Evidence map›Paper›PMID 39974765›Full record

ArticleChina CDC weekly2025

Comparative Analysis of Epidemiological and Clinical Characteristics Between Mpox Cases with and Without HIV - China, 2023.

Yichen Jin, Qianqian Qin, Chao Li, Houlin Tang, Dapeng Zhang, Wenqing Bai, Fangfang Chen, Peilong Li, Pairidai Duolaitiniyazi, Ruiqi Ren and 5 more

Abstract read
In one paragraph

Article in China CDC weekly, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
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

15 authors.

Yichen JinNational Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Qianqian QinNational Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Chao LiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Houlin TangNational Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Dapeng ZhangNational Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Wenqing BaiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Fangfang ChenNational Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Peilong LiNational Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Pairidai DuolaitiniyaziChinese Center for Disease Control and Prevention, Beijing, China.
Ruiqi RenNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Dan LiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Nijuan XiangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Guoqing ShiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Fan LyuNational Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Qun LiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to analyze the epidemiological characteristics and clinical symptoms of mpox cases with and without human immunodeficiency virus (HIV) reported in China in 2023, providing evidence for coordinated prevention and control strategies for both infections. Method: All confirmed mpox cases reported in 2023 were extracted from China's Information System for Disease Control and Prevention. Data were collected from the surveillance system and epidemiological investigations. Statistical analyses were performed using SPSS 24.0, with group comparisons conducted using Results: Among 1,712 confirmed mpox cases in China during 2023, 802 (46.8%) were people with human immunodeficiency virus (PWH). Of the 1,702 male cases, 97.3% of PWH and 91.1% of those without HIV self-identified as men who have sex with men (MSM). Age distribution showed 79.4% of PWH and 87.6% of those without HIV were under 40 years old, while 64.2% of PWH and 71.3% of those without HIV were reported from eastern regions. Cardinal symptoms at diagnosis occurred at similar rates between those with and without HIV, including rash (90.9% Conclusion: Male mpox cases with HIV was more likely to be MSM, older, and reported from central and western regions compared to those without HIV. No significant differences were observed in cardinal symptom occurrence between groups. These findings emphasize the importance of implementing integrated prevention strategies targeting both HIV and mpox, particularly among key populations.

Indexed as

clinical symptomsepidemiological characteristicshuman immunodeficiency virus (HIV)mpox

Identifiers

PMID39974765
PMCPMC11832442

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

None linked

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.