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Spatial epidemiological approaches to inform leptospirosis surveillance and control: A systematic review and critical appraisal of methods.
Dhewantara, Pandji W; Lau, Colleen L; Allan, Kathryn J; Hu, Wenbiao; Zhang, Wenyi; Mamun, Abdullah A; Soares Magalhães, Ricardo J.
Afiliação
  • Dhewantara PW; UQ Spatial Epidemiology Laboratory, School of Veterinary Science, The University of Queensland, Gatton, Queensland, Australia.
  • Lau CL; Pangandaran Unit for Health Research and Development, National Health Research and Development, Ministry of Health of Indonesia, Pangandaran, West Java, Indonesia.
  • Allan KJ; Research School of Population Health, Australian National University, Canberra, Australian Capital Territory, Australia.
  • Hu W; Child Health Research Centre, The University of Queensland, Brisbane, Queensland, Australia.
  • Zhang W; Institute of Biodiversity, Animal Health and Comparative Medicine, College of Medical Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.
  • Mamun AA; School of Public Health and Social Work, Queensland University of Technology, Brisbane, Queensland, Australia.
  • Soares Magalhães RJ; Center for Disease Surveillance and Research, Institute of Disease Control and Prevention of PLA, Beijing, China.
Zoonoses Public Health ; 66(2): 185-206, 2019 03.
Article em En | MEDLINE | ID: mdl-30593736
Leptospirosis is a global zoonotic disease that the transmission is driven by complex geographical and temporal variation in demographics, animal hosts and socioecological factors. This results in complex challenges for the identification of high-risk areas. Spatial and temporal epidemiological tools could be used to support leptospirosis control programs, but the adequacy of its application has not been evaluated. We searched literature in six databases including PubMed, Web of Science, EMBASE, Scopus, SciELO and Zoological Record to systematically review and critically assess the use of spatial and temporal analytical tools for leptospirosis and to provide general framework for its application in future studies. We reviewed 115 articles published between 1930 and October 2018 from 41 different countries. Of these, 65 (56.52%) articles were on human leptospirosis, 39 (33.91%) on animal leptospirosis and 11 (9.5%) used data from both human and animal leptospirosis. Spatial analytical (n = 106) tools were used to describe the distribution of incidence/prevalence at various geographical scales (96.5%) and to explored spatial patterns to detect clustering and hot spots (33%). A total of 51 studies modelled the relationships of various variables on the risk of human (n = 31), animal (n = 17) and both human and animal infection (n = 3). Among those modelling studies, few studies had generated spatially structured models and predictive maps of human (n = 2/31) and animal leptospirosis (n = 1/17). In addition, nine studies applied time-series analytical tools to predict leptospirosis incidence. Spatial and temporal analytical tools have been greatly utilized to improve our understanding on leptospirosis epidemiology. Yet the quality of the epidemiological data, the selection of covariates and spatial analytical techniques should be carefully considered in future studies to improve usefulness of evidence as tools to support leptospirosis control. A general framework for the application of spatial analytical tools for leptospirosis was proposed.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Zoonoses / Modelos Estatísticos / Análise Espaço-Temporal / Leptospirose Tipo de estudo: Etiology_studies / Incidence_studies / Prognostic_studies / Risk_factors_studies / Screening_studies / Systematic_reviews Limite: Animals / Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Zoonoses / Modelos Estatísticos / Análise Espaço-Temporal / Leptospirose Tipo de estudo: Etiology_studies / Incidence_studies / Prognostic_studies / Risk_factors_studies / Screening_studies / Systematic_reviews Limite: Animals / Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article