Scholarlink

<p>Invasive <i>Aedes</i> mosquitoes are major vectors of arboviral diseases such as dengue, Zika, and chikungunya, posing an increasing threat to global public health. Their recent geographic expansion calls for predictive models to simulate population dynamics and transmission risk. Temperature is a key driver in these models, influencing traits that affect vector competence. Numerous datasets on temperature-dependent traits exist for <i>Aedes aegypti</i> and <i>Aedes albopictus</i>, though they are scattered, inconsistent, and difficult to synthesise. For emerging species like <i>Aedes japonicus</i> and <i>Aedes koreicus</i>, such datasets are scarce. To address these gaps, we developed <Emphasis FontCategory="NonProportional">AedesTraits</Emphasis>, an open-access, machine-readable dataset aligned with VecTraits standards. It compiles and systematises experimental data on temperature-dependent traits across these four <i>Aedes</i> species, covering life-history, morphological, physiological, and behavioural traits. Our synthesis highlights existing knowledge gaps and identifies under-studied species and traits. By promoting data systematisation and accessibility, <Emphasis FontCategory="NonProportional">AedesTraits</Emphasis> supports <i>Aedes</i>–borne disease modelling and fosters international collaboration in the development of forecasting tools for arbovirus outbreaks.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

AedesTraits: A global dataset of temperature–dependent trait responses in Aedes mosquitoes

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月22日

查看全文
  • Daniele Da Re,
  • Veronica Andreo,
  • Tomas Valentin San Miguel,
  • Margo Blaha,
  • Roberto Rosà,
  • Annapaola Rizzoli,
  • Joe Harrison,
  • Sean Sorek,
  • Leah R. Johnson,
  • Paul J. Huxley

摘要

Invasive Aedes mosquitoes are major vectors of arboviral diseases such as dengue, Zika, and chikungunya, posing an increasing threat to global public health. Their recent geographic expansion calls for predictive models to simulate population dynamics and transmission risk. Temperature is a key driver in these models, influencing traits that affect vector competence. Numerous datasets on temperature-dependent traits exist for Aedes aegypti and Aedes albopictus, though they are scattered, inconsistent, and difficult to synthesise. For emerging species like Aedes japonicus and Aedes koreicus, such datasets are scarce. To address these gaps, we developed AedesTraits, an open-access, machine-readable dataset aligned with VecTraits standards. It compiles and systematises experimental data on temperature-dependent traits across these four Aedes species, covering life-history, morphological, physiological, and behavioural traits. Our synthesis highlights existing knowledge gaps and identifies under-studied species and traits. By promoting data systematisation and accessibility, AedesTraits supports Aedes–borne disease modelling and fosters international collaboration in the development of forecasting tools for arbovirus outbreaks.