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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Use of an Extended Premise Condition Index for detection of priority areas for vector control actions

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Author(s):
Barbosa, Gerson Laurindo [1] ; Lage, Mariana de Oliveira [2] ; Andrade, Valmir Roberto [3] ; Alves Gomes, Antonio Henrique [4] ; Quintanilha, Jose Alberto [5] ; Chiaravalloti Neto, Francisco [6]
Total Authors: 6
Affiliation:
[1] Secretaria Saude Estado Sao Paulo, Superintendencia Controle Endemias, Rua Paula Souza 166, BR-01027000 Sao Paulo, SP - Brazil
[2] Univ Sao Paulo, Programa Posgrad Ciencia Ambiental, Ave Prof Luciano Gualberto 1289, BR-05508010 Sao Paulo, SP - Brazil
[3] Secretaria Saude Estado Sao Paulo, Superintendencia Controle Endemias, Serv Reg Campinas, Rua Fernao Pompeu Camargo 372, BR-13041025 Campinas, SP - Brazil
[4] Secretaria Saude Estado Sao Paulo, Superintendencia Controle Endemias, Rua Paula Sousa 166, BR-01027000 Sao Paulo, SP - Brazil
[5] Univ Sao Paulo, Inst Energia & Ambiente, Ave 1289, BR-05508010 Sao Paulo, SP - Brazil
[6] Univ Sao Paulo, Fac Saude Publ, Ave Doutor Arnaldo 715, BR-01246904 Sao Paulo, SP - Brazil
Total Affiliations: 6
Document type: Journal article
Source: Acta Tropica; v. 209, SEP 2020.
Web of Science Citations: 0
Abstract

The Premise Condition Index (PCI), proposed by Tun-Lin and colleagues in 1995, is a score that considers the conditions of a premise as well its yards and degree of shading. They hypothesized that the higher its value the greater the probability of the premise having the presence of Aedes aegypti. This study aimed to evaluate if there is a correspondence between PCI and Ae. aegypti infestation in four areas of a large city in the State of Sao Paulo, Brazil, if the inclusion of new categories related to the presence of animals in premises would increase the probability of detecting predictive areas for vector control actions and, if so, to propose an expanded PCI. The positivity of the premises for the presence of Ae. aegypti was modeled considering a Bernoulli probability distribution, in a Bayesian context using the Integrated Nested Laplace Approximation. The study showed that, in general, the higher the value of the PCI of a premise, the more likely it is to have the presence of Ae. aegypti, and the inclusion of information on the animals' presence can increase the discriminatory power of PCI. These results support the proposition of an extended PCI that would consider, in addition to the conditions of the premise, the presence of animals to classify it regarding the risk of the presence of Ae. aegypti. (AU)

FAPESP's process: 15/06687-3 - Evaluation of importance from the strategic places in dispersion of the vector Aedes aegypti, and the use of premise condition index and remote sensing images for risk areas identification for Aedes aegypti
Grantee:Gerson Laurindo Barbosa
Support Opportunities: Regular Research Grants