A WHO-TDR Expert meeting in collaboration with Umeå University Freiburg Institute of Advanced Studies (FRIAS) entitled "Dengue-Zika-Chikungunya early outbreak warning and response" was held in Freiburg on April 5-6, 2017.
Countries endemic for Aedes-borne viral diseases and countries with low-level or no transmission are threatened by outbreaks which are detected late and where the response mechanisms are often inadequate. Early detection of outbreaks poses a challenge, since no universally accepted or proven set of early warning indicators exists. Candidates for triggering a dengue outbreak alert have been defined, but no systematic analyses or validations of these indicators has been found, and at the first stakeholder meeting in June 2012 it was shown that practically no country uses outbreak alerts for an early response.
Within the context of a WHO-TDR-led Research Work Programme to develop a new adaptable model for dengue surveillance and outbreak response, a model dengue outbreak contingency plan has been developed together with WHO Regions and endemic countries (Technical Handbook for dengue surveillance, dengue outbreak prediction/detection and outbreak response; WHO-TDR 2016). Also a retrospective study has been conducted in five endemic countries (Brazil, Mexico, Dominican Republic, Vietnam, Malaysia) on the sensitivity, specificity and predictive value of candidate alert signals for dengue outbreaks, as well as different definitions of what constitutes a dengue outbreak.
The results obtained were discussed and analysed in several WHO Expert meetings. The best performing and most consistent "dengue outbreak definition" was developed and the best performing alarm signals for dengue outbreaks were identified (see Bowman et al. 2016; doi:10.1371).
Based on these findings, a computer-assisted programme was developed to facilitate the practical use of the early warning tool in district health offices. The tool was field tested prospectively for about 18 months in three countries. Subsequently an operational guide for Early Warning and Response Systems (EWARS) for dengue outbreaks was developed and tested. This guide was published on the WHO-TDR website in February 2017.
However, challenges remain regarding: i) how to incorporate emerging Aedes-borne diseases, such as Zika and Chikungunya into the EWARS, ii) how to make use of social media and incorporate other alarm signals in the early warning tool and iii) how to identify risk groups (geographical, social) for priority interventions.
The Umeå team has carried out complementary work in the following areas: forecasting of dengue incidence in time and space-time in relation to disease surveillance and lagged weather conditions; the association of dengue incidence and sea surface temperature (El Niño); mathematical modelling of Aedes vector abundance; Zika & dengue vectorial capacity and transmission potential in relation to weather conditions; mining of indicators of dengue disease transmission; utilising social media as proxies for human mobility; prototyping an information dashboard including forecasts, social media trends, and events posts run as a “cloud” dashboard solution in collaboration with Microsoft; and developing health economic methods to assess economic benefits of responding to early warnings from a health provider perspective.
Please find below the overall objectives of this meeting, the presentation topics and the participants. A further meeting will be held in Sweden in June to develop a new dashboard for decision makers for EWARS and work will then continue on testing and implementing this in the Americas and Asia.
Overall objective: to contribute to the further development of the Early Warning and Response System for outbreaks of Aedes-borne diseases. Specifically:
- To present and discuss the current status of the Early Warning and Response System (EWRS) using the retrospective and prospective study results in Mexico, Brazil, Malaysia and other countries
- To present and discuss the current status of work on i) outbreak warning for Zika and Chikungunya; ii) the use of social media for early outbreak warning; iii) peoples` movements for identifying increased infection risks; iv) demo disease intelligence and visualization dashboard; prediction/forecasts of Aedes abundance
- To discuss the steps towards a joint approach developing a comprehensive EWARS
- The Current status of EWARS for dengue (Prof. Max Petzold, Laith Hussain, Dr. Axel Kroeger);
- Which complementary research is needed? (Dr. Axel Kroeger, Dr. Piero Olliaro);
- Towards alarm signals building on social media (Prof. Joacim Rocklöv, Aditya Ramadona);
- Model options and performance of space-time models for Aedes borne diseases (Prof. Joacim Rocklöv , Aditya Ramadona, Dr. Mikkel Quam);
- Climate resources and time and space scale issues of near real time global data resources (Dr. Angel Muñoz)
- Economic assessment of the impact of Aedes-borne diseases (Eduardo Alfonso)
- A method for evaluating economic benefits of EWARS coupled responses (Dr. Yesim Tozan)
- Modelling of Aedes vector abundance (Dr. Jing Helmersson, Prof. Joacim Rocklöv)
Discussion topics covered:
- The Options on extending alarm signals to other Aedes-borne diseases
- The Identification of high risk areas/groups
- How to get climate data in real time
- Next steps for extending Dengue-EWARS to Zika/Chikungunya
- Next steps towards identification of high risk groups
- Dashboard technique & developments; transfer STATA based To-Do handbook to open access option
- Transfer of Stat scripts to “R” or others.
- Dr. Erika Garcia, Epidemiologist at WHO, Chikungunya and Zika Control, Control of Epidemic Diseases (CED), Pandemic and Epidemic Disease Department
- Dr. Piero Olliaro, Unit Leader at WHO/TDR, Special Programme for Research and Training in Tropical Diseases (TDR), Intervention and Implementation Research Unit
- Pr. Axel Kroeger, Scientist at WHO/TDR and Professor at University of Freiburg
- Pr. Max Petzold, Professor at University of Gothenburg, Sahlgrenska Academy, Centre for Applied Biostatistics
- Assoc. Pr. Joacim Rocklöv, Scientist, Research Group Leader at Umeå University, Unit of Epidemiology and Global Health, Umeå Centre for Global Health Research
Expert Panel Participants:
- Dr. Jing Helmersson, Scientific Researcher at Umeå University, Epidemiology and Global Health Unit, Umeå Centre for Global Health Research- Disease Transmission Modelling Expert
- Dr. Yien-Ling Hii, Scientific Researcher at Umeå University, Epidemiology and Global Health Unit, Umeå Centre for Global Health Research- Early Warning Modelling Expert
- Laith Hussain, PhD Candidate at University of Gothenburg, Sahlgrenska Academy, Centre for Applied Biostatistics- Early Outbreak Warning and Response System Expert
- Prasad Liyanage, Epidemiologist at Sri Lankan Ministry of Health, PhD Candidate at Umeå University, Epidemiology and Global Health Unit, Disease Surveillance and Response Expert
- Dr. Ángel G. Muñoz, Scientific Researcher at Princeton University, Atmospheric and Oceanic Sciences, NOAA/Geophysical Fluid Dynamics Laboratory-Climate Science Expert
- Dr. Mikkel B. Quam, Scientific Researcher at Umeå University, Epidemiology and Global Health Unit, Umeå Centre for Global Health Research- Trans-Border Disease Modelling Expert
- Aditya Ramadona, PhD Candidate at Umeå University, Epidemiology and Global Health Unit –Spatial-Temporal Modeler with Expertise in Social Media Data Mining
- Eric Schlegel, Software Engineer at Microsoft-Open Source Software Development Expert
- Beat Schwegler, Lead Cloud Architect and Coder at Microsoft, Technical Evangelism and Development Team- Cloud Computing and Software Development Expert
- Eduardo Alfonso Sierra, Health Economist at WHO/TDR, Intervention and Implementation Research- Health Economics Expert, Early Outbreak Warning and Response System
- Assoc. Pr. Yesim Tozan, Clinical Associate Professor at New York University, College of Global Public Health- Health Economics Expert, Vector Borne Infectious Tropical Diseases
- Dr. Rafdzah Ahmad Zaki, Lecturer at University of Malaya, Department of Social and Preventive Medicine, Unit of Epidemiology & Biostatistics, Clinical Epidemiology Expert