Evidence map›Paper›PMID 36684875›Full record

ArticleFrontiers in public health2022

Predicting global potential distribution of

Hongyun Li, Ying Liang, Li Dong, Cancan Li, Lu Zhang, Bin Wang, Delong Ma, Qunzheng Mu, Jun Wang, Haifeng Hou and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Projecting the potential distribution ofFrontiers in public health · 2025
    Article
  4. Predicting the potential distribution areas ofFrontiers in public health · 2025
    Article
  5. Article
  6. Prediction of Suitable Habitat Distribution ofJournal of fungi (Basel, Switzerland) · 2023
    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

11 authors.

Hongyun LiSchool of Public Health, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Ying LiangState Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Li DongState Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Cancan LiBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
Lu ZhangState Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Bin WangState Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Delong MaDepartment of Infectious Diseases, Shizhong Center for Disease Control and Prevention, Jinan, China.
Qunzheng MuState Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Jun WangState Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Haifeng HouSchool of Public Health and The Second Affiliated Hospital of Shandong First Medical University, Taian, China.
Qiyong LiuState Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Methods: Maximum entropy models (MaxEnt) were utilized to predict the distributions of these two fleas and their trends into the future. The main environmental factors influencing the distribution of these two fleas were analyzed. A risk assessment system was constructed to calculate the invasion risk values of the species. Results: Temperature has a significant effect on the distribution of the potentially suitable areas for Conclusion: In order to achieve early detection, early interception, and early management, China should perfect its monitoring infrastructure and develop scientific prevention and control strategies to prevent the invasion of foreign flea vectors.

Indexed as

PlagueSiphonapteraAnimalsChinaClimate ChangeRisk Assessmentclimate changeglobal distributionplague vector fleaspotential suitable areasrisk assessment

Identifiers

PMID36684875
PMCPMC9850084

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.