A weather-driven mathematical model of Culex population abundance and the impact of vector control interventions

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Bhowmick, Suman, Irwin, Patrick, Lopez, Kristina, Fritz, Megan Lindsay, Smith, Rebecca Lee
Natura: Preprint
Pubblicazione: 2024
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866913505649623040
author Bhowmick, Suman
Irwin, Patrick
Lopez, Kristina
Fritz, Megan Lindsay
Smith, Rebecca Lee
author_facet Bhowmick, Suman
Irwin, Patrick
Lopez, Kristina
Fritz, Megan Lindsay
Smith, Rebecca Lee
contents Even as the incidence of mosquito-borne diseases like West Nile Virus (WNV) in North America has risen over the past decade, effectively modelling mosquito population density or, the abundance has proven to be a persistent challenge. It is critical to capture the fluctuations in mosquito abundance across seasons in order to forecast the varying risk of disease transmission from one year to the next. We develop a process-based mechanistic weather-driven Ordinary Differential Equation (ODE) model to study the population biology of both aqueous and terrestrial stages of mosquito population. The progression of mosquito lifecycle through these stages is influenced by different factors, including temperature, daylight hours, intra-species competition and the availability of aquatic habitats. Weather-driven parameters are utilised in our work, are a combination of laboratory research and literature data. In our model, we include precipitation data as a substitute for evaluating additional mortality in the mosquito population. We compute the \textit{Basic offspring number} of the associated model and perform sensitivity analysis. Finally, we employ our model to assess the effectiveness of various adulticides strategies to predict the reduction in mosquito population. This enhancement in modelling of mosquito abundance can be instrumental in guiding interventions aimed at reducing mosquito populations and mitigating mosquito-borne diseases such as the WNV.
format Preprint
id arxiv_https___arxiv_org_abs_2409_11550
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A weather-driven mathematical model of Culex population abundance and the impact of vector control interventions
Bhowmick, Suman
Irwin, Patrick
Lopez, Kristina
Fritz, Megan Lindsay
Smith, Rebecca Lee
Populations and Evolution
Biological Physics
Even as the incidence of mosquito-borne diseases like West Nile Virus (WNV) in North America has risen over the past decade, effectively modelling mosquito population density or, the abundance has proven to be a persistent challenge. It is critical to capture the fluctuations in mosquito abundance across seasons in order to forecast the varying risk of disease transmission from one year to the next. We develop a process-based mechanistic weather-driven Ordinary Differential Equation (ODE) model to study the population biology of both aqueous and terrestrial stages of mosquito population. The progression of mosquito lifecycle through these stages is influenced by different factors, including temperature, daylight hours, intra-species competition and the availability of aquatic habitats. Weather-driven parameters are utilised in our work, are a combination of laboratory research and literature data. In our model, we include precipitation data as a substitute for evaluating additional mortality in the mosquito population. We compute the \textit{Basic offspring number} of the associated model and perform sensitivity analysis. Finally, we employ our model to assess the effectiveness of various adulticides strategies to predict the reduction in mosquito population. This enhancement in modelling of mosquito abundance can be instrumental in guiding interventions aimed at reducing mosquito populations and mitigating mosquito-borne diseases such as the WNV.
title A weather-driven mathematical model of Culex population abundance and the impact of vector control interventions
topic Populations and Evolution
Biological Physics
url https://arxiv.org/abs/2409.11550