Tracking Cholera in Coastal Regions using Satellite Observations

Abstract

Cholera remains a significant health threat across the globe. The pattern and magnitude of the seven global pandemics suggest that cholera outbreaks primarily originate in coastal regions and then spread inland through secondary means. Cholera bacteria show strong association with plankton abundance in coastal ecosystems. This review study investigates relationship(s) between cholera incidence and coastal processes and explores utility of using remote sensing data to track coastal plankton blooms, using chlorophyll as a surrogate variable for plankton abundance, and subsequent cholera outbreaks. Most studies over the last several decades have primarily focused on the microbiological and epidemiological understanding of cholera outbreaks. Accurate identification and mechanistic understanding of large scale climatic, geophysical and oceanic processes governing cholera-chlorophyll relationship is important for developing cholera prediction models. Development of a holistic understanding of these processes requires long and reliable chlorophyll dataset(s), which are beginning to be available through satellites. We have presented a schematic pathway and a modeling framework that relate cholera with various hydroclimatic and oceanic variables for understanding disease dynamics using latest advances in remote sensing. Satellite data, with its unprecedented spatial and temporal coverage, have potentials to monitor coastal processes and track cholera outbreaks in endemic regions.

FIGURE 1

Countries affected by the Seventh Pandemic of Cholera (compiled from World Health Organization (WHO), Center for Disease Control and Prevention (CDC), and various news sources, Countries in the red shade have reported cholera outbreaks)

FIGURE 2

Space-time variations of chlorophyll (mg/m³) in the Bay of Bengal (a) Mean chlorophyll; (b) Lowest chlorophyll month (February) and (c) Highest chlorophyll month (September). This figure is based on climatology of 10 years of SeaWiFS data at 9km spatial resolution.

FIGURE 3

Cholera, River Discharge and Chlorophyll in Bay of Bengal. The climatology has been calculated using ten years of monthly (a) SeaWiFs data for chlorophyll, (b) incidence data of cholera incidence from ICDDR,B and (c) discharge data obtained from Bangladesh University of Engineering and Technology. The data has been normalized between 0 and 1.

FIGURE 4

Cholera, River Discharge and Chlorophyll in Coastal Mozambique. The climatology has been calculated using ten years of monthly (a) SeaWiFs data for chlorophyll, (b) incidence data of cholera incidence from literature and (c) discharge data obtained from River Discharge Data (RIVDIS: www.rivdis.sr.unh.edu). The data has been normalized between 0 and 1.

FIGURE 5

Possible ocean corridors for cholera outbreaks along tropical coastal regions (shown as the black box spanning between 30N to 30S) cholera outbreaks. The figure has been constructed using ten years (September 1997- March 2010) of monthly chlorophyll data. The global chlorophyll visualization were produced with the Giovanni online data system, developed and maintained by the NASA GES DISC.

Figure 6

Plausible Flow Diagram for a Macro-SIR modeling framework