Evidence map›Paper›PMID 35397554›Full record

ArticleInfectious diseases of poverty2022

Mapping the distributions of blood-sucking mites and mite-borne agents in China: a modeling study.

Tao Wang, Fanfei Meng, Tianle Che, Jinjin Chen, Haiyang Zhang, Yang Ji, Zhengwei Fan, Guoping Zhao, Wenhui Zhang, Baogui Jiang and 8 more

Open access · goldAbstract read
In one paragraph

Article in Infectious diseases of poverty, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.3field-weighted citation impact, top 19% of its field
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

12 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Article
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  6. Article
  7. Challenges ofInsects · 2025
    Review
  8. Predicting the potential distribution areas ofFrontiers in public health · 2025
    Article
  9. Article
  10. Review
  11. Article
  12. 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

18 authors at 4 institutions in 3 countries.

Tao Wang *State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China.
Fanfei Meng *State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China.
Tianle CheState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China.
Jinjin ChenState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China.
Haiyang ZhangState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China.
Yang JiState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China.
Zhengwei FanState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China.
Guoping ZhaoState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China.
Wenhui ZhangState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China.
Baogui JiangState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China.
Qiang XuState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China.
Chenlong LvState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China.
Taoxing ShiState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China.
Shiman RuanJinan Center for Disease Control and Prevention, Jinan, 250021, People's Republic of China.
Lanzheng LiuJinan Center for Disease Control and Prevention, Jinan, 250021, People's Republic of China.
Wei LiuState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China. liuwei@bmi.ac.cn.
Yang YangDepartment of Biostatistics, College of Public Health and Health Professions and Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA. yangyang@ufl.edu.
Liqun FangState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China. fang_lq@163.com.ORCID http://orcid.org/0000-0002-4981-1483
Institute of Microbiology · CNInstitute of Microbiology · BYShandong Center for Disease Control and Prevention · CNUniversity of Florida Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEmerging mite-borne pathogens and associated disease burdens in recent decades are raising serious public health concerns, yet their distributions and ecology remain under-investigated. We aim to describe the geographical distributions of blood-sucking mites and mite-borne agents and to assess their ecological niches in China.

methodsWe mapped 549 species of blood-sucking mites belonging to 100 genera at the county level and eight mite-associated agents detected from 36 species of blood-sucking mites in China during 1978-2020. Impacts of climatic and environmental factors on the ecology of 21 predominant vector mites and a leading pathogen, Orientia tsutsugamushi, were assessed using boosted regression tree (BRT) models, and model-predicted risks were mapped. We also estimated the model-predicted number, area and population size of affected counties for each of the 21 mite species in China.

resultsLaelaps echidninus is the leading mite species that potentially affects 744 million people, followed by La. jettmari (517 million) and Eulaelaps stabularis (452 million). Leptotrombidium scutellare is the mite species harboring the highest variety of mite-borne agents including four Rickettsia species and two viruses, followed by Eu. stabularis (2 agents), L. palpale (2) and La. echidninus (2). The top two agents that parasitize the largest number of mite species are O. tsutsugamushi (28 species) and hantavirus (8). Mammalian richness, annual mean temperature and precipitation of the driest quarter jointly determine the ecology of the mites, forming four clusters of major mite species with distinct geographic distributions. High-risk areas of O. tsutsugamushi are mainly distributed in southern and eastern coastal provinces where 71.5 million people live.

conclusionsEcological niches of major mite species and mite-borne pathogens are much more extensive than what have been observed, necessitating expansion of current filed surveillance.

Indexed as

Orientia tsutsugamushiRickettsiaScrub TyphusTrombiculidaeAnimalsChinaHumansMammalsChinaDistributionMiteMite-borne diseaseMite-borne pathogenRisk determinant

Identifiers

PMID35397554
PMCPMC8994071
OpenAlexW4223546061

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.