Evidence map›Paper›PMID 39720120›Full record

ArticleFrontiers in reproductive health2024

Global, regional, and national burden of HIV and tuberculosis and predictions by Bayesian age-period-cohort analysis: a systematic analysis for the global burden of disease study 2021.

Xuebin Tian, Chong Wang, Zhihao Hao, Jingjing Chen, Nanping Wu

Abstract read
In one paragraph

Article in Frontiers in reproductive health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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  7. Magnitude and trends ofThe Pan African medical journal · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Xuebin TianCell Biology Research Platform, Jinan Microecological Biomedicine Shandong Laboratory, Jinan, Shandong, China.
Chong WangClinical Laboratory, Qingdao Hospital, University of Health and Rehabilitation Sciences (Qingdao Municipal Hospital), Qingdao, China.
Zhihao HaoDepartment of Clinical Laboratory, Shandong Provincial Third Hospital, Shandong University, Jinan, Shandong, China.
Jingjing ChenSchool of Public Administration, Guangxi University, Nanning, Guangxi, China.
Nanping WuCell Biology Research Platform, Jinan Microecological Biomedicine Shandong Laboratory, Jinan, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To assess sex, age, regional differences, and the changing trend in human immunodeficiency virus and tuberculosis (HIV-TB) in different regions from 1990 to 2021, and project future trends. Methods: Global Burden of Disease Study 2021 data were analyzed to assess HIV-TB incidence, death, prevalence, and DALY rates from 1990 to 2021, including different types of TB co-infections (drug-susceptible, multidrug-resistant, and extensively drug-resistant). Bayesian age-period-cohort models were used to forecast age-standardized DALY rates through 2035. Results: In 2021, there were approximately 1.76 million HIV-TB infections and 200,895 deaths globally. The highest burden of HIV-DS-TB and HIV-MDR-TB was found in Southern Sub-Saharan Africa, while HIV-XDR-TB was most prevalent in Eastern Europe. The co-infection burden was highest among individuals aged 30-49. Key risk factors were unsafe sex, drug use, and intimate partner violence, with regional variations. The global burden of HIV-TB remains high, and age-standardized DALY rates are expected to increase in the coming years, especially in regions with low socio-demographic indices (SDI). Conclusion: The burden of HIV-TB co-infection correlates with the socio-demographic index (SDI): countries with a low SDI have a higher burden. Therefore, clinical diagnosis and treatment in such areas are more challenging and may warrant more attention. High death rates underscore the importance of early management.

Indexed as

age-standardized rateBayesian age-period-cohortdisability-adjusted life yearsdisease burdenhuman immunodeficiency virus and tuberculosis

Identifiers

PMID39720120
PMCPMC11666487

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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 OpenQuestion graph.