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Call for papers - Application of advanced statistical methods in infectious diseases

Guest Editors

Zhongjie Shi, MD, PhD, Wayne State University, USA
Sergei S. Simakov, PhD, DSc, Moscow Institute of Physics and Technology, Russia

Submission Status: Open   |   Submission Deadline: 30 August 2024


BMC Infectious Diseases is calling for submissions to our Collection on Application of advanced statistical methods in infectious diseases.  This collection aims to highlight the innovative use of statistical methods beyond traditional approaches, thereby advancing our understanding of infectious diseases and improving public health interventions. We welcome research submissions addressing but not limited to: advanced statistical methods in infectious diseases, including bioinformatics analysis, machine learning, Bayesian methods, network analysis, spatial and spatio-temporal methods, longitudinal data analysis, multivariate techniques, data integration, meta-analysis, statistical modeling of vaccine efficacy and emerging infectious diseases.

Meet the Guest Editors

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Zhongjie Shi, MD, PhD, Wayne State University, USA

Dr Zhongjie Shi is an assistant professor at Wayne State University, USA. His research interests include Ob & Gyn, pediatrics, infectious diseases, especially focusing on the interruption of mother-to-child transmission of viruses, as well as perinatal infectious diseases that could lead to neurological disability in children.


Sergei S. Simakov, PhD, DSc, Moscow Institute of Physics and Technology, Russia

Dr Sergei S. Simakov is an associate professor and the chair leading the Department of Computational Physics at Moscow Institute of Physics and Technology (MIPT), Russia, as well as an associate professor at Laboratory of Mathematical Modelling in Medicine, Sechenov University, Russia. Being a principle investigator of many national research projects, he is an expert in developing mathematical models, discretization methods in biomedicine, global transport processes in human, environmental effects on human, graph layout algorithms.


About the Collection

BMC Infectious Diseases is calling for submissions to our Collection on Application of advanced statistical methods in infectious diseases. 

Statistical methods play a crucial role in understanding and combating infectious diseases, especially during the global pandemic of Covid-19. While the basic t-tests and Chi-square tests have been widely used in most biomedical research, there is a growing need to explore and apply more advanced statistical techniques. This Collection aims to highlight the innovative use of statistical methods beyond traditional approaches, thereby advancing our understanding of infectious diseases and improving public health interventions.

We welcome research submissions covering a broad range of topics related to the application of advanced statistical methods in infectious diseases. Potential areas of interest are exemplified as:

  • Bioinformatics analysis of infectious diseases data
  • Machine learning and artificial intelligence techniques in infectious diseases research
  • Bayesian methods and their applications in infectious diseases modeling
  • Network analysis and modeling in infectious diseases epidemiology 
  • Spatial and spatio-temporal statistical methods in infectious diseases research
  • Longitudinal data analysis and prediction modeling in infectious diseases
  • Multivariate statistical techniques for analyzing complex infectious diseases datasets
  • Data integration and meta-analysis approaches in infectious diseases research
  • Advanced statistical methods for assessing vaccine efficacy and effectiveness
  • Advanced statistical modeling of emerging infectious diseases and outbreak investigations


Image credit: janews094 / stock.adobe.com

  1. The COVID-19 pandemic has presented unprecedented public health challenges worldwide. Understanding the factors contributing to COVID-19 mortality is critical for effective management and intervention strategi...

    Authors: Maryam Seyedtabib, Roya Najafi-Vosough and Naser Kamyari
    Citation: BMC Infectious Diseases 2024 24:411
    Content type: Research Published on:

  2. Infectious diarrhea remains a major public health problem worldwide. This study used stacking ensemble to developed a predictive model for the incidence of infectious diarrhea, aiming to achieve better predict...

    Authors: Pengyu Wang, Wangjian Zhang, Hui Wang, Congxing Shi, Zhiqiang Li, Dahu Wang, Lei Luo, Zhicheng Du and Yuantao Hao
    Citation: BMC Infectious Diseases 2024 24:265
    Content type: Research Published on:

  3. Gonorrhea has long been a serious public health problem in mainland China that requires attention, modeling to describe and predict its prevalence patterns can help the government to develop more scientific in...

    Authors: Zhende Wang, Yongbin Wang, Shengkui Zhang, Suzhen Wang, Zhen Xu and ZiJian Feng
    Citation: BMC Infectious Diseases 2024 24:113
    Content type: Research Published on:

  4. Brucellosis poses a significant public health concern. This study explores the spatial and temporal dynamic evolution of human brucellosis in China and analyses the spatial heterogeneity of the influencing fac...

    Authors: Meng Zhang, Xinrui Chen, Qingqing Bu, Bo Tan, Tong Yang, Liyuan Qing, Yunna Wang and Dan Deng
    Citation: BMC Infectious Diseases 2024 24:76
    Content type: Research Published on:

  5. Uganda has a high incidence and prevalence of tuberculosis (TB). Analysis of spatial and temporal distribution of TB is an important tool for supporting spatial decision-making, planning, and policy formulatio...

    Authors: Freda Loy Aceng, Steven Ndugwa Kabwama, Alex Riolexus Ario, Alfred Etwom, Stavia Turyahabwe and Frank Rwabinumi Mugabe
    Citation: BMC Infectious Diseases 2024 24:46
    Content type: Research Published on:

  6. Remdesivir (RDV) is an antiviral agent approved for the treatment of coronavirus disease 2019 (COVID-19); however, is not recommended for patients with renal impairment. Due to limitations associated with pros...

    Authors: Eunmi Yang, Han Zo Choi, Subin Kim, Dong Hyun Oh, Mi Young Ahn, Sinyoung Ham, Eunyoung Lee, Jaehyun Jeon, Min-Kyung Kim, Hee-Chang Jang, Sang-Won Park and Jae-Phil Choi
    Citation: BMC Infectious Diseases 2024 24:3
    Content type: Research Published on:

  7. Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease discovered in China in 2009. The purpose of this study was to describe the spatiotemporal distribution of SFTS and to identi...

    Authors: Qing Duan, Xueying Tian, Bo Pang, Yuwei Zhang, Chuanhao Xiao, Mingxiao Yao, Shujun Ding, Xiaomei Zhang, Xiaolin Jiang and Zengqiang Kou
    Citation: BMC Infectious Diseases 2023 23:891
    Content type: Research Published on:

  9. Opioid use disorder (OUD) has been associated with adverse health outcomes, and its potential impact on COVID-19 outcomes is of significant concern. This study aimed to assess the susceptibility and clinical o...

    Authors: Mojtaba Hedayatyaghoobi, Mehdi Azizmohammad Looha, Arman Shafiee, Kyana Jafarabady, Omid Safari, Amirhesam Alirezaei and Mahmood Bakhtiyari
    Citation: BMC Infectious Diseases 2023 23:851
    Content type: Research Published on:

Submission Guidelines

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This Collection welcomes submission of original Research Articles. Should you wish to submit a different article type, please read our submission guidelines to confirm that type is accepted by the journal. Articles for this Collection should be submitted via our submission system, Snapp. During the submission process you will be asked whether you are submitting to a Collection, please select "Application of advanced statistical methods in infectious diseases" from the dropdown menu.

Articles will undergo the journal’s standard peer-review process and are subject to all of the journal’s standard policies. Articles will be added to the Collection as they are published.

The Editors have no competing interests with the submissions which they handle through the peer review process. The peer review of any submissions for which the Editors have competing interests is handled by another Editorial Board Member who has no competing interests.