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H. Christian Tsoungui Obama

Publications -  6
Citations -  24

H. Christian Tsoungui Obama is an academic researcher. The author has contributed to research in topics: Herd immunity & Immunology. The author has an hindex of 2, co-authored 2 publications receiving 6 citations.

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Preventing COVID-19 spread in closed facilities by regular testing of employees - an efficient intervention in long-term care facilities and prisons

TL;DR: These measures provide an economically meaningful way to protect vulnerable risk groups characterized by an elevated risk of severe infections in closed facilities, in which contact-reducing measures are difficult to implement due to imminent unavoidable close human-to-human contacts.
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Is increased mortality by multiple exposures to COVID-19 an overseen factor when aiming for herd immunity?

TL;DR: Simulations indicate that a potential second lockdown can substantially decrease the epidemic peak, the number of multi-infections and deaths, and underlines another facet questioning disease management strategies aiming for herd immunity in the COVID-19 pandemic.
Journal ArticleDOI

The many definitions of multiplicity of infection

TL;DR: A formal statistical framework is introduced and a concise definition of MOI and its distribution on the host-population level is suggested, showing how it relates to alternative definitions such as the number of distinct haplotypes within an infection or the maximum number of alleles detectable across a set of genetic markers.
Journal ArticleDOI

A maximum-likelihood method to estimate haplotype frequencies and prevalence alongside multiplicity of infection from SNP data

TL;DR: A statistical framework to obtain maximum-likelihood estimates (MLE) of haplotype frequencies and prevalence alongside MOI from malaria SNP data, i.e., multiple biallelic marker loci is introduced and can be applied to any infectious disease with similar transmission behavior.
Posted ContentDOI

Predicting the impact of COVID-19 vaccination campaigns - a flexible age-dependent, spatially-stratified predictive model, accounting for multiple viral variants and vaccines

TL;DR: A model designed to predict the effect of vaccination campaigns on the spread of viral variants is introduced and is capable of providing useful predictions for the COVID-19 pandemic, and hence provides a relevant tool for epidemic decision-making.