Piano Mobilità Lazio » Statistiche

COME CAMBIANO LE TUE ABITUDINI

Piano della Mobilità — Sat, 04 Jul 2020 08:13:39 +0000

Areté Methodos

Impacts of COVID-19 on the transport sector

Piano della Mobilità — Mon, 29 Jun 2020 15:38:52 +0000

Paper (Available at SSRN)

May 2020 Road Safety dashboard

Piano della Mobilità — Tue, 16 Jun 2020 08:36:01 +0000

French road safety observatory

COVID-19 – Rapporto sugli spostamenti della comunità

Piano della Mobilità — Mon, 15 Jun 2020 06:28:36 +0000

Google

To Evaluate and Predict Transportation Trends around COVID-19

Piano della Mobilità — Sat, 13 Jun 2020 06:59:49 +0000

CONNECTED CITIES WITH SMART TRANSPORTATION

L’impatto del Covid-19 sugli utenti del trasporto pubblico in Italia

Piano della Mobilità — Thu, 04 Jun 2020 06:18:37 +0000

MOOVIT

COVID-19 Community Mobility Report

Piano della Mobilità — Thu, 21 May 2020 13:19:32 +0000

Google

Research on the effects of COVID-19 measures on road safety in the Netherlands

Piano della Mobilità — Fri, 15 May 2020 09:44:18 +0000

VIA Traffic Solutions Software

Report 20: Using mobility to estimate the transmission intensity of COVID-19 in Italy

Piano della Mobilità — Mon, 04 May 2020 06:23:15 +0000

Following the emergence of a novel coronavirus (SARS-CoV-2) and its spread outside of China, Italy was the first European country to be hit by COVID-19. As of 1st May 2020, 28,238deaths have been reported nationally with 13,860 having occurred in Lombardy, the most populous and worst hit region in Italy. In Lombardy, infection has been estimated to be introduced in early January and transmission went undetected until the first confirmed case of COVID-19 was reported on 20th of February. On the 21st of February case testing began in order to trace new SARS-CoV-2 infections, and the first COVID-19 death was reported on the 23rd of February in Vo, in the Veneto region.

Mathematical and statistical models are useful tools to better understand the transmission dynamics of infectious diseases. They can assess the dynamics of an epidemic as it evolves in time, evaluate the impact of interventions and simulate future scenarios. While models often rely on noisy epidemiological data, they can be designed to account for the uncertainties in the data and represent conceptual frameworks that can be used to look at trends, infer dynamics and answer real-world questions using an evidence-based approach. The real-time analysis and modelling of epidemic data can thus provide
data-driven and scientific evidence that can inform the response, planning and public health decision making against the current COVID-19 pandemic.

Per approfondimenti sullo studio: https://www.imperial.ac.uk/media/imperial-college/medicine/mrc-gida/2020-05-04-COVID19-Report-20.pdf

Pubblicato da: Imperial College – UK