Baobab Index

BACKGROUND: The molecular and spatial epidemiology of Mycobacterium tuberculosis (Mtb) in relation to diagnostic delays remains underexplored in Kenya. This study was conducted to map the spatial clustering and characterize circulating lineages/sub-lineages of Mtb, and their transmission patterns associated with diagnostic delays in Nairobi County. METHODS: DNA was extracted from 101 Mtb isolates collected from newly diagnosed pulmonary tuberculosis (PTB) patients in Nairobi County and genotyped using the mycobacterial interspersed repetitive unit variable number tandem repeat (MIRU VNTR) method. Spatial analysis was conducted using ArcMap version 10.8.2, and statistical associations were assessed using logistic regression. RESULTS: The majority of isolates were Mtb (92/101, 91.1%; 95% CI: 85.5–96.7). Lineage 4 (Euro-American) was the predominant lineage (64/101, 63.4%; 95% CI: 54.0–72.8), followed by Lineage 2 (East Asian; 16.8%), Lineage 3 (South Asian; 10.9%), and Lineage 5 (West African; 8.9%). The most common sublineages were LAM (33/101, 32.7%), Beijing (17/101, 16.8%), S (15/101, 14.9%), Delhi/CAS (11/101, 10.9%), and UgandaI/II (10/101, 9.9%). The molecular clustering rate was 12.7%. After adjustment, Mtb lineage was not associated with diagnostic delay (Ancestral vs Modern: aOR = 1.05, 95% CI 0.38–2.91, p = 1.000). CONCLUSIONS: This study identified considerable Mtb strain diversity in Nairobi County. Although molecular clustering was low (12.7%), suggesting that most cases were not part of recent transmission chains, a small number of strains, including Beijing and Uganda I/II, appeared in compact molecular clusters. These clusters may represent localized transmission but cannot be definitively interpreted as such without epidemiologic linkage.

Medium-chain acyl-CoA dehydrogenase deficiency (MCADD), a potentially lethal metabolic disorder, is often associated with single-nucleotide polymorphisms (SNPs) in the acyl-CoA dehydrogenase, medium-chain (

Severe acute malnutrition (SAM) is a leading cause of childhood morbidity and mortality that is defined by anthropometric measurements, weight-for-height

This study investigated the polyphenolic composition, antioxidant capacity, and antianemic effects of aqueous leaf (JPEL) and berry (JPEB) extracts of Juniperus phoenicea ssp. turbinata L. (J. phoenicea ssp. turbinata). The plant is traditionally used to treat various ailments. HPLC-DAD analysis identified quercetin as the major compound (JPEB 49.09%; JPEL 31.34%), followed by p-coumaric acid (27.07% in JPEB), catechin (14.69% in JPEL), and gallic acid (JPEB 13.69%; JPEL 12.08%). Antioxidant activity was assessed using DPPH and reducing power assays, with the most active extract showing IC

Accurate estimation of antimalarial drug efficacy against P. falciparum requires PCR correction to distinguish recrudescence from new infection in recurrent infections. Here, we compared two different genotyping techniques and different decision algorithms used for PCR correction using samples collected in a Therapeutic Efficacy Study (TES) conducted in Rwanda in 2018. We first optimized an assay to genotype four microsatellites by capillary electrophoresis and assessed its sensitivity in detecting minority clones with laboratory parasite strain mixtures. We then analyzed patient samples by capillary electrophoresis using msp1, msp2, glurp and microsatellites (length-polymorphic markers) and amplicon deep sequencing using cpmp, ama1, cpp and csp (SNP-rich markers), and assessed their diversity and allelic frequency. We classified the recurrent infections as recrudescence or new infection based on different marker combinations and decision algorithms (WHO, 2/3, Bayesian algorithm). Among microsatellites, TA40 and PfPK2 had the highest sensitivity in detecting minority clones. Msp2/3D7, glurp and SNP-rich markers had the highest genetic diversity and lowest allelic frequencies. The WHO algorithm identified the fewest recrudescences across all marker combinations, while the 2/3 identified the most. The Bayesian algorithm yielded intermediate results. Replacing glurp with any of the microsatellites or using SNP-rich markers did not significantly alter recrudescence estimates. Amplicon sequencing of SNP-rich markers provided the most consistent results regardless of the decision algorithm used and therefore holds great potential for reliable PCR correction. Additionally, probabilistic approaches may provide more robust results compared to match counting algorithms; however, they require rigorous validation with datasets from different transmission settings.

This study reports the draft genome sequence of

Podoconiosis is a neglected tropical disease (NTD) causing chronic lower limb lymphoedema through prolonged barefoot exposure to irritant volcanic soils. Despite affecting an estimated 4 million people globally, podoconiosis remains absent from the Global Burden of Disease study and severely under-researched relative to its impact. East Africa carries the greatest regional burden, yet no comprehensive synthesis of prevalence, disability-adjusted life years (DALYs), or economic burden data exists for the region. This systematic review and meta-analysis aimed to address this gap by synthesizing available evidence on the prevalence and health and economic burden of podoconiosis across East Africa. We conducted a systematic search of PubMed/MEDLINE, EMBASE, SCOPUS, Web of Science, EconLit, WHO AFROLIB, and Google Scholar for studies published in English between 2011 and 2023. Studies reporting population-based podoconiosis prevalence, DALYs, or economic burden data from East African countries as defined by the UN M49 geoscheme were eligible for inclusion. Grey literature was also searched, including reports, ministry of health documents, and conference proceedings both in English and French, to capture evidence not indexed in academic databases. The search was updated in March 2026 to ensure the most current evidence was captured. Quality assessment was performed using the Newcastle-Ottawa Scale. Prevalence data were pooled using a random-effects model with the DerSimonian-Laird estimator and Freeman-Tukey double arcsine transformation. Subgroup analyses were conducted by country, sample size, and geographic scope. Fourteen studies met the inclusion criteria, comprising 10 from Ethiopia, 2 from Kenya, and 1 each from Uganda and Rwanda, collectively examining 1,720,437 individuals. The overall pooled prevalence was 1.19 (95% CI: 1.14-1.25) on the transformed scale, with extreme heterogeneity (I² = 99.0%). The Ethiopia-specific pooled prevalence was 4.52% (95% CI: 3.92-5.16%), compared to 0.20% (95% CI: 0.10-0.33%) for the non-Ethiopian subgroup, a more than 20-fold difference. A consistent inverse relationship between sample size and observed prevalence was identified across all analyses, reflecting the systematic tendency of smaller studies to target confirmed endemic foci while larger surveys captured broader populations. Only one study Deribe et al. (2020), reported DALY and economic burden estimates, confined to Ethiopia, estimating 172,073 DALYs annually and a total economic burden of US$213.2 million per year. Podoconiosis imposes a substantial but profoundly under-quantified burden across East Africa, with disease intensity disproportionately concentrated in Ethiopian highland communities. The near-complete absence of DALY and economic burden data outside Ethiopia represents a critical evidence gap. Standardised nationally representative surveys, expansion of burden modelling beyond Ethiopia, and advocacy for inclusion of podoconiosis in the Global Burden of Disease study are urgently needed to support evidence-based policy and resource prioritisation across the region. This systematic review was registered in the PROSPERO International Prospective Register of Systematic Reviews with the registration number: CRD42023432640.

Genomic surveillance has become an indispensable tool for the identification of pathogens and tracking of transmission chains. Building upon the global sequencing and surveillance infrastructure developed and expanded during the COVID-19 pandemic, these capacities are now being adapted to track other pathogens in low- and middle-income countries which remain disproportionately affected by infectious diseases. This is evident in the recent and unprecedented spread of mpox virus in regions experiencing multiple concurrent infectious disease outbreaks, highlighting the need for broad, adaptable diagnostic detection and sequencing capacity. In this Perspective, we describe the applications, insights, and challenges encountered during ongoing capacity building efforts for the characterization of the mpox outbreak and other emerging pathogens in the African Great Lakes Region.

In Africa, the disease burden of diarrheal and respiratory diseases is amplified by limited surveillance capacity, diagnostic limitations, and socioeconomic inequalities. In rapidly urbanizing settings such as Kigali (Rwanda), integrating wastewater-based epidemiology (WBE) into existing surveillance systems offers a promising strategy for generating real-time epidemiological intelligence, identifying community-level hotspots, and addressing gaps in traditional reporting systems. Gastrointestinal and respiratory infections remain major causes of morbidity and mortality globally, particularly in low- and middle-income countries (LMICs), where traditional clinical surveillance systems frequently underreport the true disease burden. This systematic review synthesizes current evidence on the detection of gastrointestinal and respiratory pathogens in wastewater and evaluates the utility of WBE for early warning and public health action. A narrative review approach was used to identify peer-reviewed literature, global health reports, and surveillance studies focusing on the wastewater detection of gastrointestinal and respiratory pathogens. Databases including PubMed, Scopus, and Google Scholar were searched for studies published between 2000 and 2026. The search yielded 1247 records, of which 312 duplicates were removed. After title/abstract screening, 228 full-text articles were retrieved and assessed for eligibility. After a detailed evaluation, 108 studies were excluded for the following reasons: absence of pathogen-specific wastewater data (