ABSTRACT
Genetic evolution of Rift Valley fever virus (RVFV) in Africa has been shaped mainly by environmental changes such as abnormal rainfall patterns and climate change that has occurred over the last few decades. These gradual environmental changes are believed to have effected gene migration from macro (geographical) to micro (reassortment) levels. Presently, 15 lineages of RVFV have been identified to be circulating within the Sub-Saharan Africa. International trade in livestock and movement of mosquitoes are thought to be responsible for the outbreaks occurring outside endemic or enzootic regions. Virus spillover events contribute to outbreaks as was demonstrated by the largest epidemic of 1977 in Egypt. Genomic surveillance of the virus evolution is crucial in developing intervention strategies. Therefore, we have developed a computational tool for rapidly classifying and assigning lineages of the RVFV isolates. The computational method is presented both as a command line tool and a web application hosted at https://www.genomedetective.com/app/typingtool/rvfv/ . Validation of the tool has been performed on a large dataset using glycoprotein gene (Gn) and whole genome sequences of the Large (L), Medium (M) and Small (S) segments of the RVFV retrieved from the National Center for Biotechnology Information (NCBI) GenBank database. Using the Gn nucleotide sequences, the RVFV typing tool was able to correctly classify all 234 RVFV sequences at species level with 100% specificity, sensitivity and accuracy. All the sequences in lineages A (n = 10), B (n = 1), C (n = 88), D (n = 1), E (n = 3), F (n = 2), G (n = 2), H (n = 105), I (n = 2), J (n = 1), K (n = 4), L (n = 8), M (n = 1), N (n = 5) and O (n = 1) were also correctly classified at phylogenetic level. Lineage assignment using whole RVFV genome sequences (L, M and S-segments) did not achieve 100% specificity, sensitivity and accuracy for all the sequences analyzed. We further tested our tool using genomic data that we generated by sequencing 5 samples collected following a recent RVF outbreak in Kenya. All the 5 samples were assigned lineage C by both the partial (Gn) and whole genome sequence classifiers. The tool is useful in tracing the origin of outbreaks and supporting surveillance efforts.Availability: https://github.com/ajodeh-juma/rvfvtyping.
Subject(s)
Rift Valley Fever , Rift Valley fever virus , Animals , Commerce , Genomics , Internationality , Kenya , Phylogeny , Rift Valley Fever/epidemiology , Rift Valley fever virus/geneticsABSTRACT
Rift Valley fever (RVF) is a febrile vector-borne disease endemic in Africa and continues to spread in new territories. It is a climate-sensitive disease mostly triggered by abnormal rainfall patterns. The disease is associated with high mortality and morbidity in both humans and livestock. RVF is caused by the Rift Valley fever virus (RVFV) of the genus Phlebovirus in the family Phenuiviridae. It is a tripartite RNA virus with three genomic segments: small (S), medium (M) and large (L). Pathogen genomic sequencing is becoming a routine procedure and a powerful tool for understanding the evolutionary dynamics of infectious organisms, including viruses. Inspired by the utility of amplicon-based sequencing demonstrated in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and Ebola, Zika and West Nile viruses, we report an RVFV sample preparation based on amplicon multiplex polymerase chain reaction (amPCR) for template enrichment and reduction of background host contamination. The technology can be implemented rapidly to characterize and genotype RVFV during outbreaks in a near-real-time manner. To achieve this, we designed 74 multiplex primer sets covering the entire RVFV genome to specifically amplify the nucleic acid of RVFV in clinical samples from an animal tissue. Using this approach, we demonstrate achieving complete RVFV genome coverage even from samples containing a relatively low viral load. We report the first primer scheme approach of generating multiplex primer sets for a tripartite virus which can be replicated for other segmented viruses.
Subject(s)
COVID-19 , Rift Valley Fever , Rift Valley fever virus , Zika Virus Infection , Zika Virus , Animals , Humans , Rift Valley fever virus/genetics , Multiplex Polymerase Chain Reaction , SARS-CoV-2/genetics , Genomics , COVID-19 TestingABSTRACT
Considering the early inequity in global COVID-19 vaccine distribution, we compared the level of population immunity to SARS-CoV-2 with vaccine uptake and refusal between rural and urban Kenya two years after the pandemic onset. A population-based seroprevalence study was conducted in the city of Nairobi (n = 781) and a rural western county (n = 810) between January and February 2022. The overall SARS-CoV-2 seroprevalence was 90.2% (95% CI, 88.6−91.2%), including 96.7% (95% CI, 95.2−97.9%) among urban and 83.6% (95% CI, 80.6−86.0%) among rural populations. A comparison of immunity profiles showed that >50% of the rural population were strongly immunoreactive compared to <20% of the urban population, suggesting more recent infections or vaccinations in the rural population. More than 45% of the vaccine-eligible (≥18 years old) persons had not taken a single dose of the vaccine (hesitancy), including 47.6% and 46.9% of urban and rural participants, respectively. Vaccine refusal was reported in 19.6% of urban and 15.6% of rural participants, attributed to concern about vaccine safety (>75%), inadequate information (26%), and concern about vaccine effectiveness (9%). Less than 2% of vaccine refusers cited religious or cultural beliefs. These findings indicate that despite vaccine inequity, hesitancy, and refusal, herd immunity had been achieved in Kenya and likely other African countries by early 2022, with natural infections likely contributing to most of this immunity. However, vaccine campaigns should be sustained due to the need for repeat boosters associated with waning of SARS-CoV-2 immunity and emergence of immune-evading virus variants.
ABSTRACT
Between the months of April and June 2004, an Ebola hemorrhagic fever (EHF) outbreak was reported in Yambio county, southern Sudan. Blood samples were collected from a total of 36 patients with suspected EHF and were tested by enzyme-linked immunosorbent assay (ELISA) for immunoglobulin G and M antibodies, antigen ELISA, and reverse-transcription polymerase chain reaction (PCR) of a segment of the Ebolavirus (EBOV) polymerase gene. A total of 13 patients were confirmed to be infected with EBOV. In addition, 4 fatal cases were classified as probable cases, because no samples were collected. Another 12 patients were confirmed to have acute measles infection during the same period that EBOV was circulating. Genetic analysis of PCR-positive samples indicated that the virus was similar to but distinct from Sudan EBOV Maleo 1979. In response, case management, social mobilization, and follow-up of contacts were set up as means of surveillance. The outbreak was declared to be over on 7 August 2004.