Scenario switcher - htm #1377
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Scenario switcher - htm #1377
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…ty as small population size over 7 days will not schedule VMMC through HIV module. Remove HIV_Prevention_Circumcision in assert statement for HIV services delivered in one week
…x with updated NTP2019 TB data
# Conflicts: # resources/malaria/ResourceFile_malaria.xlsx # src/tlo/methods/hiv.py # src/tlo/methods/malaria.py
# Conflicts: # resources/ResourceFile_Improved_Healthsystem_And_Healthcare_Seeking.xlsx # resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES.xlsx # src/tlo/methods/malaria.py # tests/test_malaria.py
# Conflicts: # resources/ResourceFile_HIV.xlsx # src/tlo/methods/hiv.py
…rdioMetabolicDisorders
…or hiv infection and add comments
Co-authored-by: Tim Hallett <39991060+tbhallett@users.noreply.github.com>
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Output plots here - these are the annual numbers of deaths due to HIV/AIDS, TB and malaria for each scenario. Population size 75,000 and scale-up implemented at 2012 and run to 2020. I think all looks fine. TB is always a bit noisy due to low incidence (1 or 2 cases per 1000) but we can still see the benefits of scale-up, and the additional benefit of 'All scale-up' where HIV program would also have a beneficial effect on TB burden.
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…on used in other modules (instead of years since the beginning of the simulation)
tbhallett
approved these changes
Jun 27, 2024
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This PR builds from PR #1273 and adds a set of scale-up scenarios hosted within the HIV module. These scenarios can switch key HIV, TB or malaria parameters to meet targets at a specified date.
The new scale-up parameters are defined in ResourceFile_HIV, sheet scaleup_parameters
HIV parameters meet the 95-95-95 targets
TB parameters meet the 90s targets
Malaria parameters follow the Malawi National Malaria Communication Strategy 2022-2030. Note the limit for ITN coverage is 0.7 (set by the lookup tables which have 0.7 as max coverage) and IRS can be either 0 or 0.8. Therefore neither can be set to 100% coverage. ITN household coverage could be assumed to be 100%, but only 70% of householders sleep under the bed-net.
test_HTMscaleup.py checks the parameters are set correctly and scaled-up appropriately. These tests are not exhaustive - not every parameter is checked and not every combination of scenarios are checked. A selection of parameters are checked for each scenario.
scripts/malaria/analysis_malaria.py can be used to run the scenarios
TO DO: once PR #1273 finalised and in master, pull these changes in to avoid merge conflicts.