Skip to main navigation Skip to search Skip to main content

Modeling and Predicting Counts and Environmental Correlates of Mosquito Distributions in Haiti Using Surveillance Data from the Ouest Department

  • Ian A. Pshea-Smith
  • , Bernard Okech
  • , John So
  • , Jacques Boncy
  • , Ian Sutherland
  • , Theron Hamilton
  • , James Dunford
  • , Jason Blanton
  • , Alexandre Existe
  • , Francisca Javiera Rudolph
  • , Graham A. Matulis
  • , Jose Miguel Ponciano
  • , Jeffrey W. Koehler
  • , Jason K. Blackburn
  • , Michael E. von Fricken*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Vector-borne diseases present significant public health challenges in Haiti, particularly dengue fever and lymphatic filariasis (LF), with Haiti hosting 90% of LF at-risk individuals in the Americas. Understanding mosquito vector distribution is crucial, especially as ongoing sociopolitical instability in Haiti limits vector surveillance and control measures. This study analyzed the spatial distribution and abundance patterns of key mosquito vectors using ecological modeling approaches. Mosquito surveillance was conducted at 19 sites from the communes of Carrefour, Genier, and Léogâne in the Ouest Department of Haiti from August 2018 to September 2019 using BG Sentinel, CDC Gravid, and CDC Light traps. Environmental covariates including temperature, precipitation, wind speed, elevation, and land-cover data were incorporated into boosted regression trees to predict mosquito presence and abundance. Of 22,504 mosquitoes captured, Culex quinquefasciatus dominated (53.44%), followed by Cx. nigripalpus (19.99%), Aedes aegypti (16.87%), Ae. albopictus (6.37%), Ae. mediovittatus (1.65%), and Psorophora columbiae (1.68%). Precipitation and temperature emerged as key correlates of mosquito presence and abundance. Predictive mapping demonstrated spatial heterogeneities in presence and abundance across each month for each species. These findings serve as a foundation for evidence-based vector control, and future research should incorporate additional environmental variables and expand sampling locations to strengthen predictive capabilities.

Original languageEnglish
Pages (from-to)50-58
Number of pages9
JournalAmerican Journal of Tropical Medicine and Hygiene
Volume115
Issue number1
DOIs
StatePublished - Jul 2026

Fingerprint

Dive into the research topics of 'Modeling and Predicting Counts and Environmental Correlates of Mosquito Distributions in Haiti Using Surveillance Data from the Ouest Department'. Together they form a unique fingerprint.

Cite this