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Record W7117358089 · doi:10.61440/jidt.2025.v3.47

A Global Review of Invasive Haemophilus Influenzae Diseases from 2000-2023: A Systematic Review of Current Status, Challenges, and Future Perspectives

2025· article· W7117358089 on OpenAlexaboutno aff
Abas Mahammed, Destaw Damtie, Tirusew Sema

Bibliographic record

Venuenot available
Typearticle
Language
FieldImmunology and Microbiology
TopicBacterial Infections and Vaccines
Canadian institutionsnot available
Fundersnot available
KeywordsHaemophilus influenzaeDiseaseIncidence (geometry)Transmission (telecommunications)Review articleSystematic reviewPathogenBacterial disease

Abstract

fetched live from OpenAlex

Background: Haemophilus influenzae is a causal agent of invasive bacterial diseases that affect both children and adults. H.influenzae is a pleomorphic gram-negative coccobacillus and it is a common commensal of the upper respiratory tract. It is a human-only pathogen that can cause severe invasive diseases. These bacterial infections can range from mild, such as ear infections, to severe, such as bloodstream infections. The infections typically affect children younger than 5 years old and old age person older than 65 years. They also affect people who are immunocompromised, such as those with certain medical conditions. The highest incidence rates of invasive H.influenzae disease have recently been discovered in various nations, including North America, Canada, and parts of Europe. To monitor the evolving nature of invasive H.influenzae disease critically reviewed data is required to capture the true status of invasiveness of the H. influenzae disease. Developing new vaccines against H.influenzae is a potential solution to protect some vulnerable populations against the invasive disease due to this bacterial species. Materials & Methods: Since there were not sufficient articles before 2000, we restricted the publication period and examined invasive H. influenzae illness from March 1, 2000 to March 1, 2023. This systematic review was conducted using English databases, PubMed and Google Scholar, to fully extract all pertinent articles published worldwide Findings: A total of 545 articles were recognized in electronic databases, among them eleven articles meeting the inclusion criteria were reviewed in this research. Nearly every country in the European WHO Region included the Hib vaccine in their suggested NIPs. Between 2007 and 2014, 12 European nations reported 10, 624 cases of invasive H. influenzae infection. Conclusion: this review suggests that an extensive surveillance system that collects information on serotype, genotype, immunological characterization, and vaccination status is required to follow the trends described in this Review and eradicate H. influenzae illnesses and their global impacts. This review article thoroughly investigates recent and up-to-date biomedical science perspective development, innovation, findings, publications and current areas of scientific interest and gap including pathogenicity, diagnosis, multidrug-resistance, Molecular characterization and genetic evolution, epidemiology and immunological characteristics of H. influenzae, including specific current issues that are affecting the research and development of vaccines to treat H.influenzae non-serotype b diseases and providing insight into how these problems may be overcome.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.025
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.022
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.006
Bibliometrics0.0250.028
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.294
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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