Matico: herbal COVID-19 treatment with benefits

The word’s on everybodies lips here in Cusco.

“Matico”

Matico is a tropical tree which is believed to have healing characteristics by the native people of the Amazon jungle in Peru. In recent weeks word has been spreading like wildfire throughout the Cusco region that Matico prevents and heals Covid-19. I was going to write about Matico, take some nice pictures, make some silly jokes. Matico is also believed to be an aphrodisiac. Origin of the rumor on Facebook. Quarantine, aphrodisiac, Facebook, you see where that was going.

Alas there will be no silly jokes, just a picture of a glass of Matico drink and some lines of Go code. The healthcare system in Cusco has collapsed, all the news is bad. Decades of institutional failure have caught up with Peru in the Covid-19 crisis and frankly I find work the easiest thing to deal with right now. The time just doesn’t seem right for silly jokes.

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I’m not into herbal supplements but if you are, you might try my friend Colin at Peruvian Naturals. All legit too.

Iquitos Peru possibly the first region with demonstrated herd immunity (Covid-19)

Excellent report in La Republica today. The results are preliminary but there appears to be a strong degree of confidence:

  • 71% of the population show presence of Covid-19 antibodies, 22% IgM (active infection) and 49% IgG (previously infected).
  • Hospitalizations have dropped 90% from the earlier peak of the crisis in Iquitos.

Other areas of Peru, including here in Cusco, appear to be just now entering into the worst of the Covid-19 crisis, which is noteworthy because containment measures have been the same throughout Peru but the epidemic appears to have moved in waves throughout different areas of the country.

UNSAAC study of Covid-19 mortality rates at high elevations

A recently published study by Anahi Cardona and Manuel Montoya of the Universidad Nacional de San Antonio Abad del Cusco (UNSAAC) concludes that there is a statistically significant difference in Covid-19 mortality rates at high elevations.

Here in Cusco there have been 3 fatalities attributed to Covid-19 to date but there is growing concern that the underlying infection rate is set to increase. Time will tell.

Stay safe.

Suspected Covid-19 fatalities left to rot in Cusco (Updated)

Allegedly, unconfirmed, and I very much hope it isn’t true but word reaches that the corpse of a person who died several days ago here in Cusco has still not been removed from the home where the person passed. I cannot confirm this is true but the source is not an internet rumor.

There have been various other reports, some confirmed, of people with symptoms seeking help to no avail. Hope for a miracle.

Update 4/9: Authorities have now formally denied this was happening and it appears the deceased person did not have Covid-19. People remain nervous about the lack of resources to fight the pandemic. As of yesterday, fewer than 400 Covid-19 tests had been administered in Cusco.

Covid-19 transparency, please.

Forget about the wild conspiracies, I’m not going there. But I think as a society we can’t make smart decisions if we don’t have real data. Copy and paste this and email it to your local newspaper or civil registry office. It’s a sample SQL query that would show year-over-year nr. of death certificates issued by fiscal week.

Even with the inherent lag of counting deaths, I think this would provide a much clearer picture of the onset and evolution of the epidemic than most visualizations I’ve seen elsewhere. You pay taxes, you have a right to know.

-- YoY change by fiscal week.
SELECT 
    my_2019_data.fiscal_week AS fiscal_week, 
    my_2019_data.nr_death_certificates AS 2019_deaths,
    my_2020_data.nr_death_certificates AS 2020_deaths,
    CASE WHEN my_2020_data.nr_death_certificates IS NOT NULL THEN to_char( (my_2020_data.nr_death_certificates::numeric - my_2019_data.nr_death_certificates::numeric) / (my_2019_data.nr_death_certificates::numeric / 100::numeric), '999D99' ) ELSE NULL END AS yoy_change_2019_2020 
FROM
  ( SELECT fw AS fiscal_week, count(death_certificates) AS nr_death_certificates 
    FROM
      ( SELECT extract(week FROM date_deceased) AS fw, * 
        FROM my_public_records.death_certificates
        WHERE death_certificates.date_deceased >= '2019-01-01'::date
        AND death_certificates.date_deceased < '2020-01-01'::date
      ) mydata_19
    GROUP BY fw 
    ORDER BY fw 
  ) my_2019_data
LEFT JOIN
  ( SELECT fw AS fiscal_week, count(death_certificates) AS nr_death_certificates 
    FROM
      ( SELECT extract(week FROM date_deceased) AS fw, * 
        FROM my_public_records.death_certificates
        WHERE death_certificates.date_deceased >= '2020-01-01'::date
        AND death_certificates.date_deceased < '2021-01-01'::date
      ) mydata_20
    GROUP BY fw 
    ORDER BY fw 
  ) my_2020_data USING(fiscal_week);