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Environmental Justice & Public Health: Climate, Land, & (Health) Outcome of Dengue Fever (CLOUD)

understand the spatiotemporal changes and the underlying forcing mechanisms of dengue fever in Peru

Project Overview

Dengue fever -- an infectious disease caused by dengue virus, is one of the most widely spread mosquito-borne viral diseases. Climate factors, such as temperature, humidity, precipitation, wind speed and sunshine hours, are important variables for modeling its outbreaks, magnitude and spread.

Socioeconomic and environmental factors affect the habitat of the Aedes species mosquitoes (Ae. aegypti or Ae. Albopictus), such as the urbanization, vegetation, water body, poverty, and accessibility are found to be significant factors for incidences of dengue fever. In addition, communities’ risk of dengue is influenced by the knowledge, attitude, and practice of the population, such as routine vector control activities.

Our overall objective is to to use remote sensing-based data and work with local communities to understand the spatiotemporal changes and the underlying forcing mechanisms of dengue fever in Peru, its health and environmental justice impacts, and possible options for policy interventions considering the changing climate, lands, and society

Questions to be answered

  1. (1) What are the quantitative contributions of land cover change, specific management practices, and climate changes (means and extremes) to the social and physical C fluxes of managed ecosystems and landscapes?
  2. (2) What are the spatial and temporal changes of their contributions in managed agricultural-forest landscapes?
  3. (3) How will future land use changes (including alternative management practices) impact C sequestration in an upper, mid-latitude managed ecosystem?

Acknowledgements

Funded by Interdisciplinary Research in Earth Science (IDS)
Download project summary

Recent Activity

April 2019:

Gabriela Shirkey (PhD student) is awarded the NSF GRFP starting fall 2019

  • Changes in land cover type across the Kalamazoo Watershed (Landsat 30m resolution data) demonstrate the increasing rates of urbanization and from 1996 to 2011. Credit: Rong Zhang
  • May-July 2017: Five flux towers can be found across the Kalamazoo Watershed representing urban, marsh, forest, and agricultural land.
  • March 20, 2017: Annual Legislative Breakfast hosted by the Kalamazoo Environmental Council.

    • Conceptual Framework and Hypothesis

    Conceptual framework of CLOUD: drivers, vulnerability, impact, and adaptation strategies. We include natural and human drivers on the vulnerability and spatiotemporal changes of dengue fever through testing 4 hypotheses in 3 thrusts. Integrated modeling will focus on the mechanisms and forecasts of future outbreaks in the contexts of environmental justice through development of adaptive and mitigative action plans. Downscaled future climate, LCLUC, human demography, and socioeconomic conditions will be the major scenarios for our model endeavors.

    flow chart titled: Future Climate: RCP Scenarios, CMIP5 or 6

    Figure 1. (above)

    an image depicting the land cover types of the Kalamazoo, MI watershed

    Figure 2.

    Research Tasks

    Task 1:
    Task 2:
    Task 3:

    Open Data Resources

    In alliance with NASA, our researchers openly share their data with the broader community. The latest information and resources from our project can be found here for exploration and education.

    Data use policy

    Use of this data is for non-profit, personal, or educational use only. To publish this data or apply it in other for-profit endeavours, please contact Dr. Jiquan Chen for information. For help interpreting the data, contact the author listed. Information provided here does not conflict with our committment to confidentiality or expose personal information from survey participants.

    Activities

    Dec 1-7, 2024: Our research team conducted semistructure interviews, meetings with local collaborators, as well as site visits in Lima, Poura, and Iqutos ( Peilei Fan, Jiquan Chen, Ruben Briceno, Qing Xia, Bill Cunningham, and Sabrina Vieyra)

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    Presentations

    Team Members

    		      
    Briceno, Ruben COI, MSU jqchen@msu.edu
    Chen, Jiquan COI (MSU PI)
    		 jqchen@msu.edu
    Fan, Peilei PI, TU Peilei.Fan@tufts.edu
    Irfan, Furqan COI, MSU irfanfur@msu.edu
         
         
         
         
         
        
        
    Xia, Qing Collaborator, MSU xiaqing@msu.edu