ArticleBMC public health2026
Mortality trends and epidemiological characteristics among people living with HIV in Huangshi, China: a time-series analysis (2004-2024).
Article in BMC public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
objectiveTo analyze the epidemiological characteristics and dynamic trends of people living with HIV (PLWH) in Huangshi between 2004 and 2024, thereby providing a scientific basis for the optimization of regional HIV prevention and control strategies.
methodsSurveillance data of PLWH from Huangshi during the period 2004-2024 were collected. Descriptive epidemiology methods were employed to examine the temporal distribution, demographic features (including age, sex, marital status), transmission routes, clinical manifestations, and mortality patterns. A Cochrane-Armitage trend test was utilized to assess changes in gender composition, while SPSS 27 was leveraged to establish a time-series model based on exponential smoothing techniques to forecast future mortality counts.
resultsThe number of PLWH in Huangshi exhibited a marked increase post-2009, peaking in 2015, followed by a significant decline from 2020 onward. Key structural shifts were observed: (1) among reported cases, the 51-80 age group accounted for the highest proportion (representing the age composition within the infected population, rather than age-specific incidence in the general population). Male cases showed a pronounced upward trend, whereas female cases demonstrated a gradual decrease. (2) Sexual transmission constituted the predominant mode, accounting for 95.02% of cases, with heterosexual transmission highly concentrated among males aged 51-70 years. (3) The primary opportunistic infections were persistent fever and Pneumocystis pneumonia. Post-2013, mortality rates escalated significantly, yet over one-third of deaths were attributed to causes unrelated to HIV, with cardiovascular diseases and malignancies ranking as major contributors, reflecting a shift toward chronic comorbidity management. (4) Time-series modeling predicted a gradual decline in the estimated number of HIV-related deaths for the years 2025-2028.
conclusionHIV transmission in Huangshi has evolved into a stage characterized by sexual transmission as the primary route, with a notable increase in the disease burden among older adults and males. The focus is now transitioning from HIV-related mortality to the management of chronic comorbidities. Future HIV prevention efforts in the city should adopt comprehensive strategies, including targeted interventions and enhanced surveillance for males-particularly older males-strengthened treatment and prevention measures, and integrated approaches to chronic disease management to address the evolving epidemiological landscape.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.