Genetic diversity of Dengue virus serotypes circulating among Aedes mosquitoes in selected regions of northeastern Nigeria
Bibliographic record
Abstract
The flaviviruses are mosquito borne pathogens that continue to pose a considerable public health risk to animals and humans. The members of this group includes, Dengue virus (DENV), Yellow fever virus (YVF), Japanese encephalitis virus (JEV), West Nile virus (WEV) and Zika virus (ZKV). The DENV mosquito vector is endemic to tropical and subtropical climates, placing ∼40% of the world's population at direct risk of dengue infection. Currently, in Nigeria the status of DENV serotypes circulating among mosquito vectors is unknown. Our study was designed to identify and characterize the DENV serotypes circulating in Aedes mosquito populations collected in selected sites in Nigeria. The mosquitoes were collected and identified morphologically to species level using colored identification keys of Rueda. Generally, each species identified was tested in pools of 20 individuals of each Aedes species. RT-PCR and semi nested PCR were used to detect DENV serotypes in mosquitoes and characterized using Sanger sequencing methods. The results showed that DENV serotypes were detected in 58.54% (24/41) of the pools of Aedes mosquitoes from Mubi, Numan and Yola screened. All DENV1-4 serotypes were detected in Ae. aegypti. While DENV 1, 2 and 4 were detected in Ae. albopictus. And only DENV 2 was detected in Ae. galloisi with DENV4 serotype being reported for the first time in Nigeria. DENV2 (37.8%) was the most detected serotypes, while double and triple co-infections of serotypes were detected in 24.4% of the pools. Phylogenetic analysis revealed a strong evolutionary relatedness of DENV serotypes in our study with that of South and Southeast Asia, North America, and other African countries. This is the first reports on the natural DENV serotypes co-infection among Aedes species pools in Nigeria, which can create possible interaction with other flaviviruses causing animal and human diseases. In addition, our study postulates the possible linkage between DENV serotypes infection and human febrile flu-like disease burden being experienced by host communities in northeastern Nigeria.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".