ArticleChaos, solitons, and fractals2022
Towards predicting COVID-19 infection waves: A random-walk Monte Carlo simulation approach.
Article in Chaos, solitons, and fractals, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed.
- Confronting the known unknown: historical lessons and future strategies for Disease X.Frontiers in public health · 2026Review
- Stochastic modelling of viral infection spread via a Partial Integro-Differential Equation.Infectious Disease Modelling · 2025Article
- Human activity-aware coverage path planning for robot-based mosquito control.Scientific reports · 2025Article
- How Does Vaccine-Induced Immunity Compare to Infection-Acquired Immunity in the Dynamics of COVID-19?Pathogens (Basel, Switzerland) · 2025Article
- Plausible explanation for the third COVID-19 wave in India and its implications.Infectious Disease Modelling · 2023Article
- Stochastic SIR model predicts the evolution of COVID-19 epidemics from public health and wastewater data in small and medium-sized municipalities: A one year study.Chaos, solitons, and fractals · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Phenomenological and deterministic models are often used for the estimation of transmission parameters in an epidemic and for the prediction of its growth trajectory. Such analyses are usually based on single peak outbreak dynamics. In light of the present COVID-19 pandemic, there is a pressing need to better understand observed epidemic growth with multiple peak structures, preferably using first-principles methods. Along the lines of our previous work [Physica A
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.