A model for COVID-19 and bacterial pneumonia coinfection with community- and hospital-acquired infections

Pérez, Ángel; Oluyori, David A.

doi:10.53391/mmnsa.2022.016

Cited by 18 publications

(12 citation statements)

References 37 publications

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“…However, several analytical solutions of SIR and SEIRD models obtained by different analytical methods are available in the literature. By comparing the proposed models in this paper with those previously introduced (see, e.g., previous studies [39][40][41][42]), the proposed models are more generalized with fractional-order derivatives. Further, most of the solutions for epidemic models are numerical (see, e.g., previous studies [43][44][45]), so analytical exact or approximate solutions are rarely available.…”

Section: Discussionmentioning

confidence: 94%

Conformable mathematical modeling of the COVID‐19 transmission dynamics: A more general study

Thabet

Kendre

2023

Math Methods in App Sciences

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Many challenges are still faced in bridging the gap between mathematical modeling and biological sciences. Measuring population immunity to assess the epidemiology of health and disease is a challenging task and is currently an active area of research. However, to meet these challenges, mathematical modeling is an effective technique in shaping the population dynamics that can help disease control. In this paper, we introduce a susceptible–infected–recovered (SIR) model and a susceptible–exposed–infected–recovered–deceased (SEIRD) model based on conformable space‐time partial differential equations (PDEs) for the coronavirus disease 2019 (COVID‐19) pandemic. As efficient analytical tools, we present new modifications based on the fractional exponential rational function method (ERFM) and an analytical technique based on the Adomian decomposition method for obtaining the solutions for the proposed models. These analytical approaches are more efficacious for obtaining analytical solutions for nonlinear systems of PDEs with conformable derivatives. The interesting result of this paper is that it yields new exact and approximate solutions to the proposed COVID‐19 pandemic models with conformable space‐time partial derivatives.

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Section: Discussionmentioning

confidence: 94%

Conformable mathematical modeling of the COVID‐19 transmission dynamics: A more general study

Thabet

Kendre

2023

Math Methods in App Sciences

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“…39 Given the advances in other infectious disease modeling, we acknowledge tradeoffs in data availability on community prevalence, biological understanding, and research efforts. Transmission models of other pathogens, especially ones that cause respiratory infections and circulate widely in the community, such as in uenza 40 , pertussis 41 , MDR-tuberculosis 42 , and, more recently, SARS-CoV-2 43,44 , have included the community-hospital interface due to their importance in the disease dynamics and their contributions to nosocomial infections. Household transmissions can be modeled when epidemiological data becomes available, which was the case for SARS-CoV-245.…”

Section: Challenges and Gaps In Modeling Transmission Of Haicausing P...mentioning

confidence: 99%

The Contribution of Community Transmission to the Burden of Hospital-associated Pathogens: A Systematic Scoping Review of Epidemiological Models

Lin,

Poleon,

Hamilton

et al. 2024

Preprint

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Healthcare-associated infections (HAI), particularly those involving multi-drug resistant organisms (MDRO), pose a significant public health threat. Understanding the transmission of these pathogens in short-term acute care hospitals (STACH) is crucial for effective control. Mathematical and computational models play a key role in studying transmission but often overlook the influence of long-term care facilities (LTCFs) and the broader community on transmission. In a systematic scoping review of 8,811 studies from 2016 to 2022, we explored the modeling landscape of the hospital-community interface in HAI-causing pathogen transmission. Among the 29 eligible studies, 27% (n=8) exclusively modeled LTCFs, 45% (n=13) focused on non-healthcare-related community settings, and 31% (n=9) considered both settings. Studies emphasizing screening and contact precautions were more likely to include LTCFs but tended to neglect the wider community. This review emphasizes the crucial need for comprehensive modeling that incorporates the community's impact on both clinical and public health outcomes.

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“…However, the mathematical model to examine the impact of various physiological parameters that disturb nerve cells and invite neurodegenerative conditions has been studied in the given literature [24][25][26][27][28][29][30][31][32][33][34][35]. The co-dynamics of COVID-19 with diabetes [36], comorbidity [37], bacterial pneumonia [38], and tuberculosis [39] are proposed and analyzed.…”

Section: Introductionmentioning

confidence: 99%

Mechanistic insights of COVID-19 dynamics by considering the influence of neurodegeneration and memory trace

Joshi

2024

Phys. Scr.

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COVID-19 has been declared a global pandemic as it disturbs education, society, agriculture, the economy, poverty, death rate, social development, mental psychology, and many more. Neurodegenerative disease is a brain disorder associated with several pathological factors along with mental psychology. This paper introduces a mathematical model to inspect mechanistic insights into COVID-19 dynamics by considering the influence of neurodegeneration and memory trace. The analysis of the proposed model and the existence and uniqueness of the model are derived using the ﬁxed-point criteria. A numerical experiment is presented to validate the theoretical results and examine the impact of various biological parameters, the influence of neurodegeneration, and memory trace on the transmission dynamics of COVID-19.

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A model for COVID-19 and bacterial pneumonia coinfection with community- and hospital-acquired infections

Cited by 18 publications

References 37 publications

Conformable mathematical modeling of the COVID‐19 transmission dynamics: A more general study

Conformable mathematical modeling of the COVID‐19 transmission dynamics: A more general study

The Contribution of Community Transmission to the Burden of Hospital-associated Pathogens: A Systematic Scoping Review of Epidemiological Models

Mechanistic insights of COVID-19 dynamics by considering the influence of neurodegeneration and memory trace

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