We quantify the effect of mobility habits in the spread of the Coronavirus in Italy. • Daily COVID-19 cases are directly related to the mobility habits performed 21 days before. • Population density, PM pollutant and number of tests per day have a direct relationship with the infection. • Temperature has an inverse relationship with the spread of the virus. • The areas close to the outbreak had a higher risk of contagion (time-decay phenomena).
The Covid-19 pandemic has caused an unprecedented global crisis and led to a huge number of deaths, economic hardship and the disruption of everyday life. Measures to restrict accessibility adopted by many countries were a swift yet effective response to contain the spread of the virus. Within this topic, this paper aims to support policies and decision makers in defining the most appropriate strategies to manage the Covid-19 crisis. Precisely the correlation between positive Covid-19 cases and transport accessibility of an area was investigated through a multiple linear regression model. Estimation results show that transport accessibility was the variable that better explained the number of Covid-19 infections (about 40% in weight), meaning that the greater is the accessibility of a certain geographical area, the easier the virus reaches its population. Furthermore, other context variables were also significant, i.e. socio-economic, territorial and pollutant variables. Estimated findings show that accessibility, which is often used to measure the wealth of an area, becomes its worst enemy during a pandemic, providing to be the main vehicle of contagion among its citizens. These original results allow the definition of possible policies and/or best practices to better manage mobility restrictions. The quantitative estimates performed show that a possible and probably more sustainable policy for containing social interactions could be to apply lockdowns in proportion to the transport accessibility of the areas concerned, in the sense that the higher the accessibility, the tighter should be the mobility restriction policies adopted.
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.
Lockdown policies applied worldwide to limit the spread of COVID-19, and mainly based on health considerations, have negatively impacted on public transport (PT) usage, suspected as a means for the virus spreading due to difficulties ensuring social distancing. This resulted not only in a setback to sustainable mobility, but also impacting on equity and social exclusion issues. The paper aimed to cover this topic, investigating the conjecture that the spread of the coronavirus is directly correlated to PT usage. A correlation analysis among the daily number of certified coronavirus cases and the PT trips measured in the day in which the contagions occurred was performed within the second wave in Italy. The appropriateness of the case study is twofold because Italy was one of the main European countries with a high mass contagion and because the vaccination campaign had not yet started in Italy. Estimation results show a high correlation (up to 0.87) between COVID-19 contagion and PT trips performed 22 days before. This threshold indicates that quarantine measures, commonly set at two weeks and based only on incubation considerations, were inadequate as a containment strategy, and may have produced a possible slowdown in identifying new cases and hence, in adopting mitigation policies. A cause–effect test was also implemented, concluding that there is a strong causal link between COVID-19 and PT trips. The main issues discussed in this research cover the transportation and the health filed but also laid the groundwork for ethical considerations concerning the right to mobility and social equity. Obtained results could yield significant insights into the context variables that influence the spread of the virus, also helping appropriate definition of restrictive policies, thereby ensuring a sustainable recovery and development of urban areas in the post-pandemic era.
In the transport sector, a rational and shared planning process is commonly based on the comparison of different design alternatives through quantitative evaluations and stakeholders’ engagement. Among the most adopted evaluation methods, there are cost–benefit analysis (CBA) and multi-criteria analysis (MCA). Both these methods have strengths and weaknesses, which do not allow the conclusion that one technique is dominant over the other. Starting from these considerations, the aim of this paper is to propose a sustainable evaluation process for investments in the transport sector, based on the combined use of both CBA and MCA analysis and a stakeholders’ engagement. The proposed evaluation method was also applied to a real case study: the decision-making process for a new highway in a high naturalistic and touristic area in north of Italy. Furthermore, a “weighted criteria process definition” based on the Delphi method was also performed within a public engagement process. Research results show that the application of both the evaluation analyses (CBA and MCA) allows the selection of the most rational althernative from a sustainable, shared and technical point of view. Precisely, the estimations performed underline that the CBA analysis significantly underestimated the non-users’ benefits, while the opposite occurred for the MCA analysis. The incidence of the non-users’ benefits is only the 14% of the total for the CBA, while it reaches more than the 79% for the MCA. This result is very relevant underling how, for a decision-making processes aimed in comparing different design alternatives for which non-users impacts are expected as relevant against the users ones, the unique application of the most consolidated CBA analyses are not always adequate, while the joint use of the two evaluation methods ensures robust and rational choices for a sustainable development.
Sustainability can be defined as the capacity to satisfy current needs without compromising future generations. Sustainable development clashes with the transport sector because of the latter’s high fossil fuels usage, consumption of natural resources and emission of pollutant and greenhouse gases. Electric mobility seems to be one of the best options to achieve both the sustainability goals and the mobility needs. This paper critically analysed weaknesses, strengths and application fields of electric mobility, proposing a real case application of an e-mobility bus fleet in Sorrento peninsula (Italy). The aim and the originality of this research was to propose a public transport design methodology based on a “strong sustainability” policy and applied to a real case study. To be precise, the renewing of the “old” bus fleet with a diesel plug-in hybrid one charged by a photovoltaic system was proposed, aiming to both improve environmental sustainability and perform an investment return for a private operator in managing the transport service. The proposed case study is particularly suitable because the peculiar morphology of the Sorrento peninsula in Italy does not allow other types of public transport services (e.g., rail, metro). Furthermore, this area, rich in UNESCO sites, has always been an international tourist destination because of the environment and landscape. Estimation results show that the new e-mobility bus service will be able to reduce the greenhouse gases emissions up to the 23%, with a financial payback period of 10 years for a private investor.
The conjecture discussed in this paper was that the daily number of certified cases of COVID-19 is direct correlated to the average particular matter (PM) concentrations observed several days before when the contagions occurred (short-term effect), and this correlation is higher for areas with a higher average seasonal PM concentration, as a measure of prolonged exposure to a polluted environment (long-term effect). Furthermore, the correlations between the daily COVID-19 new cases and the mobility trips and those between the daily PM concentrations and mobility trips were also investigated. Correlation analyses were performed for the application case study consisting in 13 of the main Italian cities, through the national air quality and mobility monitoring systems. Data analyses showed that the mobility restrictions performed during the lockdown produced a significant improvement in air quality with an average PM concentrations reduction of about 15%, with maximum variations ranging between 25% and 42%. Estimation results showed a positive correlation (stronger for the more highly polluted cities) between the daily COVID-19 cases and both the daily PM concentrations and mobility trips measured about three weeks before, when probably the contagion occurred. The obtained results are original, and if confirmed in other studies, it would lay the groundwork for the definition of the main context variables which influenced the COVID-19 spread. The findings highlighted in this research also supported by the evidence in the literature and allow concluding that PM concentrations and mobility habits could be considered as potential early indicators of COVID-19 circulation in outdoor environments. However, the obtained results pose significant ethical questions about the proper urban and transportation planning; the most polluted cities have not only worst welfare for their citizens but, as highlighted in this research, could lead to a likely greater spread of current and future respiratory and/or pulmonary health emergencies. The lesson to be learned by this global pandemic will help planners to better preserve the air quality of our cities in the post-COVID-19 era.
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