Structural Design and Data Requirements for Simulation Modelling in HIV/AIDS: A Narrative Review.

Born out of a necessity for fiscal sustainability, simulation modeling is playing an increasingly prominent role in setting priorities for combination implementation strategies for HIV treatment and prevention globally. The design of a model and the data inputted into it are central factors in ensuring credible inferences. We executed a narrative review of a set of dynamic HIV transmission models to comprehensively synthesize and compare the structural design and the quality of evidence used to support each model. We included 19 models representing both generalized and concentrated epidemics, classified as compartmental, agent-based, individual-based microsimulation or hybrid in our review. We focused on four structural components (population construction; model entry, exit and HIV care engagement; HIV disease progression; and the force of HIV infection), and two analytical components (model calibration/validation; and health economic evaluation, including uncertainty analysis). While the models we reviewed focused on a variety of individual interventions and their combinations, their structural designs were relatively homogenous across three of the four focal components, with key structural elements influenced by model type and epidemiological context. In contrast, model entry, exit and HIV care engagement tended to differ most across models, with some health system interactions-particularly HIV testing-not modeled explicitly in many contexts. The quality of data used in the models and the transparency with which the data was presented differed substantially across model components. Representative and high-quality data on health service delivery were most commonly not accessed or were unavailable. The structure of an HIV model should ideally fit its epidemiological context and be able to capture all efficacious treatment and prevention services relevant to a robust combination implementation strategy. Developing standardized guidelines on evidence syntheses for health economic evaluation would improve transparency and help prioritize data collection to reduce decision uncertainty

Structural Design and Data Requirements for Simulation Modelling in HIV/AIDS: A Narrative Review.

Born out of a necessity for fiscal sustainability, simulation modeling is playing an increasingly prominent role in setting priorities for combination implementation strategies for HIV treatment and prevention globally. The design of a model and the data inputted into it are central factors in ensuring credible inferences. We executed a narrative review of a set of dynamic HIV transmission models to comprehensively synthesize and compare the structural design and the quality of evidence used to support each model. We included 19 models representing both generalized and concentrated epidemics, classified as compartmental, agent-based, individual-based microsimulation or hybrid in our review. We focused on four structural components (population construction; model entry, exit and HIV care engagement; HIV disease progression; and the force of HIV infection), and two analytical components (model calibration/validation; and health economic evaluation, including uncertainty analysis). While the models we reviewed focused on a variety of individual interventions and their combinations, their structural designs were relatively homogenous across three of the four focal components, with key structural elements influenced by model type and epidemiological context. In contrast, model entry, exit and HIV care engagement tended to differ most across models, with some health system interactions-particularly HIV testing-not modeled explicitly in many contexts. The quality of data used in the models and the transparency with which the data was presented differed substantially across model components. Representative and high-quality data on health service delivery were most commonly not accessed or were unavailable. The structure of an HIV model should ideally fit its epidemiological context and be able to capture all efficacious treatment and prevention services relevant to a robust combination implementation strategy. Developing standardized guidelines on evidence syntheses for health economic evaluation would improve transparency and help prioritize data collection to reduce decision uncertainty

Development and Calibration of a Dynamic HIV Transmission Model for 6 US Cities.

Background. Heterogeneity in HIV microepidemics across US cities necessitates locally oriented, combination implementation strategies to prioritize resources. We calibrated and validated a dynamic, compartmental HIV transmission model to establish a status quo treatment scenario, holding constant current levels of care for 6 US cities. Methods. Built off a comprehensive evidence synthesis, we adapted and extended a previously published model to replicate the transmission, progression, and clinical care for each microepidemic. We identified a common set of 17 calibration targets between 2012 and 2015 and used the Morris method to select the most influential parameters for calibration. We then applied the Nelder-Mead algorithm to iteratively calibrate the model to generate 2000 best-fitting parameter sets. Finally, model projections were internally validated with a series of robustness checks and externally validated against published estimates of HIV incidence, while the face validity of 25-year projections was assessed by a Scientific Advisory Committee (SAC). Results. We documented our process for model development, calibration, and validation to maximize its transparency and reproducibility. The projected outcomes demonstrated a good fit to calibration targets, with a mean goodness-of-fit ranging from 0.0174 (New York City [NYC]) to 0.0861 (Atlanta). Most of the incidence predictions were within the uncertainty range for 5 of the 6 cities (ranging from 21% [Miami] to 100% [NYC]), demonstrating good external validity. The face validity of the long-term projections was confirmed by our SAC, showing that the incidence would decrease or remain stable in Atlanta, Los Angeles, NYC, and Seattle while increasing in Baltimore and Miami. Discussion. This exercise provides a basis for assessing the incremental value of further investments in HIV combination implementation strategies tailored to urban HIV microepidemics

Development and Calibration of a Dynamic HIV Transmission Model for 6 US Cities.

Background. Heterogeneity in HIV microepidemics across US cities necessitates locally oriented, combination implementation strategies to prioritize resources. We calibrated and validated a dynamic, compartmental HIV transmission model to establish a status quo treatment scenario, holding constant current levels of care for 6 US cities. Methods. Built off a comprehensive evidence synthesis, we adapted and extended a previously published model to replicate the transmission, progression, and clinical care for each microepidemic. We identified a common set of 17 calibration targets between 2012 and 2015 and used the Morris method to select the most influential parameters for calibration. We then applied the Nelder-Mead algorithm to iteratively calibrate the model to generate 2000 best-fitting parameter sets. Finally, model projections were internally validated with a series of robustness checks and externally validated against published estimates of HIV incidence, while the face validity of 25-year projections was assessed by a Scientific Advisory Committee (SAC). Results. We documented our process for model development, calibration, and validation to maximize its transparency and reproducibility. The projected outcomes demonstrated a good fit to calibration targets, with a mean goodness-of-fit ranging from 0.0174 (New York City [NYC]) to 0.0861 (Atlanta). Most of the incidence predictions were within the uncertainty range for 5 of the 6 cities (ranging from 21% [Miami] to 100% [NYC]), demonstrating good external validity. The face validity of the long-term projections was confirmed by our SAC, showing that the incidence would decrease or remain stable in Atlanta, Los Angeles, NYC, and Seattle while increasing in Baltimore and Miami. Discussion. This exercise provides a basis for assessing the incremental value of further investments in HIV combination implementation strategies tailored to urban HIV microepidemics

Building the Case for Localized Approaches to HIV: Structural Conditions and Health System Capacity to Address the HIV/AIDS Epidemic in Six US Cities.

Since the discovery of the secondary preventive benefits of antiretroviral therapy, national and international governing bodies have called for countries to reach 90% diagnosis, ART engagement and viral suppression among people living with HIV/AIDS. The US HIV epidemic is dispersed primarily across large urban centers, each with different underlying epidemiological and structural features. We selected six US cities, including Atlanta, Baltimore, Los Angeles, Miami, New York, and Seattle, with the objective of demonstrating the breadth of epidemiological and structural differences affecting the HIV/AIDS response across the US. We synthesized current and publicly-available surveillance, legal statutes, entitlement and discretionary funding, and service location data for each city. The vast differences we observed in each domain reinforce disparities in access to HIV treatment and prevention, and necessitate targeted, localized strategies to optimize the limited resources available for each city's HIV/AIDS response

Can the 'Ending the HIV Epidemic' initiative transition the USA towards HIV/AIDS epidemic control?

: Using a dynamic HIV transmission model calibrated for six USA cities, we projected HIV incidence from 2020 to 2040 and estimated whether an established UNAIDS HIV epidemic control target could be met under ideal implementation of optimal combination strategies previously defined for each city. Four of six cities (Atlanta, Baltimore, New York City and Seattle) were projected to achieve epidemic control by 2040 and we identified differences in reaching epidemic control across racial/ethnic groups

Developing a dynamic HIV transmission model for 6 U.S. cities: An evidence synthesis.

BackgroundDynamic HIV transmission models can provide evidence-based guidance on optimal combination implementation strategies to treat and prevent HIV/AIDS. However, these models can be extremely data intensive, and the availability of good-quality data characterizing regional microepidemics varies substantially within and across countries. We aim to provide a comprehensive and transparent description of an evidence synthesis process and reporting framework employed to populate and calibrate a dynamic, compartmental HIV transmission model for six US cities.MethodsWe executed a mixed-method evidence synthesis strategy to populate model parameters in six categories: (i) initial HIV-negative and HIV-infected populations; (ii) parameters used to calculate the probability of HIV transmission; (iii) screening, diagnosis, treatment and HIV disease progression; (iv) HIV prevention programs; (v) the costs of medical care; and (vi) health utility weights for each stage of HIV disease progression. 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 ranked the quality of each parameter using context- and domain-specific criteria and verified sources and assumptions with our scientific advisory committee.FindingsTo inform the 1,667 parameters needed to populate our model, we synthesized evidence from 59 peer-reviewed publications and 24 public health and surveillance reports and executed primary analyses using 11 data sets. Of these 1,667 parameters, 1,517 (91%) were city-specific and 150 (9%) were common for all cities. Notably, 1,074 (64%), 201 (12%) and 312 (19%) parameters corresponded to categories (i), (ii) and (iii), respectively. Parameters ranked as best- to moderate-quality evidence comprised 39% of the common parameters and ranged from 56%-60% across cities for the city-specific parameters. We identified variation in parameter values across cities as well as within cities across risk and race/ethnic groups.ConclusionsBetter integration of modelling in decision making can be achieved by systematically reporting on the evidence synthesis process that is used to populate models, and by explicitly assessing the quality of data entered into the model. The effective communication of this process can help prioritize data collection of the most informative components of local HIV prevention and care services in order to reduce decision uncertainty and strengthen model conclusions

Ending the HIV Epidemic Among Persons Who Inject Drugs: A Cost-Effectiveness Analysis in Six US Cities.

BackgroundPersons who inject drugs (PWID) are at a disproportionately high risk of HIV infection. We aimed to determine the highest-valued combination implementation strategies to reduce the burden of HIV among PWID in 6 US cities.MethodsUsing a dynamic HIV transmission model calibrated for Atlanta, Baltimore, Los Angeles, Miami, New York City, and Seattle, we assessed the value of implementing combinations of evidence-based interventions at optimistic (drawn from best available evidence) or ideal (90% coverage) scale-up. We estimated reduction in HIV incidence among PWID, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios (ICERs) for each city (10-year implementation; 20-year horizon; 2018 $US).ResultsCombinations that maximized health benefits contained between 6 (Atlanta and Seattle) and 12 (Miami) interventions with ICER values ranging from$94 069/QALY in Los Angeles to $146 256/QALY in Miami. These strategies reduced HIV incidence by 8.1% (credible interval [CI], 2.8%-13.2%) in Seattle and 54.4% (CI, 37.6%-73.9%) in Miami. Incidence reduction reached 16.1%-75.5% at ideal scale.ConclusionsEvidence-based interventions targeted to PWID can deliver considerable value; however, ending the HIV epidemic among PWID will require innovative implementation strategies and supporting programs to reduce social and structural barriers to care

Human Immunodeficiency Virus transmission by HIV Risk Group and Along the HIV Care Continuum: A Contrast of 6 US Cities

Understanding the sources of HIV transmission provides a basis for prioritizing HIV prevention resources in specific geographic regions and populations. This study estimated the number, proportion, and rate of HIV transmissions attributable to individuals along the HIV care continuum within different HIV transmission risk groups in 6 US cities. We used a dynamic, compartmental HIV transmission model that draws on racial behavior-specific or ethnic behavior-specific and risk behavior-specific linkage to HIV care and use of HIV prevention services from local, state, and national surveillance sources. We estimated the rate and number of HIV transmissions attributable to individuals in the stage of acute undiagnosed HIV, nonacute undiagnosed HIV, HIV diagnosed but antiretroviral therapy (ART) naïve, off ART, and on ART, stratified by HIV transmission group for the 2019 calendar year. Individuals with undiagnosed nonacute HIV infection accounted for the highest proportion of total transmissions in every city, ranging from 36.8% (26.7%-44.9%) in New York City to 64.9% (47.0%-71.6%) in Baltimore. Individuals who had discontinued ART contributed to the second highest percentage of total infections in 4 of 6 cities. Individuals with acute HIV had the highest transmission rate per 100 person-years, ranging from 76.4 (58.9-135.9) in Miami to 160.2 (85.7-302.8) in Baltimore. These findings underline the importance of both early diagnosis and improved ART retention for ending the HIV epidemic in the United States. Differences in the sources of transmission across cities indicate that localized priority setting to effectively address diverse microepidemics at different stages of epidemic control is necessary