January 2026 – MyAfroDNA

Jan

January 14, 2026

AI, Citizen Science, and the Future of Malaria Surveillance in Africa

Malaria remains one of Africa’s most persistent public health challenges, and early detection of disease vectors is critical to reducing transmission. A recent development in Madagascar highlights how artificial intelligence (AI) and citizen science are reshaping how malaria threats are identified and monitored across the continent.

According to a report by SciDev.Net, researchers used AI-powered image recognition tools alongside community participation to detect a potentially invasive malaria mosquito species, Anopheles stephensi, in Madagascar. This species is particularly concerning because it thrives in urban environments, breeding in water containers such as buckets, tyres, and tanks, settings where malaria transmission has traditionally been lower.

The detection was triggered when a citizen submitted a mosquito larva image via the NASA GLOBE Observer app. AI models trained on thousands of verified mosquito images classified the specimens with high confidence, demonstrating how digital tools can complement traditional entomological surveillance, especially in resource-limited settings.

For Africa, this approach has major implications. Conventional mosquito surveillance relies heavily on field trapping, microscopy, and laboratory confirmation, methods that are often expensive, slow, and unevenly distributed. AI-supported systems allow for rapid, scalable, and community-driven monitoring, improving early warning capacity and public health response.

At MyAfroDNA, we view this as part of a broader shift toward integrated genomic, digital, and environmental surveillance. Combining AI, biospecimen analysis, and genomic research can strengthen malaria control strategies, support vector mapping, and improve our understanding of how mosquito populations evolve and spread.

MyAfroDNA is actively seeking collaboration with researchers, public health institutions, universities, and malaria-focused organisations to support:

Vector genomics and biospecimen research

AI-assisted disease surveillance

Data-driven malaria prevention strategies

Together, we can build African-led, evidence-based solutions for malaria research and control.

Reach out to collaborate with MyAfroDNA.

Source: SciDev.Net – AI and citizens detect invasive mosquito in Madagascar
https://www.scidev.net/sub-saharan-africa/news/ai-and-citizens-detect-invasive-mosquito-in-madagascar/

Jan

January 11, 2026

Admin african biobank, genomics research

Beyond Clinics: How Wastewater Surveillance Is Transforming Disease Detection in Africa

Public health surveillance has traditionally relied on clinics, hospitals, and laboratories to report cases of disease. But across much of Africa, this system captures only part of the picture. Many people do not seek care, cannot access testing, or are excluded from formal health systems altogether. As a result, outbreaks are often detected late, under-reported, or missed entirely.

A recent report in Nature highlights how wastewater surveillance is changing this reality, using sewage to track disease trends at the community level, even when clinical data is limited.

What is wastewater surveillance?

Wastewater surveillance involves testing sewage for genetic material from pathogens such as viruses and bacteria. When people are infected, traces of these pathogens are shed through bodily waste and end up in wastewater systems. By analysing these samples, scientists can estimate disease circulation across entire communities, without relying on individual testing or hospital visits.

In practical terms, one wastewater sample can represent thousands or even millions of people.

Lessons from South Africa

Researchers in South Africa demonstrated how wastewater monitoring can reveal disease trends that conventional surveillance fails to capture. By comparing viral signals in sewage with reported clinical cases, they found a significant gap between actual infections and officially recorded data.

In several instances, wastewater data showed rising infection levels weeks before clinics recorded an increase in cases. This early signal is especially important in lower-income or underserved areas, where testing rates tend to be lower, and outbreaks are more likely to go unnoticed.

The findings underscore a critical reality: absence of data does not mean absence of disease.

Beyond COVID-19

While wastewater surveillance gained prominence during the COVID-19 pandemic, its applications extend far beyond one virus. Researchers are now detecting genetic material linked to:

Measles

Mpox

Influenza

Hepatitis A and E

In some cases, these pathogens were identified in wastewater even when no clinical cases had been officially reported in the area. This positions wastewater surveillance as a powerful early-warning system for emerging and re-emerging diseases.

Why this matters for Africa

Wastewater surveillance offers several advantages that are particularly relevant in African contexts:

Equity: It captures health data from entire communities, including people who are not represented in clinical systems.

Cost-effectiveness: Monitoring a few sites can be more affordable than mass individual testing.

Early detection: Public health authorities can respond sooner, potentially preventing wider outbreaks.

Genomic insight: Sequencing wastewater samples allows scientists to track variants and pathogen evolution over time.

For regions facing resource constraints, these benefits can strengthen public health decision-making without placing additional burdens on individuals.

The challenges ahead

Despite its promise, wastewater surveillance is not without limitations. It requires:

Laboratory infrastructure and sequencing capacity

Skilled personnel for data analysis

Sustainable funding and policy support

Encouragingly, continental initiatives, including efforts led by Africa CDC, are working toward integrating wastewater and environmental surveillance into broader disease monitoring systems.

Where MyAfroDNA fits in

At MyAfroDNA, we believe that genomic tools should serve real-world public health needs, especially in underrepresented regions. Wastewater surveillance demonstrates how genomics can move beyond laboratories and clinics to inform population-level health decisions.

As Africa continues to invest in biospecimen science, molecular testing, and genomic research, approaches like wastewater surveillance will be essential for building resilient, inclusive health systems.

Better data leads to better decisions and better outcomes for communities.

Jan

January 5, 2026

Admin African genetics, genomics research

Understanding Ancestry Labels in Genetic Research

Recent advances published in the American Journal of Human Genetics highlight a pivotal shift in how scientists describe human populations in genetic studies — moving away from outdated racial terms toward more precise and meaningful descriptors like ancestry and ethnicity. In deepening our understanding of human genetic variation, language matters — both scientifically and ethically.

For decades, human genetics research sometimes relied on broad, socially loaded terms such as “race” or “Caucasian.” However, analyses tracking terms used in AJHG articles over time show a clear decline in the use of “race” and a rise in the use of labels like “African,” “European,” “Asian,” “ancestry,” and “ethnicity”. This shift reflects a growing recognition that continental labels and ancestry descriptors are more biologically and socially meaningful than simplistic racial categories.

This transition is not just semantic. Accurate terms improve how we design studies, interpret results and communicate findings — especially in genetics and genomic medicine, where variation is often deeply structured by geography, migration and population history rather than socially constructed groupings.

For a company like MyAfroDNA, this conversation underscores why African-centred genomics must be anchored in scientifically precise and culturally respectful language. Africa is the most genetically diverse continent on Earth, and understanding its genetic variation requires nuanced, context-specific frameworks rather than broad, imprecise categories.

By advocating for the use of ancestry and ethnicity labels rooted in deep genomic data — rather than traditional racial descriptors — the field is moving toward more accurate, inclusive and equitable genomics research. This evolution aligns with our mission: to enrich African genomic representation, empower informed interpretation, and advance science that reflects real human diversity.

Diversifying Translational and Genomics Research

Monthly Archives: January 2026