Nowcasting COVID-19 incidence indicators during the Italian first outbreak

A novel parametric regression model is proposed to fit incidence data typically collected during epidemics. The proposal is motivated by real-time monitoring and short-term forecasting of the main epidemiological indicators within the first outbreak of COVID-19 in Italy. Accurate short-term predictions, including the potential effect of exogenous or external variables are provided. This ensures to accurately predict important characteristics of the epidemic (e.g., peak time and height), allowing for a better allocation of health resources over time. Parameter estimation is carried out in a maximum likelihood framework. All computational details required to reproduce the approach and replicate the results are provided

A non-parametric Hawkes process model of primary and secondary accidents on a UK smart motorway

A self-exciting spatiotemporal point process is fitted to incident data from the UK National Traffic Information Service to model the rates of primary and secondary accidents on the M25 motorway in a 12-month period during 2017–2018. This process uses a background component to represent primary accidents, and a self-exciting component to represent secondary accidents. The background consists of periodic daily and weekly components, a spatial component and a long-term trend. The self-exciting components are decaying, unidirectional functions of space and time. These components are determined via kernel smoothing and likelihood estimation. Temporally, the background is stable across seasons with a daily double peak structure reflecting commuting patterns. Spatially, there are two peaks in intensity, one of which becomes more pronounced during the study period. Self-excitation accounts for 6–7% of the data with associated time and length scales around 100 min and 1 km, respectively. In-sample and out-of-sample validation are performed to assess the model fit. When we restrict the data to incidents that resulted in large speed drops on the network, the results remain coherent

Circular Economy Ecosystem Coordination: A comparative study of two sectoral cases

Circular solutions require a systemic approach involving multiple actors within and across industrial sectors. This has implications for the structure and dynamics within geographically bounded entrepreneurial ecosystems. Actors within the entrepreneurial ecosystem assume the role of ‘system coordination’ but very little is known about this role. As circular solutions and transformations cannot be realized in isolation, a better understanding of this coordination role is pertinent, which actors perform it and the strategies they use to overcome challenges. We conduct a comparative study of two sectoral cases in the Netherlands. Our preliminary findings from the case on circular textiles shows that coordination is distributed among several and diverse ecosystem actors to close technical material flows, whereas our preliminary findings in agri-food show that coordination is concentrated among actors that explicitly assume the coordination role to close biological material flows. We intend to make novel contributions to the literature on circular economy business transformation and entrepreneurial ecosystems as well as provide insights on the system coordination role for policy makers and practitioners

Compositional analysis of fish communities in a fast changing marine ecosystem

Le preoccupazioni dovute agli effetti delle attivita umane e del cambiamento climatico sull’ecosistema marino del Mediterraneo hanno recentemente richiesto nuovi lavori di ricerca sulla risposta delle comunita ittiche alle pressioni ambientali di cui soffrono. Le limitazioni principali degli approcci statistici standard e che non possono adeguatamente gestire la complessit ` a delle interazioni che si osservano tra sottopopolazioni. In questo lavoro, studiamo una comunita di 129 specie di pesci demersali che abitano la costa del Lazio. Lo scopo principale e quello di capire se le composizioni siano cambiate nel tempo e, nel caso, verificare possibili relazioni statistiche con variazioni della temperatura. I risultati mostrano che questa zona del Mediterraneo sta subendo una lenta ma progressiva meridionalizzazione dei pesci che la abitano.Concerns about the effects of human activities and climate change on the Mediterranean marine ecosystem are recently demanding new research work on the response of fish communities to environmental pressures to which they are subjected. The main limitation of standard statistical approaches is that they cannot properly account for the complex interactions occurring among subpopulations. In this work, we analyze a community of 129 demersal fish species living in front of the Lazio coast. The goal is to understand if the compositions changed over time and if so, verify any statistical relationship with changes in water temperature. Results show that this area of the Mediterranean Sea is undergoing a slow but progressive meridionalization of the fish inhabiting its water

Compositional analysis of fish communities in a fast-changing marine ecosystem

Le preoccupazioni dovute agli effetti delle attivita umane e del cambiamento climatico sull’ecosistema marino del Mediterraneo hanno recentemente richiesto nuovi lavori di ricerca sulla risposta delle comunita ittiche alle pressioni ambientali di cui soffrono. Le limitazioni principali degli approcci statistici standard e che non possono adeguatamente gestire la complessit ` a delle interazioni che si osservano tra sottopopolazioni. In questo lavoro, studiamo una comunita di 129 specie di pesci demersali che abitano la costa del Lazio. Lo scopo principale e quello di capire se le composizioni siano cambiate nel tempo e, nel caso, verificare possibili relazioni statistiche con variazioni della temperatura. I risultati mostrano che questa zona del Mediterraneo sta subendo una lenta ma progressiva meridionalizzazione dei pesci che la abitano.Concerns about the effects of human activities and climate change on the Mediterranean marine ecosystem are recently demanding new research work on the response of fish communities to environmental pressures to which they are subjected. The main limitation of standard statistical approaches is that they cannot properly account for the complex interactions occurring among subpopulations. In this work, we analyze a community of 129 demersal fish species living in front of the Lazio coast. The goal is to understand if the compositions changed over time and if so, verify any statistical relationship with changes in water temperature. Results show that this area of the Mediterranean Sea is undergoing a slow but progressive meridionalization of the fish inhabiting its water

Circular moonshot: understanding field logic shifts and the influence of business models for sustainability on field change

We aim to understand the interaction between shifting organizational field logics and field actors’ responses to reconcile logic plurality and maintain legitimacy through business model innovation. Drawing on a multimethod, longitudinal field study in the fashion industry, we traced how de novo and incumbent firms integrate circular logics in business models (for sustainability) and uncover how productive tensions in field logics lead to experimental spaces for business model innovation. Our findings showed a shift in the discourse on circular logic that diverted attention and resources from materials innovation (e.g. recycling) to business model innovation (e.g. circular business models). By juxtaposing the degree of field logic tension and the degree of business model innovation, we derive four types of business model hybridization responses that actors engaged in to maintain legitimacy – constrained, limited, integrated, and expanded. Our study generates new insights on business models for sustainability as vehicles for organizational field change. We make novel contributions to the literatures on organizational fields, business models for sustainability and business model innovation

Covid-19 in Italy: Modelling, communications, and collaborations

When Covid-19 arrived in Italy in early 2020, a group of statisticians came together to provide tools to make sense of the unfolding epidemic and to counter misleading media narratives. Here, members of StatGroup-19 reflect on their work to date

Model-based clustering for monitoring cetaceans population dynamics

We introduce a Bayesian multivariate framework to investigate the sitefidelity patterns and estimate the population size of bottlenose dolphins (Tursiops truncatus) at the Tiber River estuary (central Mediterranean, Tyrrhenian Sea, Rome, Italy) between 2017 and 2020. In order to compare the results obtained through a distancebased clustering (Pace et al., 2021), a model-based clustering is performed using the same site-fidelity metrics: in particular, a multivariate finite mixture model is assumed for the vector of metrics (McLachlan et al., 2019). The proposed approach consists of two steps. We start with a Bayesian model-based classification of individuals in three different clusters labeled resident, part-time and resident using 347 unique individuals identified. Each individual is allocated to the group with the greatest estimated posterior probability. Finally, for each group, we estimate the corresponding population size via a capture-recapture analysis based on the Jolly-Seber model (Schwarz & Arnason, 1996): this kind of model allows to take into account the apparent survival probability of the animal in the population along with the capture probability. The results are compared to those obtained by the distance-based classification provided by Pace et al. (2021)