Defining and detecting malaria epidemics in the highlands of western Kenya.
Epidemic detection algorithms are being increasingly recommended for malaria surveillance in sub-Saharan Africa. We present the results of applying three simple epidemic detection techniques to routinely collected longitudinal pediatric malaria admissions data from three health facilities in the highlands of western Kenya in the late 1980s and 1990s. The algorithms tested were chosen because they could be feasibly implemented at the health facility level in sub-Saharan Africa. Assumptions of these techniques about the normal distribution of admissions data and the confidence intervals used to define normal years were also investigated. All techniques identified two "epidemic" years in one of the sites. The untransformed Cullen method with standard confidence intervals detected the two "epidemic" years in the remaining two sites but also triggered many false alarms. The performance of these methods is discussed and comments made about their appropriateness for the highlands of western Kenya.
Hay
Simon I
SI
Department of Zoology, University of Oxford, Oxford, United Kingdom. simon.hay@zoology.ox.ac.uk
Simba
Milka
M
Busolo
Millie
M
Noor
Abdisalan M
AM
Guyatt
Helen L
HL
Ochola
Sam A
SA
Snow
Robert W
RW
D000293:Adolescent; D000465:Algorithms; D000531:Altitude; D000818:Animals; D002648:Child; D002675:Child, Preschool; D016001:Confidence Intervals; D004196:Disease Outbreaks; D004812:Epidemiologic Methods; D006801:Humans; D007223:Infant; D007630:Kenya / Q000453:epidemiology; D016778:Malaria, Falciparum / Q000453:epidemiology*; D010963:Plasmodium falciparum / Q000302:isolation & purification*; D011891:Rain; D012189:Retrospective Studies; D012621:Seasons