Conference PaperPDF Available

Participatory disease detection through digital volunteerism: how the doctorme application aims to capture data for faster disease detection in thailand

April 2014

DOI:10.1145/2567948.2579273

Conference: Proceedings of the companion publication of the 23rd international conference on World wide web companion

Authors:

Patipat Susumpow

Opendream

Adam Wade Crawley

Centers for Disease Control and Prevention

This paper reports the work in progress of incorporating a participatory disease detection mechanism into the existing web- and mobile device application DoctorMe in Thailand. As Southeast Asia has a high likelihood of hosting potential outbreaks of epidemics it is crucial to enable citizens to collectively contribute to improved public health through crowdsourced data, which is currently lacking. This paper focuses foremost on the localised approach, utilizing elements such as gamification, digital volunteerism and personalised health recommendations for participating users. DoctorMe's participatory disease detection approach aims to tap into the accelerating technological landscape in Thailand and to improve personal health and provide valuable data for institutional analysis that may prevent or decrease the impact of infectious disease outbreaks.

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Participatory Disease Detection through Digital

Volunteerism: How the DoctorMe Application Aims to

Capture Data for Faster Disease Detection in Thailand

Patipat Susumpow

Opendream

14/5 Soi 11 Sirimagaiajarn Rd.

Sutep Maung

Chiang Mai 50200 Thailand

patipat@opendream.co.th

Patcharaporn Pansuwan

Opendream

14/5 Soi 11 Sirimagaiajarn Rd.

Sutep Maung

Chiang Mai 50200 Thailand

pat@opendream.co.th

Adam W. Crawley

Skoll Global Threats Fund

1808 Wedemeyer St, Ste. 300

San Francisco, CA 94129

acrawley@skollglobalthreats.org

Nathalie Sajda

Opendream

299/92 Suttisan Winitchai Rd.

Samsennok, Huay Kwang

Bangkok 10310 Thailand

nathalie@opendream.co.th

ABSTRACT

This paper reports the work in progress of incorporating a

participatory disease detection mechanism into the existing web-

and mobile device application DoctorMe in Thailand. As

Southeast Asia has a high likelihood of hosting potential

outbreaks of epidemics it is crucial to enable citizens to

collectively contribute to improved public health through

crowdsourced data, which is currently lacking. This paper focuses

foremost on the localised approach, utilizing elements such as

gamification, digital volunteerism and personalised health

recommendations for participating users. DoctorMe’s

participatory disease detection approach aims to tap into the

accelerating technological landscape in Thailand and to improve

personal health and provide valuable data for institutional analysis

that may prevent or decrease the impact of infectious disease

outbreaks.

Keywords

Participatory surveillance, digital disease detection, gamification,

crowdsourcing, Thailand.

1. INTRODUCTION

Southeast Asia has long been a ‘hotspot’ for emerging and re-

emerging diseases; it was the birthplace of both severe acute

respiratory syndrome (SARS) in 2003 and highly pathogenic

avian influenza (HPAI) H5N1 between 2003 and 2005 [1,2]. As

viruses of zoonotic origin, these diseases typify pathogens with

the greatest pandemic potential, made all the more dangerous

when found in a region of the world, such as Southeast Asia, that

contains a high level of wildlife and microbial diversity [3]. The

region is in the midst of rapid social, economic, and

environmental change, driven by increased travel and trade to the

region, urbanisation, and changing agricultural practices. While

many of these trends may increase the risk for emerging diseases,

technological advancements in digital communications and

medical diagnostics can play a key role in protecting the

population’s health.

Over the last decade the public health community has made

significant progress in global surveillance for emerging and re-

emerging diseases, with a number of new disease surveillance

technologies now complementing more traditional reporting

systems. The Program for Monitoring Emerging Diseases (Pro-

MED), a global listserve of infectious disease reporting [4], and

the Global Public Health Intelligence Network (GPHIN), a news

aggregation system that detects early signs of disease outbreaks

[5], were two of the first efforts to leverage the Internet for global

infectious disease surveillance. Other systems such as HealthMap

[6], MedISys [7], and Biocaster [8] have also been developed,

using a variety of digital media and a blend of computer

algorithms and human expertise to detect the first signs of disease

transmission [9]. In addition to these data-mining techniques,

participatory epidemiology, with roots in wildlife health

surveillance [10], has the potential to directly engage the public in

disease surveillance through online reporting of symptoms to

platforms such as Influenzanet [11] in Europe, Flutracking [12] in

Australia, and Flu Near You [13] in North America. These

participatory methods combined with digital communications

hold great potential for detecting outbreaks faster.

Committee (IW3C2). IW3C2 reserves the right to provide a hyperlink to

the author's site if the Material is used in electronic media.

WWW’14 Companion, April 7–11, 2014, Seoul, Korea.

ACM 978-1-4503-2745-9/14/04.

http://dx.doi.org/10.1145/2567948.2579273

663

2. PARTICIPATORY APPROACHES

EMERGING IN THAILAND

Recent improvements in international and regional disease

surveillance networks will complement the ongoing

improvements in disease detection and reporting. In East and

Southeast Asia regional collaborations have improved through

partnerships within World Health Organization (WHO) regions,

the development of the Mekong Basin Disease Surveillance

System (MBDS), and growing participation in the Training

Programs in Epidemiology and Public Health Interventions

Network (TEPHINET) [1]. Thailand, geographically located in

the heart of Southeast Asia and a key partner in both MBDS and

the Asian Partnership for Emerging Infectious Disease Research

(APEIR), hosts a population of approximately 67 million people

and is working with neighbouring MBDS countries to improve

community participation in disease surveillance, strengthen

surveillance at the human-animal interface, and improve

epidemiology capacity.

In addition to regional collaborations, Thailand’s Ministry of

Public Health (MOPH) works closely with the United States’

Centers for Disease Control and Prevention (CDC) on a range of

initiatives, including a Global Disease Detection (GDD) Regional

Center that was established in 2004 and which WHO designated a

Collaborating Center for Implementation of International Health

Regulations National Surveillance and Response Capacity.

Through the GDD the CDC works with Thailand and other

partners to detect a range of diseases, including influenza,

tuberculosis, anthrax, and other zoonotic and vector-borne

diseases by developing sustainable, local capacity to address these

threats.

Beyond traditional governmental partnerships, Thailand has

demonstrated a willingness to improve public health through the

use of new technologies. GeoChat, a group communication tool

that uses SMS, email, and Twitter for chat, reports, and alerts, is

being used in some Thai-Laos border provinces to improve

disease surveillance communication [14]. This effort is supported

by a collaboration between MBDS, Innovative Support to

Emergencies, Diseases, and Disasters (InSTEDD), a non-profit

organisation focused on using a blend of social and technical

approaches to improve global health, safety and sustainable

development, and Opendream, a social enterprise with expertise

in Internet solution development and information design with

“one single bold aim — deliver the information, change the

world”. GeoChat has also been used to support communication

among the Thai Hospital Network, with over 900 facilities,

enabling users to exchange information and receive alerts about

disease outbreaks in the country.

2.1 DoctorMe: Incorporating Participatory

Surveillance into a Self-Care Application

Thailand holds the advantageous position of enhancing innovative

approaches, as illustrated in the GeoChat case, through its rapidly

emerging technology sector. In Thailand, mobile phone

penetration was reported in the second quarter of 2013 to have

reached 131.8%, with the number of mobile subscriptions

exceeding its population. Meanwhile, Internet access reaches

35.8% of the population, at 23.86 million users [15]. Similar to

the global trend, the majority of mobile phone- and Internet users

are found in urban areas. The potential for tapping into the large

pool of mobile and Internet users with the aim to capture health

data is promising.

As Southeast Asia is a hotspot for disease outbreaks and

Thailand’s technological capacity continues to increase, the web-

and mobile application DoctorMe aims to incorporate a

participatory disease surveillance mechanism to capture health

data from citizens.

In 2009 Folk Doctor Foundation digitalised their bi-weekly

healthcare magazine in collaboration with Change Fusion, a non-

profit project of Opendream, and with financial support from the

Thai Health Promotion Foundation. In late 2011, this initiative

developed into the free iOS and Android mobile device

application known as DoctorMe, and was incorporated into the

Folk Doctor Foundation website in 2012. DoctorMe’s

digitalisation of existing general health care information

published in a handbook created by the Folk Doctor Foundation

has enabled a more cost-effective and wider scale of outreach.

The DoctorMe mobile application has, since its launch in 2011,

steadily been ranked amongst the most popular applications in the

health and fitness category of mobile applications in Thailand,

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both in the iOS and Android markets. By the end of 2013, the

application had been downloaded by over 400,000 users and has

35,000 active users monthly. DoctorMe also provides a Global

Positioning System (GPS) with a database of over 1000 registered

hospitals and clinics, free emergency call system and information

regarding medicines and Thai herbal remedies.

DoctorMe’s current version does not collect user data, but

identifies trending symptoms searched by users. By early 2014,

the DoctorMe web- and mobile application will integrate a

participatory disease surveillance mechanism that is incorporated

into the existing application.

Together with the financial support of the Skoll Global Threats

Fund and in collaboration with the Folk Doctor Foundation,

Opendream has developed the software and incentive-basis for

DoctorMe to incorporate a function for citizens to contribute to

public health though community reported data, potentially

enhancing the process of detecting diseases faster.

2.2 Incentives for Participatory Surveillance

DoctorMe’s participatory surveillance mechanism has from an

early stage utilised a community approach. Opendream's

participation and co-organisation of the hack-a-thon1 “epihack” in

Phnom Penh, Cambodia in August 2013, marked the first step in

DoctorMe's conceptual development, through collectively

developing the functions, desired impact and incentives that could

be applied in the application.

DoctorMe holds the advantage of being an existing application

with a broad, and continuously growing, user base. However,

designing the incentives for engaging users in the participatory

surveillance mechanisms are crucial.

To leverage the pre-existing function of healthcare advice,

DoctorMe aims to generate relevant data for users reporting

symptoms of disease. One incentive for participating citizens will

be customised health advice, based on the health status reported,

as well as a personal health tracker, allowing the user to identify

one’s own health trends. In addition, DoctorMe uses an appealing

design, which has been referred to as “Asian cuteness”, and

integrates a gamification element, meaning that as a user actively

reports their health status they will be virtually rewarded through

badges and personalised avatars. DoctorMe also desires to

advocate for so-called digital volunteerism, where users are aware

of the value of individual reporting as a public health good. As

volunteerism is a distinguishing characteristic found in the Thai

society, such as local rescue work or temple work, the concept of

digital volunteerism may be engaging.

1 The “epihack” hack-a-thon is an event gathering designers,

software developers and public health experts from across the

globe to jointly improve and develop health-based technology.

3. DOCTORME AS A PARTICIPATORY

DISEASE DETECTOR – THE GROWING

NEED IN SOUTHEAST ASIA

DoctorMe is the first application of its kind in the Southeast Asian

region, a geographically important region, as it holds a high

likelihood of fostering emerging diseases. DoctorMe has carefully

given attention to a vast spectrum of factors that may ensure the

successful implementation and function of its participatory

disease surveillance mechanism, both among web- and mobile

device users. It is crucial to localise DoctorMe through allowing

users to report their interaction with animals (which no other

digital participatory disease mechanism allows), as this may be a

factor for disease spread. Through the weekly push notifications

and email blasts DoctorMe aims to collect health reports with a

gamification approach and advocacy of digital volunteerism,

while delivering personalised health recommendations to users.

DoctorMe illustrates the potential for combining creative tools

while enhancing public health through crowdsourced data.

Thus, the two main objectives of DoctorMe’s participatory

surveillance approach are; (a) to provide users personalised health

care recommendations through a feedback loop based on the

reported symptoms, which consequently contributes to improved

personal health and potentially decreases the costs of medical

care, and (b) to utilise the captured data on an institutional level to

track public health trends and identify potential disease outbreaks,

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which may be analysed by the Thai Bureau of Epidemiology,

local hospitals or veterinarians. All data captured by DoctorMe

will stored by Opendream on behalf of the Thai Health Promotion

Foundation and the application will be built using open source

code. Data will be provided to the Thai Bureau of Epidemiology

for analysis by that institution.

DoctorMe is an application that has grown from the initial

function of providing useful health recommendations to

incorporating a participatory disease surveillance mechnaism.

DoctorMe addresses the pressing need of including the general

public in the disease reporting process. This technology represents

an effective, scalable and cost-effective tool to reach the aim of

detecting diseases more rapidly for safer societies.

4. ACKNOWLEDGMENTS

Our thanks to the Thai Health Promotion Foundation, Folk

Doctor Foundation and Change Fusion, who jointly enabled

DoctorMe to bridge technology and public health. We are also

grateful for the support and encouragement of the Skoll Global

Threats Fund in taking DoctorMe to the next level, by

incorporating a participatory disease surveillance element into the

system. Last, but not least, our thanks to the whole Opendream

team - that joyfully and creatively constructed the online

application; whose impact reached offline.

5. REFERENCES

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pathogenic avian influenza H5N1: prospects from a spatial-

based model. Vet. Res. 41, 28 (2010).

[3] Morse, S. S. et al. Prediction and prevention of the next

pandemic zoonosis. Lancet 380, 1956–1965 (2012).

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Objective To develop a participatory system for monitoring the activity of influenza-like-illness among the United States general population. Introduction The emergence of new influenza strains including H1N1, H5N1, H3N2v as well as other respiratory pathogens such as SARS, along with generally weak information about household and community transmission of influenza, enforce the need for augmented influenza surveillance. At the same time, Internet penetration and access has grown, with 82% of American adults using the Internet [1], enabling transfer and communication of information that can be collected and aggregated in near real-time. Surveillance targeted towards influenza in other countries, and towards malaria in India, has previously been executed with good user engagement [2,3]. In this study, we created an online participatory influenza surveillance tool in the United States, called Flu Near You. Methods Volunteer users were primarily solicited via collaboration with the American Public Health Association and their members’ networks starting Oct. 24, 2011. Upon registration, each user is sent a weekly email, taking them to the Flu Near You website. On the website they fill in a short survey asking if they had any of 10 symptoms: fever, cough, sore throat, shortness of breath, chills/night sweats, fatigue, nausea or vomiting, diarrhea, body aches and headache, in the last week. Users can also enroll their household members and enter information in for them weekly. A map of influenza activity is made available to users, and anyone accessing the website [Figure 1]. On the map, the number of individuals reporting with no symptoms, some symptoms, or Influenza-like illness are visualized, aggregated to the zip code level. Users can also compare the contributed data with other surveillance systems: the Centers for Disease Control and Prevention, and Google Flu Trends for the same time period [Figure 1]. We also obtained user feedback through a survey in early July 2012. Results As of August 21, 2012, there are over 9300 Flu Near You users, from all 50 states. 94.0% of users are between 20 and 70 years, although 37.2% of household members are < 20 years old. Overall 62.0% of members (users and household) were female. We found that 46.4% of users answered 3 or more surveys. Qualitatively from survey responses, we learned that simple feedback and an emphasis on public health education are important in this type of system. Conclusions We found that it is possible to engage users in a symptom self-reporting system and augment information about influenza for the nation. Increased uptake would increase the value of the system for the public and public health professionals. Flu Near You is expanding in its second season, working to increase user participation. Other connected projects are also examining the expansion into other diseases with high prevalence and in need of augmented surveillance. With a larger user base and through a longer period of execution, systems like Flu Near You will help to improve our understanding of influenza epidemiology as well as guide implementation of relevant and timely public health interventions, for example in estimating vaccination rates and efficacy among different demographic groups. Information reported by individuals can augment traditional public health surveillance methods for more timely detection of disease outbreaks, monitoring disease activity and increasing the public’s engagement in their own and population’s health.

BioCaster: detecting public health rumors with a Web-based text mining system

Article

Full-text available

Jan 2008

Son Doan

Prospects for Emerging Infections in East and Southeast Asia 10 Years after Severe Acute Respiratory Syndrome

Article

Full-text available

Jun 2013

It is 10 years since severe acute respiratory syndrome (SARS) emerged, and East and Southeast Asia retain a reputation as a hot spot of emerging infectious diseases. The region is certainly a hot spot of socioeconomic and environmental change, and although some changes (e.g., urbanization and agricultural intensification) may reduce the probability of emerging infectious diseases, the effect of any individual emergence event may be increased by the greater concentration and connectivity of livestock, persons, and products. The region is now better able to detect and respond to emerging infectious diseases than it was a decade ago, but the tools and methods to produce sufficiently refined assessments of the risks of disease emergence are still lacking. Given the continued scale and pace of change in East and Southeast Asia, it is vital that capabilities for predicting, identifying, and controlling biologic threats do not stagnate as the memory of SARS fades.

Prediction and prevention of the next pandemic zoonosis

Article

Full-text available

Dec 2012
LANCET

Most pandemics--eg, HIV/AIDS, severe acute respiratory syndrome, pandemic influenza--originate in animals, are caused by viruses, and are driven to emerge by ecological, behavioural, or socioeconomic changes. Despite their substantial effects on global public health and growing understanding of the process by which they emerge, no pandemic has been predicted before infecting human beings. We review what is known about the pathogens that emerge, the hosts that they originate in, and the factors that drive their emergence. We discuss challenges to their control and new efforts to predict pandemics, target surveillance to the most crucial interfaces, and identify prevention strategies. New mathematical modelling, diagnostic, communications, and informatics technologies can identify and report hitherto unknown microbes in other species, and thus new risk assessment approaches are needed to identify microbes most likely to cause human disease. We lay out a series of research and surveillance opportunities and goals that could help to overcome these challenges and move the global pandemic strategy from response to pre-emption.

Online Flutracking Survey of Influenza-like Illness during Pandemic (H1N1) 2009, Australia

Article

Full-text available

Dec 2010

We compared the accuracy of online data obtained from the Flutracking surveillance system during pandemic (H1N1) 2009 in Australia with data from other influenza surveillance systems. Flutracking accurately identified peak influenza activity timing and community influenza-like illness activity and was significantly less biased by treatment-seeking behavior and laboratory testing protocols than other systems.

Anthropogenic factors and the risk of Highly Pathogenic Avian Influenza H5N1: prospects from a spatial-based model

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Dec 2009

Beginning in 2003, highly pathogenic avian influenza (HPAI) H5N1 virus spread across Southeast Asia, causing unprecedented epidemics. Thailand was massively infected in 2004 and 2005 and continues today to experience sporadic outbreaks. While research findings suggest that the spread of HPAI H5N1 is influenced primarily by trade patterns, identifying the anthropogenic risk factors involved remains a challenge. In this study, we investigated which anthropogenic factors played a role in the risk of HPAI in Thailand using outbreak data from the "second wave" of the epidemic (3 July 2004 to 5 May 2005) in the country. We first performed a spatial analysis of the relative risk of HPAI H5N1 at the subdistrict level based on a hierarchical Bayesian model. We observed a strong spatial heterogeneity of the relative risk. We then tested a set of potential risk factors in a multivariable linear model. The results confirmed the role of free-grazing ducks and rice-cropping intensity but showed a weak association with fighting cock density. The results also revealed a set of anthropogenic factors significantly linked with the risk of HPAI. High risk was associated strongly with densely populated areas, short distances to a highway junction, and short distances to large cities. These findings highlight a new explanatory pattern for the risk of HPAI and indicate that, in addition to agro-environmental factors, anthropogenic factors play an important role in the spread of H5N1. To limit the spread of future outbreaks, efforts to control the movement of poultry products must be sustained.

Digital Disease Detection - Harnessing the Web for Public Health Surveillance

Article

Full-text available

Jun 2009
NEW ENGL J MED

John Brownstein, Clark Freifeld, and Lawrence Madoff write that a new generation of disease-surveillance “mashups” can mine, categorize, filter, and visualize online intelligence about epidemics in real time.

BioCaster: Detecting public health rumors with a Web-based text mining system

Article

Full-text available

Nov 2008
BIOINFORMATICS

BioCaster is an ontology-based text mining system for detecting and tracking the distribution of infectious disease outbreaks from linguistic signals on the Web. The system continuously analyzes documents reported from over 1700 RSS feeds, classifies them for topical relevance and plots them onto a Google map using geocoded information. The background knowledge for bridging the gap between Layman's terms and formal-coding systems is contained in the freely available BioCaster ontology which includes information in eight languages focused on the epidemiological role of pathogens as well as geographical locations with their latitudes/longitudes. The system consists of four main stages: topic classification, named entity recognition (NER), disease/location detection and event recognition. Higher order event analysis is used to detect more precisely specified warning signals that can then be notified to registered users via email alerts. Evaluation of the system for topic recognition and entity identification is conducted on a gold standard corpus of annotated news articles. Availability: The BioCaster map and ontology are freely available via a web portal at http://www.biocaster.org. Contact: collier@nii.ac.jp

Epidemiología participativa en la vigilancia de enfermedades y la investigación

Article

Dec 2007
REV SCI TECH OIE

L'epidemiologie participative consiste a appliquer les methodes participatives a la recherche epidemiologique et a la surveillance des maladies. Il s'agit d'une technique eprouvee qui a surmonte la plupart des contraintes des methodes epidemiologiques traditionnelles et permis de resoudre un grand nombre de problemes dans les domaines de la surveillance et de la recherche en sante animale. Mise au point dans le cadre de petits programmes communautaires de sante animale, cette methode a ete appliquee ensuite dans des initiatives internationales de grande envergure pour la prophylaxie des maladies animales. Le Programme mondial d'eradication de la peste bovine a fait appel a l'epidemiologie participative en tant qu'outil de surveillance pour la peste bovine. Par la suite, cette methode a ete utilisee en Afrique et en Asie dans des configurations tant rurales qu'urbaines de lutte contre la fievre aphteuse, la peste des petits ruminants et l'influenza aviaire hautement pathogene. La surveillance participative contribue de maniere significative a la prophylaxie des pathologies rares comme des affections courantes. Les auteurs examinent les principales applications de l'epidemiologie participative en soulignant les lecons tirees de l'experience sur le terrain. En outre, ils exposent les defis futurs ainsi que les aires nouvelles qui s'ouvrent a la recherche.

ProMED-mail: An Early Warning System for Emerging Diseases

Article

Aug 2004
CLIN INFECT DIS

Lawrence C Madoff

The Program for Monitoring Emerging Diseases (ProMED-mail) reports on outbreaks of diseases of infectious or toxic etiology, whether natural or intentionally released, that affect humans. Open to all sources, free of political constraints, and available to users free of charge, ProMED-mail exploits the speed and ubiquity of the Internet to serve as an early warning system for the detection of emerging disease outbreaks. ProMED-mail monitors diseases of plants and animals of agricultural importance in addition to zoonoses because of their key role in disease emergence. Reports are carefully screened for validity and are placed in an appropriate context by commentary and references from a panel of expert moderators. Reports are then posted to the Web and sent by e-mail to >32,000 subscribers in >150 countries.