Assessing the use of hospital staff influenza-like absence (ILA) for enhancing hospital preparedness and national surveillance

BMC Infectious Diseases

Volumn 15, Issue 1, 2015, Pages

  Drumright, Lydia N ^a,b   Frost, Simon ^a   Elliot, Alex J ^c   Catchpole, Mike ^c   Pebody, Richard G ^c   Atkins, Mark ^d   Harrison, John ^d   Parker, Penny ^d   Holmes, Alison H ^b,d  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^b The National Institute for Health Research Health Protection Research Unit in Blood Borne and Sexually Transmitted Infections at University College London in partnership with UK Health Security Agency   (United Kingdom)

^c PUBLIC HEALTH ENGLAND   (United Kingdom)

^d IMPERIAL COLLEGE HEALTHCARE NHS TRUST   (United Kingdom)

Author keywords

Emergency preparedness; Epidemiology; Healthcare workers; Influenza; Informatics; Syndromic surveillance

Indexed keywords

ABSENTEEISM; ADOLESCENT; ADULT; ALGORITHM; ARTICLE; BAYES THEOREM; COMMON COLD; CONTROLLED STUDY; COUGHING; DISEASE COURSE; DISEASE SURVEILLANCE; FEASIBILITY STUDY; FLU LIKE SYNDROME; HEALTH CARE QUALITY; HEALTH CARE SYSTEM; HOSPITAL INFORMATION SYSTEM; HOSPITAL MANAGEMENT; HOSPITAL PATIENT; HOSPITAL PERSONNEL; HUMAN; INFLUENZA; INFLUENZA LIKE ABSENCE; LABORATORY TEST; MAJOR CLINICAL STUDY; MEDICAL INFORMATION; PREVENTIVE HEALTH SERVICE; PRIMARY MEDICAL CARE; PROGRAM EFFECTIVENESS; PUBLIC HEALTH PROBLEM; SEASONAL VARIATION; STATISTICAL MODEL; TIME SERIES ANALYSIS; CIVIL DEFENSE; EPIDEMIOLOGICAL MONITORING; FEMALE; INFLUENZA A VIRUS (H1N1); INFLUENZA, HUMAN; MALE; MIDDLE AGED; PRIMARY HEALTH CARE; PROSPECTIVE STUDY; STANDARDS; STATISTICS AND NUMERICAL DATA; TOTAL QUALITY MANAGEMENT; VACCINATION; YOUNG ADULT;

ABSENTEEISM; ADOLESCENT; ADULT; ALGORITHMS; CIVIL DEFENSE; EPIDEMIOLOGICAL MONITORING; FEMALE; HUMANS; INFLUENZA A VIRUS, H1N1 SUBTYPE; INFLUENZA, HUMAN; MALE; MIDDLE AGED; PERSONNEL, HOSPITAL; PRIMARY HEALTH CARE; PROSPECTIVE STUDIES; QUALITY IMPROVEMENT; VACCINATION; YOUNG ADULT;

EID: 84925851303     PISSN: None     EISSN: 14712334     Source Type: Journal    
DOI: 10.1186/s12879-015-0789-z     Document Type: Article

References (40)

1. Birrell PJ, Ketsetzis G, Gay NJ, Cooper BS, Presanis AM, Harris RJ, et al. Bayesian modeling to unmask and predict influenza A/H1N1pdm dynamics in London. Proc Natl Acad Sci. 2011;108:18238-43.
2. World Health Organisation. WHO global technical consultation: global standards and tools for influenza surveillance. Geneva: 2012. Accessible online at: http://www.who.int/influenza/resources/documents/INFSURVMANUAL.pdf.
3. Nicoll A, Brown C, Karcher F, Penttinen P, Hegermann-Lindencrone M, Villanueva S, et al. Developing pandemic preparedness in Europe in the 21st century: experience, evolution and next steps. Bull World Health Organ. 2012;90:311-7.
4. Needleman J, Buerhaus P, Mattke S, Stewart M, Zelevinsky K. Nurse-staffing levels and the quality of care in hospitals. New Engl J Med. 2002;346:1715-22.
5. Aiken LH, Clarke SP, Sloane DM, Sochalski J, Silber JH. Hospital nurse staffing and patient mortality, nurse burnout, and job dissatisfaction. JAMA. 2002;288:1987-93.
6. Health Protection Agency Real Time Surveillance Team. Influenza Syndromic Surveillance. Report. Birmingham: 2012. Accessible online at: https://www.gov.uk/government/collections/syndromic-surveillance-systems-and-analyses.
7. United States Department of Health and Human Services Centers for Disease Control and Prevention. Overview of Influenza Surveillance in the United States. 2014. Accessible online at: http://www.cdc.gov/flu/weekly/overview.htm.
8. Elliot AJ, Hughes HE, Hughes TC, Locker TE, Shannon T, Heyworth J, et al. Establishing an emergency department syndromic surveillance system to support the London 2012 Olympic and Paralympic Games. Emerge Med J. 2012;29:954-60.
9. Cooper DL, Verlander NQ, Elliot AJ, Joseph CA, Smith GE. Can syndromic thresholds provide early warning of national influenza outbreaks? J Public Health. 2009;31:17-25.
10. Presanis AM, Pebody RG, Paterson BJ, Tom BDM, Birrell PJ, Charlett A, et al. Changes in severity of 2009 pandemic A/H1N1 influenza in England: a Bayesian evidence synthesis. BMJ. 2011;343:d5408. doi:10.1136/bmj.d5408.
11. Evans B, Charlett A, Powers C, McLean E, Zhao H, Bermingham A, et al. Has estimation of numbers of cases of pandemic influenza H1N1 in England in 2009 provided a useful measure of the occurrence of disease? Influenza Other Respi Viruses. 2011;5:e504-12.
12. Haywood A. Flu watch Consortium -Community study of influenza transmission and immunity. 2012. Accessible online at: http://www.idrn.org/documents/events/presentations/pandemic/Andrew%20Hayward.pdf.
13. Razuri H, Romero C, Tinoco Y, Guezala MC, Ortiz E, Silva M, et al. Population-based active surveillance cohort studies for influenza: lessons from Peru. Bull World Health Organ. 2012;90:318-20.
14. Ross AM, Kai J, Salter R, Fleming DM, Ross J. Presentation with influenza-like illness in general practice: implications for use of neuraminidase inhibitors. Commun Dis Public Health. 2000;3:256-60.
15. Dailey L, Watkins RE, Plant AJ. Timeliness of data sources used for influenza surveillance. J Am Med Inform Assoc. 2007;14:626-31.
16. Carneiro HA, Mylonakis E. Google trends: a web-based tool for real-time surveillance of disease outbreaks. Clin Infect Dis. 2009;49:1557-64.
17. Corley C, Cook DJ, Mikler AR, Singh KP. Text and structural data mining of influenza mentions in web and social media. Int J Environ Res Public Health. 2010;7:596-615.
18. Broniatowski DA, Paul MJ, Dredze M. National and local influenza surveillance through twitter: An analysis of the 2012-2013 influenza epidemic. PLoS One. 2013;8:e83672.
19. Brooks-Pollock E, Tilston N, Edmunds WJ, Eames KT. Using an online survey of healthcare-seeking behaviour to estimate the magnitude and severity of the 2009 H1N1v influenza epidemic in England. BMC Infect Dis. 2011;11:68.
20. Lenaway DD, Ambler A. Evaluation of a school-based influenza surveillance system. Public Health Rep. 1995;110:333.
21. Besculides M, Heffernan R, Mostashari F, Weiss D. Evaluation of school absenteeism data for early outbreak detection, New York City. BMC Public Health. 2005;5:105.
22. Hay SI, George DB, Moyes CL, Brownstein JS. Big data opportunities for global infectious disease surveillance. PLoS Med. 2013;10:e1001413.
23. Virnig BA, McBean M. Administrative data for public health surveillance and planning. Annu Rev Public Health. 2001;22:213-30.
24. Overhage JM, Grannis S, McDonald CJ. A comparison of the completeness and timeliness of automated electronic laboratory reporting and spontaneous reporting of notifiable conditions. Am J Public Health. 2008;98:344.
25. Lazer DM, Kennedy R, King G, Vespignani A. The parable of Google Flu: Traps in big data analysis. 2014.
26. Höhle M, Riebler A. The R-Package 'surveillance'. SFB386 Discussion Paper 422. Department of Statistics, University of Munich; 2005. Accessible online at: http://www.stat.uni-muenchen.de/sfb386/papers/dsp/paper422.pdf.
27. Vega T, Lozano JE, Meerhoff T, Snacken R, Mott J, Ortiz de Lejarazu R, et al. Influenza surveillance in Europe: establishing epidemic thresholds by the Moving Epidemic Method. Influenza Other Respi Viruses. 2013;7:546-58.
28. R Developmental Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2012.
29. Höhle M. Surveillance: An R package for the monitoring of infectious diseases. Comput Stat. 2007;22:571-82.
30. Lozano Alonso JE. MEM: Moving Epidemic Method Package. R package version 1.4; 2014. http://CRAN.R-project.org/package=mem.
31. World Health Organisation. WHO Interim Global Epidemiological Surveillance Standards for Influenza (July 2012). Geneva: 2012. Accessible online at: http://www.who.int/influenza/resources/documents/INFSURVMANUAL.pdf.
32. Seto WH, Cowling BJ, Lam HS, Ching PT, To ML, Pittet D. Clinical and non-clinical healthcare workers faced a similar risk of acquiring, pandemic H1N1 infection. Clin Infect Dis. 2009;2011(53):280-3.
33. Kane RL, Shamliyan TA, Mueller C, Duval S, Wilt TJ. The association of registered nurse staffing levels and patient outcomes: systematic review and meta-analysis. Med Care. 2007;45:1195-204.
34. Jena AB, Baldwin DC, Daugherty SR, Meltzer DO, Arora VM. Presenteeism among resident physicians. JAMA. 2010;304:1166-8.
35. McKevitt C, Morgan M, Dundas R, Holland WW. Sickness absence and GÇÿworking throughGÇÖillness: a comparison of two professional groups. J Public Health. 1997;19:295-300.
36. Aronsson G, Gustafsson K, Dallner M. Sick but yet at work. An empirical study of sickness presenteeism. J Epidemiol Community Health. 2000;54:502-9.
37. Quenel P, Dab W, Hannoun C, Cohen JM. Sensitivity, specificity and predictive values of health service based indicators for the surveillance of influenza A epidemics. Int J Epidemiol. 1994;23:849-55.
38. Alexander R. Which is the world's biggest employer? BBC News Magazine edition; 2012. Accessible online at: http://www.bbc.co.uk/news/magazine-17429786.
39. Institute of Medicine. Crisis standards of care: a systems framework for catastrophic disaster response. Washington DC: National Academic Press; 2012.
40. Eames KTD, Brooks-Pollock E, Paolotti D, Perosa M, Gioannini C, Edmunds WJ. Rapid assessment of influenza vaccine effectiveness: analysis of an internet-based cohort. Epidemiol Infect. 2012;140:1309-15.