Trends in mosquito species distribution modeling: insights for vector surveillance and disease control

Posted on October 10, 2023

LIPPI, MUNDIS, SIPPY, FLENNIKEN, CHAUDHARY, HECHT, RYAN – Trends in mosquito species distribution modeling: insights for vector surveillance and disease control Catherine Lippi, Stephanie Mundis, Rachel Sippy, Matthew Flenniken, Anusha Chaudhary, Gavriella Hecht, Colin Carlson, Sadie Ryan Article first published online: 28 August 2023 DOI: https://doi.org/10.1186/s13071-023-05912-z ABSTRACT: Species distribution modeling (SDM) has become an increasingly common […]

Postdoc Appreciation Week

Posted on September 23, 2020

For Postdoc Appreciation Week, the department would like to thank Dr. Chen, Dr. Khatami, Dr. Sippy, and Dr. White for all of their hard work and scholarship! Find out more about how UF is celebrating National Postdoc Appreciation Week here!

Summarizing the Research and Knowledge Gaps for Mosquito-borne Arboviruses in Ecuador

Posted on August 28, 2020

GAINESVILLE, FL – Researchers and clinicians in Ecuador face a challenging environment: this biodiverse country is home to many disease hosts and vectors. Particularly, the mosquitoes in Ecuador carry and transmit arboviruses (arthropod-borne viruses). This group includes diseases like dengue, chikungunya, Mayaro virus, yellow fever, and Zika, among others. All are spread by overlapping mosquito species. […]

Machine Learning Predictions of Dengue Patients Outcomes Yield Promising Results

Posted on March 5, 2020

GAINESVILLE, FL – Helping patients with dengue can be challenging – especially in countries with multiple diseases spread by mosquitoes. Dengue, chikungunya, and Zika are viruses spread by the same type of mosquito; all three viruses are present in Ecuador and many other countries in Latin America and the Caribbean. Patients infected with one of […]

Severity Index for Suspected Arbovirus (SISA): Machine learning for accurate prediction of hospitalization in subjects suspected of arboviral infection

Posted on February 14, 2020

SIPPY, RYAN – Severity Index for Suspected Arbovirus (SISA): Machine learning for accurate prediction of hospitalization in subjects suspected of arboviral infection Rachel Sippy, Daniel F. Farrell, Daniel A. Lichtenstein, Ryan Nightingale, Megan A. Harris, Joseph Toth, Paris Hantztidiamantis, Nicholas Usher, Cinthya Cueva Aponte, Julio Barzallo Aguilar, Anthony Puthumana, Christina D. Lupone, Timothy Endy, Sadie […]

MedGeo researchers present at EPI Research Day

Posted on February 13, 2020

MedGeo researchers from the Quantitative Disease Ecology & Conservation Lab (QDEC Lab) and Spatial Epidemiology & Ecology Research Laboratory (SEER Lab) made a strong showing at Emerging Pathogens Institute‘s EPI Research Day 2020!

Insecticide Resistance Threatens the Control of Mosquito-Borne Disease in Ecuador

Posted on June 24, 2019

GAINESVILLE – In the battle against vector borne disease, mosquito control using insecticides is an essential tool. But what happens when that tool starts to fail, and how do you know it? Insecticides are regularly used by public health agencies to reduce populations of blood-sucking mosquitoes. Effective control programs are important to public health because, […]

Seasonal and geographic variation in insecticide resistance in Aedes aegypti in southern Ecuador

Posted on June 10, 2019

LIPPI, MUNDIS, RYAN, SIPPY – Seasonal and geographic variation in insecticide resistance in Aedes aegypti in southern Ecuador Sadie J. Ryan, Stephanie J. Mundis, Alex Aguirre, Catherine A. Lippi, Efraín Beltrán, Froilán Heras, Valeria Sanchez, Mercy J. Borbor-Cordova, Rachel Sippy, Anna M. Stewart-Ibarra , Marco Neira Article first published online: 10 JUN 2019 PLoS Neglected […]

Dr. Rachel Sippy

Dr. Rachel Sippy Postdoctoral Researcher rsippy@ufl.edu @GermCurves https://sippy.pophealth.wisc.edu/ Google Scholar (319) 551-1000 Curriculum Vita Focus Areas: GeoSpatial Analysis & Techniques Medical Geography in Global Health (MGGH) Research Statement: I am interested in epidemiology and disease seasonality in a causal framework as well as predictions of disease outcomes or epidemics. I primarily focus on vectorborne illness […]

Geography

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