ArticlePublic health action2019
Identifying exceptional malaria occurrences in the absence of historical data in South Sudan: a method validation.
Article in Public health action, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
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7 authors.
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Abstract
backgroundDetecting unusual malaria events that may require an operational intervention is challenging, especially in endemic contexts with continuous transmission such as South Sudan. Médecins Sans Frontières (MSF) utilises the classic average plus standard deviation (AV+SD) method for malaria surveillance. This and other available approaches, however, rely on antecedent data, which are often missing.
objectiveTo investigate whether a method using linear regression (LR) over only 8 weeks of retrospective data could be an alternative to AV+SD.
designIn the absence of complete historical malaria data from South Sudan, data from weekly influenza reports from 19 Norwegian counties (2006-2015) were used as a testing data set to compare the performance of the LR and the AV+SD methods. The moving epidemic method was used as the gold standard. Subsequently, the LR method was applied in a case study on malaria occurrence in MSF facilities in South Sudan (2010-2016) to identify malaria events that required a MSF response.
resultsFor the Norwegian influenza data, LR and AV+SD methods did not perform differently (
conclusionThe LR method seems a plausible alternative to the AV+SD method in situations where retrospective data are missing.
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