Modeling infectious epidemics

Infectious Diseases of Humans: Dynamics and Control

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Infectious Diseases of Humans: Dynamics and Control

Anderson, R. M., & May, R. M. (1991) · doi:10.1093/oso/9780198545996.001.0001 · Cited by 6,179

Vaccination and herd immunity to infectious diseases

Anderson, R. M., & May, R. (1985) · Nature · doi:10.1038/318323a0 · Cited by 716

The SIR model and the Foundations of Public Health

Weiss, H. M. (2013) · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · Cited by 226

Epidemics: Models and Data using R

Bjørnstad, O. N. (2018) · International Linear Collider · doi:10.1007/978-3-319-97487-3 · Cited by 54

Modeling COVID-19 scenarios for the United States

IHME COVID-19 Forecasting Team, Reiner, R. C., Barber, R. M., Collins, J. K., Zheng, P., Adolph, C., Albright, J., Antony, C. M., Aravkin, A. Y., Bachmeier, S. D., et al. (2021) · Nature Medicine · doi:10.1038/s41591-020-1132-9 · Cited by 556

A modelling framework to assess the likely effectiveness of facemasks in combination with ‘lock-down’ in managing the COVID-19 pandemic

Stutt, R. O. J. H., Retkutė, R., Bradley, M. S. A., Gilligan, C. A., & Colvin, J. (2020) · Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rspa.2020.0376 · Cited by 304

Variation in the COVID-19 infection-fatality ratio by age, time, and geography during the pre-vaccine era: a systematic analysis

(2022) · The Lancet · doi:10.1016/s0140-6736(21)02867-1 · Cited by 306

Estimating global, regional, and national daily and cumulative infections with SARS-CoV-2 through Nov 14, 2021: a statistical analysis

Barber, R. M., Sorensen, R. J. D., Pigott, D. M., Bisignano, C., Carter, A., Amlag, J. O., Collins, J. K., Abbafati, C., Adolph, C., Allorant, A., et al. (2022) · The Lancet · doi:10.1016/s0140-6736(22)00484-6 · Cited by 298

The SEIRS model for infectious disease dynamics

Bjørnstad, O. N., Shea, K., Krzywinski, M., & Altman, N. (2020) · Nature Methods · doi:10.1038/s41592-020-0856-2 · Cited by 231

Defensive Modeling of Fake News Through Online Social Networks

Shrivastava, G., Kumar, P., Ojha, R. P., Srivastava, P. K., Mohan, S., & Srivastava, G. (2020) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2020.3014135 · Cited by 158

The europe second wave of COVID-19 infection and the Italy “strange” situation

Bontempi, E. (2020) · Environmental Research · doi:10.1016/j.envres.2020.110476 · Cited by 154

Rates of SARS-CoV-2 transmission and vaccination impact the fate of vaccine-resistant strains

Rella, S. A., Kulikova, Y. A., Dermitzakis, E. T., & Kondrashov, F. A. (2021) · Scientific Reports · doi:10.1038/s41598-021-95025-3 · Cited by 139

Logistic equation and COVID-19

Pelinovsky, E. N., Куркин, А. А., Kurkina, O. E., Kokoulina, M. V., & Епифанова, А. С. (2020) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2020.110241 · Cited by 96

Adaptive Bayesian Learning and Forecasting of Epidemic Evolution—Data Analysis of the COVID-19 Outbreak

Gaglione, D., Braca, P., Millefiori, L. M., Soldi, G., Forti, N., Maranò, S., Willett, P., & Pattipati, K. R. (2020) · IEEE Access · doi:10.1109/access.2020.3019922 · Cited by 50

Fractional SIR epidemiological models

Taghvaei, A., Georgiou, T. T., Norton, L., & Tannenbaum, A. (2020) · Scientific Reports · doi:10.1038/s41598-020-77849-7 · Cited by 49

The SIR dynamic model of infectious disease transmission and its analogy with chemical kinetics

Simon, C. M. (2020) · PeerJ Physical Chemistry · doi:10.7717/peerj-pchem.14 · Cited by 41

Heterogeneity in susceptibility dictates the order of epidemic models

Rose, C., Medford, A. J., Goldsmith, C. F., Vegge, T., Weitz, J. S., & Peterson, A. A. (2021) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2021.110839 · Cited by 36

Agent-Based Computational Epidemiological Modeling

Bisset, K. R., Cadena, J., Khan, M., & Kuhlman, C. J. (2021) · Journal of the Indian Institute of Science · doi:10.1007/s41745-021-00260-2 · Cited by 35

Dynamic tracking with model-based forecasting for the spread of the COVID-19 pandemic

Cooper, I., Mondal, A., & Antonopoulos, C. G. (2020) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2020.110298 · Cited by 27

EKF-SIRD model algorithm for predicting the coronavirus (COVID-19) spreading dynamics

Sebbagh, A., & Kechida, S. (2022) · Scientific Reports · doi:10.1038/s41598-022-16496-6 · Cited by 26

Estimation of Infection Rate and Predictions of Disease Spreading Based on Initial Individuals Infected With COVID-19

Chae, S. Y., Lee, K.-E., Lee, H. M., Jung, N., Le, Q. A., Mafwele, B. J., Lee, T. H., Kim, D. H., & Lee, J. W. (2020) · Frontiers in Physics · doi:10.3389/fphy.2020.00311 · Cited by 26

Data Assimilation Predictive GAN (DA-PredGAN) Applied to a Spatio-Temporal Compartmental Model in Epidemiology

Silva, V. L. S., Heaney, C. E., Li, Y., & Pain, C. C. (2022) · Journal of Scientific Computing · doi:10.1007/s10915-022-02078-1 · Cited by 27

Climate warming and influenza dynamics: the modulating effects of seasonal temperature increases on epidemic patterns

Ruan, W., Liang, Y., Sun, Z., & An, X. (2025) · npj Climate and Atmospheric Science · doi:10.1038/s41612-025-00968-3 · Cited by 26

Revisiting classical SIR modelling in light of the COVID-19 pandemic

Kalachev, L. V., Landguth, E. L., & Graham, J. (2022) · Infectious Disease Modelling · doi:10.1016/j.idm.2022.12.002 · Cited by 22

Applying Laplace Adomian decomposition method (LADM) for solving a model of Covid-19

Nave, O., Shemesh, U., & Hartuv, I. (2021) · Computer Methods in Biomechanics & Biomedical Engineering · doi:10.1080/10255842.2021.1904399 · Cited by 20

Policy and behavioral response to shock events: An agent-based model of the effectiveness and equity of policy design features

Shastry, V., Reeves, D. C., Willems, N., & Rai, V. (2022) · PLoS ONE · doi:10.1371/journal.pone.0262172 · Cited by 20

Global short-term forecasting of COVID-19 cases

Oliveira, T. D. P., & Moral, R. D. A. (2021) · Scientific Reports · doi:10.1038/s41598-021-87230-x · Cited by 16

A simple, SIR-like but individual-based epidemic model: Application in comparison of COVID-19 in New York City and Wuhan

Liu, X. (2020) · Results in Physics · doi:10.1016/j.rinp.2020.103712 · Cited by 16

Quickest Detection and Forecast of Pandemic Outbreaks: Analysis of COVID-19 Waves

Soldi, G., Forti, N., Gaglione, D., Braca, P., Millefiori, L. M., Maranò, S., Willett, P., & Pattipati, K. R. (2021) · IEEE Communications Magazine · doi:10.1109/mcom.101.2001252 · Cited by 16

Uncertainty and the management of epidemics

Shea, K., Bjørnstad, O. N., Krzywinski, M. I., & Altman, N. (2020) · Nature Methods · doi:10.1038/s41592-020-0943-4 · Cited by 16

Investigating the effectiveness of re-opening policies before vaccination during a pandemic: SD modelling research based on COVID-19 in Wuhan

Qian, Y. P., Xie, W., Zhao, J., Xue, M., Liu, S., Wang, L., Li, W., Dai, L., & Cai, Y. (2021) · BMC Public Health · doi:10.1186/s12889-021-11631-w · Cited by 16

A Time-Dependent Mathematical Model for COVID-19 Transmission Dynamics and Analysis of Critical and Hospitalized Cases with Bed Requirements

Singh, A. K., Bajpai, M. K., & Gupta, S. L. (2023) · Lecture notes in electrical engineering · doi:10.1007/978-981-99-0189-0_7 · Cited by 15

A new approximation of mean-time trends for the second wave of COVID-19 pandemic evolving in key six countries

Ershkov, S. V., & Rachinskaya, A. (2021) · Nonlinear Dynamics · doi:10.1007/s11071-021-06244-2 · Cited by 14

Fractal and fractional SIS model for syphilis data

Gabrick, E. C., Sayari, E., Souza, D. L. M., Borges, F. S., Trobia, J., Lenzi, E. K., & Batista, A. M. (2023) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/5.0153122 · Cited by 12

Interval nonlinear initial-valued problem using constraint intervals: Theory and an application to the Sars-Cov-2 outbreak

Cecconello, M. D. S., Mizukoshi, M. T., & Lodwick, W. A. (2021) · Information Sciences · doi:10.1016/j.ins.2021.08.045 · Cited by 12

Integrating Data Science and Earth Science

Bouwer, L. M., Dransch, D., Ruhnke, R., Rechid, D., Frickenhaus, S., & Greinert, J. (2022) · SpringerBriefs in earth system sciences · doi:10.1007/978-3-030-99546-1 · Cited by 10

Effects of quarantine disobedience and mobility restrictions on COVID-19 pandemic waves in dynamical networks

Stipic, D., Bradac, M., Lipić, T., & Boris Podobnik, A. (2021) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2021.111200 · Cited by 12

Infection transmission and prevention in metropolises with heterogeneous and dynamic populations

Rezapour, S., Baghaian, A., Naderi, N., & Sarmiento, J. P. (2021) · European Journal of Operational Research · doi:10.1016/j.ejor.2021.09.016 · Cited by 10

An Agent-Based Model for Disease Epidemics in Greece

Thomopoulos, V., & Tsichlas, K. (2024) · Information · doi:10.3390/info15030150 · Cited by 7

Intervention strategies with 2D cellular automata for testing SARS-CoV-2 and reopening the economy

Lugo, I., & Alatriste-Contreras, M. G. (2022) · Scientific Reports · doi:10.1038/s41598-022-17665-3 · Cited by 11

Transition from susceptible-infected to susceptible-infected-recovered dynamics in a susceptible-cleric-zombie-recovered active matter model

Libál, A., Forgács, P., Néda, Á., Reichhardt, C. J. O., Hengartner, N., & Reichhardt, C. J. O. (2023) · Physical review. E · doi:10.1103/physreve.107.024604 · Cited by 7

Teaching Undergraduate Physical Chemistry Lab with Kinetic Analysis of COVID-19 in the United States

Smith, D. K., Lauro, K., Kelly, D., Fish, J., Lintelman, E., McEwen, D., Smith, C., Stecz, M., Ambagaspitiya, T. D., & Chen, J. (2022) · Journal of Chemical Education · doi:10.1021/acs.jchemed.2c00416 · Cited by 6

Dynamics, statistics, and task allocation of foraging ants

Zhang, N., & Yong, E. H. (2023) · Physical review. E · doi:10.1103/physreve.108.054306 · Cited by 6

Estimating time-varying epidemiological parameters and underreporting of Covid-19 cases in Brazil using a mathematical model with fuzzy transitions between epidemic periods

Lima, H. S., Tupinambás, U., & Guimarães, F. G. (2024) · PLoS ONE · doi:10.1371/journal.pone.0305522 · Cited by 9

SIR (Susceptible–Infectious–Removed) Model of Epidemiology as an Extended Example for Chemical Kinetics Students

McBane, G. C. (2021) · Journal of Chemical Education · doi:10.1021/acs.jchemed.1c00195 · Cited by 6

SERDUX-MARCIM: Maritime Cyberattack simulation using Dynamic Modeling, Compartmental Models in Epidemiology and Agent-based Modeling

Cabuya-Padilla, D. E., López, D. D., Martínez-Páez, J., Hernández, L., & Castaneda-Marroquin, C. (2025) · International Journal of Information Security · doi:10.1007/s10207-025-00985-6 · Cited by 5

Age-Related Model for Estimating the Symptomatic and Asymptomatic Transmissibility of COVID-19 Patients

Tan, J., Shen, Y., Ge, Y., Martínez, L., & Huang, H. (2022) · Biometrics · doi:10.1111/biom.13814 · Cited by 4

Analytical solution of l-i SEIR model–Comparison of l-i SEIR model with conventional SEIR model in simulation of epidemic curves

Liu, X. (2023) · PLoS ONE · doi:10.1371/journal.pone.0287196 · Cited by 5

Assessing Epidemic Curves for Evidence of Superspreading

Meagher, J., & Friel, N. (2022) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/rssa.12919 · Cited by 4

A Mean-Field Approximation of SIR Epidemics on an Erdös–Rényi Network Model

Durón, C., & Farrell, A. P. (2022) · Bulletin of Mathematical Biology · doi:10.1007/s11538-022-01026-2 · Cited by 5

Spatial Allocation of Scarce COVID-19 Vaccines *†‡Preprint

Castonguay, F. M., Blackwood, J. C., Howerton, E., Shea, K., Sims, C. B., & Sanchirico, J. N. (2020) · medRxiv · doi:10.1101/2020.12.18.20248439 · Cited by 5

Increasing Effectiveness of Genetically Modifying Mosquito Populations: Risk Assessment of Releasing Blood-Fed Females

Xia, S., Ury, J., & Powell, J. R. (2021) · American Journal of Tropical Medicine and Hygiene · doi:10.4269/ajtmh.19-0729 · Cited by 6

Adaptive dynamic social networks using an agent-based model to study the role of social awareness in infectious disease spread

López, L., & Giovanini, L. (2025) · Physica D Nonlinear Phenomena · doi:10.1016/j.physd.2025.134530 · Cited by 4

Development of Mathematical Models Taking into Account the Effect of Isolating Individuals in a Population

Аманбаев, Т. Р., & Antony, S. J. (2022) · Mathematical Models and Computer Simulations · doi:10.1134/s2070048222030036 · Cited by 4

COVID-19 Vulnerability Mapping of Asian Countries

Sarkar, S. K., Morshed, M. M., & Chakraborty, T. (2022) · Disaster Medicine and Public Health Preparedness · doi:10.1017/dmp.2022.139 · Cited by 4

Mean-field approach to Rydberg facilitation in a gas of atoms at high and low temperatures

Brady, D., & Fleischhauer, M. (2023) · Physical Review A · doi:10.1103/physreva.108.052812 · Cited by 4

Wastewater-based effective reproduction number and prediction under the absence of shedding information

Ando, H., & Reynolds, K. A. (2024) · Environment International · doi:10.1016/j.envint.2024.109128 · Cited by 3

Estimating the basic reproduction number from noisy daily data

Descary, M.-H., & Froda, S. (2022) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2022.111210 · Cited by 3

Measuring the impact of social-distancing, testing, and undetected asymptomatic cases on the diffusion of COVID-19

Jeon, S. (2022) · PLoS ONE · doi:10.1371/journal.pone.0273469 · Cited by 3

Chimeric Forecasting: An experiment to leverage human judgment to improve forecasts of infectious disease using simulated surveillance data

McAndrew, T., Gibson, G., Braun, D., Srivastava, A., & Brown, K. (2024) · Epidemics · doi:10.1016/j.epidem.2024.100756 · Cited by 2

The timing of contact restrictions and pro-active testing balances the socio-economic impact of a lockdown with the control of infectionsPreprint

Bej, S., & Olaf Wolkenhauer, A. (2020) · medRxiv · doi:10.1101/2020.05.08.20095596 · Cited by 3

Identification of the COVID-19 epidemiological dynamics at State of Amazonas and optimal vaccination strategy proposal

de Oliveira, K. C., Batista, T. A. D. S., Chui, D. D. S., & Silva, G. C. (2023) · Journal of the Brazilian Society of Mechanical Sciences and Engineering · doi:10.1007/s40430-023-04539-6 · Cited by 2

Digital Epidemiology

Mejova, Y. (2022) · Springer eBooks · doi:10.1007/978-3-031-16624-2_15 · Cited by 1

The relationship between compartment models and their stochastic counterparts: A comparative study with examples of the COVID-19 epidemic modeling

Zhao, Z., Zhou, Y., Guan, J., Yan, Y., Jing, Z., Peng, Z., Chen, F., Zhao, Y., & Shao, F. (2023) · Journal of Biomedical Research · doi:10.7555/jbr.37.20230137 · Cited by 2

Opinion-driven risk perception and reaction in SIS epidemics

Arango, M. O., Bizyaeva, A., Levin, S. A., & Leonard, N. E. (2025) · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · doi:10.23919/acc63710.2025.11107837 · Cited by 2

MATHEMATICAL MODEL FOR PREDICTIONS OF COVID-19 DYNAMICS

Lazarova, L. K. (2022) · International Journal of Apllied Mathematics · doi:10.12732/ijam.v35i1.9 · Cited by 2

Fractional Order Epidemiological Model of Fake Information Mitigation in OSNs With PINN, TFC, and ELM

Srivastava, V. K., Srivastava, P. K., & Yadav, A. K. (2024) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-5271-7.ch009 · Cited by 2

COVID-19 dynamical evolution prediction in Mexico, decision making and social implementation: mid/low income countries study

Fernandez-Erana, S., Fernández-Eraña, L., & Fernández‐Guasti, M. (2020) · Technium Romanian Journal of Applied Sciences and Technology · doi:10.47577/technium.v2i7.1681 · Cited by 2

Should the rate term in the basic epidemiology models be second-order?Preprint

Peterson, A. A., Goldsmith, C. F., Rose, C. F., Medford, A. J., & Vegge, T. (2020) · arXiv (Cornell University) · Cited by 2

Modeling music popularity as an epidemic: insights from the Brazilian market

Oliveira, G. P., Vassio, L., da Silva, A. P. C., & Moro, M. M. (2025) · Anais do Brazilian Workshop on Social Network Analysis and Mining (BraSNAM) · doi:10.5753/brasnam.2025.8760 · Cited by 1

Contagious Rhythms: A Wave-Based Epidemic Approach for Music Virality on Social Platforms

Oliveira, G. P., Vassio, L., da Silva, A. P. C., & Moro, M. M. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-13513-1_16 · Cited by 1

ABC-RF-rejection: A two-stage machine-learning-enhanced framework for efficient likelihood-free inference

Retkutė, R., & Gilligan, C. A. (2026) · Epidemics · doi:10.1016/j.epidem.2026.100931 · Cited by 1

Развитие математических моделей эпидемии с учетом влияния изоляции особей в популяции

Аманбаев, Т. Р., Энтони, С. Д., & Antony, S. J. (2021) · Matematicheskoe modelirovanie · doi:10.20948/mm-2021-11-03 · Cited by 1

A Privacy-Preserving Approach to Identify COVID-19 Infection Origins via Volunteered Share of Health Data Records by Mobile Users

Zhou, W., Ding, Y., Jolfaei, A., Haghighi, M. S., & Wen, S. (2022) · IEEE Sensors Journal · doi:10.1109/jsen.2022.3192843 · Cited by 1

A look at endemic equilibria of compartmental epidemiological models and model control via vaccination and mitigation

Chyba, M., Klotz, T., Mileyko, Y., & Shanbrom, C. (2023) · Mathematics of Control Signals and Systems · doi:10.1007/s00498-023-00365-2 · Cited by 2

Examining pathogen avoidance in predator-prey and scavenging systems

Clapp, J. G., Malmberg, J. L., & Holbrook, J. D. (2024) · Frontiers in Ecology and Evolution · doi:10.3389/fevo.2024.1481290 · Cited by 1

Toward Interpretable Machine Learning for Understanding Epidemic Data

Hougen, D. F., Pei, J., & Kanneganti, S. T. (2020) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata50022.2020.9377834 · Cited by 1

A note on epidemiologic models: SIR modeling of the COVID-19 with variable coefficients

Cakir, Z., & Şendur, A. (2022) · BULLETIN OF THE KARAGANDA UNIVERSITY-MATHEMATICS · doi:10.31489/2022m1/43-51 · Cited by 1

The Digital Earth Smart Monitoring Concept and Tools

Koedel, U., Dietrich, P., Fischer, P. F., Greinert, J., Bundke, U., Burwicz, E., Haas, A., Herrarte, I., Haroon, A., Jegen, M., et al. (2022) · SpringerBriefs in earth system sciences · doi:10.1007/978-3-030-99546-1_6 · Cited by 1

Can Catastrophe Theory explain expansion and contagious of Covid-19?Preprint

Caetano, M. A. L. (2021) · medRxiv · doi:10.1101/2021.01.02.21249133 · Cited by 1

Two new compartmental epidemiological models and their equilibriaPreprint

Balisacan, J., Chyba, M., & Shanbrom, C. (2021) · medRxiv · doi:10.1101/2021.09.03.21263050 · Cited by 1

Estimating epidemiological parameters and underreporting of Covid-19 cases in Brazil using a multi-wave mathematical modelPreprint

Lima, H. S., Tupinambás, U., & Guimarães, F. G. (2023) · Research Square · doi:10.21203/rs.3.rs-3161529/v1 · Cited by 1

Disentangling Increased Testing From Covid-19 Epidemic SpreadPreprint

Lengerich, B. J., Neiswanger, W., Lengerich, E. J., & Xing, E. (2020) · medRxiv · doi:10.1101/2020.07.09.20141762

On outbreak of 3rd wave of Covid-19 pandemic in India and RussiaPreprint

Ershkov, S. V., Rachinskaya, A., & Prosviryakov, E. Y. (2021) · arXiv (Cornell University)

Peer Review #1 of "The SIR dynamic model of infectious disease transmission and its analogy with chemical kinetics (v0.1)"

(2020) · PeerJ Physical Chemistry · doi:10.7287/peerj-pchem.14v0.1/reviews/1

Peer Review #2 of "The SIR dynamic model of infectious disease transmission and its analogy with chemical kinetics (v0.1)"

(2020) · PeerJ Physical Chemistry · doi:10.7287/peerj-pchem.14v0.1/reviews/2

Modification of Epidemiological Model for Predicting the Development of a Socially Significant Infection (by the Example of Chronic Viral Hepatitis C)

Yakhina, R. A. (2022) · Statistics and Economics · doi:10.21686/2500-3925-2022-4-87-96

SIR

Bjørnstad, O. N. (2022) · Use R! · doi:10.1007/978-3-031-12056-5_2

Invasion and Eradication

Bjørnstad, O. N. (2022) · Use R! · doi:10.1007/978-3-031-12056-5_15

R 0

Bjørnstad, O. N. (2022) · Use R! · doi:10.1007/978-3-031-12056-5_3

A Spatio-Temporal Approach For Determining Individual's Covid-19 Risks

Agun, H. V. (2023) · Bilişim Teknolojileri Dergisi · doi:10.17671/gazibtd.1135014

Scientific management of subsistence materials during the COVID-19 outbreak in Changchun

Hu, H., Fan, L., & Wang, Q. (2023) · Highlights in Business Economics and Management · doi:10.54097/hbem.v12i.8387

Hazardous Influential Node Identification in Online Social Networks

Nedunchezhian, P., Karunanithy, K., Bhuvaneswari, M., Mahalingam, M., & Rashid, T. A. (2023) · Journal of the Institution of Electronics and Telecommunication Engineers · doi:10.1080/03772063.2023.2234870

MONOPOLI: A Customizable Model for Forecasting COVID-19 Around the World Using Alternative Nonpharmaceutical Intervention Policy Scenarios, Human Movement Data, and Regional Demographics

Arehart, C. H., Arehart, J. H., David, M. Z., D’Amico, B., Sozzi, E., Dukić, V., & Pomponi, F. (2023) · Springer eBooks · doi:10.1007/978-3-030-93954-0_2-1

STAR: Spread of innovations on graph structures with the Susceptible‐Tattler‐Adopter‐Removed model

Parviero, R., Hellton, K. H., Canright, G., & Scheel, I. (2024) · Stat · doi:10.1002/sta4.671

Crafting 10 Years of Statistics Explanations: Points of Significance

Altman, N., & Krzywinski, M. I. (2024) · Annual Review of Statistics and Its Application · doi:10.1146/annurev-statistics-112723-034555

Infektionsepidemiologie: eine Einführung in Methoden, Modelle und Kennzahlen

Salzberger, B. (2024) · Krankenhaushygiene up2date · doi:10.1055/a-2305-9374

LRCu: A High-Performance Parallel Program for Identifying Hub Genes

Liu, J., & Ji, X. (2024) · International Congress on Image and Signal Processing (CISP) · doi:10.1109/cisp-bmei64163.2024.10906138

Modélisation de la dynamique de la COVID-19, de la dengue et de l’établissement de Wolbachia dans les populations d’Aedes aegypti en Nouvelle-Calédonie

Ochida, N. (2023) · theses.fr (ABES) · doi:10.70675/b6368863z7bbfz49d3za1f3zce37fc726fd3

Epidemic wave dynamics of music virality on online social platforms

Oliveira, G. P., Vassio, L., da Silva, A. P. C., & Moro, M. M. (2026) · Social Network Analysis and Mining · doi:10.1007/s13278-026-01607-2

Groups Model (GM) of Spread of Infection in a Population

Аманбаев, Т. Р. (2026) · Journal of Engineering Physics and Thermophysics · doi:10.1007/s10891-026-03422-0

On the Modelling of Epidemics

Castillo‐Chávez, C., Cooke, K. L., & Levin, S. A. (1989) · Cited by 3

Modeling Epidemics, Bioterror

Hampton, T. (2004) · JAMA · doi:10.1001/jama.291.24.2933-d · Cited by 1

Editorial: Mathematical modeling of infectious disease dynamics

Siettos, C. I. (2016) · Virulence · doi:10.1080/21505594.2016.1150402 · Cited by 1

Longitudinal assessment of hormonal and physical alterations during normal puberty in boys. VI. Modeling of growth velocity, mean growth hormone (GH mean), and serum testosterone (T) concentrations

Zhang, J., Peddada, S. D., Malina, R. M., & Rogol, A. D. (2000) · American Journal of Human Biology · doi:10.1002/1520-6300(200011/12)12:6 · Cited by 22

On the mathematical modeling of epidemics caused by infectious diseases

Cunha, A., Tosin, M., & Basilio, J. (2021) · doi:10.13140/rg.2.2.27928.26884