Evaluation of the Impact of Coinfection and Superinfection on Chikungunya and Mayaro Viruses’ Replication in Aedes aegypti
Bibliographic record
Abstract
The simultaneous circulation of multiple arboviruses, often driven by (re)emergence events, poses challenges to public health systems. In Brazil, the co-circulation of Dengue virus (DENV), Zika virus (ZIKV), Chikungunya virus (CHIKV), and Oropouche virus (OROV), together with the potential urban emergence of Mayaro virus (MAYV), underscores the importance of understanding interactions among these pathogens within their vectors. This study investigated the effects of CHIKV and MAYV coinfection and superinfection on replication dynamics in Aedes aegypti. Mosquitoes were experimentally exposed to CHIKV and MAYV through artificial blood meals under coinfection and superinfection conditions. Infection (IR), dissemination (DR), and transmission (TR) rates, as well as viral loads, were quantified by quantitative reverse transcription PCR (qRT-PCR). To confirm viral replication and assess cytopathic effects, positive saliva samples were inoculated in Vero cells, followed by serial passages and plaque assays for viral titration. The results showed that Ae. aegypti is capable of transmitting both CHIKV and MAYV concurrently during coinfection. However, in superinfection scenarios, prior infection with either virus significantly reduced the transmission efficiency of the subsequently acquired virus, indicating viral interference at the replication level. These findings underscore the complexity of arboviral interactions within vectors and highlight their potential implications for transmission dynamics. Continuous entomo-virological surveillance and targeted research are essential for anticipating and mitigating the impact of arboviral co-circulation in endemic regions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 teacher head, 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".