Interdependence between confirmed and discarded cases of dengue, chikungunya and Zika viruses in Brazil: A multivariate time-series analysis.
The co-circulation of different arboviruses in the same time and space poses a significant threat to public health given their rapid geographic dispersion and serious health, social, and economic impact. Therefore, it is crucial to have high quality of case registration to estimate the real impact o...
| Main Authors: | , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2020-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0228347 |
| _version_ | 1818681792296648704 |
|---|---|
| author | Juliane F Oliveira Moreno S Rodrigues Lacita M Skalinski Aline E S Santos Larissa C Costa Luciana L Cardim Enny S Paixão Maria da Conceição N Costa Wanderson K Oliveira Maurício L Barreto Maria Glória Teixeira Roberto F S Andrade |
| author_facet | Juliane F Oliveira Moreno S Rodrigues Lacita M Skalinski Aline E S Santos Larissa C Costa Luciana L Cardim Enny S Paixão Maria da Conceição N Costa Wanderson K Oliveira Maurício L Barreto Maria Glória Teixeira Roberto F S Andrade |
| author_sort | Juliane F Oliveira |
| collection | DOAJ |
| description | The co-circulation of different arboviruses in the same time and space poses a significant threat to public health given their rapid geographic dispersion and serious health, social, and economic impact. Therefore, it is crucial to have high quality of case registration to estimate the real impact of each arboviruses in the population. In this work, a Vector Autoregressive (VAR) model was developed to investigate the interrelationships between discarded and confirmed cases of dengue, chikungunya, and Zika in Brazil. We used data from the Brazilian National Notifiable Diseases Information System (SINAN) from 2010 to 2017. There were three peaks in the series of dengue notification in this period occurring in 2013, 2015 and in 2016. The series of reported cases of both Zika and chikungunya reached their peak in late 2015 and early 2016. The VAR model shows that the Zika series have a significant impact on the dengue series and vice versa, suggesting that several discarded and confirmed cases of dengue could actually have been cases of Zika. The model also suggests that the series of confirmed and discarded chikungunya cases are almost independent of the cases of Zika, however, affecting the series of dengue. In conclusion, co-circulation of arboviruses with similar symptoms could have lead to misdiagnosed diseases in the surveillance system. We argue that the routinely use of mathematical and statistical models in association with traditional symptom-surveillance could help to decrease such errors and to provide early indication of possible future outbreaks. These findings address the challenges regarding notification biases and shed new light on how to handle reported cases based only in clinical-epidemiological criteria when multiples arboviruses co-circulate in the same population. |
| first_indexed | 2024-12-17T10:08:35Z |
| format | Article |
| id | doaj.art-ce9ce13bc25f48b3b969a3334aff13b3 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-17T10:08:35Z |
| publishDate | 2020-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-ce9ce13bc25f48b3b969a3334aff13b32022-12-21T21:53:07ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-01152e022834710.1371/journal.pone.0228347Interdependence between confirmed and discarded cases of dengue, chikungunya and Zika viruses in Brazil: A multivariate time-series analysis.Juliane F OliveiraMoreno S RodriguesLacita M SkalinskiAline E S SantosLarissa C CostaLuciana L CardimEnny S PaixãoMaria da Conceição N CostaWanderson K OliveiraMaurício L BarretoMaria Glória TeixeiraRoberto F S AndradeThe co-circulation of different arboviruses in the same time and space poses a significant threat to public health given their rapid geographic dispersion and serious health, social, and economic impact. Therefore, it is crucial to have high quality of case registration to estimate the real impact of each arboviruses in the population. In this work, a Vector Autoregressive (VAR) model was developed to investigate the interrelationships between discarded and confirmed cases of dengue, chikungunya, and Zika in Brazil. We used data from the Brazilian National Notifiable Diseases Information System (SINAN) from 2010 to 2017. There were three peaks in the series of dengue notification in this period occurring in 2013, 2015 and in 2016. The series of reported cases of both Zika and chikungunya reached their peak in late 2015 and early 2016. The VAR model shows that the Zika series have a significant impact on the dengue series and vice versa, suggesting that several discarded and confirmed cases of dengue could actually have been cases of Zika. The model also suggests that the series of confirmed and discarded chikungunya cases are almost independent of the cases of Zika, however, affecting the series of dengue. In conclusion, co-circulation of arboviruses with similar symptoms could have lead to misdiagnosed diseases in the surveillance system. We argue that the routinely use of mathematical and statistical models in association with traditional symptom-surveillance could help to decrease such errors and to provide early indication of possible future outbreaks. These findings address the challenges regarding notification biases and shed new light on how to handle reported cases based only in clinical-epidemiological criteria when multiples arboviruses co-circulate in the same population.https://doi.org/10.1371/journal.pone.0228347 |
| spellingShingle | Juliane F Oliveira Moreno S Rodrigues Lacita M Skalinski Aline E S Santos Larissa C Costa Luciana L Cardim Enny S Paixão Maria da Conceição N Costa Wanderson K Oliveira Maurício L Barreto Maria Glória Teixeira Roberto F S Andrade Interdependence between confirmed and discarded cases of dengue, chikungunya and Zika viruses in Brazil: A multivariate time-series analysis. PLoS ONE |
| title | Interdependence between confirmed and discarded cases of dengue, chikungunya and Zika viruses in Brazil: A multivariate time-series analysis. |
| title_full | Interdependence between confirmed and discarded cases of dengue, chikungunya and Zika viruses in Brazil: A multivariate time-series analysis. |
| title_fullStr | Interdependence between confirmed and discarded cases of dengue, chikungunya and Zika viruses in Brazil: A multivariate time-series analysis. |
| title_full_unstemmed | Interdependence between confirmed and discarded cases of dengue, chikungunya and Zika viruses in Brazil: A multivariate time-series analysis. |
| title_short | Interdependence between confirmed and discarded cases of dengue, chikungunya and Zika viruses in Brazil: A multivariate time-series analysis. |
| title_sort | interdependence between confirmed and discarded cases of dengue chikungunya and zika viruses in brazil a multivariate time series analysis |
| url | https://doi.org/10.1371/journal.pone.0228347 |
| work_keys_str_mv | AT julianefoliveira interdependencebetweenconfirmedanddiscardedcasesofdenguechikungunyaandzikavirusesinbrazilamultivariatetimeseriesanalysis AT morenosrodrigues interdependencebetweenconfirmedanddiscardedcasesofdenguechikungunyaandzikavirusesinbrazilamultivariatetimeseriesanalysis AT lacitamskalinski interdependencebetweenconfirmedanddiscardedcasesofdenguechikungunyaandzikavirusesinbrazilamultivariatetimeseriesanalysis AT alineessantos interdependencebetweenconfirmedanddiscardedcasesofdenguechikungunyaandzikavirusesinbrazilamultivariatetimeseriesanalysis AT larissaccosta interdependencebetweenconfirmedanddiscardedcasesofdenguechikungunyaandzikavirusesinbrazilamultivariatetimeseriesanalysis AT lucianalcardim interdependencebetweenconfirmedanddiscardedcasesofdenguechikungunyaandzikavirusesinbrazilamultivariatetimeseriesanalysis AT ennyspaixao interdependencebetweenconfirmedanddiscardedcasesofdenguechikungunyaandzikavirusesinbrazilamultivariatetimeseriesanalysis AT mariadaconceicaoncosta interdependencebetweenconfirmedanddiscardedcasesofdenguechikungunyaandzikavirusesinbrazilamultivariatetimeseriesanalysis AT wandersonkoliveira interdependencebetweenconfirmedanddiscardedcasesofdenguechikungunyaandzikavirusesinbrazilamultivariatetimeseriesanalysis AT mauriciolbarreto interdependencebetweenconfirmedanddiscardedcasesofdenguechikungunyaandzikavirusesinbrazilamultivariatetimeseriesanalysis AT mariagloriateixeira interdependencebetweenconfirmedanddiscardedcasesofdenguechikungunyaandzikavirusesinbrazilamultivariatetimeseriesanalysis AT robertofsandrade interdependencebetweenconfirmedanddiscardedcasesofdenguechikungunyaandzikavirusesinbrazilamultivariatetimeseriesanalysis |