An analysis of WHO FluNet and FluID influenza surveillance data for South East Asia Region, 2015-2023.

Influenza is known to cause seasonal epidemics and recurrent pandemics and demands robust surveillance systems for strain detection and trend monitoring. There are global surveillance systems (FluNet and FluID) to monitor the trends in influenza virus strains and epidemiology. SEAR has been vulnerable to influenza outbreaks and hence, efforts to enhance surveillance have been ongoing. However, there is limited analysis of data trends from influenza surveillance systems from SEAR member states (MS). To describe the virological and epidemiological characteristics of influenza in WHO SEAR and MS therein for the years 2015 till 2023. Influenza surveillance data from 2015 to 2023 was extracted for all WHO SEAR MS. This included virological surveillance data from FluNet and epidemiological data from FluID. Descriptive analysis was conducted for the proportionate distribution of Influenza A and B, their subtypes and proportion of ILI and SARI cases. The analysis elicited annual patterns and trends of influenza infections in each MS and across the SEAR region. A multivariable linear regression model was fitted with SARI cases as the outcome against ILI cases, influenza test positivity, country, seasonality and pre-and post- covid period with statistical significance set at p<0.05. During the reporting period, a total of 5,97,781 specimens were processed in 11 countries. A total of 85,105 (14.2%) specimens were laboratory confirmed influenza positive cases. Two peaks were seen in 2019 and 2021 in almost all the SEAR MS. India (37.4%) had the highest number of confirmed influenza cases followed by Nepal (15.6%) and Bangladesh (10.3%). Influenza A (75.5%) dominated in almost all years and countries. Thailand reported the highest ILI cases (n = 19.4 million; 95.4%), followed by Sri Lanka (n = 0.6 million; 2.9%) and Bhutan (0.8%). Nepal had the highest number of SARI cases (n = 1,03,010; 36.4%), followed by Bangladesh (n = 1,00,772; 35.6%) and Sri Lanka (n = 21,688; 7.7%). In the adjusted model, influenza positivity was associated with higher SARI cases (β = 17.35, p= 0.005), while ILI, seasonality and pandemic period were not. Enhancing influenza surveillance data can improve epidemic readiness and seasonal vaccination planning. Improving the quality and timeliness of data submissions to FluNet and FluID is crucial, as current data gaps hinder effective decision-making at the regional and global levels. WHO has provided strategic guidance for strengthening the two databases and the Global Influenza Surveillance and Response System (GISRS), urging collaborative and regionally harmonized action including optimizing sentinel site networks and leveraging from COVID-19 for future pandemic preparedness.