The association between long-term particulate matter (PM) exposure and all-cause mortality has been well-documented. However, evidence is still limited from high-exposed cohorts, especially for PM₁ which is smaller while more toxic than other commonly investigated particles. We aimed to examine the potential casual links of long-term PMs exposure with all-cause mortality in high-exposed areas. A total of 580,757 participants in southern China were enrolled during 2009-2015 and followed up to 2020. The annual average concentration of PM₁, PM_2.5, and PM₁₀ at 1 km² spatial resolution was assessed for each residential address through validated spatiotemporal models. We used marginal structural Cox models to estimate the PM-mortality associations which were further stratified by sociodemographic, lifestyle factors and general exposure levels. 37,578 deaths were totally identified during averagely 8.0 years of follow-up. Increased exposure to all 3 PM size fractions were significantly associated with increased risk of all-cause mortality, with hazard ratios (HRs) of 1.042 (95 % confidence interval (CI): 1.037-1.046), 1.031 (95 % CI: 1.028-1.033), and 1.029 (95 % CI: 1.027-1.031) per 1 μg/m³ increase in PM₁, PM_2.5, and PM₁₀ concentrations, respectively. We observed greater effect estimates among the elderly (age ≥ 65 years), unmarried participants, and those with low education attainment. Additionally, the effect of PM₁, PM_2.5, and PM₁₀ tend to be higher in the low-exposure group than in the general population. We provided comprehensive evidence for the potential causal links betweenlong-term PM exposureand all-cause mortality, and suggested stronger links for PM₁compared to large particles and among certain vulnerable subgroups.

This study investigated the genotype-specific dynamics of molecular HIV clusters (MHCs) in Guangzhou, China, aiming to enhance HIV control. HIV pol sequences from people with HIV (PWH) in Guangzhou (2008-2020) were obtained for genotyping and molecular network creation. MHCs were identified and categorized into three types: emerging, growing, or stable. Clustering rates, proportions of cluster types, and members within each type were calculated and their trends were assessed using joinpoint regression. Among 8395 PWH, the most prevalent HIV-1 genotypes were CRF07_BC (39.7%) and CRF01_AE (32.6%). The genotype composition has been stable since 2012 (Ps > 0.05). The overall clustering rate was 43.3%, with significant variations across genotypes (P < 0.001), indicating genotype-specific transmission fitness. Significant declines in overall and genotype-specific clustering rates toward the end of 2020 (Ps < 0.05), potentially offer support for HIV control efforts in reducing local infections. The continuously increasing proportions of stable clusters and the gradually decreasing proportions of emerging and growing clusters (either Ps < 0.05 or Ps > 0.05) suggest a trend toward stable molecular network structure. However, growing clusters exhibited CRF55_01B, CRF07_BC, and CRF59_01B dominance that indicate their priority for interventions. The evolving MHCs highlight the genotype-specific cluster dynamics, providing fresh insights for enhanced prevention and control strategies.

Background: High-resolution and longitudinal HIV molecular surveillance can inform the evolving hotspots to tailor regionally focused control strategies. Methods: HIV-1 pol sequences of three predominant genotypes (CRF01_AE, CRF07_BC, and CRF55_01B) were collected for molecular network reconstruction from people living with HIV (PLWH) in Guangzhou (2018–2020). They were categorized by geographical residences into central, suburban, and outer suburban areas. Clustering rates, assortativity coefficients, and intensity matrices were employed to assess transmission dynamics, geographic mixing patterns, and intra- and inter-area transmission, respectively. Results: Of the 2469 PLWH, 55.5% resided in the central area. Clustering rates showed no significant differences across areas (44.5%, 40.6% vs. 45.7%; p = 0.184). However, the transmission hotspots for CRF01_AE and CRF55_01B shifted to the outer suburban area. PLWH tended to form links within their local area (assortativity coefficient = 0.227, p < 0.001), particularly for CRF01_AE (0.512, p < 0.001; intra-area intensity = 69.2%). The central area exhibited the highest but decreasing intra-area transmission (74.5% to 30.2%), while intra- and inter-area transmission involving the outer suburban area increased (23.1% to 38.2%). Conclusions: Despite most PLWH residing in the central area, the outer suburban area emerged as the hotspot, requiring interventions towards both intra- and inter-area transmission.