H1N1 virus attack rates were higher among marines (37%), junior‐ranking personnel (34%), and persons aged 19–24 years (36%). In multivariable analysis, a higher risk of illness was found for women versus men (odds ratio [OR] = 2·2; 95% confidence interval [CI]: 1·1–4·4), marines versus navy personnel (OR = 1·7; 95% CI, 1·0–2·9), and those aged 19–24 versus ≥35 years (OR = 3·9; 95% CI, 1·2–12·8). Fifty‐three percent of infected persons did not recall respiratory illness symptoms. Among infected persons, only 35% met criteria for acute respiratory illness and 11% for influenza‐like illness. Conclusions Approximately half of H1N1 infections were asymptomatic, and thus, the attack rate was higher than estimated by clinical illness alone. Enhanced infection control measures including pre‐embarkation illness screening, improved self‐reporting of illness, isolation of ill and quarantine of exposed contacts, and prompt antiviral chemoprophylaxis and treatment might be useful in controlling shipboard influenza outbreaks.
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Affiliation(s)
- Christina B Khaokham
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA, USA.
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Mahmud SM, Van Caeseele P, Hammond G, Kurbis C, Hilderman T, Elliott L. No association between 2008-09 influenza vaccine and influenza A(H1N1)pdm09 virus infection, Manitoba, Canada, 2009. Emerg Infect Dis 2013; 18:801-10. [PMID: 22516189 PMCID: PMC3358049 DOI: 10.3201/eid1805.111596] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Receipt of seasonal inactivated trivalent vaccine neither increased nor decreased the risk for pandemic influenza virus infection. We conducted a population-based study in Manitoba, Canada, to investigate whether use of inactivated trivalent influenza vaccine (TIV) during the 2008–09 influenza season was associated with subsequent infection with influenza A(H1N1)pdm09 virus during the first wave of the 2009 pandemic. Data were obtained from a provincewide population-based immunization registry and laboratory-based influenza surveillance system. The test-negative case–control study included 831 case-patients with confirmed influenza A(H1N1)pdm09 virus infection and 2,479 controls, participants with test results negative for influenza A and B viruses. For the association of TIV receipt with influenza A(H1N1)pdm09 virus infection, the fully adjusted odds ratio was 1.0 (95% CI 0.7–1.4). Among case-patients, receipt of 2008–09 TIV was associated with a statistically nonsignificant 49% reduction in risk for hospitalization. In agreement with study findings outside Canada, our study in Manitoba indicates that the 2008–09 TIV neither increased nor decreased the risk for infection with influenza A(H1N1)pdm09 virus.
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Uchida M, Tsukahara T, Kaneko M, Washizuka S, Kawa S. Evaluation of factors affecting variations in influenza A/H1N1 history in university students, Japan. J Infect Chemother 2013; 19:665-72. [PMID: 23325064 DOI: 10.1007/s10156-012-0540-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2012] [Accepted: 12/16/2012] [Indexed: 11/30/2022]
Abstract
Although the natural history of H1N1 has been found to vary among patients, little is known about the factors that affect these variations. Infected patients with an extended infection history may shed virus longer and spread infection. To further clarify these variations, we evaluated the natural history of H1N1 infection in 324 university students using a descriptive epidemiological method and analyzed factors affecting the natural history of infection. The median times from infection to fever development and from fever development to cure were 2 days (range 0-8 days) and 5 days (range 1-12 days), respectively, and the median time not attending classes was 5 days (range, 1-13 days). Variations in H1N1 natural history were associated with both environmental and individual factors, including route of infection, grade, gender, epidemic period, respiratory and gastrointestinal symptoms and headache. Steps affecting these factors may help control variations in H1N1 natural history and may enhance infection control measures.
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Affiliation(s)
- Mitsuo Uchida
- Center for Health, Safety and Environmental Management, Shinshu University, 3-1-1 Asahi, Matsumoto, 390-8621, Japan.
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Ravert RD, Fu LY, Zimet GD. Reasons for Low Pandemic H1N1 2009 Vaccine Acceptance within a College Sample. Adv Prev Med 2012; 2012:242518. [PMID: 23227350 PMCID: PMC3514795 DOI: 10.1155/2012/242518] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2012] [Accepted: 10/22/2012] [Indexed: 11/17/2022] Open
Abstract
This study examined health beliefs associated with novel influenza A (H1N1) immunization among US college undergraduates during the 2009-2010 pandemic. Undergraduates (ages 18-24 years) from a large Midwestern University were invited to complete an online survey during March, 2010, five months after H1N1 vaccines became available. Survey items measured H1N1 vaccine history and H1N1-related attitudes based on the health belief literature. Logistic regression was used to identify attitudes associated with having received an H1N1 vaccine, and thematic analysis of student comments was conducted to further understand influences on vaccine decisions. Among the 296 students who participated in the survey, 15.2% reported having received an H1N1 vaccine. In regression analysis, H1N1 immunization was associated with seasonal flu vaccine history, perceived vaccine effectiveness, perceived obstacles to vaccination, and vaccine safety concerns. Qualitative results illustrate the relationship of beliefs to vaccine decisions, particularly in demonstrating that students often held concerns that vaccine could cause H1N1 or side effects. Vaccine safety, efficacy, and obstacles to immunization were major considerations in deciding whether to accept the H1N1 pandemic vaccine. Therefore, focusing on those aspects might be especially useful in future vaccine efforts within the college population.
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Affiliation(s)
- Russell D. Ravert
- Department of Human Development & Family Studies, University of Missouri, Columbia, MO 65211, USA
| | - Linda Y. Fu
- Goldberg Center for Community Pediatric Health, Children's National Medical Center, Washington, DC 20010, USA
| | - Gregory D. Zimet
- Section of Adolescent Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
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van Riet E, Ainai A, Suzuki T, Hasegawa H. Mucosal IgA responses in influenza virus infections; thoughts for vaccine design. Vaccine 2012; 30:5893-900. [DOI: 10.1016/j.vaccine.2012.04.109] [Citation(s) in RCA: 83] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2012] [Accepted: 04/20/2012] [Indexed: 10/28/2022]
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Gao Y, Wen Z, Dong K, Zhong G, Wang X, Bu Z, Chen H, Ye L, Yang C. Characterization of immune responses induced by immunization with the HA DNA vaccines of two antigenically distinctive H5N1 HPAIV isolates. PLoS One 2012; 7:e41332. [PMID: 22859976 PMCID: PMC3409192 DOI: 10.1371/journal.pone.0041332] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2011] [Accepted: 06/25/2012] [Indexed: 12/24/2022] Open
Abstract
The evolution of the H5N1 highly pathogenic avian influenza virus (HPAIV) has resulted in high sequence variations and diverse antigenic properties in circulating viral isolates. We investigated immune responses induced by HA DNA vaccines of two contemporary H5N1 HPAIV isolates, A/bar-headed goose/Qinghai/3/2005 (QH) and A/chicken/Shanxi/2/2006 (SX) respectively, against the homologous as well as the heterologous virus isolate for comparison. Characterization of antibody responses induced by immunization with QH-HA and SX-HA DNA vaccines showed that the two isolates are antigenically distinctive. Interestingly, after immunization with the QH-HA DNA vaccine, subsequent boosting with the SX-HA DNA vaccine significantly augmented antibody responses against the QH isolate but only induced low levels of antibody responses against the SX isolate. Conversely, after immunization with the SX-HA DNA vaccine, subsequent boosting with the QH-HA DNA vaccine significantly augmented antibody responses against the SX isolate but only induced low levels of antibody responses against the QH isolate. In contrast to the antibody responses, cross-reactive T cell responses are readily detected between these two isolates at similar levels. These results indicate the existence of original antigenic sin (OAS) between concurrently circulating H5N1 HPAIV strains, which may need to be taken into consideration in vaccine development against the potential H5N1 HPAIV pandemic.
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MESH Headings
- Adaptive Immunity
- Amino Acid Sequence
- Animals
- Antibodies, Viral/blood
- Antigens, Viral/biosynthesis
- Antigens, Viral/genetics
- Antigens, Viral/immunology
- Chickens
- Epitopes, T-Lymphocyte/chemistry
- Epitopes, T-Lymphocyte/immunology
- Female
- Geese
- HeLa Cells
- Hemagglutinins, Viral/biosynthesis
- Hemagglutinins, Viral/genetics
- Hemagglutinins, Viral/immunology
- Humans
- Immunization, Secondary
- Influenza A Virus, H5N1 Subtype/genetics
- Influenza A Virus, H5N1 Subtype/immunology
- Influenza Vaccines/administration & dosage
- Influenza Vaccines/genetics
- Influenza Vaccines/immunology
- Influenza in Birds/immunology
- Influenza in Birds/prevention & control
- Influenza in Birds/virology
- Mice
- Mice, Inbred BALB C
- T-Lymphocytes/immunology
- Vaccination
- Vaccines, DNA/administration & dosage
- Vaccines, DNA/genetics
- Vaccines, DNA/immunology
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Affiliation(s)
- Yulong Gao
- National Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin, People’s Republic of China
- Department of Microbiology and Immunology and Emory Vaccine Center, Emory University School of Medicine, Atlanta, Georgia, United States of America
| | - Zhiyuan Wen
- National Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin, People’s Republic of China
- Department of Microbiology and Immunology and Emory Vaccine Center, Emory University School of Medicine, Atlanta, Georgia, United States of America
| | - Ke Dong
- Department of Microbiology and Immunology and Emory Vaccine Center, Emory University School of Medicine, Atlanta, Georgia, United States of America
- Central Laboratory, Tangdu Hospital, Fourth Military Medical University, Xi’an, People’s Republic of China
| | - Gongxun Zhong
- National Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin, People’s Republic of China
| | - Xiaomei Wang
- National Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin, People’s Republic of China
| | - Zhigao Bu
- National Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin, People’s Republic of China
| | - Hualan Chen
- National Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin, People’s Republic of China
| | - Ling Ye
- Department of Microbiology and Immunology and Emory Vaccine Center, Emory University School of Medicine, Atlanta, Georgia, United States of America
| | - Chinglai Yang
- Department of Microbiology and Immunology and Emory Vaccine Center, Emory University School of Medicine, Atlanta, Georgia, United States of America
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Chowell G, Echevarría-Zuno S, Viboud C, Simonsen L, Miller MA, Fernández-Gárate I, González-Bonilla C, Borja-Aburto VH. Epidemiological characteristics and underlying risk factors for mortality during the autumn 2009 pandemic wave in Mexico. PLoS One 2012; 7:e41069. [PMID: 22815917 PMCID: PMC3397937 DOI: 10.1371/journal.pone.0041069] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2012] [Accepted: 06/17/2012] [Indexed: 01/04/2023] Open
Abstract
Background Elucidating the role of the underlying risk factors for severe outcomes of the 2009 A/H1N1 influenza pandemic could be crucial to define priority risk groups in resource-limited settings in future pandemics. Methods We use individual-level clinical data on a large series of ARI (acute respiratory infection) hospitalizations from a prospective surveillance system of the Mexican Social Security medical system to analyze clinical features at presentation, admission delays, selected comorbidities and receipt of seasonal vaccine on the risk of A/H1N1-related death. We considered ARI hospitalizations and inpatient-deaths, and recorded demographic, geographic, and medical information on individual patients during August-December, 2009. Results Seasonal influenza vaccination was associated with a reduced risk of death among A/H1N1 inpatients (OR = 0.43 (95% CI: 0.25, 0.74)) after adjustment for age, gender, geography, antiviral treatment, admission delays, comorbidities and medical conditions. However, this result should be interpreted with caution as it could have been affected by factors not directly measured in our study. Moreover, the effect of antiviral treatment against A/H1N1 inpatient death did not reach statistical significance (OR = 0.56 (95% CI: 0.29, 1.10)) probably because only 8.9% of A/H1N1 inpatients received antiviral treatment. Moreover, diabetes (OR = 1.6) and immune suppression (OR = 2.3) were statistically significant risk factors for death whereas asthmatic persons (OR = 0.3) or pregnant women (OR = 0.4) experienced a reduced fatality rate among A/H1N1 inpatients. We also observed an increased risk of death among A/H1N1 inpatients with admission delays >2 days after symptom onset (OR = 2.7). Similar associations were also observed for A/H1N1-negative inpatients. Conclusions Geographical variation in identified medical risk factors including prevalence of diabetes and immune suppression may in part explain between-country differences in pandemic mortality burden. Furthermore, access to care including hospitalization without delay and antiviral treatment and are also important factors, as well as vaccination coverage with the 2008–09 trivalent inactivated influenza vaccine.
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Affiliation(s)
- Gerardo Chowell
- Division of Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America.
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Cowling BJ, Ng S, Ma ESK, Fang VJ, So HC, Wai W, Cheng CKY, Wong JY, Chan KH, Ip DKM, Chiu SS, Peiris JSM, Leung GM. Protective Efficacy Against Pandemic Influenza of Seasonal Influenza Vaccination in Children in Hong Kong: A Randomized Controlled Trial. Clin Infect Dis 2012; 55:695-702. [DOI: 10.1093/cid/cis518] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
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Hellenbrand W, Jorgensen P, Schweiger B, Falkenhorst G, Nachtnebel M, Greutélaers B, Traeder C, Wichmann O. Prospective hospital-based case-control study to assess the effectiveness of pandemic influenza A(H1N1)pdm09 vaccination and risk factors for hospitalization in 2009-2010 using matched hospital and test-negative controls. BMC Infect Dis 2012; 12:127. [PMID: 22650369 PMCID: PMC3464893 DOI: 10.1186/1471-2334-12-127] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2011] [Accepted: 05/31/2012] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND We performed a case-control study to estimate vaccine effectiveness (VE) for prevention of hospitalization due to pandemic influenza A(H1N1)pdm09 (pH1N1) and to identify risk factors for pH1N1 and acute respiratory infection (ARI) in 10 hospitals in Berlin from December 2009 to April 2010. METHODS Cases were patients aged 18-65 years with onset of ARI ≤10 days before admission testing positive for pH1N1 by PCR performed on nasal and throat swabs or by serological testing. Cases were compared to (1) matched hospital controls with acute surgical, traumatological or other diagnoses matched on age, sex and vaccination probability, and (2) ARI patients testing negative for pH1N1. Additionally, ARI cases were compared to matched hospital controls. A standardized interview and chart review elicited demographic and clinical data as well as potential risk factors for pH1N1/ARI. VE was estimated by 1-(Odds ratio) for pH1N1-vaccination ≥10 days before symptom onset using exact logistic regression analysis. RESULTS Of 177 ARI cases recruited, 27 tested pH1N1 positive. A monovalent AS03-adjuvanted pH1N1 vaccine was the only pandemic vaccine type identified among cases and controls (vaccination coverage in control group 1 and 2: 15% and 5.9%). The only breakthrough infections were observed in 2 of 3 vaccinated HIV positive pH1N1 patients. After exclusion of HIV positive participants, VE was 96% (95%CI: 26-100%) in the matched multivariate analysis and 46% (95%CI: -376-100%) in the test-negative analysis. Exposure to children in the household was independently associated with hospitalization for pH1N1 and ARI. CONCLUSIONS Though limited by low vaccination coverage and number of pH1N1 cases, our results suggest a protective effect of the AS03-adjuvanted pH1N1 vaccine for the prevention of pH1N1 hospitalization. The use of hospital but not test-negative controls showed a statistically protective effect of pH1N1-vaccination and permitted the integrated assessment of risk factors for pH1N1-infection. To increase statistical power and to permit stratified analyses (e.g. VE for specific risk groups), the authors suggest pooling of future studies assessing effectiveness of influenza vaccines for prevention of severe disease from different centres.
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Affiliation(s)
- Wiebke Hellenbrand
- Immunization Unit, Department of Infectious Disease Epidemiology, Robert Koch Institute, DGZ-Ring 1, 13086 Berlin, Germany.
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Seale H, Mak JPI, Razee H, MacIntyre CR. Examining the knowledge, attitudes and practices of domestic and international university students towards seasonal and pandemic influenza. BMC Public Health 2012; 12:307. [PMID: 22537252 PMCID: PMC3447694 DOI: 10.1186/1471-2458-12-307] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2011] [Accepted: 04/26/2012] [Indexed: 11/29/2022] Open
Abstract
Background Prior to the availability of the specific pandemic vaccine, strategies to mitigate the impact of the disease typically involved antiviral treatment and “non-pharmaceutical” community interventions. However, compliance with these strategies is linked to risk perceptions, perceived severity and perceived effectiveness of the strategies. In 2010, we undertook a study to examine the knowledge, attitudes, risk perceptions, practices and barriers towards influenza and infection control strategies amongst domestic and international university students. Methods A study using qualitative methods that incorporated 20 semi-structured interviews was undertaken with domestic and international undergraduate and postgraduate university students based at one university in Sydney, Australia. Participants were invited to discuss their perceptions of influenza (seasonal vs. pandemic) in terms of perceived severity and impact, and attitudes towards infection control measures including hand-washing and the use of social distancing, isolation or cough etiquette. Results While participants were generally knowledgeable about influenza transmission, they were unable to accurately define what ‘pandemic influenza’ meant. While avian flu or SARS were mistaken as examples of past pandemics, almost all participants were able to associate the recent “swine flu” situation as an example of a pandemic event. Not surprisingly, it was uncommon for participants to identify university students as being at risk of catching pandemic influenza. Amongst those interviewed, it was felt that ‘students’ were capable of fighting off any illness. The participant’s nominated hand washing as the most feasible and acceptable compared with social distancing and mask use. Conclusions Given the high levels of interaction that occurs in a university setting, it is really important that students are informed about disease transmission and about risk of infection. It may be necessary to emphasize that pandemic influenza could pose a real threat to them, that it is important to protect oneself from infection and that infection control measures can be effective.
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Affiliation(s)
- Holly Seale
- School of Public Health and Community Medicine, Faculty of Medicine, The University of New South Wales, South Wales, Australia.
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Cheng VCC, To KKW, Tse H, Hung IFN, Yuen KY. Two years after pandemic influenza A/2009/H1N1: what have we learned? Clin Microbiol Rev 2012; 25:223-63. [PMID: 22491771 PMCID: PMC3346300 DOI: 10.1128/cmr.05012-11] [Citation(s) in RCA: 154] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
The world had been anticipating another influenza pandemic since the last one in 1968. The pandemic influenza A H1N1 2009 virus (A/2009/H1N1) finally arrived, causing the first pandemic influenza of the new millennium, which has affected over 214 countries and caused over 18,449 deaths. Because of the persistent threat from the A/H5N1 virus since 1997 and the outbreak of the severe acute respiratory syndrome (SARS) coronavirus in 2003, medical and scientific communities have been more prepared in mindset and infrastructure. This preparedness has allowed for rapid and effective research on the epidemiological, clinical, pathological, immunological, virological, and other basic scientific aspects of the disease, with impacts on its control. A PubMed search using the keywords "pandemic influenza virus H1N1 2009" yielded over 2,500 publications, which markedly exceeded the number published on previous pandemics. Only representative works with relevance to clinical microbiology and infectious diseases are reviewed in this article. A significant increase in the understanding of this virus and the disease within such a short amount of time has allowed for the timely development of diagnostic tests, treatments, and preventive measures. These findings could prove useful for future randomized controlled clinical trials and the epidemiological control of future pandemics.
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Affiliation(s)
- Vincent C C Cheng
- Department of Microbiology, Queen Mary Hospital, Hong Kong Special Administrative Region, China
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Impacts on influenza A(H1N1)pdm09 infection from cross-protection of seasonal trivalent influenza vaccines and A(H1N1)pdm09 vaccines: systematic review and meta-analyses. Vaccine 2012; 30:3209-22. [PMID: 22387221 DOI: 10.1016/j.vaccine.2012.02.048] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2011] [Revised: 02/04/2012] [Accepted: 02/20/2012] [Indexed: 01/07/2023]
Abstract
Cross-protection by seasonal trivalent influenza vaccines (TIVs) against pandemic influenza A H1N1 2009 (now known as A[H1N1]pdm09) infection is controversial; and the vaccine effectiveness (VE) of A(H1N1)pdm09 vaccines has important health-policy implications. Systematic reviews and meta-analyses are needed to assess the impacts of both seasonal TIVs and A(H1N1)pdm09 vaccines against A(H1N1)pdm09.We did a systematic literature search to identify observational and/or interventional studies reporting cross-protection of TIV and A(H1N1)pdm09 VE from when the pandemic started (2009) until July 2011. The studies fulfilling inclusion criteria were meta-analysed. For cross-protection and VE, respectively, we stratified by vaccine type, study design and endpoint. Seventeen studies (104,781 subjects) and 10 studies (2,906,860 subjects), respectively, reported cross-protection of seasonal TIV and VE of A(H1N1)pdm09 vaccines; six studies (17,229 subjects) reported on both. Thirteen studies (95,903 subjects) of cross-protection, eight studies (859,461 subjects) of VE, and five studies (9,643 subjects) of both were meta-analysed and revealed: (1) cross-protection for confirmed illness was 19% (95% confident interval=13-42%) based on 13 case-control studies with notable heterogeneity. A higher cross-protection of 34% (9-52%) was found in sensitivity analysis (excluding five studies with moderate/high risk of bias). Further exclusion of studies that recruited early in the pandemic (when non-recipients of TIV were more likely to have had non-pandemic influenza infection that may have been cross-protective) dramatically reduced heterogeneity. One RCT reported cross-protection of 38% (19-53%) for confirmed illness. One case-control study reported cross-protection of 50% (40-59%) against hospitalisation. (2) VE of A(H1N1)pdm09 for confirmed illness was 86% (73-93%) based on 11 case-control studies and 79% (22-94%) based on two cohort studies; VE against medically-attended ILI was 32% (8-50%) in one cohort study. TIVs provided moderate cross-protection against both laboratory-confirmed A(H1N1)pdm09 illness (based on eight case-control studies with low risk of bias and one RCT) and also hospitalisation. A finding of increased risk from seasonal vaccine was limited to cases recruited early in the pandemic. A(H1N1)pdm09 vaccines were highly effective against confirmed A(H1N1)pdm09 illness. Although cross-protection was less than the direct effect of strain-specific vaccination against A(H1N1)pdm09, TIV was generally beneficial before A(H1N1)pdm09 vaccine was available.
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Abstract
Pandemic influenza A (H1N1) (pH1N1) was first identified in North America in early 2009. The pandemic flu outbreak during the 2009–2010 influenza season demonstrated how rapidly a new strain of flu can emerge and spread. Vaccination is the most effective method to prevent influenza, and vaccination during a pandemic is critical in limiting morbidity and mortality. Unfortunately, reports of vaccination rates for pH1N1 vaccines during the 2009–2010 influenza season indicated low rates for various demographic groups, including pregnant women, health care workers, child care workers, college students, and the general public. Furthermore, when asked about perceptions of pH1N1 vaccines, respondents in a variety of studies from the pH1N1 pandemic indicated common and universal misconceptions about influenza vaccines, especially in regard to perceptions of need, efficacy and safety. Therefore, if vaccination rates are to increase, an important outcome especially during pandemics, the psychological characteristics underpinning perceptions of influenza vaccines need to be understood better.
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Vilella A, Serrano B, Marcos MA, Serradesanferm A, Mensa J, Hayes E, Anton A, Rios J, Pumarola T, Trilla A. Pandemic influenza A(H1N1) outbreak among a group of medical students who traveled to the Dominican Republic. J Travel Med 2012; 19:9-14. [PMID: 22221806 DOI: 10.1111/j.1708-8305.2011.00580.x] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
BACKGROUND From the beginning of the influenza pandemic until the time the outbreak described here was detected, 77,201 cases of pandemic influenza A(H1N1) with 332 deaths had been reported worldwide, mostly in the United States and Mexico. All of the cases reported in Spain until then had a recent history of travel to Mexico, the Dominican Republic, or Chile. We describe an outbreak of influenza among medical students who traveled from Spain to the Dominican Republic in June 2009. METHODS We collected diagnostic samples and clinical histories from consenting medical students who had traveled to the Dominican Republic and from their household contacts after their return to Spain. RESULTS Of 113 students on the trip, 62 (55%) developed symptoms; 39 (45%) of 86 students tested had laboratory evidence of influenza A(H1N1) infection. Most students developed symptoms either just before departure from the Dominican Republic or within days of returning to Spain. The estimated secondary attack rate of influenza-like illness among residential contacts of ill students after return to Spain was 2.1%. CONCLUSIONS The attack rate of influenza A(H1N1) can vary widely depending on the circumstances of exposure. We report a high attack rate among a group of traveling medical students but a much lower secondary attack rate among their contacts after return from the trip. These findings may aid the development of recommendations to prevent influenza.
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Affiliation(s)
- Anna Vilella
- Preventive Medicine and Epidemiology Department, Hospital Clinic, Barcelona, Spain
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Ramsey MA, Marczinski CA. College students' perceptions of H1N1 flu risk and attitudes toward vaccination. Vaccine 2011; 29:7599-601. [PMID: 21827812 DOI: 10.1016/j.vaccine.2011.07.130] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2011] [Revised: 07/26/2011] [Accepted: 07/27/2011] [Indexed: 10/17/2022]
Abstract
College students are highly susceptible to the H1N1 virus, yet previous studies suggest that college students perceive themselves at low risk for the flu. We surveyed 514 undergraduates to assess their perceptions of H1N1 flu risk and opinions about flu vaccines. A third of respondents stated that they were not at risk of getting the H1N1 flu because they were young. Responses indicated a distrust of the safety and effectiveness of influenza vaccinations; only 15.8% of participants planned on receiving H1N1 vaccination. Top reasons for refusing the H1N1 vaccine included questioning vaccine safety and effectiveness, and concerns about potential serious and/or benign side effects. Top reasons for H1N1 vaccination acceptance included receiving a doctor recommendation for the vaccine, having previously gotten a seasonal vaccine, and being at high-risk for influenza. Our findings suggest that college students are inaccurate in assessing their risk level and are unlikely to seek vaccinations.
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Affiliation(s)
- Meagan A Ramsey
- Department of Psychological Science, Northern Kentucky University, Highland Heights, KY 41099, USA
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Lim WY, Chen CHJ, Ma Y, Chen MIC, Lee VJM, Cook AR, Tan LWL, Flores Tabo N, Barr I, Cui L, Lin RTP, Leo YS, Chia KS. Risk factors for pandemic (H1N1) 2009 seroconversion among adults, Singapore, 2009. Emerg Infect Dis 2011; 17:1455-62. [PMID: 21801623 PMCID: PMC3381584 DOI: 10.3201/eid1708.101270] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
A total of 828 community-dwelling adults were studied during the course of the pandemic (H1N1) 2009 outbreak in Singapore during June-September 2009. Baseline blood samples were obtained before the outbreak, and 2 additional samples were obtained during follow-up. Seroconversion was defined as a >4-fold increase in antibody titers to pandemic (H1N1) 2009, determined by using hemagglutination inhibition. Men were more likely than women to seroconvert (mean adjusted hazards ratio [HR] 2.23, mean 95% confidence interval [CI] 1.26-3.93); Malays were more likely than Chinese to seroconvert (HR 2.67, 95% CI 1.04-6.91). Travel outside Singapore during the study period was associated with seroconversion (HR 1.76, 95% CI 1.11-2.78) as was use of public transport (HR 1.81, 95% CI 1.05-3.09). High baseline antibody titers were associated with reduced seroconversion. This study suggests possible areas for intervention to reduce transmission during future influenza outbreaks.
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Affiliation(s)
- Wei-Yen Lim
- National University of Singapore-Epidemiology and Public Health, Yong Loo Lin School of Medicine, Singapore.
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Muscatello DJ, Barr M, Thackway SV, Macintyre CR. Epidemiology of influenza-like illness during Pandemic (H1N1) 2009, New South Wales, Australia. Emerg Infect Dis 2011; 17:1240-7. [PMID: 21762578 PMCID: PMC3381394 DOI: 10.3201/eid1707.101173] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
To rapidly describe the epidemiology of influenza-like illness (ILI) during the 2009 winter epidemic of pandemic (H1N1) 2009 virus in New South Wales, Australia, we used results of a continuous population health survey. During July-September 2009, ILI was experienced by 23% of the population. Among these persons, 51% were unable to undertake normal duties for <3 days, 55% sought care at a general practice, and 5% went to a hospital. Factors independently associated with ILI were younger age, daily smoking, and obesity. Effectiveness of prepandemic seasonal vaccine was ?20%. The high prevalence of risk factors associated with a substantially increased risk for ILI deserves greater recognition.
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Affiliation(s)
- David J Muscatello
- New South Wales Department of Health, North Sydney, New South Wales, Australia
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Use of a web forum and an online questionnaire in the detection and investigation of an outbreak. Online J Public Health Inform 2011; 3:ojphi-03-1. [PMID: 23569598 PMCID: PMC3615775 DOI: 10.5210/ojphi.v3i1.3506] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
A campylobacteriosis outbreak investigation provides relevant examples of how two web-based technologies were used in an outbreak setting and potential reasons for their usefulness. A web forum aided in outbreak detection and provided contextual insights for hypothesis generation and questionnaire development. An online questionnaire achieved a high response rate and enabled rapid preliminary data analysis that allowed for a targeted environmental investigation. The usefulness of these tools may in part be attributed to the existence of an internet savvy, close-knit community. Given the right population, public health officials should consider web-based technologies, including web fora and online questionnaires as valuable tools in public health investigations.
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Lipsitch M, Finelli L, Heffernan RT, Leung GM, Redd SC. Improving the evidence base for decision making during a pandemic: the example of 2009 influenza A/H1N1. Biosecur Bioterror 2011; 9:89-115. [PMID: 21612363 PMCID: PMC3102310 DOI: 10.1089/bsp.2011.0007] [Citation(s) in RCA: 74] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2011] [Accepted: 04/25/2011] [Indexed: 12/14/2022]
Abstract
This article synthesizes and extends discussions held during an international meeting on "Surveillance for Decision Making: The Example of 2009 Pandemic Influenza A/H1N1," held at the Center for Communicable Disease Dynamics (CCDD), Harvard School of Public Health, on June 14 and 15, 2010. The meeting involved local, national, and global health authorities and academics representing 7 countries on 4 continents. We define the needs for surveillance in terms of the key decisions that must be made in response to a pandemic: how large a response to mount and which control measures to implement, for whom, and when. In doing so, we specify the quantitative evidence required to make informed decisions. We then describe the sources of surveillance and other population-based data that can presently--or in the future--form the basis for such evidence, and the interpretive tools needed to process raw surveillance data. We describe other inputs to decision making besides epidemiologic and surveillance data, and we conclude with key lessons of the 2009 pandemic for designing and planning surveillance in the future.
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MESH Headings
- Communicable Diseases, Emerging/epidemiology
- Communicable Diseases, Emerging/prevention & control
- Communicable Diseases, Emerging/transmission
- Communicable Diseases, Emerging/virology
- Data Collection
- Data Interpretation, Statistical
- Decision Making, Organizational
- Humans
- Influenza A Virus, H1N1 Subtype
- Influenza, Human/epidemiology
- Influenza, Human/prevention & control
- Influenza, Human/transmission
- Influenza, Human/virology
- Pandemics
- Population Surveillance
- Public Opinion
- Severity of Illness Index
- Vaccination/methods
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Affiliation(s)
- Marc Lipsitch
- Department of Epidemiology, Harvard School of Public Health, Harvard University, 677 Huntington Ave., Boston, MA 02115, USA.
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Guh A, Reed C, Gould LH, Kutty P, Iuliano D, Mitchell T, Dee D, Desai M, Siebold J, Silverman P, Massoudi M, Lynch M, Sotir M, Armstrong G, Swerdlow D. Transmission of 2009 pandemic influenza A (H1N1) at a Public University--Delaware, April-May 2009. Clin Infect Dis 2011; 52 Suppl 1:S131-7. [PMID: 21342885 DOI: 10.1093/cid/ciq029] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
We investigated the first documented university outbreak of the 2009 pandemic influenza A(H1N1) to identify factors associated with disease transmission. An online student survey was administered to assess risk factors for influenza-like illness (ILI), defined as fever with cough or sore throat. Of 6049 survey respondents, 567 (9%) experienced ILI during 27 March to 9 May 2009. Studying with an ill contact (adjusted risk ratios [aRR], 1.29; 95% confidence intervals [CI], 1.01-1.65) and caring for an ill contact (aRR, 1.51; CI, 1.14-2.01) any time during 27 March to 9 May were predictors for ILI. Respondents reported that 680 (6%) of 11,411 housemates were ill; living with an ill housemate was a predictor for ILI (RR, 1.38; CI, 1.04-1.83). Close contact or prolonged exposures to ill persons were likely associated with experiencing ILI. Self-protective measures should be promoted in university populations to mitigate transmission.
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Affiliation(s)
- Alice Guh
- Epidemic Intelligence Office, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
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Jhung MA, Swerdlow D, Olsen SJ, Jernigan D, Biggerstaff M, Kamimoto L, Kniss K, Reed C, Fry A, Brammer L, Gindler J, Gregg WJ, Bresee J, Finelli L. Epidemiology of 2009 pandemic influenza A (H1N1) in the United States. Clin Infect Dis 2011; 52 Suppl 1:S13-26. [PMID: 21342884 DOI: 10.1093/cid/ciq008] [Citation(s) in RCA: 118] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
In April 2009, the Centers for Disease Control and Prevention confirmed 2 cases of 2009 pandemic influenza A (H1N1) virus infection in children from southern California, marking the beginning of what would be the first influenza pandemic of the twenty-first century. This report describes the epidemiology of the 2009 H1N1 pandemic in the United States, including characterization of cases, fluctuations of disease burden over the course of a year, the age distribution of illness and severe outcomes, and estimation of the overall burden of disease.
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Affiliation(s)
- Michael A Jhung
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
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Iuliano AD, Dawood FS, Silk BJ, Bhattarai A, Copeland D, Doshi S, France AM, Jackson ML, Kennedy E, Loustalot F, Marchbanks T, Mitchell T, Averhoff F, Olsen SJ, Swerdlow DL, Finelli L. Investigating 2009 pandemic influenza A (H1N1) in US schools: what have we learned? Clin Infect Dis 2011; 52 Suppl 1:S161-7. [PMID: 21342889 DOI: 10.1093/cid/ciq032] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
US investigations of school-based outbreaks of 2009 pandemic influenza A (H1N1) virus infection characterized influenza-like illness (ILI) attack rates, transmission risk factors, and adherence to nonpharmaceutical interventions. We summarize seven school-based investigations conducted during April-June 2009 to determine what questions might be answered by future investigations. Surveys were administered 5-28 days after identification of the outbreaks, and participation rates varied among households (39-86%) and individuals (24-49%). Compared with adults (4%-10%) and children aged <4 years (2%-7%), elementary through university students had higher ILI attack rates (4%-32%). Large gatherings or close contact with sick persons were identified as transmission risk factors. More participants reported adherence to hygiene measures, but fewer reported adherence to isolation measures. Challenges included low participation and delays in survey initiation that potentially introduced bias. Although school-based investigations can increase our understanding of epidemiology and prevention strategy effectiveness, investigators should decide which objectives are most feasible, given timing and design constraints.
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Affiliation(s)
- A Danielle Iuliano
- Division of HIV AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA.
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