Causal Inference During A Pandemic: Evidence on the Effectiveness of Nebulized Ibuprofen as an Unproven Treatment for COVID-19 in Argentina

By: Sebastian Calonico, Rafael Di Tella and Juan Cruz Lopez Del Valle

Format:Print
| Language:English

Abstract

Many medical decisions during the pandemic were made without the support of causal evidence obtained in clinical trials. We study the case of nebulized ibuprofen (NaIHS), a drug that was extensively used on COVID-19 patients in Argentina amidst wild claims about its effectiveness and without regulatory approval. We study data on 5,146 patients hospitalized in 11 health centers spread over 4 provinces, of which a total of 1,019 (19.8%) received the treatment. We find a large, negative and statistically significant correlation between NaIHS treatment and mortality using inverse probability weighting estimators. We consider several threats to identification, including the selection of “low” risks into NaIHS, spillovers affecting patients in the control group, and differences in the quality of care in centers that use NaIHS. While the negative correlation appears to be, broadly, robust, our results are best interpreted as emphasizing the benefits of running a randomized controlled trial and the challenges of incorporating information produced in other, less rigorous circumstances.