Primary health care data-based early warning system for dengue outbreaks: a nationwide case study in BrazilResearch in context
Summary: Background: Traditional surveillance presents limitations for early outbreak detection. Primary health care (PHC) administrative data applied to syndromic surveillance offers a cost-effective way to integrate early warning systems (EWS). We evaluate the potential of an EWS for dengue outbr...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-08-01
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| Series: | The Lancet Regional Health. Americas |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667193X25001759 |
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| author | Rejane Santos-Silva Pilar Tavares Veras Florentino Thiago Cerqueira-Silva Vinicius de Araújo Oliveira Juracy Bertoldo Junior George C.G. Barbosa Gerson O. Penna Viviane S. Boaventura Pablo I. Pereira Ramos Manoel Barral-Netto Izabel Marcilio |
| author_facet | Rejane Santos-Silva Pilar Tavares Veras Florentino Thiago Cerqueira-Silva Vinicius de Araújo Oliveira Juracy Bertoldo Junior George C.G. Barbosa Gerson O. Penna Viviane S. Boaventura Pablo I. Pereira Ramos Manoel Barral-Netto Izabel Marcilio |
| author_sort | Rejane Santos-Silva |
| collection | DOAJ |
| description | Summary: Background: Traditional surveillance presents limitations for early outbreak detection. Primary health care (PHC) administrative data applied to syndromic surveillance offers a cost-effective way to integrate early warning systems (EWS). We evaluate the potential of an EWS for dengue outbreaks using PHC data in Brazil. Methods: We applied the Early Aberration Reporting System (EARS-C1 and EARS-C2) to arbovirus-related PHC encounters from October 1, 2022, to March 1, 2024, to establish an EWS across 5570 municipalities. We assessed EWS timeliness, sensitivity, and positive predictive value (PPV) against fixed-incidence dengue outbreak thresholds. Findings: Arbovirus-related PHC encounters occurred in 5364 (96.3%) and dengue cases in 5269 (94.6%) Brazilian municipalities. PHC-based warnings anticipated 48.5% (100 cases/100,000 inhabitants), and 68.4% (300/100,000) of outbreaks detected by existing surveillance. Timeliness was higher in municipalities with over 100,000 inhabitants. Interpretation: The EARS algorithm applied to PHC data anticipated outbreaks up to four weeks before suspected case reporting. Its use of routine data ensures broader coverage and scalability. This study demonstrates the feasibility of integrating PHC data into an EWS for early dengue outbreak detection in Brazil. Funding: Rockefeller Foundation’s Health Initiative and Fundação de Amparo à Pesquisa do Estado da Bahia, Brazil. |
| format | Article |
| id | doaj-art-a601c8c71b2b4cec8f5343f533e43d90 |
| institution | Kabale University |
| issn | 2667-193X |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | The Lancet Regional Health. Americas |
| spelling | doaj-art-a601c8c71b2b4cec8f5343f533e43d902025-08-20T03:30:15ZengElsevierThe Lancet Regional Health. Americas2667-193X2025-08-014810116510.1016/j.lana.2025.101165Primary health care data-based early warning system for dengue outbreaks: a nationwide case study in BrazilResearch in contextRejane Santos-Silva0Pilar Tavares Veras Florentino1Thiago Cerqueira-Silva2Vinicius de Araújo Oliveira3Juracy Bertoldo Junior4George C.G. Barbosa5Gerson O. Penna6Viviane S. Boaventura7Pablo I. Pereira Ramos8Manoel Barral-Netto9Izabel Marcilio10Centro de Integração de Dados e Conhecimento para Saúde (Cidacs), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (Fiocruz Bahia), Salvador, BrazilCentro de Integração de Dados e Conhecimento para Saúde (Cidacs), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (Fiocruz Bahia), Salvador, Brazil; Laboratório de Medicina e Saúde Pública de Precisão, Fundação Oswaldo Cruz, Salvador, BrazilLaboratório de Medicina e Saúde Pública de Precisão, Fundação Oswaldo Cruz, Salvador, Brazil; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United KingdomCentro de Integração de Dados e Conhecimento para Saúde (Cidacs), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (Fiocruz Bahia), Salvador, Brazil; Faculdade de Medicina da Bahia, Universidade Federal da Bahia, Salvador, BrazilCentro de Integração de Dados e Conhecimento para Saúde (Cidacs), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (Fiocruz Bahia), Salvador, BrazilCentro de Integração de Dados e Conhecimento para Saúde (Cidacs), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (Fiocruz Bahia), Salvador, BrazilNúcleo de Medicina Tropical, Universidade de Brasília, Brasília, Brazil; Escola de Governo Fiocruz Brasília, Fiocruz Brasília, Brasília, BrazilLaboratório de Medicina e Saúde Pública de Precisão, Fundação Oswaldo Cruz, Salvador, Brazil; Faculdade de Medicina da Bahia, Universidade Federal da Bahia, Salvador, BrazilCentro de Integração de Dados e Conhecimento para Saúde (Cidacs), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (Fiocruz Bahia), Salvador, BrazilCentro de Integração de Dados e Conhecimento para Saúde (Cidacs), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (Fiocruz Bahia), Salvador, Brazil; Laboratório de Medicina e Saúde Pública de Precisão, Fundação Oswaldo Cruz, Salvador, Brazil; Faculdade de Medicina da Bahia, Universidade Federal da Bahia, Salvador, BrazilCentro de Integração de Dados e Conhecimento para Saúde (Cidacs), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (Fiocruz Bahia), Salvador, Brazil; Escola Bahiana de Medicina e Saúde Pública, Salvador, Brazil; Corresponding author. I. Marcilio Centro de Integração de Dados e Conhecimento para Saúde, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Parque Tecnológico Edf. Tecnocentro, Rua Mundo 121, sala 315, Salvador, BA 41745-715, Brazil.Summary: Background: Traditional surveillance presents limitations for early outbreak detection. Primary health care (PHC) administrative data applied to syndromic surveillance offers a cost-effective way to integrate early warning systems (EWS). We evaluate the potential of an EWS for dengue outbreaks using PHC data in Brazil. Methods: We applied the Early Aberration Reporting System (EARS-C1 and EARS-C2) to arbovirus-related PHC encounters from October 1, 2022, to March 1, 2024, to establish an EWS across 5570 municipalities. We assessed EWS timeliness, sensitivity, and positive predictive value (PPV) against fixed-incidence dengue outbreak thresholds. Findings: Arbovirus-related PHC encounters occurred in 5364 (96.3%) and dengue cases in 5269 (94.6%) Brazilian municipalities. PHC-based warnings anticipated 48.5% (100 cases/100,000 inhabitants), and 68.4% (300/100,000) of outbreaks detected by existing surveillance. Timeliness was higher in municipalities with over 100,000 inhabitants. Interpretation: The EARS algorithm applied to PHC data anticipated outbreaks up to four weeks before suspected case reporting. Its use of routine data ensures broader coverage and scalability. This study demonstrates the feasibility of integrating PHC data into an EWS for early dengue outbreak detection in Brazil. Funding: Rockefeller Foundation’s Health Initiative and Fundação de Amparo à Pesquisa do Estado da Bahia, Brazil.http://www.sciencedirect.com/science/article/pii/S2667193X25001759Early warning systemDengueArbovirusSurveillance |
| spellingShingle | Rejane Santos-Silva Pilar Tavares Veras Florentino Thiago Cerqueira-Silva Vinicius de Araújo Oliveira Juracy Bertoldo Junior George C.G. Barbosa Gerson O. Penna Viviane S. Boaventura Pablo I. Pereira Ramos Manoel Barral-Netto Izabel Marcilio Primary health care data-based early warning system for dengue outbreaks: a nationwide case study in BrazilResearch in context The Lancet Regional Health. Americas Early warning system Dengue Arbovirus Surveillance |
| title | Primary health care data-based early warning system for dengue outbreaks: a nationwide case study in BrazilResearch in context |
| title_full | Primary health care data-based early warning system for dengue outbreaks: a nationwide case study in BrazilResearch in context |
| title_fullStr | Primary health care data-based early warning system for dengue outbreaks: a nationwide case study in BrazilResearch in context |
| title_full_unstemmed | Primary health care data-based early warning system for dengue outbreaks: a nationwide case study in BrazilResearch in context |
| title_short | Primary health care data-based early warning system for dengue outbreaks: a nationwide case study in BrazilResearch in context |
| title_sort | primary health care data based early warning system for dengue outbreaks a nationwide case study in brazilresearch in context |
| topic | Early warning system Dengue Arbovirus Surveillance |
| url | http://www.sciencedirect.com/science/article/pii/S2667193X25001759 |
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