A General Linear Model Approach to Determine the Effect of Un-lockdown on COVID-19 Pandemic in New Delhi

Abstract

Introduction: As new strains of SARCOV2 virus emerge across the world, it is imperative to investigate measures which restrict the movement of the general population such as social and travel restrictions by lockdowns to mitigate the effects of COVID-19. Thus, our paper helps in two ways: 1) Drastic measures like lockdown are essential but cannot be a feasible long-term intervention. Therefore, it is crucial to understand if the same unlock down can be reversed without compromising public health needs. Our paper provides evidence on the same; and 2) Our report also provides an insight into the trends of disease transmission during different phases of the un-lockdown.Methods: We examine the spread of pandemic during different phases of Un-lockdown (8th June to 31st October 2020). Since Rt calculation takes into consideration numerous factors, we use β, the transmission coefficient that governs the transition of population from Susceptible to Exposed pool, to examine the effect of public heaThelth interventions on disease spread.Results: The comparison of the distribution of fitted β values, thus calculated using SEIR model and GLM have been done and a Welch Two Sample t-test suggests that the GLM fitted β and SEIR β data sets are not significantly different from one another.Conclusion: We provide evidence that un-lockdown can be achieved without increasing the transmission of disease disproportionately. Thus, a phased wise approach to un-lockdown is encouraged. We also provide the rationale for using β over Rt values to specifically assess the effect of public health interventions designed to decrease exposure.