My Internship Experience
Internship
My internship took place during the summer semester from mid July to September 2020 which was completed remotely due to the COVID-19 pandemic. Despite the unforeseen situation, I succeeded to meet the goal and challenges of delivering the expected output and learnt a lot under the guidance of Dr. Marie-Fanny Racault, Earth Observation Scientist at PML. Having worked as a marine scientist for the past years, I chose to do an internship in the field of ocean remote sensing as I am eager to learn more and enhance my skills in using geospatial information in solving health applications. I was working as an Earth Observation intern at the Plymouth Marine Lab (PML) as part of the Pathways of Dispersal for Cholera And Solutions Tools (PODCAST) project. I am grateful to my supervisor Dr. Marie-Fanny Racault and her team for their guidance that enhance my skills in using python programming to predict cholera outbreaks from climate data taken from Earth orbiting satellites.
Organization Profile
Plymouth Marine Laboratory is a world-renowned marine research organization located in the United Kingdom. For over 40 years, the Plymouth Marine Laboratory have provided evidence-based environmental solutions to societal challenges by applying cutting-edge, interdisciplinary research that benefits society and promotes stewardship of marine ecosystems. PML researchers has contributed to science by delivering highly cited scientific papers, to providing scientific evidence for policy and training the next generation of marine scientists. Moreover, PML have a commercial trading subsidiary, PML Applications Ltd, which delivers services, products and solutions related to the marine environment in key sectors such as ballast water management and biofouling. Further information provided on the PML website.
Host Department
I was working in the department of Earth Observation Science and Application (EOSA) under the Pathways of Dispersal for Cholera And Solutions Tools (PODCAST) project. The project comprises of a multidisciplinary expert team of scientists from UK, India and Japan. The PODCAST project is funded by the Natural Environment Research Council (NERC) in partnership with Japan Science and Technology Agency (JST) and India’s Department of Biotechnology (DBT), with the goal to investigate transmission pathways and to produce risk maps for cholera outbreaks to help reduce the threat of this waterborne disease for human health.
Further information about the project is provided on the link https://www.pml.ac.uk/Research/Projects/PODCAST.
About the Project
As an Earth Observation intern, I was performing Earth Observation data analysis for the project entitled: Investigating relationships between cholera incidence and remotely-sensed oceanic variables in coastal regions of India. Throughout my internship period, I learned about Earth Observation data acquisition, data compilation, EO data processing and analysis, results visualization interpretation using python programming and report submission.
Research Goal
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The aim of the study is to explore the relationships between cholera outbreaks and Satellite Water Marker (SWM) model compared with cholera outbreaks and chlorophyll-a concentration in coastal regions of India.
Research Objectives
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Calculating the SWM based on the ratio between remote-sensing reflectance in the blue (412 nm) and green (555 nm) wavelengths;
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Estimating and comparing the seasonal correlation coefficients between cholera outbreaks and SWM model and between cholera outbreaks and chlorophyll-a concentrations at selected sites along the coast of India;
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Exploring the possibility to develop site-specific linear relationships between cholera outbreaks and ocean-colour observations.
Abstract
Cholera outbreaks have been persistent in India and around the world which is caused by the bacterium Vibrio cholera. Previous studies have shown significant evidence that phytoplankton can form an environmental reservoir for V. cholerae bacteria and coastal phytoplankton (chlorophyll-a) and environmental conditions with 2-3-months lag. A Satellite Water Marker (SWM) index employed by Jutla et al. (2013) is used in this study to explore the relationships between cholera outbreaks, SWM and chlorophyll-a concentration in coastal regions of India. Although the climatology of SWM and chlorophyll-a have been observed to follow very closely the same trends in the regions under investigation, the SWM peaks precede by approximately two months the peak in cholera incidence, thus supporting the findings from Jutla et al. (2013). Furthermore, the correlation matrixes of SWM/cholera cases gave more realistic outcomes of 2-3 months lag phase compared to that of chlorophyll-a /cholera cases. These preliminary results suggested that SWM index may be utilized to predict cholera outbreaks in the coastal regions of India, thus providing adequate time to take measures to reduce the impact of this seasonal endemic disease.
Regional setting
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The chosen study area in the coastal regions in India
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Based on the observations of reported cholera cases (see figure), four regions of interest are defined along the Indian coastline with regions A and B located along the Arabian Sea, region C located at the southern tip of the Peninsula which share both semi-enclosed seas’ coastlines, and region D located along the Bay of Bengal to investigate potential relationships between environmental conditions and reported.
Data Sources
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Cholera
Clinical data of cholera outbreaks data were obtained from the publicly available Integrated Disease Surveillance Programme (IDSP) archive at https://idsp.nic.in/
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Chlorophyll-a
Chlorophyll-a datasets were downloaded from the European Space Agency Climate Change Initiative (ESA-CCI) data archive at spatial resolution of 4 km and monthly resolution over the 2009 to 2019.
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Remote Sensing Reflectance (Rrs)
The remote-sensing reflectance datasets were downloaded from the ESA-CCI data archive at spatial resolution of 4 km and monthly resolution over the period of 2009 to 2019. Satellite-measured radiance data of Rrs 412 nm and Rrs 555 nm were used in this study to determine the Satellite Water Marker index.
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Physical environmental parameters
Satellite measurements of other parameters such as Sea surface Temperature (SST), Sea Surface Salinity (SSS) and Sea Level Anomaly (SLA) can also help to better understand the controlling factors on the chlorophyll production near the coasts.The SST were obtained from the ESA-CCI data archive at 4 km spatial resolution on a monthly basis from 2008 to 2016. Monthly SSS were extracted from the ESA-CCI from a period of 2010 to 2018. Monthly SLA datasets were also extracted from the ESA-ECCI from 2009 to 2015.
Methodology
Satellite Water Marker (SWM)
The satellite water marker model is calculated based on the variability of the remote sensing reflectance in the blue (412 nm) and green (555 nm) wavelengths respectively to predict the occurrences of cholera. Satellite measured radiances at 412 nm and 555 nm extracted from the ESA-CCI 4km spatial resolution datasets from 2009-2019 are used to compute SWM. The SWM model function is calculated from studies done by Jutla, (2013) as follows:
Results
Comparing climatology of cholera occurrences versus chlorophyll-a concentration and SWM
Monthly Climatology investigation of physical environmental parameters
Seasonal correlation analysis between cholera cases and chlorophyll-a and between cholera cases and SWM
Climatology Map
References
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Campbell, A.M., Racault, M.-F., Goult, S., Laurenson, A., 2020. Cholera Risk: A Machine Learning Approach Applied to Essential Climate Variables. International Journal of Environmental Research and Public Health 17, 9378. https://doi.org/10.3390/ijerph17249378.
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JUTLA, A., WHITCOMBE, E., HASAN, N., HALEY, B., AKANDA, A., HUQ, A., ALAM, M., SACK, R. B. & COLWELL, R. 2013. Environmental factors influencing epidemic cholera. The American journal of tropical medicine and hygiene, 89, 597-607.
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JUTLA, A. S., AKANDA, A. S., GRIFFITHS, J. K., COLWELL, R. & ISLAM, S. 2011. Warming oceans, phytoplankton, and river discharge: implications for cholera outbreaks. The American journal of tropical medicine and hygiene, 85, 303-308.
JUTLA, A. S., AKANDA, A. S. & ISLAM, S. 2010. Tracking Cholera in Coastal Regions using Satellite Observations. Journal of the American Water Resources Association, 46, 651-662.
JUTLA, A. S., AKANDA, A. S. & ISLAM, S. 2012. Satellite Remote Sensing of Space-Time Plankton Variability in the Bay of Bengal: Connections to Cholera Outbreaks. Remote sensing of environment, 123, 196-206. -
RACAULT, M.F., ABDULAZIZ, A., GEORGE, G., MENON, PUNATHIL, M., MCCONVILLE, LOVEDAY, PLATT, SATHYENDRANATH & VIJAYAN 2019. Environmental Reservoirs of Vibrio cholerae: Challenges and Opportunities for Ocean-Color Remote Sensing. Remote Sensing, 11, 2763.
