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This tool should be explored further within the context of malaria classification for epidemic-prone areas of Africa.
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Based on the aggregate mean PfPR2 10, districts were then classified using a modification of the classical malaria endemicity classification.
Using the malaria endemicity classification proposed by Hay et al. (2008), Zone 1 experiences unstable transmission, Zone 2 is divided roughly equally between unstable and moderate stable transmission, Zone 3 is a mixture of moderate and intense stable transmission, and Zones 4 and 5 are primarily areas of intense transmission (Table 1).
Malaria endemicity classifications of low (≤ 5%), moderate (6-39%), and high (≥ 40%) based on malaria prevalence data at baseline or the control group in children 2-10 years of age were based on the mapping criteria proposed by the Malaria Atlas Project (Hay 2008).
Furthermore, the hierarchical importance of these factors in influencing highland malaria is analysed using classification and regression trees [11], [12] (CART).
Utilizing both SR and PR in children 2 10 years, a classification of malaria endemicity was proposed by WHO and revised by Metselaar et al[7]: hypoendemic if SR 2 10 or PR 2 10 is <10%, mesoendemic if SR 2 10 or PR 2 10 is 10 50%, hyperendemic if SR 2 10 or PR 2 10 is 51 75% and holoendemic if SR 2 10 or PR in children <1year is >75%.
To understand the impact of this level of incidence, it is interesting to compare it with World Health Organization (WHO) classification for malaria distribution.
This study appears to be of high clinical relevance since the automated classification of malaria parasite is useful for mass screening and drug selection for treatment of the infection.
In addition to meeting the IMCI classification of severe malaria, most cases were also identified as malaria at a health facility.
While it is difficult to estimate the incidence of true malaria-attributable mortality, it is likely that the mis-classification of malaria deaths will be internally consistent within a study, and thus analysis of percentage age-distributions will suffer less from such errors than would cross-site comparisons.
Here, we have adapted the risk classifications of malaria that are currently defined in the Sudan national malaria strategic plan to suit the ambitions of the National Malaria Control Program NMCPP).
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