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Why Sub-Saharan Africa Outperformed in COVID-19 Severity

Investigating why Sub-Saharan Africa saw lower severe COVID-19 cases.

Perpetual Wanjiku, Benedict Orindi, John Kimotho, Shahin Sayed, Reena Shah, Mansoor Saleh, Jedidah Mwacharo, Christopher Maronga, Vivianne Olouch, Ann Karanu, Jasmit Shah, Zaitun Nneka, Lynette Isabella Ochola-Oyier, Abdirahman I. Abdi, Susanna Dunachie, Philip Bejon, Eunice Nduati, Francis M. Ndungu

― 6 min read


Africa's COVID-19 Africa's COVID-19 Response Uncovered surprising COVID-19 performance. Examining Sub-Saharan Africa's
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COVID-19, caused by the virus SARS-CoV-2, has affected millions worldwide. While the pandemic hit hard in many regions, Sub-Saharan Africa (SSA) reported fewer Severe cases and deaths compared to North America and Europe. This unexpected situation has raised questions about why some areas handle the virus better than others.

The Mystery of Lower Severity in SSA

Despite having less robust healthcare systems, SSA has shown lower rates of severe COVID-19. Some ideas floated about this mystery include:

  • Younger Population: SSA has a younger demographic, which may be less affected by severe disease.
  • Climate: Warmer weather and outdoor living might play a role.
  • Past Infections: Exposure to other infectious diseases may have conditioned the immune system.
  • Vaccines: Prior vaccinations like BCG could influence immune response.

While these points are interesting, they are still under investigation.

Understanding Immune Responses

When the body is infected, it launches a defense, including the production of Cytokines (small proteins) and Chemokines (signaling molecules). In the case of COVID-19, an uncontrolled release of these substances is often called a "cytokine storm." This storm can lead to serious complications, including organ failure and acute respiratory distress syndrome (ARDS).

Research has linked high levels of certain cytokines to severe COVID-19 outcomes. These include IL-1β, IL-6, TNF-α, and others. It’s like your immune system going a bit overboard and throwing a party that nobody wanted.

The Kenyan Study

To better grasp the immune response to COVID-19 in SSA, a study was conducted in Kenya. The researchers gathered blood samples from individuals in Nairobi, a busy urban area, and Kilifi, a quieter rural location. They wanted to compare how immune responses varied between those with mild and severe symptoms.

Study Design and Participants

Researchers collected samples from 188 patients diagnosed with COVID-19 between June 2020 and August 2022. The participants were categorized based on their symptoms into five groups: Asymptomatic, mild, moderate, severe, and critical. It turns out that the only severe cases were found in Nairobi, not Kilifi. Perhaps Kilifi residents had some secret sauce, but the researchers were unable to taste it.

Blood Sample Collection

Blood was taken from patients shortly after diagnosis and periodically over a month. The team measured cytokines and checked how immune cells responded to pieces of the virus. They also looked for interferon-gamma (IFN-γ), a vital player in the immune defense.

COVID-19 Severity Classification

Patients were classified into categories based on their symptoms—like a sorting hat but for diseases. Asymptomatic patients had no symptoms, while mild cases exhibited typical symptoms without difficulty breathing. Moderate cases showed respiratory infections but managed to keep oxygen levels up. Severe cases struggled with oxygen levels, and critical cases faced severe respiratory failure.

Immune Response Measurement

Plasma and PBMC Isolation

The blood was divided into plasma and peripheral blood mononuclear cells (PBMCs). Plasma is the liquid part of the blood that carries nutrients and proteins, while PBMCs include various immune cells. After separation, these samples were carefully stored for analysis.

Testing with Synthetic Peptides

To check how the immune cells reacted, the scientists exposed the PBMCs to synthetic pieces of the virus. This helps see if the immune cells are ready to fight off the invader if they encounter it for real. It’s like preparing soldiers for battle—except the soldiers are cells, and the battlefield is in the body.

Interferon Gamma ELISpot Assay

The researchers used a special test, called the ELISpot assay, to quantify the IFN-γ response of the immune cells. This test tells how well immune cells can recognize and respond to the virus. If more cells attack, then the immune system is doing its job.

Measuring Cytokine Levels

To understand the inflammatory response better, scientists measured the levels of 22 different cytokines and chemokines. This data gives insight into how the immune system is responding, and whether it’s doing so in a controlled or chaotic manner.

Results: Who's Winning the Immune Game?

Differences in Immune Response by Severity

As expected, different levels of immune responses were observed based on the severity of the disease. Asymptomatic patients had the highest levels of some immune responses, while severe patients had a more chaotic response with plenty of inflammatory cytokines. It seems that those who were asymptomatic were almost like cool cats who were unfazed by the virus.

Geographic Variations

When comparing Nairobi to Kilifi, researchers found significant differences. Asymptomatic patients in Kilifi had notably higher levels of immune responses to some virus pieces. So, while urban dwellers in Nairobi were busy fighting off the virus with a high number of cytokines, rural residents in Kilifi seemed to keep things chill.

Time Matters: Changes Over the Month

The study didn’t just look at one snapshot in time; they tracked how immune responses evolved over a month. This provided vital information about how the immune system changes as the disease progresses.

Changes in Immune Responses Over Time

In asymptomatic patients, the immune response remained steady. However, in severe cases, certain cytokines returned to baseline levels after a month. It's like a roller coaster: some highs and lows as the immune system reacts to the infection.

Higher Responses in Mild Cases

Mild and moderate cases showed more significant fluctuations in immune responses. It suggests that people who didn’t get severely ill had their Immune Systems working efficiently to keep the infection at bay.

Comparison of Cytokines and Immune Markers

Pro-Inflammatory Cytokines

In severe patients, pro-inflammatory cytokines began high but gradually declined. This is expected as the body stabilizes post-infection. In contrast, certain chemokines like MIP-1α and MCP-1 increased over time, possibly indicating a persistent immune response needed to recruit additional immune cells to help fight the infection.

SDF-1α and Its Possible Role

SDF-1α was found at elevated levels among asymptomatic patients. This chemokine helps in recruiting immune cells and may play a protective role against developing severe disease. It’s like an all-star coach getting all the best players on the field for a winning team.

Conclusion: What Did We Learn?

This study sheds light on how different immune responses might explain why SSA had lower rates of severe COVID-19. While urban areas like Nairobi faced harsher responses, rural areas like Kilifi had more balanced immune reactions.

Key Takeaways

  • Cytokine Storms: Severe cases experienced chaotic cytokine responses linked to worse outcomes.
  • Geographic Variations: Differences in immune responses highlight how location may affect disease severity.
  • Protective Immune Responses: Certain markers, like SDF-1α, may help prevent severe disease and could offer insights for future treatments.

Final Thoughts

Although this study has opened doors to understanding COVID-19 responses, much remains to be explored. More research is needed to confirm these findings and potentially apply strategies to help manage future pandemics. For now, it seems that keeping a cool head—much like the asymptomatic folks in Kilifi—might just be the key to weathering the storm of infections.

Original Source

Title: Induction of an early IFN-γ cellular response and high plasma levels of SDF-1α are inversely associated with COVID-19 severity and residence in rural areas in Kenyan patients

Abstract: IntroductionCOVID-19 was less severe in Sub-Saharan Africa (SSA) compared with Europe and North America. It is unclear whether these differences could be explained immunologically. Here we determined the levels of ex vivo SARS-CoV-2 peptide-specific IFN-{gamma} producing cells, and levels of plasma cytokines and chemokines over the first month of COVID-19 diagnosis among Kenyan COVID-19 patients from urban and rural areas. MethodsBetween June 2020 and August 2022, we recruited and longitudinally monitored 188 COVID-19 patients from two regions in Kenya, Nairobi (urban, n = 152) and Kilifi (rural, n = 36), with varying levels of disease severity - severe, mild/moderate, and asymptomatic. IFN-{gamma} secreting cells were enumerated at 0-, 7-, 14- and 28-days post diagnosis by an ex vivo enzyme-linked immunospot (ELISpot) assay following in vitro stimulation of peripheral blood mononuclear cells (PBMCs) with overlapping peptides from several SARS-CoV-2 proteins. A multiplexed binding assay was used to measure the levels of 22 plasma cytokines and chemokines. ResultsHigher frequencies of IFN-{gamma}-secreting cells against the SARS-CoV-2 spike peptides were observed on the day of diagnosis among the asymptomatic compared to the patients with severe COVID-19. Higher concentrations of 17 of the 22 cytokines and chemokines measured were positively associated with severe disease, and in particular interleukin (IL)-8, IL-18 and IL-1ra (p

Authors: Perpetual Wanjiku, Benedict Orindi, John Kimotho, Shahin Sayed, Reena Shah, Mansoor Saleh, Jedidah Mwacharo, Christopher Maronga, Vivianne Olouch, Ann Karanu, Jasmit Shah, Zaitun Nneka, Lynette Isabella Ochola-Oyier, Abdirahman I. Abdi, Susanna Dunachie, Philip Bejon, Eunice Nduati, Francis M. Ndungu

Last Update: 2024-12-26 00:00:00

Language: English

Source URL: https://www.medrxiv.org/content/10.1101/2024.12.22.24319505

Source PDF: https://www.medrxiv.org/content/10.1101/2024.12.22.24319505.full.pdf

Licence: https://creativecommons.org/licenses/by/4.0/

Changes: This summary was created with assistance from AI and may have inaccuracies. For accurate information, please refer to the original source documents linked here.

Thank you to medrxiv for use of its open access interoperability.

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