Table 2.
Summary of model characteristics and modeling approaches in included studies
| Characteristics | Number (out of 24 models) | % (out of 24 models) | References |
|---|---|---|---|
| (B10) Types of transmission model | |||
| Deterministic, dynamica, compartmental model | 10 | 42 | [12, 29, 39, 46–48, 52–54, 57–59, 61, 66] |
| Analytical model (deterministic, static) | 6 | 25 | [15, 40–44, 51, 55, 56, 60, 64, 65, 67, 75] |
| Stochastic, dynamic individual-based (e.g., agent-based network model) | 4 | 17 | [13, 45, 49, 50, 62, 63, 71] |
| Stochastic, static individual-based (e.g., microsimulation model) | 2 | 8 | [14, 68, 73, 74] |
| Deterministic, static, compartmental (e.g., (semi-)Markov cohort model) | 2 | 8 | [69, 70, 72] |
| (B11) The model captured age-specific care engagement behaviorb | 7 | 29 | [12–14, 45, 53–56, 60, 74] |
| (B12) The model captured age-specific HIV exposure risk or acquisition/transmission risk in an exposurec | 16 | 67 | [12–15, 39–56, 59, 60, 64, 65, 67, 71, 73, 74] |
| (B13) The model captured nonrandom mixingd | 13 | 54 | [12, 13, 39, 45–50, 52–56, 62, 63, 66, 71] |
| (B14) If sexual behaviors explicitly modeled, characteristics of partnership dynamics and/or partner- or act-level sexual behaviors | |||
| Condom use | 13 | 54 | [29, 39, 46, 49, 50, 52–63, 66] |
| Number of concurrent partners (i.e., concurrency), number of partners per year | 12 | 50 | [12, 13, 29, 39, 45, 47–50, 52–58, 62, 63, 71] |
| Frequency of coital acts (within a partnership) | 12 | 50 | [12, 29, 39, 47–50, 52–58, 61, 66, 71] |
| Not modeled | 7 | 29 | [14, 15, 40–44, 51, 64, 65, 67–70, 72–75] |
| Types of relationship/relationship duration/tendency to form various type of relationships | 6 | 25 | [13, 45, 47–50, 53, 54, 61–63] |
| Partner change rate | 5 | 21 | [46–48, 52, 59, 62, 63] |
| Role preference (insertive/receptive/both) | 1 | 4 | [66] |
| Characteristic | Number (out of 20 studies) | % (out of 20 studies) | References |
|---|---|---|---|
| (C15) Approach to long-term health benefit | |||
| (C15.1) Methods of translating averted infections into LYs/QALYs gained or DALYs averted | |||
| Using the transmission model directly | 11 | 55 | [12, 13, 45, 46, 49, 50, 52, 54, 62, 69, 73] |
| Using the transmission model indirectlyd | 3 | 15 | [14, 72, 74] |
| Calculated independent of the transmission model using an analytical approache | 3 | 15 | [29, 51, 60] |
| Using external published estimates for LYs/QALYs/DALYs per averted infection | 2 | 10 | [66, 71] |
| Mixed | 1 | 5 | [70] |
| (C15.2) Effect of delaying age at infection incorporated into LYs/QALYs gained or DALYs averted | |||
| Yesf | 16 | 80 | [12–14, 45, 46, 49–52, 54, 60, 69, 70, 72–74] |
| No | 2 | 10 | [66, 71] |
| Unspecified (insufficient details about the model provided) | 2 | 10 | [29, 62] |
| Characteristic | Number (out of 30 studies) | % (out of 30 studies) | References |
|---|---|---|---|
| (C16) Approach to long-term cost impacts | |||
| (C16.1) Methods of translating averted infections into future cost savings on HIV-related care | |||
| Using the transmission model directly | 22 | 73 | [12, 13, 15, 43, 45, 46, 49, 50, 52–54, 58, 59, 61, 62, 65, 67–70, 72, 73] |
| Using external published estimates | 3 | 10 | [51, 66, 71] |
| Using the transmission model indirectlye | 3 | 10 | [14, 39, 74] |
| Calculated independent of the transmission model using an analytical approache | 1 | 3 | [60] |
| Unspecified | 1 | 3 | [64] |
| (C16.2) Effect of delaying age at infection incorporated into future cost-savings on HIV-related care | |||
| Yesg | 25 | 83 | [12–15, 39, 43, 45, 46, 49, 50, 52–54, 58–60, 64, 65, 67–70, 72–74] |
| No | 3 | 10 | [51, 66, 71] |
| Unspecified | 2 | 7 | [61, 62] |
DALY disability-adjusted life year, LY life year, QALY quality-adjusted life year
aA dynamic model means that force of infection is a function of the size or proportion of the population infected (i.e., prevalence), which changes over time in one simulation run [16]
bIncludes PrEP uptake, linkage to HIV care, and adherence to care or ART, not including studies without sufficient details to infer this feature
cExcluding the effect of intervention, not including models without sufficient details to infer this feature
dIncludes mixing between sexual activity groups and/or different age groups, not including models without sufficient details to infer this feature
eSee Appendix Table A2 for detailed descriptions of the approach used in each study
fAs an example, if a transmission model was used to tabulate life-year measures, and the model uses age-dependent mortality, then the effect of delaying age at infection is captured because an infection incurred at age 25 years had a different impact on mortality than that incurred at age 60 years; a counterexample would be to use a published estimate that assumes constant lifespan regardless of age at infection
gAs an example, if a transmission model was used to tabulate HIV-related care every cycle, then the effect of delaying age at infection is captured because the later the infection happens, the less time costs will be incurred (though costs incurred in later years could be higher); a counterexample is when a published estimate was used which assumed a fixed lifetime HIV cost. In this case, regardless of when the infection happens, it is assumed to incur a constant lifetime HIV cost