Abstract
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.
Highlights
Influenza is a highly infectious viral disease that represents a considerable public health problem, as it is a cause of significant morbidity and mortality rates globally [1,2]; the most severe clinical symptoms and mortality occur in high-risk populations [3]
Two important benefits include the comparison of data from the current influenza season to previous seasons and the identification of an increased activity during a specific time frame, which could represent the onset of an influenza epidemic
The historical influenza-like illness (ILI) time series used in this study is shown in Figure 1, indicating that the highest activity was recorded in 2016/17 and the lowest in the 2015/16 influenza season
Summary
Influenza is a highly infectious viral disease that represents a considerable public health problem, as it is a cause of significant morbidity and mortality rates globally [1,2]; the most severe clinical symptoms and mortality occur in high-risk populations [3]. The severity and duration of the influenza epidemic vary every year due to differences in virus circulation, population susceptibility and climatic factors; in addition, the onset, duration, intensity, geographic spread of influenza and the severity of the disease are often unpredictable [7,8,9,10]. The specific goal of influenza surveillance is to provide timely and high-quality epidemiological data to reduce the impact of illness and to inform public health authorities in their appropriate response to this disease. Two important benefits include the comparison of data from the current influenza season to previous seasons and the identification of an increased activity during a specific time frame, which could represent the onset of an influenza epidemic. 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. 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
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
