Evidence map›Paper›PMID 42180661›Full record

ArticleChina CDC weekly2026

A Review of Epidemiological Modeling Studies on Monkeypox.

Jiahui Li, Qixuan Luo, Emiliano Beltran, Qiuping Chen, Sandra Perez, Roger Frutos, Yanhua Su, Ziyan Liu, Jia Rui, Tianmu Chen and 2 more

Abstract read
In one paragraph

Article in China CDC weekly, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Jiahui Li *State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, Xiamen University, Xiamen City, Fujian Province, China.
Qixuan Luo *National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen City, Fujian Province, China.
Emiliano BeltranGeographic Data Science Lab (GDSL), University of Liverpool, Liverpool, Merseyside, United Kingdom.
Qiuping ChenState Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, Xiamen University, Xiamen City, Fujian Province, China.
Sandra PerezUniversity Nice Côte d'Azur, Nice, France.
Roger FrutosState Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, Xiamen University, Xiamen City, Fujian Province, China.
Yanhua SuState Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, Xiamen University, Xiamen City, Fujian Province, China.
Ziyan LiuHunan Provincial Center for Disease Control and Prevention, Changsha City, Hunan Province, China.
Jia RuiAix-Marseille University, IHU Méditerranée-Infection, Marseille, France.
Tianmu ChenState Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, Xiamen University, Xiamen City, Fujian Province, China.
Kaiwei LuoHunan Provincial Center for Disease Control and Prevention, Changsha City, Hunan Province, China.
Zeyu ZhaoState Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, Xiamen University, Xiamen City, Fujian Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Between 2022 and 2025, nearly 130,000 confirmed monkeypox (mpox) cases, including over 280 deaths, were reported to the World Health Organization (WHO) from 130 countries and territories, prompting the WHO to declare it a public health emergency of international concern on two occasions. Hence, to enable a scientific approach to prevention and control, transmission dynamics through mathematical modeling must be elucidated. Through a comprehensive literature review on the modeling of mpox transmission dynamics, this study indicates that existing research primarily extends the susceptible-infectious-recovered (SIR) modeling framework and largely focuses on the 2022 global outbreak. The analysis revealed significant variations in mpox virulence, particularly dependent on the subtypes, and variations according to the descending order of clades: Ib>Ia>IIa>IIb. Interpersonal transmission capacity was notably higher for clade II than for clade I, highlighting geographical disparities, with the highest transmission capacity in the Americas, moderate in Europe and Oceania, and the lowest in Asia. In contrast, Africa maintained consistently low but non-declining transmission levels. Furthermore, the study confirmed significant co-infection patterns between mpox and sexually transmitted diseases, such as Human Immunodeficiency Virus (HIV) and syphilis, along with evidence of synergistic transmission interactions among multiple pathogens. This study provides crucial modeling evidence for mpox regulation. By quantifying high-risk populations, evaluating intervention effectiveness, and identifying the risks associated with subtypes and geographic areas, this study offers a comprehensive reference for understanding the interface between model complexity and practical application. These advancements have enhanced the strategic focus and precision of public health responses during outbreaks.

Indexed as

model parameterizationmpoxtransmission dynamics modelingtransmission potential

Identifiers

PMID42180661
PMCPMC13191295

What OpenQuestion holds

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Registered trials

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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.