1.
|
Anthony M. Pasion, Juancho A. Collera,
2019,
2184,
0094-243X,
060013,
10.1063/1.5136445
|
|
2.
|
Mohammad A. Safi, Salisu M. Garba,
Global Stability Analysis of SEIR Model with Holling Type II Incidence Function,
2012,
2012,
1748-670X,
1,
10.1155/2012/826052
|
|
3.
|
Isam Al-Darabsah, Yuan Yuan,
A Stage-Structured Mathematical Model for Fish Stock with Harvesting,
2018,
78,
0036-1399,
145,
10.1137/16M1097092
|
|
4.
|
Isaac Mwangi Wangari, Lewi Stone, Nakul Chitnis,
Backward bifurcation and hysteresis in models of recurrent tuberculosis,
2018,
13,
1932-6203,
e0194256,
10.1371/journal.pone.0194256
|
|
5.
|
Abderrazak Nabti, Behzad Ghanbari,
Global stability analysis of a fractional SVEIR epidemic model,
2021,
0170-4214,
10.1002/mma.7285
|
|
6.
|
Yoshiaki Muroya, Yoichi Enatsu, Huaixing Li,
A note on the global stability of an SEIR epidemic model with constant latency time and infectious period,
2013,
18,
1553-524X,
173,
10.3934/dcdsb.2013.18.173
|
|
7.
|
D. Breda, O. Diekmann, W. F. de Graaf, A. Pugliese, R. Vermiglio,
On the formulation of epidemic models (an appraisal of Kermack and McKendrick),
2012,
6,
1751-3758,
103,
10.1080/17513758.2012.716454
|
|
8.
|
Anjana Das, M. Pal,
Modeling and Analysis of an Imprecise Epidemic System with Optimal Treatment and Vaccination Control,
2018,
13,
1793-0480,
37,
10.1142/S1793048018500042
|
|
9.
|
Yoichi Enatsu, Yukihiko Nakata,
Stability and bifurcation analysis of epidemic models with saturated incidence rates: An application to a nonmonotone incidence rate,
2014,
11,
1551-0018,
785,
10.3934/mbe.2014.11.785
|
|
10.
|
Bruno Buonomo, Marianna Cerasuolo,
The effect of time delay in plant--pathogen interactions with host demography,
2015,
12,
1551-0018,
473,
10.3934/mbe.2015.12.473
|
|
11.
|
Anjana Das, M. Pal,
A mathematical study of an imprecise SIR epidemic model with treatment control,
2018,
56,
1598-5865,
477,
10.1007/s12190-017-1083-6
|
|
12.
|
Isam Al-Darabsah, Yuan Yuan,
A periodic disease transmission model with asymptomatic carriage and latency periods,
2018,
77,
0303-6812,
343,
10.1007/s00285-017-1199-1
|
|
13.
|
Mohamed El Fatini, Idriss Sekkak,
Lévy noise impact on a stochastic delayed epidemic model with Crowly–Martin incidence and crowding effect,
2020,
541,
03784371,
123315,
10.1016/j.physa.2019.123315
|
|
14.
|
Global stability for epidemic
model with constant latency and infectious periods,
2012,
9,
1551-0018,
297,
10.3934/mbe.2012.9.297
|
|
15.
|
Dimitri Breda, Stefano Maset, Rossana Vermiglio,
Numerical recipes for investigating endemic equilibria of age-structured SIR epidemics,
2012,
32,
1553-5231,
2675,
10.3934/dcds.2012.32.2675
|
|
16.
|
Xavier Bardina, Marco Ferrante, Carles Rovira,
Stochastic Epidemic SEIRS Models with a Constant Latency Period,
2017,
14,
1660-5446,
10.1007/s00009-017-0977-8
|
|
17.
|
A M Pasion, J A Collera,
Delay-induced stability switches in an SIRS epidemic model with saturated incidence rate and temporary immunity,
2019,
1298,
1742-6588,
012006,
10.1088/1742-6596/1298/1/012006
|
|
18.
|
Luca Dell’Anna,
Solvable delay model for epidemic spreading: the case of Covid-19 in Italy,
2020,
10,
2045-2322,
10.1038/s41598-020-72529-y
|
|
19.
|
Muhammad Shoaib, Adeeba Haider, Muhammad Asif Zahoor Raja, Kottakkaran Sooppy Nisar,
Artificial intelligence knacks-based computing for stochastic COVID-19 SIRC epidemic model with time delay,
2022,
36,
0217-9792,
10.1142/S0217979222501740
|
|
20.
|
Ritwik Bhaduri, Ritoban Kundu, Soumik Purkayastha, Michael Kleinsasser, Lauren J. Beesley, Bhramar Mukherjee, Jyotishka Datta,
Extending the susceptible‐exposed‐infected‐removed (SEIR) model to handle the false negative rate and symptom‐based administration of COVID‐19 diagnostic tests:
SEIR‐fansy
,
2022,
41,
0277-6715,
2317,
10.1002/sim.9357
|
|
21.
|
Jasmina Đorđević, Bojana Jovanović,
Dynamical analysis of a stochastic delayed epidemic model with lévy jumps and regime switching,
2023,
360,
00160032,
1252,
10.1016/j.jfranklin.2022.12.009
|
|
22.
|
Sarita Bugalia, Jai Prakash Tripathi, Hao Wang,
Mathematical modeling of intervention and low medical resource availability with delays: Applications to COVID-19 outbreaks in Spain and Italy,
2021,
18,
1551-0018,
5865,
10.3934/mbe.2021295
|
|
23.
|
Qiubao Wang, Hao Wu,
There exists the “smartest” movement rate to control the epidemic rather than “city lockdown”,
2022,
106,
0307904X,
696,
10.1016/j.apm.2022.02.018
|
|
24.
|
Maximilian Pawleta, Susanne Kiefer, Edeltraud Gehrig,
Visualization of relevant parameter dependencies in a delay SEIQ epidemic model — A live script program for didactic and interactive demonstrations,
2023,
14,
1793-9623,
10.1142/S1793962323500423
|
|
25.
|
Md. Mamun-Ur-Rashid Khan, Md. Rajib Arefin, Jun Tanimoto,
Time delay of the appearance of a new strain can affect vaccination behavior and disease dynamics: An evolutionary explanation,
2023,
24680427,
10.1016/j.idm.2023.06.001
|
|
26.
|
Jiapu Zhang,
2023,
Chapter 28,
978-3-031-36772-4,
897,
10.1007/978-3-031-36773-1_28
|
|
27.
|
Nuning Nuraini, Fadiya Nadhilah Soekotjo, Almira Alifia, Kamal Khairudin Sukandar, Bony Wiem Lestari,
Assessing potential surge of COVID-19 cases and the need for booster vaccine amid emerging SARS-CoV-2 variants in Indonesia: A modelling study from West Java,
2023,
9,
24058440,
e20009,
10.1016/j.heliyon.2023.e20009
|
|
28.
|
A. Ben Lahbib, L. Azrar,
Time delay and nonlinear incidence effects on the stochastic SIRC epidemic model,
2024,
11,
23129794,
84,
10.23939/mmc2024.01.084
|
|
29.
|
Jing Zhang, Tong Jin,
A Stochastic Semi-Parametric SEIR Model with Infectivity in an Incubation Period,
2024,
12,
2227-7390,
1580,
10.3390/math12101580
|
|