Skip to main content

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 November 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

Back to top

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. Though, many countries are currently in the COVID post-pandemic era, people’s health protective behaviours are still essential to protect their health and well-being. This study aims to evaluate people’s under...

    Authors: Piyapong Janmaimool, Jaruwan Chontanawat, Siriphan Nunsunanon and Surapong Chudech
    Citation: BMC Infectious Diseases 2024 24:887
  2. Pulmonary tuberculosis (PTB) is a prevalent chronic disease associated with a significant economic burden on patients. Using machine learning to predict hospitalization costs can allocate medical resources eff...

    Authors: Shiyu Fan, Abudoukeyoumujiang Abulizi, Yi You, Chencui Huang, Yasen Yimit, Qiange Li, Xiaoguang Zou and Mayidili Nijiati
    Citation: BMC Infectious Diseases 2024 24:875
  3. Describing the transmission dynamics of infectious diseases across different regions is crucial for effective disease surveillance. The multivariate time series (MTS) model has been widely adopted for construc...

    Authors: Jie Yu, Huimin Wang, Miaoshuang Chen, Xinyue Han, Qiao Deng, Chen Yang, Wenhui Zhu, Yue Ma, Fei Yin, Yang Weng, Changhong Yang and Tao Zhang
    Citation: BMC Infectious Diseases 2024 24:832
  4. Predicting an individual’s risk of death from COVID-19 is essential for planning and optimising resources. However, since the real-world mortality rate is relatively low, particularly in places like Hong Kong,...

    Authors: Jie Lian, Fan Huang, Xinhai Huang, Kitty Yu-Yeung Lau, Kei Shing Ng, Carlin Chun Fai Chu, Simon Ching Lam, Mohamad Koohli-Moghadam and Varut Vardhanabhuti
    Citation: BMC Infectious Diseases 2024 24:803
  5. Students in school are more likely to be sick from communicable diseases like diarrheal illnesses, acute respiratory infections, and other illnesses linked to poor personal hygiene. Poor hygiene practices are ...

    Authors: Getaneh Haile Minda, Habiteyes Hailu Tola, Abebe Feyissa Amhare, Asefa Kebie and Tewodros Endale
    Citation: BMC Infectious Diseases 2024 24:781
  6. Spatiotemporal analysis is a vital method that plays an indispensable role in monitoring epidemiological changes in diseases and identifying high-risk clusters. However, there is still a blank space in the spa...

    Authors: Shuishui Pan, Lili Chen, Xin Xin, Shihong Li, Yixing Zhang, Yichen Chen and Shaotan Xiao
    Citation: BMC Infectious Diseases 2024 24:761
  7. To analyze the clinicopathological features of schistosomal and non-schistosomal colorectal cancer in Central China and compare them with other areas of the Yangtze River Basin.

    Authors: Yuanting Zhu, Xiaoxue Wu, Xiaoshan Ran, Chun Rao and Ping Gong
    Citation: BMC Infectious Diseases 2024 24:732
  8. There is a need to understand the relationship between COVID-19 Convalescent Plasma (CCP) anti-SARS-CoV-2 IgG levels and clinical outcomes to optimize CCP use. This study aims to evaluate the relationship betw...

    Authors: Hyung Park, Chang Yu, Liise-anne Pirofski, Hyunah Yoon, Danni Wu, Yi Li, Thaddeus Tarpey, Eva Petkova, Elliott M. Antman and Andrea B. Troxel
    Citation: BMC Infectious Diseases 2024 24:639
  9. 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
  10. 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
  11. 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
  12. 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
  13. 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
  14. 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
  15. 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
  16. 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

Submission Guidelines

Back to top

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.