De Gruyter
Epidemiologic Methods
(ISSN 2161-962X)
About this journal
Objective
Epidemiologic Methods aims at filling the gap for a journal to publish innovative methodology for epidemiologic research. Most social and applied science fields have one or more journals devoted exclusively to methodology. Epidemiologic Methods provides such a journal for the field of epidemiology.
In 2020-2022 we have invited less methodology-oriented epidemiology papers to support in part dissemination of knowledge on the COVID pandemic.
From January 1st, 2023 onwards, we are re-centering the journal on methodological publications. We seek contributions on innovative methodology for epidemiologic research, real-world evidence, and evidence generation in a broader sense, and welcome submissions that provide a comprehensive evaluation or comparison of state-of-the-art methods in the context of epidemiologic research (via simulation studies or analyses of real data sets). We invite papers that may be more technical or of greater length than what has traditionally been allowed by journals in epidemiology. Applications and examples with real data to illustrate the methodology are strongly encouraged.
Submit your article
We invite you to contribute to the following special issues:
Special Issue 1: Covid-19: lessons learned in the use of epidemiologic methods. The deadline for submission is December 31, 2022. - All articles published in this issue are publicly available.
Special Issue 2: Causal inference in comparative effectiveness research
CALL FOR SUBMISSIONS for the special thematic issue on Causal inference in comparative effectiveness, with Dr. Hélène Karcher Novartis, Switzerland) and Prof. Fan Li (Yale University, US) and as Issue Editors. The issue is scheduled for publication in 2023. The (extended) deadline for submission is August 31, 2023.
The proposed special issue aims to inform and educate a broad community of researchers conducting prospective and/or retrospective observational (real-world) studies or related comparative effectiveness studies using a range of possible causal inference methods. We aim to support these studies with innovative methods and/or practical considerations with thoughtful case study illustrations.
Therefore, we welcome article submissions dealing with the development of novel methods or case studies in the field of causal inference, including, but not limited, to the following topics:
Review of current statistical methods for causal inference in epidemiology and comparative effectiveness
Development of innovative causal inference methods for the design or analysis of observational data
Comprehensive simulation evaluation to compare state-of-the-art causal inference methods in the context of epidemiological studies
Case studies or tutorials on the application of state-of-the-art causal inference methods, with explanations on their implementation, how to improve current practice and possible limitations
In particular, the best paper nominated by the editors will be awarded a full Open Access waiver by the publisher De Gruyter!
More information you can find HERE