The burden of malaria in Sudan: incidence, mortality and disability – adjusted life – years

Abstract Background Estimating the burden of malaria in Sudan is important for evidence-based planning of malaria control. Estimates of malaria burden in terms of DALYs (Disability Adjusted Life Years) were not developed locally. This study synthesized information from different sources to calculate...

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Bibliographic Details
Published in:Malaria Journal
Main Authors: Malik Elfatih M, Abdalla Safa I, Ali Kamil M
Format: Article in Journal/Newspaper
Language:English
Published: BMC 2007
Subjects:
Online Access:https://doi.org/10.1186/1475-2875-6-97
https://doaj.org/article/3df5ef7288ad4e4e865cd0a8724d0d76
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Summary:Abstract Background Estimating the burden of malaria in Sudan is important for evidence-based planning of malaria control. Estimates of malaria burden in terms of DALYs (Disability Adjusted Life Years) were not developed locally. This study synthesized information from different sources to calculate malaria incidence, mortality and DALYs lost in Sudan in 2002. Methods A search for local studies and reports providing epidemiological data on malaria in Sudan was conducted. Preliminary estimates of incidence rate, case fatality rate and mortality rate were developed from the data found. The preliminary estimates were processed in the disease modelling computer software, DisMod II, to produce internally consistent mortality and incidence rates, which were used to calculate DALYs lost due to malaria. Results Malaria incidence in Sudan was estimated to be about 9 million episodes in 2002 and the number of deaths due to malaria was about 44,000. 2,877,000 DALYs were lost in Sudan in 2002 due to malaria mortality, episodes, anaemia and neurological sequelae. Children under five years of age had the highest burden. Males had the highest incidence and mortality, but females lost more DALYs. Conclusion Formal health system data underestimated malaria burden. The burden estimates can be useful in informing decision making, although uncertainty around them needs to be quantified. Epidemiological research is needed to fill data gaps and update the estimates.