Road’s mortality prediction for the most vulnerable users in the context of the Covid-19 pandemic in Santiago de Cali, Colombia
Bibliographic Data
| ID | 22188636 |
|---|---|
| Authors | Jackeline Murillo-Hoyos (0000-0003-0644-0923, Universidad del Valle), Ribká Soracipa Muñoz, Yolanda Soracipa Muñoz (0000-0002-7997-6561), Daniel Eduardo Guzmán Rodríguez (Universidad del Valle), Catalina Correa (0000-0003-4998-1228), Sandra Catalina Correa Herrera, Signed Esperanza Prieto-Bohórquez, Signed Prieto (0000-0002-7896-231X), Cristian Julio Molina (0000-0002-8820-2314, Universidad del Valle) |
| Year | 2024 |
| Volume | 8 |
| Issue | 9 |
| Pages | 3293 |
| Publication date | 2024-09-02 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Infrastructure Policy and Development (JOURNAL) |
| Journal identifiers | ISSN: 2572-7923 • E-ISSN: 2572-7931 |
| Publisher | EnPress Publisher (PUBLISHER) |
| DOI | 10.24294/jipd.v8i9.3293 |
| OpenAlex | W4402142406 |
| Language | EN |
| References cited | 3 |
The purpose of this study is to predict the frequency of mortality from urban traffic injuries for the most vulnerable road users before, during and after the confinement caused by COVID-19 in Santiago de Cali, Colombia. Descriptive statistical methods were applied to the frequency of traffic crash frequency to identify vulnerable road users. Spatial georeferencing was carried out to analyze the distribution of road crashes in the three moments, before, during, and after confinement, subsequently, the behavior of the most vulnerable road users at those three moments was predicted within the framework of the probabilistic random walk. The statistical results showed that the most vulnerable road user was the cyclist, followed by motorcyclist, motorcycle passenger, and pedestrian. Spatial georeferencing between the years 2019 and 2020 showed a change in the behavior of the crash density, while in 2021 a trend like the distribution of 2019 was observed. The predictions of the daily crash frequencies of these road users in the three moments were very close to the reported crash frequency. The predictions were strengthened by considering a descriptive analysis of a range of values that may indicate the possibility of underreporting in cases registered in the city’s official agency. These results provide new elements for policy makers to develop and implement preventive measures, allocate emergency resources, analyze the establishment of policies, plans and strategies aimed at the prevention and control of crashes due to traffic injuries in the face of extraordinary situations such as the COVID-19 pandemic or other similar events
2019-20 coronavirus outbreak · Archaeology · Disease · Geography · Outbreak · Pandemic · Pathology · Sociology · Demography · Medicine · Traffic and Road Safety · Virology
| Highly cited | No |
|---|