Background
Human immunodeficiency virus (HIV) infection is a global health concern. Globally, the number of people living with HIV was 37.7 million, with 1.5 million people newly infected with HIV, in 2020 [
1]. This suggests continued HIV transmission despite a reduction in its incidence. In China, the acquired immunodeficiency syndrome (AIDS) epidemic has been categorized into three phases: sporadic cases (1985–1988), endemic outbreaks (1989–1994), and the expansion phase (1995–present day) [
2]. In October 2020, 1.045 million people in China were living with HIV/AIDS (prevalence: 0.075%) [
3]. Driven by its policy, China has played a key role in the global fight against HIV/AIDS [
4]. Nonetheless, the country faces complex challenges endeavoring to control the disease in both rural and urban areas [
5]. Guangxi ranks third in terms of HIV infection cases in China, with the local population infection rate of 0.13% [
6]. Nanning is ranked as the top city in Guangxi based on the number of reported surviving cases [
7], with 7068 deaths from 2001 to 2020 [
8]. Concerning the AIDS epidemic, the Guangxi government initiated the first (Phase I) and second (Phase II) rounds of the Guangxi AIDS Conquering Project (GACP) in 2010 and 2015, respectively [
9,
10]. In the GACP, the local government established an AIDS Working Committee as the technical body responsible for oversight in 2010, to implement the responsibility of community leaders in AIDS prevention and treatment and hold those who fail to fulfill their responsibilities accountable. Combining local initiatives with the China Comprehensive AIDS Response (CARES) Programme, the Guangxi government has actively utilized investments in financial and human resources to enhance HIV prevention education, voluntary counseling and testing, sentinel surveillance, behavioral interventions, health care, and antiretroviral therapies (ARTs). However, the effects of GACP have rarely been evaluated or reviewed.
Spatial models help assess prevention efforts [
11], plan resource allocation [
12], infer gaps in service delivery, and understand biases in surveillance data, adapt services, and target interventions [
13]. In sub-Saharan Africa, strategies for eliminating HIV are designed by mapping the geographic dispersion patterns of HIV-infected individuals [
11]. Compared with the individual level, the spatiotemporal level of HIV-related outcomes can potentially provide fresh insights into public health strategies and prevention measures [
14]. Although geographic information systems have been used for several years to monitor infectious diseases, their capacity to target services for regional disease prevention and control strategies is underutilized [
13,
15].
This study aimed to assess the effectiveness of the GACP implemented in Guangxi, China, and provide data in strategy and practice improvements to achieve the UNAIDS 95-95 targets. These targets aim to ensure that, by 2025, 95% of individuals living with HIV are aware of their HIV status, 95% of those who know their HIV-positive status are receiving treatment, and 95% of individuals on HIV treatment have suppressed viral loads. We used a geostatistical framework to reveal the geographic dispersion pattern of HIV-infected individuals at different stages of GACP implementation to determine the effectiveness of GACP implementation.
Discussion
This study evaluated the effectiveness of GACP by mapping the geographic dispersion pattern of HIV prevalence. Since the GACP was initiated, the HIV epidemic has been contained in Nanning, suggesting that the interventions have achieved remarkable results. However, the HIV epidemic has shifted toward diffusion in the surrounding rural counties. Economic development, floating population, and medical care levels may be driving factors for the spatial heterogeneity of AIDS.
Visualization of the habitual residence of HIV-reported cases in Nanning over a 25-year period revealed that the distribution of cases became more geographically scattered. The city center has become a hub for HIV-reported cases with a stable HIV prevalence. However, HIV prevalence in the Hengzhou and Binyang Counties decreased during the second GACP period. Furthermore, the LISA analysis indicated that Hengzhou County withdrew from the high-high clustering region, indicating that the two phases of the GACP played a big role in HIV control in these two counties. Hengzhou County was the hardest-hit area, followed by Binyang County and the urban center where the first HIV-reported case was detected [
8]. During the GACP period, local governments stepped up multisectoral collaborations to expand HIV testing coverage, promote HIV education, and combat sex trafficking based on the CARES policy [
27]. HIV awareness, testing, and treatment coverage have also improved.
Nevertheless, some northwestern administrative regions, including Long’an County, Mashan County, and Shanglin County, have experienced an increasing HIV prevalence during the GACP period. Furthermore, scanning statistics identified five HIV clusters in border counties after 2010. In the second phase of the GACP, tertiary clusters appeared in the Mashan and Shanglin Counties. Our results confirmed that the HIV epidemic in Nanning was not ubiquitous but was an evident geographically distinct cluster, with a disproportionately high number of reported HIV infection cases. Notably, in northwestern suburban counties, HIV/AIDS prevention was only completely implemented after launching the GACP, compared with other areas that implemented the CARES policy before launching the GACP. The number of HIV tests performed has increased annually during the GACP period, which could have played a vital role in increasing the incidence of HIV infection. However, the detection of HIV clusters implies that current interventions may be suboptimal in these districts. HIV clusters were mainly distributed in the northwestern counties of Nanning City, likely reflecting the accumulation of specific spatiotemporal risk factors [
28,
29]. Disease control and prevention departments should pay close attention to epidemic hotspots, focusing on strengthening HIV/AIDS surveillance and prevention in the surrounding rural areas in the northwest.
Subsequently, we tracked the spatiotemporal variation in the reported HIV infection cases in Nanning by identifying centroids and their shifts. The results also showed an evident trend: the centroids of the HIV-reported case area displayed a southeast–northwest direction, specifically in Phase II of the GACP, suggesting that Nanning City might experience a diffusion of HIV outward from cities into rural areas, consistent with other countries and globally [
23,
30]. There are several possible reasons for this shift in spatiotemporal centroids. First, given the historically higher HIV prevalence in the southeast, several HIV prevention and treatment programs launched by the GACP have focused on this region, which has led to HIV epidemic stabilization or even a decline. Second, since the GACP was initiated in 2010, older HIV-infected people have been detected in northwestern rural Nanning. However, effective interventions targeting this population are lacking, resulting in a continuous increase in infection rates [
31]. Third, changes in proximity to urban connectivity may also play a role. Frequent border population movement between northwestern counties and cities with an elevated incidence of AIDS, including Congzuo, Baise, Hechi, and Laibin, may increase the incidence of AIDS [
32,
33].
This study explored the spatial characteristics and factors correlating with HIV transmission. The effects of different macroscopic factors on the AIDS epidemic were more prevalent in northwestern Nanning than in southeastern Nanning, as evidenced by the higher estimated coefficients. First, all regression coefficients of economic development were negative, consistent with previous findings related to the spatial distribution of AIDS and the main socioeconomic driving factors in China [
34,
35]. Low-cost sex trafficking [
27] and poverty [
36,
37] in northwest Nanning have been proven to exacerbate AIDS/HIV infection. Second, our findings confirmed that the floating population positively affected the number of HIV infection cases in Nanning. Previous studies have linked migration and mobile populations to an increased risk of HIV [
28,
38], which may have contributed to the AIDS epidemic in northern Nanning [
11]. Furthermore, lower per capita medical expenditure was associated with higher rates of HIV infection. In contrast, counties in rural areas are significantly more likely to lack access to medical investment [
11,
39], and medically underserved areas may restrict the surveillance capability of spatial epidemiology [
34,
40]. Therefore, health departments should consider adopting effective HIV prevention allocation strategies in rural areas with insufficient economic and health resources.
This study has some limitations. First, we cannot claim causality between economic and demographic variables or other social phenomena and HIV transmission. Second, the multifaceted nature of factors influencing reported HIV/AIDS cases, such as potential underreporting, may have influenced hotspot identification in our study. This could potentially limit a comprehensive and accurate assessment of the true effectiveness of efforts in preventing and controlling HIV. However, the existing data did not allow us to adjust for these factors. Third, some critical ecological variables were not included in our geospatial models, which may have affected the validity of the prediction maps. Despite these limitations, the findings of this study highlight the advantages of developing geospatial technologies to improve disease mapping and surveillance. Importantly, we identified trends in the spatial distribution of HIV epidemics following the implementation of local prevention strategies. This finding will benefit future targeted HIV prevention and control efforts in Guangxi Province.
Conclusions
The HIV epidemic has been effectively controlled, particularly in areas with higher HIV prevalence, suggesting that the GACP has achieved remarkable results. However, with the implementation of the GACP, HIV diffusion shifted to the surrounding rural counties. This would exacerbate the significant urban–rural disparities in medical health care. Thus, in the third stage of the GACP, policymakers should pay more attention to the upscaling of age-specific HIV education and testing to initiate early ART in rural areas. Additionally, more resources and appropriate interventions should be committed to subpopulations and regions that are underserved and require health facilities and care personnel in the country.
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