Did the Indian lockdown avert deaths?

TL;DR

This paper uses SEIR models to argue that early lockdowns delay but do not significantly reduce total COVID-19 deaths, highlighting limitations in simple models for policy evaluation.

Contribution

It demonstrates that early lockdowns in simple models do not avert deaths and discusses the limitations of such models in assessing real-world impact.

Findings

Lockdowns delay but do not prevent deaths in SEIR models.

Simple models cannot reliably quantify lockdown effects on fatalities.

Qualitative effects of lockdowns may increase or decrease total toll.

Abstract

Within the context of SEIR models, we consider a lockdown that is both imposed and lifted at an early stage of an epidemic. We show that, in these models, although such a lockdown may delay deaths, it eventually does not avert a significant number of fatalities. Therefore, in these models, the efficacy of a lockdown cannot be gauged by simply comparing figures for the deaths at the end of the lockdown with the projected figure for deaths by the same date without the lockdown. We provide a simple but robust heuristic argument to explain why this conclusion should generalize to more elaborate compartmental models. We qualitatively discuss some important effects of a lockdown, which go beyond the scope of simple models, but could cause it to increase or decrease an epidemic's final toll. Given the significance of these effects in India, and the limitations of currently available data, we conclude that simple epidemiological models cannot be used to reliably quantify the impact of the Indian lockdown on fatalities caused by the COVID-19 pandemic.