SUMMARY: Accurate pathogen identification is crucial during outbreaks, especially with the emergence of new variants requiring frequent primer updates. However, resources for maintaining up-to-date verification of primer sequences are often limited, which poses challenges for reliable diagnosis and hinders potential monitoring efforts based on genome sequencing. To address this, we introduce ViralPrimer, a web server facilitating primer design, SARS-CoV-2 and Mpox variant monitoring, and adaptation to future threats. ViralPrimer aims to enhance diagnostic accuracy with its comprehensive primer database, mutation analysis assistance, and user primer upload feature. Its adaptable design allows monitoring of other rapidly mutating pathogens, contributing to broader public health protection efforts. AVAILABILITY AND IMPLEMENTATION: ViralPrimer is freely accessible and open to all users with no login requirement at https://viralprimer.elte.hu/. The application is hosted on a DJANGO v3.2.13 web server, with a PostgreSQL database, and the frontend was implemented using jQuery v3.6.0, vanilla JavaScript vES6, and Bootstrap v5.1.

This paper presents operational experience of large-scale unicast network tomography, that samples a part of the European Internet. In the paper we describe in detail the ETOMIC measurement platform that was used to conduct the experiments, and its potential in future scaled-up measurements. The main results of the paper are maps showing various spatial and temporal structure in the characteristics of queueing delay corresponding to the resolved part of the European Internet. These maps reveal that the average queueing delay on different network segments spans more than two orders of magnitude. At the most loaded time of day we find that the distribution of average queueing delays among the different segments follows closely a log-normal distribution.