--- /dev/null
+#!/usr/bin/env python
+# coding: utf-8
+# %%
+# Data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)
+
+# %%
+import itertools
+import collections
+import json
+import pandas as pd
+import numpy as np
+from scipy.stats import gmean
+import datetime
+import sqlalchemy
+import os
+
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+
+
+# %%
+connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'
+
+
+# %%
+engine = sqlalchemy.create_engine(connection_string)
+
+
+# %%
+# DEATH_COUNT_THRESHOLD = 10
+COUNTRIES_CORE = tuple('IT DE UK ES IE FR BE'.split())
+# COUNTRIES_NORDIC = 'SE NO DK FI UK'.split()
+# COUNTRIES_FRIENDS = 'IT UK ES BE SI MX'.split()
+# # COUNTRIES_FRIENDS = 'IT UK ES BE SI PT'.split()
+
+# COUNTRIES_AMERICAS = ['AG', 'AR', 'AW', 'BS', 'BB', 'BZ', 'BM', 'BO', 'BR', 'VG', 'KY', # excluding Canada and USA
+# 'CL', 'CO', 'CR', 'CU', 'CW', 'DM', 'DO', 'EC', 'SV', 'GL', 'GD', 'GT',
+# 'GY', 'HT', 'HN', 'JM', 'MX', 'MS', 'NI', 'PA', 'PY', 'PE', 'PR', 'KN',
+# 'LC', 'VC', 'SX', 'SR', 'TT', 'TC', 'VI', 'UY', 'VE']
+# COUNTRIES_OF_INTEREST = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS))
+# COUNTRIES_ALL = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS + COUNTRIES_NORDIC + COUNTRIES_AMERICAS))
+
+
+# # Write results to summary file
+
+# %%
+def singleton_sql_value(engine, query_string):
+ with engine.connect() as conn:
+ result = conn.execute(query_string)
+ return result.next()[0]
+
+
+# %%
+last_uk_date = singleton_sql_value(engine, 'select max(date) from uk_data')
+
+
+# %%
+last_intl_date = singleton_sql_value(engine, 'select max(report_date) from weekly_cases')
+
+
+# %%
+thirty_days_ago = last_uk_date - datetime.timedelta(days=30)
+
+
+# %%
+total_uk_deaths = singleton_sql_value(engine, 'select sum(new_deaths) from uk_data')
+deaths_in_past_month = singleton_sql_value(engine, f"select sum(new_deaths) from uk_data where date > '{thirty_days_ago.isoformat()}'")
+cases_in_past_month = singleton_sql_value(engine, f"select sum(new_cases) from uk_data where date > '{thirty_days_ago.isoformat()}'")
+total_uk_deaths, deaths_in_past_month, cases_in_past_month
+
+
+# %%
+with open('covid_summary.md', 'w') as f:
+ f.write('% Covid death data summary\n')
+ f.write('% Neil Smith\n')
+ f.write(f'% Created on {datetime.datetime.now().strftime("%Y-%m-%d")}\n')
+ f.write('\n')
+ f.write(f'> Last UK data from {last_uk_date.strftime("%d %b %Y")}. ')
+ f.write(f' Last international data from {last_intl_date.strftime("%d %b %Y")}.\n')
+ f.write('\n')
+
+
+# %%
+with open('covid_summary.md', 'a') as f:
+ f.write('## Headlines (UK data)\n')
+ f.write('\n')
+ f.write('| []() | |\n')
+ f.write('|:---|---:|\n')
+ f.write(f'| Deaths reported so far | {total_uk_deaths} | \n')
+ f.write(f'| Deaths in last 30 days | {deaths_in_past_month} | \n')
+ f.write(f'| Cases in last 30 days | {cases_in_past_month} | \n')
+# f.write(f'| Total Covid deaths to date (estimated) | {uk_deaths_to_date:.0f} |\n')
+ f.write('\n')
+
+
+# %%
+query_string = f'''select geo_id, country_name, culm_deaths
+from weekly_cases join countries using (geo_id)
+where geo_id in {COUNTRIES_CORE}
+ and report_date = '{last_intl_date.isoformat()}'
+order by geo_id'''
+
+with engine.connect() as conn:
+ results = list(conn.execute(query_string))
+results
+
+# %%
+with open('covid_summary.md', 'a') as f:
+ f.write('## International comparison\n')
+ f.write('\n')
+ f.write(f'Based on weekly data. Last data from {last_intl_date.strftime("%d %b %Y")}\n')
+ f.write('\n')
+ f.write('### Total deaths\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('| Country ID | Country name | Total deaths |\n')
+ f.write('|:-----------|:-------------|-------------:|\n')
+ for c_id, c_name, t_deaths in results:
+ f.write(f'| {c_id} | {c_name} | {t_deaths} |\n')
+ f.write('\n')
+
+
+# %%
+with open('covid_summary.md', 'a') as f:
+ f.write('### Deaths per week\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('\n')
+
+
+# %%
+with open('covid_summary.md', 'a') as f:
+ f.write('## UK data\n')
+ f.write('\n')
+ f.write('### Total deaths\n')
+ f.write('\n')
+ f.write(f'Deaths reported up to {last_uk_date.strftime("%d %b %Y")}: {total_uk_deaths}\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('\n')
+
+# %%
+with open('hospital_normalisation_date.json') as f:
+ hospital_normalisation_date_data = json.load(f)
+
+
+# %%
+with open('covid_summary.md', 'a') as f:
+ f.write('### Hospital care\n')
+ f.write(f'Based on a 7-day moving average\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('Due to the large scale differences between the three '
+ 'measures, they are all normalised to show changes ')
+ f.write(f'since {pd.to_datetime(hospital_normalisation_date_data["hospital_normalisation_date"]).strftime("%d %B %Y")}.\n')
+ f.write('\n')
+ f.write('People in hospital, and on mechanical ventilators\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('\n')
+
+
+# %%
+with open('covid_summary.md', 'a') as f:
+ f.write('### Testing effectiveness\n')
+ f.write('\n')
+ f.write('A question about testing is whether more detected cases is a result of more tests being '
+ 'done or is because the number of cases is increasing. One way of telling the differeence '
+ 'is by looking at the fraction of tests that are positive.\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('Numbers of positive tests and cases, '
+ '7-day moving average.\n'
+ 'Note the different y-axes\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('Fraction of tests with a positive result, both daily figures and '
+ '7-day moving average.\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('The trajectory of tests done vs fraction positive tests.\n')
+ f.write('\n')
+ f.write('Points higher indicate more tests; points to the right indicate more positive tests.'
+ 'More tests being done with the same infection prevelance will move the point up '
+ 'and to the left.\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('\n')
+ f.write('\n')
+
+
+# %%
+with open('covid_summary.md', 'a') as f:
+ f.write('# Data sources\n')
+ f.write('\n')
+ f.write('> Covid data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)\n')
+ f.write('\n')
+ f.write("""> Population data from:
+
+* [Office of National Statistics](https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/weeklyprovisionalfiguresondeathsregisteredinenglandandwales) (Endland and Wales) Weeks start on a Saturday.
+* [Northern Ireland Statistics and Research Agency](https://www.nisra.gov.uk/publications/weekly-deaths) (Northern Ireland). Weeks start on a Saturday. Note that the week numbers don't match the England and Wales data.
+* [National Records of Scotland](https://www.nrscotland.gov.uk/statistics-and-data/statistics/statistics-by-theme/vital-events/general-publications/weekly-and-monthly-data-on-births-and-deaths/weekly-data-on-births-and-deaths) (Scotland). Note that Scotland uses ISO8601 week numbers, which start on a Monday.""")
+
+ f.write('\n\n')
+ f.write('> [Source code available](https://git.njae.me.uk/?p=covid19.git;a=tree)\n')
+ f.write('\n')
+
+
+# %%
+os.system('pandoc --toc -s covid_summary.md > covid_summary.html')
+
+
+# %%
+os.system('scp covid_summary.html neil@ogedei:/var/www/scripts.njae.me.uk/covid/index.html')
+os.system('scp covid_deaths_total_linear.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp cases_and_deaths.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp cases_and_deaths_last_60_days.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp deaths-radar-2021.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp covid_deaths_per_week.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp fraction_positive_tests.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/ ')
+os.system('scp tests_and_cases.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp deaths_by_date_last_6_weeks.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp fraction_positive_tests_vs_tests.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp tests_vs_fraction_positive_animation.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/ ')
+os.system('scp people_in_hospital.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp cases_admissions_deaths.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+
+
+# %%
+with open('uk_covid_deaths.js', 'w') as f:
+ f.write(f"document.write('{total_uk_deaths}');")
+
+with open('uk_deaths_30_days.js', 'w') as f:
+ f.write(f"document.write('{deaths_in_past_month}');")
+
+with open('uk_cases_30_days.js', 'w') as f:
+ f.write(f"document.write('{cases_in_past_month}');")
+
+with open('last_uk_date.js', 'w') as f:
+ f.write(f"document.write('{pd.to_datetime(last_uk_date).strftime('%d %B %Y')}');")
+
+with open('last_intl_date.js', 'w') as f:
+ f.write(f"document.write('{pd.to_datetime(last_intl_date).strftime('%d %B %Y')}');")
+
+
+# %%
+os.system('scp uk_covid_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp uk_deaths_30_days.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp uk_cases_30_days.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+# # !scp estimated_total_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+# # !scp excess_deaths_upto.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+os.system('scp last_uk_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp last_intl_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp hospital_normalisation_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+
+
+# %%
+
+
+
+
projects / covid19.git / blobdiff