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Antar Jutla
Antar Jutla
University of Florida | Website

Applied Research Topic

Predictive Assessment of Clinically Active Biothreats in Coastal and Ocean Waters Using PACE Data
Co-PI: Rita Colwell, University of Maryland

Potential Applications Predictive risk assessment for coastal HABs / pathogens / biothreats


Biothreats are defined as biological agents that pose a significant threat to the well-being of human communities and include harmful algal blooms (HABs) and water-borne infectious pathogens. Pathogens in the global oceans are on constant move all of the time. Given favorable environmental conditions, these pathogens may develop habitat in their preferred niches and then can interact with vulnerable population that may result in the outbreak of water-borne diseases (and may act as biothreats). A changing climate is likely to have wide-ranging effects on various pathogens and thus on human health. Most of these effects are likely to occur where hydrologic, climatic, and ecological extremes converge with population vulnerability, particularly in the developing world and pose a severe threat to national security for developed countries. Several studies have attempted to link prevalence of diseases with climate variability and change. However, for most waterborne pathogens, in situ surveillance is spotty, diagnoses are not uniform, and understanding of the effects of climate related drivers remains limited. This is where satellites like PACE can fill in the gaps by providing alternate venues to quantify risk of emergence of pathogens and impacts of changing climate on coastal communities.

Our goal is to understand and distinguish major biothreats along global coastal and oceanic waters with emphasis on Chesapeake Bay and coastal Florida. We will obtain pathogen data and then use it to understand utility of PACE datasets in developing prediction risks of emergence and presence of major biothreats (Vibrio spp). We are currently developing an innovative tool called Biothreat Assessment Tool (BAT), a satellite-based predictive risk assessment for threats at various spatial and temporal scales, and PACE datasets can really enhance the scope and utility of the BAT in future. Specific objectives are to:
  1. Develop early protocols to use PACE datasets to understand and characterize functional form association with biothreats (Vibrio spp) in the coastal and oceanic waters, and
  2. Enhance our existing prediction models (for cholera) by integrating speciation level information of plankton and plankton health into algorithms.


Our work has been used by several United Nations (UN) agencies to make real time decisions of when and where to initiate relief and mitigation activities. For example, our cholera work is currently used by UNCEF for making real time decisions on where and when to provide safe water and sanitation access to population. We expect that our work, through PACE will only enhance such activities and will support public health, policy analysis and decision-making domains.


The hyperspectral resolution of PACE OCI will enable us to take an unprecedented dive to study details on speciation of plankton which may then be related to a particular water-borne pathogen. This will further enhance out understanding on global coastal and ocean bioecology. Further, the spatial resolution of PACE is optimal for developing protocols for determine risk of infections to coastal human communities. This will then help us to quantify aspects of resilience and sustainability of natural and built infrastructure under current and changing climate scenarios.

End User(s)

United Nations Office for Coordinator of Humanitarian Affairs (UNOCHA)
World Health Organization (WHO)
United Nations International Children's Emergency Fund (UNCEF)

SAT Partner(s)

Michael Twardowski


R.R. Colwell (1996). Global climate and infectious disease: the cholera paradigm. Science, vol. 274, no. 5295, pp. 2025–2031.

A. Haines, R.S. Kovats, D. Campbell-Lendrum, and C. Corvalan (2006) Climate change and human health: Impacts, vulnerability and public health. Public Health, vol. 120, no. 7, pp. 585–596, DOI: 10.1016/j.puhe.2006.01.002.

A.J. McMichael. (2008) Global Environmental Change and Human Health. Ecosyst. Health, vol. 3, no. 4, pp. 200–210, DOI: 10.1111/j.1526-0992.1997.00053.pp.x.

A. Jutla, A.S. Akanda, A. Huq, A.S.G. Faruque, R. Colwell, and S. Islam. (2013). A water marker monitored by satellites to predict seasonal endemic cholera. Remote Sens. Lett., vol. 4, no. 8, pp. 822–831, DOI: 10.1080/2150704X.2013.802097.

A.S. Akanda (2011) Warming oceans, phytoplankton, and river discharge: implications for cholera outbreaks,” Am. J. Trop. Med. Hyg., vol. 85, no. 2, pp. 303–308, DOI:10.4269/ajtmh.2011.11-0181.

Population distribution and water-borned disease outbreak
Population distribution and water-borned disease outbreak. Rectangles represent regions with reported disease epidemics.