There is an increasing interest in the potential role of influenza infection in evoking ischemic vascular events, including acute myocardial infarction (AMI). Such an etiological link can have important implications for both primary (influenza vaccination) and secondary (antiviral treatment or thromboprophylaxis) prevention strategies. However, establishing conclusive evidence is hindered by shortcomings of traditional epidemiological designs used to study this association including cohort, case-control and ecological studies. An alternative design, the self-controlled case series (SCCS), has important advantages over more traditional designs because 1) it eliminates fixed confounder bias as each study subject serves as its own control (i.e. self-controlled) and 2) is particularly suitable for studying assocations where both the exposure (influenza infection) and outcome (AMI) are relatively rare. This design was recently applied for the first time to study the link between influenza infection and AMI occurrence in Ontario, Canada (published: New England Journal of Medicine, January 2018). The case-series was created by linking several healthcare registries. A 6-fold increased risk of AMI during the week following a confirmed influenza infection was found, while for other respiratory viral pathogens, relative risks were much lower (2.8-3.5). This indicates that effects specific to influenza virus infection can trigger AMI, which has important implications for influenza prevention and treatment in cardiovascular risk-management. Yet, these findings need to be corroborated before guidelines and policies are updated accordingly. Hence, we propose to replicate this landmark study. We will follow similar approaches for data collection, linkage and analysis as in the original study, but the study cohort will consist of Dutch citizens instead. Importantly, we will be able to account for deaths during follow-up by linking with individual-level mortality data from deaths registries. This is a substantial improvement in comparison to the original study, where this was not accounted for.