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Determining dengue infection risk in the Colombo district of Sri Lanka by inferencing the genetic parameters of Aedes mosquitoes.
Chathurangika, Piyumi; Premadasa, Lakmini S; Perera, S S N; De Silva, Kushani.
Afiliação
  • Chathurangika P; Research & Development Centre for Mathematical Modeling, Department of Mathematics, Faculty of Science, University of Colombo, 00030, Colombo, Sri Lanka.
  • Premadasa LS; International Center for the Advancement of Research and Education (I·CARE), Texas Biomedical Research Institute, San Antonio, 78227, TX, USA.
  • Perera SSN; Research & Development Centre for Mathematical Modeling, Department of Mathematics, Faculty of Science, University of Colombo, 00030, Colombo, Sri Lanka.
  • De Silva K; Research & Development Centre for Mathematical Modeling, Department of Mathematics, Faculty of Science, University of Colombo, 00030, Colombo, Sri Lanka. kdesilva@maths.cmb.ac.lk.
BMC Infect Dis ; 24(1): 944, 2024 Sep 09.
Article em En | MEDLINE | ID: mdl-39251932
ABSTRACT

BACKGROUND:

For decades, dengue has posed a significant threat as a viral infectious disease, affecting numerous human lives globally, particularly in tropical regions, yet no cure has been discovered. The genetic trait of vector competence in Aedes mosquitoes, which facilitates dengue transmission, is difficult to measure and highly sensitive to environmental changes.

METHODS:

In this study we attempt, for the first time in a non-laboratory setting, to quantify the vector competence of Aedes mosquitoes assuming its homogeneity across both species; aegypti and albopictus and across the four Dengue serotypes. Estimating vector competence in relation to varying rainfall patterns was focused in this study to showcase the changes in this vector trait with respect to environmental variables. We quantify it using an existing mathematical model originally developed for malaria in a Bayesian inferencing setup. We conducted this study in the Colombo district of Sri Lanka where the highest number of human populations are threatened with dengue. Colombo district experiences continuous favorable temperature and humidity levels throughout the year creating ideal conditions for Aedes mosquitoes to thrive and transmit the Dengue disease. Therefore we only used the highly variable and seasonal rainfall as the primary environmental variable as it significantly influences the number of breeding sites and thereby impacting the population dynamics of Aedes.

RESULTS:

Our research successfully deduced vector competence values for the four identified seasons based on Monsoon rainfalls experienced in Colombo within a year. We used dengue data from 2009 - 2022 to infer the estimates. These estimated values have been corroborated through experimental studies documented in the literature, thereby validating the malaria model to estimate vector competence for dengue disease.

CONCLUSION:

Our research findings conclude that environmental conditions can amplify vector competence within specific seasons, categorized by their environmental attributes. Additionally, the deduced vector competence offers compelling evidence that it impacts disease transmission, irrespective of geographical location, climate, or environmental factors.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aedes / Dengue / Vírus da Dengue / Mosquitos Vetores Limite: Animals / Humans País/Região como assunto: Asia Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aedes / Dengue / Vírus da Dengue / Mosquitos Vetores Limite: Animals / Humans País/Região como assunto: Asia Idioma: En Ano de publicação: 2024 Tipo de documento: Article