This document discusses disease surveillance networks and provides examples. It begins by defining key concepts like surveillance, emerging diseases, and networks. It then provides examples of successful surveillance networks, including SISEA/Pasteur in Southeast Asia, the Mekong Basin Disease Surveillance network, and tuberculosis surveillance. These networks improved disease detection and response through established nodes, standardized reporting procedures, and capacity building. The document concludes that interconnected surveillance networks can enhance sensitivity and specificity of disease detection compared to isolated efforts.

1. Surveillance of emerging
diseases and networks: “the
whole is (still) more than its part”
Dr Jean-Jacques BERNATAS, MD (Montpellier), MSc
(DEA Paris 6)
Public Health Specialist
Senior medical advisor, International SOS
Jakarta, Indonesia - 17th December 2010 - Universitas Indonesia, Center for
Research and Integrated Development Tropical Health and Infectious Diseases

2. Plan
 Introduction
 Definition and concepts
 Examples
 Rapid assessment

3. Introduction -1
 Health surveillance is not a new deal:
 14th century: Republic of Venice, Italy. Surveillance of
bubonic plague on ships before disembarkation
 1878, USA: congress authorized Public Health
Services to collect data for detecting “pestilential
diseases” and undertake quarantine measures
 Worldwide smallpox eradication in the 1970’s
succeeded because of an active surveillance of the
new cases
 1980’s: introduction of computers improved data
aggregation and analysis
 1990’s to 2000’s web revolution

4. Introduction -2
 SARS epidemic in 2003 demonstrated the efficiency of a
global surveillance network: GOARN/WHO (created in
2000), and also our global fragility facing new pathogens
 Core of the IHR 2005 and PHEIC
 At the national level: US-CDC (USA), InVS (France), …
 At regional level: ECDC (Europe), MDBS (Mekong
Region), …

5.  Health-related Events
under Surveillance
 Detection Decision
Notification Action
International Health Regulations (IHR)
2005 decision
instrument (simplified from annex 2 of
IHR).
Introduction -3

6. Definitions and concepts
 Surveillance
 Emerging disease
 Network
 Systems theory

7. Definitions and concepts: Surveillance
(1)
 Operational concept: “… process that is used to collect,
manage, analyze, interpret and report information about the status of
specific diseases or their antecedents in a specific population “ (J. W.
Buehler in “Modern Epidemiology”, Rothman &al.)
 Objectives:
 Descriptive epidemiology of health
problems TIME-PLACE-PERSONS
 Monitoring, planning PH interventions:
 Evaluation
 Education and policy
 (Research?): they nourish each other

8. Definitions and concepts: Surveillance
(2)
 Attributes of surveillance (US CDC, 2001):
 Timeliness: depends on the objective of the system. TB:
quarterly reports; Influenza: weekly reports; Ebola or other
hemorrhagic fever: hours.
 Sensitivity: ability to detect an event at interest
 Predictive value: are reported cases really cases? Does it
measure what it aims to measure.
 Representativeness: /target population.
 Data quality: accuracy, completeness.
 Simplicity: time, money wasting; error risk mitigation.
 Flexibility: adaptation to needs and circumstances.
 Acceptability: willing to participate, motivation, perreniality

9. Definitions and concepts:
Emerging disease
 Emergence of a new human pathogen:
 Emergence of human pathogenicity in
commensal human species (S. Aureus
MRSA)
 Interspecies transfer from animals to human:
A(H1N1)so, A(H5N1), HIV, SARS-CoronaV
 Presence of a known human pathogen in new
areas (West-Nile in NYC in 1999 then in all US;
chikungunya in Indian ocean) or dramatic and
sudden extension of pre existing pathogen (DF in
South-East Asia, )
 Emergence of knowledge: identification of a new
pathogen in specific human diseases (HCV in
Egypt, HHV8 and Kaposi sarcoma in Africa):
1918 “Spanish flu”

10. Definitions and concepts:
Emerging disease
 Human-animal contacts
 Virus-to-human adaptation: influenza
viruses
 Virus-to-vector adaptation: chikungunya
(Reunion Island, 2005: Aedes
aegyptiAedes albopictus)
 Climate change
 Movements of population: short-term
(travel) vs. long-term (migration)
perspectives
 Density of population, both human and
animal (animal husbandry)
Weiss RA, Nature Medicine, 2004

11. Definitions and concepts:
Network (“jaringan”?)
 Nodes and vertices (vertex/vertices):
 Topology: description of the relations between
nodes
 Other properties: connectivity, directed vs. non
directed, eccentricity, radius, diameter, coloring
graph
 Why?!

12. Definitions and concepts:
Network (“jaringan”?) -2
 Method for modeling infectious diseases based on
contacts patterns. (How a rumor spread all over
the world or the “Facebook modeling” …)
Fraser, PNAS, 2004
(Christian, CID, 2004)
Stochastic models in opposition with
deterministic models (famous “R0, S/I/R and
differential equations)

13. Definitions and concepts:
System theory
 Interacting entities
 Primary interactions: positive and negative
feedback
 Emerging properties and science of
complexity (Ilya Prigogine).
 Broader framework to conceptualize the
interactions in all organized systems,
including biological and epidemiological ones
 Distributed systems vs. centralized systems

14. Examples
 SISEA/Pasteur
 MDBS
 TB
Christian, CID, 2004

15. Examples: SISEA/Pasteur -1
 Objective: to contribute to the improvement of the detection and handling of
epidemic situations in the region, with 3 components:
 Strengthen national reference laboratories
 Strengthen epidemic detection
 Strengthen outbreak response capacities
at national and regional levels, in collaboration with WHO
 Nodes: healthcare facilities in Vietnam, Laos, China and Cambodia among
Pasteur Institutes International Network in South-East Asia; national health
authorities
 Vertices: monthly reports to national health authorities, and regular
workshops.
 Findings:
 Knowledge of respiratory viruses pattern circulation in SEA,
 Emergence of knowledge: meiloidiosis in Cambodia,
 Alert and disease control: japanese encephalitis in South Vietnam,
 Capacity building and strengthening of national surveillance
institution: skills and procedures

16. 16
Network .... and sub-network
International Pasteur Institutes Network – 32 members on 5 continents
Examples: SISEA/Pasteur -2 NODES
= MODEL

17. 17
Network of laboratories & hospital-based sentinel sites
IPS
- pediatric hospital of Nanxiang
- Guangxi CDCNIHE
- Provincial Hospital of Hai Duong
- District hospital of Cam Giang
- 19 communes
NCLE
- Setthathirath Hospital, Vientiane
- Mahosot Hospital, Vientiane,
- Friendship hospital, Vientiane,
- Luanprabang regional hospital
IPNT
- Provincial Hospital of Binh Dinh
- District Hospital of Phu Cat
IP HCMC
- Ben Tre provincial hospital
- Cu Lao Minh district hospitalIP Cambodia
- Provincial hospital of Takkeo
- Provincial hospital of Kampong Cham
Examples: SISEA/Pasteur -3

18. Vertices: case definition of SARI adopted in Vietnam and used to report the
cases:
≤ 05 y.o. > 05 y.o.
Cough or breathing difficulty
AND
One of the following:
Tachypnea
Chest indrawing
General signs of danger
Onset of symptoms up to and including 7
days
Fever ≥ 38o C (or history of fever)
AND
Cough OR sore throat OR breathing difficulty
AND
One of the following:
≥ 30 respirations/min
New infiltrate on chest X-ray
Inability to speak full sentences
Use of accessory respiratory muscles
Arterial O2 saturation ≤ 92% on air (no
oxygen therapy)
Onset of symptoms ≤ 7 days
Examples: SISEA/Pasteur -4

19. Examples: SISEA/Pasteur -5
 Findings/outcomes:
 Improving surveillance through a better knowledge of
some EIDs: ARI&AES. 2 examples:
 Improving surveillance in Lao PDR
 Improving surveillance in Cambodia:

20. Improving surveillance in Lao PDR:
• Technical assistance in microbiology and epidemiology
• ALRI surveillance, complementary approach to the other
surveillance system implemented (EWORS, EWARN, ILI):
• ILI: 2007 to 2008 : 507 ILI specimens collected → 142 (28 %)
+ve for IAV and IBV, 2009 : 533 specimens collected → 139
(26 %) +ve for Influenza IAV and IVB.
• ALRI: Jul 08 to Oct 09: 222 specimens collected → 26(11.7%)
+ve for IAV and IVB; 24 sputum specimens collected for
bacteriology testing: 11(45.8%) +ve: S. pneumonia, H.
influenza, S. aureus, P. aeruginosa, K. pneumonia (+ C.
albicans)
• Contribution to ILI surveillance
• Strenghtening virology, bacteriology,
epidemiology capacities
• Implementing a new sentinel site in Luanprabang
Influenza A,B
11%
Enterovirus
9%
HMPV
1%
Para influenza
virus
4%
Mixed
2%
Negative
73%
ALRI Virology tested, 2009
N=139
Examples: SISEA/Pasteur -6

21. Improving surveillance in Cambodia – 1 (Vong S and al.):
Implementation of the ALRI surveillance activities in April,2007: on Nov 2009, 3177
patients enrolled. In depth clinical classification and data validation (Pr. Mayaud and
al., Paris).
9,2
6,7
0
19,1
32
28,8
0
15,5
45
3,6
41,3
17,2
0
5
10
15
20
25
30
35
40
45
50
viro
bact
B
K
viro
bact
B
K
viro
bact
B
K
viro
bact
B
K
Percentage%
Extra-respiratory
pathologies
Pneumonia Pleural
infections
Other
respiratory
infections
Viro and bacterio : # positive results / #
samples tested (%)
BK : # positive / # cases (%)
Examples: SISEA/Pasteur -7

22. Examples: SISEA/Pasteur -8
 Findings/outcomes:
 Capacity strenghtening
 Equipment, consumables
 HR
 Network integration and partnerships

23. 23
International Short Course in Biostatistics - REDI centre -
Singapore, November 9-13, 2009.
Capacity strengthening and epidemiology
24 trainees/12 from SISEA and
12 from Indonesia
Daily and final evaluation; very
good input from SISEA trainees
Very good perception by the
trainees
New ties with professionals
coming from Indonesia, and
Singapore
High quality of the collaboration
with REDI and NUS, who are
demanding for other
collaboration in training
Examples: SISEA/Pasteur -9

24. Examples: MDBS (Mekong Basin
Disease Surveillance) -1
 Objective:
 “to strengthen national and Mekong sub-regional
capabilities in disease surveillance and response to
outbreaks of priority diseases, in order that they can be
effectively controlled.”
 Nodes: healthcare facilities involved in cross-boarder activities
 Vertices: weekly reports, training sessions, workshops
 Findings: improved skills and commitment regarding
infectious diseases in this area;

25. Examples: MDBS (Mekong Basin
Disease Surveillance) -2
NODES

26. Examples: MDBS (Mekong Basin
Disease Surveillance) -3 VERTICES

27. Examples: MDBS (Mekong Basin
Disease Surveillance) -4
FINDINGS

28. Examples: TB -1
 Objective: integrative part of DOTS
 Definition: DOTS strategy= Directly Observed Treatment Short-
course strategy
 sustained political commitment
 uninterrupted supply of quality-assured drugs
 access to quality-assured sputum microscopy
 standardized short-course chemotherapy including direct
observation of the treatment at least during the intensive phase
 Recording and reporting system standardized information
system enabling outcome assessment
 objective of the information system:
 Activities evaluation
 Burden disease: reported smear+ cases, prevalence of smear +
pulmonary cases (prevalence survey), tuberculin survey
 And also: HIV co-infections, and drug resistance monitoring
(laboratories network)

29.  Nodes:
 National level: local/regional TB centers; TB laboratories
 International level= NTP
 Vertices:
 Standardized quarterly reports: case report and treatment
outcomes
 Laboratory quality control activities and surveillance of
sensitivity
 Anti TB drugs management &supply
 Is a centralized system:
Examples: TB -2

30.  Findings:
 Monitoring NTP at the global, regional and
national level.
 burden of disease estimation  advocacy for
appropriate funding and policy
 (Re-)emerging diseases: MDR- and XDR-TB
 help to adapt and monitor the response
 Triggers operational research: DOTS
evaluation and implementation according to
specific context and constrains
Examples: TB -3

31. Rapid assessment
 SWOT:
 Strengths
 Weaknesses
 Opportunities
 Threats

32. Rapid assessment:
Strengths
 Distributed systems: “filter-effect”, improving the sensitivity and
specificity:
 A weak signal will be tested through other centres/nodes:
 if confirmed, then amplification= sensitivity ( true +ves)
 +ve feedback
 If not confirmed, then attenuation= specificity ( false –ves)
 -ve feedback
 Multiple identical weak signals will sum in a strong signal
(noise reduction)
 Needs a dense network covering the area at interest
 Feed the curiosity (scientific) and develop the exchanges:
techniques, procedures, quality control,
 Extend the size sample to give more consistency to the findings

33. Rapid assessment:
Weaknesses
1- Quality of the system: ex. Lack of completeness:

34. Rapid assessment:
Weaknesses
2- Appropriate use of data for a comprehensive and
coordinated response in due-time:
 Cross boarder actions not easy to set up: political and
cultural concerns
 Continuity/long-term= sustainability
 Same data may be interpreted differently by the partners,
and may trigger different responses.

35. Rapid assessment:
Opportunities
 IT development: from ancient paper register (TB register) era to
web-based reporting system (TB, MDBS)
 Political and economical development, international cooperation,
necessary in our global village: countries have mutual
advantages to cooperate, both developed and developing
countries
 “Public health emergency of international concern” (PHEIC,
IHR 2005): increasing global threats (SARS, AI, SI, bioterrorism)
and global awareness improved fund raising
 Progress in knowledge (molecular biology) forces us to imagine
new possibilities and increases awareness on the extraordinary
adaptability of the human pathogens to our weapons: objective
tends to cooperate rather than to eradicate

36. Rapid assessment:
Threats
 Multiplication of networks not consistently
interconnected: conflictual information, adverse effect in
term of PH action
 Political and/or economical consequences: is it possible
that neighboring adverse countries share fully sensitive
information (Ex. North Korea/South Korea,
Myanmar/Thailand, China, Japan, …)  limitation of
the global world?
 Sharing biological material: whom do the strains
collected belong to?

37. Conclusions & prospects -1
 The whole is more than its part:
 TB control NP success is to some extend due to a strong and
simple interconnected information system
 Quick response rely on a dense and fluid network: SRAS
y = x2
- x
0
500
1000
1500
2000
2500
3000
3500
4000
0 10 20 30 40 50 60 70
number of vertices
numberofcontacts(fullyconnected)
 Adding vertices to a network:
 Multiplies the number of interactions
 Increases sensitivity and sensibility

38. 38
≠
AND
≠
Timeliness, accuracy and adaptability to correct quickly
what Science bet before A(H1N1)sw-o regarding a
possible pandemic:
Conclusions & prospects -2

39. References
 Modern Infectious Epidemiology, 2nd Ed. Johan Giesecke. 2002,
Arnold
 Modern Epidemiology, 3rd Ed. KJ Rothman, S Greensland, TL
Lash. 2008, Lipicott Williams & Wlkins
 IHR 2005, WHO
 Management of Tuberculosis: A Guide to the Essentials of Good
Clinical Practice , N. Aït-Khaled, E. Alarcón, R. Armengol et al.
6th Ed. International Union Against Tuberculosis and Lung
Disease (The Union), 2010.
 MDBS project,
http://www.mbdsoffice.com/pdf/MBDS_Presentation_Dec2009.p
df
 Public Health Surveillance: A Historical Review with a Focus on
HIV/AIDS. Michael A. Stoto. RAND Health, 2003. See
http://www.rand.org/

40. Acknowledgements
 Universitas Indonesia, Center for Research and Integrated
Development Tropical Health and Infectious Diseases
 Pasteur Institute and International Pasteur Institutes Network:
 Institut Pasteur du Cambodge: Dr Sirenda Vong, Dr Sowath, Dr Laurence Borand, Sophie Goyet, Dr
Philippe Buchy, Dr Bertrand Guillard. Pr Jean-Louis Sarthou,
 NIHE: Pr Nguyen Tran Hien, Dr Nguyen Thi Thuong, Dr. Nguyen Van Duong
 Institut Pasteur Nha Trang: Pr Bui Trong Chien, Dr. Vien Quang Mai, Dr.Trinh Thi Xuan Mai
 Institut Pasteur Ho Chi Minh Ville: Pr Tran Ngoc Huu, Dr.Kien Quoc, Dr. Huong Vu Thi Hu Que
 Institut Pasteur de Shanghai: Dr Wei Wang, Dr Peijun Ren, Dr Jin Zhang, Dr Changgui Dong, Dr Yize Li, Dr
Peng Lu, Dr Vincent Deubel, M. I. Robin
 NCLE: Dr Phengta Vongprachanh, Dr Hansila Phoupaseuth, Dr. Somvay Ongkhammy, Dr Matthida, Dr
Darouny Phonekeo, Dr. Noikaseumsy Sithivong, Dr Thongchanh Sissouk, M. Phayvan, Dr Anne-Charlotte
Sentilhes
 Unité de Coordination : Mme Silvia Ostberg, Dr Roberto Bruzzone (HKU-Pasteur Institute
 Institut Pasteur Paris: Dr Isabelle Catala, Dr Marc Jouan, Dr Arnaud Fontanet, Kathrin Victoir
 REDI centre: Dr Rodney HOFF, Dr. Za Reed, Dr Philippe Cavallier, Mrs. Quake Ai Li
 NUS: Pr. CHIA, Dr. Elizabeth Alderman Jahncke
 And International SOS/AEA company