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  Exploring the availability and content of vaccinology courses across the globe: A scoping review

  (Taylor & Francis, 2026-06-22)

  Nyasulu, Peter S;

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  Tamuzi, Jacques L;

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  Iwu-Jaja, Chinwe ;

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  Tiwari, Ritika;

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  Sakala, Doris Y;

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  Mapping current vaccinology courses is critical for identifying educational gaps, refining program content, and increasing international cooperation to achieve a competent and well-coordinated global vaccination effort. This scoping review investigates the availability and content of vaccinology courses throughout the world, with a focus on Africa where there is a need for strengthened immunization systems and workforce capacity. Eight vaccinology courses, including short professional training and university certificate programs, were offered in Africa, including Morocco, Senegal, Uganda, Kenya, Ethiopia, Rwanda, Ghana, South Africa, and Zimbabwe. Our findings indicated that the percentages of vaccinology modules significantly vary between Africa and other continents, specifically: introduction to immunology, epidemiology, biology of pathogens, vaccine types, vaccine pharmacology, clinical research methodology, pharmacovigilance and vaccine safety, health economics, immunization programs, vaccine manufacture, the role of international organizations in vaccine development, vaccine advocacy, and vaccine cold chain management. By analyzing and comparing specific characteristics of the courses, our results also found multiple gaps and potential challenges related to target population, course objectives, method of course delivery, course contents, duration of course, training, practical sessions delivery, course costs, and funding constraints.

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  Knowledge, perceptions, uptake, and determinants of HPV vaccination, and preferred delivery strategies among out-of-school girls in Masaka, Uganda

  (Taylor & Francis, 2026-04-02)

  Kitonsa, Jonathan;

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  Kafeero, Paddy;

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  Ankunda, Violet ;

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  Muhumuza, Richard;

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  Mukasa Kibengo, Freddie;

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  Cervical cancer is a leading cause of cancer-related mortality among women in sub-Saharan Africa, and accounts for 80% of female cancer cases in Uganda. The Human Papillomavirus (HPV) vaccine prevents cervical cancer but is mainly administered to school-going girls aged 9–15 y, potentially excluding out-of-school girls. This study assessed knowledge, perceptions, uptake, and preferred delivery strategies among out-of-school girls aged 9–20 y in inland and fishing communities in Masaka, Uganda. Between August and October 2024, we surveyed 428 girls (214 per community) using structured questionnaires. Descriptive statistics summarized participant characteristics, and logistic regression identified factors associated with uptake. The median age was 17 y (IQR: 15–19). Nearly one-fifth (19.9%) were married or cohabiting, and 62.4% had ever had sex. Less than half (44.2%) reported prior knowledge of the HPV vaccine, though most recognized its importance (73.4%) and safety (72.2%). Uptake remained low: 29.9% had received at least one dose, and 12.9% had completed two doses. Prior awareness strongly predicted uptake (aOR = 7.82; 95% CI: 4.67–13.44), with higher uptake in fishing communities (aOR = 2.21; 95% CI: 1.30–3.84). Lower uptake was associated with being out of school for 6–10 y (aOR = 0.24; 95% CI: 0.14–0.40) and prior sexual experience (aOR = 0.51; 95% CI: 0.27–0.96). Among unvaccinated girls, 91.2% expressed willingness to receive the vaccine. Preferred strategies included community outreaches (57.7%), health facility approaches (53.3%), and door-to-door delivery (29.2%). Uptake among out-of-school girls was low despite high willingness, underscoring the need for targeted interventions in high-risk settings.

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  Screening PTSD in clinical populations within East Africa: results from the first follow-up study of NeuroGAP-psychosis

  (Taylor & Francis, 2026-03-16)

  Jha, Shaili C.;

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  Stroud, Rocky E.;

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  Dice, Ana Lucia Espinosa ;

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  Kyebuzibwa, Joseph;

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  Gichuru, Stella;

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  Background: Given the high burden of trauma in Sub-Saharan Africa, there is a critical need for scalable tools to screen for trauma and posttraumatic stress disorder (PTSD) symptoms, especially in low-resource settings. Objective: This study aimed to evaluate the utility, reliability, and validity of the Primary Care PTSD Screen for DSM-5 (PC-PTSD-5) administered over the telephone to individuals previously enrolled in the Neuropsychiatric Genetics of African Populations-Psychosis study (NeuroGAP-Psychosis) study in Uganda (N = 4,921) and Kenya (N = 3,149). Method: Cases with psychosis and controls without psychosis (patients, caretakers, or employees) were recontacted from the NeuroGAP-Psychosis study and enrolled in a follow-up study. This follow-up included a phone-based assessment of trauma and PTSD using the Life Events Checklist for DSM-5 (LEC-5) and the PC-PTSD-5, followed by an in-person assessment of PTSD using the PTSD Checklist for the DSM-5 (PCL-5). All interviews were conducted in local languages and by trained research assistants. Results: High rates of participant recontact and completion were achieved, with 60% of participants in the Ugandan cohort and 85% in the Kenyan cohort successfully completing the trauma and PTSD assessment over the phone. In both countries, approximately 80% of those screened by phone also completed the in-person interview. The PC-PTSD-5 demonstrated overall good to acceptable reliability (α = 0.85/ω = 0.86 in Ugandan cohort; α = 0.76/ω = 0.77 in Kenyan cohort), across both cases with psychosis and controls without psychosis, and across the different study languages. Furthermore, evaluation of the PC-PTSD-5 against the PCL-5 in Uganda revealed strong performance based on both sensitivity (91%) and specificity (77%). Conclusions: The first follow-up study in NeuroGAP-Psychosis successfully demonstrates the feasibility of a hybrid telephone and in-person PTSD screening protocol in Sub-Saharan Africa. The results are a first step in establishing the research and clinical use of brief, scalable PTSD screening instruments in low-resource settings and in populations affected by psychosis. This study demonstrates large-scale recontact, consent, and PTSD screening via telephone and in-person in the NeuroGAP-Psychosis study in Uganda and Kenya.Studies focused on trauma or PTSD symptom assessments can successfully combine phone and in-person methods to facilitate research in low-resource settings and clinical screenings.The PC-PTSD-5 can be used as an effective first-step screening tool across different local languages and among individuals with and without psychosis in this cohort.

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  Detection of selection signatures in indigenous African cattle reveals genomic footprints of adaptation, production and temperament traits

  (Springer US, 2026-01-28)

  Okwasiimire, Rodney;

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  Kugonza, Donald R.;

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  Gao, Junxin ;

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  Weldenegodguad, Melak;

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  Makgahlela, Mahlako L.;

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  Indigenous cattle account for approximately 80% of Uganda’s cattle population. These animals are well adapted to the country’s ten agroecological zones and are mainly kept under pastoral and agropastoral systems. Unlike commercial breeds, they thrive on low-quality feeds, while tolerating major tropical diseases and parasites including tsetse flies, ticks, and vector-borne infections. Whole-genome sequence (WGS) analysis offers opportunities to uncover genomic regions underlying these adaptations and to trace the genetic footprints of long-term breeding decisions taken by cattle keepers. In this study, WGS data from 95 animals representing six indigenous cattle populations (Ankole, Karamojong, Nganda10, Nganda17, Nkedi, and Ntuku) were analyzed to identify genomic regions under putative selection. Two complementary approaches were applied: enumeration of the µ-statistic in RAiSD and runs of homozygosity (ROH) analysis. RAiSD identified population-level signals, while conserved ROH regions were defined using breed-specific SNP-incidence thresholds. The two methods identified 803 and 49 candidate genes respectively. The top genes identified included SLC37A1 (BTA1), CHCHD3 (BTA4), and RAB3GAP1 (BTA2) detected by RAiSD, and IL26 (BTA5), FBXL7 (BTA20), and HSPA9 (BTA7) contained in ROH. Furthermore, the regions harbored 107 novel genes (92 detected by RAiSD and 15 by ROH), corresponding to 255 quantitative trait loci. The identified genes under putative selection are associated with economically important traits including adaptation to tropical environments, resistance to parasites and diseases, and other farmerpreferred characteristics. These findings provide insights into the genetic basis of adaptation, selection and production in Ugandan indigenous cattle, supporting conservation and breeding strategies to enhance resilience and productivity

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  Early risk prediction of gestational diabetes using routine antenatal care clinical data using machine learning

  (Springer International Publishing, 2026-05-10)

  Ahishakiye, Emmanuel;

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  Nakirijja, Justine;

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  Ahimbisibwe, Shallon

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  Gestational diabetes mellitus (GDM) is a major contributor to adverse maternal and neonatal outcomes, particularly in low-resource settings where timely diagnostic testing is not always feasible. Early identification of high-risk pregnancies using routinely collected antenatal information could support targeted screening and preventive care. This study evaluated the feasibility of early GDM risk prediction using machine learning models trained on routine antenatal care data from 3525 pregnancies in Uganda (2153 non-GDM and 1372 GDM cases). Logistic regression, Random Forest, XGBoost, and a soft-voting ensemble were developed and assessed using a held-out test set. Model performance was evaluated using receiver operating characteristic area under the curve (ROC AUC), precision–recall AUC (PR AUC), accuracy, precision, recall, and F1-score, and interpretability was examined using SHapley Additive exPlanations (SHAP). Tree-based models demonstrated strong discrimination, with Random Forest and XGBoost achieving ROC AUC values of 0.997 and PR AUC values above 0.995, while logistic regression achieved ROC AUC of 0.982. Random Forest achieved high sensitivity (recall = 0.994), missing only two GDM cases in the test set. SHAP analysis identified body mass index, high-density lipoprotein cholesterol, blood pressure, and prior metabolic history as influential predictors, with feature effects consistent with established clinical knowledge. The proposed approach is intended as an early risk-stratification and triage support tool rather than a diagnostic system. All predictors were available prior to confirmatory glucose testing, and model outputs are designed to prioritise women for further evaluation and follow-up. Although performance estimates reflect internal validation within a referral-hospital cohort, the findings demonstrate that routinely collected antenatal variables contain clinically meaningful predictive information. With external and prospective validation, interpretable machine learning models may support more efficient screening and monitoring of gestational diabetes in resource-constrained antenatal care settings. CrossRef

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