Perspective | May 21, 2009 Digital Disease Detection — Harnessing the Web for Public Health Surveillance John S. Brownstein, Ph.D., Clark C. Freifeld, B.S., and Lawrence C. Madoff, M.D.

1. The NEW ENGLA ND JOURNAL of MEDICINE
Perspective may 21, 2009
Digital Disease Detection — Harnessing the Web
for Public Health Surveillance
John S. Brownstein, Ph.D., Clark C. Freifeld, B.S., and Lawrence C. Madoff, M.D.
T he Internet has become a critical medium for
clinicians, public health practitioners, and lay-
people seeking health information. Data about dis-
tries.2 ProMED uses the Internet
to disseminate information on
outbreaks by e-mailing and post-
ing case reports, including many
eases and outbreaks are disseminated not only through gleaned from readers, along with
expert commentary. In 1997, the
online announcements by govern- outbreaks and emerging diseases. Public Health Agency of Canada,
ment agencies but also through Because Web-based sources fre- in collaboration with the WHO,
informal channels, ranging from quently contain data not captured created the Global Public Health
press reports to blogs to chat through traditional government Intelligence Network (GPHIN),
rooms to analyses of Web searches communication channels, they are whose software retrieves relevant
(see box). Collectively, these sourc- useful to public health agencies, articles from news aggregators
es provide a view of global health including the Global Outbreak every 15 minutes, using exten-
that is fundamentally different Alert and Response Network of sive search queries. ProMED and
from that yielded by the disease the World Health Organization GPHIN played critical roles in
reporting of the traditional public (WHO), which relies on such informing public health officials
health infrastructure.1 sources for daily surveillance ac- of the outbreak of SARS, or se-
Over the past 15 years, Inter- tivities. vere acute respiratory syndrome,
net technology has become inte- Early efforts in this area were in Guangdong, China, as early as
gral to public health surveillance. made by the International Society November 2002, by identifying in-
Systems using informal electron- for Infectious Diseases’ Program formal reports on the Web through
ic information have been credited for Monitoring Emerging Diseas- news media and chat-room dis-
with reducing the time to recog- es, or ProMED-mail, which was cussions.
nition of an outbreak, preventing founded in 1994 and has grown More recently, the advent of
governments from suppressing into a large, publicly available re- openly available news aggrega-
outbreak information, and facil- porting system, with more than tors and visualization tools has
itating public health responses to 45,000 subscribers in 188 coun- spawned a new generation of dis-
n engl j med 360;21 nejm.org may 21, 2009 2153
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2. P ERS P E C T IV E Digital Disease Detection — Harnessing the Web for Public Health Surveillance
Digital Resources for Disease
Detection.
Sample Web-based data sources
ProMED-mail, www.promedmail.
org
Global Public Health Intelligence
Network (GPHIN), www.
phac-aspc.gc.ca/media/nr-rp/
2004/2004_gphin-rmispbk-eng.
php
HealthMap, www.healthmap.org
MediSys, http://medusa.jrc.it
EpiSPIDER, www.epispider.org
BioCaster, http://biocaster.nii.ac.jp
Wildlife Disease Information Node,
http://wildlifedisease.nbii.gov
H5N1 Google Earth mashup,
www.nature.com/avianflu/ Screen Shot of HealthMap during the Recent Salmonella Typhimurium Outbreak.
google-earth HealthMap displays 319 articles about the outbreak that has affected 38 U.S. states.
ICM AUTHOR Brownstien RETAKE 1st
Avian Influenza Daily Digest Fig 1 2nd
and blog, www.aidailydigest. public REG F officials, clinicians, information they report pales in
health FIGURE
blogspot.com and international travelers. Other comparison to the potential
CASE 3rdcol-
TITLE Revised
Google Flu Trends, www.google. similar systems include MediSys, lective intelligence that can be
EMail
org/flutrends Line 4-C
EpiSPIDER, BioCaster, and garnered from the public. An es-
Argus,Enon SIZE
ARTIST: mleahy
the Wildlife Disease Information H/T H/T
timated 37 to 52% ofpts
Google Insights for Search, www.
FILL Combo 198 Americans
google.com/insights/search Node. Automated analysis of on- seek health-related information
DiSTRIBuTE, www.syndromic.org/ and radio on the Internet each year, gener-
line video materials AUTHOR, PLEASE NOTE:
projects/DiSTRIBuTE.htm
broadcastsFigure has provide addi- and type has beenengines to find
will soon been redrawn ally using search reset.
GeoSentinel, www.istm.org/ Please checkadvice on conditions, symptoms,
tional sources for early detection. carefully.
geosentinel/main.html
The ease of use of blogs, mail- and treatments. Logs of users’
Emerging Infections Network,
http://ein.idsociety.org
ing lists, RSS (Really Simple Syndi- chosen keywords and location in-
JOB: 36021 ISSUE: 5-21-09
cation) feeds, and freely available formation encoded in their com-
Argus, http://biodefense.
georgetown.edu mapping technology has meant puters’ IP (Internet Protocol) ad-
that even an individual expert can dresses can be analyzed to provide
Sample health-related social-
networking sites create an important global re- a low-cost data stream yielding
Physicians, www.sermo.com
source. For instance, Declan But- important insights into current
ler, a reporter at Nature, took ag- disease trends.3 The power of
Patients, www.patientslikeme.com
gregated data from various sources these data has been demonstrat-
Everyone, www.healthysocial.org
to provide a view of the spread ed by studies of search engines
of H5N1 avian influenza on a provided by Google4 and Yahoo,5
ease-surveillance “mashups” (Web Google Earth interface. Similarly, in which data on searches using
application hybrids) that can mine, Claudinne Roe of the Office of influenza-related keywords were
categorize, filter, and visualize on- the Director of National Intelli- used to generate an epidemic curve
line intelligence about epidemics gence produces the Avian Influ- that closely matched that gener-
in real time. For instance, Health- enza Daily Digest and blog, a col- ated by traditional surveillance for
Map (see image) is an openly avail- lection of unclassified information influenza-related illness, deaths,
able public health intelligence about confirmed and suspected and laboratory results. Google Flu
system that uses data from dispa- human and animal cases of H5N1 Trends now provides a prospective
rate sources to produce a global influenza. view of current influenza search
view of ongoing infectious disease Although news media repre- patterns throughout the United
threats. It has between 1000 and sent an important adjunct to the States. By making the information
150,000 users per day, including public health infrastructure, the freely available to public health
2154 n engl j med 360;21 nejm.org may 21, 2009
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3. PE R S PE C T IV E Digital Disease Detection — Harnessing the Web for Public Health Surveillance
opportunities for connecting ex-
18 120
perts who identify and report out-
Outbreak Investigation
Public Announcement
Cases by onset date
Searches for “salmonella” breaks. Information technologies
16
Searches for “peanut butter” such as wikis, social networks,
Searches for “diarrhea” 100
and Web-based portals can facil-
No. of Salmonella Typhimurium Infections
14 Searches for “recall”
itate communication and collab-
Standardized Google Search Volume
Searches for “food poisoning”
oration to accelerate the dissemi-
12 80
nation of reports of infectious
diseases and aid in mobilizing a
10
response. Some scientific societies
60
are now leveraging technologies
8
for distributed data exchange,
analysis, and visualization. For
6 40
instance, the International Society
for Disease Surveillance has cre-
4
ated the Distributed Surveillance
20
Taskforce for Real-Time Influen-
2
za Burden Tracking and Evalua-
tion (DiSTRIBuTE), a group of
0 0
state and local health depart-
8
08
8
8
9
09
00
00
00
00
ments that use the Web to share,
20
20
,2
,2
,2
,2
1,
1,
r1
r1
r1
y1
integrate, and analyze health data
er
ry
be
be
be
ar
ua
ob
nu
em
em
em
br
ct
across large regions. And the In-
Ja
O
pt
ov
ec
Fe
Se
D
N
ternational Society of Travel Med-
Infections with the Outbreak Strain of Salmonella Typhimurium, as reported by the CDC icine, in collaboration with the
as of February 8, 2009. Centers for Disease Control and
Lines show data from Google Insights for Search, representing a portion of Web searches based in Prevention (CDC), has created the
ICM AUTHOR: Browstein
the United States across all Google domains relative to the total number of searches done on
RETAKE 1st
2nd
Google over time Fand scaled toof 2maximum value of 100. The data have been standardized by
FIGURE 2 a
GeoSentinel project, which brings
REG
3rd
subtracting the mean volume from the previous 12 months for each term.
CASE
together travel and tropical-med-
Revised
EMail Line 4-C icine clinics in an electronic net-
SIZE
officials, clinicians, and ordinary nella,” and search volumes were
Enon
ARTIST: ts H/T H/T
2� col
work for surveillance of travel-
Combo
citizens, such tools could help to compared with the corresponding related illnesses. Similarly, the
AUTHOR, PLEASE NOTE:
guide medical redrawn and type has been reset.
Figure has been decision making volumes from the previous year. Emerging Infections Network, ad-
and underscore thecheck carefully. of The initial public report of salmo-
Please importance ministered by the Infectious Dis-
vaccination and other preventive nella was released on January 7,
JOB: 36021 ISSUE: 05-21-09
eases Society of America in col-
measures. 2009, triggering an increase in laboration with the CDC, is a
An example of the power of searches for “salmonella,” “recall,” Web-based network of more than
search-term surveillance can be and “peanut butter,” but we saw 1000 infectious disease specialists
found in an examination of the earlier peaks in searches for “di- that is geared toward finding cas-
recent peanut-butter–associated arrhea” and “food poisoning.” Ad- es during outbreaks and detecting
outbreak of Salmonella enterica sero- mittedly, these data provide only new or unusual clinical events.
type Typhimurium. Using Google preliminary evidence of an emerg- Broader Web-based networks
Insights for Search, a search-vol- ing problem and require further are also proving useful for sur-
ume reporting tool from Google, study, but they highlight possibili- veillance. Social-networking sites
we compared the epidemic curve ties for early disease detection. for clinicians, patients, and the
of onset dates for confirmed in- Though mining the Web is a general public hold potential for
fections with trends in the vol- valuable new direction (see side- harnessing the collective wisdom
ume of Internet searches on re- bar on the H1N1 influenza epi- of the masses for disease detec-
lated terms in the United States demic), these sources cannot re- tion. Given the continued deploy-
(see graph). Search terms included place the efforts of public health ment of personally controlled elec-
“diarrhea,” “peanut butter,” “food practitioners and clinicians. The tronic health records, we expect
poisoning,” “recall,” and “salmo- Internet is also providing new that patients’ contributions to dis-
n engl j med 360;21 nejm.org may 21, 2009 2155
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4. P ERS P E C T IV E Digital Disease Detection — Harnessing the Web for Public Health Surveillance
Influenza A (H1N1) Virus, 2009 — Online Monitoring
T he value of Web-based informa-
tion for early disease detection,
public health monitoring, and risk
communication has never been as
evident as it is today, given the emer-
gence of the current influenza A
(H1N1) virus. Many ongoing efforts
have underscored the important
roles that Internet and social-media
tools are playing in the detection of
and response to this outbreak.
In March and early April, while
much of the world was focusing on Information on Suspected or Confirmed Cases of H1N1 Influenza That HealthMap Has
the threat of avian influenza originat- Collected since April 1 from Mexico, the Southern United States, and Central America.
ing in Asia, intelligence-gathering The balloon shows the initial reports from La Gloria, Veracruz. The markers represent
locations where there have been unofficial reports about suspected or confirmed cases
systems were also extracting evi- of H1N1 (not the individual cases themselves) as well as other reports of influenza and
dence of an epidemic of acute respi- other respiratory illness. Darker markers indicate increased recent report volume.
ratory infections in Mexico. Early in-
formal reports from the Mexican guage media until weeks later (April trolled the outbreak at the source.
press indicated that a “mysterious” 21), when two children living near Clearly, this event also highlights
influenza-like illness was occurring San Diego (neither of whom had the swift response capability of the
in the town of La Gloria in the state been exposed to pigs) presented global public health community.
of Veracruz, where it was reported with mild respiratory symptoms and The emergence of H1N1 has
that up to 60% of the 3000 inhabit- fever. In those cases, the Centers been subsequently tracked through
ants had been infected and 2 had for Disease Control and Prevention both automated and manual data
died since early March. The Health- had confirmed the presence of entry and visualization with the use
Map system, for instance, collected H1N1 on April 17.4 The timeline of full-spectrum Web-based com-
and disseminated a local media re- thus emphasizes the importance of munication strategies. Though tra-
port describing this event on April 1, surveillance of local information ditional official and media commu-
2009 (see map).1 This report was sources in local languages. nication channels remain in place,
followed by another on April 2 de- Epidemic-intelligence systems Web-based mapping, search-term
scribing the possible role of Granjas receive many reports of mysterious surveillance, “microblogging,” and
Carroll, a U.S.-owned pig farm, in respiratory illness daily, and the de- online social networks have emerged
the epidemic.2 On April 10, the cision to consider this event one of as alternative forms of rapid dis-
Global Public Health Intelligence international significance requires semination of information. Under-
Network (GPHIN) reported acute interpretation of context — for ex- standably, some observers worry
respiratory illness in Veracruz to the ample, of the level of background about their ability to inspire public
World Health Organization (WHO). noise inherent in various data-min- concern beyond the necessary lev-
This alert was followed by immedi- ing systems. A fully moderated ap- els. Clearly, these tools must be
ate communication among the proach (in which each communica- used with restraint and appropriate
WHO’s Global Outbreak Alert and tion is reviewed by someone with evaluation.
Response Network, the Pan Amer- expertise in the subject matter), 1. Morales AT. Veracruz: reporta agente mu-
ican Health Organization, and the such as that of the International nicipal extraño brote epidémico que ha cob-
rado dos vidas. La Jornada. April 1, 2009.
Mexican Ministry of Health.3 Society for Infectious Diseases’ Pro- 2. Martinez R. Extraño brote epidemiológico
Other informal media sources gram for Monitoring Emerging Dis- causa la muerte a dos bebés en Veracruz.
subsequently began to reflect the eases (ProMED), though poten- Proceso. April 2, 2009.
3. Harris G. Questions linger over the value
spread of the epidemic through tially less timely, provides critical, of a global illness surveillance system. New
parts of Mexico, including Oaxaca, evidence-based risk assessment. York Times. May 1, 2009.
Baja California, Mexico City, and San An in-depth evaluation is required 4. Swine influenza A (H1N1) infection in two
children — southern California, March–April
Luis Potosí. Reports of this outbreak to determine whether any earlier 2009. MMWR Morb Mortal Wkly Rep 2009;
did not appear in the English-lan- intervention efforts might have con- 58:400-2.
2156 n engl j med 360;21 nejm.org may 21, 2009
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Copyright © 2009 Massachusetts Medical Society. All rights reserved.

5. PE R S PE C T IV E Digital Disease Detection — Harnessing the Web for Public Health Surveillance
ease surveillance will increase. their potential for public health research software developer at the Chil-
dren’s Hospital Informatics Program in
Eventually, mobile-phone technol- practice and clinical decision mak- Boston and a master’s candidate in the
ogy, enabled by global positioning ing. Sources such as analyses of New Media Medicine Group of the MIT Me-
systems and coupled with short- search-term use and news media dia Laboratory in Cambridge, MA. Dr. Brown-
stein and Mr. Freifeld are the cocreators of
message-service messaging (text- may also face difficulties with the HealthMap system. Dr. Madoff is a pro-
ing) and “microblogging” (with verification and follow-up. Though fessor of medicine at the University of Mas-
Twitter), might also come into they hold promise, these new sachusetts Medical School, Worcester, an
infectious disease physician with the Mas-
play. For instance, an organiza- technologies require careful eval- sachusetts Department of Public Health,
tion called Innovative Support to uation. Ultimately, the Internet Boston, and editor of ProMED-mail, a pro-
Emergencies, Diseases, and Dis- provides a powerful communica- gram of the International Society for Infec-
tious Diseases.
asters (InSTEDD) has developed tions channel, but it is health care
open-source technology to permit professionals and the public who 1. Brownstein JS, Freifeld CC, Reis BY, Mandl
KD. Surveillance Sans Frontières: Internet-
seamless cross-border communi- will best determine how to use based emerging infectious disease intelli-
cation between mobile devices for this channel for surveillance, pre- gence and the HealthMap Project. PLoS Med
early warning and response in re- vention, and control of emerging 2008;5(7):e151.
2. Madoff LC. ProMED-mail: an early warn-
source-constrained settings. diseases. ing system for emerging diseases. Clin Infect
These Internet-based systems Dr. Brownstein, Mr. Freifeld, and Dr. Dis 2004;39:227-32.
Madoff report receiving grant support from
are quickly becoming dominant Google.org. No other potential conflict of
3. Eysenbach G. Infodemiology: tracking
flu-related searches on the web for syndromic
sources of information on emerg- interest relevant to this article was reported. surveillance. AMIA Annu Symp Proc 2006:
ing diseases, though their effects 244-8.
This article (10.1056/NEJMp0900702) was
on public health measures remain published at NEJM.org on May 7, 2009.
4. Ginsberg J, Mohebbi MH, Patel RS, Bram-
mer L, Smolinski MS, Brilliant L. Detecting
uncertain. Information overload, influenza epidemics using search engine
false reports, lack of specificity Dr. Brownstein is a faculty member at the query data. Nature 2009;457:1012-4.
of signals, and sensitivity to ex- Children’s Hospital Informatics Program, 5. Polgreen PM, Chen Y, Pennock DM, Nel-
Children’s Hospital Boston, and an assis- son FD. Using Internet searches for influenza
ternal forces such as media inter- tant professor of pediatrics at Harvard surveillance. Clin Infect Dis 2008;47:1443-8.
est may limit the realization of Medical School, Boston. Mr. Freifeld is a Copyright © 2009 Massachusetts Medical Society.
he alth c are 2 0 0 9
What Works in Market-Oriented Health Policy?
Meredith B. Rosenthal, Ph.D.
T here is a widespread belief,
embraced by President Barack
Obama as well as congressional
interests — can be implemented
even in highly regulated settings.
The main question is how to de-
Thus, the adoption of policies
that increase the share of costs
paid by patients is one way to save
and industry leaders, that the next sign these interventions to improve money on medical care.
round of health care reform should the medical system, without harm- However, research also shows
leverage market forces to lower the ful side effects (see table). that there are limitations to the
cost of care and improve its qual- On the demand side, consum- usefulness of cost sharing for im-
ity. The use of market forces in er cost sharing has been used for proving efficiency. Most impor-
health policy typically involves al- decades to alter decisions about tant, patients with high levels of
tering out-of-pocket prices and in- care seeking, adherence, and pur- cost sharing appear equally like-
formation for consumers (the de- suit of lower-cost treatment op- ly to cut back on essential health
mand side) and incentives for tions. A 10% increase in the out- care services as on services of low
providers (the supply side). Such of-pocket cost of care has been or no value. Such findings sug-
market-oriented reforms — poli- shown to reduce total spending gest that consumer cost sharing
cies that alter the economic envi- per patient by roughly 2%.1 Sim- ought to be selective, or value-
ronment in which consumers and ilarly, adding a high (approximate- based: low cost sharing for high-
providers make health care choic- ly $1,000) deductible to a plan re- value services and high cost shar-
es in pursuit of their individual duces total spending by 4 to 15%.2 ing for low-value services. Some
n engl j med 360;21 nejm.org may 21, 2009 2157
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