Integrating malaria surveillance with climate data for outbreak detection and forecasting: the EPIDEMIA system
- PMID: 28231803
- PMCID: PMC5324298
- DOI: 10.1186/s12936-017-1735-x
Integrating malaria surveillance with climate data for outbreak detection and forecasting: the EPIDEMIA system
Abstract
Background: Early 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.
Methods: The 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.
Results: The 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.
Conclusions: Successful 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.
Keywords: Early detection; Early warning; Environmental data; Forecasting; Malaria informatics system; Remote sensing; Risk map; Surveillance.
Figures




Similar articles
-
Improving epidemic malaria planning, preparedness and response in Southern Africa. Report on the 1st Southern African Regional Epidemic Outlook Forum, Harare, Zimbabwe, 26-29 September, 2004.Malar J. 2004 Oct 22;3:37. doi: 10.1186/1475-2875-3-37. Malar J. 2004. PMID: 15500683 Free PMC article.
-
Analysing trends and forecasting malaria epidemics in Madagascar using a sentinel surveillance network: a web-based application.Malar J. 2017 Feb 13;16(1):72. doi: 10.1186/s12936-017-1728-9. Malar J. 2017. PMID: 28193215 Free PMC article.
-
An online operational rainfall-monitoring resource for epidemic malaria early warning systems in Africa.Malar J. 2005 Jan 21;4:6. doi: 10.1186/1475-2875-4-6. Malar J. 2005. PMID: 15663795 Free PMC article.
-
Forecasting and prevention of epidemic malaria: new perspectives on an old problem.Parassitologia. 1999 Sep;41(1-3):439-48. Parassitologia. 1999. PMID: 10697900 Review.
-
The development of Malaria Early Warning Systems for Africa.Trends Parasitol. 2001 Sep;17(9):438-45. doi: 10.1016/s1471-4922(01)02077-3. Trends Parasitol. 2001. PMID: 11530356 Review.
Cited by
-
A genetic algorithm for identifying spatially-varying environmental drivers in a malaria time series model.Environ Model Softw. 2019 Sep;119:275-284. doi: 10.1016/j.envsoft.2019.06.010. Epub 2019 Jun 24. Environ Model Softw. 2019. PMID: 33814961 Free PMC article.
-
Comparing malaria early detection methods in a declining transmission setting in northwestern Ethiopia.BMC Public Health. 2021 Apr 24;21(1):788. doi: 10.1186/s12889-021-10850-5. BMC Public Health. 2021. PMID: 33894764 Free PMC article.
-
The Arbovirus Mapping and Prediction (ArboMAP) system for West Nile virus forecasting.JAMIA Open. 2023 Dec 21;7(1):ooad110. doi: 10.1093/jamiaopen/ooad110. eCollection 2024 Apr. JAMIA Open. 2023. PMID: 38186743 Free PMC article.
-
Unexplored Opportunities: Use of Climate- and Weather-Driven Early Warning Systems to Reduce the Burden of Infectious Diseases.Curr Environ Health Rep. 2018 Dec;5(4):430-438. doi: 10.1007/s40572-018-0221-0. Curr Environ Health Rep. 2018. PMID: 30350265 Review.
-
Evaluation of Remotely Sensed and Interpolated Environmental Datasets for Vector-Borne Disease Monitoring Using In Situ Observations Over the Amhara Region, Ethiopia.Sensors (Basel). 2020 Feb 28;20(5):1316. doi: 10.3390/s20051316. Sensors (Basel). 2020. PMID: 32121264 Free PMC article.
References
-
- Maes P, Harries AD, Van den Bergh R, Noor A, Snow RW, Tayler-Smith K, et al. Can timely vector control interventions triggered by atypical environmental conditions prevent malaria epidemics? A case-study from Wajir County, Kenya. PLoS ONE. 2014;9:e92386. doi: 10.1371/journal.pone.0092386. - DOI - PMC - PubMed
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical