Background: Hepatitis B virus (HBV) is an infectious disease of global significance, causing a significant health burden in Africa due to complications associated with infection, such as cirrhosis and liver cancer. In Nigeria, which is considered a high prevalence country, estimates of HBV cases are inconsistent, and therefore additional clarity is required to manage HBV-associated public health challenges.Methods: A systematic review of the literature (via PubMed, Advanced Google Scholar, African Index Medicus) was conducted to retrieve primary studies published between 1 January 2010 and 31 December 2019, with a random-effects model based on proportions used to estimate the population-based prevalence of HBV in the Nigerian population.Results: The final analyses included 47 studies with 21,702 participants that revealed a pooled prevalence of 9.5%. A prevalence estimate above 8% in a population is classified as high. Sub-group analyses revealed the highest HBV prevalence in rural settings (10.7%). The North West region had the highest prevalence (12.1%) among Nigeria’s six geopolitical zones/regions. The estimate of total variation between studies indicated substantial heterogeneity. These variations could be explained by setting and geographical region. The statistical test for Egger’s regression showed no evidence of publication bias (p = 0.879).Conclusions: We present an up-to-date review on the prevalence of HBV in Nigeria, which will provide critical data to optimise and assess the impact of current prevention and control strategies, including disease surveillance and diagnoses, vaccination policies and management for those infected.

Background. Gastroenteritis due to foodborne disease is a leading cause of death in developing countries. In Nigeria, there is an increasing demand for beef. Yet, there is no surveillance for Escherichia coli O157:H7 contamination of raw beef and little is known about the carriage of this pathogen in Nigeria’s livestock. Methods. A total of 415 samples, including 180 cow carcass swabs, 180 caecal content samples, 16 water samples, 25 hand swabs and 14 knife swabs were collected at a large abattoir in the Moro region of Kwara State, Nigeria. The samples were enriched in modified tryptone broth containing novobiocine, and plated onto Sorbitol–MacConkey agar (Oxoid SR0172E) supplemented with 0.05 mg l⁻¹ cefixime and 2.5 mg l⁻¹ potassium tellurite (Oxoid) (CT-SMAC). Indole-producing isolates were confirmed serologically by serotyping with antisera specific for the O157 and H7 antigens. The E. coli O157:H7 isolates were further tested for their susceptibility to antibiotic agents using the disc diffusion method. Commercially available Gram-negative multi-discs (Oxoid) comprising nitrofurantoin (30 µg), ampicillin (5 µg), ceftazidime (30 µg), gentamicin (10 µg), ciprofloxacin (5 µg), augmentin (30 µg), ofloxacin (5 µg) and cefuroxime (30 µg) were tested. Results. Overall, 16 (3.9 %) samples were contaminated with E. coli O157:H7, of which 10 (5.6 %) were isolated from carcass swabs, 4 (2.2 %) from caecal content samples and 2 (12.5 %) from water. All isolates were multidrug-resistant (MDR), with resistance to ampicillin, ceftazidime and cefuroxime being the most common. Conclusion. This study provides evidence to suggest that E. coli O157:H7 exists in the beef production chain. The pathogen reveals a high frequency of multidrug resistance, suggesting that consumers and handlers of such meat are at risk of contracting antibiotic-resistant E. coli O157:H7-associated foodborne disease. Routine monitoring of antibiotic resistance is critical to uncovering novel therapeutic strategies that will help inform clinical practice guidelines.

ObjectiveTo investigate the phytochemical components of Abrus precatorius (A. precatorius) and the in-vitro susceptibility of Salmonella typhi and Shigella dysenteriae to the aqueous extracts of A. precatorius leaf, seed and root.MethodsThe leaf, seed and root of A. precatorius were collected and homogenized separately after drying at 40 °C for seven days in hot-air oven. The aqueous extracts of each of the parts were prepared and subjected to phytochemical screening. Dilutions of 400, 300, 200, 100 mg/mL, of each of the extracts were used for broth dilution in minimum inhibitory concentration (MIC) determination against clinical isolates of Salmonella typhi and Shigella dysenteriae, while 50, 40, 30, 20, and 10 mg/mL dilutions were used for the agar diffusion test and 100 μg/mL and 10 μg/mL of gentamycin were used as controls for broth dilution in MIC determination and agar diffusion test, respectively.ResultsQualitative study reveals that tannin, saponins, alkaloids, flavonoids, terpenoids, steroids and phenols were present in all of the plant parts. The leaf has the highest quantities of tannin and phenol. The root generally showed the lowest quantity of all the compounds. The pathogens were susceptible to aqueous extracts of the leaf, stem and root of A. precatorius at 50 mg/mL. At concentrations of 40, 30 and 20 mg/mL, all the aqueous extracts of A. precatorius showed variation in MIC, but produced no minimum bactericide effect upon subculture. There were variations in diameter of zone of inhibition against the organisms at lower concentrations.ConclusionsThese findings suggest that A. precatorius is a valuable source of phytochemicals with promising antibacterial activity. Considering this bioactivity, A. precatorius could be probed further for toxicity, and to obtain some novel antibacterial molecules

Access to Hepatitis B Virus (HBV) testing for people in low-resource settings has long been challenging due to the gold standard, enzyme immunoassay, being prohibitively expensive, and requiring specialised skills and facilities that are not readily available, particularly in remote and isolated laboratories. Routine pathology data in tandem with cutting-edge machine learning shows promising diagnostic potential. In this study, recursive partitioning (“trees”) and Support Vector Machines (SVMs) were applied to interrogate patient dataset (n = 916) that comprised results for Hepatitis B Surface Antigen (HBsAg) and routine clinical chemistry and haematology blood tests. These algorithms were used to develop a predictive diagnostic model of HBV infection. Our SVM-based diagnostic model of infection (accuracy = 85.4%, sensitivity = 91%, specificity = 72.6%, precision = 88.2%, F1-score = 0.89, Area Under the Receiver Operating Curve, AUC = 0.90) proved to be highly accurate for discriminating HBsAg positive from negative patients, and thus rivals with immunoassay. Therefore, we propose a predictive model based on routine blood tests as a novel diagnostic for early detection of HBV infection. Early prediction of HBV infection via routine pathology markers and pattern recognition algorithms will offer decision-support to clinicians and enhance early diagnosis, which is critical for optimal clinical management and improved patient outcomes.

This paper discusses the contributions that One Health principles can make in improving global response to zoonotic infectious disease. We highlight some key benefits of taking a One Health approach to a range of complex infectious disease problems that have defied a more traditional sectoral approach, as well as public health policy and practice, where gaps in surveillance systems need to be addressed. The historical examples demonstrate the scope of One Health, partly from an Australian perspective, but also with an international flavour, and illustrate innovative approaches and outcomes with the types of collaborative partnerships that are required.

HepB LiveTest is a machine learning decision support system developed for the early detection of hepatitis B virus (HBV). However, there is a lack of evidence on its generalisability. In this study, we aimed to externally assess the clinical validity and portability of HepB LiveTest in predicting HBV infection among independent patient cohorts from Nigeria and Australia. The performance of HepB LiveTest was evaluated by constructing receiver operating characteristic curves and estimating the area under the curve. Delong’s method was used to estimate the 95% confidence interval (CI) of the area under the receiver-operating characteristic curve (AUROC). Compared to the Australian cohort, patients in the derivation cohort of HepB LiveTest and the hospital-based Nigerian cohort were younger (mean age, 45.5 years vs. 38.8 years vs. 40.8 years, respectively; p < 0.001) and had a higher incidence of HBV infection (1.9% vs. 69.4% vs. 57.3%). In the hospital-based Nigerian cohort, HepB LiveTest performed optimally with an AUROC of 0.94 (95% CI, 0.91–0.97). The model provided tailored predictions that ensured most cases of HBV infection did not go undetected. However, its discriminatory measure dropped to 0.60 (95% CI, 0.56–0.64) in the Australian cohort. These findings indicate that HepB LiveTest exhibits adequate cross-site transportability and clinical validity in the hospital-based Nigerian patient cohort but shows limited performance in the Australian cohort. Whilst HepB LiveTest holds promise for reducing HBV prevalence in underserved populations, caution is warranted when implementing the model in older populations, particularly in regions with low incidence of HBV infection.