Effect evaluation method and application of HIV (Human Immunodeficiency Virus) transmission high-risk group intervention measure

Abstract

The invention belongs to the technical field of AIDS prevention and control, and particularly relates to an effect evaluation method and application of intervention measures for HIV transmission high-risk groups. The effect evaluation method comprises the following steps: S1, constructing a new infection risk prediction model: # imgabs0 # imgabs1 # S2, based on the new infection risk prediction model, constructing an HIV transmission high-risk group intervention measure effect evaluation model, the HIV transmission high-risk group intervention measure effect evaluation model comprises a TasP intervention measure effect evaluation model, and the TasP intervention measure effect evaluation model comprises a TasP intervention measure effect evaluation model; after the TasP intervention measure effect evaluation model is enhanced by the TasP intervention measure, the new infection decline proportion represents the effect of the TasP intervention measure: # imgabs2. The new infection risk prediction model is constructed to evaluate the influence of the HIV propagation high-risk group intervention measure on the reduction of the HIV new infection of the MSM group in the real world; the evaluation result provides theoretical guidance for optimizing intervention measures, formulating proper intervention strategies and reasonably distributing health resources.

Description

Technical Field

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

[0002] AIDS is caused by infection with the human immunodeficiency virus (HIV). The general population is susceptible and there is no vaccine to prevent it. Once infected, people carry the virus for life and are highly contagious and have a high mortality rate. Behavioral and biological interventions for people at high risk of HIV transmission are the main strategies currently in place to curb the spread of AIDS. The main intervention measures include: condom promotion interventions, pre-exposure prophylaxis (PrEP) interventions, testing and counseling interventions, and antiviral treatment (TasP) interventions.

[0003] Currently, there is a lack of scientific guidance on the coverage, intensity and frequency of intervention measures, as well as a lack of scientific evaluation tools for intervention measures. As a result, behavioral and biological measures such as condom promotion, pre-exposure prevention, testing and consultation, and antiviral treatment have not achieved effective prevention and control results after many years of implementation, and the AIDS prevention and control situation remains severe.

[0004] How to scientifically evaluate the effectiveness of intervention measures for people at high risk of HIV transmission, rationally allocate and effectively utilize medical resources with limited medical resources, and guide the precise and high-quality implementation of HIV intervention work has become a technical problem that needs to be solved urgently. Summary of the invention

[0005] In order to solve the drawbacks of the above-mentioned prior art, the present invention introduces a new infection risk prediction model, and based on the new infection risk prediction model, establishes a risk prediction model for HIV new infection under biobehavioral intervention measures such as antiviral treatment, testing consultation, condom use promotion and pre-exposure prevention, and systematically and comprehensively evaluates the effects of multiple intervention measures in the real world on reducing new HIV infections in MSM populations, and predicts the impact of different implementation strengths of various measures on reducing new HIV infections. The main purpose is to explore the appropriate intervention measures that need to be taken for MSM populations with different transmission risks under the condition of limited medical resources, further guide the intervention work to be carried out accurately and with high quality, and conduct scientific evaluation of the work effect in a timely manner. The present invention has important guiding significance for formulating a comprehensive AIDS prevention and control strategy suitable for my country, and can also provide new ideas for the prevention and control of other infectious diseases.

[0006] The specific technical solutions of the present invention are as follows:

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

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

[0009] like Figure 1 As shown in the figure, the basic principles and assumptions for constructing the new infection risk estimation model are as follows:

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

[0011] ②The total number of people who survived HIV / AIDS transmitted through homosexuality is N, which is divided into high-risk and low-risk groups according to the occurrence of high-risk behaviors. 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 people diagnosed with HIV / AIDS who receive antiviral treatment is τ (the second 95% target), and the proportion of those who achieve viral suppression is σ (the third 95% target).

[0012] The specific division method of high-risk group and low-risk group is as follows:

[0013] The scores were calculated according to the MSM risk assessment scale, with risk assessment scores ≥10 being classified as high-risk group and scores <10 being classified as low-risk group.

[0014] Table 1 MSM risk assessment scale

[0015]

[0016]

[0017] ③ The average transmission risk coefficient of HIV / AIDS in the low-risk group is β / person-year; antiviral treatment can reduce the transmission risk of HIV / AIDS by The transmission risk factor of HIV / AIDS in the low-risk group with viral suppression under antiviral treatment is β / person-year; the risk of HIV / AIDS transmission in the high-risk group is Г times that of the low-risk group, so its transmission risk coefficient is Гβ / person-year. Under the effect of antiviral treatment, the transmission risk coefficient is Гβ / person-year.

[0018] Based on this, the new infection risk estimation equation was constructed:

[0019]

[0020] Simplifying formula (X), we get the new infection risk estimation model:

[0021]

[0022] In formula (I), n is the number of new infections per year, cases; N is the total number of HIV / AIDS survivors transmitted through homosexual transmission, cases; β is the average transmission risk coefficient of HIV / AIDS in the low-risk group, person / year; ρ is the proportion of the high-risk group in N, dimensionless; d1 is the proportion of confirmed cases in the high-risk group, dimensionless; τ is the proportion of HIV / AIDS diagnosed and receiving antiviral treatment, dimensionless; σ is the proportion of viral suppression, dimensionless; is the proportion of HIV / AIDS transmission risk that can be reduced by antiviral treatment, dimensionless; Γ is the HIV / AIDS transmission risk of the high-risk group is Г times that of the low-risk group; d2 is the proportion of confirmed cases in the low-risk group, dimensionless.

[0023] S2. Based on the new infection risk estimation model, a model for evaluating the effect of intervention measures for high-risk groups of HIV transmission is constructed. The model for evaluating the effect of intervention measures for high-risk groups of HIV transmission includes the TasP model for evaluating the effect of intervention measures:

[0024] The TasP intervention effect evaluation model characterizes the effect of the TasP intervention by the decrease in the proportion of new infections after the TasP intervention.

[0025] The World Health Organization has proposed the goal of "ending AIDS globally by 2030". One of the specific measures is to achieve "three 95%s" in diagnosis and treatment measures (diagnosis, antiviral treatment and treatment effectiveness): 95% of HIV-infected people know their infection status through testing, 95% of diagnosed infected people receive antiviral treatment for AIDS, and 95% of infected people receiving antiviral treatment have the virus suppressed.

[0026] The number of new infections per year under the actual implementation of diagnosis and treatment measures is n0. Based on formula (I), we get:

[0027]

[0028] In formula (IV), d1, d2, τ0, and σ0 are the actual completion status of diagnosis, antiviral treatment, and viral suppression, respectively. The proportion of HIV / AIDS transmission risk reduced by antiretroviral treatment.

[0029] The annual number of new infections when the diagnosis and treatment measures reach the target value (i.e. the detection diagnosis ratio, antiviral treatment ratio and viral suppression ratio achieve the "three 95%" targets) is n 预 , based on formula (I), we get:

[0030]

[0031] In formula (XI), d 1预 ,d 2预 , τ 预 , σ 预 The rates of confirmed diagnosis, antiviral treatment and viral suppression reached 95%, The proportion of HIV / AIDS transmission risk reduced by antiretroviral treatment.

[0032] The calculation method for the reduction in new infections after strengthening the TasP intervention measures is as follows:

[0033]

[0034] Based on formula (IV), formula (XI) and formula (XII), the final expression of the reduction rate of new infections after strengthening the TasP intervention measures is obtained:

[0035]

[0036] In formula (II), P is the percentage of new infections decreased after the intensification of TasP intervention measures, %; the representative meanings of other parameters are shown in formula (IV), formula (XI) and formula (XII).

[0037] Based on the TasP intervention effect evaluation model, we can obtain the annual decrease rate of new infections after taking the TasP intervention measures, and intuitively demonstrate the role of TasP intervention measures in HIV intervention work.

[0038] Furthermore, the HIV transmission high-risk population intervention measures effect evaluation model also includes a testing and consultation intervention measures effect evaluation model:

[0039] The effectiveness evaluation model of the testing and consultation intervention measures characterizes the effectiveness of the testing and consultation intervention measures by the reduction rate of new infections after the measures are strengthened:

[0040] Let i = 1, representing the high-risk group; i = 2, representing the low-risk group; d i are the detection ratios of high, medium and low risk groups, respectively; T i is the average time from infection to detection and diagnosis, days, then the relationship between the detection rate and the detection time is as follows:

[0041]

[0042] In formula (XIII), n i is the number of new infections in high-risk and low-risk groups under the actual implementation of various measures, cases, obtained by formula (I); N i It is the estimated cumulative number of surviving HIV / AIDS patients in high-risk and low-risk groups under the actual implementation of various measures, cases, where N1=*ρ, N2=N*(1-ρ).

[0043] Therefore, it can be deduced from formula (XIII):

[0044]

[0045] In formula (XIV), exp is an exponential function with the natural constant e as the base.

[0046] Let the frequency of HIV antibody testing for MSM be F i , the unit is times / year, T i =1 / F i , (XV)

[0047] The relationship between the detection rate and the detection frequency can be derived from formula (XIV) and formula (XV):

[0048]

[0049] By increasing the detection frequency (F i ), expand the detection rate (d i ), thus obtaining:

[0050] n0=1+2

[0051] Right now

[0052]

[0053]

[0054] Where τ0 and σ0 are the actual completion of antiviral treatment and viral suppression, respectively. The percentage of HIV / AIDS transmission risk reduced by antiretroviral treatment. 1预 To determine the proportion of confirmed cases in the high-risk group after the intensification of the test counseling intervention measures, d 2预 is the proportion of confirmed cases in the low-risk group after the strengthening of testing and consultation intervention measures. p′ is the proportion of new infections decreased after the strengthening of testing and consultation intervention measures, %.

[0055] The testing and consulting intervention effect evaluation model can intuitively show the relationship between the testing frequency and the detection discovery ratio. Through this model, the detection discovery ratio under different testing frequencies can be inferred, that is, the intervention effect under different testing and consulting intervention measures can be predicted, providing scientific guidance for the implementation of testing and consulting intervention measures.

[0056] Furthermore, the HIV transmission high-risk population intervention measures effect evaluation model also includes a condom promotion and use intervention measures effect evaluation model:

[0057] The evaluation model of condom promotion and use intervention measures is used to characterize the effectiveness of condom promotion and use intervention measures by the reduction rate of new infections after the intensified implementation of condom promotion and use intervention measures:

[0058] Long-term use of condoms can reduce the risk of HIV transmission to ε1. When the proportion of condom use in the MSM population changes from the baseline data C0 to C1, the number of new infections can be reduced by 1-ε1 (c1-c0). The evaluation model for the effectiveness of condom promotion intervention measures is as follows:

[0059]

[0060] In formula (VI), x is the number of new infection cases per year after the implementation of condom promotion and use intervention measures, cases; C0 is the initial proportion of condom use among MSM, dimensionless; C1 is the proportion of condom use among MSM after the implementation of condom promotion and use intervention measures, ε1 is the protective effect of long-term condom use, %;

[0061] The final expression of the decline rate of new infections after the intensified implementation of condom promotion and use intervention measures is obtained:

[0062]

[0063] In formula (VII), p X The rate of new infections decreased by % after the intensified implementation of condom promotion intervention measures.

[0064] Based on the evaluation model of the effectiveness of condom promotion and use intervention measures, the annual reduction rate of new infections after the implementation of condom promotion and use intervention measures can be obtained, which intuitively reflects the effect of the implementation of condom promotion and use intervention measures on reducing new infections annually, and can also reflect the impact of different enforcement strengths on the results, providing scientific guidance for the implementation of condom promotion and use intervention measures.

[0065] Furthermore, the HIV transmission high-risk population intervention measure effect evaluation model also includes a PrEP intervention measure effect evaluation model:

[0066] The PrEP intervention effectiveness evaluation model characterizes the intervention effectiveness of the PrEP intervention by measuring the decrease in the proportion of new infections after the intensive implementation of the PrEP intervention.

[0067] When the proportion of high-risk MSM receiving PrEP is ω, the effectiveness of PrEP in reducing the risk of HIV transmission is ε′, and the proportion of new HIV infections in the high-risk group is Г / (1+Г), ​​the PrEP intervention effect evaluation model is as follows:

[0068]

[0069]

[0070] In formula (VIII), n y is the number of new infection cases per year after the implementation of the enhanced PrEP intervention measures, cases; ω is the proportion of high-risk MSM receiving PrEP, dimensionless; ε' is the effectiveness of pre-exposure prevention measures, %;

[0071] In formula (IX), p y The percentage of new infections decreased after the intensive implementation of PrEP intervention measures, %.

[0072] Based on the PrEP intervention effect evaluation model, the annual decrease rate of new infections after the PrEP intervention can be obtained, which intuitively reflects the effect of PrEP intervention measures on reducing new infections annually, and can also reflect the impact of different enforcement strengths on the results, providing scientific guidance for the implementation of PrEP intervention measures.

[0073] The present invention also discloses the application of any of the above-mentioned methods for evaluating the effect of intervention measures for high-risk groups of HIV transmission, which is used to guide HIV intervention work.

[0074] The sources of the data involved in the present invention are shown in Table 2

[0075] Sources of data in Table 2

[0076]

[0077]

[0078] References:

[0079] 1.NSW HIV Strategy 2016–2020:Data Report[C].2016.

[0080] 2. Smith DK, Herbst JH, Zhang

[0081] 3.Mccormack S, Dunn DT, Desai M, et al. Pre-exposure prophylaxis to prevent the acquisition of HIV-1infection (PROUD): effectiveness results from the pilot phase of a pragmatic open-label randomized trial[J].Lancet(London,England),2016,387(10013):53–60.DOI:10.1016 / S0140-6736(15)00056-2.

[0082] 4.Cohen MS, Chen YQ, Mccauley M, et al. Prevention of HIV-1infection with early antiretroviral therapy[J]. The New England journal of medicine, 2011, 365(6): 493–505. DOI: 10.1056 / NEJMoa1105243.

[0083] Compared with the prior art, the present invention has the following beneficial effects:

[0084] The present invention constructs a new infection risk prediction model to evaluate the impact of intervention measures for high-risk groups for HIV transmission in the real world on reducing new HIV infections in MSM populations. The evaluation results of the present invention provide theoretical guidance for optimizing intervention measures, formulating appropriate intervention strategies, and rationally allocating health resources.

[0085] This paper introduces the disease new infection risk estimation equation, constructs the relationship chain between the process and the outcome, and evaluates the effects of TasP intervention, testing and consultation intervention, condom use promotion and pre-exposure prevention on the outcome of new HIV infection. Based on the constructed HIV transmission high-risk population intervention effect evaluation model, the comprehensive effect of biological-behavioral intervention measures on new HIV infection in MSM population is systematically explained from the overall level. BRIEF DESCRIPTION OF THE DRAWINGS

[0086] Figure 1 The schematic diagram is a schematic diagram of the model for evaluating the effect of intervention measures for high-risk groups of HIV transmission according to the present invention.

[0087] Figure 2 This is a diagram showing the evaluation results of Example 1.

[0088] Figure 3 This is a diagram showing the evaluation results of Example 2.

[0089] Figure 4 This is a diagram showing the evaluation results of Example 3. DETAILED DESCRIPTION

[0090] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings.

[0091] Example 1

[0092] TasP interventions:

[0093] When the proportion of HIV / AIDS testing, diagnosis, antiviral treatment and viral suppression in the MSM population rises to "90-90-90" in 2020-2030, the new HIV infection in the MSM population in Shandong Province will increase by 20% compared with 2012; when it rises to "95-90-90", the new HIV infection in the MSM population will remain unchanged compared with 2012; when it rises to "95-95-90", the new HIV infection in the MSM population will decrease by 18% compared with 2012; when it rises to "95-95-95", the new HIV infection in the MSM population will decrease by 35% compared with 2012. The results are as follows: Figure 2 As shown, Figure 2 This is the decrease in new infections when the HIV / AIDS diagnosis and treatment level is raised to "90-90-90", "95-90-90", "95-95-90" and "95-95-95" respectively.

[0094] Example 2

[0095] Behavioral interventions to promote condom use:

[0096] Assuming that the baseline proportion of condom use among MSM is C0, and the effectiveness of long-term condom use is ε1, when the condom use coverage reaches C1, this will lead to a decrease in the number of new HIV infections per year at a rate of 1-ε1(c1-c0), and the number of new HIV infections n x See formula (VI).

[0097]

[0098]

[0099] By increasing the condom promotion coverage rate among MSM from 12% to 50%, raising the HIV / AIDS diagnosis and treatment level to "95-95-95", and increasing the PrEP coverage rate of the high-risk group of MSM to 30% within 5 years (2020-2025), formulas (VI) and (VII) were used to evaluate the reduction of new HIV infections among MSM by 2030 due to the increase in the promotion coverage rate of TasP and condom use. In formula (VI), the indicator values ​​refer to Table 2.

[0100] On the basis of achieving the "95-95-95" goal of HIV / AIDS diagnosis and treatment levels by 2030, the coverage rate of condom use promotion will be increased by 10 percentage points each year in the five years from 2020 to 2025, and its effectiveness will be evaluated.

[0101] Results: For every 10 percentage point increase in condom use promotion coverage, the new HIV infection rate among MSM will decrease by 5 percentage points by 2030 compared with 2012. When the condom use promotion coverage among MSM reaches 50%, the new HIV infection rate among MSM will decrease by 55% by 2030 compared with 2012. Figure 3 As shown, Figure 3 This is the decrease in new infections when the HIV / AIDS diagnosis and treatment level is raised to "95-95-95" and the proportion of condom use is increased.

[0102] Example 3

[0103] Testing-Counselling Interventions and PrEP Biomedical Interventions:

[0104] For low-risk and high-risk MSM, the study assumes that 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, and explores the number of new HIV infections at the corresponding testing frequencies. In 2030, the diagnosis and treatment level of HIV / AIDS in the MSM population will be improved to "d-95-95", and the proportion of new HIV infections that will decrease by 2030 compared with 2012 at different diagnosis and treatment levels is estimated. Considering the economic burden of increasing the testing frequency, the testing frequency is increased to 2 / 4 times / year, and combined with PrEP biological intervention measures, the PrEP coverage rate will be gradually increased within 5 years (2020-2025). By 2030, the PrEP coverage rate of the high-risk population will maintain the coverage level of 2025. The combination of formula (III) and (IX) is used to evaluate the effect of combined testing consultation and high-risk PrEP biomedical intervention measures on reducing new HIV infections in the MSM population.

[0105] The results show:

[0106] On the basis of testing low-risk and high-risk MSM 2 and 4 times a year respectively, the PrEP coverage rate of high-risk groups will increase by 10 percentage points in 5 years. The research results show that for every 10 percentage point increase in the PrEP coverage rate of high-risk groups, the new HIV infection rate of MSM population will decrease by 6 percentage points by 2030 compared with 2012; when the PrEP coverage rate of high-risk groups is expanded to 70% within 5 years, the new HIV infection rate of MSM population will decrease by 50% by 2030 compared with 2012. The results are as follows: Figure 4 As shown, Figure 4 The decrease in new infections occurs when the testing frequency is 2 / 4 and the pre-exposure prophylaxis coverage rate among MSM increases proportionally.

Claims

1. A method for evaluating the effectiveness of intervention measures for HIV transmission high-risk populations, characterized in that: The steps include: S1. Construct a new infection risk estimation model: In formula (I), n is the number of new infections per year, cases; N is the total number of HIV / AIDS survivors transmitted through homosexuality, 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 proportion of confirmed cases in the high-risk group, dimensionless; τ is the proportion of people diagnosed with HIV / AIDS who receive antiviral treatment, dimensionless; σ is the proportion of people who achieve viral suppression, dimensionless; is the proportion of HIV / AIDS transmission risk that can be reduced by antiviral treatment, dimensionless; Γ is the HIV / AIDS transmission risk of the high-risk group is Γ times that of the low-risk group; d2 is the proportion of confirmed cases in the low-risk group, dimensionless; S2. Based on the new infection risk estimation model, a model for evaluating the effect of intervention measures for high-risk groups of HIV transmission is constructed. The model for evaluating the effect of intervention measures for high-risk groups of HIV transmission includes a TasP model for evaluating the effect of intervention measures. The TasP intervention effect evaluation model characterizes the effect of the TasP intervention by the reduction ratio of new infections after the TasP intervention is strengthened: In formula (Ⅱ), P is the percentage of new infections reduced after the intensification of TasP intervention measures, %; d1, d2, τ0, σ0 are the values ​​when the "three 95% targets" are actually achieved; d 1预 ,d 2预 , τ 预 , σ 预 The achievement value for the "three 95% targets" is 95%; The proportion by which antiretroviral treatment can reduce the risk of HIV / AIDS transmission.

2. The method for evaluating the effect of intervention measures for high-risk groups of HIV transmission according to claim 1, characterized in that: The HIV transmission high-risk population intervention measures effect evaluation model also includes a testing and consultation intervention measures effect evaluation model. The test consultation intervention effect evaluation model characterizes the effect of the test consultation intervention by the reduction rate of new infections after the test consultation intervention is strengthened: In formula (III), p′ is the decrease in the proportion of new infections after the strengthening of the testing and consultation intervention measures, %; In formula (V), d 1预 The proportion of confirmed tests in the high-risk group after the strengthening of the test consultation intervention measures; d 2预 To determine the proportion of confirmed tests in the low-risk group after the testing consultation intervention was strengthened.

3. The method for evaluating the effect of intervention measures for high-risk groups of HIV transmission according to claim 1, characterized in that: The HIV transmission high-risk population intervention measures effect evaluation model also includes a condom promotion and use intervention measures effect evaluation model. The condom promotion and use intervention effect evaluation model characterizes the effect of the condom promotion and use intervention measures by the reduction rate of new infections after the condom promotion and use intervention measures are strengthened: In formula (VI), n x The number of new infections per year after the intensification of condom promotion interventions was ; ε1 is the effectiveness of continuous condom use, %; C0 is the initial proportion of condom use among MSM, dimensionless; C1 is the proportion of condom use among MSM after the intensification of condom promotion intervention measures; In formula (VII), p X The percentage of new infections decreased after the intensification of condom promotion interventions was %.

4. The method for evaluating the effect of intervention measures for high-risk groups of HIV transmission according to claim 1, characterized in that: The HIV transmission high-risk population intervention measures effect evaluation model also includes a PrEP intervention measures effect evaluation model, The PrEP intervention effect evaluation model characterizes the intervention effect of the PrEP intervention by the reduction rate of new infections after the PrEP intervention is strengthened. In formula (VIII), ny is the number of new infection cases per year after the strengthening of PrEP intervention measures, cases; ω is the proportion of high-risk MSM people receiving PrEP, dimensionless; ε′ is the effectiveness of pre-exposure prevention measures, %; In formula (IX), p y This is the decrease in new infections after the intensification of PrEP intervention measures, %.

5. The method for evaluating the effect of intervention measures for high-risk groups of HIV transmission according to claim 1, characterized in that: The basis for dividing the high-risk group and the low-risk group is: the score is calculated according to the MSM risk assessment scale, and the score ≥10 is the high-risk group, and <10 is the low-risk group.

6. The method for evaluating the effectiveness of intervention measures for HIV transmission high-risk populations according to claim 1, characterized in that: The "three 95% goals" are: 95% of HIV-infected people know their infection status through testing and diagnosis, 95% of diagnosed infected people receive AIDS antiviral treatment, and 95% of infected people receiving antiviral treatment have the virus suppressed.

7. The use of the method for evaluating the effect of intervention measures for high-risk groups of HIV transmission according to any one of claims 1 to 6, characterized in that: Used to guide HIV intervention work.

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