Ross River Virus and the Necessity of Multiscale, Eco-epidemiological Analyses

被引:14
|
作者
Flies, Emily J. [1 ,3 ]
Weinstein, Philip [2 ]
Anderson, Sharolyn J. [5 ]
Koolhof, Iain [4 ]
Foufopoulos, Johannes [6 ]
Williams, Craig R. [1 ]
机构
[1] Univ South Australia, Sch Pharm & Med Sci, Mawson Lakes, Australia
[2] Adelaide Univ, Sch Biol Sci, Adelaide, SA, Australia
[3] Univ Tasmania, Sch Biol Sci, Private Bag 55, Hobart, Tas 7001, Australia
[4] Univ Tasmania, Menzies Inst Med Res, Hobart, Tas, Australia
[5] Univ South Australia, Sch Nat & Built Environm, Mawson Lakes, Australia
[6] Univ Michigan, Sch Sustainabil & Environm, Ann Arbor, MI 48109 USA
来源
JOURNAL OF INFECTIOUS DISEASES | 2018年 / 217卷 / 05期
关键词
Multiscale; epidemiology; spatial; arbovirus; ecology; MOSQUITO-BORNE DISEASE; SOUTH-AUSTRALIA; ARBOVIRUS SURVEILLANCE; COMMUNITY COMPOSITION; CLIMATE VARIABILITY; TEMPORAL ANALYSIS; TRANSMISSION; QUEENSLAND; RISK; CULICIDAE;
D O I
10.1093/infdis/jix615
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Background. Zoonotic vector-borne disease prevalence is affected by vector, human, and reservoir host factors, which are influenced by habitat and climate; these 5 components interact on microhabitat-to-landscape scales but are often analyzed at a single spatial scale. Methods. We present an information theoretic, multiscale, multiple regression analysis of the ecological drivers of Ross River virus. We analyze the spatial pattern of 20 years of Ross River virus infections from South Australia (1992-2012; n = 5261), using variables across these 5 components of disease ecology at 3 spatial scales. Results. We found that covariate importance depended on the spatial scale of the analysis; some biotic variables were more important at fine scales and some abiotic variables were more important at coarser spatial scales. The urban score of an area was most predictive of infections, and mosquito variables did not improve the explanatory power of these models. Conclusions. Through this multiscale analysis, we identified novel drivers of the spatial distribution of disease and recommend public health interventions. Our results underline that single-scale analyses may paint an incomplete picture of disease drivers, potentially creating a major flaw in epidemiological analyses. Multiscale, ecological analyses are needed to better understand infectious disease transmission.
引用
收藏
页码:807 / 815
页数:9
相关论文
共 50 条
  • [1] An Integrative Eco-Epidemiological Analysis of West Nile Virus Transmission
    Tran, Annelise
    L'Ambert, Gregory
    Balanca, Gilles
    Pradier, Sophie
    Grosbois, Vladimir
    Balenghien, Thomas
    Baldet, Thierry
    Lecollinet, Sylvie
    Leblond, Agnes
    Gaidet-Drapier, Nicolas
    [J]. ECOHEALTH, 2017, 14 (03) : 474 - 489
  • [2] An Integrative Eco-Epidemiological Analysis of West Nile Virus Transmission
    Annelise Tran
    Grégory L’Ambert
    Gilles Balança
    Sophie Pradier
    Vladimir Grosbois
    Thomas Balenghien
    Thierry Baldet
    Sylvie Lecollinet
    Agnès Leblond
    Nicolas Gaidet-Drapier
    [J]. EcoHealth, 2017, 14 : 474 - 489
  • [3] THE DYNAMICS OF AN ECO-EPIDEMIOLOGICAL SYSTEM
    Bercia, Cristina
    [J]. UNIVERSITY POLITEHNICA OF BUCHAREST SCIENTIFIC BULLETIN-SERIES A-APPLIED MATHEMATICS AND PHYSICS, 2010, 72 (04): : 53 - 60
  • [4] The dynamics of an eco-epidemiological system
    Bercia, Cristina
    [J]. UPB Scientific Bulletin, Series A: Applied Mathematics and Physics, 2010, 72 (04): : 53 - 60
  • [5] Eco-epidemiological types and stratification
    [J]. MALARIA VECTOR CONTROL AND PERSONAL PROTECTION: REPORT OF A WHO STUDY GROUP, 2006, 936 : 11 - 12
  • [6] Complex Dynamics in an Eco-epidemiological Model
    Andrew M. Bate
    Frank M. Hilker
    [J]. Bulletin of Mathematical Biology, 2013, 75 : 2059 - 2078
  • [7] On the dynamical behavior of an eco-epidemiological model
    Ibrahim, Hiba Abdullah
    [J]. INTERNATIONAL JOURNAL OF NONLINEAR ANALYSIS AND APPLICATIONS, 2021, 12 (02): : 1749 - 1767
  • [8] An eco-epidemiological model with the impact of fear
    Sarkar, Kankan
    Khajanchi, Subhas
    [J]. CHAOS, 2022, 32 (08)
  • [9] Dynamical bifurcation of an eco-epidemiological system
    Bercia, C.
    [J]. BSG PROCEEDINGS 19, 2012, 19 : 18 - 26
  • [10] RANDOM PERTURBATIONS OF AN ECO-EPIDEMIOLOGICAL MODEL
    de Jesus, Lopo F.
    Silva, Cesar M.
    Vilarinho, Helder
    [J]. DISCRETE AND CONTINUOUS DYNAMICAL SYSTEMS-SERIES B, 2022, 27 (01): : 257 - 275