With Africa having the highest neonatal mortality rate in the world, vaginal infections, including Sexually Transmitted Infections (STIs), could have serious implications for women's reproductive health and their pregnancy outcomes. Hence, critical research is needed to better understand the microorganisms present in various vaginal infections, and their role in particular pregnancy outcomes.
Using Artificial Intelligence (AI) and next-generation sequencing technology, my team of researchers at the University of Nairobi are breaking new ground in understanding how the vaginal microbiome and vaginal infections affect a woman's reproductive health and pregnancy outcomes. This technology could enable us to identify whether women who deliver at term have a certain microbiome, compared to those experiencing pre-term birth.
This research is not only the first of its kind in Kenya - it is cutting edge research with significant tangible impact in improving pregnancy outcomes for women around the world. It also informs the development of faster and less invasive testing - such as a urine test - at the point of care, and potentially the development of more effective therapeutic treatments. If health workers can diagnose and treat an infection at the point of care, you mitigate risk to mother and baby, and reduce the cost of treatment.
Risks of vaginal infections in pregnancy
Testing for vaginal infections - particularly asymptomatic infections such as bacterial vaginosis - is not routinely carried out in prenatal examinations. Healthcare providers seldom carry out a full screening for both symptomatic and asymptomatic infections. They often do syphilis screening, and screenings in the case of premature rupture of the membranes, but there is no integrated approach for identifying asymptomatic infections.
Some studies indicate around 20 per cent of women attending gynaecology clinics in Kenya have vaginal infections including bacterial vaginosis and parasitic infections, or STIs including syphilis, gonorrhoea, Chlamydia and Trichomonas vaginalis. However, data suggests that as many as 73 per cent of women have asymptomatic vaginal infections.
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Our five-year research project includes screening and monitoring over 1,500 women attending six medical facilities in Kenya over two years. Having acquired advanced tools such as Polymerase Chain Reaction (PCR) machines to analyse bacteria, and an Illumina MiSeq sequencer for targeted and microbial genome applications, we will use next generation sequencing and AI to analyse microbial communities, and metabolomic profiling to identify predictive and diagnostic signatures of adverse pregnancy outcomes.
By working to identify predictive biomarkers for adverse pregnancy outcomes, we may be able to improve reproductive health for women not only in Kenya, but around the world, and support health officials with better intervention strategies to support healthier pregnancy outcomes.
Prof Moses Obimbo Madadi, leading Clinician-Scientist and Associate Professor at the University of Nairobi