Special Issue "Diagnosis and Management of Meningococcal Disease"

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Diagnostic Microbiology and Infectious Disease".

Deadline for manuscript submissions: 31 May 2021.

Special Issue Editor

Prof. Dr. Georgina Tzanakaki
E-Mail Website
Guest Editor
National Meningitis Reference Laboratory, Department of Public Health Policy, School of Public Health, University of West Attica, Athens, Greece
Interests: Neisseria meningitidis; Spreptococcus pneumoniae; Haemophilus influenzae; bacterial meningitis; molecular diagnosis; outbreak investigation; laboratory surveillance; Public Health Microbiology, meningococcal and pneumococcal vaccines

Special Issue Information

Dear Colleagues,

Invasive meningococcal disease (IMD) is an acute, severe, and potentially life-threatening infection characterized by meningitis, sepsis or, less commonly, pneumonia, arthritis, pericarditis, and abdominal disorders. The severity of the disease, combined with its rapid progression and nonspecific syndromes, continues to result in an unacceptable level of childhood morbidity and mortality.

As unpredictable sporadic cases and outbreaks contribute to ongoing changes in epidemiology, improved understanding of disease dissemination is an urgent priority for advancing public health and clinical management.

Genetic approaches such as advances in high-throughput nucleotide sequencing and bioinformatics have been used to define invasive genetic types, search for virulence factors and potential vaccine components and investigate the effects of vaccines on population structure. Internet-accessible servers are being established to support bioinformatics analysis, data management, and data sharing. Strategic WGS implementation is necessary to monitor the molecular epidemiology of meningococcal disease and construct a global view of meningococcal disease epidemiology.

As antibiotics are one of the most important tools used for prophylaxis and treatment of IMD, global antibiotic resistance surveillance is imperative to ensure the continued efficacy of all IMD treatments.

Data from carriage studies could be used to investigate the possible effect of large scale vaccination on the spread of meningococcal variants expressing non-vaccine antigens and to understand the relationship between carrier and disease-causing strains.

Despite the incredible advances, there is still much to do, from diagnosis to patient management. This Special Issue in the journal Diagnostics will focus on articles covering a range of topics including novel diagnostic approaches, utilizing our available diagnostic armamentarium for surveillance, vaccine implementation, antimicrobial sensitivity/resistance patterns, as well as novel treatment and management approaches. It is, therefore, my pleasure to invite submissions of high quality research-based or review papers related to the aforementioned topics to create a timely and highly relevant collection of articles tackling this pertinent public health problem.

Prof. Dr. Georgina Tzanakaki
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • Invasive Meningococcal Disease
  • Molecular epidemiology
  • Molecular diagnosis (including advanced sequencing technology)
  • Clinical diagnosis
  • Clinical management
  • Therapeutic approaches
  • Vaccine prevention strategies
  • MenB protein vaccines
  • Vaccination programs and high risk patient populations
  • Meningococcal modeling in outbreaks and persistence on vaccine protection
  • Emergence of new meningococcal clones
  • Surveillance
  • Mass gatherings
  • preventive measures
  • Evolution of hypervirulent strains
  • N. meningitidis and non-specific syndromes
  • Carriage studies
  • Sero-epidemiology

Published Papers (1 paper)

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Open AccessArticle
Artificial Intelligence in Differential Diagnostics of Meningitis: A Nationwide Study
Diagnostics 2021, 11(4), 602; https://doi.org/10.3390/diagnostics11040602 - 28 Mar 2021
Viewed by 520
Differential diagnosis between bacterial and viral meningitis is crucial. In our study, to differentiate bacterial vs. viral meningitis, three machine learning (ML) algorithms (multiple logistic regression (MLR), random forest (RF), and naïve-Bayes (NB)) were applied for the two age groups (0–14 and >14 [...] Read more.
Differential diagnosis between bacterial and viral meningitis is crucial. In our study, to differentiate bacterial vs. viral meningitis, three machine learning (ML) algorithms (multiple logistic regression (MLR), random forest (RF), and naïve-Bayes (NB)) were applied for the two age groups (0–14 and >14 years) of patients with meningitis by both conventional (culture) and molecular (PCR) methods. Cerebrospinal fluid (CSF) neutrophils, CSF lymphocytes, neutrophil-to-lymphocyte ratio (NLR), blood albumin, blood C-reactive protein (CRP), glucose, blood soluble urokinase-type plasminogen activator receptor (suPAR), and CSF lymphocytes-to-blood CRP ratio (LCR) were used as predictors for the ML algorithms. The performance of the ML algorithms was evaluated through a cross-validation procedure, and optimal predictions of the type of meningitis were above 95% for viral and 78% for bacterial meningitis. Overall, MLR and RF yielded the best performance when using CSF neutrophils, CSF lymphocytes, NLR, albumin, glucose, gender, and CRP. Also, our results reconfirm the high diagnostic accuracy of NLR in the differential diagnosis between bacterial and viral meningitis. Full article
(This article belongs to the Special Issue Diagnosis and Management of Meningococcal Disease)
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