# A narrative review of heterogeneity in SARS-CoV-2 infection outcomes and vaccine efficacy: strategizing pandemic preparedness in Africa

**Authors:** Trisha Kerai, Mark Woolhouse, Norman Z. Nyazema, Francisca Mutapi

PMC · DOI: 10.3389/fpubh.2026.1761547 · 2026-02-03

## TL;DR

This review explores why Africa had fewer severe SARS-CoV-2 cases and how pre-existing immunity and other factors affect vaccine responses and pandemic preparedness.

## Contribution

The paper highlights the need for more immunology studies to understand how pre-existing immunity influences vaccine efficacy and pandemic outcomes in Africa.

## Key findings

- Africa had fewer SARS-CoV-2 hospitalizations and deaths than expected, possibly due to factors like age demographics and pre-existing immunity.
- Pre-existing immunity can both enhance and interfere with vaccine responses through mechanisms like original antigenic sin.
- Understanding immune heterogeneity is crucial for improving vaccine development and pandemic preparedness.

## Abstract

Disease epidemiology during the COVID-19 pandemic differed greatly across the globe. In contrast to early pandemic predictions, Africa recorded the fewest SARS-CoV-2 related hospitalizations and deaths. Hypotheses proposed to explain this paradox include underreporting, age demographics, climate, national mitigation strategies, lifestyle factors, pre-existing cross-reactive protection, and host genetic determinants. This traditional, narrative review evaluates these hypotheses investigated in the published literature, and highlights knowledge gaps which limit our understanding and obscure validation of potential explanations. It also discusses how responses to vaccines, the primary intervention sought to control infectious disease outbreaks, may vary both within the African population and across other continents. Potential explanations in the literature include pre-existing immunity, poor nutrition, immune modulating co-infections, comorbidities, microbiome composition, genetic polymorphisms, and demographic factors. Previous studies have shown that pre-existing (infection-derived) immunity or cross-reactive immune responses can augment vaccine-elicited positive responses and can protect against reinfection in a way similar to immunization. Conversely, there are also studies showing that prior immunity interferes with the efficacy of new vaccines through mechanisms like original antigenic sin and immune imprinting. Thus, there is need for more immunology studies to understand the relative contribution of pre-existing cross-reactive immune responses to the epidemiology of new pathogens. These studies are particularly essential to understand the differences between pandemic preparedness and population vulnerability, as well as to inform vaccine development and vaccine effectiveness monitoring studies. SARS-CoV-2 serves as an important case study to understand heterogeneity between and within populations in immune responses to both the pathogen and to vaccination. This understanding is crucial in informing vaccine research and development aimed at supporting the 100-day mission for when the next pandemic threat emerges.

## Linked entities

- **Diseases:** SARS-CoV-2 (MONDO:0100096), COVID-19 (MONDO:0100096)

## Full-text entities

- **Genes:** ACE2 (angiotensin converting enzyme 2) [NCBI Gene 59272] {aka ACEH}, TP53 (tumor protein p53) [NCBI Gene 7157] {aka BCC7, BMFS5, LFS1, P53, TRP53}, S (surface glycoprotein) [NCBI Gene 43740568] {aka spike glycoprotein}, APOE (apolipoprotein E) [NCBI Gene 348] {aka AD2, APO-E, ApoE4, LDLCQ5, LPG}, ABO (ABO, alpha 1-3-N-acetylgalactosaminyltransferase and alpha 1-3-galactosyltransferase) [NCBI Gene 28] {aka A3GALNT, A3GALT1, GTA, GTB, NAGAT}, HLA-A (major histocompatibility complex, class I, A) [NCBI Gene 3105] {aka HLAA}, CRP (C-reactive protein) [NCBI Gene 1401] {aka PTX1}
- **Diseases:** iron deficiency (MESH:D000090463), food insecurity (MESH:D005517), non-communicable diseases (MESH:D000073296), cholera (MESH:D002771), obesity (MESH:D009765), lymphopenia (MESH:D008231), diabetes (MESH:D003920), schistosomiasis (MESH:D012552), influenza (MESH:D007251), respiratory diseases (MESH:D012140), coronary heart disease (MESH:D003327), respiratory infectious diseases (MESH:D012141), inflammatory (MESH:D007249), chronic liver disease (MESH:D008107), yellow fever (MESH:D015004), pertussis (MESH:D014917), infectious (MESH:D003141), HIV (MESH:D015658), malaria (MESH:D008288), diphtheria (MESH:D004165), rotavirus (MESH:D012400), Anaemia (MESH:D000743), polio (MESH:D011051), tuberculosis (MESH:D014376), measles (MESH:D008457), underweight (MESH:D013851), cardiovascular diseases (MESH:D002318), helminth infections (MESH:D007239), COVID-19 (MESH:D000086382), hypertension (MESH:D006973), malnourished (MESH:D044342), death (MESH:D003643), co-infections (MESH:D060085)
- **Chemicals:** iron (MESH:D007501), zinc (MESH:D015032), folic acid (MESH:D005492), calcium (MESH:D002118), selenium (MESH:D012643), potassium (MESH:D011188), vitamins A, E, K, and D (-)
- **Species:** Human immunodeficiency virus 1 (no rank) [taxon 11676], Gammacoronavirus (genus) [taxon 694013], Severe acute respiratory syndrome coronavirus 2 (no rank) [taxon 2697049], Schistosoma mansoni (species) [taxon 6183], Mus musculus (house mouse, species) [taxon 10090], Orthocoronavirinae (subfamily) [taxon 2501931], Middle East respiratory syndrome-related coronavirus (no rank) [taxon 1335626], Ebola virus (no rank) [taxon 1570291], gut metagenome (species) [taxon 749906], Plasmodium falciparum (malaria parasite P. falciparum, species) [taxon 5833], Homo sapiens (human, species) [taxon 9606]

## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12909571/full.md

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Source: https://tomesphere.com/paper/PMC12909571