02826nas a2200361 4500000000100000008004100001260001000042653001900052653001300071653001200084653001200096653002400108100001300132700001500145700001300160700001200173700001400185700001200199700001400211700001500225700001100240700001300251700001500264700001500279700001300294700001200307245014100319856005200460300001200512490000700524520191900531022001402450 2023 d bLepra10aGeneral Energy10aEthiopia10aleprosy10aMapping10ahigh leprosy burden1 aFekadu L1 aLambert SM1 aKebede T1 aKumsa A1 aKetema KH1 aAbere W1 aTadesse T1 aNigussie S1 aLema T1 aKasang C1 aFastenau A1 aStützle S1 aBaraki A1 aLetta T00aMapping leprosy in Ethiopia: Capture and analysis of district and health facility data to identify and map high leprosy burden districts uhttps://leprosyreview.org/article/94/4/20-20324 a264-2750 v943 a

Introduction: Leprosy is considered an important public health problem due to its morbidity and socioeconomic impact. The new case notification in Ethiopia has remained static for decades. National leprosy data are reported regionally, without considering the tendency of case clustering under low prevalence situations. To identify high endemic areas and populations at risk, leprosy mapping at different levels of administrative units of the country (by zones, district and health facilities) was conducted, thereby ensuring the provision of necessary leprosy control activities as well as the appropriate utilization of limited resources.

Methodology: Data available nationally for the five-year period 2008–2012 were first analyzed. Then data were collected directly from leprosy registers held in health facilities of all woreda (districts) in Ethiopia for a six-year period (2008–2013). The data were gathered by district TB-Leprosy experts under close supervision of the respective Zonal health departments and Regional health bureaux.

Results: Direct data from 92% of the 837 districts in the country were collected. The findings showed pockets of ‘high endemicity’ with a leprosy prevalence rate >1/10,000 population in 93 districts, making up 54% of all leprosy cases in the country.

Conclusions: These findings obtained from disaggregated data will contribute to reducing the burden of leprosy in the 93 “hotspot” areas by helping the leprosy control program to institute locally adjusted, intensive, and targeted leprosy interventions. Further studies will be needed to assess pilots of adjusted responses, which include active case finding in selected areas, contact tracing, geographical distribution of cases, environmental studies, and education campaigns.

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