An evaluation method and application of the intervention measures for high-risk populations of HIV transmission

Abstract

The present invention belongs to the technical field of AIDS prevention and control, and specifically relates to a method for evaluating the effectiveness of intervention measures for high-risk populations of HIV transmission and its application. The effectiveness evaluation method includes the following steps: S1 constructing a prediction model for the risk of new infections; S2 based on the prediction model for the risk of new infections, constructing an effectiveness evaluation model for intervention measures for high-risk populations of HIV transmission, and the effectiveness evaluation model for intervention measures for high-risk populations of HIV transmission includes an effectiveness evaluation model for TasP intervention measures. The effectiveness of the TasP intervention measures is characterized by the proportion of the decrease in new infections after the TasP intervention measures are strengthened. The present invention constructs a prediction model for the risk of new infections to evaluate the impact of intervention measures for high-risk populations of HIV transmission in the real world on reducing new HIV infections in the MSM population. The evaluation results of the present invention provide theoretical guidance for optimizing intervention measures, formulating appropriate intervention strategies, and reasonably allocating health resources.

Description

Technical Field

[0001] The present invention belongs to the technical field of AIDS prevention and control, and particularly relates to a method for evaluating the effectiveness of intervention measures for high-risk populations of HIV transmission and its application. Background Art

[0002] AIDS is caused by the infection of the Human Immunodeficiency Virus (HIV). The population is generally susceptible and there is no vaccine for prevention. Once infected, the virus will be carried for life, with strong infectivity and high fatality rate. Conducting behavioral and biological interventions for high-risk populations of HIV transmission is the main strategy to contain the spread of AIDS at present. The main intervention measures include: the intervention measure of promoting the use of condoms, the Pre-Exposure Prophylaxis (PrEP) intervention measure, the testing and counseling intervention measure, and the Treat as Prevention (TasP) intervention measure.

[0003] Men who have Sex with Men (MSM) are high-risk populations for HIV infection due to characteristics such as having multiple sexual partners, casual sexual partners, and a high frequency of unprotected sexual behavior. This population also transmits HIV to the general population, causing heterosexual transmission and mother-to-child transmission. Factors such as the strong mobility and concealment of the MSM population and self-discrimination increase the difficulty of implementing prevention and control measures. At present, there is a lack of scientific guidance on aspects such as the coverage, intensity, and frequency of the implementation of intervention measures, and there is also a lack of scientific evaluation tools for the work of intervention measures, resulting in the fact that behavioral and biological measures such as the promotion of condom use, pre-exposure prophylaxis, testing and counseling, and antiviral treatment have not achieved effective prevention and control results after being implemented for many years, and the situation of AIDS prevention and control is still relatively severe.

[0004] How to scientifically evaluate the effectiveness of intervention measures for high-risk populations of HIV transmission, so as to reasonably allocate and effectively utilize medical resources under limited medical resources and guide the precise and high-quality development of HIV intervention work has become a technical problem to be solved urgently. Summary of the Invention

[0005] To address the drawbacks of the above-mentioned existing technologies, the present invention introduces a new infection risk prediction model, and based on this new infection risk prediction model, a risk prediction model for new HIV infections is established under biobehavioral intervention measures such as antiviral treatment, testing and counseling, condom use promotion, and pre-exposure prophylaxis. The system comprehensively evaluates the effects of multiple intervention measures in the real world on reducing new HIV infections among MSM populations, and predicts the impact of different implementation intensities of various measures on reducing new HIV infections. The main purpose is to explore appropriate intervention measures that need to be taken for MSM populations with different transmission risks under limited medical resources, further guide the precise and high-quality implementation of intervention work, and conduct scientific evaluations of the work effects in a timely manner. The present invention has important guiding significance for formulating comprehensive prevention and control strategies for AIDS suitable for China, and can also provide new ideas for the prevention and control of other infectious diseases.

[0006] The specific technical solution of the present invention is as follows:

[0007] A method for evaluating the effects of intervention measures for high-risk populations of HIV transmission, comprising the following steps:

[0008] S1. Construct a new infection risk prediction model:

[0009] As Figure 1 shown, the basic principles and hypothesis premises for constructing the new infection risk prediction model are as follows:

[0010] ① New HIV infections are caused by the transmission of infectious HIV / AIDS (source of infection). According to whether the virus is suppressed, infectious HIV / AIDS can be divided into two parts. The first part is HIV / AIDS that has not been detected and diagnosed, diagnosed but not treated, and treated but not achieved virus suppression. The second part is HIV / AIDS that has achieved virus suppression but is still infectious.

[0011] ② The total survival number of HIV / AIDS transmitted through same-sex contact is N, which is divided into a high-risk group and a low-risk group according to the occurrence of high-risk behaviors. Among them, the proportion of the high-risk group is ρ, and the detection and diagnosis proportion is d1 (the first 95% target); the proportion of the low-risk group is 1 - ρ, and the detection and diagnosis proportion is d2 (the first 95% target); the proportion of HIV / AIDS detected and diagnosed who receive antiviral treatment is τ (the second 95% target), and the proportion of those who achieve virus suppression is σ (the third 95% target).

[0012] Among them, the specific classification methods for the high-risk group and the low-risk group are as follows:

[0013] According to the MSM risk assessment scale, calculate the score. If the risk assessment score ≥ 10, it belongs to the high-risk group; if < 10, it belongs to the low-risk group.

[0014] Table 1 MSM risk assessment scale

[0015]

[0016] ③The average transmission risk coefficient of infectious HIV / AIDS in the low-risk group is β per person-year; if the antiviral treatment can reduce the transmission risk of HIV / AIDS by a proportion of φ, then the transmission risk coefficient of HIV / AIDS with viral suppression in the low-risk group under the effect of antiviral treatment is (1 - φ)β per person-year; the HIV / AIDS transmission risk in the high-risk group is Γ times that of the low-risk group, so its transmission risk coefficient is Γβ per person-year, and the transmission risk coefficient under the effect of antiviral treatment is (1 - φ)Γβ per person-year.

[0017] Based on this, an estimated equation for new infection risk was constructed:

[0018] (X)

[0019] Simplifying equation (X), a prediction model for new infection risk was obtained:

[0020] (Ⅰ)

[0021] In equation (Ⅰ), n is the number of new infections per year, cases; N is the total number of surviving HIV / AIDS transmitted through same-sex, cases; β is the average transmission risk coefficient of infectious HIV / AIDS in the low-risk group, persons / year; ρ is the proportion of the high-risk group in N, dimensionless; d1 is the detection and diagnosis proportion in the high-risk group, dimensionless; τ is the proportion of those receiving antiviral treatment for the detection and diagnosis of HIV / AIDS, dimensionless; σ is the proportion of those with viral suppression, dimensionless; φ is the proportion by which antiviral treatment can reduce the transmission risk of HIV / AIDS, dimensionless; Γ is the multiple by which the HIV / AIDS transmission risk in the high-risk group is of the low-risk group; d2 is the detection and diagnosis proportion in the low-risk group, dimensionless.

[0022] S2. Based on the prediction model for new infection risk, an evaluation model for the effectiveness of intervention measures for high-risk populations of HIV transmission was constructed. The evaluation model for the effectiveness of intervention measures for high-risk populations of HIV transmission includes an evaluation model for the effectiveness of TasP intervention measures:

[0023] The evaluation model for the effectiveness of TasP intervention measures characterizes the effectiveness of TasP intervention measures by the proportion of decline in new infections after the intervention of TasP intervention measures.

[0024] The World Health Organization has put forward the goal of "ending AIDS globally by 2030". One of the specific measures is to achieve "three 95%" in diagnosis and treatment measures (diagnosis and detection, antiviral treatment, and treatment effect): that is, 95% of HIV-infected individuals know their infection status through testing, 95% of diagnosed infected individuals receive antiretroviral therapy for AIDS, and 95% of infected individuals receiving antiretroviral therapy have their virus suppressed.

[0025] The annual number of newly infected cases under the actual implementation intensity of the diagnosis and treatment measures is , based on Equation (I), we get:

[0026] (IV)

[0027] In Equation (IV), τ0 and σ0 are respectively the actual completion situations of detection and diagnosis, antiviral treatment, and virus suppression, and φ is the proportion by which antiviral treatment reduces the HIV / AIDS transmission risk.

[0028] The annual number of newly infected cases when the diagnosis and treatment measures reach the target values (i.e., the "three 95%" targets for the detection and diagnosis proportion, antiviral treatment proportion, and virus suppression proportion) is , based on Equation (I), we get:

[0029] (XI)

[0030] In Equation (XI), respectively represent that the detection and diagnosis, antiviral treatment, and virus suppression proportions reach 95%, is the proportion by which antiviral treatment reduces the HIV / AIDS transmission risk.

[0031] After strengthening the TasP intervention measures, the calculation method for the proportion of decline in newly infected cases is as follows:

[0032] (XII)

[0033] Based on Equation (IV), Equation (XI), and Equation (XII), we get the final expression for the proportion of decline in newly infected cases after strengthening the TasP intervention measures:

[0034] (II)

[0035] In Equation (II), P is the proportion of decline in newly infected cases after strengthening the TasP intervention measures, %; the meanings of other parameters are as shown in Equation (IV), Equation (XI), and Equation (XII).

[0036] Based on the TasP intervention measure effectiveness evaluation model, it can be concluded that after taking the TasP intervention measures, the annual proportion of decline in newly infected cases intuitively demonstrates the role of the TasP intervention measures in HIV intervention work.

[0037] Furthermore, the HIV transmission high-risk population intervention measure effectiveness evaluation model further includes a detection and counseling intervention measure effectiveness evaluation model:

[0038] The effect evaluation model of the detection counseling intervention measures is characterized by the proportion of new infections decreased after the measures are strengthened:

[0039] Let , representing the high-risk group; , representing the low-risk group; are the detection discovery proportions of the high, medium, and low-risk groups respectively; is the average time from infection to detection and diagnosis, in days. Then the relationship between the detection discovery proportion and the detection discovery time is as follows:

[0040] (XIII)

[0041] In formula (XIII), are the annual new infection numbers of the high and low-risk groups under the actual implementation intensity of each measure, in cases, which can be obtained from formula (I); are the estimated cumulative number of existing living HIV / AIDS cases in the high and low-risk groups under the actual implementation intensity of each measure, in cases, where , = ).

[0042] Therefore, it is deduced from formula (XIII) that:

[0043] (XIV)

[0044] In formula (XIV), exp is the exponential function with the natural constant e as the base.

[0045] Let the frequency of MSM population receiving HIV antibody testing be , with the unit of times / year, , (XV)

[0046] Then the relationship between the detection discovery proportion and the detection frequency is deduced from formula (XIV) and formula (XV):

[0047] (XVI);

[0048] By increasing the detection frequency ( ), the detection discovery proportion ( ) is expanded, and thus:

[0049]

[0050] That is (Ⅳ);

[0051] (Ⅴ);

[0052] (Ⅲ);

[0053] In the formula respectively represent the actual completion of antiviral treatment and virus suppression, and φ represents the proportion of the reduction in the HIV / AIDS transmission risk caused by antiviral treatment. is the detection and diagnosis proportion in the high-risk group after the enhancement of the detection and counseling intervention measure, is the detection and diagnosis proportion of the low-risk group after the enhancement of the detection and counseling intervention measure. is the proportion of the decrease in new infections after the enhancement of the detection and counseling intervention measure, %.

[0054] The relationship between the detection frequency and the detection discovery proportion can be intuitively presented through the evaluation model of the detection and counseling intervention measure effect. Through this model, the detection discovery proportion at different detection frequencies can be inferred, that is, the intervention effect under different implementation intensities of the detection and counseling intervention measure can be predicted, providing scientific guidance for the implementation of the detection and counseling intervention measure.

[0055] Furthermore, the evaluation model for the intervention measure effect of the high-risk population of HIV transmission also includes the evaluation model for the intervention measure effect of condom promotion and use:

[0056] The evaluation model for the intervention measure effect of condom promotion and use characterizes the effect of the condom promotion and use intervention measure through the proportion of the decrease in new infections after the intensive implementation of the condom promotion and use intervention measure:

[0057] The long-term use of condoms can reduce the HIV transmission risk by , when the condom use proportion of the MSM population changes from the baseline data to , the new infections can be reduced by . Then the evaluation model for the intervention measure effect of condom promotion and use is as follows:

[0058] (VI)

[0059] In formula (VI), is the number of new infection cases in a year after the implementation of the condom promotion and use intervention measure, case; is the initial condom use proportion of the MSM population, dimensionless; is the condom use proportion of the MSM population after the implementation of the condom promotion and use intervention measure, is the protective effect of long-term condom use, %;

[0060] Then the final expression of the proportion of the decrease in new infections after the intensive implementation of the condom promotion and use intervention measure is obtained:

[0061] (VII)

[0062] In formula (VII), is the percentage decrease in new infections after the enhanced implementation of condom promotion intervention measures, %.

[0063] Based on the evaluation model of the condom promotion intervention measures, the annual percentage decrease in new infections after the implementation of the condom promotion intervention measures can be obtained, which intuitively reflects the effect of the implementation of the condom promotion intervention measures on reducing annual new infections, and can also reflect the impact of different implementation intensities on the results, providing scientific guidance for the implementation of the condom promotion intervention measures.

[0064] Furthermore, the evaluation model of the HIV transmission high-risk population intervention measures further includes the PrEP intervention measure evaluation model:

[0065] The PrEP intervention measure evaluation model characterizes the intervention effect of the PrEP intervention measures by the percentage decrease in new infections after the enhanced implementation of the PrEP intervention measures.

[0066] When the proportion of PrEP acceptance in the high-risk MSM population is ω and the effective rate of PrEP in reducing the risk of HIV transmission is ε the proportion of new HIV infections in the high-risk group is Г / (1 + Г), then the PrEP intervention measure evaluation model is as follows:

[0067] (VIII)

[0068] (IX)

[0069] In formula (VIII), is the number of new annual infection cases after the enhanced implementation of the PrEP intervention measures, cases; ω is the proportion of high-risk MSM population accepting PrEP, dimensionless, and ε' is the effectiveness of pre-exposure prophylaxis measures, %;

[0070] In formula (IX), is the percentage decrease in new infections after the enhanced implementation of the PrEP intervention measures, %.

[0071] Based on the PrEP intervention measure evaluation model, the annual percentage decrease in new infections after the implementation of the PrEP intervention measures can be obtained, which intuitively reflects the effect of the PrEP intervention measures on reducing annual new infections, and can also reflect the impact of different implementation intensities on the results, providing scientific guidance for the implementation of the PrEP intervention measures.

[0072] The present invention also discloses the application of the evaluation method for the HIV transmission high-risk population intervention measures described above, which is used to guide HIV intervention work.

[0073] The sources of the data involved in the present invention are shown in Table 2

[0074] Sources of data involved in Table 2

[0075]

[0076] References:

[0077] 1. NSW HIV Strategy 2016 – 2020: Data Report[C]. 2016.

[0078] 2. Smith DK, Herbst JH, Zhang X, et al. Condom effectiveness for HIV prevention by consistency of use among men who have sex with men in the United States[J]. Journal of acquired immune deficiency syndromes (1999), 2015, 68(3):337–344. DOI: 10.1097 / QAI.0000000000000461.

[0079] 3. Mccormack S, Dunn DT, Desai M, 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[J]. Lancet (London, England), 2016, 387(10013):53–60. DOI: 10.1016 / S0140-6736(15)00056-2.

[0080] 4. Cohen MS, Chen YQ, McCauley M, et al. Prevention of HIV-1 infection with early antiretroviral therapy[J]. The New England journal of medicine, 2011, 365(6):493–505. DOI: 10.1056 / NEJMoa1105243.

[0081] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0082] The present invention constructs a prediction model for the risk of new infections to evaluate the impact of intervention measures for high-risk groups of HIV transmission in the real world on reducing new HIV infections in the MSM population. The evaluation results of the present invention provide theoretical guidance for optimizing intervention measures, formulating appropriate intervention strategies, and reasonably allocating health resources.

[0083] The present invention introduces an equation for estimating the risk of new disease infections, constructs a relationship chain between the process and the outcome, and evaluates the effects of measures such as TasP intervention, testing and counseling intervention, promotion of condom use, and pre-exposure prophylaxis on the outcome of new HIV infections. And based on the evaluation model of the effectiveness of intervention measures for high-risk groups of HIV transmission constructed, the comprehensive effects of biological-behavioral intervention measures on new HIV infections in the MSM population are systematically elaborated from an overall level. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Figure 1 It is a schematic diagram for constructing an evaluation model of the effectiveness of intervention measures for high-risk groups of HIV transmission of the present invention.

[0085] Figure 2 It is a graph of the evaluation results of Example 1.

[0086] Figure 3 It is a graph of the evaluation results of Example 2.

[0087] Figure 4 It is a graph of the evaluation results of Example 3. DETAILED DESCRIPTION OF THE INVENTION

[0088] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

[0089] Example 1

[0090] TasP intervention measure:

[0091] When the proportions of HIV / AIDS testing and diagnosis, antiviral treatment, and viral suppression among MSM reach "90-90-90" from 2020 to 2030, the newly reported HIV infections among MSM in Shandong Province increase by 20% compared to 2012; when evaluated using Equation (II), when it reaches "95-90-90", the newly reported HIV infections among MSM remain unchanged compared to 2012; when it reaches "95-95-90", the newly reported HIV infections among MSM decrease by 18% compared to 2012; when it reaches "95-95-95", the newly reported HIV infections among MSM decrease by 35% compared to 2012. The results are as Figure 2 shown, Figure 2 the changes in the decline of newly reported infections when the HIV / AIDS diagnosis and treatment level is increased to "90-90-90", "95-90-90", "95-95-90", and "95-95-95" respectively.

[0092] Example 2

[0093] Behavior intervention measures for promoting condom use:

[0094] Assume that the baseline proportion of condom use among MSM is , the effective rate of long-term condom use is , when the condom use coverage rate reaches , this will lead to a reduction in the number of newly reported infections per year at a proportion, and the number of newly reported HIV infections see Equation (VI).

[0095] (VI)

[0096] (VII)

[0097] By increasing the promotion coverage rate of condoms among MSM from 12% to 50%, improving the HIV / AIDS diagnosis and treatment level to "95-95-95", and increasing the PrEP coverage rate of the high-risk group among MSM to 30% within 5 years (2020-2025), Equations (VI) and (VII) are used to evaluate the reduction of newly reported HIV infections among MSM due to the increase in TasP and condom use promotion coverage rate by the end of 2030. In Equation (VI), the index values refer to Table 2.

[0098] Based on the goal that the HIV / AIDS diagnosis and treatment level reaches "95-95-95" by the end of 2030, the condom use promotion coverage rate is increased by 10 percentage points year by year from 2020 to 2025 within 5 years, and its effect is evaluated.

[0099] Result analysis: For every 10 percentage point increase in the promotion coverage rate of condom use, the newly reported HIV infections among MSM population by 2030 will decrease by 5 percentage points compared to 2012; when the promotion coverage rate of condom use among MSM population reaches 50%, the newly reported HIV infections among MSM population by 2030 will decrease by 55% compared to 2012, as Figure 3 shown, Figure 3 which is the change in newly reported infections when the diagnosis and treatment level of HIV / AIDS is improved to "95-95-95" and the proportion of condom use increases equally.

[0100] Example 3

[0101] Testing, counseling and intervention, and PrEP biomedical intervention measures:

[0102] For low-risk and high-risk MSM populations, the research hypothesis for the testing frequency is as follows (low-risk / high-risk): 2 / 3 times / year, 2 / 4 times / year, 3 / 4 times / year, 3 / 6 times / year. The number of newly reported HIV infections corresponding to the respective testing frequencies is explored. The diagnosis and treatment level of HIV / AIDS among MSM population will be improved to "d-95-95" by 2030. The proportion of the decrease in the number of newly reported HIV infections by 2030 compared to 2012 is estimated for different diagnosis and treatment levels. Considering the economic burden brought by increasing the testing frequency, the testing frequency is increased to 2 / 4 times / year, and combined with the PrEP biomedical intervention measure, the PrEP coverage rate is gradually increased within 5 years (2020-2025). By 2030, the PrEP coverage rate of high-risk population maintains the coverage rate level in 2025. Using the combination of formula (Ⅲ) and (IX), the effect of the combined testing, counseling and PrEP biomedical intervention measures for high-risk population on reducing the newly reported HIV infections among MSM population is evaluated.

[0103] The results show that:

[0104] Based on the annual testing of 2 and 4 times for low-risk and high-risk populations among MSM respectively, the PrEP coverage rate of high-risk population increases by 10 percentage points successively within 5 years. The research results find that for every 10 percentage point increase in the PrEP coverage rate of high-risk population, the newly reported HIV infections among MSM population by 2030 will decrease by 6 percentage points compared to 2012; when the PrEP coverage rate of high-risk population expands to 70% within 5 years, the newly reported HIV infections among MSM population by 2030 will decrease by 50% compared to 2012. The results are as Figure 4 shown, Figure 4 which is the change in newly reported infections when the testing frequency is 2 / 4 times and the pre-exposure prophylaxis coverage rate among MSM population increases proportionally.

Claims

1. An evaluation method for the effectiveness of intervention measures for high-risk populations of HIV transmission, characterized in that, It includes the following steps: S1. Construct a new infection risk prediction model: （Ⅰ）； In formula (Ⅰ), n is the number of new infections per year, cases; N is the total number of surviving HIV / AIDS transmitted through same-sex contact, cases; β is the average transmission risk coefficient of infectious HIV / AIDS in the low-risk group, person / year; ρ is the proportion of the high-risk group in N, dimensionless; d1 is the detection and diagnosis proportion in the high-risk group, dimensionless; τ is the proportion of HIV / AIDS patients who receive antiviral treatment after detection and diagnosis, dimensionless; σ is the proportion of patients achieving viral suppression, dimensionless; φ is the proportion by which antiviral treatment can reduce the transmission risk of HIV / AIDS, dimensionless; Γ is Γ times the transmission risk of HIV / AIDS in the high-risk group compared to the low-risk group; d2 is the detection and diagnosis proportion in the low-risk group, dimensionless; S2. Based on the new infection risk prediction model, construct an evaluation model for the effectiveness of intervention measures for high-risk populations of HIV transmission. The evaluation model for the effectiveness of intervention measures for high-risk populations of HIV transmission includes an evaluation model for the effectiveness of TasP intervention measures. The evaluation model for the effectiveness of TasP intervention measures is characterized by the proportion of new infections decreased after the TasP intervention measures are strengthened to represent the effectiveness of the TasP intervention measures: （Ⅱ）； In formula (II), P is the percentage decrease in new infections after the intensification of TasP interventions, %; It is the value under the actual completion of the "three 95% targets"; It is the value when the "three 95% targets" are achieved and is 95%; φ is the proportion by which antiretroviral therapy can reduce the transmission risk of HIV / AIDS; The evaluation model for the effectiveness of intervention measures for high-risk populations of HIV transmission also includes an evaluation model for the effectiveness of testing and counseling intervention measures. The evaluation model for the effectiveness of testing and counseling intervention measures is characterized by the proportion of new infections decreased after the testing and counseling intervention measures are strengthened to represent the effectiveness of the testing and counseling intervention measures: （Ⅲ）； （Ⅳ）； （Ⅴ）； (XVI); In formula (III), is the percentage decrease in new infections after the intensification of the detection consultation intervention measure; In formula (V), is the detection and diagnosis proportion in the high-risk group after the enhancement of detection and counseling intervention measures; is the detection and diagnosis proportion in the low-risk group after the enhancement of detection and counseling intervention measures; In formula (XVI), , representing the high-risk group; , representing the low-risk group; is the annual new infection numbers of the high- and low-risk groups under the actual implementation intensity of each measure, in cases; is the estimated cumulative number of surviving HIV / AIDS cases in the high- and low-risk groups under the actual implementation intensity of each measure, in cases; is the detection frequency.

2. The method for evaluating the effectiveness of intervention measures for high-risk populations of HIV transmission according to claim 1, characterized in that, The evaluation model for the effectiveness of intervention measures for high-risk populations of HIV transmission also includes an evaluation model for the effectiveness of condom promotion and use intervention measures. The evaluation model for the effectiveness of condom promotion and use intervention measures is characterized by the proportion of new infections decreased after the condom promotion and use intervention measures are strengthened to represent the effectiveness of the condom promotion and use intervention measures: (VI) (VII) In formula (VI), is the number of newly infected cases per year after the intensification of the intervention measures for promoting condom use, in cases; is the effectiveness of continuous condom use, in %; is the initial proportion of condom use among MSM population, dimensionless; is the proportion of condom use among MSM population after the intensification of the intervention measures for promoting condom use; In formula (VII), is the percentage decrease in new infections after the intensification of condom promotion and use interventions, %.

3. The method for evaluating the effectiveness of intervention measures for high-risk populations of HIV transmission according to claim 1, wherein The evaluation model for the effectiveness of intervention measures for high-risk populations of HIV transmission also includes an evaluation model for the effectiveness of PrEP intervention measures. The evaluation model for the effectiveness of PrEP intervention measures is characterized by the proportion of new infections decreased after the PrEP intervention measures are strengthened to represent the intervention effect of the PrEP intervention measures. (VIII) (IX) In formula (VIII), y is the number of new infection cases per year after the PrEP intervention is strengthened, in cases; ω is the proportion of high-risk MSM population receiving PrEP, dimensionless; ε' is the effectiveness of pre-exposure prophylaxis, %. In formula (IX), is the percentage reduction in new infections after the PrEP intervention is strengthened, %.

4. The method for evaluating the effectiveness of HIV transmission high-risk population intervention measures according to claim 1, wherein The basis for dividing the high-risk group and the low-risk group is: calculate the score according to the MSM risk assessment scale. If the score ≥ 10, it is the high-risk group; if < 10, it is the low-risk group.

5. The method for evaluating the effectiveness of intervention measures for high-risk populations of HIV transmission according to claim 1, characterized in that, The "three 95% targets" are: 95% of HIV-infected individuals know their infection status through detection and diagnosis, 95% of diagnosed infected individuals receive antiretroviral therapy for AIDS, and 95% of infected individuals receiving antiretroviral therapy achieve viral suppression.

6. Use of the method for evaluating the effectiveness of the intervention measures for high-risk populations of HIV transmission, characterized in that: It is used to guide HIV intervention work.

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