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In this paper we use data from waves 1–5 of NIDS-CRAM to investigate labour market outcomes in 2020/1 for four age groups: youth (aged 18–24), prime-age adults (aged 25–39), middle-age adults (aged 40–54) and older adults (aged 55–64). We contrast outcomes just before and just after the advent of the COVID-19 pandemic and lockdown (February and April 2020) with outcomes one year later (March 2021), and study transitions between the periods. We find that although the NIDS-CRAM employment-to-population ratio was near identical in February 2020 and March 2021 (56.4% versus 56.6%), there had been extensive churning between the two periods. By March 2021, 23% of the February 2020 employed had lost work and 30% of the non-employed had found work. Amidst these changes, youth experienced the largest employment-to-population ratio increase, while older adults suffered the largest decrease in employment and a decline in participation rates (changes not statistically significant). [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]