A Model for the Lifespan Loss Due to a Viral Disease: Example of the COVID-19 Outbreak

Abstract

The end of the acute phase of the COVID-19 pandemic is near in some countries as declared by World Health Organization (WHO) in January 2022 based on some studies in Europe and South Africa despite unequal distribution of vaccines to combat the disease spread globally. The heterogeneity in individual age and the reaction to biological and environmental changes that has been observed in COVID-19 dynamics in terms of different reaction to vaccination by age group, severity of infection per age group, hospitalization and Intensive Care Unit (ICU) records show different patterns, and hence, it is important to improve mathematical models for COVID-19 pandemic prediction to account for different proportions of ages in the population, which is a major factor in epidemic history. We aim in this paper to estimate, using the Usher model, the lifespan loss due to viral infection and ageing which could result in pathological events such as infectious diseases. Exploiting epidemiology and demographic data firstly from Cameroon and then from some other countries, we described the ageing in the COVID-19 outbreak in human populations and performed a graphical representation of the proportion of sensitivity of some of the model parameters which we varied. The result shows a coherence between the orders of magnitude of the calculated and observed incidence numbers during the epidemic wave, which constitutes a semi-quantitative validation of the mathematical modelling approach at the population level. To conclude, the age heterogeneity of the populations involved in the COVID-19 outbreak needs the consideration of models in age groups with specific susceptibilities to infection.

Prediction analysis of the length of time for changes in the status of positive patients for covid-19 delta and omicron variants using the markov chain model

“…This indicates a decrease in life expectancy due to COVID-19. Similar results were obtained using the Usher projection matrix model that represents the life cycle (Oshinubi et al, 2022), using the lifespan inequality (Aburto et al, 2021), using the life expectancy of the Continuous Renal Replacement Therapy (CRRT) filter (Legouis et al, 2021), using the calculation of life expectancy (Castro et al, 2021;Gibson & Olivia, 2020;Marois et al, 2020), and calculation of premature mortality or the number of years lost due to early death (years of potential life lost) (Islam et al, 2021).…”

“…These results are consistent and in line with the previous research. Previous research has shown that life expectancy, in general, will decline in 2020 and 2021, during the COVID-19 pandemic, compared to previous years (Aburto et al, 2021;Aburto et al, 2022;Gibson & Olivia, 2020;Heuveline, 2021;Legouis et al, 2021;Oshinubi et al, 2022). Meanwhile, in this research, it was seen that there was a decrease in the average remaining life span of someone infected with COVID-19 compared to healthy people.…”

mRNA COVID-19 Vaccines—Facts and Hypotheses on Fragmentation and Encapsulation

“…Current research is focused on further optimization of pegylated lipids or on the development of different stealth lipids, such as polysarcosine-conjugated lipids which show great promise [ 179 ]. To reduce the allergic effects, in-depth studies could be carried out on the population to be vaccinated in order to personalize the recall and booster policies [ 180 , 181 ] by targeting sub-populations at risk, specified by identifying their risk factors (allergy, age, history families, comorbidities, geo-climatic and socio-economic environment [ 182 , 183 , 184 , 185 , 186 , 187 , 188 , 189 , 190 , 191 , 192 , 193 , 194 ]).…”

Desk Review on COVID-19 Pandemic in Sub-Sahara Africa: The Challenges and Proffered Solutions

“…In cases of disease outbreaks such as the COVID-19 pandemic, studying the African setting is crucial because of the continent's unique cultural landscape. In lieu of this, studies from South Africa (Oshinubi et al, 2022, Oloniiju et al, 2022) created a mathematical model of the COVID-19 dynamic in their work, focusing on control strategies that are workable in an African environment. With regards to establishing control strategies, Adeniran et al (2021) studied the interaction of sneeze and cough droplets with indoor air of a regular African hospital clinic to investigate the feasibility of adopted protocols and guidelines to control the spread of COVID-19 transmission using numerous threedimensional coupled Discrete Phase Models, shown below.…”