ABSTRACT
Decision-making processes related to transportation systems are often very complex, belonging to the class of “wicked problems” in social studies. The literature and the media abound in examples of transportation planning “failures” including decisions made, delayed or withdrawn without any traceable motivations, public opposition, public opposition, extra costs/implementation times and outright cancellation, wrong traffic/revenue forecasts. Planning failures stem from several causes, including technical errors in forecasting predictable effects, lack of consensus, new governance cycles and inability to recognize the intrinsic uncertainty affecting some key variables. The underlying assumption of this paper is that the quality of the decision-making process critically depends on how the process is structured and managed. The paper proposes a conceptual model to represent and organize transport planning as a cognitive decision-making process with strong involvement of different stakeholders in various stages, accounting for different levels of uncertainty and including short- and long-term decisions options. The result is a planning process that allows for changes in objectives, strategies and decisions during different stages of the process itself, as is usually the case when different governance and socio-economic cycles succeed over time. However, the process maintains a form of procedural consistency and is intended to counteract the “Penelope syndrome”, whereby decisions made under previous governance cycles are undone regardless of their merits and costs. The real-life implementation of the proposed model requires strong “political commitment” to an open and accountable decision-making process, a technical structure able to act as “process owner” coordinating technical and engagement activities, and a general societal attitude towards organized participation to public decision making. The proposed model was applied to the Regional Transportation Plan of Veneto in Italy where the above conditions applied. A number of lessons were learnt from that exercise: i) stakeholders’ engagement revealed an important potential to manage uncertainty and increase consensus;ii) flexibility and robustness with respect to medium–to–high uncertainty levels already recognized at the time of the plan (immediately before the COVID-19 crisis) were an appreciated feature of the plan;iii) separation between mature decisions and those needing further analysis was a success strategy, reducing political “decision costs” (from naysaying) by delaying decisions still recognizing underlying needs;iv) reduced decision time (a largely bi-partisan vote in less than one year).
ABSTRACT
Early known cases of COVID-19 emerged in late 2019 in the city of Wuhan (China) and in a relatively short time, it has reached more than 200 countries up to July 2020. In Italy, from 21 February 2020, (first official Italian positive case of COVID-19) until 27 July 2020, 246,286 confirmed cases were observed of which over 68,150 (28%) needed hospitalization and 35,112 died. In recent scientific research, it has been shown that the severity of symptoms and mortality rates were different not only among the various countries of the world but also in different regions of the same country. This research investigates whether and by how much air environmental conditions (such as exposure to fine particulate matter-PM2.5, sea air masses and altitude) influences the risk of hospitalization due to COVID-19 in Italy, once the spreading of the virus and the percentage of the elderly in the population have been accounted for. A log-linear multiple regression model was estimated where the log of the ratio of hospitalized patients per inhabitant, since the beginning of the epidemic up to July 27, has been considered as a dependent variable. Among the independent variables, the ones that have been taken into account are the spreading of the virus, the rate of people over 50 years of age, the concentration of PM2.5, the rate of population living by the sea, the rate of green public space for each resident and the ratio of population living at a high altitude. The results showed an increase in the hospitalization rate in terms of the percentage of people over 50 and the average concentration of PM2.5. If average limits of PM2.5 concentration allowed by the current European regulations (25 µg/m3) were respected in all Italian provinces, that would have led to 7339 less hospitalizations for COVID-19 (-11%). On the contrary, near the coast there were lower hospitalized cases in the referred period. In the hypothetical case that no Italians lived near the sea, about 1363 (+2%) more hospitalizations would have been recorded in the analysis period in addition to the effect of a lower PM concentration. This paper wanted to investigate which are the areas with a higher risk of hospitalization in Italy, so as to help the Italian Government to strengthen Health System measures, predicting the most suffering areas and health care systems. According to the results, this is directly related to the severity of symptoms which decreased with the long-time exposure to the sea.