Individuals under 65 years may be the predominant drivers of COVID-19 in West Africa

In a recent study posted to the medRxiv* preprint server, researchers evaluated the effects of age structure and vaccine prioritization regarding coronavirus disease 2019 (COVID-19) in West Africa (WA).

Study: Impact of age-structure and vaccine prioritization on COVID-19 in West Africa. Image Credit: NTL studio/Shutterstock
Study: Impact of age-structure and vaccine prioritization on COVID-19 in West Africa. Image Credit: NTL studio/Shutterstock

The COVID-19 pandemic has adversely impacted countries in every region of the world. The African continent has witnessed fewer devastating effects than other regions. The demographic distribution, epidemiological disparities, low detection rate, and timely implementation of non-pharmaceutical interventions (NPIs) like social distancing, quarantine/isolation of suspected/confirmed cases, travel bans, etc., might explain the observed variations in case burden across different settings.

Given the population demographics and socio-economic structure of countries in WA, pharmaceutical interventions like anti-viral medication and vaccines are crucial and a favorable strategy to curb the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Mathematical models have been instrumental in providing comprehensive insights into COVID-19 dynamics, helping inform various policies and interventions.

The study and findings

In the present study, researchers formulated a mathematical framework accounting for age structure and vaccination to estimate the contribution of the older and younger population to COVID-19 incidence in WA. The authors developed three compartmental models for SARS-CoV-2 transmission dynamics in WA.  

The first model (basic model) was based on an extended Kermack-Mckenderick type framework and divided the human population based on disease and vaccination status into nine distinct classes – latent, vaccinated susceptible, unvaccinated susceptible, pre-symptomatic infectious, asymptomatic infectious, symptomatic infectious, confirmed cases, hospitalized, and recovered.

Model-2 was an extension of the basic model and was obtained by stratifying the population into vaccinated (Nv) and non-vaccinated (Nu) cohorts. These two cohorts were further sub-divided similarly to the basic model. The third model (model-3) was an integrated/hybrid model. Model-3 was obtained by extending model-2 to account for age structure. Two age groups were defined based on the risk of COVID-19. The first group comprised individuals < 65 years (adult-youth), whereas the second group had people aged ≥ 65 years (elderly adults).

Some parameters of all three models were available in the literature, and others were unknown, which were estimated by fitting the corresponding model to daily COVID-19 case data for 16 countries in WA. A simplified basic model version without vaccination was fitted to data for the pre-vaccine period to integrate the entire COVID-19 data from February 28, 2020, to May 24, 2022. Model fitting and parameter estimation were performed using a non-linear least-squares algorithm.

The research team performed a global uncertainty and sensitivity analysis using Latin hypercube sampling (LHS) and partial rank correlation coefficient (PRCC). They noted that the variability in community transmission and recovery rates of asymptomatic infectious individuals and the detection rates of symptomatic infectious individuals generated the highest uncertainty in the peak COVID-19 cases in WA.

This showed that asymptomatic infectious subjects, particularly those below 65 years, were the leading drivers of COVID-19 in WA. Next, the models were simulated to analyze the impact of control measures, vaccination, relaxation of control measures, and newer SARS-CoV-2 variants. Simulation results of model-1 indicated that at least 84% of the WA population had to be fully vaccinated with vaccines available in WA to reduce the control reproduction number (Rc) to less than 1. Lower vaccination coverage(s) was required with model-2 (73%) and model-3 (68%).

The researchers reported that reducing Rc to below one was impossible by vaccinating only the young or the adult population, even when complemented with a 20% increase in the use of masks unless the daily vaccination rate was exceptionally high. Nevertheless, the disease could be contained if both youth and older adults were vaccinated at specific target rates.

Vaccination appeared to impact the peak number of daily cases significantly. If the vaccination rate were maintained at baseline (5000 people vaccinated/day) in model-1, multiple COVID-19 waves would occur, with the next wave reaching the peak by mid-November 2022. If the rate was increased to 1.2 million/day, then a 14% reduction in baseline peak cases would result as per model-1 and a 21% reduction with model-2.

Notably, increasing the vaccination rate of young adults resulted in a greater reduction of the peak size, albeit the higher vaccination of both age groups remains critical to controlling SARS-CoV-2 spread. The researchers observed that reinforcing the transmission control strategies could prevent future COVID-19 waves, whereas relaxing the existing control measures would result in new waves of infection.

Conclusion

In this study, researchers developed, parameterized, and analyzed a compartmental mathematical framework for evaluating transmission dynamics of COVID-19 with different vaccination strategies. The findings indicated that people below 65 years were the predominant drivers of COVID-19 in WA.

Significantly, the authors noted that prioritizing a vaccine with high efficacy would increase the prospects of curtailing the disease. Additionally, the emergence of a new SARS-CoV-2 variant or relaxing existing control measures in WA would cause a more devastating wave of SARS-CoV-2 infections. Overall, advances in current control measures are imperative to ameliorate the COVID-19 pandemic.

*Important notice

medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Journal reference:

Taboe HB, Asare-Baah M, Yesmin A, Ngonghala CN. (2022). Impact of age-structure and vaccine prioritization on COVID-19 in West Africa. medRxivdoi:10.1101/2022.07.03.22277195

Tarun Sai Lomte

Written by

Tarun Sai Lomte

Tarun is a writer based in Hyderabad, India. He has a Master’s degree in Biotechnology from the University of Hyderabad and is enthusiastic about scientific research. He enjoys reading research papers and literature reviews and is passionate about writing.

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