On October 13-15, 2008, over 65 people gathered from around Cambodia to participate in a CDC-led avian influenza pandemic training and simulation exercise in the Stung Treng province. CDC provided the public health training and InSTEDD introduced and tested new uses of mobile phones that will help with pandemic preparedness and response.

1. Workshop on Simulation Exercise for AI Focusing
on Information Technology
Stung Treng Province, Cambodia, October 13‐15, 2008
After Action Report
Taha A. Kass‐Hout, MD, MS
Draft of 12/04/2008
Our primary aim was to provide and test a prototype emergency response system based on open source
technologies that would strengthen the response capabilities of Rapid Response Teams (RRT), referral
hospital, first responders and local communities within the provinces, villages and communes in the
setting of an avian influenza pandemic. A series of user‐centered design sessions and training with the
MoH, RRT team and various community members were conducted before and during the exercise. More
specifically, participating RRT and hospitals needed to validate and get training on existing plans, and to
develop Pandemic Response Plans for their province, for effective communication prevention and
control of the spread of disease and leverage the open source tools we developed in‐country to help
them achieve this goal.

2.
Table of Contents
Introduction....................................................................................................................................................... 3
The Simulation Exercise ..................................................................................................................................... 3
The Situation.............................................................................................................................................................3
The Objective and Opportunity ................................................................................................................................4
The Approach............................................................................................................................................................4
The Exercise: Avian Flu Outbreak in 3 Villages on October 15, 2008 .......................................................................5
Pandemic Alert Period (WHO Pandemic Stages 3 and 4).....................................................................................5
Pandemic Alert Period (WHO Pandemic Stage 5) ................................................................................................5
Participants ..........................................................................................................................................................6
Participants Feedback .......................................................................................................................................10
Cell Phone Use ........................................................................................................................................................10
Using Geochat.........................................................................................................................................................11
Challenges and Opportunities............................................................................................................................11
Costs and sustainability......................................................................................................................................12
Conclusion ........................................................................................................................................................13
Appendix I: Agenda...........................................................................................................................................14
Simulation Exercise for AI focusing on Information Technology, Sekong Star Hotel (Stung Treng), 13‐15 October,
2008 ........................................................................................................................................................................14
Appendix II: Strategic Opportunities..................................................................................................................15
Opportunities to Enhance Disease Detection and Response for Cambodia and the MBDS Region.......................15
Surveillance Data Storage and Management.....................................................................................................16
Direct Participation of Labs Laboratory .............................................................................................................17
Unstructured Text and RSS Feeds ......................................................................................................................17
Collaboration......................................................................................................................................................17
Analytics and Visualization.................................................................................................................................17
Appendix III: Mekong Region Geochat Coverage [to date] .................................................................................17
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3. Workshop on Simulation Exercise for AI Focusing on Information
Technology: Stung Treng Province, Cambodia, October 13-15, 2008
Routine health facility based disease surveillance systems, such as those on which most MBDS countries
depend, could provide neither a complete nor a representative picture of health problems in the
communities. This is primarily due to the fact that patients who cannot get access to public health
facilities or who choose not to use them are not reported by these systems. In order to overcome this
limitation, we augment facility‐based health information systems with a community‐based approach
based upon a collaborative network of people involved in the systematic detection and reporting of
health‐related events from their
community. We tested this initial
capability (InSTEDD’s Geochat) in a cross‐
sector and cross‐province Avian Influenza
(AI) community simulation exercise in
Stung Treng province, Cambodia. This
collaborative effort was sponsored by
InSTEDD and conducted jointly with the
Stung Treng Provisional Health
Department (PHD), Cambodia CDC, and
Cambodia Ministry of Health (MoH.)
Introduction The Stung Treng province faces many health
problems and often relies on the public health system or its
community‐based organizations for help in lieu of medical
practitioners or clinics. It also turns to affordable cell phones in lieu
of landlines for mobility, and cost savings. Public health practitioners
and community practitioners who provide local services find ongoing
communication with individuals in communities of need, to be a
challenge. InSTEDD worked with Cambodia Ministry of Health,
Cambodia CDC, Stung Treng Provisional Health Department, local
health centers, and simulated participation of cross‐border officials
to help address this challenge using text‐messaging (SMS) as an
affordable means to improve outreach communication and
disseminate multi‐directional information among various agencies
and those in the field. SE Asia Region (Source: Wikipedia)
The Simulation Exercise
The Situation Public health officials are on alert because of increasing concerns about the prospect of
an influenza pandemic. Moreover, because of recent problems with the availability and strain‐specificity
of flu vaccines, as well as the rising specter of the avian flu, officials from Cambodia Ministry of Health
(MoH), CDC and Stung Treng Provisional Health Department (PHD) are alarmed about the potential
inability to prevent or contain a human pandemic once it erupts in a few villages. Cambodia MoH, in
coordination with Cambodia CDC, adopted and adapted the WHO Global pandemic preparedness plan
to prepare for, respond to, and contain an outbreak of pandemic flu. With a population of >100,000
(>25,000 in the city), and many more visiting the province each day, the Stung Treng province was the
focus of the exercise (Please see Appendix I for agenda). Furthermore, since Lao PDR became an ASEAN
member, many national roads have been renovated and/or constructed, with support from many
international donors. Geographical isolation, which has always been a characteristic of Lao PDR, is
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4. beginning to break down, affording both new potential and challenges for development, but also
increasing the likelihood of disease spread from Lao (Champasak) to Cambodia (Stung Treng).
The Objective and Opportunity With
InSTEDD as a sponsor and technical partner, the
Stung Treng Province took the lead in organizing an
intensive (2.5 days) coordinated exercise. The
scope of this government‐led exercise included the
execution of a WHO comprehensive plan to
evaluate pandemic influenza preventive measures
and avian flu preparedness for Cambodia.
InSTEDD's augmented this effort by facilitating
multi‐directional communication among entities
charged with preparedness and response in the
Stung Treng province, and the other six Cambodian
participating provinces.
Our primary aim was to provide and test a
prototype emergency response system based on
open source technologies that would strengthen
the response capabilities of Rapid Response Teams
(RRT), referral hospital, first responders and local
communities within the provinces, villages,
communes and cross‐border in the setting of an
avian influenza pandemic. A series of user‐
centered design sessions and training with the
MoH, RRT team and various community members
were conducted before and during the exercise.
More specifically, participating RRT and hospitals WHO Pandemic Severity (Source: WHO)
needed to validate and get training on existing
plans, and to develop Pandemic Response Plans for their province, for effective communication
prevention and control of the spread of disease and leverage the open source tools we developed in‐
country to help them achieve this goal.
The Approach In collaboration with CDC and the MoH, InSTEDD assembled a team of over 75
participants,
representing 7 provinces,
from various
governmental sectors
(e.g., RRTs, district and
provincial health
departments, local and
provincial government,
law enforcement) at
multiple levels to
participate in an Avian AI Exercise Discussion Facilitated by Dr. Chan Vuthy, Chief, Surveillance Bureau, KH‐
Influenza (AI) exercise. CDC, Cambodia
The AI exercise took
place October 13‐15, 2008 to collect communication protocol responses through an SMS channel.
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5. InSTEDD conducted on‐site training on using SMS on October 13 and October 14, 2008 and carried out
the simulation exercise during the morning of October 15, 2008. The Stung Treng Rapid Response Team
(RRT) was also able to leverage valuable experience and lessons learned from a recent Geochat session
with InSTEDD in the previous week. The exercise incrementally simulated pandemic phase 5 in a
simulation format. The goal was aimed at having local groups understand and develop local
implementation of response plan to identify areas that require improvements and additional resources
and to provide each participating group with a viable pandemic response plan.
The Exercise: Avian Flu
Outbreak in 3 Villages on
October 15, 2008 The exercise
focused on tracking the existing spread
of avian influenza strains (such as
H5N1) that may possibly mutate into a
highly contagious human pandemic and
utilize Geochat, among other
techniques and tools, to help
communicate messages. There were
several specific challenges addressed in Least and worst case pandemic scenario played by
the exercise: Dr. Sovann Ly, Cambodia MoH
• This is a truly global task—the presence of a highly communicable human‐to‐human strain of
the virus anywhere requires immediate notification.
• Focus is on population and clinical data since animal data is not currently shared by other
government (Agriculture) or private sectors (Transportation)
• It is necessary to treat the outbreak as a linked collection of health events (corresponding to a
regional areas) rather than a single event, since there will likely be multiple response teams
operating at multiple levels.
Pandemic Alert Period (WHO Pandemic Stages 3 and 4) At this stage, the majority of human
infections have been directly from birds, and only limited human‐to human infection has been observed.
Key steps in addressing the current phases in the WHO Global preparedness plan involve:
• Developing one or more standing groups will be dedicated to Pan Flu Surveillance. (Likely, there
would be a national one for general tracking, and a dedicated group for planning at the
region/local levels.)
• Incorporate International Data feeds
for international human (WHO) and
animal (OIE) data. (These may require
NLP processing of free text, or may
require human intervention in the case
of animal data form OIE.)
• Define a “High Level” health event to
represent the H5N1 threat, and to
associate ongoing tasks for further
monitoring.
Pandemic Alert Period (WHO Pandemic
Stage 5) When larger clusters of human‐to‐
human infection have been observed it will be Introduction to InSTEDD’s Geochat as it relates to the
necessary to: Simulation Exercise
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6. • Create a Health Event for each cluster that is linked to the “overall” H5N1 Health Event.
• Spawn tasks for each new Health Event for development of case definitions, and for monitoring
selected indicators.
• Create new groups (as necessary) for RRT and local (village lead and local authorities) response
teams for each of these clusters.
Participants A participant survey was conducted after the training (we received 55 responses
(~73.33% response rate).) Based on this survey, the majority of participants (12 Female (23.5%) and 39
Male (76.5%), 4 missing responses) had health or public health backgrounds as follows:
• There were a total of 20 nurses (37%, 1 missing response), 12 nurses primarily used Nokia
phones (60%), and they joined multiple groups with the majority being in the Yellow2 group (11
(55%)), Yellow1 group (4 (20%)), and Blue1 group (2 (10%).)
• There were a total of 12 MDs (22%, 1 missing response), 9 MDs primarily used Nokia phones
(75%), and they uniformly joined multiple groups (majority are in group Yellow2 (25%).)
• There was 1 participant with a
formal degree in public health
(MPH) who used a Nokia phone and
joined the Green3 group.
• Other participants 11 (20%) had
various background or training (data
entry, laboratory, midwife,
pharmacy, physiotherapy, infectious
diseases, malaria and diarrhea, or
Geochat Training conducted by the InSTEDD Team
IT); the majority have used Nokia
phones (73%), and uniformly
Geochat Group n %
joined multiple groups.
Blue1 (simulated cross-border—Champasak) 4 7.5
• 19% of participants did not Green1 (Kampot) 4 7.5
specify their background or Green2(Takeo) 2 3.8
training. Green3 (Kompong Speu) 2 3.8
• Almost half the participants (23 Green4 (Ratanakiri) 0 0
(42.59%), 1 missing response) Green5 (Mondulkiri) 2 3.8
were between the ages of 36‐45 Green6 (Kampong Cham) 3 5.7
Yellow1 (Rapid Response Team) 6 11.3
year. 3 under 25 years old
Yellow2 (Provincial Health and Reference Hospital) 18 34
(5.56%, 1 missing response), 14 Yellow3 (Authorities) 7 13.2
between the ages of 26‐35 years Yellow4 (Others) 5 9.4
(25.93%, 1 missing response),
and 14 over 45 years old (25.93%, 1 missing response.)
• Most participants had electricity at work (47 (85.45%)) and at home (48 (90.57%), 2 missing
responses), had phone coverage at home (50 (94.34%), 2 missing responses) and work (51
(92.73%), and had Computer at home (32 (60.38%), 2 missing responses) and at work (26
(47.27%).) The majority of participants did not have Internet at home (18 (33.96%), 2 missing
responses) nor at work (13 (23.64%).)
The participants; per instructions from CDC, broke out into 3 major groups of ~20 people in each group
(2 provinces in each group) and CDC facilitated various preparedness and response plan discussions in a
Q/A format specifically targeted at the local level. For the purpose of the exercise, we further broke the
3 groups into Geochat groups to match their roles. Various SMS messages were exchange during the
simulation exercise following the Ministry of Health communication policy. Participants were then asked
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7. to join one of 10 different groups given their role in the exercise. The majority of the users (18 users or
34%) joined the Stung Treng Provincial Health and Reference Hospital (Yellow2) group (2 missing
responses), 13 users (24.6%) were from other provinces, and 7 users were representatives from the
authorities group (fire, police, etc.)
Though Geochat (in its current design) does not have a specific policy module for hierarchical
information flow, the hierarchies of chain of command and chain of responsibilities were fully respected
by augmenting each step of the simulation exercise as follows:
1. Step One: few cases were reported to Stung Treng PHD by villagers in 2 villages. PHD notifies
CDC and sends RRT team to the two villages. RRT team members communicate among
themselves the findings from the two villages.
Communicating Parties Geochat Message Khmer Translation (using English
characters)
Stung Treng RRT Stung 5 cases ILI in 5 karney mean ILI nov srok a
Treng RRT Village a
Stung Treng RRT Stung 3 cases ILI in 3 karney mean ILI nov srok b
Treng RRT Village b
2. Step Two: The head of the RRT team wastes no chance of suspecting Avian Influenza. He sends
CDC an alert from the field of suspect AI cases from these villages and awaits recommendations
from CDC on how to proceed.
Communicating Parties Geochat Message Khmer Translation (using English characters)
Head RRT CDC 8 cases suspect AI 8 karmey sangsay AI
3. Step Three: CDC alerts all provinces (including Stung Treng) and Champasak (through a
simulated cross‐border coordination) of suspect AI outbreak.
Communicating Parties Geochat Message Khmer Translation (using English
characters)
CDC PHD and RH in Stung Suspect AI outbreak in Sangsay AI pteus nov Stung
Treng Stung Treng Treng
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8. CDC ALL Parties Suspect AI outbreak in Sangsay AI pteus nov Stung
Stung Treng Treng
4. Step Four: CDC immediately follows‐up with clear case definition for suspect AI.
Communicating Geochat Message Khmer Translation (using
Parties English characters)
CDC ALL 7 Suspect AI case definition, Niyominey karaney sagsay AI:
Provisional Health fever > 38c with kamdov leus 38c, pagnaha
Departments and respiratory problem phlov danghoem ( khaork, hot,
simulated cross‐ (cough, dyspnea, sore chheu kor, hear sambor) reu
border throat, runny nose) or roksangna phseng phseng
other symptom (diarrhea, (reak, chheusach dom
myalgia, etc.) AND close cheadoeum) NOUNG ban pah
contact with poultry (sick pal cheamuoy sat del chheu reu
or dead chicken) over last gnab khnong kamlong 7 thgney
7 days mun
5. Step Five: While CDC awaits further testing, given the matched case definition above in the
villages, CDC orders authorities to close access to villages immediately.
Communicating Parties Geochat Message Khmer Translation (using English
characters)
CDC/PHD Authorities (e.g., Close access to Bit kar chang choul phum
Police) village
6. Step Six: At this point, villages are in self‐sustainment mode where each village lead coordinate
and collaborate with families and local authorities to issue Quarantine, distribute medication
and PPE masks, request help from local authorities in maintaining order in the village and
making sure Quarantine is in effect for identified cases, alert local hospitals or treatment centers
of the situation so they prepare infection control units, and help the sick reach local treatment
center per protocol. For training purposes we relaxed the assumption of hierarchical reporting
at the very end of the exercise by letting information flow freely within workgroups, in particular
for those representing field workers. This allowed users to get more familiar with the software
and be more creative in coordinating an outbreak/pandemic response.
Communicating Geochat Message Khmer Translation (using English
Parties characters)
General Messages 1. Does anyone have a 1. Teu nak na mean lan te?
among field car? 2. Yeun trov ka thnam
workers, first 2. We need medicine 3. Yeun trov ka PPE
responders, 3. We need PPEs 4. Nor na chea prathean phom?
authorities, and 4. Who is the head of 5. Cruosa trov ka aha
government village? 6. Knhon trov ka mazut
officials at CDC and 5. Family needs food 7. Men anugnat ouy mean ka
provisional levels. 6. I need mazut choub chum nov wat
(gasoline) 8. Te phsa boeuk reu nov?
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9. 7. No gathering allowed 9. Te sala boeuk reu nov?
at Pagoda 10.Knom trov ka lanpet
8. Is market open? 11.Teu mean avey ouy yeung
9. Is school open? chhouy te?
10.I need an ambulance 12.Ter yerng ach chuoy avey
11.Can we help? ban?
12.What can we do to 13.Ter neak mean thnam
help? bonthem te?
13.Do you have extra 14.Bat yerng mean thnam
medicine? 15.Ter neak mean thnam krob
14.Yes, we have extra kran te?
medicine 16.Te yerng khmean thnam te
15.Do you have enough 17.Ter neak mean PPE bonthem
medicine? te?
16.No, we don’t have 18.Bat yerng mean PPE
any medicine 19.Ter neak mean PPE krob kran
17.Do you have extra te?
PPEs? 20.Te yerng khmean PPE te
18.Yes, we have extra 21.Ter yerng ach tor tuol
PPEs chumnuoy pi Quarantine te?
19.Do you have enough
PPEs?
20.No, we don’t have
any PPEs
21.Can we get help with
Quarantine
The findings of this simulation exercise suggest potential use of SMS text‐messaging as a communication
medium for bi‐directional exchange between field practitioners, field practitioners and central, and
cross sectors. A contribution of this simulation exercise is the data collection in a community setting in
bridging the digital divide where affordability is a limitation. The following figure shows the overall
number of messages exchanged during the exercise (including test and training messages)
Total Messages (exercise and training) Exchanged during the AI Simulation Exercise.
October 13, 2008 thru October 15, 2008, Stung Treng, Cambodia
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10. Exercise Phase Delivery Date Number of Messages Number of Parts Message Status
Actual Exercise 10/15/2008 1 1 Error delivering message
Actual Exercise 10/15/2008 2204 2213 Received by recipient
Actual Exercise 10/15/2008 26 26 Delivered to gateway
Training 10/14/2008 16 16 Error delivering message
Training 10/14/2008 776 776 Received by recipient
Training 10/14/2008 62 62 Delivered to gateway
Training 10/13/2008 5 5 Error delivering message
Training 10/13/2008 496 496 Received by recipient
Training 10/13/2008 48 48 Delivered to gateway
Breakdown and Status of Messages (exercise and training) Exchanged during the AI Simulation Exercise,
October 13, 2008 thru October 15, 2008, Stung Treng, Cambodia
Total Messages (exercise only) Exchanged during the morning of the AI Simulation Exercise,
October 15, 2008, Stung Treng, Cambodia
Participants Feedback According to the survey results (using Likert scale and open‐ended
questions) we provide the following summary:
Cell Phone
Use
Participants
used a total of
14 different
phone with
the majority of
participants
(73%) used
Nokia (2 users
did not have
phone during
the exercise, 3 missing responses.) The majority of the phones did not support local Khmer language (47
(94%), 5 missing responses).) MobiTel code (012) provided mobile service for 2/3rd of the phones (33
(67.35%)), and Sinawatra (code 011) were the service provider for 1/3rd of the phones (16 (32.65%).)
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11. Using Geochat Of the 55 complete responses 45 (82.2%) users were able to join a group, 46 (84.4%)
sent at least one message to a group, 47 (85.5%) users receive at least one message from a group, and 3
(5.5%) were unable to use Geochat.
The feedback we received was very positive:
Phone Type n %
• Users favored the training and they: Golden 1 1.9
a. would like similar training in the future (mean 1.3 (95% no phone 2 3.8
CI: 1.1‐1.5 (0.10 SD)), with 1 quot;Definitely, I would like to Nokia 38 73.1
Nokia 6085 1 1.9
do this type of training againquot; and 5 quot;Definitely NOT, I Nokia 6270 1 1.9
would not like to do this type of exercise againquot;, 1 Nokia 63 00 1 1.9
missing response), Nokia 6300 1 1.9
b. felt the training was adequate (mean 1.8 (95% CI: 1.6‐ Nokia 7610 1 1.9
Nokia N 95 1 1.9
2.1 (0.12 SD)), with 1 quot;Yes, I learned a lotquot; and 5 quot;not Nokia N70 1 1.9
reallyquot;, 2 missing responses) and Nokia N81 1 1.9
c. felt their questions were answered (mean 1.4 (95% CI: Nokia(6120) 1 1.9
Nokia(N95) 1 1.9
1.2‐1.6 (0.10 SD)), with 1 quot;Yes, all my questions were
Sony Ericson 1 1.9
answeredquot; and 5 quot;none of my questions were
answeredquot;, 5 missing responses.) Geochat Group Preference n
• Users felt confident they can use the system on their own Village health volunteer 41
(mean 1.8 (95% CI: 1.6‐2.1 (0.13 SD)), with 1 being Village health center 45
Completely Confident and 5 Not at all Confident.) District heath department 38
• Users asked for using Geochat immediately (“ASAP”) for real Provincial health department 44
Cambodia CDC 43
life scenarios and in other provinces (1 missing response.)
Provincial RRT 43
Participants were then asked their preference; if they were using National RRT 39
Geochat today, of which group they will join. The following table Authority 36
summarizes the responses for each role (assuming the groups were NGO 27
formed based on the role of participants.) Cross border 33
Other 9
Challenges and Opportunities ICTs have enabled public health
officials in Cambodia (and other countries in the region) to coordinate public health response. More
traditional ICTs like radio and television have been beneficial in disease prevention and epidemic
response. In Cambodia, this has been evident in response to recent Avian Influenza cases, HIV/AIDS,
Malaria and Cholera amongst other diseases. More recent ICTs like mobile phones, email and Internet
could also be used for training, outbreak investigation and coordinated response, and even sending
health alerts to the general public. Although Geochat has the potential to be greatly beneficial for the
public health sector in Cambodia
(and other countries in the Southeast Asia region and similar developing countries), its success is
sometimes marred by challenges and contradictions. This includes the workable condition and costs of
ICT equipment, mobile coverage, level of awareness, and skills of the potential users, technology
compatibility and policy provisions amongst others. The ICT infrastructure status in Cambodia currently
is unable to adequately support the full benefits of Geochat in the public health and health sectors.
Internet access is very limited or non‐existent below the provisional level. Most health centers and
provisional health departments still use manual systems of recording and exchanging weekly and
monthly information. Cost of text‐messaging or accessing the internet (further discussed in next
section), maintaining the equipment and buying new ones are also a challenge. In addition to the costs
and status of infrastructure, there is currently very little emphasis on quot;horizontalquot; collaboration (e.g.,
province‐to‐province, or local‐to‐local.) Related to this are the following elements as requested in the
feedback we received from participants:
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12. • Local Khmer language support to make it easier to communicate, especially for those in the
field.
• More frequent training in Stung Treng and other provinces
• Faster delivery of message once it’s been sent—(during the exercise users experienced delayed
message delivery (in some instances for up to 60‐90 minutes), an issue we believe might be
related to local mobile service provider (MobiTel and/or Sinawatra) since the Geochat system
received all messages in time. Our engineers continue to work with MobiTel and health officials
to find a solution once the problem is further identified.)
When we asked why a user might not want to use Geochat, quot;Need Geochat as soon as possible to get
only 10 users (or 18% or the total responses) indicated their ready to fight epidemic disease especially AIquot;
inability to use for the following reasons:
• 3 users (5.5%) find it difficult to use an English‐based quot;…slow SMS response, hard to communicate
phone across different group” Kampot
• 2 users (3.6%) cannot afford a cell phone
• 3 users (5.5%) find it difficult to use an English‐based quot;...suggest InSTEDD to support RRT team for
smooth operation because I will learn more
phone AND cannot afford a cell phone from InSTEDD.quot;
• 1 user finds it difficult to use text‐messaging (SMS)
• 1 user (1.8%) worried about delayed response to CDC “I suggest having Geochat training in other
provinces…”
or MoH
We envision Geochat to also enable distance learning for health personnel and others on several health
issues.
Costs and sustainability Though we haven’t conducted an economic study on the annual per capita
cost to the Cambodian government, the Geochat model offers a toll free number to the user through a
SMS gateway at a country or regional level. We anticipate the cost will be only a small fraction of what
would be for each user to use their personal number. Additional costs include occasional visits from
Phnom Penh for training, supervision, and evaluation. This cost would be even lower if the system was
operated by the District once appropriately trained by our team. We anticipate Geochat to be lower
than that of many similar systems running in developing countries to date, because of its use of existing
health infrastructure and staff, which costs much less than projects run by non‐governmental
organizations where additional staff and facilities have to be funded (O’Neill 1993; Cairncross et al.
1997.) The anticipated amount of staff time
required to manage the system will be relatively
small; 1 day per month during the ICT meeting for
central level, plus a half‐day of training, and time
spent on outbreak response, if any. Additional
focus is on training Provisional and District health
departments, health centers and Village Health
Volunteers (VHVs) (3–4 half days per month.)
The InSTEDD Geochat (and other InSTEDD tools) –
coupled with the InSTEDD local innovation lab –
has many attributes that could make it more The Komphun rural Health Center serves over 7000
viable – that is sustainable – than other initiatives. population in the Stung Treng and neighboring
provinces. The center’s director already uses SMS to
First, VHVs and health staff could potentially run
communicate potential outbreak information or
and manage the system by themselves, with little
suspect AI cases to PHD and CDC
technical or supervisory support. Second, the
system augments the existing health system and
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13. resources, following the Ministry of Health policy and strategy to strengthen the Operational District
structure. It gives the Operational District and health center a mechanism to fulfill their role in disease
prevention and control in the communities. Third, the InSTEDD Geochat comprises mechanisms to
maintain VHVs’ motivation to continue community‐based surveillance. The mechanisms include
continuous training and supportive supervision from the InSTEDD local staff in the innovation lab,
‘instant feedback’, and involvement in data analysis and decision‐making. Additional mechanisms could
be offered by the Cambodian government which include; health care benefits and work recognition.
Conclusion This exercise introduced protocols and basic communication tactics hypothesized to
improve pandemic preparedness. An AI scenario was selected by the MoH and CDC due to the
“commanding nature” initiated in a typical pandemic response effort. The setting presented supported a
response action that was realistic to the community practitioner role. Direct application with response
tactics and the type of role the community practitioner can play in a pandemic that extends beyond
routine surveillance activities especially that external help may not be available or is not known to occur.
However, the challenge of finding ways to increase SMS usage through everyday needs in local
communities remains. Practice to increase use of mobile technologies including SMS text‐messaging can
assist community practitioners working in the field and can enhance preparedness and response. We
recommend that a community based surveillance system is most needed by Cambodia and the region.
InSTEDD suite of tools (Geochat, Hotline, Riff, Mesh4x, and RNA)—run and maintained by Cambodia
MoH and local health staff—is feasible and that this framework can produce useful information for
training and for monitoring trends to identify potential outbreaks of common infectious diseases (Please
refer to Appendix II for a further discussion on a recommended strategy and opportunities for Cambodia
and the region.)
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14. Appendix I: Agenda
Simulation Exercise for AI focusing on Information Technology, Sekong Star Hotel
(Stung Treng), 13­15 October, 2008
Date/Time Program/Topic presentation Presenter
Day 1
8:00‐8:30 Registration
8:30‐9:30 Opening Session
Welcome Address Director of CDC
Department
Representation of
InSTEDD
Director of Stung Treng
PHD
09:30‐10:00 Tea/Coffee Break
10:00‐12:00 Updated Situation general of AI in the Dr. Ly Sovann
world
Lunch
13:30‐15:00 National Surveillance Response in Dr. Chan Vuthy
Cambodia
15:00‐15:30 Tea/Coffee Break
15:30‐17:00 National Plan for AI Response Dr. Ly Sovann
Day 2
8:00‐8:30 Registration
08:30‐10:00 Discussion on Rapid Containment plan CDC/MOH and RRT/ST
10:00‐10:30 Tea/Coffee Break
10:00‐12:00 Continuous Discussion CDC/MOH and RRT/ST
12:00‐13:30 Lunch
13:30‐15:00 Focusing on information technology InSTEDD Representation
15:00‐15:30 Tea/Coffee Break
15:30‐17:00 Focusing on information technology InSTEDD Representation
(Continuous)
Day 3
8:00‐8:30 Registration
08:30‐10:00 Field testing on information technology
10:00‐10:30 Tea/Coffee Break
10:00‐11:00 Field testing on information technology
(Continuous)
11:00‐11:30 Closing session
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15. Appendix II: Strategic Opportunities
Opportunities to Enhance Disease Detection and Response for Cambodia and the MBDS Region
The incidence of specific infectious diseases in Cambodia such as Guinea worm infection, yaws, malaria,
HIV and tuberculosis; pregnancy outcomes; nutritional status of children; and vital events is tracked
through various disease surveillance programs, each of which focuses on a single disease. This approach
does not maximize the value of scarce resources available at the peripheral level and often misses
emerging infections. The confirmation in the first week of February 2005 that the H5N1 strain of avian
influenza had claimed its first human victim in Cambodia had raised great concerns about surveillance
capabilities in Cambodia and in nearby countries. In addition, the diagnosis of the very first case was
made not in Cambodia but in neighboring Vietnam, where the 25‐year‐old woman had sought treatment
and died on January 30, 2005.
These incidents underscore the need to have a better surveillance approach; for both human and
animal, for Cambodia and the region. Cambodia, Laos, and Myanmar have relatively small poultry
populations, and therefore there is probably less H5N1 virus in circulation in these countries. But their
underdeveloped surveillance capabilities also offer less chance of early detection of an outbreak,
especially if the virus becomes easily transmissible among humans. Clearly, what is most needed in
Cambodia is a community‐based disease surveillance, in which data (human and animal) are actively
collected through periodic home visits. This approach will yield a higher proportion of cases reported
than the current passive data collection surveillance systems. The use of tally sheets; that can easily be
deployed on cell phones, to record and report events is most appropriate for semi‐literate Village Health
Volunteers (VHVs) in remote areas which could also help reduce errors in data collection. Since the first
incident H5N1 confirmed human case from Cambodia, US CDC has funded several efforts in conjunction
with WHO and Cambodia MoH to strengthen VHVs in the Kendal and Kampot Provinces (in the southern
tip of Cambodia) hotspots. To‐date, there are more than 260 village workers that are well trained in
identifying and reporting human and animal health events—(two workers per village; a human health
reporter and animal health reporter, for each of 140 villages in the two provinces.) Events currently
monitored are multiple, important, relevant and relatively easy for local people to identify.
Furthermore, a community‐based surveillance system which is developed with local participation and
locally managed is likely to be more effective than vertically‐run programs and projects developed and
implemented by national, international or non‐governmental organizations.
The current disease surveillance process in the region is anomaly‐centric (change in health‐related
patterns) as identified by perceived health‐related threats. The objective of better and earlier disease
detection is to detect and to characterize these changes such as environmental changes (e.g., heat
wave, hurricane, and chemical spills), causes of disease and the demographics of affected individuals,
and the potential disease agents. The analysis must produce information in a form that is useful to
decision makers. The following exhibit illustrates the process of how biosurveillance requires a
combination of active and passive surveillance systems along with an intervention model. Initially, an
ongoing passive surveillance system monitors existing baseline information as well as identifies
anomalies from that baseline.
A sensitive and responsive passive surveillance system will rapidly initiate an appropriate active
surveillance response as well as a timely intervention and response (e.g., quarantine of a localized area
until further details can be ascertained through the active surveillance process). Active surveillance
starts when a change in health‐related pattern worthy of attention warrants some intervening activity.
All of these activities and processes must be able to function through already existing and well‐defined
policies, protocols, and enabling infrastructure. Infrastructure includes channels of communication in
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16. daily and emergency conditions, data networks with common messaging and architecture adherent to
health and public health standards, and the vision of nationally integrated public health and clinical
systems. This integrated approach would exhibit a flexible, sustainable system of systems that is
nationally‐led, provision or district‐directed, and locally‐operated to provide for a stronger national
biosurveillance system.
When the analysis of routinely collected data (e.g., notifiable diseases (e.g., HIV/AIDS, TB, Cholera,
Malaria, etc.) raises suspicion of an outbreak, a health department may decide to collect additional data
(which feeds back into the analytic process) and take action such as issuing a boil‐water advisory, or
treating individuals with antibiotics or vaccines.
In the case of many public health events, the time lag between exposure to a pathogen and the onset of
symptoms may vary from hours to days to weeks, so effective response to such an event will require a
well conceived, active surveillance process supported by clear scientific evidence. This surveillance can
be further facilitated by an information system integration that enables the timely collection, analysis,
and dissemination of critical information to prevent or mitigate the effects on populations from such
events.
InSTEDD suite of tools and local innovation lab (in Phnom Penh1) can support further sustainment of this
local capacity in which its performance can be linked to the importance of events monitored, the system
design and its key players. InSTEDD has developed a hotline proof‐of‐concept in which the diseases or
syndromes to be reported are locally the most important communicable diseases in terms of severity,
burden or epidemic potential. This proof‐of‐concept can easily be expanded to support community‐
based surveillance. In combination with the hotline, InSTEDD’s Geochat can provide a multi‐directional
flow of information, instant feedback, local use of data, and simplicity as well as decentralized
management of the system. It enables information to be fed back to all participants of the system and
decisions to be made to address identified issues within the same day of data reporting that can
potentially minimize the related workload of the health staff as well. This process challenges all
participants to take necessary remedial action together, the results of which can be closely monitored
by them. This will also overcome constraints due to delayed feedback and non‐participation of local
health staff and communities in data analysis, decision‐making and action‐taking; therefore insuring
better identification and response to local emerging threats. Additionally, births and deaths, on the
contrary, constitute important and relevant information needed for appropriate planning of disease
control and prevention activities as well for monitoring infant and child mortality, as birth and death
registration are not currently available in Cambodia. This information can easily be collected and
exchanged during routine home visits. All these events have elicited the interest of health staff and
VHVs, who are the end users of the data they collect. Furthermore, we propose the following
framework; augmenting existing efforts, in order to insure a comprehensive and integrated disease
surveillance for Cambodia and the region:
Surveillance Data Storage and Management The current systems in place do not address how a
recipient of surveillance data will store the data or make it available for analysis. Our approach (depicted
here) factors in a modification to support sharing a minimum data set (MDS), in addition to its current
collections of data, leveraging on existing investment. This approach will not mandate local facilities to
adopt any particular storage strategy and schema, but will “push” the data directly to them using both
message‐ (e.g., Geochat microformat via a country or regional SMS gateway) and document‐based
means.
1
Phnom Penh Innovation Lab team giving its first steps! http://edjez.instedd.org/2008/09/phnom‐penh‐innovation‐lab‐team‐
giving.html
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17. Direct Participation of Labs Laboratory information is not shared in timely manner, the availability of
this data can further enhance detection and validation of potential disease outbreaks.
Unstructured Text and RSS Feeds Incorporation of unstructured text sources into surveillance
applications may accelerate detection (e.g., ProMed, feeds from news agencies, text‐messages from
localities, etc.)
Collaboration A collaborative and workflow system must exist in order to bridge existing
communication streams to support a comprehensive detection and response capability. The InSTEDD
platform consists of a suite of collaborative tools, processes and services (Mesh4X, Riff, Geochat
microformats, and RNA) that can provide such capability. These tools were developed through a user‐
centered and iterative design approach
Analytics and Visualization We propose a two‐pronged approach to developing and fielding analytics.
At the initial phase, a cross‐regional capability for SEA must be established, so that agencies of all levels
may use a common set of analytics that we can develop. In the next phase, we will work with users on
identifying an initial test bed for developing analytics and indicators that are optimized for local and
cross‐border health departments and localities. InSTEDD’s RNA can be adapted to provide a
collaborative analytic framework where a myriad of sources, retrieval, analytics (inductive and
deductive), human experts’ input and hypotheses generation, review, and collaboration techniques
coexist seamlessly. RNA can help:
• Identify, characterize, localize and track disease‐related events;
• Maintain a cross‐community awareness of the transmission patterns of diseases in the region;
• Integrate and analyze data relating to disease transmission;
• Predict and detect new onsets, outbreaks and patterns of disease transmission; and
• Disseminate alerts and notifications to respective communities of interest.
Appendix III: Mekong Region Geochat Coverage [to date]
Country Network GEOCHAT COVERAGE 96%
Cambodia CamGSM (MobiTel ~ Tango)) TRUE 1
Cambodia Camshin (Shinawatra) DCS 1800 TRUE 1
Cambodia HelloGSM (Telekom Malaysia ~ Casacom) GSM 900 TRUE 1
China China Mobile TRUE 1
China China Telecom TRUE 1
China China Unicom TRUE 1
Lao Milicom (Tigo) TRUE 1
Thailand AIS (Advanced Info Service) TRUE 1
Thailand Digital Phone Co TRUE 1
Thailand TAC (DTAC) TRUE 1
Thailand True Move (Orange) TRUE 1
Vietnam Mobifone (VMS) TRUE 1
Vietnam Viettel TRUE 1
Vietnam Vinaphone (VTS) TRUE 1
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