On the robustness of effectiveness estimation of nonpharmaceutical interventions against COVID-19 transmission

by   Mrinank Sharma, et al.

There remains much uncertainty about the relative effectiveness of different nonpharmaceutical interventions (NPIs) against COVID-19 transmission. Several studies attempt to infer NPI effectiveness with cross-country, data-driven modelling, by linking from NPI implementation dates to the observed timeline of cases and deaths in a country. These models make many assumptions. Previous work sometimes tests the sensitivity to variations in explicit epidemiological model parameters, but rarely analyses the sensitivity to the assumptions that are made by the choice the of model structure (structural sensitivity analysis). Such analysis would ensure that the inferences made are consistent under plausible alternative assumptions. Without it, NPI effectiveness estimates cannot be used to guide policy. We investigate four model structures similar to a recent state-of-the-art Bayesian hierarchical model. We find that the models differ considerably in the robustness of their NPI effectiveness estimates to changes in epidemiological parameters and the data. Considering only the models that have good robustness, we find that results and policy-relevant conclusions are remarkably consistent across the structurally different models. We further investigate the common assumptions that the effect of an NPI is independent of the country, the time, and other active NPIs. We mathematically show how to interpret effectiveness estimates when these assumptions are violated.


page 7

page 16

page 17


Compartmental Models for COVID-19 and Control via Policy Interventions

We demonstrate an approach to replicate and forecast the spread of the S...

Utilizing Concept Drift for Measuring the Effectiveness of Policy Interventions: The Case of the COVID-19 Pandemic

As a reaction to the high infectiousness and lethality of the COVID-19 v...

When and How to Lift the Lockdown? Global COVID-19 Scenario Analysis and Policy Assessment using Compartmental Gaussian Processes

The coronavirus disease 2019 (COVID-19) global pandemic has led many cou...

A Full Bayesian Model to Handle Structural Ones and Missingness in Economic Evaluations from Individual-Level Data

Economic evaluations from individual-level data are an important compone...

A quantitative analysis of the 2017 Honduran election and the argument used to defend its outcome

The Honduran incumbent president and his administration recently declare...

Revealing the Transmission Dynamics of COVID-19: A Bayesian Framework for R_t Estimation

In epidemiological modelling, the instantaneous reproduction number, R_t...

Statistical methods used to combine the effective reproduction number, R(t), and other related measures of COVID-19 in the UK

In the COVID-19 pandemic, a range of epidemiological models have been us...

Please sign up or login with your details

Forgot password? Click here to reset