02594nas a2200349   4500000000100000008004100001653000900042653002200051653004300073653001800116653001400134653001300148653001800161100002600179700001100205700001400216700001200230700002300242700002400265700002300289700002200312700002100334700002100355700002200376700002100398700001400419700001500433245017900448856007100627520153300698022001302231       2017                            d10aNTDs10aZika virus (ZIKV)10aGeographical information systems (GIS)10aPublic health10aTravelers10aColombia10aLatin America1 aRodríguez-Morales AJ1 aRuiz P1 aTabares J1 aOssa CA1 aYepes-Echeverry MC1 aRamirez-Jaramillo V1 aGalindo-Marquez ML1 aGarcía-Loaiza CJ1 aSabogal-Roman JA1 aParra-Valencia E1 aLagos-Grisales GJ1 aLozada-Riascos C1 aPijper CA1 aGrobusch M00aMapping the ecoepidemiology of Zika virus infection in urban and rural areas of Pereira, Risaralda, Colombia, 2015–2016: Implications for public health and travel medicine.  uhttp://www.sciencedirect.com/science/article/pii/S14778939173007533 a<h4><strong>Objective </strong>Geographical information systems (GIS) have been demonstrated earlier to be of great use to inform public health action against vector-borne infectious diseases.<br />
<strong>Methods </strong>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.<br />
<strong>Results </strong>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 (r<sup>2</sup>&nbsp;&gt;&nbsp;0.25; p&nbsp;&lt;&nbsp;0.05).<br />
<strong>Conclusions </strong>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.</h4>
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