Just a quick calculation on my part, if you see any serious errors or omissions please let me know:

• MINSA is currently reporting 18,589 deaths in men over age 60. See page 5 of the data, the actual nr. will probably be higher when you open the page as the data is updated regularly.
• The OpenCovid-Peru project is showing that the total COVID-19 death toll in Peru, based on analysis of death certificates filed, is likely to be about 2.4 times higher than the fatalities reported by MINSA. In my opinion that is a reliable estimate. That would put the actual death toll among men over age 60 around 44,000 to date.
• The population of men over 60 in Peru should be in the magnitude of 1.8 million according to demographic data from the CIA.

Do the math and it appears that COVID-19 has already killed nearly 2.5 percent of men over age 60. That’s about 1 per graduating class if you were in an industrialized country. Peru is just now entering the worst of the second wave, only time will tell what the true impact of COVID-19 will be. So far COVID-19 has been devastating here in Peru and there’s no sign of it letting up any time soon.

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);