Evidence map›Paper›PMID 39152514›Full record

ArticleInfectious diseases of poverty2024

Epidemiological features and temporal trends of the co-infection between HIV and tuberculosis, 1990-2021: findings from the Global Burden of Disease Study 2021.

Shun-Xian Zhang, Ji-Chun Wang, Jian Yang, Shan Lv, Lei Duan, Yan Lu, Li-Guang Tian, Mu-Xin Chen, Qin Liu, Fan-Na Wei and 10 more

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Article in Infectious diseases of poverty, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 2 pooled it
–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

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.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

20 authors.

Shun-Xian Zhang *Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China.
Ji-Chun Wang *Department of Science and Technology, Chinese Center for Disease Control and Prevention, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Beijing, 102206, China.
Jian YangDepartment of Science and Technology, Chinese Center for Disease Control and Prevention, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Beijing, 102206, China.
Shan LvNational Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases; National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Shanghai, 200025, China.
Lei DuanNational Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases; National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Shanghai, 200025, China.
Yan LuNational Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases; National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Shanghai, 200025, China.
Li-Guang TianNational Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases; National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Shanghai, 200025, China.
Mu-Xin ChenNational Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases; National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Shanghai, 200025, China.
Qin LiuNational Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases; National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Shanghai, 200025, China.
Fan-Na WeiNational Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases; National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Shanghai, 200025, China.
Xin-Yu FengSchool of Global Health, Chinese Center for Tropical Diseases Research-Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Guo-Bing YangGansu Provincial Center for Disease Control and Prevention, Lanzhou, 730000, China.
Yong-Jun LiGansu Provincial Center for Disease Control and Prevention, Lanzhou, 730000, China.
Yu WangLonghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China.
Xiao-Jie HuLonghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China.
Ming YangLonghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China.
Zhen-Hui LuLonghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China.
Shao-Yan ZhangLonghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China.
Shi-Zhu LiNational Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases; National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Shanghai, 200025, China. lisz@nipd.chinacdc.cn.
Jin-Xin ZhengSchool of Global Health, Chinese Center for Tropical Diseases Research-Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China. jamesjin63@163.com.ORCID http://orcid.org/0000-0003-1476-1903

Funding

Medical Innovation Research Special Project of the Shanghai 2021 21Y11922500
6 · The paper itself

Abstract

backgroundThe co-infection of human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS) and tuberculosis (TB) poses a significant clinical challenge and is a major global public health issue. This study aims to elucidate the disease burden of HIV-TB co-infection in global, regions and countries, providing critical information for policy decisions to curb the HIV-TB epidemic.

methodsThe ecological time-series study used data from the Global Burden of Disease (GBD) Study 2021. The data encompass the numbers of incidence, prevalence, mortality, and disability-adjusted life year (DALY), as well as age-standardized incidence rate (ASIR), prevalence rate (ASPR), mortality rate (ASMR), and DALY rate for HIV-infected drug-susceptible tuberculosis (HIV-DS-TB), HIV-infected multidrug-resistant tuberculosis (HIV-MDR-TB), and HIV-infected extensively drug-resistant tuberculosis (HIV-XDR-TB) from 1990 to 2021. from 1990 to 2021. The estimated annual percentage change (EAPC) of rates, with 95% confidence intervals (CIs), was calculated.

resultsIn 2021, the global ASIR for HIV-DS-TB was 11.59 per 100,000 population (95% UI: 0.37-13.05 per 100,000 population), 0.55 per 100,000 population (95% UI: 0.38-0.81 per 100,000 population), for HIV-MDR-TB, and 0.02 per 100,000 population (95% UI: 0.01-0.03 per 100,000 population) for HIV-XDR-TB. The EAPC for the ASIR of HIV-MDR-TB and HIV-XDR-TB from 1990 to 2021 were 4.71 (95% CI: 1.92-7.59) and 13.63 (95% CI: 9.44-18.01), respectively. The global ASMR for HIV-DS-TB was 2.22 per 100,000 population (95% UI: 1.73-2.74 per 100,000 population), 0.21 per 100,000 population (95% UI: 0.09-0.39 per 100,000 population) for HIV-MDR-TB, and 0.01 per 100,000 population (95% UI: 0.00-0.03 per 100,000 population) for HIV-XDR-TB in 2021. The EAPC for the ASMR of HIV-MDR-TB and HIV-XDR-TB from 1990 to 2021 were 4.78 (95% CI: 1.32-8.32) and 10.00 (95% CI: 6.09-14.05), respectively.

conclusionsThe findings indicate that enhancing diagnostic and treatment strategies, strengthening healthcare infrastructure, increasing access to quality medical care, and improving public health education are essential to combat HIV-TB co-infection.

Indexed as

CoinfectionGlobal Burden of DiseaseHIV InfectionsTuberculosisAdultFemaleGlobal HealthHumansIncidenceMalePrevalenceTuberculosis, Multidrug-ResistantCo-infectionEpidemiologyGlobal burden of disease 2021HIV/AIDSTuberculosis

Identifiers

PMID39152514
PMCPMC11328430

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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.