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 20. This study aims to assess and identify the impact of mobility on reporting and registration of missing persons. 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. The COVID-19 pandemic and subsequent lockdowns have added further challenges to this scenario. 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 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.
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