Increasing frequency of secondary dengue infections in sequential outbreaks (2016-2024). Clinical impact and diagnostic challenges.
Espindola, S. L.; Pereson, M. J.; Lema, J. M.; Kachuk, A.; Carballo, G.; Aloisi, N.; Badano, M. N.; Miretti, M.; Di Lello, F. A.; Bare, P. C.
Show abstract
Successive dengue virus (DENV) outbreaks can progressively reshape population immunity influencing disease expression and diagnostic performance. Objectives The aim was to evaluate the impact of secondary infections across sequential outbreaks on clinical severity, serotype dynamics and diagnostic concordance. Methods This retrospective study analyzed 976 febrile-stage samples from three sequential outbreaks in Misiones, Argentina. For serotyping and clinical analyses, 869 viremic samples confirmed by at least one direct method were included (2016: n=512; 2019: n=148; 2024: n=209). Additionally, 318 samples, including 107 non-viremic cases, were used to compare NS1 rapid diagnostic tests (NS1 Ag) and RT-PCR. Viral serotyping and clinical and laboratory markers of disease severity were evaluated. Results Secondary infections increased from 31.05% (2016) to 43.24% (2019) and 53.87% (2024) (p<0.0010). Serotype distribution shifted from DENV-1 predominance in 2016 (95.12%), DENV-1/DENV-4 co-circulation in 2019 (60.71%/39.29%), and DENV-2 predominance in 2024 (97.60%). Secondary infections were associated with more severe disease manifestations, particularly in 2024, with higher hematocrit (p=0.0120) and hemoglobin (p=0.0080), lower white blood cells (p=0.020) and platelet counts (p=0.0030), and elevated AST (p=0.0007) and ALT (p=0.0130). Concordance between NS1 Ag and RT-PCR was lower in secondary infections (k=0.457 vs k=0.759, p=0.0013). Conclusions The rising frequency of secondary infections may affect both clinical severity and diagnostic performance during outbreaks. The clinical impact was more evident in 2024, likely associated with the introduction of a new serotype. These findings highlight the need for optimized surveillance and diagnostic strategies to improve case detection and patient management during epidemics.
Matching journals
The top 11 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Dengue severity by serotype and immune status in 19 years of pediatric clinical studies in Nicaragua 97%
- Distinguishing non severe cases of dengue from COVID-19 in the context of co-epidemics: a cohort study in a SARS-CoV-2 testing center on Reunion island 95%
- The epidemiology of Mayaro virus in the Americas: A systematic review and key parameter estimates for outbreak modelling 95%
Similar papers in this journal
- SARS-CoV-2 seroassay optimization and performance in a population with high background reactivity in Mali 92%
- A case-cluster of aseptic meningitis associated with a newly identified recombinant echovirus6/CoxsackievirusB1 enterovirus 92%
- Risk of SARS-CoV-2 transmission by fomites: a clinical observational study in highly infectious COVID-19 patients 92%
Similar papers in this journal
Similar papers in this journal
- Re-introduction of dengue virus serotype 2 in the state of Rio de Janeiro after almost a decade of epidemiological silence 95%
- Modulated Zika virus NS1 conjugate offers advantages for accurate detection of Zika virus specific antibody in double antigen binding and Ig capture enzyme immunoassays 94%
- Performance estimation of two in-house ELISA assays for COVID-19 surveillance through the combined detection of anti-SARS-CoV-2 IgA, IgM, and IgG immunoglobulin isotypes 94%
Similar papers in this journal
- Dissecting age-stratified immunity to different dengue virus serotypes and Zika viruses among children in a highly endemic region in Sri Lanka 96%
- Clinical and serological findings of Madariaga and Venezuelan equine encephalitis viral infections: A follow-up study five years after an outbreak in Panama 94%
- Occurrence of Four Dengue Virus Serotypes and Chikungunya Virus in Kilombero, Tanzania during Dengue Outbreak in 2018 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.