Evidence map›Paper›PMID 38467129›Full record

ReviewThe Lancet. Microbe2024

The global distribution and the risk prediction of relapsing fever group Borrelia: a data review with modelling analysis.

Tian Tang, Ying Zhu, Yuan-Yuan Zhang, Jin-Jin Chen, Jian-Bo Tian, Qiang Xu, Bao-Gui Jiang, Guo-Lin Wang, Nick Golding, Max L Mehlman and 4 more

Abstract readReview
In one paragraph

Review in The Lancet. Microbe, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Mapping the Global Distribution ofTransboundary and emerging diseases · 2025
    Pooled it
  2. Review
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Analytical comparison of 11 CE-IVD marked real-time PCR assays for Borrelia burgdorferi sensu lato detection.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2025
    Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Review
  16. Article
  17. Prevalence of Lyme Disease and Relapsing FeverPathogens (Basel, Switzerland) · 2024
    Review
  18. Systematic investigation of theOne health (Amsterdam, Netherlands) · 2024
    Article
  19. 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

14 authors.

Tian TangState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Ying ZhuDepartment of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China.
Yuan-Yuan ZhangState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Jin-Jin ChenState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Jian-Bo TianDepartment of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China.
Qiang XuState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Bao-Gui JiangState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Guo-Lin WangState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Nick GoldingTelethon Kids Institute, Nedlands, WA, Australia; School of Population Health, Curtin University, Bentley, WA, Australia; Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia.
Max L MehlmanDepartment of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Chen-Long LvState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Simon I HayDepartment of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Li-Qun FangState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China. Electronic address: fang_lq@163.com.
Wei LiuState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China; Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China. Electronic address: liuwei@bmi.ac.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe recent discovery of emerging relapsing fever group Borrelia (RFGB) species, such as Borrelia miyamotoi, poses a growing threat to public health. However, the global distribution and associated risk burden of these species remain uncertain. We aimed to map the diversity, distribution, and potential infection risk of RFGB.

methodsWe searched PubMed, Web of Science, GenBank, CNKI, and eLibrary from Jan 1, 1874, to Dec 31, 2022, for published articles without language restriction to extract distribution data for RFGB detection in vectors, animals, and humans, and clinical information about human patients. Only articles documenting RFGB infection events were included in this study, and data for RFGB detection in vectors, animals, or humans were composed into a dataset. We used three machine learning algorithms (boosted regression trees, random forest, and least absolute shrinkage and selection operator logistic regression) to assess the environmental, ecoclimatic, biological, and socioeconomic factors associated with the occurrence of four major RFGB species: Borrelia miyamotoi, Borrelia lonestari, Borrelia crocidurae, and Borrelia hermsii; and mapped their worldwide risk level.

findingsWe retrieved 13 959 unique studies, among which 697 met the selection criteria and were used for data extraction. 29 RFGB species have been recorded worldwide, of which 27 have been identified from 63 tick species, 12 from 61 wild animals, and ten from domestic animals. 16 RFGB species caused human infection, with a cumulative count of 26 583 cases reported from Jan 1, 1874, to Dec 31, 2022. Borrelia recurrentis (17 084 cases) and Borrelia persica (2045 cases) accounted for the highest proportion of human infection. B miyamotoi showed the widest distribution among all RFGB, with a predicted environmentally suitable area of 6·92 million km

interpretationThe predicted high-risk regions are considerably larger than in previous reports. Identification, surveillance, and diagnosis of RFGB infections should be prioritised in high-risk areas, especially within low-income regions.

fundingNational Key Research and Development Program of China.

Indexed as

BorreliaRelapsing FeverAnimalsHumans

Identifiers

PMID38467129
PMCPMC12513746

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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.