| Improved inference of time-varying reproduction numbers during infectious disease outbreaks |
45 |
| Using phenomenological models for forecasting the 2015 Ebola challengeBruce |
24 |
| The RAPIDD ebola forecasting challenge: Synthesis and lessons learnt |
20 |
| Quantitative risk assessment of salmon louse-induced mortality of seaward-migrating post-smolt Atlantic salmon |
17 |
| Real-time forecasting of infectious disease dynamics with a stochastic semi-mechanistic model |
17 |
| Results from the second year of a collaborative effort to forecast influenza seasons in the United States |
13 |
| Modelling the global spread of diseases: A review of current practice and capability |
11 |
| A simple approach to measure transmissibility and forecast incidence |
10 |
| The 2017 plague outbreak in Madagascar: Data descriptions and epidemic modelling |
9 |
| Estimating the impact of violent events on transmission in Ebola virus disease outbreak, Democratic Republic of the Congo, 2018-2019 |
9 |
| Systematic biases in disease forecasting - The role of behavior change |
9 |
| Epidemics on dynamic networks |
9 |
| Assessing reporting delays and the effective reproduction number: The Ebola epidemic in DRC, May 2018-January 2019 |
9 |
| Using data-driven agent-based models for forecasting emerging infectious diseases |
8 |
| A systematic review of MERS-CoV seroprevalence and RNA prevalence in dromedary camels: Implications for animal vaccination |
8 |
| Acute illness from Campylobacter jejuni may require high doses while infection occurs at low doses |
7 |
| Digital Dermatitis in dairy cattle: The contribution of different disease classes to transmission |
6 |
| A practical generation-interval-based approach to inferring the strength of epidemics from their speed |
6 |
| Role of animal movement and indirect contact among farms in transmission of porcine epidemic diarrhea virus |
6 |
| The importance of being urgent: The impact of surveillance target and scale on mosquito-borne disease control |
6 |
| Practical unidentifiability of a simple vector-borne disease model: Implications for parameter estimation and intervention assessment |
5 |
| Modeling Marek's disease virus transmission: A framework for evaluating the impact of farming practices and evolution |
5 |
| Contemporary statistical inference for infectious disease models using Stan |
5 |
| Geographic transmission hubs of the 2009 influenza pandemic in the United States |
5 |
| The impact of influenza vaccination on infection, hospitalisation and mortality in the Netherlands between 2003 and 2015 |
5 |
| Temperature impacts on dengue emergence in the United States: Investigating the role of seasonality and climate change |
5 |
| Real-time predictions of the 2018-2019 Ebola virus disease outbreak in the Democratic Republic of the Congo using Hawkes point process models |
5 |
| GEOFIL: A spatially-explicit agent-based modelling framework for predicting the long-term transmission dynamics of lymphatic filariasis in American Samoa |
5 |
| Confronting data sparsity to identify potential sources of Zika virus spillover infection among primates |
5 |
| Contagion! The BBC Four Pandemic - The model behind the documentary |
5 |
| Vaccinating children against influenza increases variability in epidemic size |
4 |
| Fogarty International Center collaborative networks in infectious disease modeling: Lessons learnt in research and capacity building |
4 |
| Introduction to particle Markov-chain Monte Carlo for disease dynamics modellers |
4 |
| Dengue modeling in rural Cambodia: Statistical performance versus epidemiological relevance |
4 |
| Real-time prediction of influenza outbreaks in Belgium |
4 |
| Complementing the power of deep learning with statistical model fusion: Probabilistic forecasting of influenza in Dallas County, Texas, USA |
4 |
| The drivers of squirrelpox virus dynamics in its grey squirrel reservoir host |
4 |
| A dynamic network model to disentangle the roles of steady and casual partners for HIV transmission among MSM |
4 |
| Hepatitis C transmission in young people who inject drugs: Insights using a dynamic model informed by state public health surveillance |
4 |
| Identifying genotype specific elevated-risk areas and associated herd risk factors for bovine tuberculosis spread in British cattle |
4 |
| Accurate forecasts of the effectiveness of interventions against Ebola may require models that account for variations in symptoms during infection |
4 |
| Tuberculosis outbreak investigation using phylodynamic analysis |
4 |
| A model for leptospire dynamics and control in the Norway rat (Rattus norvegicus) the reservoir host in urban slum environments |
3 |
| Contact tracing for the control of infectious disease epidemics: Chronic Wasting Disease in deer farms |
3 |
| Efficient vaccination strategies for epidemic control using network information |
3 |
| Analyzing and forecasting the Ebola incidence in North Kivu, the Democratic Republic of the Congo from 2018-19 in real time |
3 |
| Estimating HIV incidence from surveillance data indicates a second wave of infections in Brazil |
3 |
| Model-based estimates of transmission of respiratory syncytial virus within households |
3 |
| Assessing the role of dens in the spread, establishment and persistence of sarcoptic mange in an endangered canid |
3 |
| School dismissal as a pandemic influenza response: When, where and for how long? |
3 |
