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Most Downloaded Infectious Disease Modelling Articles

The most downloaded articles from ScienceDirect 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 | Enahoro Iboi | Tin Phan | Keenan Eikenberry | Yang Kuang | Eric Kostelich | Abba B. Gumel

Face mask use by the general public for limiting the spread of the COVID-19 pandemic is controversial, though increasingly recommended, and the potential of this intervention is not well understood....

2. Propagation analysis and prediction of the COVID-19

Lixiang Li | Zihang Yang | Zhongkai Dang | Cui Meng | Jingze Huang | Haotian Meng | Deyu Wang | Guanhua Chen | Jiaxuan Zhang | Haipeng Peng | Yiming Shao

Based on the official data modeling, this paper studies the transmission process of the Corona Virus Disease 2019 (COVID-19). The error between the model and the official data curve is quite small....

3. Estimating epidemic exponential growth rate and basic reproduction number

Junling Ma

The initial exponential growth rate of an epidemic is an important measure of the severeness of the epidemic, and is also closely related to the basic reproduction number. Estimating the growth rate...

4. Bidirectional impact of imperfect mask use on reproduction number of COVID-19: A next generation matrix approach

David N. Fisman | Amy L. Greer | Ashleigh R. Tuite

The use of masks as a means of reducing transmission of COVID-19 outside healthcare settings has proved controversial. Masks are thought to have two modes of effect: they prevent infection with COVID-19...

5. A simple model for COVID-19

Julien Arino | Stéphanie Portet

An SL1L2I1I2A1A2R epidemic model is formulated that describes the spread of an epidemic in a population. The model incorporates an Erlang distribution of times of sojourn in incubating, symptomatically...

6. Why is it difficult to accurately predict the COVID-19 epidemic?

Weston C. Roda | Marie B. Varughese | Donglin Han | Michael Y. Li

Since the COVID-19 outbreak in Wuhan City in December of 2019, numerous model predictions on the COVID-19 epidemics in Wuhan and other parts of China have been reported. These model predictions have...

7. Relatedness of the incidence decay with exponential adjustment (IDEA) model, “Farr's law” and SIR compartmental difference equation models

Mauricio Santillana | Ashleigh Tuite | Tahmina Nasserie | Paul Fine | David Champredon | Leonid Chindelevitch | Jonathan Dushoff | David Fisman

Mathematical models are often regarded as recent innovations in the description and analysis of infectious disease outbreaks and epidemics, but simple mathematical expressions have been in use for projection...

8. An updated estimation of the risk of transmission of the novel coronavirus (2019-nCov)

Biao Tang | Nicola Luigi Bragazzi | Qian Li | Sanyi Tang | Yanni Xiao | Jianhong Wu

The basic reproduction number of an infectious agent is the average number of infections one case can generate over the course of the infectious period, in a naïve, uninfected population. It is well-known...

9. A COVID-19 epidemic model with latency period

Z. Liu | P. Magal | O. Seydi | G. Webb

At the beginning of a COVID-19 infection, there is a period of time known as the exposed or latency period, before an infected person is capable of transmitting the infection to another person. We develop...

10. Transmission potential of the novel coronavirus (COVID-19) onboard the diamond Princess Cruises Ship, 2020

Kenji Mizumoto | Gerardo Chowell

An outbreak of COVID-19 developed aboard the Princess Cruises Ship during January–February 2020. Using mathematical modeling and time-series incidence data describing the trajectory of the outbreak...

11. Real-time forecasts of the COVID-19 epidemic in China from February 5th to February 24th, 2020

K. Roosa | Y. Lee | R. Luo | A. Kirpich | R. Rothenberg | J.M. Hyman | P. Yan | G. Chowell

The initial cluster of severe pneumonia cases that triggered the COVID-19 epidemic was identified in Wuhan, China in December 2019. While early cases of the disease were linked to a wet market, human-to-human...

12. Fitting dynamic models to epidemic outbreaks with quantified uncertainty: A primer for parameter uncertainty, identifiability, and forecasts

August 2017
Gerardo Chowell

Mathematical models provide a quantitative framework with which scientists can assess hypotheses on the potential underlying mechanisms that explain patterns in observed data at different spatial and...

13. Early transmission dynamics of COVID-19 in a southern hemisphere setting: Lima-Peru: February 29th–March 30th, 2020

César V. Munayco | Amna Tariq | Richard Rothenberg | Gabriela G. Soto-Cabezas | Mary F. Reyes | Andree Valle | Leonardo Rojas-Mezarina | César Cabezas | Manuel Loayza | Gerardo Chowell | Dante Castro Garro | Kevin Martel Vasquez | Edith Solis Castro | Isabel Sandoval Ordinola | Javier Masias Mimbela | Kely Meza Cornejo | Fabiola Caruajulca Quijano | Lenin La Torre Rosillo | Luis Ordoñez Ibarguen | Mario Vasquez Dominguez | Rommell Veintimilla Gonzalez Seminario | Martha Calderón Silva | Mayra Saavedra Dreyfus | Miguel Luna Pineda | Milagros Durand | Noemí Janampa | Jesus Chuquihuaccha | Susan Mateo Lizarbe | David Enriquez Cusi | Idania Mamani Pilco | Alex Jaramillo | Karina Vargas | Oswaldo Cabanillas | Juan Arrasco | María Vargas | Willy Ramos

The COVID-19 pandemic that emerged in Wuhan China has generated substantial morbidity and mortality impact around the world during the last four months. The daily trend in reported cases has been rapidly...

14. Mathematical epidemiology: Past, present, and future

May 2017
Fred Brauer

We give a brief outline of some of the important aspects of the development of mathematical epidemiology....

15. A primer on stochastic epidemic models: Formulation, numerical simulation, and analysis

May 2017
Linda J.S. Allen

Some mathematical methods for formulation and numerical simulation of stochastic epidemic models are presented. Specifically, models are formulated for continuous-time Markov chains and stochastic differential...

16. Reproduction numbers of infectious disease models

August 2017
Pauline van den Driessche

This primer article focuses on the basic reproduction number, ℛ0, for infectious diseases, and other reproduction numbers related to ℛ0 that are useful in guiding control strategies. Beginning with...

17. Infection-acquired versus vaccine-acquired immunity in an SIRWS model

Tiffany Leung | Patricia T. Campbell | Barry D. Hughes | Federico Frascoli | James M. McCaw

In some disease systems, the process of waning immunity can be subtle, involving a complex relationship between the duration of immunity—acquired either through natural infection or vaccination—and...

18. Canada needs to rapidly escalate public health interventions for its COVID-19 mitigation strategies

Francesca Scarabel | Lorenzo Pellis | Nicola Luigi Bragazzi | Jianhong Wu

After the declaration of COVID-19 pandemic on March 11th, 2020, local transmission chains starting in different countries including Canada are forcing governments to take decisions on public health...

19. Epidemics on networks: Reducing disease transmission using health emergency declarations and peer communication

Asma Azizi | Cesar Montalvo | Baltazar Espinoza | Yun Kang | Carlos Castillo-Chavez

Understanding individual decisions in a world where communications and information move instantly via cell phones and the internet, contributes to the development and implementation of policies aimed...

20. Discrete time forecasting of epidemics

Daniel A.M. Villela

Forecasting in the domain of infectious diseases aims at estimating the number of cases ahead of time during an epidemic, hence fundamentally requires understanding its dynamics. In fact, estimates...

21. A novel IDEA: The impact of serial interval on a modified-Incidence Decay and Exponential Adjustment (m-IDEA) model for projections of daily COVID-19 cases

Ben A. Smith

The SARS-CoV-2 virus causes the disease COVID-19, and has caused high morbidity and mortality worldwide. Empirical models are useful tools to predict future trends of disease progression such as COVID-19...

22. Mathematical modeling and the transmission dynamics in predicting the Covid-19 - What next in combating the pandemic

A. Anirudh

Mathematical predictions in combating the epidemics are yet to reach its perfection. The rapid spread, the ways, and the procedures involved in containment of a pandemic demand the earliest understanding...

23. Mathematical epidemiology in a data-rich world

Julien Arino

I discuss the acquisition and use of “background” data in mathematical epidemiology models, advocating a proactive approach to the incorporation of said data. I illustrate various mechanisms for acquiring...

24. Bayesian inference for dynamical systems

Weston C. Roda

Bayesian inference is a common method for conducting parameter estimation for dynamical systems. Despite the prevalent use of Bayesian inference for performing parameter estimation for dynamical systems,...

25. Using statistics and mathematical modelling to understand infectious disease outbreaks: COVID-19 as an example

Christopher E. Overton | Helena B. Stage | Shazaad Ahmad | Jacob Curran-Sebastian | Paul Dark | Rajenki Das | Elizabeth Fearon | Timothy Felton | Martyn Fyles | Nick Gent | Ian Hall | Thomas House | Hugo Lewkowicz | Xiaoxi Pang | Lorenzo Pellis | Robert Sawko | Andrew Ustianowski | Bindu Vekaria | Luke Webb

During an infectious disease outbreak, biases in the data and complexities of the underlying dynamics pose significant challenges in mathematically modelling the outbreak and designing policy. Motivated...

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