Ontology highlight
ABSTRACT: Background
Seasonal influenza has major implications for healthcare services as outbreaks often lead to high activity levels in health systems. Being able to predict when such outbreaks occur is vital. Mathematical models have extensively been used to predict epidemics of infectious diseases such as seasonal influenza and to assess effectiveness of control strategies. Availability of comprehensive and reliable datasets used to parametrize these models is limited. In this paper we combine a unique epidemiological dataset collected in Malta through General Practitioners (GPs) with a novel method using cross-sectional surveys to study seasonal influenza dynamics in Malta in 2014-2016, to include social dynamics and self-perception related to seasonal influenza.Methods
Two cros
SUBMITTER: Marmara V
PROVIDER: S-EPMC8502089 | biostudies-literature | 2021 Oct
REPOSITORIES: biostudies-literature