Spatio-temporal Monitoring of Health Epidemics  in Real-Time-Some Considerations
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Spatio-temporal Monitoring of Health Epidemics in Real-Time-Some Considerations

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Proposal for monitoring real-time syndromic surveillance of epidemics

Proposal for monitoring real-time syndromic surveillance of epidemics

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Spatio-temporal Monitoring of Health Epidemics  in Real-Time-Some Considerations Spatio-temporal Monitoring of Health Epidemics in Real-Time-Some Considerations Presentation Transcript

  • Spatio-temporal Monitoring of Health Epidemics in Real-Time Some Considerations Sanjay Rana
  • Summary
    • Presentation will merely present a broad overview of the areas relevant in developing a system for monitoring the concentration of airborne pathogens in the public transport.
    • Areas of interest will range from Biotechnology to Intelligent Transport System.
    • Proposal still at the preparation stage so presentation only serves to create an awareness and collect responses.
    • “ Prevention is better than cure”
    • Erasmus
  • Contents
    • Objectives, Motivation & Aspirations
    • Concept
    • Challenges
  • 1. Objective
    • Develop a real-time surveillance network to monitor & model the presence & spread of airborne pathogens in public transport vehicles.
    • In much the same way, we can monitor and model air quality by monitoring harmful gases across the city, the pathogen surveillance will be one of the indicators of the health of the city.
  • 1. Motivation
    • Health Risks from:
      • Dramatic increase in the dynamics of people movements
      • Bio-terrorism
      • Ageing population
      • Climate Change
    • Intellectual mysteries:
      • Spatio-temporal evolution of airborne infections in real-time, with implications on prevention and containment
      • Genetic evolution of pathogen species
    • Economical pressure:
      • Cost of sick leave to organisations
      • Cost of maintaining health to individuals
  • 1. Aspirations Short-term Real-time health of the city, specially in times of known high risks Long-term Understanding of systematic patterns of infection and interaction of socio-economic-environmental factors
  • 2. Concept
    • Existing Solution
      • Syndromic Surveillance
      • According to Centre for Disease Control (www.cdc.gov) , “The term “syndromic surveillance” applies to surveillance using health-related data that precede diagnosis and signal a sufficient probability of a case or an outbreak to warrant further public health response”
      • Based on health data from various data sources such as hospitals, emergency rooms, ambulatory care clinics, pharmacies, poison control centers, and clinical laboratories
      • Traditionally collected weekly but CDC’s BioSense Programme aims to receive data at 15 minutes interval
  • 2.Concept
    • Syndromic Surveillance System examples
  • 2. Concept
    • Two main limitations of syndromic surveillance systems for airborne pathogens
      • Design of the surveillance network is similar to that of point-source pollution monitoring networks. Therefore, an infection with origin on a transport network may be reported as being originated at the hospital etc. It would be difficult to track the origin of the infection
      • Essentially based on self-reported data. Typically, people don’t seek medical help immediately after the onset of initial symptoms. Therefore, a person is allowed to carry the infection around in the public and situations becomes critical in case of “super-spreaders”
  • 2. Concept
    • Proposed Solution
      • Real-time collection, analysis, and communication of field data from the vehicles (buses, trains, flights) in the public transport network
      • In-situ Collection and Analysis
        • Biosensor network inside the vehicle
        • Collect information on both airborne pathogens and air quality inside the various parts of the vehicle
      • Communication
        • Using the Intelligent Transport Systems (ITS) infrastructure, such as used for reporting timetable.
      • Analysis at Command and Control Centre
        • Data Mining for patterns
        • Dispatch of emergency services if threshold met
  • 2. Concept Real-time Risk Assessment and Contingency Planning (R2ACP)
    • Biosensor
    • Comms
    • ITS
    Research
    • Epidemiology
    • GeoComputation
    Research
  • 3. Challenges
    • Research Challenges for R2ACP for Health Surveillance
    • Biosensor
    • Dimension – portable, durable, nanotech (?)
    • Pathogens – common cold to SARS or indicator species & unknown species
    • Detection - Preferably remote, air sampling, remote bio-luminescence [ Fomites ]
    • Safety – discreet and secure
    • Cost – affordable
  • 3. Challenges
    • Research Challenges for R2ACP for Health Surveillance
    • Communications
    • Real-time location – GPS or A-GPS, RFID, Automatic Vehicle Loc.
    • Mechanism – GPRS, Wi-Fi, Satellite up-link, Bluetooth, RFID
    • Format – SMS
    • Bandwidth –
    • Encryption –
    • Cost – affordable
  • 3. Challenges
    • Research Challenges for R2ACP for Health Surveillance
    • Intelligent Transport System
    • Complex scheduling and network
    • Integration of R2ACP comms into transport comms infrastructure
    • Passenger Information Systems via web, inside vehicle, stations
    • Vehicle Information Systems for drivers
    • Encryption
    • Affordable
    • Real-time Rome
  • 3. Challenges
    • Research Challenges for R2ACP for Health Surveillance
    • Epidemiology
    • Models to interpret near real-time multiple streams of data from biosensor-on-board (BOB) vehicles on bio-aerosol pathogen composition and other physico-chemical data on air quality
    • Thresholds for raising alarm
      • Accuracy
      • Ethical issues – inform the passengers?
  • 3. Challenges
    • Research Challenges for R2ACP for Health Surveillance
    • GeoComputation
    • Geovisualization –
      • collaborative platform for C&C officers
      • virtual reality
      • large-scale for large area
      • multi-scale
      • multi-thematic
      • multi-modal
      • online systems for public awareness
    • Spatial Analysis – Algorithms for Data mining (spatial statistics) similar to tracking financial crimes (?), hot spot
    • Performance – Grid Computing i.e. using redundant machines for computing scenarios and daily data analysis during the night or low usage (e.g. SETI screensaver).
  • 3. Challenges
    • Non-Research Challenges for R2ACP for Health Surveillance
    • Who is responsible and for how long?
      • Owner - Public sector - NHS or HPA or DoH
      • Installation – Private Contractors
      • Maintenance – Private Contractors
      • Operation – Public-sector with private contracts to other public sector organisation e.g. NHS etc.
    • Who should pay for it? Public-Private Partnership but where is the profit?
  • 3. Challenges
    • Droplet Transmission
      • Micro-organisms travel in large respiratory droplets (coughing, sneezing, drip, exhale) over short distances (~ 3 feet).
      • Most common and rapid mechanism for airborne infections.
      • The infection carrying surfaces (fomites) could be on any object e.g. door knobs, handrails, pens, cups,….
    Image © Keith Berry (permission pending) Image © macsite.org (permission pending) Image © Brian Lema (permission pending) Some fomites and mechanisms of infections on public transport