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Probability of dengue transmission and propagation in a non-endemic temperate area: conceptual model and decision risk levels for early alert, prevention and control.
Marques-Toledo, Cecilia A; Bendati, Maria Mercedes; Codeço, Claudia T; Teixeira, Mauro M.
Affiliation
  • Marques-Toledo CA; Departamento de Bioquimica e Imunologia do Instituto de Ciencias Biologicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil. ceciliamarquestoledo@ufmg.br.
  • Bendati MM; Vigilancia de Roedores e Vetores da Secretaria Municipal de Saude (CGVS/SMS), Porto Alegre, Brazil.
  • Codeço CT; Programa de Computacao Cientifica, Fundacao Oswaldo Cruz, Rio de Janeiro, Brazil.
  • Teixeira MM; Departamento de Bioquimica e Imunologia do Instituto de Ciencias Biologicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
Parasit Vectors ; 12(1): 38, 2019 Jan 16.
Article in En | MEDLINE | ID: mdl-30651125
ABSTRACT

BACKGROUND:

Dengue viruses have spread rapidly across tropical regions of the world in recent decades. Today, dengue transmission is observed in the Americas, Southeast Asia, Western Pacific, Africa and in non-endemic areas of the USA and Europe. Dengue is responsible for 16% of travel-related febrile illnesses. Although most prevalent in tropical areas, risk maps indicate that subtropical regions are suitable for transmission. Dengue-control programs in these regions should focus on minimizing virus importation, community engagement, improved vector surveillance and control.

RESULTS:

We developed a conceptual model for the probability of local introduction and propagation of dengue, comprising disease vulnerability and receptivity, in a temperate area, considering risk factors and social media indicators. Using a rich data set from a temperate area in the south of Brazil (where there is active surveillance of mosquitoes, viruses and human cases), we used a conceptual model as a framework to build two probabilistic models to estimate the probability of initiation and propagation of local dengue transmission. The final models estimated with good accuracy the probabilities of local transmission and propagation, with three and four weeks in advance, respectively. Vulnerability indicators (number of imported cases and dengue virus circulation in mosquitoes) and a receptivity indicator (vector abundance) could be optimally integrated with tweets and temperature data to estimate probability of early local dengue transmission.

CONCLUSIONS:

We demonstrated how vulnerability and receptivity indicators can be integrated into probabilistic models to estimate initiation and propagation of dengue transmission. The models successfully estimate disease risk in different scenarios and periods of the year. We propose a decision model with three different risk levels to assist in the planning of prevention and control measures in temperate regions at risk of dengue introduction.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Disease Outbreaks / Endemic Diseases / Dengue / Dengue Virus / Models, Biological Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Adolescent / Adult / Aged / Aged80 / Animals / Child / Child, preschool / Female / Humans / Infant Country/Region as subject: America do sul / Brasil Language: En Journal: Parasit Vectors Year: 2019 Document type: Article Affiliation country: Brazil

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Disease Outbreaks / Endemic Diseases / Dengue / Dengue Virus / Models, Biological Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Adolescent / Adult / Aged / Aged80 / Animals / Child / Child, preschool / Female / Humans / Infant Country/Region as subject: America do sul / Brasil Language: En Journal: Parasit Vectors Year: 2019 Document type: Article Affiliation country: Brazil