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Samuel Iddi

Researcher at University of Ghana

Publications -  54
Citations -  566

Samuel Iddi is an academic researcher from University of Ghana. The author has contributed to research in topics: Overdispersion & Medicine. The author has an hindex of 12, co-authored 44 publications receiving 358 citations. Previous affiliations of Samuel Iddi include Katholieke Universiteit Leuven & University of Southern California.

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Mathematical modelling of earlier stages of COVID-19 transmission dynamics in Ghana

TL;DR: In this paper , a modified SEIR compartmental model with nine compartments (CoVCom9) was developed to describe the dynamics of SARS-CoV-2 transmission in Ghana.
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Bayesian latent time joint mixed-effects model of progression in the Alzheimer's Disease Neuroimaging Initiative.

TL;DR: It is shown that long‐term disease dynamics from cognitively healthy to dementia using data from the Alzheimer's Disease Neuroimaging Initiative is similar to that from the previous studies.
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Estimating the Evolution of Disease in the Parkinson's Progression Markers Initiative.

TL;DR: Results reveal that, even though diagnostic category was not included in the model, it seems to accurately reflect the temporal ordering of the disease state consistent with diagnosis categorization at baseline, and results indicated that the specific binding ratio on striatum and the total Unified Parkinson’s Disease Rating Scale show high discriminability between disease stages.
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Coping strategies adapted by Ghanaians during the COVID-19 crisis and lockdown: A population-based study.

TL;DR: In this paper, the authors examined how people are coping with the COVID-19 crisis in Ghana and identified factors influencing it, including financial security and optimism about the disease, praying and sleeping more during the pandemic than before reduces one's chances of coping well.
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Mathematical modeling of COVID-19 infection dynamics in Ghana: Impact evaluation of integrated government and individual level interventions.

TL;DR: In this article, the SEIQHRS model was proposed to predict the trajectory of the COVID-19 pandemic in Ghana and the effective basic reproductive number (Re) was estimated in real-time using three different estimation procedures and simulated worse case epidemic scenarios and the impact of integrated individual and government interventions on the epidemic in the long term using compartmental models.