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Community-based organizations deliver peer-led support services to people living with HIV. Systematic reviews have found that peer-led community-based support services can improve HIV treatment outcomes; however, few studies have been implemented to evaluate its impact on mortality using long-term follow-up data.
We aimed to evaluate the associations between the receipt of peer-led community-based support services and HIV treatment outcomes and survival among people living with HIV in Wuxi, China.
We performed a propensity score–matched retrospective cohort study using data collected from the Chinese National HIV/AIDS Comprehensive Information Management System for people living with HIV in Wuxi, China, between 2006 and 2021. People living with HIV who received adjunctive peer-led community-based support for at least 6 months from a local community-based organization (exposure group) were matched to people living with HIV who only received routine clinic-based HIV care (control group). We compared the differences in HIV treatment outcomes and survival between these 2 groups using Kaplan-Meier curves. We used competing risk and Cox proportional hazards models to assess correlates of AIDS-related mortality (ARM) and all-cause mortality. We reported adjusted subdistribution hazard ratio and adjusted hazard ratio with 95% CIs.
A total of 860 people living with HIV were included (430 in the exposure group and 430 in the control group). The exposure group was more likely to adhere to antiretroviral therapy (ART; 396/430, 92.1% vs 360/430, 83.7%;
The receipt of peer-led community-based support services correlated with significantly improved HIV treatment outcomes and survival among people living with HIV in a middle-income country in Asia. The 15-year follow-up period in this study allowed us to identify associations with survival not previously reported in the literature. Future interventional trials are needed to confirm these findings.
According to the 2020 global AIDS report, 38 million people are living with HIV globally, of whom 25.4 million are receiving antiretroviral therapy (ART) [
The overall life expectancy of people living with HIV with good adherence to ART is approaching that of the general population in many high-income countries [
Task shifting involves the rational redistribution of tasks from the professional health workforce to community-based organizations (CBOs) and community health workers (CHWs) and is recognized by the World Health Organization (WHO) as an important strategy to optimize HIV care [
CBOs and CHWs have played a critical role in optimizing the HIV care continuum in China, especially in efforts to increase access to ART and improve retention in care [
Using routine surveillance records on people living with HIV, we conducted a propensity score–matched cohort study of individuals who were served by local CBOs on HIV care. Convenient sampling method was used to enroll people living with HIV who had received peer-led community-based support services from local CBOs in the exposure group. In the meantime, we used propensity score matching (PSM) to enroll a comparable control group from other people living with HIV who had never received such a service.
Wuxi is a city of 8.5 million people in China’s Jiangsu Province. As of December 2021, a total of 4111 people living with HIV were registered as living in Wuxi. Rainbow Family is currently the only CBO registered with the local government to provide services for people living with HIV in Wuxi. This CBO has been providing support services to people living with HIV since June 2006.
In 2003, China implemented free ART for people living with HIV [
In Wuxi, all newly diagnosed people living with HIV are informed of their diagnosis and receive their initial HIV care visit at a local CDC clinic or infectious diseases hospital. At this initial visit, health care providers will introduce people living with HIV to the peer-led community-based support services offered at Rainbow Family and provide a referral if desired. A CHW from Rainbow Family will be assigned to any referred person living with HIV in Wuxi. Not all newly diagnosed people living with HIV opt to use the peer support services provided by CBOs. Factors influencing decision-making include, but are not limited to, self-acceptance of HIV status, willingness to expose their sexual orientation to others in the CBOs, and willingness to be followed up by peer CHWs in daily life.
CHWs at Rainbow Family are people living with HIV themselves and recruited as volunteers working for CBOs in their spare time who have documented adherence to ART for at least 12 months and demonstrated strong interpersonal and communication skills. Before providing services to clients, CHWs at Rainbow Family receive education on HIV pathogenesis, prevention, and treatment, as well as training on how to provide psychological support and referrals to other medical services. CHW trainings are led by professional health care workers, including public health practitioners from the Wuxi municipal CDC, HIV doctors and nurses, mental health counselors, and experienced peer educators. After passing the professional training, the CHWs will be assigned clients who are people living with HIV and initiate the peer-led community-based support according to guidelines.
The peer-led community-based support model provided by Rainbow Family was designed as a patient-centered peer support model. CHWs build trust and rapport with people living with HIV through regular face-to-face communication, contact through WeChat (an instant messaging software widely used in China), telephone calls, home visits, and group activities. These regular interactions allow CHWs to provide health care services and support to people living with HIV that are tailored to the individual needs of clients.
A social, medical, and mental ART support (SMART) model is used as a conceptual framework to guide this service (
The social, medical, and mental antiretroviral therapy (SMART) model of community-based peer-led support for people living with HIV in Wuxi, China. ART: antiretroviral therapy.
In accordance with national HIV treatment guidelines, HIV diagnoses are reported via the Chinese National HIV/AIDS Comprehensive Information Management System (CNHCIMS) within 24 hours. Information on sociodemographic characteristics, risk behaviors, CD4 count, HIV viral load, and mortality is recorded in the CNHCIMS. We extracted case report data from the CNHCIMS on sociodemographic characteristics and risk factors for HIV transmission for all people living with HIV in Wuxi between January 1, 2006, and December 31, 2019. We also extracted follow-up data detailing care retention, ART adherence, CD4 and viral load monitoring, mortality, and the cause of death for the same people living with HIV between January 1, 2006, and December 31, 2021.
Rainbow Family collects and records the name and government-issued ID card number of all people living with HIV who have been assigned a CHW and received peer-led community-based support services. We obtained a list of people living with HIV who ever received peer-led community-based support from Rainbow Family, and persons on this list were linked to the CNHCIMS data by their unique government-issued ID card number. People living with HIV were assigned to the exposure group if they met the following inclusion criteria: (1) age ≥18 years at HIV diagnosis; (2) initiated ART on and before December 31, 2019; and (3) received peer-led community-based support from Rainbow Family for at least 6 months.
People living with HIV in Wuxi identified in the CNHCIMS who had not received peer-led community-based support from Rainbow Family were eligible to be assigned to the control group in our analysis. To adjust for potential confounders, PSM was used to match people living with HIV in the exposure group with controls. Sex, age at diagnosis, ethnicity, education, marital status, occupation, the route of HIV infection, and baseline CD4 count are factors found to be significantly associated with survival among people living with HIV in previous studies and therefore were included in our PSM model [
When implementing PSM, propensity scores were generated using logistic regression, with the receipt versus nonreceipt of peer-led community-based support as the dependent variable. Propensity scores were generated for each of the imputed data sets, and an average propensity score for each observation was calculated across data sets. Each patient who received peer-led community-based support services (exposure group) was matched 1:1 with a patient who received routine support (control group) according to their propensity scores, using the nearest neighbor matching method without replacement.
Two sets of variables were extracted from the CNHCIMS. The first set was variables in HIV case report data set evaluated at diagnosis, which involved sex (male and female), age at diagnosis (continuous), ethnicity (Han and others), education (primary or less, secondary, and tertiary), marital status (unmarried, married, and divorced or widowed), occupation (student and others), the route of HIV infection (men who have sex with men and others including heterosexual behavior, drug use, and blood donation), the date of HIV diagnosis, and baseline CD4 count (cells/μL). All these variables were categorized into 2 or 3 subgroups where necessary and applicable. The other set was variables in the follow-up data set recorded after HIV diagnosis, in which drug collection, ART interruption, and scheduled follow-up visit were used to measure adherence to ART, and CD4 and viral load were used to measure retention in care.
All data on study outcomes were extracted from the CNHCIMS, and all outcomes were assessed using these extracted data. Adherence to ART was defined as never having a documented period of ART interruption and never having a period when a scheduled follow-up clinic visit was missed >3 months. Retention in care was defined as having received either CD4 or viral load monitoring on at least 1 occasion ≥12 months after ART initiation. People living with HIV who were on ART for at least 6 months and had a documented HIV viral load ≤1000 copies per mL were considered to be virally suppressed [
Information on the cause of death was obtained from diagnosis codes in the CNHCIMS. Causes of death were classified into categories of ARM, NARM, and all-cause mortality according to the coding causes of death in HIV Project protocol [
Descriptive statistics were used to summarize baseline demographic characteristics and HIV treatment outcomes for both the exposure and control groups. Differences between groups were compared using the Pearson chi-square test. Person-years (PY) was used to estimate ARM, NARM, and all-cause mortality. The Kaplan-Meier method was used to generate survival curves, and the log rank test was conducted to assess differences in survival time between the exposure and control groups. Competing risk models were used to identify factors potentially associated with ARM. Subdistribution hazard ratios were reported with corresponding 95% CIs. Cox proportional hazards models were used to assess correlates of all-cause mortality with reporting hazard ratios and its 95% CIs. Sex, age at diagnosis, ethnicity, marital status, education, occupation, the mode of transmission, the date of HIV diagnosis, baseline CD4 count, the receipt of peer-led community-based support, adherence to ART, and retention in care were included in the adjusted analysis for correlates of mortality and mortality, in which variables with a
This study was approved by the Ethics Review Committee of Wuxi Municipal Centre for Disease Control and Prevention (WXCDC2022014). A unique ID number was used to protect each participant’s privacy.
Data describing a total of 2794 people living with HIV were retrieved from the CNHCIMS between 2006 and 2019, among whom 430 met the criteria to be assigned to the exposure group. There were significant differences in baseline characteristics, including sex (
Baseline characteristics of people living with HIV assigned to the exposure and control groups before and after propensity score matching (PSM).
Variables | Before PSM | After PSM | ||||||||||||||
|
Exposure group (n=430), n (%) | Other people living with HIV (n=2364), n (%) | Exposure group (n=430), n (%) | Control group (n=430), n (%) | ||||||||||||
|
.005 |
|
.77 | |||||||||||||
|
Male | 365 (84.9) | 2117 (89.6) |
|
365 (84.9) | 368 (85.6) |
|
|||||||||
|
Female | 65 (15.1) | 247 (10.5) |
|
65 (15.1) | 62 (14.4) |
|
|||||||||
|
<.001 |
|
.89 | |||||||||||||
|
<30 | 196 (45.6) | 741 (31.4) |
|
196 (45.6) | 198 (46.1) |
|
|||||||||
|
≥30 | 234 (54.4) | 1623 (68.6) |
|
234 (54.4) | 232 (54) |
|
|||||||||
|
.61 |
|
.73 | |||||||||||||
|
Han ethnicity | 425 (98.8) | 2329 (98.5) |
|
425 (98.8) | 426 (99.1) |
|
|||||||||
|
Others | 5 (1.2) | 35 (1.5) |
|
5 (1.2) | 4 (0.9) |
|
|||||||||
|
<.001 |
|
.27 | |||||||||||||
|
Primary or less | 16 (3.7) | 280 (11.8) |
|
16 (3.7) | 23 (5.4) |
|
|||||||||
|
Secondary | 234 (54.4) | 1404 (59.4) |
|
234 (54.4) | 214 (49.7) |
|
|||||||||
|
Tertiary | 180 (41.9) | 680 (28.8) |
|
180 (41.9) | 193 (44.9) |
|
|||||||||
|
<.001 |
|
.09 | |||||||||||||
|
Unmarried | 210 (48.8) | 859 (36.3) |
|
210 (48.8) | 228 (53) |
|
|||||||||
|
Married | 147 (34.2) | 790 (33.4) |
|
147 (34.2) | 118 (27.5) |
|
|||||||||
|
Divorced and widowed | 73 (17) | 715 (30.3) |
|
73 (17) | 84 (19.5) |
|
|||||||||
|
<.001 |
|
.90 | |||||||||||||
|
Student | 41 (9.5) | 69 (2.9) |
|
41 (9.5) | 42 (9.8) |
|
|||||||||
|
Others | 389 (90.5) | 2295 (97.1) |
|
389 (90.5) | 388 (90.2) |
|
|||||||||
|
.23 |
|
.94 | |||||||||||||
|
MSMa | 262 (60.9) | 1511 (63.9) |
|
262 (60.9) | 261 (60.7) |
|
|||||||||
|
Others | 168 (39.1) | 853 (36.1) |
|
168 (39.1) | 169 (39.3) |
|
|||||||||
|
.50 |
|
.62 | |||||||||||||
|
Before June 2016 | 275 (64) | 1472 (62.3) |
|
275 (64) | 268 (62.3) |
|
|||||||||
|
After June 2016 | 155 (36.1) | 892 (37.7) |
|
155 (36.1) | 162 (37.7) |
|
|||||||||
|
.001 |
|
.76 | |||||||||||||
|
<200 | 126 (29.3) | 899 (38) |
|
126 (29.3) | 122 (28.4) |
|
|||||||||
|
≥200 | 304 (70.7) | 1465 (62) |
|
304 (70.7) | 308 (71.6) |
|
aMSM: men who have sex with men.
bSince June 2016, all people living with HIV in China have been encouraged to initiate antiretroviral therapy regardless of CD4 cell count.
Among all 860 people living with HIV included in our analysis, 733 (85.2%) were men, 394 (45.8%) were diagnosed with HIV aged <30 years, 851 (99%) were of Han ethnicity, 373 (43.4%) had completed high school or had a higher level of educational achievement, and 83 (9.7%) were current students. More than half were unmarried (438/860, 50.9%) and were men who have sex with men (523/860, 60.8%). More than one-third (317/860, 36.9%) were diagnosed after June 2016, and just under one-third (248/860, 28.8%) had a CD4 count <200 cells/μL at the time of HIV diagnosis.
Compared with the control group, people living with HIV in the exposure group were more likely to adhere to ART (396/430, 92.1% vs 360/430, 83.7%;
Antiretroviral therapy (ART) adherence and retention in HIV care between the exposure and control groups (n=860).
Variables | Total (n=860), n (%) | Exposure group (n=430), n (%) | Control group (n=430), n (%) | Chi-square ( |
|||||||||
|
14.2 (1) | <.001 | |||||||||||
|
Yes | 756 (87.9) | 396 (92.1) | 360 (83.7) |
|
|
|||||||
|
No | 104 (12.1) | 34 (7.9) | 70 (16.3) |
|
|
|||||||
|
50.7 (1) | <.001 | |||||||||||
|
Yes | 729 (84.8) | 402 (93.5) | 327 (76.1) |
|
|
|||||||
|
No | 131 (15.2) | 28 (6.5) | 103 (24) |
|
|
aART: antiretroviral therapy.
bAdherence to ART was defined as never having a documented period of ART interruption and never having a period when a scheduled follow-up clinic visit was missed by more than 3 months.
cRetention in care was defined as receiving either CD4 or viral load monitoring within 12 months after ART initiation.
Viral suppression between the exposure and control groups (n=860).
Variables | Exposure group | Control group | ||||||||||
|
Values, n/N (%) | Chi-square ( |
Trend ( |
Values, n (%) | Chi-square ( |
Trend ( |
||||||
|
501.5 (4) | <.001 |
|
211.4 (4) | <.001 | |||||||
|
9-12 | 88/430 (20.5) |
|
|
59/430 (13.7) |
|
|
|||||
|
9-15 | 211/430 (49.1) |
|
|
115/430 (26.7) |
|
|
|||||
|
9-18 | 292/430 (67.9) |
|
|
169/430 (39.3) |
|
|
|||||
|
9-21 | 341/430 (79.3) |
|
|
207/430 (48.1) |
|
|
|||||
|
9-24 | 381/430 (88.6) |
|
|
243/430 (56.5) |
|
|
|||||
|
0.02 (4) | .89 |
|
0.1 (4) | .79 | |||||||
|
9-12 | 83/88 (94.3) |
|
|
52/59 (88.1) |
|
|
|||||
|
9-15 | 196/211 (92.9) |
|
|
105/115 (91.3) |
|
|
|||||
|
9-18 | 271/292 (92.8) |
|
|
154/169 (91.1) |
|
|
|||||
|
9-21 | 317/341 (93) |
|
|
187/207 (90.3) |
|
|
|||||
|
9-24 | 357/381 (93.7) |
|
|
217/243 (89.3) |
|
|
During the study period, 25 individuals died within 4316.8 PY of follow-up. Among the 25 people living with HIV who died, 19 (76%) and 6 (24%) were attributed to ARM and NARM, respectively. Reasons for ARM were AIDS-related opportunistic infections (9/19, 47%), AIDS-related malignancies (6/19, 31%), and HIV wasting syndrome (4/19, 21%). Compared with the control group, the exposure group had lower rates of ARM (1.8 vs 7.0 per 1000 PY; rate difference −5.2;
Survival analysis showed that people living with HIV in the exposure group had higher cumulative survival rates (
All-cause mortality between the exposure and control groups.
Correlates of AIDS-related mortality (ARM) and all-cause mortality among people living with HIV.
Characteristics | PYa of follow-up | ARM | All-cause mortality | ||||||
|
|
Deaths, n | Mortality rate (per 1000 PY; %) | Adjusted SHRb (95% CI) | Deaths, n | Mortality rate (per 1000 PY; %) | Adjusted HRc (95% CI) | ||
|
|||||||||
|
Male | 3650.43 | 17 | 4.7 | Reference | 22 | 6.0 | Reference | |
|
Female | 666.47 | 2 | 3.0 | 0.32 (0.05-1.87)d | 3 | 4.5 | 0.30 (0.08-1.12)d | |
|
|||||||||
|
<30 | 1934.85 | 4 | 2.1 | Reference | 4 | 2.1 | Reference | |
|
≥30 | 2382.05 | 15 | 6.3 | 1.99 (0.52-7.61) | 21 | 8.8 | 2.44 (0.56-10.77) | |
|
|||||||||
|
Han ethnicity | 4206.67 | 18 | 4.3 | Reference | 24 | 5.7 | Reference | |
|
Others | 110.23 | 1 | 9.1 | 1.46 (0.24-8.79) | 1 | 9.1 | 1.25 (0.15-10.15)d | |
|
|||||||||
|
Unmarried | 2143.83 | 6 | 2.8 | Reference | 6 | 2.8 | Reference | |
|
Married | 1424.30 | 6 | 4.2 | 0.67 (0.20-2.28) | 10 | 7.0 | 1.08 (0.28-4.16) | |
|
Divorced and widowed | 748.77 | 7 | 9.3 | 1.10 (0.29-4.15) | 9 | 12.0 | 1.43 (0.35-5.85) | |
|
|||||||||
|
Primary or less | 196.50 | 1 | 5.1 | Reference | 3 | 15.3 | Reference | |
|
Secondary | 2320.90 | 14 | 6.0 | 1.85 (0.16-21.30)d | 18 | 7.8 | 0.67 (0.18-2.47) | |
|
Higher | 1799.50 | 4 | 2.2 | 1.34 (0.07-25.00)d | 4 | 2.2 | 0.36 (0.06-1.98) | |
|
|||||||||
|
Student | 397.19 | 1 | 2.5 | Reference | 1 | 2.5 | Reference | |
|
Others | 3919.71 | 18 | 4.6 | 0.61 (0.07-5.76)d | 24 | 6.1 | 0.76 (0.07-7.71) | |
|
|||||||||
|
MSMe | 2554.63 | 6 | 2.3 | Reference | 9 | 3.5 | Reference | |
|
Others | 1762.27 | 13 | 7.4 | 3.17 (1.19-8.41) | 16 | 9.1 | 1.82 (0.67-4.94) | |
|
|||||||||
|
Before June 2016 | 2997.84 | 15 | 5.0 | Reference | 20 | 6.7 | Reference | |
|
After June 2016 | 1319.06 | 4 | 3.0 | 0.69 (0.16-2.97)d | 5 | 3.8 | 0.43 (0.14-1.30)d | |
|
|||||||||
|
<200 | 1290.49 | 13 | 10.1 | Reference | 15 | 11.6 | Reference | |
|
≥200 | 3026.40 | 6 | 2.0 | 0.24 (0.09-0.66) | 10 | 3.3 | 0.39 (0.17-0.90) | |
|
|||||||||
|
No | 2144.74 | 15 | 7.0 | Reference | 20 | 9.3 | Reference | |
|
Yes | 2172.12 | 4 | 1.8 | 0.28 (0.09-0.95) | 5 | 2.3 | 0.30 (0.11-0.82) | |
|
|||||||||
|
Yes | 3760.96 | 10 | 2.7 | Reference | 15 | 4.0 | Reference | |
|
No | 555.94 | 9 | 16.2 | 4.55 (1.74-12.50) | 10 | 18.0 | 3.70 (1.56-8.33) | |
|
|||||||||
|
No | 855.34 | 6 | 7.0 | Reference | 10 | 11.7 | Reference | |
|
Yes | 3461.56 | 13 | 3.8 | 0.46 (0.14-1.54) | 15 | 4.3 | 0.27 (0.11-0.64) |
aPY: person-years.
bSHR: subdistribution hazard ratio.
cHR: hazard ratio.
dThese variables were tested associated with mortality at
eMSM: men who have sex with men.
fART: antiretroviral therapy.
In this propensity score–matched analysis of HIV treatment outcomes and mortality among people living with HIV in Wuxi between 2006 and 2021, we found that people living with HIV who received peer-led community-based support had better ART adherence, higher rates of retention in care, and improved survival rates than people living with HIV who had not received these services. Rates of viral suppression and compliance to viral load monitoring guidelines were high in the exposure group, with >90% of people living with HIV who had participated in the multicomponent support services program achieving viral suppression 9 to 24 months after HIV diagnosis. Most previous studies evaluating the relationship between peer-led support and HIV treatment outcomes were implemented in low- to middle-income countries (LMICs) in Africa or high-income countries, with few previous studies having been conducted in Asia [
People living with HIV in China who received at least 6 months of adjunctive peer-led community-based support had better ART adherence, viral suppression, and retention in HIV care than those in matched controls who only received standard clinic-based HIV care. Differences in retention in care were particularly pronounced, with >93% and only 76% of people living with HIV in the exposure and control groups retained in HIV care for ≥12 months after ART initiation, respectively. Our findings are similar to previous observational and experimental evaluations of support programs delivered by CHWs to people living with HIV in LMICs [
Compared with matched controls, the receipt of peer-led community-based support services was associated with 72% and 70% reductions in ARM and all-cause mortality, respectively, among people living with HIV in China. These findings are consistent with previous studies conducted in Rwanda [
The peer-led community-based support services provided by Rainbow Family adopted a multicomponent SMART framework that attempted to provide broad support for HIV care across multiple domains, including HIV education and counseling, ART adherence and laboratory monitoring reminders, social and emotional support for interpersonal relationships and disclosure of HIV status, and mental health counseling. Although the WHO guidelines encourage task shifting of HIV services to CHWs in resource-limited settings, little guidance is available as to which types of support services or delivery models should be prioritized in task-shifting efforts to optimize health outcomes among people living with HIV [
Although the Chinese government has established the China AIDS Fund to support the development of grassroots organizations including CBOs providing service to people living with HIV, there are only a small number of people living with HIV who are served by peer CHWs. As CBOs in China are required to register as an official nongovernmental organization in a local Civil Affairs Bureau and most of them do not have sufficient personnel and funding to support themselves to achieve this, they have to apply for governmental funding on HIV as grassroots organizations through cooperation with local CDCs or specialized infectious disease hospital, which limits their development and growth owing to lacking endorsement from the government [
To the best of our knowledge, this is the first study to evaluate associations between the receipt of a multicomponent peer-led support service and survival among people living with HIV over a 15-year follow-up period and in a country in Asia based on a propensity score–matched analysis.
Our study has several important limitations. The nonrandomized retrospective nature of our analysis prevents us from determining whether peer-led community-based support caused the observed differences in HIV treatment outcomes and survival between the exposure and control groups. Confounding factors may be responsible for some or all of our observed associations. For example, it is possible people living with HIV who were experiencing a mental health crisis or socioeconomic instability were both systematically more likely to have poor HIV treatment outcomes and less likely to remain connected to support services at Rainbow Family for at least 6 months. We used PSM to match individuals in the exposure and control groups to control for many common confounders that are known to influence HIV treatment outcomes; however, the possibility of unmeasured confounders influencing our results remains. Of note, by limiting our analytical sample to the 430 people living with HIV who received peer-led community-based support and 430 of matched controls, the representativeness of our sample may have been impacted, and people living with HIV included in this analysis may not be representative of people living with HIV in China more broadly. Therefore, the generalizability of our results must be interpreted with caution. In addition, although Rainbow Family was the only CBO registered with the local government to provide community-based support services to people living with HIV in Wuxi between 2006 and 2021, it is possible that other local CBOs or nongovernmental organizations were providing support services to some of the persons included in our analysis that were unknown to the local government or these authors, resulting in misclassification bias.
This study adds additional evidence supporting the use of peer-led community-based HIV initiatives and peer support interventions in LMICs, demonstrating that these programs are likely impactful in resource-limited settings beyond sub-Saharan Africa. The SMART framework used to guide the multicomponent HIV support services provided by Rainbow Family may be a model for similar services in other LMICs, particularly in other parts of China and East Asia where comprehensive peer-led support for people living with HIV remains less common. Further studies conducted across diverse settings are needed to confirm the effect and cost-effectiveness of such interventions.
AIDS-related mortality
antiretroviral therapy
community-based organization
center for disease control and prevention
community health worker
Chinese National HIV/AIDS Comprehensive Information Management System
low- to middle-income country
non–AIDS-related mortality
propensity score matching
person-years
social, medical, and mental antiretroviral therapy support
World Health Organization
This study was supported by grants of the Programme of Science and Technology Development Plan of Wuxi Municipal Science and Technology Bureau (grant Y20222006), Top Talent Support Program for Young and Middle-aged People of Wuxi Municipal Health Commission (grant BJ2020099), the Natural Science Foundation of China Excellent Young Scientists Fund (grant 82022064), Natural Science Foundation of China International and Regional Research Collaboration Project (grant 72061137001), the Sanming Project of Medicine in Shenzhen (grant SZSM201811071), the High Level Project of Medicine in Longhua, Shenzhen (grant HLPM201907020105), the Shenzhen Science and Technology Innovation Commission Basic Research Program (grant JCYJ20190807155409373), Special Support Plan for High-Level Talents of Guangdong Province (grant 2019TQ05Y230), and the Fundamental Research Funds for the Central Universities (grant 58000-31620005). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
XM and HZ conceived the study. XM, HY, WM, and HZ designed the study protocol and analysis plan. XM, HY, TF, and HZ wrote the manuscript. JG provided consultation on data analysis. WM, JG, and TF edited the manuscript and assisted with the interpretation of results. ZL critically reviewed the manuscript. XM is the cocorresponding author. All authors critically reviewed and substantively revised the manuscript. All authors have approved the final version of the manuscript for publication.
None declared.