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Diaz-Quijano FA, Siqueira de Carvalho D, Raboni SM, Shimakura SE, Maron de Mello A, Vieira da Costa-Ribeiro MC, Silva L, da Cruz Magalhães Buffon M, Cesario Pereira Maluf EM, Graeff G, Almeida G, Preto C, Luhm KR. Effectiveness of mass dengue vaccination with CYD-TDV (Dengvaxia®) in the state of Paraná, Brazil: integrating case-cohort and case-control designs. LANCET REGIONAL HEALTH. AMERICAS 2024; 35:100777. [PMID: 38807985 PMCID: PMC11131085 DOI: 10.1016/j.lana.2024.100777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 04/21/2024] [Accepted: 05/06/2024] [Indexed: 05/30/2024]
Abstract
Background CYD-TDV (Dengvaxia®) was the first dengue vaccine approved, launched in Brazil in 2015 for individuals aged 9-44 years. We aimed to estimate the effectiveness of CYD-TDV in preventing symptomatic dengue cases during a campaign targeting individuals aged 15-27 years in selected municipalities in Paraná, Brazil. Additionally, we examined whether a history of dengue, as recorded by the surveillance system, modified the vaccine's effectiveness. Methods We conducted a case-cohort analysis comparing the frequency of vaccination, with at least one dose of CYD-TDV, in individuals with dengue confirmed by RT-PCR, identified by the surveillance system during 2019 and 2020, with the vaccination coverage in the target population. Moreover, in a case-control design using weighted controls, we assessed the documented history of dengue as a modifier of the vaccine's effectiveness. We used a logistic random-effects regression model, with data clustered in municipalities and incorporating covariates such as the incidence of dengue before the campaign, age, and sex. We calculated vaccine effectiveness (VE) as (1-relative risk) x 100%. Findings 1869 dengue cases were identified, which had a vaccination frequency significantly lower than the overall vaccination coverage in the target population (50.3% vs. 57.2%, respectively; overall VE: 21.3%; 95% confidence interval [CI]: 13.4%-28.4%). In individuals with a documented history of dengue, vaccination had a VE of 71% (95% CI: 58%-80%) in reducing the incidence of dengue. However, vaccination was not associated with a significant reduction in the overall dengue case risk in individuals without a documented history of dengue (VE: 12%; 95% CI: -21% to 36%). In this last stratum, vaccination was associated with reduced cases due to DENV-1 and DENV-4, but an excess of DENV-2 cases. Interpretation Vaccination led to a significant reduction in reported dengue cases within the target population. The case-control design suggested that this reduction was primarily driven by the benefits observed in individuals with a documented history of dengue. In endemic regions with limited serological testing facilities, a previous history of dengue diagnosis recorded by epidemiological surveillance could be used to triage candidates for CYD-TDV vaccination. Funding Research supported by Sanofi.
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Affiliation(s)
- Fredi Alexander Diaz-Quijano
- Department of Epidemiology, Laboratory of Causal Inference in Epidemiology – LINCE-USP, School of Public Health, University of São Paulo, São Paulo, SP, Brazil
| | | | - Sonia Mara Raboni
- Department of Public Health, Federal University of Paraná, Curitiba, Brazil
| | - Silvia Emiko Shimakura
- Department of Statistics, Federal University of Paraná, Curitiba, Brazil
- Postgraduate Program in Public Health, Federal University of Paraná, Curitiba, Brazil
| | | | - Magda Clara Vieira da Costa-Ribeiro
- Postgraduate Program in Public Health, Federal University of Paraná, Curitiba, Brazil
- Department of Basic Pathology and Postgraduate Program in Microbiology, Parasitology and Pathology, Federal University of Paraná, Curitiba, Brazil
| | - Lineu Silva
- Department of Public Health, Federal University of Paraná, Curitiba, Brazil
| | | | | | - Gabriel Graeff
- Foundation of the Federal University of Paraná, Curitiba, Brazil
| | - Gustavo Almeida
- Postgraduate Program in Public Health, Federal University of Paraná, Curitiba, Brazil
| | - Clara Preto
- Postgraduate Program in Public Health, Federal University of Paraná, Curitiba, Brazil
| | - Karin Regina Luhm
- Department of Public Health, Federal University of Paraná, Curitiba, Brazil
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Vitale M, Lupone CD, Kenneson-Adams A, Ochoa RJ, Ordoñez T, Beltran-Ayala E, Endy TP, Rosenbaum PF, Stewart-Ibarra AM. A comparison of passive surveillance and active cluster-based surveillance for dengue fever in southern coastal Ecuador. BMC Public Health 2020; 20:1065. [PMID: 32631315 PMCID: PMC7336448 DOI: 10.1186/s12889-020-09168-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 06/25/2020] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Dengue is a major emerging infectious disease, endemic throughout the tropics and subtropics, with approximately 2.5 billion people at risk globally. Active (AS) and passive surveillance (PS), when combined, can improve our understanding of dengue's complex disease dynamics to guide effective, targeted public health interventions. The objective of this study was to compare findings from the Ministry of Health (MoH) PS to a prospective AS arbovirus research study in Machala, Ecuador in 2014 and 2015. METHODS Dengue cases in the PS system were compared to laboratory confirmed acute dengue illness cases that entered the AS study during the study period. Variables of interest included age class and sex. Outbreak detection curves by epidemiologic week, overall cumulative incidence and age-specific incidence proportions were calculated. Descriptive statistics were tabulated for all variables of interest. Chi-square tests were performed to compare demographic characteristics between the AS and PS data sets in 2014 and 2015. RESULTS 177 and 245 cases were identified from 1/1/2014 to 12/31/2015 by PS and AS, respectively; nine cases appeared in both systems. AS identified a greater number of laboratory-confirmed cases in 2014, accounting for more than 60% of dengue cases in the study area. In 2015, the opposite trend was observed with PS identifying 60% of the dengue cases in the study area. Peak transmission time in laboratory confirmed dengue illness, as noted by AS and PS was similar in 2014, whereas earlier detection (7 weeks) was observed by AS in 2015. Younger patients were more frequently identified by PS, while older patients were identified more frequently by AS. The cumulative incidence proportion for laboratory confirmed dengue illness reported via PS to the MoH was 4.12 cases per 10,000 residents in 2014, and 2.21 cases per 10,000 residents in 2015. CONCLUSIONS Each surveillance system captured distinct demographic subgroups within the Machala population, possibly due to differences in healthcare seeking behaviors, access to care, emerging threats of other viruses transmitted by the same mosquito vector and/or differences in clinical presentation. Integrating AS with pre-existing PS can aid in identifying additional cases in previously underdiagnosed subpopulations, improving our understanding of disease dynamics, and facilitating the implementation of timely public health interventions.
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Affiliation(s)
- Melissa Vitale
- Institute for Global Health and Translational Science, SUNY Upstate Medical University, 505 Irving Avenue Suite 4200, Syracuse, NY, USA
- Department of Public Health and Preventive Medicine, SUNY Upstate Medical University, 750 East Adams Street, Syracuse, NY, USA
- College of Medicine, MD Program, SUNY Upstate Medical University, 750 East Adams Street, Syracuse, NY, USA
| | - Christina D Lupone
- Institute for Global Health and Translational Science, SUNY Upstate Medical University, 505 Irving Avenue Suite 4200, Syracuse, NY, USA.
- Department of Public Health and Preventive Medicine, SUNY Upstate Medical University, 750 East Adams Street, Syracuse, NY, USA.
| | - Aileen Kenneson-Adams
- Institute for Global Health and Translational Science, SUNY Upstate Medical University, 505 Irving Avenue Suite 4200, Syracuse, NY, USA
| | | | | | - Efráin Beltran-Ayala
- Ministry of Health, Machala, El Oro, Ecuador
- Department of Medicine, Universidad Técnica de Machala, Machala, El Oro, Ecuador
| | - Timothy P Endy
- Institute for Global Health and Translational Science, SUNY Upstate Medical University, 505 Irving Avenue Suite 4200, Syracuse, NY, USA
- Department of Public Health and Preventive Medicine, SUNY Upstate Medical University, 750 East Adams Street, Syracuse, NY, USA
- Department of Microbiology and Immunology, SUNY Upstate Medical University, 750 East Adams Street, Syracuse, NY, USA
| | - Paula F Rosenbaum
- Institute for Global Health and Translational Science, SUNY Upstate Medical University, 505 Irving Avenue Suite 4200, Syracuse, NY, USA
- Department of Public Health and Preventive Medicine, SUNY Upstate Medical University, 750 East Adams Street, Syracuse, NY, USA
| | - Anna M Stewart-Ibarra
- Institute for Global Health and Translational Science, SUNY Upstate Medical University, 505 Irving Avenue Suite 4200, Syracuse, NY, USA
- Department of Public Health and Preventive Medicine, SUNY Upstate Medical University, 750 East Adams Street, Syracuse, NY, USA
- Department of Medicine, SUNY Upstate Medical University, 750 East Adams Street, Syracuse, NY, USA
- Department of Montevideo, Inter-American Institute for Global Change Research, Montevideo, Uruguay
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Martins ABS, Correia FGS, Cavalcanti LPDG, Alencar CH. Dengue in northeastern Brazil: a spatial and temporal perspective. Rev Soc Bras Med Trop 2020; 53:e20200435. [PMID: 33331609 PMCID: PMC7747832 DOI: 10.1590/0037-8682-0435-2020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 10/23/2020] [Indexed: 01/17/2023] Open
Abstract
INTRODUCTION: The state of Ceará (Brazilian Northeast) has a high incidence of dengue. Therefore, we aimed to characterize the temporal patterns and spatial distribution of dengue cases in Ceará during 2001-2019. METHODS: A spatiotemporal ecological study was performed with secondary data. Time-trend analysis was performed using a segmented log-linear regression model to estimate the average annual percentage change (AAPC) and the annual percentage change (APC) in incidence of dengue. We also performed spatiotemporal analysis to identify the place, time, and relative risk (RR) of dengue clusters. RESULTS: There were 539,653 dengue cases. The AAPC reduced over time (-9.5%; 95% confidance interval [CI]: -18.3; -0.3). Three trends were identified-2001-2004: APC=-20.9% (95% CI: -65.1 to 44.8), 2005-2015: APC=7.9% (95% CI: -6.0 to 98.9), and 2016-2019: APC=-48.8% (95% CI: -83.0 to -6.1). During 2001-2007, 10 significant clusters were identified (RR=3.57-14.38: n=4 and RR=0.05-0.39: n=6). During 2008-2013, there was 1 cluster in the western region (RR= 3.40) and four other clusters (RR=0.02-0.15). The last period presented 5 high-RR clusters (RR=2.95-9.24). The low-RR clusters were located in the central-north, central-south, south, and northwest regions. However, the central-west region remained a high-RR cluster region throughout the study period. CONCLUSIONS: Dengue showed a decreasing incidence. During the epidemic years, the southern, eastern, and western regions presented high-risk clusters. Introduction of a new dengue serotype in a low-RR area can cause explosive outbreaks due to population susceptibility.
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Nunes PCG, Daumas RP, Sánchez-Arcila JC, Nogueira RMR, Horta MAP, Dos Santos FB. 30 years of fatal dengue cases in Brazil: a review. BMC Public Health 2019; 19:329. [PMID: 30898104 PMCID: PMC6429821 DOI: 10.1186/s12889-019-6641-4] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Accepted: 03/10/2019] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Over the last 30 years, extensive dengue epidemics have occurred in Brazil, characterized by emergences and re-emergences of different serotypes, a change in the epidemiological profile and an increase in the number of severe and fatal cases. Here, we present a review on the dengue fatal cases that occurred in Brazil in 30 years (1986-2015). METHODS We performed an ecological study by using secondary data on dengue fatal cases obtained in the National System of Reported Diseases (Sistema de Informação de Agravos de Notificação -SINAN) and in the Mortality Information System (SIM), both maintained by the Brazilian Ministry of Health. Cases were analyzed by region, demographic variables, clinical classification and complications based on the data available. RESULTS In 30 years (1986-2015), the Southeast region reported 43% (n = 2225) of all dengue deaths in the country. The Midwest region was responsible for 18% of the fatal cases. After 2000, deaths occurred in almost all states, with the exception of Santa Catarina and Rio Grande do Sul, South region. From 2006 to 2010, the number of deaths increased, with higher rates of mortality, especially in Goiás and Mato Grosso. From 2011 to 2015, Goiás became the state with the highest mortality rate in the country, and Rio Grande do Sul reported its first dengue deaths. In 30 years, a total of 2682 dengue deaths occurred in males and 2455 in females, and an equal distribution between the sexes was observed. From 1986 to 2006, dengue deaths occurred predominantly in individuals over 15 years old, but this scenario changed in 2007-2008. After 2009, fatal cases on individuals above 15 years old became more frequent, with peaks in the years of 2010, 2013 and 2015. CONCLUSIONS The Brazil is experiencing a hyperendemic scenario, which has resulted in the co-circulation of the four DENV serotypes and with the increasing occurrence of severe and fatal cases. The disease surveillance and studies characterizing what has been reported overtime, are still important tools to better understand the factors involved in the disease outcome.
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Affiliation(s)
- Priscila Conrado Guerra Nunes
- Viral Immunology Laboratory, Oswaldo Cruz Institute, IOC, Oswaldo Cruz Foundation, FIOCRUZ, Avenida Brasil, 4365. Manguinhos, Rio de Janeiro, Brazil
| | - Regina Paiva Daumas
- Clinical Epidemiology Laboratory, Evandro Chagas Clinical Research Institute-FIOCRUZ, Avenida Brasil, 4365. Manguinhos, Rio de Janeiro, Brazil
| | - Juan Camilo Sánchez-Arcila
- Viral Immunology Laboratory, Oswaldo Cruz Institute, IOC, Oswaldo Cruz Foundation, FIOCRUZ, Avenida Brasil, 4365. Manguinhos, Rio de Janeiro, Brazil
| | - Rita Maria Ribeiro Nogueira
- Flavivirus Laboratory (LABFLA), Oswaldo Cruz Institute - FIOCRUZ, Avenida Brasil, 4365. Manguinhos, Rio de Janeiro, Brazil
| | - Marco Aurélio Pereira Horta
- Flavivirus Laboratory (LABFLA), Oswaldo Cruz Institute - FIOCRUZ, Avenida Brasil, 4365. Manguinhos, Rio de Janeiro, Brazil
| | - Flávia Barreto Dos Santos
- Viral Immunology Laboratory, Oswaldo Cruz Institute, IOC, Oswaldo Cruz Foundation, FIOCRUZ, Avenida Brasil, 4365. Manguinhos, Rio de Janeiro, Brazil.
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