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Macroeconomic transmission effects on stock market performance in Tanzania: evidence from a structural VAR analysis
(Frontiers, 2026-05-20) Peter, Michael; Mirau, Silas; Sinkwembe, Emmanuel; Kasumo, Christian; Guambe, Calisto
This study examines the dynamic interactions between key macroeconomic indicators and stock market performance in Tanzania, a frontier market in sub-Saharan Africa. Using a Structural Vector Autoregression (SVAR) framework, we analyze monthly data for the Tanzania Share Index (TSI), gold returns, inflation rate, and electricity consumption employed as a high-frequency proxy for real economic activity to address the temporal limitations of quarterly GDP data common in developing economies. Johansen co-integration analysis identifies four stable long-run relationships, while a one-lag VAR specification suggests rapid adjustment dynamics. Impulse response functions reveal that shocks dissipate within three to five months. Notably, the TSI responds negatively to economic activity shocks, indicating a structural mismatch between stock market valuations and real-sector growth. Forecast error variance decomposition further underscores this decoupling: own shocks explain approximately 75%–80% of TSI fluctuations, suggesting that within this four-variable system, macroeconomic factors account for a modest share of equity variation. Gold returns, however, exhibit persistent positive responses to inflation shocks, confirming their role as an inflation hedge. Overall, the findings suggest Tanzania's financial market remains relatively disconnected from real-sector fundamentals, reflecting its early stage of financial deepening. Policy recommendations emphasize strengthening financial infrastructure, enhancing macro-financial linkages, and developing robust commodity-price monitoring systems to improve signal transmission to capital markets.
Invasive Plant Impacts on Soil Macrofauna through Allelopathy and Environmental Modification
(CABI Digital Library, 2026-05-11) Ojija, Fredrick; Bacaro, Giovanni; Ogwu, Matthew; Akomolafe, Gbenga; Laizer, Hudson; Shayo, Philipina; Malunguja, Gisandu
Soil macrofauna taxonomic groups such as annelids (earthworms), arthropods (insects and crustaceans) and molluscs (gastropods/snails) play an essential role in soil ecosystems (van Hengstum et al., 2014; Zulu et al., 2022; Mamabolo et al., 2024). These organisms help convert organic matter into forms that can be utilized by plants, ultimately supporting soil fertility (Sofo et al., 2020; Mamabolo et al., 2024). They influence soil structure, organic matter decomposition, nutrient cycling, soil aeration and ecosystem functioning (van Hengstum et al., 2014; Ibrahima et al., 2017). Thus, their presence and diversity are integral to maintaining soil fertility and productivity, making them important bioindicators for assessing soil health (Rousseau et al., 2013; Sofo et al., 2020). Soil macrofauna physically and biologically alter the soil structure, enhancing the permeability of the soil and improving water infiltration (Zhou et al., 2022). Besides, they contribute to the creation of microhabitats for other organisms, promoting biodiversity conservation (Huerta and van der Wal, 2012). For instance, earthworms, through their burrowing and feeding activities, not only recycle nutrients but also create channels in the soil that facilitate the movement of water and air (Ibrahima et al., 2017; Yang et al., 2024).
Soil macrofauna – ants, termites and beetles – are involved in the breakdown of organic matter, including plant litter and animal remains, thereby playing a role in nutrient cycling (Jouquet et al., 2011; Ibrahima et al., 2017; Mamabolo et al., 2024). The presence and activity of these macrofauna can also influence the abundance and diversity of soil microorganisms, further enhancing nutrient cycling (Zhou et al., 2022). Research conducted by Liu et al. (2020) and Singh et al. (2019) reveals that earthworms are particularly effective at enhancing soil aggregation, which improves the structural stability of the soil. This effect is also seen in termite species, which build intricate tunnel systems that help aerate the soil and facilitate nutrient movement (Black and Okwakol, 1997; Sileshi et al., 2010; Jouquet et al., 2011, 2018; Ali et al., 2013). Table 10.1 provides some common examples of soil macrofauna species.
Integrating ML with Electronic Fiscal Devices for Real-Time Underpricing Detection in Tanzania
(Asosiasi Doktor Sistem Informasi Indonesia, 2026-05-26) Chengula, Benitho; Leo, Judith; Chimilila, Cyril
This study aims to develop a machine learning-based tool integrated into Electronic Fiscal Devices (EFDs) to detect underpricing fraud in real time in Tanzania. The motivation for this research arises from the limitations of existing EFD systems, which rely on manual and post-audit mechanisms that are ineffective in identifying fraudulent pricing during transactions. A mixed-methods approach was employed, combining qualitative insights from tax officers with quantitative data collected from traders and buyers. A dataset of 5,000 mobile phone sales transactions collected from Arusha, Dar es Salaam, and Iringa in Tanzania was pre-processed and used to train and evaluate multiple machine learning models, including Logistic Regression, Support Vector Machine, XGBoost, and Random Forest, using 5-fold cross-validation. The experimental results show that the Random Forest model outperformed other models, achieving an accuracy of 99.6% along with strong precision, recall, and F1-score values. To demonstrate practical applicability, the trained model was further integrated into a prototype EFD environment, where it enabled near real-time fraud detection and generated automated alerts for traders and tax authorities, with geolocation features supporting targeted enforcement. However, the dataset is limited to mobile phone transactions within selected regions of Tanzania, which may affect the generalisability of the findings. The novelty of this study lies in integrating machine learning–based price validation into EFD systems to support proactive detection of underpricing fraud at the point of transaction, thereby enhancing tax compliance and revenue protection.
Integrating 3D video tracking with the standard WHO tunnel assay: a proof-of-concept to support improving insecticide-treated nets for mosquito control
(Springer Nature, 2026-05-08) Bredt, Beatrice; Fatou, Mathurin; Lugenge, Aidi; Kamande, Dismas; Liechti, Nathalie; Moore, Sarah; Müller, Pie
The World Health Organization (WHO) tunnel test is a standardised laboratory assay used to characterise the biological availability and potency of active ingredients on the surface of an insecticide-treated bed net (ITN) against host-seeking mosquitoes. However, the assay provides only endpoint measurements—the proportions of mosquitoes killed and blood-fed – and therefore offers no insight into how mosquitoes interact with the ITN. Therefore, complementary behavioural data would be highly valuable, for example to reveal the extent to which mosquitoes engage with the net, thereby helping to explain differences in endpoint outcomes, or to determine the minimum assay duration required and thus improve throughput. For capturing mosquito behaviour in detail, automated three-dimensional (3D) video tracking offers a powerful approach. Here, we present a proof-of-concept study combining the WHO tunnel assay with Trackit3D, a versatile tracking system, in a laboratory in Tanzania where tunnel assays are routinely performed. The system successfully tracked multiple mosquitoes simultaneously as they were attracted to a rabbit, including measuring the duration of contact with the net, despite typical fluctuations in power supply and lighting conditions. The ability to obtain high-resolution trajectories within the WHO tunnel assay provides new opportunities to enhance the behavioural evaluation of ITNs and strengthens both the interpretability and utility of the assay.
Genetic diversity and population structure of jute mallow (Corchorus olitorius L.) global collection to guide conservation and breeding
(John Wiley & Sons, 2026-05-18) Shango, Abdul; Omondi, Emmanuel; Cervini, C.; Bernard, M.; Schranz, M.; Rabary, Bodovololona; Kabululu, Mujuni; Gumedze, Thembinkosi; Achigan‐Dako, Enoch; Venkataramana, Pavithravani; Philipo, Mashamba; van Zonneveld, Maarten
Understanding the genome-wide diversity of jute mallow (Corchorus olitorius L.) is crucial for unlocking the potential of global genebank collections, enabling the discovery and use of traits that support climate resilience, improve nutrition, and increase productivity. Using 23,471 high-quality diversity array technology sequencing single-nucleotide polymorphisms (SNPs), this study assessed the genetic diversity, population structure, and linkage disequilibrium (LD) of 607 accessions. Moderate genetic diversity was detected with a total gene diversity of 0.28, an expected heterozygosity of 0.26, and a Shannon index of 0.42. Four distinct genetic clusters were identified, reflecting geographic patterns, where Cluster 1 (n = 62) and Cluster 4 (n = 354) were predominantly composed of West African accessions. An analysis of molecular variance revealed significant genetic structuring (p < 0.001), with most genetic variation occurring within countries (45.2%), followed by within individuals (32.5%), while differentiation among clusters accounted for 18.2% and variation among regions was minimal (2.9%). LD revealed low genome-wide r2 values (mean = 0.028; r290 = 0.067) and a very rapid decay (LD50 ≈ 1 bp), with only 4.2% of SNP pairs showing significant LD (r2 > 0.1, p < 0.05), indicating extensive historical recombination. The findings suggest that a significant portion of the existing genetic variation remains untapped in breeding. Strategic conservation of the unique genetic variants through core and mini-core collections, coupled with targeted crosses among diverse regional accessions, can broaden the genetic base and support the development of resilient, high-yielding, and nutrient-rich dual-purpose varieties (i.e., leafy vegetables and industrial fibers) across diverse environments.