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The current landscape of software tools for the climate-sensitive infectious disease modelling community.
Ryan, Sadie J; Lippi, Catherine A; Caplan, Talia; Diaz, Avriel; Dunbar, Willy; Grover, Shruti; Johnson, Simon; Knowles, Rebecca; Lowe, Rachel; Mateen, Bilal A; Thomson, Madeleine C; Stewart-Ibarra, Anna M.
Afiliação
  • Ryan SJ; Quantitative Disease Ecology and Conservation Laboratory Group, Department of Geography, University of Florida, Gainesville, FL, USA; Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA. Electronic address: sjryan@ufl.edu.
  • Lippi CA; Quantitative Disease Ecology and Conservation Laboratory Group, Department of Geography, University of Florida, Gainesville, FL, USA; Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA.
  • Caplan T; The Wellcome Trust, London, UK.
  • Diaz A; Department of Earth and Environmental Sciences, Columbia University, New York, NY, USA.
  • Dunbar W; National Collaborating Centre for Healthy Public Policy, Montreal, QC, Canada.
  • Grover S; Hetco Design, London, UK.
  • Johnson S; Hetco Design, London, UK.
  • Knowles R; The Wellcome Trust, London, UK.
  • Lowe R; Barcelona Supercomputing Center, Barcelona, Spain; Catalan Institution for Research and Advanced Studies, Barcelona, Spain; Centre on Climate Change & Planetary Health and Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.
  • Mateen BA; The Wellcome Trust, London, UK.
  • Thomson MC; The Wellcome Trust, London, UK.
  • Stewart-Ibarra AM; Inter-American Institute for Global Change Research, Montevideo, Uruguay.
Lancet Planet Health ; 7(6): e527-e536, 2023 06.
Article em En | MEDLINE | ID: mdl-37286249
Climate-sensitive infectious disease modelling is crucial for public health planning and is underpinned by a complex network of software tools. We identified only 37 tools that incorporated both climate inputs and epidemiological information to produce an output of disease risk in one package, were transparently described and validated, were named (for future searching and versioning), and were accessible (ie, the code was published during the past 10 years or was available on a repository, web platform, or other user interface). We noted disproportionate representation of developers based at North American and European institutions. Most tools (n=30 [81%]) focused on vector-borne diseases, and more than half (n=16 [53%]) of these tools focused on malaria. Few tools (n=4 [11%]) focused on food-borne, respiratory, or water-borne diseases. The under-representation of tools for estimating outbreaks of directly transmitted diseases represents a major knowledge gap. Just over half (n=20 [54%]) of the tools assessed were described as operationalised, with many freely available online.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doenças Transmissíveis / Malária Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: Lancet Planet Health Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doenças Transmissíveis / Malária Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: Lancet Planet Health Ano de publicação: 2023 Tipo de documento: Article