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Mapping the ecoepidemiology of Zika virus infection in urban and rural areas of Pereira, Risaralda, Colombia, 2015–2016: Implications for public health and travel medicine

  • Universidad Tecnológica de Pereira
    ,
  • Colombian Collaborative Network on Zika and other Arboviruses (RECOLZIKA)
    ,
  • Asociación Panamericana de Infectología (API)
    ,
  • Secretary of Health and Social Security of Pereira
    ,
  • Universidad Católica de la Santísima Concepción
    ,
  • University of Amsterdam
Research Output:
Contribution to journal
Article
Peer-review

Publication Information

Output type

Research Output:
Contribution to journal
Article
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 57-66 (10 pages)

Journal (Volume, Issue Number)

Travel Medicine and Infectious Disease (Volume 18)

Publication milestones

  • Published - 07/2017

Publication status

Published - 07/2017

ISSN

1477-8939

Publication IDs

  • Scopus: 85029601726
  • PubMed: 28487212

Abstract

Objective Geographical information systems (GIS) have been demonstrated earlier to be of great use to inform public health action against vector-borne infectious diseases. Methods Using surveillance data on the ongoing ZIKV outbreak from Pereira, Colombia (2015–2016), we estimated incidence rates (cases/100,000 population), and developed maps correlating with the ecoepidemiology of the area. Results Up to October 8, 2016, 439 cases of ZIKV were reported in Pereira (93 cases/100,000 pop.), with highest rates in the South-West area. At the corregiments (sub-municipalities) of Pereira, Caimalito presented the highest rate. An urban area, Cuba, has 169 cases/100,000 pop., with a low economical level and the highest Aedic index (9.1%). Entomological indexes were associated with ZIKV incidence at simple and multiple non-linear regressions (r2 > 0.25; p < 0.05). Conclusions Combining entomological, environmental, human population density, travel patterns and case data of vector-borne infections, such as ZIKV, leads to a valuable tool that can be used to pinpoint hotspots also for infections such as dengue, chikungunya and malaria. Such a tool is key to planning mosquito control and the prevention of mosquito-borne diseases in local populations. Such data also enable microepidemiology and the prediction of risk for travelers who visit specific areas in a destination country.

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Sustainable Development Goals

  • SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well