General SIR model for visible and hidden epidemic dynamics

To simulate hidden epidemic dynamics connected with asymptomatic and unregistered patients, a new general SIR model was proposed. For some cases, the analytical solutions of the set of 5 differential equations were found, which allow simplifying the parameter identification procedure. Two waves of the pertussis epidemic in England in 2023 and 2024 were simulated with the assumption of zero hidden cases. The accumulated and daily numbers of cases and the duration of the second wave were predicted with rather high accuracy. If the trend will not change, the monthly figure of 9 new pertussis cases (as it was in January-February 2023) can be achieved only in May 2025. The proposed approach can be recommended for both simulations and predictions of different epidemics.

Authors

Institutions

Publication Details

Journal
Frontiers in Artificial Intelligence
Published
2025-02-24
DOI
https://doi.org/10.3389/frai.2025.1559880
Citations
6
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
8.21
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

General SIR model for visible and hidden epidemic dynamics

Igor Nesteruk
6 citations
Frontiers in Artificial Intelligence
COVID-19 epidemiological studies
8.21
article

General SIR model for visible and hidden epidemic dynamics

Igor Nesteruk
article en
6 citations

Abstract

To simulate hidden epidemic dynamics connected with asymptomatic and unregistered patients, a new general SIR model was proposed. For some cases, the analytical solutions of the set of 5 differential equations were found, which allow simplifying the parameter identification procedure. Two waves of the pertussis epidemic in England in 2023 and 2024 were simulated with the assumption of zero hidden cases. The accumulated and daily numbers of cases and the duration of the second wave were predicted with rather high accuracy. If the trend will not change, the monthly figure of 9 new pertussis cases (as it was in January-February 2023) can be achieved only in May 2025. The proposed approach can be recommended for both simulations and predictions of different epidemics.

Frontiers in Artificial IntelligenceVol. 8
National Academy of Sciences of Ukraine (UA)
Openalex Percentile: Top 2%
COVID-19 epidemiological studies
8.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.