surveillance of emerging diseases and networks
DESCRIPTION
How networks support emerging diseases surveillance.TRANSCRIPT
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
Plan
Introduction Definition and concepts Examples Rapid assessment
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
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), …
Health-related Events under Surveillance
Detection Decision Notification Action
International Health Regulations (IHR) 2005 decisioninstrument (simplified from annex 2 of IHR).
Introduction -3
Definitions and concepts
Surveillance Emerging disease Network Systems theory
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
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
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”
Definitions and concepts:Emerging disease
Human-animal contacts
Virus-to-human adaptation: influenza viruses
Virus-to-vector adaptation: chikungunya (Reunion Island, 2005: Aedes aegyptiAedes 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
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?!
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)
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
Examples
SISEA/Pasteur
MDBS
TB
Christian, CID, 2004
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
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Network .... and sub-network
International Pasteur Institutes Network – 32 members on 5 continents
Examples: SISEA/Pasteur -2NODES
= MODEL
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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
Vertices: case definition of SARI adopted in Vietnam and used to report the cases:
≤ 05 y.o. > 05 y.o.
Cough or breathing difficultyAND
One of the following:TachypneaChest indrawingGeneral 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 difficultyAND
One of the following:≥ 30 respirations/minNew infiltrate on chest X-rayInability to speak full sentencesUse of accessory respiratory musclesArterial O2 saturation ≤ 92% on air (no oxygen therapy)
Onset of symptoms ≤ 7 days
Examples: SISEA/Pasteur -4
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:
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,B11%
Enterovirus9%
HMPV1%
Para influenza virus4%
Mixed2%
Negative73%
ALRI Virology tested, 2009N=139
Examples: SISEA/Pasteur -6
Improving surveillance in Cambodia – 1 (Vong S and al.):Implementation of the ALRI surveillance activities in April,2007: on Nov 2009, 3177patients enrolled. In depth clinical classification and data validation (Pr. Mayaud andal., Paris).
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Extra-respiratory pathologies
Pneumonia Pleural infections
Other respiratory infections
Viro and bacterio : # positive results / # samples tested (%)
BK : # positive / # cases (%)
Examples: SISEA/Pasteur -7
Examples: SISEA/Pasteur -8
Findings/outcomes: Capacity strenghtening
Equipment, consumables HR Network integration and partnerships
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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
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;
Examples: MDBS (Mekong Basin Disease Surveillance) -2
NODES
Examples: MDBS (Mekong Basin Disease Surveillance) -3 VERTICES
Examples: MDBS (Mekong Basin Disease Surveillance) -4
FINDINGS
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)
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
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
Rapid assessment
SWOT: Strengths Weaknesses Opportunities Threats
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
Rapid assessment:Weaknesses
1- Quality of the system: ex. Lack of completeness:
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.
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
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?
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
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Adding vertices to a network: Multiplies the number of interactions Increases sensitivity and sensibility
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Timeliness, accuracy and adaptability to correct quickly what Science bet before A(H1N1)sw-o regarding a possible pandemic:
Conclusions & prospects -2
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.pdf
Public Health Surveillance: A Historical Review with a Focus on HIV/AIDS. Michael A. Stoto. RAND Health, 2003. See http://www.rand.org/
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