Online Program

328782
Examining the impacts of environmental context on the efficacy of a malaria vector control intervention


Tuesday, November 3, 2015 : 4:45 p.m. - 5:00 p.m.

Marie Lynn Miranda, PhD, School of Natural Resources & Environment, University of Michigan, Ann Arbor, MI
Joshua Tootoo, MS, GISP, Children's Environmental Health Initiative, University of Michigan, Ann Arbor, MI
Leonard Mboera, BVM, MSc., PhD, DIC, National Institute for Medical Research Tanzania, Dar-es-Salaam, Tanzania
Susan Rumisha, BSc MSc PhD, Directorate of Information Technology and Communication, National Institute for Medical Research Tanzania, Dar-es-Salaam, Tanzania
Ruiyang Li, MS, Children's Environmental Health Initiative, University of Michigan, Ann Arbor, MI
Julie Strominger, MS, School of Natural Resources and the Environment, University of Michigan, Ann Arbor, MI
Adriane Lesser, MS, Duke Global Health Institute, Duke University, Durham, NC
Randall Kramer, PhD, Nicholas School of the Environment and Duke Global Health Institute, Duke University, Durham, NC
objectives: We examine how the village level impact of microbial larviciding on vector populations is influenced by local-scale environmental context as defined by agricultural practices and rainfall in the Mvomero District of Tanzania.

methods: In the context of a cluster-randomized 2x2 factorial design evaluating both vector control (microbial larviciding) and disease management (early detection and treatment) interventions, we evaluate a larviciding intervention on village-level mosquito densities, estimated from routine entomological surveillance.

We consider spatially referenced data for agricultural practices, reported through surveys, and average rainfall in a regression framework to understand how each influences the impact of the larviciding intervention.  We control for the effects of 1) agricultural practices including presence of livestock and rice cultivation and 2) monthly rainfall on village-level malaria mosquito density before and after the intervention.

results: Twelve of 24 randomly selected villages received larviciding treatment. Entomological sampling was performed in intervals spaced before and after larviciding. Mosquito collection occurred in each of 3 homes per village on 3 consecutive days within each round. Initial analyses suggest that larviciding was linked to a reduction in mosquito density, after adjusting for the previous month’s rainfall and livestock and agricultural practices.  Further work will explore this relationship in more detail.

conclusions: Our analysis demonstrates the short-term effectiveness of the larviciding intervention. Differential reductions in malaria vector populations are likely driven by local scale environmental factors, such as rainfall, in combination with agricultural and livestock practices.

Learning Areas:

Administer health education strategies, interventions and programs
Environmental health sciences
Planning of health education strategies, interventions, and programs

Learning Objectives:
Describe a spatially referenced model designed to account for village-level environmental variations in the measurement of intervention outcomes. Evaluate a spatially and temporally fine-scaled satellite-derived dataset for estimating monthly village level rainfall. Assess the impact of rainfall and agricultural practices data on determining the effects of a malaria vector control intervention on mosquito densities.

Keyword(s): International Health, Geographic Information Systems (GIS)

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I serve as the Director of Training and lead GIS analyst for CEHI. I lead a series of projects seeking to understand the social and environmental factors that contribute to health outcomes. My research interests include: the application of administrative datasets into analyses examining environmentally driven health disparities; informal project based approaches to education and training for public health/environmental professionals; and the communication of complex data analyses through visualization.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.