Literature DB >> 26812472

Accuracy of Dengue Reporting by National Surveillance System, Brazil.

Monaise M O Silva, Moreno S Rodrigues, Igor A D Paploski, Mariana Kikuti, Amelia M Kasper, Jaqueline S Cruz, Tássia L Queiroz, Aline S Tavares, Perla M Santana, Josélio M G Araújo, Albert I Ko, Mitermayer Galvão Reis, Guilherme S Ribeiro.   

Abstract

Entities:  

Keywords:  Brazil; SINAN; Sistema de Informação de Agravos de Notificação; acute febrile illness; dengue; dimensional measurement accuracy; disease notification; infectious disease reporting; mandatory reporting; viruses

Mesh:

Substances:

Year:  2016        PMID: 26812472      PMCID: PMC4734515          DOI: 10.3201/eid2202.150495

Source DB:  PubMed          Journal:  Emerg Infect Dis        ISSN: 1080-6040            Impact factor:   6.883


× No keyword cloud information.
To the Editor: Dengue is an underreported disease globally. In 2010, the World Health Organization recorded 2.2 million dengue cases (), but models projected that the number of symptomatic dengue cases might have been as high as 96 million (). Brazil reports more cases of dengue than any other country (); however, the degree of dengue underreporting in Brazil is unknown. We conducted a study to evaluate dengue underreporting by Brazil’s Notifiable Diseases Information System (Sistema de Informação de Agravos de Notificação [SINAN]). From January 1, 2009, through December 31, 2011, we performed enhanced surveillance for acute febrile illness (AFI) in a public emergency unit in Salvador, Brazil. The surveillance team enrolled outpatients >5 years of age with measured (>37.8°C) or reported fever. Patients or their legal guardians provided written consent. The study was approved by the Oswaldo Cruz Foundation Ethics Committee, Brazil’s National Council for Ethics in Research, and the Yale Institutional Review Board. We collected participants’ blood samples at study enrollment and >15 days later. Acute-phase serum samples were tested by dengue nonstructural protein 1 ELISA and IgM ELISA (Panbio Diagnostics, East Brisbane, Queensland, Australia). Convalescent-phase serum samples were tested by IgM ELISA. In concordance with case-reporting guidelines in Brazil (), we defined dengue cases by a positive nonstructural protein 1 ELISA result or a positive acute-phase or convalescent-phase IgM ELISA result. All others were classified as nondengue AFI. We then identified which study patients were officially reported to SINAN as having a suspected case of dengue. In Brazil, notification of suspected dengue cases is mandatory. A suspected case is defined as illness in a person from an area of dengue transmission or Aedes aegypti mosquito infestation who has symptoms of dengue (fever of <7 days’ duration, plus >2 of the following symptoms: nausea/vomiting, exanthema, myalgia, arthralgia, headache, retro-orbital pain, petechiae/positive tourniquet test, or leukopenia). We used Link Plus software (CDC-Link Plus Production 2.0; Centers for Disease Control and Prevention, Atlanta, GA, USA) to perform probabilistic record linkage from our database with official reports in the SINAN database. The records were matched based on the patients’ first names, last names, and dates of birth. We then manually reviewed the matches to confirm the pairs. On the basis of the results, we calculated the sensitivity, specificity, positive predictive value (PPV), and negative predictive value of the national surveillance system. We calculated accuracy measurements with 95% CIs for the overall study period and for each study year, age group (5–14 vs. >15 years), and seasonal prevalence of dengue (months of low vs. high dengue transmission, defined by dengue detection in <20% vs. >20% of the AFI patients, respectively). We estimated multiplication factors by dividing the number of dengue cases in our study by the number of study patients who were reported to SINAN as having dengue. Of the 3,864 AFI patients identified during the 3-year study period, 997 (25.8%) had laboratory evidence of dengue infection, and 2,867 (74.2%) were classified as having nondengue AFI. Of the 997 dengue cases, 57 were reported to SINAN (sensitivity 5.7%) (Table). Of the 2,867 nondengue AFI cases, 26 were reported to SINAN as dengue cases (false-positive ratio 0.9%, specificity 99.1%). None of these 26 cases had laboratory confirmation in the SINAN database. The PPV for reporting to SINAN was 68.7%, and the negative predictive value was 75.1% (Table). PPV was higher among patients >15 years of age, which might be attributable to atypical presentations of dengue in children (,).
Table

Accuracy of a national surveillance system for recording cases of suspected dengue among patients with acute febrile illness who visited an emergency health unit of Salvador, Brazil, January 1, 2009–December 31, 2011*

Notification status of AFI patients†
Laboratory status of AFI patients, no.‡
Dengue prevalence, %§
% (95% CI)
MF¶
Dengue
Nondengue AFI
SENS
SPEC
PPV
NPV
Overall
Reported572625.85.7
(4.4–7.3)99.1
(98.7–99.4)68.7
(58.1–77.6)75.1
(73.7–76.5)12.0
Not reported
940
2,841






Study year
2009
Reported4410.33.3
(1.3–8.3)99.6
(99.0–99.9)50.0
(21.5–78.5)90.0
(88.1- 91.6)15.0
Not reported1161,039
2010
Reported27833.86.0
(4.1–8.6)99.1
(98.2–99.5)77.1
(61.0–87.9)67.4
(64.8- 69.9)12.9
Not reported423873
2011
Reported261431.26.1
(4.2–8.8)98.5
(97.5–99.1)65.0
(49.5–77.9)69.9
(67.3- 72.3)10.7
Not reported
401
929






Age group, y
5–14
Reported231525.55.8
(3.9–8.6)98.7
(97.9–99.2)60.5
(44.7–74.4)75.4
(73.2–77.5)10.4
Not reported3721,139
≥15
Reported341126.05.6
(4.0–7.8)99.4
(98.9–99.6)75.6
(61.3–85.8)75.0
(73.2–76.7)13.8
Not reported
568
1,702






Monthly dengue prevalence§
≥20%
Reported521838.16.7
(5.2–8.7)98.6
(97.7–99.1)74.3
(63.0–83.1)63.1
(61.0–65.2)11.1
Not reported7221,235
≥20%
Reported5812.12.2
(1.0–5.2)99.5
(99.0–99.8)38.5
(17.7–64.5)88.0
(86.5–89.5)17.2
Not reported2181,606

*AFI, acute febrile illness; SINAN, Sistema de Informação de Agravos de Notificação (Notifiable Diseases Information System, Brazil); SENS, sensitivity; SPEC, specificity; PPV, positive predictive value; NPV, negative predictive value; MF, multiplication factor.
†Notification status of the AFI patients was ascertained from the SINAN database on reported dengue cases for the city of Salvador. SINAN database was obtained from the Salvador Secretary of Health in January 2013.
‡Acute-phase serum samples from AFI patients were systematically tested for dengue by nonstructural protein 1 ELISA and IgM ELISA; convalescent-phase serum samples were also tested by IgM ELISA.
§Among AFI patients assisted at the sentinel surveillance emergency unit.
¶Laboratory-confirmed dengue/AFI patients reported as having a suspected case of dengue.

*AFI, acute febrile illness; SINAN, Sistema de Informação de Agravos de Notificação (Notifiable Diseases Information System, Brazil); SENS, sensitivity; SPEC, specificity; PPV, positive predictive value; NPV, negative predictive value; MF, multiplication factor.
†Notification status of the AFI patients was ascertained from the SINAN database on reported dengue cases for the city of Salvador. SINAN database was obtained from the Salvador Secretary of Health in January 2013.
‡Acute-phase serum samples from AFI patients were systematically tested for dengue by nonstructural protein 1 ELISA and IgM ELISA; convalescent-phase serum samples were also tested by IgM ELISA.
§Among AFI patients assisted at the sentinel surveillance emergency unit.
¶Laboratory-confirmed dengue/AFI patients reported as having a suspected case of dengue. We found that 1 in 4 patients with AFI had laboratory evidence of dengue infection. However, for every 20 dengue patients that we identified, only about 1 had been reported to SINAN as having dengue. During periods of low dengue transmission, only about 1 in 40 dengue cases identified was reported. Conversely, among the patients who were reported as having dengue, 31.2% did not have the disease; this percentage reached 61.5% in low-transmission periods. We estimated that overall, there were 12 dengue cases per reported case in the community, but in months of low dengue transmission, this ratio was >17:1 (Table). Comparable results have been observed in Nicaragua, Thailand, and Cambodia (–). By applying the estimated multiplication factor to the study period’s mean annual incidence of 303.8 reported dengue cases/100,000 Salvador residents (), we estimated that the actual mean annual dengue incidence for Salvador was 3,645.7 cases/100,000 residents. We showed that dengue surveillance substantially underestimated disease burden in Brazil, especially in what are considered low-transmission periods. Dengue underreporting has been attributed to passive case detection, which fails to identify persons with dengue who do not seek health care (). We also showed that surveillance failed to detect dengue cases among symptomatic patients seeking health care. Novel surveillance tools, such as active syndromic surveillance and point-of-care testing, should be applied to improve estimates of dengue incidence. Furthermore, given the recent emergence of chikungunya and Zika viruses in Brazil (), improved surveillance and laboratory diagnostics are needed to avert misclassification and mismanagement of cases.
  7 in total

1.  Under-recognition and reporting of dengue in Cambodia: a capture-recapture analysis of the National Dengue Surveillance System.

Authors:  S Vong; S Goyet; S Ly; C Ngan; R Huy; V Duong; O Wichmann; G W Letson; H S Margolis; P Buchy
Journal:  Epidemiol Infect       Date:  2011-06-21       Impact factor: 2.451

2.  High dengue case capture rate in four years of a cohort study in Nicaragua compared to national surveillance data.

Authors:  Katherine Standish; Guillermina Kuan; William Avilés; Angel Balmaseda; Eva Harris
Journal:  PLoS Negl Trop Dis       Date:  2010-03-16

3.  Differences in clinical and laboratory characteristics and disease severity between children and adults with dengue virus infection in Taiwan, 2002.

Authors:  Chin-Chou Wang; Ing-Kit Lee; Mao-Chang Su; Hung-I Lin; Yi-Chuan Huang; Shih-Feng Liu; Chao-Chien Wu; Meng-Chih Lin
Journal:  Trans R Soc Trop Med Hyg       Date:  2009-06-04       Impact factor: 2.184

4.  The differences of clinical manifestations and laboratory findings in children and adults with dengue virus infection.

Authors:  Leera Kittigul; Piyamard Pitakarnjanakul; Dusit Sujirarat; Kanokrat Siripanichgon
Journal:  J Clin Virol       Date:  2007-05-15       Impact factor: 3.168

5.  Dengue in Thailand and Cambodia: an assessment of the degree of underrecognized disease burden based on reported cases.

Authors:  Ole Wichmann; In-Kyu Yoon; Sirenda Vong; Kriengsak Limkittikul; Robert V Gibbons; Mammen P Mammen; Sowath Ly; Philippe Buchy; Chukiat Sirivichayakul; Rome Buathong; Rekol Huy; G William Letson; Arunee Sabchareon
Journal:  PLoS Negl Trop Dis       Date:  2011-03-29

6.  The global distribution and burden of dengue.

Authors:  Samir Bhatt; Peter W Gething; Oliver J Brady; Jane P Messina; Andrew W Farlow; Catherine L Moyes; John M Drake; John S Brownstein; Anne G Hoen; Osman Sankoh; Monica F Myers; Dylan B George; Thomas Jaenisch; G R William Wint; Cameron P Simmons; Thomas W Scott; Jeremy J Farrar; Simon I Hay
Journal:  Nature       Date:  2013-04-07       Impact factor: 49.962

7.  Outbreak of Exanthematous Illness Associated with Zika, Chikungunya, and Dengue Viruses, Salvador, Brazil.

Authors:  Cristiane W Cardoso; Igor A D Paploski; Mariana Kikuti; Moreno S Rodrigues; Monaise M O Silva; Gubio S Campos; Silvia I Sardi; Uriel Kitron; Mitermayer G Reis; Guilherme S Ribeiro
Journal:  Emerg Infect Dis       Date:  2015-12       Impact factor: 6.883

  7 in total
  31 in total

1.  Zika Virus and the Safety of Blood Supply in Brazil: A Retrospective Epidemiological Evaluation.

Authors:  Bruno Deltreggia Benites; Daniele Rocha; Elisabete Andrade; Daniela T Godoy; Patrícia Alvarez; Marcelo Addas-Carvalho
Journal:  Am J Trop Med Hyg       Date:  2019-01       Impact factor: 2.345

2.  Recurrent Potent Human Neutralizing Antibodies to Zika Virus in Brazil and Mexico.

Authors:  Davide F Robbiani; Leonia Bozzacco; Jennifer R Keeffe; Ricardo Khouri; Priscilla C Olsen; Anna Gazumyan; Dennis Schaefer-Babajew; Santiago Avila-Rios; Lilian Nogueira; Roshni Patel; Stephanie A Azzopardi; Lion F K Uhl; Mohsan Saeed; Edgar E Sevilla-Reyes; Marianna Agudelo; Kai-Hui Yao; Jovana Golijanin; Harry B Gristick; Yu E Lee; Arlene Hurley; Marina Caskey; Joy Pai; Thiago Oliveira; Elsio A Wunder; Gielson Sacramento; Nivison Nery; Cibele Orge; Federico Costa; Mitermayer G Reis; Neena M Thomas; Thomas Eisenreich; Daniel M Weinberger; Antonio R P de Almeida; Anthony P West; Charles M Rice; Pamela J Bjorkman; Gustavo Reyes-Teran; Albert I Ko; Margaret R MacDonald; Michel C Nussenzweig
Journal:  Cell       Date:  2017-05-04       Impact factor: 41.582

3.  Seroprevalence of Chikungunya Virus in a Rural Community in Brazil.

Authors:  Rivaldo V Cunha; Karen S Trinta; Camila A Montalbano; Michel V F Sucupira; Maricelia M de Lima; Erenilde Marques; Izilyanne H Romanholi; Julio Croda
Journal:  PLoS Negl Trop Dis       Date:  2017-01-20

4.  Genomic and epidemiological characterisation of a dengue virus outbreak among blood donors in Brazil.

Authors:  Nuno R Faria; Antonio Charlys da Costa; José Lourenço; Paula Loureiro; Maria Esther Lopes; Roberto Ribeiro; Cecilia Salete Alencar; Moritz U G Kraemer; Christian J Villabona-Arenas; Chieh-Hsi Wu; Julien Thézé; Kamran Khan; Shannon E Brent; Camila Romano; Eric Delwart; Brian Custer; Michael P Busch; Oliver G Pybus; Ester C Sabino
Journal:  Sci Rep       Date:  2017-11-09       Impact factor: 4.379

5.  Epidemiological and ecological determinants of Zika virus transmission in an urban setting.

Authors:  José Lourenço; Maricelia Maia de Lima; Nuno Rodrigues Faria; Andrew Walker; Moritz Ug Kraemer; Christian Julian Villabona-Arenas; Ben Lambert; Erenilde Marques de Cerqueira; Oliver G Pybus; Luiz Cj Alcantara; Mario Recker
Journal:  Elife       Date:  2017-09-09       Impact factor: 8.140

6.  Zika virus in the Americas: Early epidemiological and genetic findings.

Authors:  Nuno Rodrigues Faria; Raimunda do Socorro da Silva Azevedo; Oliver G Pybus; Marcio R T Nunes; Pedro F C Vasconcelos; Moritz U G Kraemer; Renato Souza; Mariana Sequetin Cunha; Sarah C Hill; Julien Thézé; Michael B Bonsall; Thomas A Bowden; Ilona Rissanen; Iray Maria Rocco; Juliana Silva Nogueira; Adriana Yurika Maeda; Fernanda Giseli da Silva Vasami; Fernando Luiz de Lima Macedo; Akemi Suzuki; Sueli Guerreiro Rodrigues; Ana Cecilia Ribeiro Cruz; Bruno Tardeli Nunes; Daniele Barbosa de Almeida Medeiros; Daniela Sueli Guerreiro Rodrigues; Alice Louize Nunes Queiroz; Eliana Vieira Pinto da Silva; Daniele Freitas Henriques; Elisabeth Salbe Travassos da Rosa; Consuelo Silva de Oliveira; Livia Caricio Martins; Helena Baldez Vasconcelos; Livia Medeiros Neves Casseb; Darlene de Brito Simith; Jane P Messina; Leandro Abade; José Lourenço; Luiz Carlos Junior Alcantara; Maricélia Maia de Lima; Marta Giovanetti; Simon I Hay; Rodrigo Santos de Oliveira; Poliana da Silva Lemos; Layanna Freitas de Oliveira; Clayton Pereira Silva de Lima; Sandro Patroca da Silva; Janaina Mota de Vasconcelos; Luciano Franco; Jedson Ferreira Cardoso; João Lídio da Silva Gonçalves Vianez-Júnior; Daiana Mir; Gonzalo Bello; Edson Delatorre; Kamran Khan; Marisa Creatore; Giovanini Evelim Coelho; Wanderson Kleber de Oliveira; Robert Tesh
Journal:  Science       Date:  2016-03-24       Impact factor: 47.728

7.  Community context and sub-neighborhood scale detail to explain dengue, chikungunya and Zika patterns in Cali, Colombia.

Authors:  Amy R Krystosik; Andrew Curtis; Paola Buritica; Jayakrishnan Ajayakumar; Robert Squires; Diana Dávalos; Robinson Pacheco; Madhav P Bhatta; Mark A James
Journal:  PLoS One       Date:  2017-08-02       Impact factor: 3.240

Review 8.  Challenges in dengue research: A computational perspective.

Authors:  José Lourenço; Warren Tennant; Nuno R Faria; Andrew Walker; Sunetra Gupta; Mario Recker
Journal:  Evol Appl       Date:  2017-11-05       Impact factor: 5.183

9.  Transmission of Chikungunya Virus in an Urban Slum, Brazil.

Authors:  Rosângela O Anjos; Vánio André Mugabe; Patrícia S S Moreira; Caroline X Carvalho; Moyra M Portilho; Ricardo Khouri; Gielson A Sacramento; Nivison R R Nery; Mitermayer G Reis; Uriel D Kitron; Albert I Ko; Federico Costa; Guilherme S Ribeiro
Journal:  Emerg Infect Dis       Date:  2020-07       Impact factor: 6.883

10.  Untapped Potential: A Qualitative Study of a Hospital-Based Dengue Surveillance System.

Authors:  Sulistyawati Sulistyawati; Maria Nilsson; Marlita Putri Ekasari; Surahma Asti Mulasari; Tri Wahyuni Sukesi; Retna Siwi Padmawati; Åsa Holmner
Journal:  Am J Trop Med Hyg       Date:  2020-05-07       Impact factor: 2.345

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.