BACKGROUND In 2024, multiple transmission foci of dengue virus serotype 2 (DENV-2) were detected across four Italian regions, resulting in the largest number of autochthonous cases ever recorded in mainland Europe. AIM We aimed to characterise DENV-2 transmission patterns in Italy in 2024. METHODS We analysed 296 locally acquired cases with symptom onset between 31 July and 31 October. Using detailed spatiotemporal data, we reconstructed transmission chains between cases with well-documented exposure sites, applying a Bayesian framework. We estimated the generation time and net reproduction number (R t ) for the main transmission foci, quantified the proportion of transmission occurred across varying distances and assessed the influence of different factors, including temperature and control interventions, on secondary transmission. RESULTS Three major foci were identified, with peak R t estimates ranging from 1.35 to 3.33. The mean generation time was 18.0 days (95% credible interval (CrI): 15.5–20.0 days). Household transmission accounted for 15.4% (95% CrI: 12.6–17.4%) of infection events. Among cases with an identified source of infection, < 1% of transmissions occurred beyond 400 m. Transmissibility declined significantly after outbreak detection, with the average number of secondary cases per infection dropping from 1.4 to 0.4. Vector control interventions were associated with a 41.0% reduction (95% CI: 6.6–63.3%) in transmission; transmission also increased by 19.8% (95% CI: 11.3–29.0%) for each 1°C rise in temperature. CONCLUSION Autochthonous dengue outbreaks in Italy in 2024 were primarily driven by short-distance transmission. Our findings support that early case detection and rapid vector control are instrumental in reducing transmission.
In a complex, ambiguous and uncertain business environment, the use of qualitative and quantitative data to inform strategic policy, decisions and actions is essential. Data increasingly plays a critical role in shaping workplace decisions that carry significant fiscal and team performance implications. Access to more data and processing power, faster and cheaper analytical software and the promise of AI should improve workplace decisions; however, data quantity and quality, time pressures and short attention spans frequently result in overconfidence, solution bias or paralysis and anxiety. This paper describes the key elements of effective decision making, including understanding the purpose, asking the right questions, validating and interrogating data to prosecute the problem and using artificial intelligence to complement human expertise, experience, resourcefulness and ingenuity. Different approaches and associated risks and opportunities in data-driven decision making are illustrated through a detailed corporate case study, insights from a research thesis and professional anecdotes. Practical recommendations are included to prompt corporate real estate (CRE) leaders to clarify their needs and cross-examine relevant sources of information when making important decisions. This paper concludes that in the current environment, critical and contextual thinking are increasingly important CRE capabilities.
Recent developments in tertiary education are demonstrating teaching and learning methods to develop students’ capability for employee-led Workplace Innovation. In this article, we describe an international collaboration to develop shared learning resources and activities in workplace innovation for adaptation in diverse tertiary education contexts. We are intentionally seeking out additional collaborating institutions that differ in mission, size, location and student demographics, to leverage our team’s diversity and encourage innovation. When shared learning resources and activities are to be used in a diverse contexts, some core principles underlying instructional success must also be shared in order to ensure adaptations do not remove key properties. We outline four instructional principles underlying the learning design and illustrate how these principles are applied in our current learning resources. We then describe some of the ways that these shared resources have been adapted for different tertiary education environments. We also discuss some of the benefits emerging from the collaboration, including how the inclusion of new resources targeting specific work domains and the transfer of new teaching and learning ideas across contexts. We conclude by describing some of the ways we are also collaborating with workplace partners, to ensure that our graduates have the capabilities needed to contribute to workplace innovation practice and to help advance the workplace innovation capability of their own employees.
