Preexposure Prophylaxis to Eliminate HIV in Taiwan by 2030: A Modeling Study

doi:10.21203/rs.3.rs-3311713/v1

Download PDF

Article

Preexposure Prophylaxis to Eliminate HIV in Taiwan by 2030: A Modeling Study

https://doi.org/10.21203/rs.3.rs-3311713/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Preexposure prophylaxis (PrEP) demonstrated 86% efficacy in randomized trials. However, globally, PrEP remains underutilized. The role of PrEP in achieving HIV elimination has been underappreciated and understudied. In Taiwan, the HIV epidemic predominantly affects young, sexually active men who have sex with men (MSM). Our stochastic modeling indicates that the HIV test-and-treat strategy has minimal impact on HIV transmissions that occur during the acute HIV infection. In contrast, a PrEP program providing access to 50% of young, high-risk MSM will halve transmissions during the acute stage and suppress the basic reproduction number (R0) of HIV to below 1, thereby facilitating its elimination. Risk compensation (i.e., none of the PrEP users using condom), imperfect adherence (at 75%), or drug resistance (at a 1% rate) do not undermine such a program's effectiveness. Deterministic modeling further indicates that implementing a 50% coverage PrEP program will reduce the trajectory of the HIV epidemic in Taiwan to below the World Health Organization’s HIV elimination threshold (1/1,000 person-years) by 2030, and such a program is highly cost-saving from a societal perspective, yielding a benefit-cost ratio of 7.16. Our findings strongly support the broad administration of PrEP to high-risk, HIV-negative MSM to achieve HIV elimination by 2030.

Health sciences/Health care/Public health/Epidemiology

Health sciences/Diseases/Infectious diseases/HIV infections

Two randomized trials, the IPERGAY study ¹ and the PROUD study ², have demonstrated that preexposure prophylaxis (PrEP) with oral emtricitabine/tenofovir (Truvada™) is highly effective when taken either daily or on demand, preventing up to 86% of HIV infections among high-risk, HIV-negative men who have sex with men (MSM). An open-label extension of the IPERGAY study further indicates that, with good adherence, the efficacy of PrEP can be as high as 97% ³. Despite these promising results, global utilization of PrEP remains limited ^{4, 5}. Financial constraints are a major barrier ^{4, 5, 6}. Additional barriers include concerns about risk compensation (i.e., increased risk-taking behaviors due to perceived reductions in HIV risk from PrEP use) ^{7, 8}, non-adherence ^{9, 10}, and the drug resistance ^{11, 12}. These challenges could hamper the control of the HIV epidemic. To date, the role of PrEP in achieving the elimination of HIV remains underappreciated and understudied ^{13, 14}.

In Taiwan, the HIV epidemic predominantly affects young, sexually active MSM, with more than 2,000 new HIV diagnoses annually from 2012 to 2017 ¹⁵. Since 2015, the Taiwan Centers for Disease Control (CDC) have implemented the World Health Organization (WHO) guidelines on initiating antiretroviral therapy (ART) immediately after an HIV diagnosis ¹⁶, aiming to achieve the UNAIDS 90-90-90 goal to decrease both HIV transmission and mortality through early ART ¹⁷. The proportion of HIV patients on ART in Taiwan improved from 67% in 2014 to 88% in 2018 ^{18, 19}. The number of new HIV diagnoses decreased to 1,991 in 2018 and 1,755 in 2019, respectively ¹⁵. In 2020, Taiwan achieved the UNAIDS 90-90-90 targets, with 90% of people living with HIV knowing their status, 93% of diagnosed patients receiving ART, and 95% of treated patients reaching an undetectable viral load ²⁰. However, up to one-third (30–40%) of new HIV patients in 2018 and thereafter were not diagnosed until the late stage ¹⁹. Moreover, during the period from 2020 through 2022, the COVID-19 pandemic led to a 30%-40% decline in HIV testing rates in Taiwan. Therefore, additional strategies that are more resilient to such disruptions than intensive HIV testing and treatment are required for eliminating HIV among this highly vulnerable population.

Cost has been a major barrier to access to PrEP in Taiwan ^{21, 22}, particularly for young MSM who are at the highest risk for HIV. The 2018–2019 PrEP demonstration project in Taiwan, with approximately 1,000 MSM participants, was supported by a donation from Gilead Science Inc. To date, public funding for the PrEP program for MSM in Taiwan remains limited, covering only Truvada™ 20 tablets every three months.

Rapid, targeted, high-coverage roll-out of PrEP was associated with a rapid decline in new HIV diagnoses in New South Wales, Australia ²³. Modeling studies suggested that HIV elimination might be possible in the Netherlands and the Paris region with PrEP coverage rates of 82% and 55%, respectively ^{24, 25}. However, the necessity, impact on achieving the WHO's goal to end the AIDS epidemic by 2030, and cost-effectiveness of implementing a high-coverage PrEP program for HIV elimination have not yet been evaluated. The present modeling study, based on comprehensive real-world Taiwan national HIV surveillance and cascade data, aimed to address the following four key questions regarding a high-coverage PrEP program targeting sexually active, high-risk, HIV-negative MSM in Taiwan:

The impact on the basic reproduction number (R0) of HIV, compared with the HIV test-and-treat strategy alone

The effects of risk compensation, drug resistance, and non-adherence on the impact of the PrEP program.

The impact on the trajectory of HIV epidemic in the next 20 years, compared with the HIV test-and-treat strategy alone

The cost-effectiveness, from an elimination perspective.

Necessity of a high coverage PrEP program for HIV elimination

We estimated the R0 as the average number of HIV transmissions that would occur during the life course of an HIV-positive young MSM with high-risk sexual behavior (50 partners/year), from 20 years to 45 years, during 1,000 simulations (see Methods: Stochastic modeling). Table 1 shows that, in the absence of PrEP, even an intense HIV test-and-treat campaign with annual HIV testing followed by immediate ART would be insufficient to suppress R0 to below 1. In contrast, a PrEP program that targets young high-risk MSM with a coverage rate of 50% will suppress the R0 of HIV to below 1, even if HIV test-and-treat remains at the status quo. Table 1 further reveal that HIV test-and-treat strategy have only minimal impact on the number of HIV transmissions that occur during the acute HIV infection stage (highlighted with brackets). Conversely, a 50% coverage PrEP program halves the HIV transmissions occurring during the acute infection stage—a reduction uniquely achievable through PrEP. Moreover, the program's impact on curtailing acute-stage transmissions increases proportionally with the coverage rate. Thus, PrEP is indispensable for the elimination of HIV among MSM.

Table 1

Impact of Test-and-Treat strategy, without or with PrEP, on the basic reproduction number, Ro, of HIV among high-risk MSM population (sexual partners = 50/year)
Basic Reproductive Number, R0 (Transmissions occur in acute stage)		PrEP coverage rate
		0%	25%	50%	75%	100%
Testing rate	Without testing, care and ART	2.98 (0.97)	2.36 (0.76)	1.70 (0.55)	1.05 (0.35)	0.41 (0.14)
	Once every 2.5 years HIV testing with HIV cascade (Status Quo)	1.46 (0.95)	1.11 (0.72)	0.79 (0.53)	0.54 (0.37)	0.20 (0.13)
	Annual HIV testing with HIV cascade	1.24 (0.97)	0.92 (0.73)	0.67 (0.52)	0.44 (0.34)	0.16 (0.13)
	Annual HIV testing followed by immediate ART	1.11 (0.88)	0.90 (0.74)	0.62 (0.50)	0.41 (0.33)	0.16 (0.13)

Table 2

Effect of (A) risk compensation and (B) 1% drug resistance on the basic reproduction number, R0, of HIV among high-risk MSM population (number of sexual partners: 50/year) (A) Risk compensation (none of PrEP users using condom)
Basic Reproductive Number, R0 (Transmissions occur in acute stage)		PrEP coverage rate
		0%	25%	50%	75%	100%
Testing Rate	Without testing, care and ART	2.88 (0.94)	2.24 (0.71)	1.66 (0.56)	1.00 (0.31)	0.40 (0.11)
	Once every 2.5 years HIV testing with HIV cascade (Status Quo)	1.51 (1.01)	1.18 (0.73)	0.79 (0.53)	0.50 (0.32)	0.21 (0.13)
	Annual HIV testing with HIV cascade	1.23 (0.94)	0.94 (0.75)	0.70 (0.52)	0.45 (0.34)	0.18 (0.14)
	Annual HIV testing followed by immediate ART	1.16 (0.95)	0.93 (0.75)	0.65 (0.52)	0.40 (0.32)	0.16 (0.12)

Table 2

(Continued) (B) 1% drug resistance (efficacy of PrEP drops to zero for an encounter with HIV-positive patient infected with emtricitabine/ tenofovir-resistant HIV strain)
Basic Reproductive Number, R0 (Transmissions occur in acute stage)		PrEP coverage rate
		0%	25%	50%	75%	100%
Testing rate	Without testing, care and ART	2.96 (0.96)	2.34 (0.78)	1.70 (0.56)	1.06 (0.35)	0.45 (0.15)
	Once every 2.5 years HIV testing with HIV cascade (Status Quo)	1.45 (0.94)	1.16 (0.76)	0.84 (0.55)	0.51 (0.33)	0.22 (0.15)
	Annual HIV testing with HIV cascade	1.20 (0.94)	0.96 (0.75)	0.68 (0.53)	0.44 (0.34)	0.18 (0.14)
	Annual HIV testing followed by immediate ART	1.14 (0.92)	0.89 (0.72)	0.64 (0.53)	0.41 (0.34)	0.17 (0.14)

Effect of risk compensation on the impact of a PrEP program

We modeled the effect of risk compensation, defined as a decrease in the condom use rate from the status quo (30%) to 0% among all high-risk MSM who take PrEP in the program. Table 2A shows that, in contrast to popular concern, risk compensation actually does not have an apparent effect on the impact of a PrEP program, as seen when comparing Table 1 with Table 2A.

Effect of drug resistance on the impact of a PrEP program

We modeled the effect of 1% drug resistance (where the efficacy of PrEP drops to zero during an encounter with an HIV-positive patient infected with an emtricitabine/tenofovir-resistant HIV strain). Table 2B shows that a drug resistance level of 1% does not have an apparent effect on the impact of a PrEP program, as seen when comparing Table 1 with Table 2B.

Effect of non-adherence on the impact of a PrEP program

We then modeled the effect of non-adherence to taking PrEP (assuming that 100% adherence corresponds to an efficacy of 97%) on the R0 of HIV among the high-risk MSM population (with 50 sexual partners per year), under the status quo HIV test-and-treat. Table 3 shows that at least 75% adherence is required for a 50% coverage rate in a PrEP program to suppress the R0 of HIV to less than 1. Figure 1 illustrates the isolines for R0, demonstrating the trade-off between adherence and coverage rate among the high-risk MSM population.

Table 3

Effect of non-adherence (assuming an efficacy of PrEP is 97% when adherence is 100%) on the basic reproduction number, Ro, of HIV among high-risk MSM population (number of sexual partners: 50/year), under status quo HIV test-and-treat (once every 2.5 years HIV testing with HIV cascade)
Basic Reproductive Number, R0 (Transmissions occur in acute stage)		PrEP coverage rate
		0%	25%	50%	75%	100%
Compliance	100%	1.49 (0.99)	1.11 (0.74)	0.73 (0.51)	0.41 (0.26)	0.04 (0.02)
	75%	1.47 (0.97)	1.19 (0.74)	0.98 (0.64)	0.67 (0.44)	0.40 (0.26)
	50%	1.43 (0.95)	1.27 (0.82)	1.11 (0.75)	0.96 (0.63)	0.78 (0.50)
	25%	1.52 (0.99)	1.34 (0.87)	1.39 (0.90)	1.17 (0.78)	1.12 (0.74)
	0%	1.44 (0.90)	1.47 (0.97)	1.55 (1.02)	1.42 (0.88)	1.44 (0.96)

Under the status quo, HIV will become endemic in Taiwan after 2030

To model the impact of a PrEP program on the trajectory of the HIV epidemic over the next 20 years, we constructed a deterministic model that takes into account the natural history of HIV disease progression, the HIV care cascade (from testing and linking to care, through to ART) (Fig. 2), as well as risk and age structure (See Methods: deterministic modeling). We calibrated the model to fit HIV surveillance data among MSM from 1990 to 2019 in Taiwan (Fig. 3). We then simulated the model under the status quo (current HIV test-and-treat rate, with limited PrEP provision at the level of the 2018–2019 demonstration project) from 2020 to 2050. Figure 4A shows that by maintaining the status quo, the HIV epidemic in MSM will initially drop rapidly from 2020 to 2026, and then enter an endemic stage. The lowest number of new HIV diagnoses will be 395 in the year 2035; thereafter, the number of HIV diagnoses will rise again.

High coverage PrEP will eliminate HIV by 2030

In accordance with stochastic modeling results, Fig. 4A shows that, in the absence of the disruption by the COVID-19 pandemic, initiating a PrEP program, scaled up over a one-year period (2021), and achieving 50% coverage in 2022 and thereafter among young high-risk MSM (15 to 44 years old), will effectively suppress HIV incidence to levels below the WHO HIV elimination threshold (HIV incidence: 1/1,000 person-years) by 2030. This approach could avert as many as 5,615 (57.7%) new HIV infections by 2040. If the PrEP coverage rate in 2022 and thereafter among young high-risk MSM increases to 75%, the time point for achieving HIV elimination will be accelerated to the year 2026.

Intensive HIV Test-and-Treat alone will not be sufficient to eliminate HIV

In keeping with the stochastic modelling results, Fig. 4B shows that an intensive HIV test-and-treat strategy alone, scaled up over a three-year period (2021–2024) with annual HIV testing for high-risk MSM aged 15 to 44 years, and immediate ART for 90% of diagnosed HIV patients, will not suffice to reduce HIV incidence to levels below the WHO HIV elimination threshold. However, it will avert 3,863 (39.7%) new HIV infections by 2040.

Synergism between PrEP and HIV Test-and-Treat

Similar to the stochastic modelling results, Fig. 4C illustrates the synergism between the PrEP program and HIV Test-and-Treat. Neither a 25% coverage rate in the PrEP program alone (among high-risk MSM aged 15 to 44 years) nor an HIV Test-and-Treat strategy alone (annual HIV testing targeted at high-risk MSM aged 15–44 with immediate ART for 90% of new HIV cases among MSM) will suffice to suppress the trajectory of the HIV epidemic to levels below the WHO HIV elimination threshold. However, the combination of both the above-stated interventions will suppress the HIV epidemic to levels below the elimination threshold by 2030.

HIV elimination by PrEP: sensitivity analysis by deterministic modeling

Table 4 shows the impact of key parameters on the feasibility of HIV elimination by PrEP, and if applicable, the timing to reach the WHO HIV elimination threshold, as determined by deterministic modeling. The coverage rate of PrEP among young high-risk MSM is the single key factor. If the coverage rate drops to 25%, then HIV elimination will not be feasible. In contrast, the often-raised concerns—including a drop in the condom use rate among PrEP users (from the current 30–0%), imperfect (75%) adherence to PrEP, an increase in the rate (to 10%) of PrEP drug resistance, an increase (to 25%) in the proportion of MSM engaging in high-risk behaviors, or no increase in the HIV testing rate among PrEP users—may delay the timing to reach the WHO HIV elimination threshold but will not change the outcome of HIV elimination by PrEP. These results also highlight that to successfully eliminate HIV by 2030, it is important to continuously educate people to ensure regular HIV testing among PrEP users, good adherence to minimize the emergence of drug resistance, and the minimization of high-risk behaviors.

Table 4

HIV elimination by PrEP: sensitivity analyses, by deterministic modelling
Scenario	HIV infections averted* N (%)	HIV Elimination† Year (C.E.)
Base scenario^a	5,615 (57.7)	2030
Coverage of PrEP decreased to 25%	3,464 (35.6)	Not feasible
Coverage of PrEP increased to 75%	6,953 (71.5)	2026
Scaling up PrEP program in 2019	6,295 (64.7)	2029
Delayed scaling up PrEP program in 2023	5,276 (54.3)	2029
Condom usage reduced from 30–0% among PrEP users	5,446 (56.0)	2031
Adherence to PrEP reduced to 75%	5,233 (53.8)	2032
Drug resistance to PrEP increased to 10%	5,330 (54.8)	2032
HIV testing rate not increased by PrEP program scaling up	5,268 (54.2)	2031
Proportion of high-risk group increasing from 17–25% between 2021 and 2024	5,049 (51.9)	2036
*Number of HIV infections and number of HIV-related death averted from Year of 2021 to Year of 2040, compared to the trajectory under the current status quo.
†HIV epidemic elimination defined by WHO as incidence lower than 1/1,000 per year.
^a The base scenario is a 50% coverage rate of PrEP targeting high-risk MSM aged 15 to 44, with 86% efficacy, scaled up over a one-year period (2021), and achieving 50% coverage in 2022 and thereafter among young high-risk MSM (15 to 44 years old). This PrEP program is associated with a 50% increase in the HIV testing rate (to be eligible for PrEP) among high-risk MSM aged 15 to 44. The proportion of the high-risk group remains stable at 17% of all MSM aged 15 to 44.

Cost and cost-effectiveness of a 50% coverage PrEP program

A high-coverage PrEP program, which includes HIV testing, renal function testing, tests for sexually transmitted infections at follow-up, and PrEP case management services, will cost 84,216 NTD (or 2,807 USD, at an exchange rate of 30 NTD for 1 USD) per person in the first year. Then it will cost 77,576 NTD (2,585.87 USD) per person in each following year (Supplementary Table 4). For comparison, each new HIV diagnosis is associated with a lifetime medical cost of 5.3 million NTD (177,165.5 USD) for patients initially without AIDS, and 4.9 million NTD (163,243.7 USD), respectively (Supplementary Table 5). A PrEP program with a 50% coverage rate for MSM aged 15–44 years at high risk for HIV over a 20-year period (2021–2040) will cost 6.8 billion NTD (227.2 million USD). However, it will avert 4,458 new HIV diagnoses (3,329 non-late diagnoses and 1,129 late diagnoses) and gain 33,864.5 quality-adjusted life years (QALYs), including the 18,109.3 QALYs gained from averting 3,329 non-late HIV diagnoses and the 15,755.1 QALYs gained from averting 1,129 late HIV diagnoses and death (Table 5). This will save 23.2 billion NTD (774.1 million USD) in HIV-associated medical costs and 25.6 billion NTD (851.9 million USD) in HIV-associated losses in human capital. From a societal perspective, a PrEP program with a 50% coverage rate for young high-risk MSM is highly cost-saving, with a benefit-cost ratio of 7.16 (for every 1 NTD spent on the PrEP program, 7.16 NTD of total societal cost, including medical costs and losses in human capital, will be saved).

Table 5

HIV diagnoses averted and quality-adjusted life year (QALY) gained by a high- coverage PrEP program.
	HIV diagnosed		QALY gained^b
	Cases	Averted cases^a N (%)	QALY gained^b
(a) Non-AIDS patients
Status quo (under 2020 situation)	8,365	-
25% coverage of PrEP	6,321	2,044 (24.4)	9,716.3
50% coverage of PrEP	5,036	3,329 (39.8)	18,109.3
75% coverage of PrEP	4,178	4,187 (50.1)	22,777.6
(b) AIDS patients
Status quo (under 2020 situation)	4,493	-
25% coverage of PrEP	3,824	669 (14.9)	8,101.3
50% coverage of PrEP	3,363	1,129 (25.1)	15,755.3
75% coverage of PrEP	3,035	1,458 (32.4)	20,333.4
Note: PrEP program is targeted at high risk MSM aged 15–44 years. Time horizon: 20 years. PrEP was scaled-up in 2021, achieving targeted coverage in 2022 and thereafter
^aAverted HIV cases indicates those prevented HIV diagnosed regards to interventions;
^bQALY gained: averted quality-adjusted life-year loss;

Cost saving by a high-coverage coverage PrEP program: sensitivity analysis

Figure 5 shows the impact of nine key parameters on the benefit-cost ratio estimate of a PrEP program. These parameters include the cost of PrEP (generic vs. brand name drugs), timing of PrEP rollout (2019 vs. 2023), mode of PrEP use (on-demand vs. daily use), time horizon (10 years vs. 30 years), cost of ART (cheapest first-line ART vs. the most expensive second-line ART), coverage rate of PrEP (25% vs. 75%), adherence to PrEP (75% vs. 100%), resistance to PrEP drugs (0% vs. 10%), and condom use (0% vs. 30%). The use of a generic drug (with one-third of the unit drug cost) and shifting from an on-demand mode of PrEP use (the base scenario) to daily use (associated with a 2-fold increase in drug use/cost) have the largest impact on the benefit-cost ratio estimate. Nevertheless, a high-coverage PrEP program remains cost-saving under the daily use scenario, with a benefit-cost ratio of 3.80. Other parameters have an even smaller impact on the benefit-cost ratio of a PrEP program.

To the best of our knowledge, this is the first study to establish the necessity of high-coverage PrEP for the elimination of HIV, while also demonstrating its high cost-effectiveness from an elimination perspective. Our modeling results show that an HIV test-and-treat strategy alone would be insufficient for the elimination of HIV. In contrast, a PrEP program achieving 50% coverage among young, high-risk MSM will decrease the basic reproductive number (R0) of HIV to below 1, thereby facilitating the path toward HIV elimination. Importantly, our analyses indicate that factors such as risk compensation (leading to a 0% condom use rate among PrEP users), imperfect adherence at a rate of 75%, and sporadic drug resistance at a rate of 1% do not significantly undermine the effectiveness of such a PrEP program. Deterministic modeling suggests that the implementation of this program among high-risk MSM aged 15 to 44 years, will drive the trajectory of the HIV epidemic in Taiwan below the WHO's HIV elimination threshold (1 per 1,000 person-years) by the year 2030. The cumulative cost of implementing such a PrEP program over a 20-year period would amount to 227.2 million USD; however, it would yield savings of 774.1 million USD in HIV-related medical expenses and an additional 851.9 million USD by averting losses in human capital. Consequently, the benefit-cost ratio stands at 7.16. Importantly, the cost-saving potential of this PrEP intervention remains robust when subjected to variations in key parameters.

The most salient finding of our study underscores the necessity of PrEP, highlighting that a high-coverage PrEP program is instrumental for the elimination of HIV in Taiwan by 2030. Our preliminary deterministic modeling results were first presented at the 21st International AIDS Conference in 2016, where we demonstrated that achieving a 50% coverage rate could eradicate the HIV epidemic among MSM in Taiwan ^{26, 27}. Subsequent studies, such as that by Rozhnova et al. (2018), indicated that an 82% PrEP coverage rate, in the context of existing ART coverage, could theoretically eliminate HIV among MSM in the Netherlands ²⁴. More recently, Jijón et al. (2021) showed that a minimum PrEP coverage of 55%, which has yet to be achieved, could eliminate the HIV epidemic among high-risk MSM in the Paris region ²⁵. In the current study, we employed stochastic modeling to demonstrate that, without a high-coverage PrEP program, the elimination of HIV in Taiwan remains unattainable. Given that successful HIV elimination hinges on attaining a high PrEP coverage among young, high-risk MSM—a demographic group particularly vulnerable due to financial constraints in accessing Truvada™ with a monthly cost ranging from 5,000 (on demand use) to 10,000 NTD (daily use), or 167 to 333 USD, in Taiwan—policy interventions such as comprehensive public funding or health insurance reimbursements are imperative to broaden access to ensure the successful elimination of HIV in Taiwan by 2030.

We found that an intensive HIV Test-and-Treat, comprising annual HIV testing followed by immediate initiation of ART upon diagnosis, is insufficient on its own for eradicating the HIV epidemic among young, high-risk MSM, as evidenced by both our stochastic and deterministic modeling outcomes (refer to Table 1 and Fig. 4, respectively). These results underscore the essential role of PrEP in achieving HIV elimination within this population. The limitation of the HIV Test-and-Treat strategy is elucidated in Table 1, which indicates its minimal impact on curtailing HIV transmissions during the acute infection stage—a short window lasting between one and three months that is unlikely to be captured by an annual testing regimen. Importantly, this stage is characterized by heightened infectiousness compared to the chronic stage of the infection. Transmissions occurring in the acute stage account for approximately one-third of all HIV transmissions and can only be effectively mitigated through the implementation of a high-coverage PrEP program. Granich et al. (the WHO modelling group), initially posited in 2009 that a universal HIV Test-and-Treat strategy would effectively eliminate the generalized, heterosexual HIV epidemic in South Africa within a decade of implementation ²⁸. However, subsequent research by Powers et al. in 2011 challenged these findings, particularly critiquing the assumed relative infectiousness during the acute stage—30.3-fold as opposed to the 3.2-fold cited by Granich et al. ^{29, 30}. In the present study, we employed a relative infectiousness rate during the acute phase of 26-fold, in alignment with research by Hollingworth et al. ³¹. Our data corroborate the limitations of an HIV Test-and-Treat approach for the eradication of HIV among MSM, echoing the conclusions drawn by Powers et al. (2011) and Akullian et al. (2020) regarding the strategy's inadequacy for eliminating HIV among heterosexual populations in Africa ^{29, 32}. Additionally, the objective of achieving annual HIV testing for young, high-risk MSM in Taiwan presents a formidable challenge due to factors such as stigma, discrimination, and legal complexities surrounding an HIV diagnosis.

In comparison to an intensive HIV Test-and-Treat strategy, high-coverage PrEP demonstrates greater resilience to disruptions caused by pandemics. This advantage arises from the potential for over-the-counter distribution of PrEP ^{33, 34}, whereas the former approach necessitates an operational medical care system. However, our modeling data highlight that suboptimal adherence could negate the benefits of high PrEP coverage, as demonstrated by the isoline of the basic reproduction number R0 under different adherence and coverage rates (see Fig. 1). Consequently, while pharmacist-led distribution or over-the-counter availability may expedite reaching the target coverage rate among young, high-risk MSM ³³ and may be particularly useful during pandemic disruptions ³⁴, educational interventions aimed at the client population are crucial for ensuring optimal adherence.

One of the major concerns for PrEP is risk compensation. While randomized controlled trials did not support that PrEP is associated with a decrease in condom use ^{1, 2, 35}, most observational studies suggested that PrEP users are more likely to have new sexually transmitted infections than non-users ^{8, 36} although this could be a result of the higher baseline risk behaviors in PrEP users. Even if risk compensation is 100% (all users stop using condoms), our modelling results still showed that such a decrease in condom use among those who use PrEP (which acts like a molecular condom) would, in fact, have a negligible effect on HIV epidemic control (Table 2A for stochastic modelling, and Table 4 for deterministic modelling). Jijón et al. (2021) also reported similar results, indicating that risk compensation with none of the PrEP users using condom only minimally increase the PrEP coverage rate required for elimination ²⁵. Likewise, our study further revealed that the other two often-raised concerns for PrEP, imperfect (75%) adherence and occasional (1%) drug resistance, do not have a meaningful impact on the effect of a high-coverage PrEP program in eliminating the HIV epidemic among MSM.

Cost and cost-effectiveness are critical considerations in policymaking. Previous studies on the cost-effectiveness of PrEP generally show that, under a persistent HIV epidemic, PrEP is cost-effective but not cost-saving unless over a very long (80 years) time horizon or with massive price reduction ^{12, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46}. In contrast, we found that PrEP using brand name Truvada™ is highly cost-saving over a 20-year time horizon when implemented to eliminate the HIV epidemic by averting a substantial amount of HIV-associated lifetime medical costs and HIV-associated losses in human capital. Although the cost required to provide high-coverage PrEP could be a constraint for implementation, our results actually show that, using the brand name Truvada™, funding for 50% of young high-risk MSM in Taiwan requires a total of 227.2 million USD over a 20-year period from 2021 to 2040, or an annual budget of approximately 11.4 million USD. This amount is only a quarter of the current annual budget (approximately 50 million USD for 6 million doses) for publicly funded annual seasonal influenza vaccination in Taiwan. Similar to previous studies ^{38, 39}, a massive reduction in the cost of PrEP drugs after the expiration of patents will make the case for high-coverage PrEP even more compelling.

On the contrary, if comprehensive publicly funded or health insurance-reimbursed PrEP is not provided for young high-risk MSM, there will be danger ahead. First, the unmet need will force potential users to purchase cheap illegal generic drugs, often of questionable quality, overseas (although some studies support the equivalence in bioavailability between generic and brand name drugs ⁴⁷). Second, without a public program that requires regular HIV testing at entry and at three-month intervals thereafter, illegal generic drug users are at high risk of unknowingly taking PrEP in the presence of HIV infection. Third, in the absence of case management services or professional counseling by physicians or pharmacists, there will be no way to ensure good adherence among users. The end result could be a disastrous emergence of resistance to PrEP drugs. Furthermore, because emtricitabine/tenofovir are also important components of ART, an emergence of drug resistance to emtricitabine/tenofovir could compromise not only the efficacy of PrEP but also the efficacy of ART.

The strength of the present study is the precise model parameterization based on high-quality Taiwan national data, including HIV surveillance, HIV cascade, and mortality data (provided by Taiwan CDC), vital statistics (from Ministry of Interior), and HIV-associated medical cost (based on Taiwan National Health Insurance database). Additional advantages include the use of risk/age-structured model, the use of both stochastic and deterministic modelling to yield robust conclusion, and the use of the best available estimates for key parameters, including the relative infectiousness in acute stage as well as the rate of HIV disease progression.

Our study is subject to several notable limitations. First, our modeling analysis does not account for the disruptive impact of the COVID-19 pandemic that emerged in 2019. Due to the absence of reliable HIV surveillance data spanning the years 2020–2022, our Taiwan MSM HIV Model was calibrated using data collected from 1990 through 2019. Consequently, projections in our counterfactual scenario relied on the epidemiological landscape of 2019, and the high-coverage PrEP program was assumed to be initiated in 2021, although a sensitivity analysis on scenario to initiate the high-coverage PrEP program in 2023 does not significantly alter the outcome. Second, while our study emphasized cost as a primary barrier to the PrEP adoption in Taiwan, we did not scrutinize other non-financial determinants that could significantly influence PrEP acceptability among Taiwan's MSM population. Factors such as distrust of health authorities and stigmatization associated with PrEP usage may pose substantial obstacles to program implementation. Third, our argument for PrEP funding was framed strictly within an economic context, drawing conclusions from cost-effectiveness analyses. However, the societal dimensions cannot be ignored; public support is pivotal, and the viability of PrEP programs could be compromised in a socio-political climate marked by citizens harboring negative perceptions of MSM

In conclusion, a high-coverage PrEP program, aiming to provide a 50% coverage rate for young, high-risk MSM is necessary, effective, and highly cost-saving to eliminate HIV in Taiwan by 2030. Our findings strongly support the broad administration of PrEP to high-risk HIV-negative MSM to achieve HIV elimination.

Study design and data source

The threshold of HIV elimination, is set as an R0 of HIV less than 1, or an annual HIV incidence of less than 1/1000 person-years.²⁸ We reviewed the published literature for parameterization, including the natural course of disease progression and transmission of HIV, as well as the effects of ART ^{48, 49} and PrEP ^{1, 2} on HIV transmission and HIV-associated mortality. We obtained Taiwan national HIV surveillance, HIV cascade, and HIV survival data from the Taiwan CDC, vital statistic data from the Taiwan Ministry of Interior ⁵⁰, and data on the costs of ART, PrEP, antimicrobial therapy for HIV-associated opportunistic infections, outpatient care, inpatient care, physician fee, case management, and other medical expenditure in Taiwan, from the Taiwan National Health Insurance database. The study procedure was approved by the Research Ethic Committee of National Taiwan University Hospital (NTUH) (REC# 201703099RINA).

Stochastic modeling

Our stochastic modelling framework has been described elsewhere ⁵¹. In brief, we simulated the life course of a young, HIV-positive MSM with high-risk sexual behaviour, from the ages of 20 to 45. On each day, the index patient may engage in sexual activity with other MSM, receive HIV testing, or die. We further consider 35 different subsequent scenarios, including whether HIV transmission occurs, whether a condom is used, whether linkage to care and the start of ART occurs, and whether a partner uses PrEP ⁵¹. We set the relative infectiousness in the acute stage of HIV infection compared to the chronic stage, a key parameter in HIV models, at 26, based on the work of Hollingworth et al.³¹ (Supplementary Fig. 1). We estimated R0 as the average number of HIV transmissions that would occur over 1,000 simulations. The mean number of sexual partners for a young, high-risk MSM was estimated to be 50, based on calibration results from our deterministic model using Taiwan HIV surveillance data. See Supplementary Table 1 for model parameterization. We used R for computing the results (see Supplementary Note 1 for R code).

Deterministic modeling

Our deterministic modelling framework has been described elsewhere ^{26, 27, 52}. In brief, the Taiwan MSM HIV Model considers the natural history of HIV disease progression ^{53, 54, 55} (from the acute stage to chronic stages with CD4 count > 500, 350–500, 200–350, < 200, then the AIDS stage), the HIV cascade ⁵⁶ (from HIV testing, to being linked to care, then on ART), risk structure (high-risk vs. low-risk, with assortative mixing ^{57, 58, 59}), age structure (15–44 years vs. 45–64 years vs. >65 years, also with assortative mixing ⁶⁰), and the demographic transition of Taiwanese population (birth rate statistics from 1990 to 2019 ⁵⁰) (Fig. 2). The parameters for HIV disease progression are based on the work of Longini et al. ⁵⁴ on 1,796 patients in US Army and the work of Veugelers et al. ⁵⁵ on the effect of age on rate of HIV disease progression. See Supplementary Table 2 for details in the parameterization of all variables in the models. HIV-associated mortality by period, age, and stage is based on our comprehensive literature review and modeling work ⁶¹ (Supplementary Table 3). The numbers of MSM who started to use PrEP in Taiwan during the 2018–2019 PrEP demonstration project were based on data from administrators ^{21, 62} and the Taiwan AIDS Society ⁶³. We calibrated the model to fit Taiwan’s national HIV surveillance data (1990–2019), HIV cascade data, and the mortality statistics of HIV patients. We estimated the HIV transmission coefficients across different periods among young high-risk MSM and their effective population size using the least square method (with an estimate of approximately 17% among all MSM aged 15–44 years). We used STELLAR software version 10.0.6 (ISEE Systems Inc. New Hampshire, USA) to compute the results (see Supplementary Note 2 for differential equations).

Economic analyses

Our framework for economic analyses has been previously described ^{26, 27, 52}. In brief, we compare HIV epidemic scenarios with or without a high-coverage PrEP program, projected into future using the deterministic model. We adopt a societal perspective over a 20-year time horizon. All future costs, including those-related to PrEP and HIV-associated medical cost, are adjusted by a 3% annual discount rate to present-day value. Supplementary Fig. 2 illustrates the cost structure for a publicly funded PrEP program ^{1, 2, 16, 64}, while Supplementary Fig. 3 outlines the cost structure for HIV-associated medical cost, stratified by whether AIDS is present at diagnosis. Both of the above were based on Taiwan National Health Insurance data from 2018 data (Supplementary Table 4 and Supplementary Table 5). We estimated lifetime HIV-associated medical cost by integrating projected lifetime survival curves with the mean HIV-associated medical cost per patient in 2018. The projected lifetime survival curves (mean survival time: 41.3 year after HIV diagnosis without AIDS, and 29.7 years after HIV diagnosis with AIDS, Supplemental Fig. 2) ^{65, 66}, used for estimating HIV-associated lifetime medical cost under Taiwan National Health Insurance, and the losses in quality-adjusted life expectancy (QALE) for each Taiwanese MSM with a new HIV diagnosis (5.44 QALY for each new HIV diagnosis without AIDS, and 13.95 QALY for each new HIV diagnosis with AIDS, Supplemental Fig. 3), are based on the work of Lo et al ⁶⁶. Quality of life among HIV-infected patients is empirically measured from HIV-positive patients using EuroQol-5D questionnaire (EQ-5D) ^{66, 67}, and integrated with projected lifetime survival for estimating QALE and QALE loss relative to general population ⁶⁸. We calculate the societal human capital saved by averting new HIV diagnoses by multiplying the total number of QALY gained, under the intervention scenario, with Taiwan’s Year 2018 per capita gross domestic product (GDP) at 754,711 NTD (25,157 USD at 30 NTD for 1 USD) ⁶⁹, in line with the WHO’s recommended threshold for cost-effectiveness of interventions ⁷⁰. For cost-saving interventions, we further calculate the benefit-cost ratio by dividing the sum of the saved HIV-associated medical cost and averted human capital loss, by the cost of the intervention.

Author Contributions

H.J.W. and C.T.F. conceived and designed the study. H.J.W., Y.P.C., and C.T.F. conducted epidemic modelling analyses. C.C.C. and C.T.F. constructed the Taiwan MSM HIV model. Y.H.C. and C.T.F. reviewed the literature for parameterization and estimated HIV-associated mortality parameters in the model. H.J.W. and C.T.F. conducted cost-effectiveness analysis. T.L. and C.T.F. conducted lifetime survival extrapolation of MSM living with HIV. T.L. analysed National Health Insurance data on cost of ART and medical care in Taiwan. H.J.W. and C.T.F. wrote the manuscript. All authors critically reviewed the draft and approved the final version of the manuscript. H.J.W., Y.H.C., and Y.P.C. contributed equally to this work.

Competing interests: All authors declare that they have no conflicts of interest.

Additional information

Supplementary information accompanies this paper at http://www.nature.com/srep.

Molina JM, et al. On-demand preexposure prophylaxis in men at high risk for HIV-1 infection. N Engl J Med 373, 2237–2246 (2015).
McCormack S, et al. Pre-exposure prophylaxis to prevent the acquisition of HIV-1 infection (PROUD): effectiveness results from the pilot phase of a pragmatic open-label randomised trial. Lancet 387, 53–60 (2016).
Molina JM, et al. Efficacy, safety, and effect on sexual behaviour of on-demand pre-exposure prophylaxis for HIV in men who have sex with men: an observational cohort study. Lancet HIV 4, e402-e410 (2017).
Killelea A, et al. Financing and Delivering Pre-Exposure Prophylaxis (PrEP) to End the HIV Epidemic. J Law Med Ethics 50, 8–23 (2022).
Marcus JL, Killelea A, Krakower DS. Perverse Incentives - HIV Prevention and the 340B Drug Pricing Program. N Engl J Med 386, 2064–2066 (2022).
Johnson J, Killelea A, Farrow K. Investing in National HIV PrEP Preparedness. N Engl J Med 388, 769–771 (2023).
Quaife M, et al. Risk compensation and STI incidence in PrEP programmes. Lancet HIV 7, e222-e223 (2020).
Hoornenborg E, et al. Sexual behaviour and incidence of HIV and sexually transmitted infections among men who have sex with men using daily and event-driven pre-exposure prophylaxis in AMPrEP: 2 year results from a demonstration study. Lancet HIV 6, e447-e455 (2019).
Zhang J, et al. Discontinuation, suboptimal adherence, and reinitiation of oral HIV pre-exposure prophylaxis: a global systematic review and meta-analysis. Lancet HIV 9, e254-e268 (2022).
Laurent C, et al. Human Immunodeficiency Virus Seroconversion Among Men Who Have Sex With Men Who Use Event-Driven or Daily Oral Pre-Exposure Prophylaxis (CohMSM-PrEP): A Multi-Country Demonstration Study From West Africa. Clin Infect Dis 77, 606–614 (2023).
Hurt CB, Eron JJ, Jr., Cohen MS. Pre-exposure prophylaxis and antiretroviral resistance: HIV prevention at a cost? Clin Infect Dis 53, 1265–1270 (2011).
Shen M, Xiao Y, Rong L, Meyers LA, Bellan SE. The cost-effectiveness of oral HIV pre-exposure prophylaxis and early antiretroviral therapy in the presence of drug resistance among men who have sex with men in San Francisco. BMC medicine 16, 58 (2018).
Nosyk B, et al. Ending the HIV epidemic in the USA: an economic modelling study in six cities. Lancet HIV 7, e491-e503 (2020).
Grulich AE, Bavinton BR. Scaling up preexposure prophylaxis to maximize HIV prevention impact. Current opinion in HIV and AIDS 17, 173–178 (2022).
Taiwan Centers for Disease Control (CDC). Statistics of HIV/AIDS. available at: https://www.cdc.gov.tw/En/Category/MPage/kt6yIoEGURtMQubQ3nQ7pA. (2023).
World Health Organization. Guideline on when to start antiretroviral therapy and on pre-exposure prophylaxis for HIV. WHO (2015).
UNAIDS. 90-90-90: An ambitious treatment target to help end the AIDS epidemic (available at: http://www.unaids.org/sites/default/files/media_asset/90-90-90_en.pdf) (2014).
Chen CH. Current HIV situation and control policy in Taiwan. In: Taiwan Public Health Association 2014 Annual Meeting, October 26, 2014, Taipei. (2014).
Tsai YC. on behalf of Taiwan Centers for Disease Control. HIV epidemiology in Taiwan. In: Taiwan Public Health Association 2019 Annual Meeting, September 27, 2019, Taipei. (2019).
Taiwan Centers for Disease Control (CDC). Taiwan archived the UNAIDS 90-90-90 targets https://www.mohwpaper.tw/adv3/maz31/utx02.asp (access August 24, 2023). (2021).
Wu HJ. Experience of 2016–2017 PrEP pilot project in Taiwan (personal communication.) (2019).
Lee YC, et al. Awareness and willingness towards pre-exposure prophylaxis against HIV infection among individuals seeking voluntary counselling and testing for HIV in Taiwan: a cross-sectional questionnaire survey. BMJ open 7, e015142 (2017).
Grulich AE, et al. Population-level effectiveness of rapid, targeted, high-coverage roll-out of HIV pre-exposure prophylaxis in men who have sex with men: the EPIC-NSW prospective cohort study. Lancet HIV, (2018).
Rozhnova G, et al. Elimination prospects of the Dutch HIV epidemic among men who have sex with men in the era of preexposure prophylaxis. AIDS 32, 2615–2623 (2018).
Jijón S, Molina JM, Costagliola D, Supervie V, Breban R. Can HIV epidemics among MSM be eliminated through participation in preexposure prophylaxis rollouts? AIDS 35, 2347–2354 (2021).
Wu HJ, Chang CC, Fang CT. Scaling-up pre-exposure prophylaxis (PrEP) as a strategy to eliminate HIV transmission among men who have sex with men (MSM): a modeling study [Poster]. In: The 21th International AIDS Conference (AIDS 2016). 2016/7/18–22, Durban, South Africa (corresponding author: Chi-Tai Fang.) (2016).
Fang CT. Scaling-up pre-exposure prophylaxis (PrEP) as a strategy to eliminate HIV transmission among men who have sex with men (MSM): a modeling study [Invited lecture]. In: The 21th Interna-tional AIDS Conference (AIDS 2016). 2016/7/16–22, Durban, South Africa.) (2016).
Granich RM, Gilks CF, Dye C, De Cock KM, Williams BG. Universal voluntary HIV testing with immediate antiretroviral therapy as a strategy for elimination of HIV transmission: a mathematical model. Lancet 373, 48–57 (2009).
Powers KA, et al. The role of acute and early HIV infection in the spread of HIV and implications for transmission prevention strategies in Lilongwe, Malawi: a modelling study. Lancet 378, 256–268 (2011).
Williams BG, Granich R, Dye C. Role of acute infection in HIV transmission. Lancet 378, 1913; author reply 1914–1915 (2011).
Hollingsworth TD, Anderson RM, Fraser C. HIV-1 transmission, by stage of infection. The Journal of infectious diseases 198, 687–693 (2008).
Akullian A, et al. The effect of 90-90-90 on HIV-1 incidence and mortality in eSwatini: a mathematical modelling study. Lancet HIV 7, e348-e358 (2020).
Kazi DS, Katz IT, Jha AK. PrEParing to End the HIV Epidemic - California's Route as a Road Map for the United States. N Engl J Med 381, 2489–2491 (2019).
Krakower D, Marcus JL. Free the PrEP - Over-the-Counter Access to HIV Preexposure Prophylaxis. N Engl J Med 389, 481–483 (2023).
Grant RM, et al. Preexposure chemoprophylaxis for HIV prevention in men who have sex with men. N Engl J Med 363, 2587–2599 (2010).
Traeger MW, et al. Association of HIV Preexposure Prophylaxis With Incidence of Sexually Transmitted Infections Among Individuals at High Risk of HIV Infection. JAMA 321, 1380–1390 (2019).
Drabo EF, Hay JW, Vardavas R, Wagner ZR, Sood N. A Cost-effectiveness Analysis of Preexposure Prophylaxis for the Prevention of HIV Among Los Angeles County Men Who Have Sex With Men. Clin Infect Dis 63, 1495–1504 (2016).
Nichols BE, Boucher CAB, van der Valk M, Rijnders BJA, van de Vijver D. Cost-effectiveness analysis of pre-exposure prophylaxis for HIV-1 prevention in the Netherlands: a mathematical modelling study. The Lancet infectious diseases 16, 1423–1429 (2016).
Cambiano V, et al. Cost-effectiveness of pre-exposure prophylaxis for HIV prevention in men who have sex with men in the UK: a modelling study and health economic evaluation. The Lancet infectious diseases 18, 85–94 (2018).
Suraratdecha C, et al. Cost and cost-effectiveness analysis of pre-exposure prophylaxis among men who have sex with men in two hospitals in Thailand. Journal of the International AIDS Society 21 Suppl 5, e25129 (2018).
van de Vijver D, et al. Cost-effectiveness and budget effect of pre-exposure prophylaxis for HIV-1 prevention in Germany from 2018 to 2058. Euro surveillance: bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin 24, (2019).
Choi H, et al. Cost-effectiveness analysis of pre-exposure prophylaxis for the prevention of HIV in men who have sex with men in South Korea: a mathematical modelling study. Sci Rep 10, 14609 (2020).
Kazemian P, et al. The Cost-effectiveness of Human Immunodeficiency Virus (HIV) Preexposure Prophylaxis and HIV Testing Strategies in High-risk Groups in India. Clin Infect Dis 70, 633–642 (2020).
Wong NS, et al. Pre-exposure prophylaxis (PrEP) for MSM in low HIV incidence places: should high risk individuals be targeted? Sci Rep 8, 11641 (2018).
Schneider K, Gray RT, Wilson DP. A cost-effectiveness analysis of HIV preexposure prophylaxis for men who have sex with men in Australia. Clin Infect Dis 58, 1027–1034 (2014).
Juusola JL, Brandeau ML, Owens DK, Bendavid E. The cost-effectiveness of preexposure prophylaxis for HIV prevention in the United States in men who have sex with men. Annals of internal medicine 156, 541–550 (2012).
Wang X, et al. InterPrEP: internet-based pre-exposure prophylaxis with generic tenofovir disoproxil fumarate/emtrictabine in London - analysis of pharmacokinetics, safety and outcomes. HIV medicine 19, 1–6 (2018).
Cohen MS, et al. Prevention of HIV-1 infection with early antiretroviral therapy. N Engl J Med 365, 493–505 (2011).
The Insight START Study Group. Initiation of antiretroviral therapy in early asymptomatic HIV infection. N Engl J Med 373, 795–807 (2015).
Vital statistics from Minister of Interior. R.O.C (Taiwan) http://www.ris.gov.tw.) (2019).
Cheng YP. Impact of pre-exposure prophylaxis on basic reproductive number of HIV among men who have sex with men in Taiwan: a stochastic modeling study [Master Thesis] (Advisor: Chi-Tai Fang, funded by MOST-106-2314-B-002-115-MY3 to Chi-Tai Fang.). National Taiwan University (2018).
Wu HJ. HIV pre-exposure prophylaxis for men who have sex with men in Taiwan: a mathematical modeling study [Master Thesis] (Advisor: Chi-Tai Fang.). National Taiwan University (2016).
Centers for Disease Control and Prevention. 1993 revised classification system for HIV infection and expanded surveillance case definition for AIDS among adolescents and adults. MMWR Recomm Rep 41, 1–19 (1992).
Longini IM, Jr., Clark WS, Gardner LI, Brundage JF. The dynamics of CD4 + T-lymphocyte decline in HIV-infected individuals: a Markov modeling approach. Journal of acquired immune deficiency syndromes 4, 1141–1147 (1991).
Veugelers PJ, et al. Determinants of HIV disease progression among homosexual men registered in the Tricontinental Seroconverter Study. American journal of epidemiology 140, 747–758 (1994).
Gardner EM, McLees MP, Steiner JF, Del Rio C, Burman WJ. The spectrum of engagement in HIV care and its relevance to test-and-treat strategies for prevention of HIV infection. Clin Infect Dis 52, 793–800 (2011).
Koblin BA, et al. Risk factors for HIV infection among men who have sex with men. AIDS 20, 731–739 (2006).
Liu WC. Comparisons of three methods to estimate incidence rates of HIV infection among persons seeking voluntary, anonymous counseling and testing services (VCT) [Master Thesis] (Advisor: Chi-Tai Fang.). National Taiwan University (2011).
Ackers ML, et al. High and persistent HIV seroincidence in men who have sex with men across 47 U.S. cities. PLoS One 7, e34972 (2012).
Shen HC. Attitude and preparedness for aging among middle age homosexual men in Taiwan [in Chinese][Master Thesis], Institute of Sociology.). National Chengchi University (2004).
Chen YH, Wu HJ, Fang CT. Mortality of HIV infection, by age, period, disease stage, care cascade and antiretroviral therapy status [Poster]. In: 10th IAS Conference on HIV Science (IAS 2019). 2019/7/21–24, Mexico City, Mexico (Corresponding author; Chi-Tai Fang.) (2019).
Wu HJ. Experience of 2018–2019 PrEP demonstration project in Taiwan (personal communication.) (2019).
Hung CC. Experience of 2018–2019 PrEP demonstration project in Taiwan (personal communication.) (2019).
Taiwan AIDS society. Guideline for the use of pre-exposure oral prophylaxis (PrEP) in Taiwan. http://www.aids-care.org.tw/DB/News/file/254-1.pdf. (2016).
Fang CT, et al. Life expectancy of patients with newly-diagnosed HIV infection in the era of highly active antiretroviral therapy. QJM 100, 97–105 (2007).
Lo T. Impact of early HIV diagnosis on quality-adjusted life expectancy in HIV-infected men who having sex with men (MSM) [Master Thesis] (Advisor: Chi-Tai Fang.). National Taiwan University (2015).
EuroQoL Group. What is EQ-5D. Available from: http://www.euroqol.org/. (accessed on 2014 Aug 15).) (2014).
Hwang JS, Hu TH, Lee LJ, Wang JD. Estimating lifetime medical costs from censored claims data. Health economics 26, e332-e344 (2017).
Director-General of Budget and Accounting and Statistics. (2018). Per Capita Gross Domestic Product. http://statdb.dgbas.gov.tw/pxweb/Dialog/Saveshow.asp.) (2018).
Marseille E, Larson B, Kazi DS, Kahn JG, Rosen S. Thresholds for the cost-effectiveness of interventions: alternative approaches. Bulletin of the World Health Organization 93, 118–124 (2015).

There is NO Competing Interest.

Download PDF

Version 1

posted

You are reading this latest preprint version

Preexposure Prophylaxis to Eliminate HIV in Taiwan by 2030: A Modeling Study

Status:

Version 1

Abstract

Figures

Introduction

Results

Necessity of a high coverage PrEP program for HIV elimination

Effect of risk compensation on the impact of a PrEP program

Effect of drug resistance on the impact of a PrEP program

Effect of non-adherence on the impact of a PrEP program

Under the status quo, HIV will become endemic in Taiwan after 2030

High coverage PrEP will eliminate HIV by 2030

Intensive HIV Test-and-Treat alone will not be sufficient to eliminate HIV

Synergism between PrEP and HIV Test-and-Treat

HIV elimination by PrEP: sensitivity analysis by deterministic modeling

Cost and cost-effectiveness of a 50% coverage PrEP program

Cost saving by a high-coverage coverage PrEP program: sensitivity analysis

Discussion

Methods

Study design and data source

Stochastic modeling

Deterministic modeling

Economic analyses

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1