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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.
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We document the diffusion of nebulized ibuprofen in Argentina as a treatment for COVID-19. As the pandemic spread, this clinically unsupported drug reached thousands of patients, even some seriously ill, despite warnings by the regulator and medical societies. Detailed daily data on deliveries for all towns in one of the largest provinces suggests a role for "rational" forces in the adoption of a miracle cure: towns adopt it when neighbors that adopt it are successful in containing deaths (a learning effect), even after controlling for the average adoption of peers. Results from a survey are consistent with learning. They also reveal a large role of beliefs: subjects that are classified as "Right" are more likely adopt and to learn, while those that are "Skeptical" report an increase in their demand when primed with the regulator's ban.
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