COVID19 update, June 15, 2020: Ivermectin redux; “modelers have failed’

(1) The Jerusalem Post interviews Prof. Eli Schwartz, the head of the tropical medicine department at Tel HaShomer hospital in the Tel Aviv borough of Ramat-Gan (one of the “Big Four” research and teaching hospitals in Israel, together with Sourasky/Ichilov in central Tel Aviv, Hadassah in suburban Jerusalem, and Rambam/Maimonides in Haifa) about a drug repurposing study involving ivermectin (an antithelmintic/anti-worm drug familiar to veterinarians and travelers to tropical countries, but not to most physicians in Western countries.

The discoverers of this drug shared the 2015 Nobel Prize in Medicine and Physiology. With the discoverers of the next-generation antimalarial artemisinin. An Australian study, part of an effort to find repurposeable already-approved drugs, found a few months ago that ivermectin liquidates the virus in vitro (i.e., in a test tube), which prompted several clinical trials:

https://doi.org/10.1016/j.antiviral.2020.104787

Here is a preprint about a retrospective, open-label study in several Dade County, FL hospitals (i.e., the Miami area):

https://www.medrxiv.org/content/10.1101/2020.06.06.20124461v2

280 patients with confirmed SARS-CoV-2 infection (mean age 59.6 years [standard deviation 17.9], 45.4% female), of whom 173 were treated with ivermectin and 107 were [given] usual care were reviewed. 27 identified patients were not reviewed due to multiple admissions, lack of confirmed COVID results during hospitalization, age less than 18, pregnancy, or incarceration.

Univariate analysis showed lower mortality in the ivermectin group (15.0 % versus 25.2%, OR 0.52, 95% CI 0.29-0.96, P=.03). Mortality was also lower among 75 patients with severe pulmonary disease treated with ivermectin (38.8% vs 80.7%, OR 0.15, CI 0.05-0.47, P=.001), but there was no significant difference in successful extubation rates (36.1% vs 15.4%, OR 3.11 (0.88-11.00), p=.07). After adjustment for between-group differences and mortality risks, the mortality difference remained significant for the entire cohort (OR 0.27, CI 0.09-0.85, p=.03; HR 0.37, CI 0.19-0.71, p=.03)

In plain English, p=0.03 means there’s a 3% chance that the difference is due to coincidence, while p=0.001 means there is just one chance in a thousand this is a coincidence. 

Considering this is a cheap and widely available drug, this sounds like great news.

(2) In a blog post at the IIF (International Institute of Forecasters), Prof. John Ioannides of Stanford and two colleagues from Northwestern U. and U. of Sydney say bluntly “Forecasting for COVID-19 has failed”. They go on to analyze the failures in detail and to conjecture reasons for them — which go further and deeper than “fog of war”. Read the whole thing — I can’t do it justice with selective quoting. Just a taste:

Failure in epidemic forecasting is an old problem. In fact, it is surprising that epidemic forecasting has retained much credibility among decision-makers, given its dubious track record. Modeling for swine flu predicted 3,100-65,000 deaths in the UK [11]. Eventually only 457 deaths occurred [12]. The prediction for foot-and-mouth disease expected up to 150,000 deaths in the UK [13] and led to slaughtering millions of animals. However, the lower bound of the prediction was as low as only 50 deaths [13], a figure close to the eventual fatalities. Predictions may work in “ideal”, isolated communities with homogeneous populations, not the complex current global world.[…]

Let’s be clear: even if millions of deaths did not happen this season, they may happen in the next wave, next season, or with some new virus in the future. A doomsday forecast may come handy to protect civilization, when and if calamity hits. However, even then, we have little evidence that aggressive measures which focus only on few dimensions of impact actually reduce death toll and do more good than harm. We need models which incorporate multicriteria objective functions. Isolating infectious impact, from all other health, economy and social impacts is dangerously narrow-minded. More importantly, with epidemics becoming easier to detect, opportunities for declaring global emergencies will escalate. Erroneous models can become powerful, recurrent disruptors of life on this planet. Civilization is threatened from epidemic incidentalomas.

(3) In brief: