Calibration

Demography

We will want to match:

• Population size and structure and breakdown by district from Census
• Number of live-births over time
• Deaths by age/time/sex from WPP/GBD

Scripts to test this are all developed. Results are a bit mixed. Disease module leads asked to examine conditions as part of rolling review process. Example script to do this:

# Get comparison
comparison = compare_number_of_deaths(logfile=sim.log_filepath, resourcefilepath=resourcefilepath)

# Make a simple bar chart
comparison.loc[('2015-2019', slice(None), '0-4', 'Childhood Diarrhoea')].sum().plot.bar()
plt.title('Deaths per year due to Childhood Diarrhoea, 2015-2019')
plt.tight_layout()
plt.show()

Epidemiology

• We will want to match, for each cause of death: overall number, age/sex breakdown

Usage of time of healthcare Workers

• Scripts to be developed to summarise this (see hallett/health-burden-summary-figure)
• Compare to CHAI data (work of Bingling She)

Usage of Consumables

• Scripts to be developed to summarise this (see hallett/health-burden-summary-figure)
• Ask Sakshi to output summary stats of number of items 'consumed' per month or per year.