{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T13:06:26Z","timestamp":1790168786969,"version":"4.1.0"},"reference-count":31,"publisher":"Public Library of Science (PLoS)","issue":"5","license":[{"start":{"date-parts":[[2022,5,20]],"date-time":"2022-05-20T00:00:00Z","timestamp":1653004800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Robert Bosch Centre for Data Science and Artificial Intelligence (RBCDSAI), Indian Institute of Technology Madras","award":["SB20210605MSRBCX008658"],"award-info":[{"award-number":["SB20210605MSRBCX008658"]}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:p>This study investigates the important role of attendant factors, such as road traffic victims\u2019 access to trauma centres, the robustness of health infrastructure, and the responsiveness of police and emergency services in the incidence of Road Traffic Injuries (RTI) during the pandemic-induced COVID-19 lockdowns. The differential effects of the first and second waves of the pandemic concerning perceived health risk and legal restrictions provide us with a natural experiment that helps us differentiate between the impact of attendant factors and the standard relationship between mobility and Road Traffic Injuries. The authors use the auto-regressive recurrent neural network method on two population levels\u2013Tamil Nadu (TN), a predominantly rural state, and Chennai, the most significant metropolitan city of the state, to draw causal inference through counterfactual predictions on daily counts of road traffic deaths and Road Traffic Injuries. During the first wave of the pandemic, which was less severe than the second wave, the traffic flow was correlated to Road Traffic Death\/Road Traffic Injury. In the second wave\u2019s partial and post lockdown phases, an unprecedented fall of over 70% in Road Traffic Injury\u2014Grievous as against Road Traffic Injury\u2014Minor was recorded. Attendant factors, such as the ability of the victim to approach relief centres, the capability of health and other allied infrastructures, transportation and medical treatment of road traffic crash victims, and minimal access to other emergency services, including police, assumed greater significance than overall traffic flow in the incidence of Road Traffic Injury in the more severe second wave. These findings highlight the significant role these attendant factors play in producing the discrepancy between the actual road traffic incident rate and the officially registered rate. Thus, our study enables practitioners to observe the mobility-adjusted actual incidence rate devoid of factors related to reporting and registration of accidents.<\/jats:p>","DOI":"10.1371\/journal.pone.0268190","type":"journal-article","created":{"date-parts":[[2022,5,20]],"date-time":"2022-05-20T13:43:38Z","timestamp":1653054218000},"page":"e0268190","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":16,"title":["Relationship between mobility and road traffic injuries during COVID-19 pandemic\u2014The role of attendant factors"],"prefix":"10.1371","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8130-9266","authenticated-orcid":true,"given":"Kandaswamy","family":"Paramasivan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rahul","family":"Subburaj","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Venkatesh Mohan","family":"Sharma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nandan","family":"Sudarsanam","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2022,5,20]]},"reference":[{"key":"pone.0268190.ref001","doi-asserted-by":"crossref","first-page":"111099","DOI":"10.1016\/j.envres.2021.111099","article-title":"The Impact of First and Second Wave of the COVID-19 Pandemic: Comparative Analysis to Design Control Measures to Cope with Negative Effects of Future Infectious Diseases in Society","volume":"22197","author":"M. 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