Outputs for early epidemic tests
mmcleod89 opened this issue · 4 comments
mmcleod89 commented
Outputs for checking the behaviour of the simulation in the early epidemic (pre-treatment & testing)
See example outputs given by Jenny, but this will mostly focus on things like:
- Number of people in each age bracket
- Number of deaths
- Number of sexual partners w/demographics
- Number of people with HIV w/demographics
- Number of births
Won't include things like testing as we're focusing on the early era.
- Output module should write these outputs for each timestep into an output file.
- Also want to be able to make graphs. (May be post processing or automatic.)
- List desired outputs in config file.
- Python script for creating comparison plots of single runs with SAS data. (Extended by #171 to allow data aggregation and averages across multiple runs.)
pineapple-cat commented
Current list of outputs to include (from 21/11/23 meeting):
- proportion of people aged 15-64 with a long-term partner (
p_ep) - proportion of people aged 15-64 with at least one short-term partner (
p_newp_ge1) - proportion of people aged 15-64 with at least five short-term partners (
p_newp_ge5) - proportion of women giving birth
- of women with HIV giving birth, proportion of children infected
- proportion of circumcised men aged 15-49
- proportion of female sex workers
- proportion of female sex workers with HIV
- proportion of people aged 15-49 with HIV (prevalence)
- measure of new HIV cases in women and men aged 15-24 (incidence)
- measure of new HIV cases in people aged 15-49 and 15-64 (incidence)
- of the infections in a given time-step, proportion of people that have been infected by a long-term partner (
p_inf_ep) (relies on #162) - of the infections in a given time-step, proportion of people that have been infected by someone in the primary infection phase (
p_inf_primary) - number of women and men aged 15+ and 20-59 dead (
n_death_2059_w,n_death_2059_m) - number of people with CD4 counts <200, 200-500, and >500 (
n_cd4_lt200) - number of people aged 15+ alive (
n_alive) - number of people with HIV (
n_hiv) - number of live births
- number of births to infected women
Additional outputs for validation:
- short-term partner gender balance (
log_gender_r_newp) - short-term partner gender balance divided by age groups (
logm15r,logm25r,logm35r,logm45r,logm55r,logw15r,logw25r,logw35r,logw45r,logw55r) - of the infections in a given time-step, proportion of people that have been infected by a short-term partner (
p_inf_newp)
mmcleod89 commented
As an example for the log gender balance variables, I think the calculation is as follows:
for logm15r this is for men with 15 <= age < 25
- The numerator is: sum of short term partners over all men in this age bracket
- The denominator is: looking at all sexually active women, add up the short term partners who are men 15-25. (For us this is made a bit more complicated by the fact that each short term partner is allowed to have their own age.)
- Take the log of this ratio
@UCL/hiv-modelling does this calculation look right to you?
andrew-phillips-1 commented
Hi Michael @mmcleod89 - Thanks - this looks right to me, yes.