Abstract
Complex transmission patterns are not immediately obvious to epidemiologists, hindering the development of effective intervention strategies. The aim is to develop network-based tools to identify transmission patterns across age-groups, occupations, and locations. Infection networks were constructed using COVID-19 contact tracing data, provided by the Cyprus Ministry of Health, for March 2020 to May 2021. Transmission patterns within/across age-groups, districts, and economic activities, as well as the presence of super-spreaders and the vulnerability of different groups, were assessed using the constructed networks for the first four pandemic waves. The constructed networks for all waves were sparse. Network analysis, showed that the first wave primarily involved older individuals and healthcare settings. During the second wave, a higher infection rate among young adults was observed. The dominant transmission patterns during the third and fourth wave existed between (i) individuals of similar ages, who more commonly interact, and (ii) individuals with an age difference of ~ 30 years (i.e. a generational gap). Cross-district patterns revealed transmissions were likely to occur between districts that are nearest geographically but also followed social trends. Furthermore, the study identified vulnerable occupations. Outdegree, representing the number of secondary infections caused by an individual, was also investigated. As the pandemic progressed, a decreased outdegree among older age groups (50 +) likely reflected the positive effect of vaccinations and immunity. In contrast, rising values among younger individuals probably reflected fewer vaccinations and more active social interactions. Age, district, and occupation patterns of transmission and super-spreader concentrations can guide targeted intervention strategies, prioritize vaccination efforts, and support decision-making for effective control and prevention of pandemics.