X-Git-Url: https://git.njae.me.uk/?a=blobdiff_plain;ds=sidebyside;f=publish.md;fp=publish.md;h=6b4ed59b5a449ebea6f4b70eb125eea112cbace9;hb=5afedd66506be7575034ae6deebcfaa7c2ced978;hp=0000000000000000000000000000000000000000;hpb=4abff18d7988bdea04a267a08a0792ba570fe0bd;p=covid19.git diff --git a/publish.md b/publish.md new file mode 100644 index 0000000..6b4ed59 --- /dev/null +++ b/publish.md @@ -0,0 +1,343 @@ +--- +jupyter: + jupytext: + formats: ipynb,md + text_representation: + extension: .md + format_name: markdown + format_version: '1.2' + jupytext_version: 1.9.1 + kernelspec: + display_name: Python 3 + language: python + name: python3 +--- + + +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) + + +```python Collapsed="false" +import itertools +import collections +import json +import pandas as pd +import numpy as np +from scipy.stats import gmean +import datetime + +import matplotlib as mpl +import matplotlib.pyplot as plt +%matplotlib inline +%load_ext sql +``` + +```python Collapsed="false" +connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid' +``` + +```python Collapsed="false" +%sql $connection_string +``` + +```python Collapsed="false" +# 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 + + +```python Collapsed="false" +last_uk_date = %sql select date from uk_data order by date desc limit 1 +last_uk_date = last_uk_date[0][0] +last_uk_date +``` + +```python Collapsed="false" +last_intl_date = %sql select report_date from weekly_cases order by report_date desc limit 1 +last_intl_date = last_intl_date[0][0] +last_intl_date +``` + +```sql magic_args="results << select date, new_cases, new_deaths " +from uk_data +order by date +``` + +```python +uk_data = results.DataFrame() +uk_data['date'] = uk_data.date.astype('datetime64[ns]') +uk_data.set_index('date', inplace=True) +uk_data.tail(10) +``` + +```python +most_recent_uk_date = %sql select max(date) from uk_data +most_recent_uk_date = most_recent_uk_date[0][0] +most_recent_uk_date +``` + +```sql Collapsed="false" magic_args="results << select geo_id, country_name, culm_deaths " +from weekly_cases join countries using (geo_id) +where geo_id in :COUNTRIES_CORE + and (geo_id, report_date) in (select geo_id, max(report_date) from weekly_cases group by geo_id) +order by geo_id +``` + +```python +thirty_days_ago = most_recent_uk_date - datetime.timedelta(days=30) +thirty_days_ago +``` + +```python +# thirty_days_ago = most_recent_uk_date - datetime.interval(days=30) +total_uk_deaths = %sql select sum(new_deaths) from uk_data +total_uk_deaths = total_uk_deaths[0][0] +deaths_in_past_month = %sql select sum(new_deaths) from uk_data where date > :thirty_days_ago +deaths_in_past_month = deaths_in_past_month[0][0] +cases_in_past_month = %sql select sum(new_cases) from uk_data where date > :thirty_days_ago +cases_in_past_month = cases_in_past_month[0][0] +total_uk_deaths, deaths_in_past_month, cases_in_past_month +``` + +```python Collapsed="false" +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') +``` + +```python Collapsed="false" +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') +``` + +```python Collapsed="false" +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('![Total deaths](covid_deaths_total_linear.png)\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') +``` + +```python Collapsed="false" +# with open('covid_summary.md', 'a') as f: +# f.write('## All-causes deaths, UK\n') +# f.write('\n') +# f.write('![All-causes deaths](deaths-radar.png)\n') +# f.write('\n') +# f.write('### True deaths\n') +# f.write('\n') +# f.write(f'The number of deaths reported in official statistics, {uk_covid_deaths}, is an underestimate ' +# 'of the true number of Covid deaths.\n' +# 'This is especially true early in the pandemic, approximately March to May 2020.\n') +# f.write('We can get a better understanding of the impact of Covid by looking at the number of deaths, ' +# 'over and above what would be expected at each week of the year.\n') +# f.write(f'The ONS (and other bodies in Scotland and Northern Ireland) have released data on the number of deaths ' +# f'up to {pd.to_datetime(excess_deaths_data["end_date"]).strftime("%d %B %Y")}.\n\n') +# f.write('If, for each of those weeks, I take the largest of the excess deaths or the reported Covid deaths, ') +# f.write(f'I estimate there have been **{uk_deaths_to_date}** total deaths so far.\n') +# f.write('\n') +``` + +```python Collapsed="false" +with open('covid_summary.md', 'a') as f: + f.write('### Deaths per week\n') + f.write('\n') + f.write('![Deaths per week](covid_deaths_per_week.png)\n') + f.write('\n') + f.write('![Deaths per week, last 6 weeks](deaths_by_date_last_6_weeks.png)\n') + f.write('\n') +``` + +```python +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('![Total deaths](cases_and_deaths.png)\n') + f.write('\n') + f.write('![Cases and deaths in last 60 days](cases_and_deaths_last_60_days.png)\n') + f.write('\n') + f.write('![Deaths compared to past five years](deaths-radar-2020.png)\n') + f.write('\n') + +``` + +```python Collapsed="false" +with open('hospital_normalisation_date.json') as f: + hospital_normalisation_date_data = json.load(f) +``` + +```python Collapsed="false" +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('![Cases, admissions, deaths](cases_admissions_deaths.png)\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('![People in hospital and on mechancial ventilators](people_in_hospital.png)\n') + f.write('\n') +``` + +```python Collapsed="false" +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('![Positive tests and cases](tests_and_cases.png)\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('![Fraction of tests with positive result](fraction_positive_tests.png)\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('![Tests against fraction positive, trajectory](fraction_positive_tests_vs_tests.png)\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('![Tests against fraction positive, trajectory](tests_vs_fraction_positive_animation.png)\n') + f.write('\n') +``` + +```python Collapsed="false" + +``` + +```python Collapsed="false" +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') + +``` + +```python Collapsed="false" +!pandoc --toc -s covid_summary.md > covid_summary.html +``` + +```python Collapsed="false" +!scp covid_summary.html neil@ogedei:/var/www/scripts.njae.me.uk/covid/index.html +!scp covid_deaths_total_linear.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/ +!scp cases_and_deaths.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/ +!scp cases_and_deaths_last_60_days.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/ +# !scp deaths-radar.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/ +!scp deaths-radar-2020.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/ +!scp covid_deaths_per_week.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/ +!scp fraction_positive_tests.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/ +!scp tests_and_cases.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/ +!scp deaths_by_date_last_6_weeks.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/ +!scp fraction_positive_tests_vs_tests.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/ +!scp tests_vs_fraction_positive_animation.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/ +!scp people_in_hospital.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/ +!scp cases_admissions_deaths.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/ +``` + +```python Collapsed="false" +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('estimated_total_deaths.js', 'w') as f: +# f.write(f"document.write('{uk_deaths_to_date:.0f}');") + +# edut = pd.to_datetime(excess_deaths_data["end_date"]).strftime('%d %B %Y') +# with open('excess_deaths_upto.js', 'w') as f: +# f.write(f"document.write('{edut}');") + +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')}');") + +``` + +```python Collapsed="false" +# pd.to_datetime(excess_deaths_upto).strftime('%d %B %Y') +``` + +```python Collapsed="false" +!scp uk_covid_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/ +!scp uk_deaths_30_days.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/ +!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/ +!scp last_uk_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/ +!scp last_intl_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/ +!scp hospital_normalisation_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/ +``` + +```python Collapsed="false" + +```