Cross-Sectional Surveys as A Tool To Study Epidemiological Factors And Exploring Social Dynamics of Seasonal Influenza In Malta

Abstract

Background: Seasonal influenza has major implications for healthcare services as outbreaks often lead to high activity levels in the health system. Mathematical models have extensively been used to predict epidemics of infectious diseases such as seasonal influenza and to assess effectiveness of proposed control strategies. However, the availability of comprehensive and reliable datasets is limited. In this paper we combine a unique epidemiological dataset collected in Malta through GPs with a novel method that uses cross-sectional surveys to study the dynamics of seasonal influenza in Malta in 2014-2016, to include social dynamics and self-perception related to seasonal influenza.Methods: Two cross-sectional public surveys (n=406 per survey) were performed by phone across the Maltese population in 2014-15 and 2015-16 influenza seasons. Survey results were compared with incidence data (diagnosed seasonal influenza cases) collected by GPs in the same period and with Google Trends data for Malta. The information was collected on whether participants recollected their health status in past months, occurrences of influenza symptoms, hospitalisation rates due to seasonal influenza, whether they sought GP advice, and other medical information. Results: We demonstrate that cross-sectional surveys are a reliable alternative source of data to medical records. The two surveys gave comparable results, indicating that the level of recollection among the public is high. Based on two seasons of data, the reporting rate in Malta varies between 14% and 22%. The comparison with Google Trends suggests that the online searches peak at about the same time as the maximum extent of the epidemic, but then the public interest declines and returns to the background level. We also found that the public intensively searched the Internet for influenza-related terms even when the number of cases was low.Conclusions: Our research shows that a telephone survey is an appropriate way to gain deeper insight into the population self-perception of influenza and its symptoms and to provide another benchmark for medical statistics provided by GPs and Google Trends. The information collected in different ways can be used to improve epidemiological modelling capacity for seasonal influenza and other infectious diseases, thus contributing to public health.