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Unclassified LA-UR-15-21206

Operated by Los Alamos National Security, LLC for the U.S. Department of Energy's NNSA

Tools and Apps to Enhance Situational

Awareness for Global Disease

Surveillance

Alina Deshpande, Ph.D. May 5th, 2015

Operated by Los Alamos National Security, LLC for the U.S. Department of Energy's NNSA | UNCLASSIFIED-LA-UR-15-21206| 2

Situational awareness - The perception of elements in the

environment within a given time and space, the

comprehension of their meaning, and the projection of their

status in the near future (Endsley, 1995)


• A suite of tools being developed to provide actionable information and knowledge

for enhanced situational awareness during an unfolding event

An app to provide context and a frame of reference for disease

surveillance information about an unfolding event, through

matching of user input to a library of global historical disease

outbreaks (http://swap.lanl.gov)

A tool to facilitate obtaining disease surveillance information.

Contains information on disease surveillance resources

worldwide (http://brd.lanl.gov)

A tool to rapidly select appropriate epidemiological models for

infectious disease prediction, forecasting and monitoring

(http://bard.lanl.gov/brd)

Situational awareness in infectious

disease surveillance – LANL tools


The surveillance window concept

The duration of time within which information obtained can be used for early

warning or early detection of a disease outbreak

Nu

mb

er

of

cases o

f in

fecti

ou

s d

isease

Time


• Cross platform app based on the surveillance window

concept (http://swap.lanl.gov)

• Contextualizes incoming information during an infectious

disease outbreak using historical outbreak data, supports

decision making

• Places a frame of reference for where a case count is

during an outbreak

• Determines whether the unfolding events are still within a

surveillance window, and therefore feasible to control

• Suggests additional information sources that could

support effective consequence management of an

outbreak

• Increases the granularity of situational awareness

The surveillance window app


The surveillance window app - SWAP 14 Diseases, 276 Outbreaks, 89 Countries – so far

Disease

specific

input

request


Development of outbreak matching

algorithm

Build representative disease portfolio of

historical outbreaks

Gather information on case count and

duration of outbreak.

Identify proximal and distal factors for each

outbreak

Select properties for similarity algorithm

Develop questions based on factors identified in each

outbreak.

Determine if these questions provide utility in identifying

patterns or outbreak

Implement weights and refine algorithm

Test each property's effect on the ranking

by one at a time elimination

Assign initial weights based on Rank Sum

weight elicitation. Refine

Test weighting/ iterate and update

Test different property functions, different weights,

and ranking without all attributes


User input

SWAP output -

Similarity scores for

outbreaks in SWAP

library

SWAP output – display of closest

matching historical outbreak with

point estimate for user input


The biosurveillance resource directory

Relational database containing biosurveillance products

and tools available worldwide (478 records covering 194

countries, http://brd.lanl.gov)

Based on framework that classifies and characterizes

biosurveillance resources

Searchable by multiple keywords (data streams,

geographic location, disease, etc.)

Provides access to resource website

Does not house data per se, facilitates discovery and

obtaining the right resources and data

Anticipated users - analysts, public health officers,

decision makers, national and local crisis planners and responders (military and civilian)


Resource Category Examples

Supersystem

A system that collects information from multiple data streams and

other surveillance systems, and analyzes the data that is collected

to inform the biosurveillance goal

GOARN

TESSy

SAGES

System

A system that collects information from one or more data streams

and analyzes the data that is collected to inform the biosurveillance

goal

Biosentinel

ASPREN

ProMed

Health Map

Data Source

A system that collects information from one or more data streams

but does not analyze the data collected for a biosurveillance goal

Google News

Gene Expression Omnibus

Crisis Mappers

Tool / Software

Software or application that enables the collection or analysis of data

Essence

EARS

First Watch

Collective

A group of individuals or organizations with the shared objective of

contributing to data collection and analysis to inform a

biosurveillance goal

Mekong Basin Disease Surveillance

Wildlife Data Integration Network

BRD Resource Types

Collective Data Source Supersystem System Tool/

Software

38 105 10 279 45


Afghanistan 2 Bhutan 2

Congo,

Republic of

the 4 France 11 Ireland 6 Liechtenstein 2 Myanmar 1 Portugal 4

South

Africa 7 Uganda 10

Albania 4 Bolivia 2 Costa Rica 1 Gabon 4 Israel 4 Lithuania 5 Namibia 2 Qatar 1

South

Sudan 3 Ukraine 3

Algeria 6

Bosnia and

Herzegovina 3 Croatia 4 Gambia 1 Italy 8 Luxembourg 5 Nauru 1 Romania 6 Spain 12

United

Arab

Emirates 1

Andorra 2 Botswana 2 Cuba 1 Georgia 1 Jamaica 1

Macedonia, Republic

of 2 Nepal 1 Russia 3 Sri Lanka 1

United

Kingdom 14

Angola 4 Brazil 3 Cyprus 5 Germany 9 Japan 9 Madagascar 2

Netherland

s 7 Rwanda 5 Sudan 5 Uruguay 1

Antigua and

Barbuda 1 Bulgaria 5

Czech

Republic 5 Ghana 5 Jordan 4 Malawi 2

New

Zealand 9

Saint Kitts

and Nevis 1 Suriname 1 Uzbekistan 1

Argentina 2 Burkina Faso 3 Denmark 4 Greece 7 Kazakhstan 2 Malaysia 1 Nicaragua 1

Saint Vincent

and the

Grenadines 1 Swaziland 2 Vanuatu 1

Armenia 2 Burundi 2 Djibouti 2 Greenland 1 Kenya 8 Maldives 1 Niger 3 Samoa 2 Sweden 7

Venezuela,

Bolivaran

Republic of 2

Australia 18 CÃ´te d'Ivoire 3 Dominica 1 Grenada 1 Kiribati 1 Mali 3 Nigeria 9

Sao Tome

and Principe 1 Switzerland 5 Vietnam 4

Austria 6 Cambodia 4

Dominican

Republic 1 Guatemala 1

Korea, Democratic

People's Republic

of 2 Malta 6 Norway 9 Saudi Arabia 1

Syria,

Syrian

Arab

Republic 2 Wales 4

Azerbaijan 3 Cameroon 6 Ecuador 1 Guinea 9 Korea, Republic of 3 Marshall Islands 1 Oman 1 Scotland 2 Taiwan 1 Yemen 2

Bahamas 1 Canada 16 Egypt 5

Guinea-

Bissau 2 Kosovo 1 Mauritania 2 Pakistan 2 Senegal 6 Tajikistan 1 Zambia 3

Bahrain 1 Cape Verde 1 El Salvador 6 Guyana 1 Kuwait 1 Mauritius 1 Palau 2 Serbia 3 Tanzania 6 Zimbabwe 1

Bangladesh 2

Central African

Republic 3 England 7 Haiti 2 Kyrgyzstan 2 Mexico 7 Palestine 1 Seychelles 1 Thailand 7

United

States 279

Barbados 2 Chad 1

Equatorial

Guinea 2 Hungary 6

Laos, Lao

People's

Democratic

Republic 3

Micronesia,

Federated States of 2 Panama 1 Sierra Leone 10 Togo 4

Belarus 3 Chile 3 Eritrea 2 Iceland 3 Latvia 5 Moldova, Republic of 2

Papua New

Guinea 2 Singapore 3 Tonga 2

Belgium 7 China 4 Estonia 5 India 5 Lebanon 2 Mongolia 2 Paraguay 3 Slovakia 5

Trinidad

and

Tobago 1

Belize 2 Colombia 2 Ethiopia 2 Indonesia 4 Lesotho 1 Montenegro 2 Peru 4 Slovenia 4 Tunisia 4

Benin 3 Comoros 1 Fiji 2

Iran, Islamic

Republic of 1 Liberia 8 Morocco 5 Philippines 5

Solomon

Islands 2 Turkey 3

Bermuda 1

Congo,

Democratic

Republic of the 4 Finland 5

Iraq, Republic

of 1 Libya 4 Mozambique 5 Poland 7 Somalia 1 Tuvalu 1

Global distribution of BSV resources


Alabama 8 Florida 17 Louisiana 7 Nevada 5 Oregon 13 Virgin Islands 1

Alaska 9 Georgia 15 Maine 11

New

Hampshire 9 Pennsylvania 13 Virginia 11

American Samoa 2 Guam 2 Maryland 17

New

Jersey 10 Puerto Rico 3 Washington 12

Arizona 10 Hawaii 10 Massachusetts 19

New

Mexico 15 Rhode Island 7 West Virginia 3

Arkansas 6 Idaho 5 Michigan 7 New York 16

South

Carolina 6 Wisconsin 9

California 20 Illinois 12 Minnesota 14

North

Carolina 96 South Dakota 3 Wyoming 3

Colorado 11 Indiana 10 Mississippi 3

North

Dakota 4 Tennessee 8

Connecticut 13 Iowa 8 Missouri 8

Northern

Marianas

Islands 1 Texas 11

Delaware 8 Kansas 6 Montana 5 Ohio 10 Utah 8

District of

Columbia 8 Kentucky 4 Nebraska 6 Oklahoma 5 Vermont 8

US distribution of BSV resources


Alabama 8 Florida 17 Louisiana 7 Nevada 5 Oregon 13 Virgin Islands 1

Alaska 9 Georgia 15 Maine 11

New

Hampshire 9 Pennsylvania 13 Virginia 11

American Samoa 2 Guam 2 Maryland 17

New

Jersey 10 Puerto Rico 3 Washington 12

Arizona 10 Hawaii 10 Massachusetts 19

New

Mexico 15 Rhode Island 7 West Virginia 3

Arkansas 6 Idaho 5 Michigan 7 New York 16

South

Carolina 6 Wisconsin 9

California 20 Illinois 12 Minnesota 14

North

Carolina 96 South Dakota 3 Wyoming 3

Colorado 11 Indiana 10 Mississippi 3

North

Dakota 4 Tennessee 8

Connecticut 13 Iowa 8 Missouri 8

Northern

Marianas

Islands 1 Texas 11

Delaware 8 Kansas 6 Montana 5 Ohio 10 Utah 8

District of

Columbia 8 Kentucky 4 Nebraska 6 Oklahoma 5 Vermont 8

US distribution of BSV resources Biosurveillance

Process: The process of gathering, integrating, interpreting, and communicating

Knowledge: Essential information related to all-hazards threats or disease activity

affecting human, animal, or plant health

Purpose: To achieve early detection and warning, contribute to overall

situational awareness of the health aspects of an incident, and to

enable better decision making at all levels - National Strategy for Biosurveillance, 2012

Early Warning of

Health Threats

Early Detection of

Health Events

Situational

Awareness

Consequence

Management

Surveillance that enables the

identification of potential threats,

including emerging and re-emerging

diseases, that may be undefined or

unexpected

Surveillance that enables

identification of disease outbreaks (either

natural or intentional in origin), or events that

have occurred, before they become

significant

Surveillance that monitors the location,

magnitude and spread of an outbreak

or event once it has occurred

Surveillance that assesses impacts and

informs response to an outbreak or an

event

Baseline Awareness Information that can inform and facilitate the achievement of the above surveillance goals and can be related to population demographics and health, the natural, social, and

built environment and underlying disease patterns and characteristics

BS

V G

OA

LS

Time

Ambulance / EMT Records

Clinic/Health Care Provider Records

ED / Hospital Records

Employment / School Records

Established Databases

Financial Records

Help Lines

Internet Search Queries

Laboratory Records

News Aggregators

Official Reports

Police / Fire Department Records

Personal Communication

Prediction Markets

Sales

Social Media

DA

TA

ST

RE

AM

CA

TE

GO

RIE

S

Algorithms

Collection Method

Data Accuracy

Data Processing Before Analysis

Data Quality

Data Reporting

Data Security

Data Structure

Data Transmission

Geospatial Characteristics

Metadata Collected

Population Characteristics

Stakeholders

…

DA

TA

ST

RE

AM

DE

TA

ILS

Infectious Disease(s)

of Interest

Human Animal Plant

Pathogen Pest

Diagnostic

Data that leads to identification of a

pathogen, or confirmed diagnosis of

disease

Syndromic

Health-related data that may precede

or substitute for formal diagnosis

Environmental

Non-health related data associated

with the social, natural, and/or built

environment

DA

TA

ST

RE

AM

CO

NT

EX

T

Dis

ease, P

op

ula

tio

n, T

yp

e

DA

TA

ST

RE

AM

CH

AR

AC

TE

RIZ

AT

ION

BIOSURVEILLANCE

DATA STREAM FRAMEWORK

SC

OP

E


0 20 40 60 80 100 120

Financial Records

Police/Fire Dept

Prediction Markets

Employment/School

Internet Search Queries

Ambulance/EMT

Sales

Social Media

Help Lines

News Aggregators

Established Databases

ED/Hospital

Personal Communication

Clinic/Health Care Provider

Official Reports

Laboratory Records

Number of Records

Data stream categories used in active

cataloged surveillance systems


Motivation for BARD development

Epidemiological models have utility in disease surveillance, however,

choice of an appropriate model is difficult without information about;

• Scope of their use (e.g. operational status of such models, their

purpose, input data needs, time to results, etc.)

• Features - the diversity of model types and the manner in which they

are described (risk mapping, disease dynamics, statistical, anomaly

detection, network, etc.)


The biosurveillance analytics resource

directory Prototype - 78 models covering Malaria, Cholera,

Influenza, Foot and Mouth disease, Dengue

(bard.lanl.gov/brd)

Provides specific information about an operational model

that has been systematically categorized and highlighted

Allows “apples to apples” comparison of multiple models

if available for a single disease

Provides links to specific models and updated and

accurate contact information for a model facilitating its

immediate use

Is a model characterization tool - The framework could

be applicable to any new models that may be included in

the future and common characteristics and attributes of

models would be cataloged


Number of

Models

Influenza Cholera Dengue FMD Malaria

Described in

research papers 109 30 22 81 34

Included in BARD

(operational

models)

25 14 14 21 13

BARD models

Model Documentation Model Association Model Distribution

3. Model has the equivalent to a

‘user manual’ 3. Model is currently in use and is

being actively promoted for use by

others

3. Model code/software is readily

available either by open-source,

by subscription/registration, or by

purchase 2. Model has technical

documentation 2. Model is linked to a website

specific to the model 2. Model code/software is

available for distribution for limited

use 1. Model has been only described

in peer-reviewed literature 1. Model is only linked to a

research group through

documentation (such as research

team from a university that has

published an article describing

results)

1. Model code/software is not

accessible/available

Working criteria for operational models


http://bard.lanl.gov/brd


• Sustainability of tools and resources • Updated and expanded content – automated data mining tools

• Curated content – Wiki style content editing and updating, engaging

all stakeholders

• Maintaining utility - outreach and tool refinement

LANL decision support tools - the

challenges

Established

Relationships


• Decision support tools offered through LANL’s Biosurveillance (BSV)

gateway (http://bsv.lanl.gov)


• Mr. Esteban Abeyta

• Ms. Lauren Castro

• Ms. Ashlynn Daughton

• Mr. Eric Generous

• Dr. Geoffrey Fairchild

• Dr. Reid Priedhorsky

• Dr. Kirsten Taylor-

McCabe

• Mrs. Nileena Velappan

• Dr. Alina Deshpande

LANL team


Thank you!

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