Integrating malaria surveillance with climate data for outbreak detection and forecasting: the EPIDEMIA system

Malaria Journal

Research

Mastewal Lake¹  Teklehaymanot Gebrehiwot¹  Yi Liu²  Gebeyaw T. Kassa³  Geoffrey M. Henebry⁴  Michael C. Wimberly⁴  Christopher L. Merkord⁴  Estifanos Bayabil⁵  Abere Mihretie⁵  Worku Awoke⁶ 

[1] Amhara National Regional State Health Bureau, Bahir Dar, Ethiopia;Department of Electrical Engineering and Computer Science, South Dakota State University, Brookings, SD, USA;Gamby College of Medical Science, Bahir Dar, Ethiopia;Geospatial Sciences Center of Excellence, South Dakota State University, Brookings, SD, USA;Health, Development, and Anti-Malaria Association, Addis Ababa, Ethiopia;School of Public Health, Bahir Dar University, Bahir Dar, Ethiopia;

关键词: Malaria informatics system;    Surveillance;    Remote sensing;    Environmental data;    Risk map;    Early detection;    Early warning;    Forecasting;   

DOI  :  10.1186/s12936-017-1735-x

 received in 2016-10-15, accepted in 2017-02-11,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundEarly indication of an emerging malaria epidemic can provide an opportunity for proactive interventions. Challenges to the identification of nascent malaria epidemics include obtaining recent epidemiological surveillance data, spatially and temporally harmonizing this information with timely data on environmental precursors, applying models for early detection and early warning, and communicating results to public health officials. Automated web-based informatics systems can provide a solution to these problems, but their implementation in real-world settings has been limited.MethodsThe Epidemic Prognosis Incorporating Disease and Environmental Monitoring for Integrated Assessment (EPIDEMIA) computer system was designed and implemented to integrate disease surveillance with environmental monitoring in support of operational malaria forecasting in the Amhara region of Ethiopia. A co-design workshop was held with computer scientists, epidemiological modelers, and public health partners to develop an initial list of system requirements. Subsequent updates to the system were based on feedback obtained from system evaluation workshops and assessments conducted by a steering committee of users in the public health sector.ResultsThe system integrated epidemiological data uploaded weekly by the Amhara Regional Health Bureau with remotely-sensed environmental data freely available from online archives. Environmental data were acquired and processed automatically by the EASTWeb software program. Additional software was developed to implement a public health interface for data upload and download, harmonize the epidemiological and environmental data into a unified database, automatically update time series forecasting models, and generate formatted reports. Reporting features included district-level control charts and maps summarizing epidemiological indicators of emerging malaria outbreaks, environmental risk factors, and forecasts of future malaria risk.ConclusionsSuccessful implementation and use of EPIDEMIA is an important step forward in the use of epidemiological and environmental informatics systems for malaria surveillance. Developing software to automate the workflow steps while remaining robust to continual changes in the input data streams was a key technical challenge. Continual stakeholder involvement throughout design, implementation, and operation has created a strong enabling environment that will facilitate the ongoing development, application, and testing of the system.

【 授权许可】

CC BY   
© The Author(s) 2017

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