Using Bayesian state-space models to understand the population dynamics of the dominant malaria vector, Anopheles funestus in rural Tanzania

被引：0
|
作者：
Halfan S. Ngowo
Fredros O. Okumu
Emmanuel E. Hape
Issa H. Mshani
Heather M. Ferguson
Jason Matthiopoulos
机构：
[1] Ifakara Health Institute,Department of Environmental Health & Ecological Sciences
[2] University of Glasgow,Institute of Biodiversity, Animal Health and Comparative Medicine
[3] University of the Witwatersrand,School of Public Health
[4] Nelson Mandela African Institution of Science & Technology,School of Life Science and Bioengineering
来源：
Malaria Journal | / 21卷
关键词：
Anopheles ; State space model; Population dynamic; Seasonality; Abundance; Density dependence;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
相关论文
共 41 条
  • [31] Detecting the effects of management regime shifts in dynamic environments using multi-population state-space models
    Falcy, Matthew R.
    Suring, Erik
    BIOLOGICAL CONSERVATION, 2018, 221 : 34 - 43
  • [32] Better inferences from population-dynamics experiments using Monte Carlo state-space likelihood methods
    De Valpine, P
    ECOLOGY, 2003, 84 (11) : 3064 - 3077
  • [33] DREISS: Using State-Space Models to Infer the Dynamics of Gene Expression Driven by External and Internal Regulatory Networks
    Wang, Daifeng
    He, Fei
    Maslov, Sergei
    Gerstein, Mark
    PLOS COMPUTATIONAL BIOLOGY, 2016, 12 (10)
  • [34] A Bayesian state-space model using age-at-harvest data for estimating the population of black bears (Ursus americanus) in Wisconsin
    Maximilian L. Allen
    Andrew S. Norton
    Glenn Stauffer
    Nathan M. Roberts
    Yanshi Luo
    Qing Li
    David MacFarland
    Timothy R. Van Deelen
    Scientific Reports, 8
  • [35] A Bayesian state-space model using age-at-harvest data for estimating the population of black bears (Ursus americanus) in Wisconsin
    Allen, Maximilian L.
    Norton, Andrew S.
    Stauffer, Glenn
    Roberts, Nathan M.
    Luo, Yanshi
    Li, Qing
    MacFarland, David
    Van Deelen, Timothy R.
    SCIENTIFIC REPORTS, 2018, 8
  • [36] Assessment of the residential Finnish wolf population combines DNA captures, citizen observations and mortality data using a Bayesian state-space model
    Samu Mäntyniemi
    Inari Helle
    Ilpo Kojola
    European Journal of Wildlife Research, 2022, 68
  • [37] Assessment of the residential Finnish wolf population combines DNA captures, citizen observations and mortality data using a Bayesian state-space model
    Mantyniemi, Samu
    Helle, Inari
    Kojola, Ilpo
    EUROPEAN JOURNAL OF WILDLIFE RESEARCH, 2022, 68 (06)
  • [38] Investigating agreement between different data sources using Bayesian state-space models: an application to estimating NE Atlantic mackerel catch and stock abundance
    Simmonds, E. John
    Portilla, Enrique
    Skagen, Dankert
    Beare, Doug
    Reid, Dave G.
    ICES JOURNAL OF MARINE SCIENCE, 2010, 67 (06) : 1138 - 1153
  • [39] Evaluation of the effects of stock enhancement on population dynamics using a state-space production model: A case study of Japanese flounder in the Seto Inland Sea
    Lin, Zhen
    Kitakado, Toshihide
    Suzuki, Naoki
    Ito, Shin-ichi
    FISHERIES RESEARCH, 2022, 251
  • [40] Evaluating the Accuracy and Precision of Multiple Abundance Estimators Using State-Space Models: A Case Study for a Threatened Population of Chinook Salmon in Johnson Creek, Idaho
    Chasco, Brandon E.
    Ward, Eric J.
    Hesse, Jay A.
    Rabe, Craig
    Kinzer, Ryan
    Vogel, Jason L.
    Orme, Rick
    NORTH AMERICAN JOURNAL OF FISHERIES MANAGEMENT, 2014, 34 (05) : 945 - 954
12345