Real-World Evidence: The Case of Peru

Real-World Evidence The Case of Peru

Causality Between Ivermectin and COVID-19 Infection Fatality Rate


Much has been said much about Peru and its use of Ivermectin as a treatment for the coronavirus. The South American country has been a point of reference regarding its use. The Peruvian government approved the use of Ivermectin by decree on May 8. Despite having received several requests to suspend it in September, Pilar Mazzetti, the new Minister of Health, ratified it. These measures have aroused much criticism among the scientific community. They do not understand why they continue to distribute the antiparasitic drug without having a randomized blind study to prove its effectiveness and overlook that the total death toll from COVID-19 in Peru is one of the world’s highest.

Turning away from opinions and moving on to facts, it is necessary to verify whether the ivermectin interventions have matched with variations in the virus’s mortality and lethality. And if they match a decrease in the number of new cases, a younger infected population, a substantial reduction in the most vulnerable people, or other factors could explain the variations.

This analysis evaluated the impact of ivermectin interventions on disease mortality and lethality. Specifically, it assessed the effect of large ivermectin distributions on the variation in the number of deaths associated with COVID-19 in the population older than 60 years, and the infection fatality rate in the same group.

In addition to focusing the study on the most vulnerable group, the study analyzes other factors that could cause variations in mortality, such as the number of positive cases in the same age group and the reduction in the population group’s size due to the deaths.

Graphical Analysis


It is well known that a correlation does not always imply causality. For a correlation to occur without causation, there must be external factors that generate either behaviors; or that the phenomena’ coincidence is the product of chance.

The correlation between the ivermectin interventions and the decrease in both mortality and lethality are quite strong and consistent in all the regions analyzed. However, this correlation could have been caused by other factors or as a product of an accident.

The most certain mechanism to rule out the accidental cause is to find the same correlation in several cases. This study has seen the correlation between Ivermectin’s intervention and the decrease in mortality and lethality in eight Peruvian states. Additionally, when analyzing two outcomes instead of one (mortality and lethality), a casual result becomes even more implausible. In this manner, we discard accidental cause as an explanation for the correlation.

Regarding external factors, we have already ruled out that they were caused by a higher percentage of the young population by including only people over 60 years of age in the study. We also rejected the variation in the number of cases when verifying that there was no decrease in these before reducing mortality. We even cancel out a substantial reduction in the susceptible population when confirming that in no case did deaths reduce this population by more than 1.2%.

Regarding susceptible population reduction at the time of the decrease (in mortality and lethality), these values were unequal in the states analyzed. As an example, the population reduction in Arequipa was four times higher than the decrease in Cusco.

A new theory emerged that some scientists say could explain the low mortality levels in some regions. It is a cross-immunity with dengue that would explain the low levels of mortality. This theory collapses by observing the high mortality rates in Peruvian states such as Arequipa or Moquegua, where there haven’t been dengue cases in the last 20 years. In those states, the mortality rose with COVID-19 cases and dropped after the intervention with Ivermectin.


In these eight Peruvian State analyses, ivermectin distributions preceded sound reductions in deaths amount and infection fatality rate. The variation in the number of detected cases or the vulnerable population decrease can’t explain the mortality and lethality improvement. Likewise, other possible explanations, such as crossed immunity with dengue, or mere causality, have been discarded due to their lack of consistency or implausibility.

The bottom line: treatment with Ivermectin is the most reasonable explanation for the decrease in the number of deaths and the fatality rate in Peru. Its implementation in public policies is a highly effective measure to reduce the mortality and lethality of COVID-19.

To read the full study, click here.

Juan Chamie is a data analyst based in Cambridge, Massachusetts. Recent employers and clients include Wayfair, Trivago, and TrueLight Energy. Get in touch with Juan via email or linkedin.