Counterfactual analysis of the impact of the first two waves of the COVID-19 pandemic on the reporting and registration of missing people in India

Author:

Paramasivan Kandaswamy,Subramani Brinda,Sudarsanam Nandan

Abstract

AbstractThe primary duty of law enforcement agencies is to ensure that a victim has the necessary information and access to the relevant tools required to seek justice. In India, complex cases such as bodily offences and property crimes capture the work and efforts of many agencies involved; however, cases related to missing persons are not often accorded similar priority or seriousness. The COVID-19 pandemic and subsequent lockdowns have added further challenges to this scenario. The government-mandated lockdowns in Tamil Nadu generally exacerbated difficult socio-economic and living conditions, thereby directly or indirectly contributing to an increased load of missing person cases. This study aims to assess and identify the impact of mobility on reporting and registration of missing persons. By adopting an auto-regressive neural networks method, this study uses a counterfactual analysis of registered missing person cases during the government-mandated lockdowns in response to the global pandemic in 2020 and 2021. The registered cases are calculated based on the daily count of cases for eleven years in Tamil Nadu, India. The lockdowns identify eight different time windows to determine the impact of mobility on the registration of cases. While there has been no significant or drastic change over the pre-pandemic period, during the pandemic, especially during the restrictive phases of the pandemic, there was a sharp fall in cases compared to the counterfactual predicted (effect sizes: −0.981 and −0.74 in 2020 and 2021), signalling towards a choked mechanism of reporting. In contrast, when most mobility restrictions were removed, an increase in cases (effect sizes of +0.931 and 0.834 in 2020 and 2021) pointed to restored and enabled reporting channels. The research findings emphasise the significance of mobility as a factor in influencing the reporting and registration of missing persons and the need to ensure this continues to help families find redress.

Publisher

Springer Science and Business Media LLC

Subject

General Economics, Econometrics and Finance,General Psychology,General Social Sciences,General Arts and Humanities,General Business, Management and Accounting

Reference32 articles.

1. Alexandrov A, Benidis K, Bohlke-Schneider M, Flunkert V, Gasthaus J, Januschowski T, Gluon TS, et al. (2019) Probabilistic time series models in python. [preprint]. Jun. Available from: https://arxiv.org/abs/1906.05264

2. AMBER Alert Europe (2022) AMBER Alert Europe. (https://www.amberalert.eu/)

3. Ambler S (2014) Invisible women a call to action; a report on missing and murdered indigenous women in Canada; 41st Parliament First Session. House of Commons Special Committee on Violence Against Indigenous Women, Ottawa Ontario. http://www.parl.gc.ca/content/hoc/Committee/412/IWFA/Reports/RP6469851/IWFArp01/IWFArp01-e.pdf

4. Briones JL, Chhabra T (2022) Navigation mesh for missing persons search: student mobile application competition: smart cities and internet of things category. In the 23rd International Conference on Distributed Computing and Networking (ICDCN 2022). Association for Computing Machinery, New York, NY, USA, 252–253. https://doi.org/10.1145/3491003.3500927

5. Calderon-Anyosa R, Bilal U, Kaufman JS (2021) Variation in non-external and external causes of death in Peru in relation to the COVID-19 lockdown.Yale J Biol Med 94(1):23–40

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3