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Journal Metrics
CiteScore: 8.1
CiteScore:
2020: 8.1
CiteScore measures the average citations received per peer-reviewed document published in this title. CiteScore values are based on citation counts in a range of four years (e.g. 2017-2020) to peer-reviewed documents (articles, reviews, conference papers, data papers and book chapters) published in the same four calendar years, divided by the number of these documents in these same four years (e.g. 2017–2020).
2020: 8.1
CiteScore measures the average citations received per peer-reviewed document published in this title. CiteScore values are based on citation counts in a range of four years (e.g. 2017-2020) to peer-reviewed documents (articles, reviews, conference papers, data papers and book chapters) published in the same four calendar years, divided by the number of these documents in these same four years (e.g. 2017–2020).
Source Normalized Impact per Paper (SNIP): 3.922
Source Normalized Impact per Paper (SNIP):
2019: 3.922
SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.
2019: 3.922
SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.
SCImago Journal Rank (SJR): 1.332
SCImago Journal Rank (SJR):
2019: 1.332
SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal’s impact.
2019: 1.332
SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal’s impact.
Imprint: KeAi
ISSN: 2468-0427
Infectious Disease Modelling
Infectious Disease Modelling is a peer-reviewed open access journal aiming to promote research working to interface mathematical modelling, infection disease data retrieval and analysis, and public health decision support. The journal welcomes original research contributing to the enhancement of this interface, and review articles of cutting edge methodologies motivated by and applicable to data collection and informatics for public health decision making and policy.
Published papers must contain substantial novelty which could include:
- Developing new frameworks, models and methodologies including comparisons with existing models, theories and methods to indicate demonstrable advantages;- Applications of exiting models and methodologies to new infectious diseases and/or public health issues;
- Integrative use of methodologies and interdisciplinary approaches to evaluate intervention programs and to inform surveillance design;
-Developing linkages between data, modelling, analytics and policy.
Editors-in-Chief: Yiming Shao, Jianhong Wu
View full editorial board
Journal Metrics
CiteScore: 8.1
CiteScore:
2020: 8.1
CiteScore measures the average citations received per peer-reviewed document published in this title. CiteScore values are based on citation counts in a range of four years (e.g. 2017-2020) to peer-reviewed documents (articles, reviews, conference papers, data papers and book chapters) published in the same four calendar years, divided by the number of these documents in these same four years (e.g. 2017–2020).
2020: 8.1
CiteScore measures the average citations received per peer-reviewed document published in this title. CiteScore values are based on citation counts in a range of four years (e.g. 2017-2020) to peer-reviewed documents (articles, reviews, conference papers, data papers and book chapters) published in the same four calendar years, divided by the number of these documents in these same four years (e.g. 2017–2020).
Source Normalized Impact per Paper (SNIP): 3.922
Source Normalized Impact per Paper (SNIP):
2019: 3.922
SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.
2019: 3.922
SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.
SCImago Journal Rank (SJR): 1.332
SCImago Journal Rank (SJR):
2019: 1.332
SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal’s impact.
2019: 1.332
SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal’s impact.
Imprint: KeAi
ISSN: 2468-0427
Recently published articles from Infectious Disease Modelling.
“Stay nearby or get checked”: A Covid-19 control strategy
Jan-Tino Brethouwer | Arnout van de Rijt | ...
Jan-Tino Brethouwer | Arnout van de Rijt | ...
Widespread testing, case isolation and contact tracing may allow safe school reopening with continued moderate physical distancing: A modeling analysis of King County, WA data
Chloe Bracis | Eileen Burns | ...
Chloe Bracis | Eileen Burns | ...
Age-structured model for COVID-19: Effectiveness of social distancing and contact reduction in Kenya
Mark Kimathi | Samuel Mwalili | ...
Mark Kimathi | Samuel Mwalili | ...
The most downloaded articles from Infectious Disease Modelling in the last 90 days.
1. To mask or not to mask: Modeling the potential for face mask use by the general public to curtail the COVID-19 pandemic Steffen E. Eikenberry | Marina Mancuso | ...
2. Infection-acquired versus vaccine-acquired immunity in an SIRWS model Tiffany Leung | Patricia T. Campbell | ...
3. Propagation analysis and prediction of the COVID-19 Lixiang Li | Zihang Yang | ...
Special Issue on the Impact of Vaccination Scale and Pathogenic Mutations on Disease Transmission
Submit your paper before 31 December 2021
Submit your paper before 31 December 2021
The most cited articles published since 2016, extracted from Scopus.
To mask or not to mask: Modeling the potential for face mask use by the general public to curtail the COVID-19 pandemic
Steffen E. Eikenberry | Marina Mancuso | ...
Steffen E. Eikenberry | Marina Mancuso | ...
An updated estimation of the risk of transmission of the novel coronavirus (2019-nCov)
Biao Tang | Nicola Luigi Bragazzi | ...
Biao Tang | Nicola Luigi Bragazzi | ...
Real-time forecasts of the COVID-19 epidemic in China from February 5th to February 24th, 2020
K. Roosa | Y. Lee | ...
K. Roosa | Y. Lee | ...
To mask or not to mask: Modeling the potential for face mask use by the general public to curtail the COVID-19 pandemicRead the featured open access paper
Special Issue on Modelling and Forecasting the 2019 Novel Coronavirus (Covid-19) TransmissionAccess all papers free online
Infectious Disease Modelling CiteScore 2020 Announced: 8.1
Congratulations to the editorial team!
Congratulations to the editorial team!
New Associate Editors of Infectious Disease Modelling
We are pleased to announce that Dr. Yijun Lou and Dr. Daihai He have been appointed as the new Associate Editors of Infectious Disease Modelling.
We are pleased to announce that Dr. Yijun Lou and Dr. Daihai He have been appointed as the new Associate Editors of Infectious Disease Modelling.
Infectious Disease Modelling Indexed in ESCI
Infectious Disease Modelling has also been indexed in Scopus, PubMed, Directory of Open Access Journals (DOAJ) and EMBASE.
Infectious Disease Modelling has also been indexed in Scopus, PubMed, Directory of Open Access Journals (DOAJ) and EMBASE.
