Given the pace of SARS-CoV-2 transmission and its relatively high mortality rate, COVID-19, has the potential to become the most severe pandemic in recent times. This virus’s spread across international borders has triggered different responses in countries around the globe with a spectrum of mild, moderate to severe outcomes. Nigeria, Africa’s most populous country with many densely populated cities, presents a unique situation for the explosive spread of SARS-CoV-2. However, at the point of this writing, the number of reported confirmed infection and mortality is comparatively lower to other countries with dense urban populations. The exact reasons for this are not clear but include societal, political and infrastructural factors that will influence the course of the outbreak in Nigeria. In this perspective, we have described the ongoing COVID-19 outbreak and its associated peculiarities. We identify critical steps that remain to be taken to contain and control the outbreak in Nigeria.

Rodent malaria models serve as important preclinical antimalarial and vaccine testing tools. Evaluating treatment outcomes in these models often requires manually counting parasite-infected red blood cells (iRBCs), a time-consuming process, which can be inconsistent between individuals and laboratories. We have developed an easy-to-use machine learning (ML)-based software, Malaria Screener R, to expedite and standardize such studies by automating the counting of Plasmodium iRBCs in rodents. This software can process Giemsa-stained blood smear images captured by any camera-equipped microscope. It features an intuitive graphical user interface that facilitates image processing and visualization of the results. The software has been developed as a desktop application that processes images on standard Windows and MacOS computers. A previous ML model created by the authors designed to count Plasmodium falciparum-infected human RBCs did not perform well counting Plasmodium-infected mouse RBCs. We leveraged that model by loading the pretrained weights and training the algorithm with newly collected data to target Plasmodium yoelii- and Plasmodium berghei-infected mouse RBCs. This new model reliably measured both P. yoelii and P. berghei parasitemia (R² = 0.9916). Additional rounds of training data to incorporate variances due to length of Giemsa staining and type of microscopes, etc., have produced a generalizable model, meeting WHO competency level 1 for the subcategory of parasite counting using independent microscopes. Reliable, automated analyses of blood-stage parasitemia will facilitate rapid and consistent evaluation of novel vaccines and antimalarials across laboratories in an easily accessible in vivo malaria model.

Introduction: Hepatitis B virus(HBV) infects about 2 billion people globally and accounts for mortality of about 800,000 from liver cirrhosis and hepatocellular carcinoma. Sub-Saharan Africa accounts for 70% of Human Immunodeficiency Virus (HIV) global burden. HIV/HBV co-infection results in early development of HBV complications, alterations of serological biomarkers of HBV. Methods: Two hundred and fifty patients with HIV/AIDS were screened for HBV and 20 (8%) were identified. Same number of HBV mono-infected individuals were recruited into the study and subsequently, HBV serological profiles which includes HBsAg, HBsAb, HBeAg, HBeAb,HBcAbIgM and HBcAbIgG were assayed using HBV ELISA kits. Result: Mean age of patients in the HBV/HIV cohort was 45.5 years while the HBV mono-infected infected cohort was 30.5 years. Majority of the HBV/HIV co-infected individuals were females (85%). Frequency of HBeAg among HIV/HBV co-infected cohort was 25% and 15% for HBV mono-infected, while the frequency of HBeAb was higher (60%) among cohort of HBV/HIV co-infected patients in comparison with the HBV mono-infected cohorts(50%). Two patients among the HIV/HBV co-infected cohort have the isolated anti-HBcAg serologic pattern. Conclusion: The study broadened the available evidence of comparative serologic profiles of Hepatitis B virus between cohorts of HBV/HIV co-infected individuals and HBV mono-infected patients in Nigeria.

Introduction: Evolution of phenotypic diversity among viruses occurs as an escape mechanism against host immune pressure or drug selective pressure. Among HIV/HBV co-infected individuals, various HBV basal core promoter (BCP)/precore (PC) region molecular mutants had been reported with associated phenotypic defect in HBeAg production. The emergence of HBeAg negative variants of HBV in HIV co-infected individuals have profound implication on the diagnosis, management and prognosis of this subset of individuals. This includes delayed clearance of HBV, early development of adverse hepatic events such as liver cirrhosis and hepatocellular carcinoma. Currently, little is known about HBV BCP/PC region genomic heterogeneity in HIV/HBV co-infected patients in Nigeria. Therefore, this study was focussed on investigating evidence of precore/core region genomic variability among HIV/HBV co-infected patients in Nigeria. Materials and methods: A total of 40 patients (20 HIV/HBV co-infected and 20 HBV mono-infected samples) were enrolled into the study and subsequently tested for HBsAg, HBeAg and HBeAb using specific Enzyme-Linked Immunosorbent Assay (ELISA). The BCP/PC genome regions (nucleotides 1653-1959) were amplified using a nested PCR assay and then subjected to BCP/PC mutational analysis in genome sites affecting HBeAg expression especially at the BCP transcriptional and PC Translational stop codon sites. Results: Overall, 5(83.3%) of the six exploitable sequences after analysis showed various BCP/PC mutations. Only 1(16.6%) sequence from an HIV/HBV co-infected patient had the BCP transcriptional (double mutation; A1762T/G1764A) mutant. Analysis of the PC translational stop codon showed 4 (66.6%) having the G1896A mutants while 33.3% (2) had G1899A mutants. Conclusion: This study has broadened the available evidence of BCP/PC region molecular mutants among HIV/HBV co-infected patients in Nigeria and assessed the difference of mutation prevalence in comparison with HBV mono-infected cohort. We therefore recommend that HIV/HBV co-infected patients be routinely screened for hepatitis B virus precore region mutants to improve their patient outcome.