In HERU-LEM/LEMHIVpack: Localized Economic HIV Model

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1.0 Data read-in {-}

As described in our evidence synthesis paper, we populated model parameters for each city by synthesizing evidence from 59 peer-reviewed publications and 24 public health and surveillance reports and executed primary analyses using 11 data sets [@evsynth]. Where data were not available, we conducted extensive model validation and calibration to ensure that uncertain model parameters produced results that matched real-world outcomes. We identified parameters that required city-specific data and stratification by gender, risk group and race/ethnicity a priori and sought out databases for primary analysis to augment our evidence synthesis. We also derived information and values for the free parameters; “free parameters” are key uncertain parameters which are not predefined by the model and lead to the most significant uncertainty in target outcomes. The Morris method [@morris1; @morris2; @morris3] was used to select the most influential parameters for calibration, and the Nelder-Mead algorithm [@neldermead1; @neldermead2] was used to iteratively calibrate the model to generate 2,000 best-fitting parameter sets.

Through this iterative calibration to specific targets/endpoints in each city - the number of diagnosed PLHIV at each year end (stratified by sex, race/ethnicity and risk group), the annual number of new HIV diagnoses (separately for the overall estimate, African/American (Black) population, and MSM), and the annual number of all-cause mortality deaths among PLHIV (separately for the overall estimate, African/American (Black) population, and MSM), free parameters and their weights were determined. Further details are provided in our calibration manuscript [@calibration]. All of this information is stored in Evidence-Inputs-Master.xlsx, Evidence-Inputs-Master-Ideal.xlsx and cali_par_all.xlsx found in the Data Files directory, and read-in using the CascadeCEA-Model-1-Module-Data.input.R script.

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1.1 Create grouping indicators {-}

In this component we generate grouping indicators for the 42 population groups; descriptions and R name for each are presented below in Table 1.This function is in the CascadeCEA-Model-0-Group.number.R script in the R directory.

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Table 1: Description of intial model parameters with their R name and values

| Group Indicator Name | Description | R name|# of groups| |:---------------------------------|:-----------------------------------------:|:---------:|:-------------:| | Male | Gender - male |m | 30 | | Female | Gender - female |f | 12 | | White | Race/ethnicity - White | white | 14 | | Black | Race/ethnicity - Blacks/African Americans | black | 14 | | Hispanic | Race/ethnicity - Hispanics/Latinos | hisp | 14 | | All MSM | All MSM groups including MWID |all.msm | 18 | | All PWID | All PWID groups including MWID |all.idu | 24 | | All MSM and PWID | Intersection of all.msm and all.idu | midu | 12 | | Opioid Agonist Therapy (OAT) | | oat | 12 | | Heterosexual | | het | 12 | | Low risk | All low-risk groups, excludes PWID | low | 15 | | High risk | All high-risk groups, excludes PWID | high | 15 | | Low-risk MSM | Intersection of all.msm and low | msm.l | 9 | | High-risk MSM | Difference between all.msm and low | msm.h | 9 | | Low-risk heterosexuals | Intersection of het and low | het.l | 6 | | Low-risk male heterosexuals | Intersection of het.l and m | het.m.l | 6 | | Low-risk female heterosexuals | Intersection of het.l and f | het.f.l | 6 | | MSM only | Difference between all.msm and all.idu | msm | 6 | | PWID only | Difference between all.idu and all.msm | idu | 12 | | Heterosexual males | Intersection of het and m | het.m | 6 | | Heterosexual females | Intersection of het and f | het.f | 6 | | Off Opioid Agonist Therapy (OAT) | Difference between all.idu and oat | off.oat | 12 | | Male PWID | Intersection of idu and m. Excludes MSM | idu.m | 6 | | Female PWID | Intersection of idu and f | idu.f | 6 | | Low-risk MSM | Intersection of msm and low | msmL | 3 | | High-risk MSM | Intersection of msm and high | msmH | 3 | | Low-risk MSM-IDU | Intersection of midu and low | miduL | 6 | | HIgh-risk MSM-IDU | Intersection of midu and high | miduH | 6 | | Low-risk hetersoexual males | Intersection of het.m and low | het.mL | 3 | | High-risk hetersoexual males | Intersection of het.m and high | het.mH | 3 | | Low-risk hetersoexual females | Intersection of het.f and low | het.fL | 3 | | High-risk hetersoexual females | Intersection of het.f and high | het.fH | 3 |

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1.2 Populate cells for model instantiation {-}

In this component, we calculate initial cell sizes for all 42 population strata and 19 model states/compartments using the model_initial function.

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1.3 Parameterization {-}

In this component, we set values for model paramaters with multiple dimensions using CascadeCEA-Model-0-Parameterization.R in the R directory. This includes loading population demographic parameters and parameters that require manipulation (either through calibration, or modification as a result of interventions). Cost-effectiveness analyses (CEA) parameters including QALY parameters, state-level costs, and intervention costs are also initialized in this step.

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1.4 Assign free parameter values {-}

In this component, values for the free parameters are derived, calibrated and updated using CascadeCEA-Model-0-Parameter.update.R in the R directory. Note that this component (1.4 Assign free parameter values) only needs to be done once - when running the model for the first time.

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