# Project-002

> **NIH NIH U19** · UNIVERSITY OF SOUTH FLORIDA · 2023 · $371,361

## Abstract

PROJECT 2 SUMMARY
Malaria epidemiology in the Greater Mekong Subregion is characterized by high spatial and temporal 
heterogeneity with the presence of diverse vector species, which have different spatial distribution, seasonal 
dynamics, ecological niche requirement, host feeding preference and vector competence. Vector control is an 
integrated component of malaria control. The changes in mosquito biting behavior and emergence of 
resistance to pyrethroid insecticides make the conventional pyrethroid insecticide-treated nets and pyrethroid-based indoor residual spray less effective in reducing malaria transmission. Environmental changes, especially 
due to deforestation, also have led to dramatic changes in the bionomics and vectorial status of different 
Anopheles species. Therefore, updated knowledge on such changes and development of new resistance 
monitoring tools are critically needed. In order to address these pressing challenges in vector control, we 
selected international border regions in China, Thailand and Myanmar to 1) determine how environmental 
changes affect the mosquito community structures, 2) study the mosquito phenotypic plasticity and 
characterize landscape genetics of a major Anopheles vector species, 3) identify whether changes of mosquito 
biting behaviors are genetically determined using genomics technology, and 4) determine the extent, 
distribution and mechanisms of insecticide resistance in a major malaria vector. The overarching objectives of 
this project are to understand the vectorial system in diverse ecological and epidemiological settings and to 
develop the needed knowledge base for effective vector control in the GMS.

## Key facts

- **NIH application ID:** 10821530
- **Project number:** 5U19AI089672-15
- **Recipient organization:** UNIVERSITY OF SOUTH FLORIDA
- **Principal Investigator:** LIWANG CUI
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $371,361
- **Award type:** 5
- **Project period:** 2010-07-01 → 2024-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10821530

## Citation

> US National Institutes of Health, RePORTER application 10821530, Project-002 (5U19AI089672-15). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10821530. Licensed CC0.

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