Surveillance Open Access
Like 0


Background: In 2009, an improved influenza surveillance system was implemented and weekly reporting to the World Health Organization on influenza-like illness (ILI) began. The goals of the surveillance system are to monitor and analyse the intensity of influenza activity, to provide timely information about circulating strains and to help in establishing preventive and control measures. In addition, the system is useful for comparative analysis of influenza data from Montenegro with other countries.

Aim: We aimed to evaluate the performance and usefulness of the Moving Epidemic Method (MEM), for use in the influenza surveillance system in Montenegro.

Methods: Historical ILI data from 2010/11 to 2017/18 influenza seasons were modelled with MEM. Epidemic threshold for Montenegro 2017/18 season was calculated using incidence rates from 2010/11–2016/17 influenza seasons.

Results: Pre-epidemic ILI threshold per 100,000 population was 19.23, while the post-epidemic threshold was 17.55. Using MEM, we identified an epidemic of 10 weeks’ duration. The sensitivity of the MEM epidemic threshold in Montenegro was 89% and the warning signal specificity was 99%.

Conclusions: Our study marks the first attempt to determine the pre/post-epidemic threshold values for the epidemic period in Montenegro. The findings will allow a more detailed examination of the influenza-related epidemiological situation, timely detection of epidemic and contribute to the development of more efficient measures for disease prevention and control aimed at reducing the influenza-associated morbidity and mortality.


Article metrics loading...

Loading full text...

Full text loading...



  1. World Health Organization (WHO). Influenza (Seasonal) Factsheet. Geneva: WHO; 2016. Available from: http://www.who.int/mediacentre/factsheets/fs211/en/.
  2. Uhart M, Bricout H, Clay E, Largeron N. Public health and economic impact of seasonal influenza vaccination with quadrivalent influenza vaccines compared to trivalent influenza vaccines in Europe. Hum Vaccin Immunother. 2016;12(9):2259-68.  https://doi.org/10.1080/21645515.2016.1180490  PMID: 27166916 
  3. Nicholson KG, Wood JM, Zambon M. Influenza. Lancet. 2003;362(9397):1733-45.  https://doi.org/10.1016/S0140-6736(03)14854-4  PMID: 14643124 
  4. Newall AT, Scuffham PA. Influenza-related disease: the cost to the Australian healthcare system. Vaccine. 2008;26(52):6818-23.  https://doi.org/10.1016/j.vaccine.2008.09.086  PMID: 18940222 
  5. Molinari NA, Ortega-Sanchez IR, Messonnier ML, Thompson WW, Wortley PM, Weintraub E, et al. The annual impact of seasonal influenza in the US: measuring disease burden and costs. Vaccine. 2007;25(27):5086-96.  https://doi.org/10.1016/j.vaccine.2007.03.046  PMID: 17544181 
  6. Guo D, Li KC, Peters TR, Snively BM, Poehling KA, Zhou X. Multi-scale modeling for the transmission of influenza and the evaluation of interventions toward it. Sci Rep. 2015;5(1):8980.  https://doi.org/10.1038/srep08980  PMID: 25757402 
  7. Snacken R, Broberg E, Beauté J, Lozano JE, Zucs P, Amato-Gauci AJ. Influenza season 2012-2013 in Europe: moderate intensity, mixed (sub)types. Epidemiol Infect. 2014;142(9):1809-12.  https://doi.org/10.1017/S0950268814001228  PMID: 24814635 
  8. Tay EL, Grant K, Kirk M, Mounts A, Kelly H. Exploring a proposed WHO method to determine thresholds for seasonal influenza surveillance. PLoS One. 2013;8(10):e77244.  https://doi.org/10.1371/journal.pone.0077244  PMID: 24146973 
  9. Won M, Marques-Pita M, Louro C, Gonçalves-Sá J. Early and Real-Time Detection of Seasonal Influenza Onset. PLoS Comput Biol. 2017;13(2):e1005330.  https://doi.org/10.1371/journal.pcbi.1005330  PMID: 28158192 
  10. Steiner SH, Grant K, Coory M, Kelly HA. Detecting the start of an influenza outbreak using exponentially weighted moving average charts. BMC Med Inform Decis Mak. 2010;10(1):37.  https://doi.org/10.1186/1472-6947-10-37  PMID: 20587013 
  11. World Health Organization (WHO). WHO Global Surveillance Standards for Influenza Geneva. Global Influenza Programme, Surveillance and Monitoring team. Geneva: WHO;2013. Available from: https://www.who.int/influenza/resources/documents/WHO_Epidemiological_Influenza_Surveillance_Standards_2014.pdf?ua=1
  12. Cooper DL, Verlander NQ, Elliot AJ, Joseph CA, Smith GE. Can syndromic thresholds provide early warning of national influenza outbreaks? J Public Health (Oxf). 2009;31(1):17-25.  https://doi.org/10.1093/pubmed/fdm068  PMID: 18032426 
  13. Closas P, Coma E, Méndez L. Sequential detection of influenza epidemics by the Kolmogorov-Smirnov test. BMC Med Inform Decis Mak. 2012;12(1):112.  https://doi.org/10.1186/1472-6947-12-112  PMID: 23031321 
  14. 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 Respir Viruses. 2013;7(4):546-58.  https://doi.org/10.1111/j.1750-2659.2012.00422.x  PMID: 22897919 
  15. World Health Organization Regional Office for Europe (WHO/Europe). Guidance for sentinel influenza surveillance in humans. Copenhagen: WHO/Europe; 2011. Available from: https://apps.who.int/iris/bitstream/handle/10665/107265/E92738.pdf?sequence=1&isAllowed=y
  16. Institute of Public Health of Montenegro. Home page. [Accessed: 19 Mar 2019]. Available from: www.ijzcg.me
  17. Vega T, Lozano JE, Meerhoff T, Snacken R, Beauté J, Jorgensen P, et al. Influenza surveillance in Europe: comparing intensity levels calculated using the moving epidemic method. Influenza Other Respir Viruses. 2015;9(5):234-46.  https://doi.org/10.1111/irv.12330  PMID: 26031655 
  18. Bowman AW, Azzalini A. Applied Smoothing Techniques for Data Analysis: the Kernel Approach with S-Plus Illustrations (Oxford Statistical Science Series). Oxford, GA: Oxford University Press, 1997; 208.
  19. Hurvich CM, Simonoff JS, Tsai C. Smoothing parameter selection in nonparametric regression using an improved Akaike information criterion. J R Stat Soc Series B Stat Methodol. 1998;60(2):271-93.  https://doi.org/10.1111/1467-9868.00125 
  20. Lozano Alonso JE. mem: The Moving Epidemics Method, R Package version 2.11. 2017. Available from: https://CRAN.R-project.org/package=mem
  21. Lozano Alonso JE. memapp: The MEM Shiny Web Application, R Package version 2.6. 2017. Available from: https://CRAN.R-project.org/package=memapp
  22. Public Health England (PHE). Surveillance of influenza and other respiratory viruses, including novel respiratory viruses, in the United Kingdom: winter 2017-2018. London: PHE; 2018. Available from: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/740606/Surveillance_of_influenza_and_other_respiratory_viruses_in_the_UK_2017_to_2018.pdf
  23. Instituto de Salud Carlos III (ISCIII). Report on Influenza Surveillance in Spain. 2017-18 season (week 40/2017 to week 20/2018). Madrid: ISCIII; 2018. Available from: http://www.isciii.es/ISCIII/es/contenidos/fd-servicios-cientifico-tecnicos/fd-vigilancias-alertas/fd-enfermedades/fd-gripe/fd-informes-semanales-vigilancia-gripe/pdfs_2017-2018/Informe_Vigilancia_GRIPE_2017-2018_27julio2018.pdf
  24. Vega Alonso T, Lozano Alonso JE, Ortiz de Lejarazu R, Gutiérrez Pérez MS. Modelling influenza epidemic-can we detect the beginning and predict the intensity and duration? Int Congr Ser. 2004;1263:281-3.
  25. Hashimoto S, Murakami Y, Taniguchi K, Nagai M. Detection of epidemics in their early stage through infectious disease surveillance. Int J Epidemiol. 2000;29(5):905-10.  https://doi.org/10.1093/ije/29.5.905  PMID: 11034976 
  26. Lucero MG, Inobaya MT, Nillos LT, Tan AG, Arguelles VL, Dureza CJ, et al. National Influenza Surveillance in the Philippines from 2006 to 2012: seasonality and circulating strains. BMC Infect Dis. 2016;16(1):762.  https://doi.org/10.1186/s12879-016-2087-9  PMID: 27993136 
  27. Paget J, Marquet R, Meijer A, van der Velden K. Influenza activity in Europe during eight seasons (1999-2007): an evaluation of the indicators used to measure activity and an assessment of the timing, length and course of peak activity (spread) across Europe. BMC Infect Dis. 2007;7(1):141.  https://doi.org/10.1186/1471-2334-7-141  PMID: 18047685 
  28. Michiels B, Nguyen VK, Coenen S, Ryckebosch P, Bossuyt N, Hens N. Influenza epidemic surveillance and prediction based on electronic health record data from an out-of-hours general practitioner cooperative: model development and validation on 2003-2015 data. BMC Infect Dis. 2017;17(1):84.  https://doi.org/10.1186/s12879-016-2175-x  PMID: 28100186 
  29. Bangert M, Gil H, Oliva J, Delgado C, Vega T, DE Mateo S, et al. Pilot study to harmonize the reported influenza intensity levels within the Spanish Influenza Sentinel Surveillance System (SISSS) using the Moving Epidemic Method (MEM). Epidemiol Infect. 2017;145(4):715-22.  https://doi.org/10.1017/S0950268816002727  PMID: 27916023 
  30. Public Health Agency Northern Ireland (HSA PHA). Surveillance of Influenza in Northern Ireland 2016-2017. Belfast: HSA PHA; 2017. Available from: http://www.publichealth.hscni.net/sites/default/files/Surveillance%20of%20Influenza%20in%20Northern%20Ireland%202016-2017.pdf
  31. National Institute for Public Health and the Environment (RIVM). Annual report Surveillance of influenza and other respiratory infections in the Netherlands: winter 2017/2018. Bilthoven: RIVM; 2018. Available from: https://www.rivm.nl/dsresource?objectid=78e45fa8-0b1c-4fa4-ad95-b55d34620bdb&type=org&disposition=inline
  32. Instituto Nacional de Saúde Doutor Ricardo Jorge. Programa Nacional de Vigilância da Gripe: relatório da época 2017/2018. [Influenza Surveillance Program: report of the period 2017/2018]. Lisbon: Instituto Nacional de Saúde Doutor Ricardo Jorge; 2018. Portugese. Available from: http://www.insa.min-saude.pt/programa-nacional-de-vigilancia-da-gripe-relatorio-da-epoca-2017-2018/

Data & Media loading...

Comment has been disabled for this content
Submit comment
Comment moderation successfully completed
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error