| Literature DB >> 33216743 |
Joelma D Monteiro1,2,3,4,5, Joanna Gardel Valverde1,6,7, Ingryd Camara Morais7, Cassio Ricardo de Medeiros Souza1,6,7, João Ciro Fagundes Neto2,3,4, Marília Farias de Melo2,3,4, Yasmin Mesquita Nascimento3,4, Brenda Elen Bizerra Alves2,3,4, Leandro Gurgel de Medeiros2,3,4, Hannaly W Bezerra Pereira2,3,4, Anne Aline Pereira de Paiva3,4, Diego G Teixeira1,6,7, Márcia Cristina Bernardo de Melo Moura8, Alessandre de Medeiros Tavares8, José Veríssimo Fernandes2,3, Selma M B Jeronimo1,5,6,7, Josélio M G Araújo2,3,4.
Abstract
The first autochthonous case of chikungunya virus (CHIKV) infection in Brazil was in September 2014 in the State of Amapá, and from there it rapidly spread across the country. The present study was conducted in 2016 in the state of Rio Grande do Norte, and the aims were to describe the epidemiological and the clinical aspects of the CHIKV outbreak. Biological samples from 284 chikungunya suspected cases were screened for CHIKV and Flavivirus (FV) RNA using qRT-PCR. Negative PCR samples were also screened for anti-CHIKV and anti-FVIgM by ELISA. CHIKV RNA were detected in 125 samples mostly occurring from January through March (46%), mainly affecting adults and older adults. We found a gradual decrease in viral RNA over the disease time. Anti-CHIKV IgM was found in 47.5% after negative CHIKV qRT-PCR. Interestingly, 45.0% simultaneously had positive results for CHIKV and FV IgM, suggesting the occurrence of virus co-circulation. The most frequent symptom was fever (91%). Women presented more chance to develop nausea and abdominal pain compared to men. Our data described and allows us to better understand the clinical and epidemiological aspects of the 2016 chikungunya outbreak in Rio Grande do Norte and can help in the early clinical diagnosis of the virus.Entities:
Year: 2020 PMID: 33216743 PMCID: PMC7678967 DOI: 10.1371/journal.pone.0241799
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1Positivity for chikungunya virus and precipitation.
Absolute number of positive chikungunya cases in Natal and Rio Grande do Norte and precipitation in Natal per week from January 2016 to December 2016.
Demographic characteristics of chikungunya cases, Rio Grande do Norte, Brazil, 2016.
| Suspected CHIKV cases | Positive CHIKV cases | |
|---|---|---|
| Male | 93 (32.7) | 53 (42.4) |
| Female | 158 (55.6) | 65 (52.0) |
| 15 (9.5) | 6 (9.2) | |
| Neonates | 33 (11.6) | 7 (5.6) |
| Years (mean±SD) | 35 ± 24 | |
| Neonates | 33 (11.6) | 7 (5.6) |
| Children (30 days <1 year) | 17 (6.0) | 10(8.0) |
| 1–10 | 15 (5.3) | 7 (5.6) |
| 11–20 | 32 (11.3) | 14 (11.2) |
| 21–30 | 32 (11.3) | 11 (8.8) |
| 31–40 | 35 (12.3) | 17 (13.6) |
| 41–50 | 30 (10.6) | 20 (16.0) |
| 51–60 | 16 (5.6) | 8 (6.4) |
| >61 | 31 (10.9) | 20 (16.0) |
| Not informed | 43 (15.1) | 11 (8.8) |
Positive cases stratified by gender, neonates and age group.
*Percentage among female gender.
Fig 2Chikungunya virus detection in different sample types.
Absolute number and frequency of chikungunya virus per sample type, from Rio Grande do Norte, Brazil, 2016.
Fig 3Chikungunya virus detection during a chikungunya outbreak, Rio Grande do Norte, Brazil, 2016.
Percentage of chikungunya virus detection correlated to day of symptom onset (A) and estimated blood viral loads of chikungunya on different days after the onset of symptoms (B).
Fig 4Venn diagram of IgM positivity.
Venn diagram for 120 negative arbovirus quantitative polymerase chain reaction (qPCR) showing chikungunya virus and flavivirus IgM positivity during chikungunya outbreak, Rio Grande do Norte, Brazil, 2016.CHIKV+: anti-CHIKV IgM positive samples; FV+: anti-ZIKV and/or anti-DENV1-4 IgM positive samples.
Chikungunya symptoms frequency and gender in Rio Grande do Norte, Brazil, 2016.
| Signs and symptoms | Symptom frequency (%) | Male symptom frequency (%) | Female symptom frequency (%) | Odds ratio | Confidence interval | p-value |
|---|---|---|---|---|---|---|
| Fever | 91.0 | 90.9 | 91.1 | 1.020 | 0.257–4.049 | 1.000 |
| Arthralgia | 86.0 | 81.8 | 89.3 | 1.852 | 0.591–5.803 | 0.386 |
| Myalgia | 61.0 | 63.6 | 58.9 | 0.820 | 0.364–1.849 | 0.683 |
| Arthritis | 56.0 | 47.7 | 62.5 | 1.825 | 0.819–4.070 | 0.160 |
| Headache | 56.0 | 54.5 | 57.1 | 1.111 | 0.502–2.461 | 0.841 |
| Back pain | 55.0 | 47.7 | 60.7 | 1.693 | 0.762–3.762 | 0.228 |
| Exanthema | 48.0 | 43.2 | 51.8 | 1.413 | 0.639–3.127 | 0.426 |
| Nausea | 47.0 | 34.1 | 57.1 | 2.578 | 1.138–5.841 | 0.027 |
| Edema | 45.0 | 45.4 | 44.6 | 0.968 | 0.438–2.140 | 1.000 |
| Asthenia | 24.0 | 27.3 | 21.4 | 0.727 | 0.290–1.827 | 0.638 |
| Vomiting | 21.0 | 18.2 | 23.2 | 1.360 | 0.508–3.647 | 0.625 |
| Conjunctivitis | 21.0 | 25.0 | 17.9 | 0.652 | 0.248–1.714 | 0.461 |
| Abdominal pain | 19.0 | 9.1 | 26.8 | 3.659 | 1.117–11.980 | 0.038 |
| Retro orbital pain | 18.0 | 9.1 | 25.0 | 3.333 | 1.011–10.990 | 0.065 |
| Vertigo | 18.0 | 11.4 | 23.2 | 2.358 | 0.770–7.220 | 0.190 |
| Diarrhea | 12.0 | 9.1 | 14.3 | 1.667 | 0.467–5.945 | 0.542 |
| Itching | 12.0 | 4.5 | 17.9 | 4.565 | 0.945–22.060 | 0.062 |
| Photophobia | 9.0 | 4.5 | 12.5 | 3.000 | 0.591–15.240 | 0.292 |
| Othersignsandsymptoms | 18 | 2.02 | 2.33 | 0.870 | 0.340–2.228 | 0.812 |
*Increased chance for females to develop chikungunya symptoms compared to males (p<0.05).
Fig 5Chikungunya signs and symptoms.
Temporal sequence of clinical signs and symptoms in acute chikungunya infection cases.