Basma AbdElGawad1, Tomás Vega2, Moustafa El Houssinie3, Amira Mohsen4, Manal Fahim5, Hanaa Abu ElSood5, Jean Jabbour4, Alaa Eid5, Samir Refaey5. 1. Department of Epidemiology and Surveillance, Preventive Sector, Ministry of Health and Population, Cairo, Egypt. Electronic address: basma.mostafa10@yahoo.com. 2. Dirección General de Salud Pública, Consejería de Sanidad, Valladolid, Spain. 3. Community Medicine Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt. 4. World Health Organization, Egypt Country Office, Cairo, Egypt. 5. Department of Epidemiology and Surveillance, Preventive Sector, Ministry of Health and Population, Cairo, Egypt.
Abstract
BACKGROUND: Establishing influenza thresholds and transmission intensity can help evaluate seasonal changes in influenza severity and potential pandemics. We aimed to evaluate the moving epidemic method (MEM) for calculating influenza thresholds for season 2016/17 in Egypt using four parameters, to identify the most useful parameter. Also to measure the agreement between both the country-specific statistical empirical method and World Health Organization method to MEM for determining the length and intensity level of activity of the influenza season. METHODS: Routinely epidemiological and laboratory data from sentinel surveillance sites for Severe Acute Respiratory Infection (SARI) and influenza-like illness (ILI) were used for calculating thresholds for seasons between 2010/11 and 2015/16 to test 2016/17 season. The parameters calculated were: screened ILI consultation rate × 1000, screened ILI composite parameter, influenza positivity percentage among sampled SARI cases, and influenza positivity percentage among sampled ILI and SARI cases. These parameters assess seasonality and intensity of influenza activity using the three proposed methods (mentioned above). Agreement between the three methods was done using several approaches. RESULTS: The intensity of influenza activity by MEM was lower than the other two methods. Agreement between MEM and each of the other two techniques varied appreciably from good to very good for seasonal duration, and poor to fair for intensity level. In addition, parameters including laboratory data showed a pattern of bi-wave activity; the first wave occurred in winter mostly between epidemiological weeks 39 and 52 and the second occurred in spring mostly between weeks 12 and 17. CONCLUSION: Parameters including laboratory data were more useful in defining seasonality of influenza. Further exploration of the MEM model in future seasons may help to provide a more comprehensive understanding of its use and application.
BACKGROUND: Establishing influenza thresholds and transmission intensity can help evaluate seasonal changes in influenza severity and potential pandemics. We aimed to evaluate the moving epidemic method (MEM) for calculating influenza thresholds for season 2016/17 in Egypt using four parameters, to identify the most useful parameter. Also to measure the agreement between both the country-specific statistical empirical method and World Health Organization method to MEM for determining the length and intensity level of activity of the influenza season. METHODS: Routinely epidemiological and laboratory data from sentinel surveillance sites for Severe Acute Respiratory Infection (SARI) and influenza-like illness (ILI) were used for calculating thresholds for seasons between 2010/11 and 2015/16 to test 2016/17 season. The parameters calculated were: screened ILI consultation rate × 1000, screened ILI composite parameter, influenza positivity percentage among sampled SARI cases, and influenza positivity percentage among sampled ILI and SARI cases. These parameters assess seasonality and intensity of influenza activity using the three proposed methods (mentioned above). Agreement between the three methods was done using several approaches. RESULTS: The intensity of influenza activity by MEM was lower than the other two methods. Agreement between MEM and each of the other two techniques varied appreciably from good to very good for seasonal duration, and poor to fair for intensity level. In addition, parameters including laboratory data showed a pattern of bi-wave activity; the first wave occurred in winter mostly between epidemiological weeks 39 and 52 and the second occurred in spring mostly between weeks 12 and 17. CONCLUSION: Parameters including laboratory data were more useful in defining seasonality of influenza. Further exploration of the MEM model in future seasons may help to provide a more comprehensive understanding of its use and application.