This abstract has been accepted at the 2024 DHIS2 Annual Conference
EARLY WARNING ALERT RESPONSE SYSTEM
Web based Early Warning and Response System (EWARS) for climate sensitive diseases How can we predict (forecast) outbreaks? Using Alarm Indicators (These are epidemiological/ entomological/ metereological variables which are able to predict an outbreak) 1. Potential alarm indicators: vector presence or density, climate (temperature, rainfall, humidity), epidemiological (probable cases, change of sero type, % sero positivity of samples), outbreak in neighboring district, others 2. Alarm Threshold: the line (threshold) above which the alarm indicator converts into an alarm signal. range of 0 – 1. Usually around 0.12 (where it gives the highest sensitivities and PPVs). 3. Alarm Signal – any week when one or more alarm indicator(s) exceed the respective alarm threshold for at least 2 or 3 weeks Information Technology: 1. Providing evidence how integrating EWARS with local data hub (e.g. DHIS2) can have significant implications 2. EWARS is best when linked to one source of data rather than to multiple sources 3. Ideally having the meteorological (and entomological) data to be linked to one central data hub to feed in and out data to EWARS Methodology : 1. Malawi is piloting EWARS in four districts 2. Dashboard I: Managed by central level Identified a FP for EWARS at national level Work in collaboration with Health and Climate Change national coordinator 3. Dashboard II: Managed by districts 4. Trained a team of 4 health workers in each district 5. Health and Climate change Focal Point 6. IDSR coordinator 7. Environmental Health Officer 8. Health Management Information Officer stakeholders involved: 1. Ministry of Health 2. Department of Climate Change and Meteorological Services 3. Public health institute of Malawi (PHIM) Surveillance 4. Mzuzu University 5. Malawi University of Business and Applied Sciences 6. Association of Environmental Journalists (AEJ) 7. Civil Society Network on Climate Change (CISONEC) 8. Digital Health Department 9. District health managers 10. National health program managers 11. National and District Response team 12. Media institutions Main results/achievement: 1. Acquisition of server where EWARS is installed 2.Signed memorandum of understanding between MoH and DCCMs to access Met. Data 3. Trained 30 health workers on the first version of EWARS from 4 pilot district 4. Identified EWARS Focal Point to oversee the dashboard both at national and district level Methodological concept: The model produces out of sample predicted probabilities of exceeding the outbreak threshold: 1. Weekly predictive probabilities of cases for each district (incidence rate) is first computed from alarm
Primary Author: HENDRICKS MGODIE
Keywords:
EWARS; Disease Surveillance; Sensitivity; Initial Response; Early Response; Late Response; Dash Board 1 & 2; outbreak prediction; Early outbreak detection;
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