Victor A Alegana1,2,3, Laurissa Suiyanka4, Peter M Macharia4, Grace Ikahu-Muchangi5, Robert W Snow4,6. 1. Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, P.O. Box 43640-00100, Nairobi, Kenya. valegana@kemri-wellcome.org. 2. Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK. valegana@kemri-wellcome.org. 3. Faculty of Science and Technology, Lancaster University, Lancaster, LAI 4YW, UK. valegana@kemri-wellcome.org. 4. Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, P.O. Box 43640-00100, Nairobi, Kenya. 5. National Malaria Control Programme, Ministry of Health, P.O Box 30016-00100, Nairobi, Kenya. 6. Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, OX3 7LJ, UK.
Abstract
BACKGROUND: There is an increasing need for finer spatial resolution data on malaria risk to provide micro-stratification to guide sub-national strategic plans. Here, spatial-statistical techniques are used to exploit routine data to depict sub-national heterogeneities in test positivity rate (TPR) for malaria among patients attending health facilities in Kenya. METHODS: Routine data from health facilities (n = 1804) representing all ages over 24 months (2018-2019) were assembled across 8 counties (62 sub-counties) in Western Kenya. Statistical model-based approaches were used to quantify heterogeneities in TPR and uncertainty at fine spatial resolution adjusting for missingness, population distribution, spatial data structure, month, and type of health facility. RESULTS: The overall monthly reporting rate was 78.7% (IQR 75.0-100.0) and public-based health facilities were more likely than private facilities to report ≥ 12 months (OR 5.7, 95% CI 4.3-7.5). There was marked heterogeneity in population-weighted TPR with sub-counties in the north of the lake-endemic region exhibiting the highest rates (exceedance probability > 70% with 90% certainty) where approximately 2.7 million (28.5%) people reside. At micro-level the lowest rates were in 14 sub-counties (exceedance probability < 30% with 90% certainty) where approximately 2.2 million (23.1%) people lived and indoor residual spraying had been conducted since 2017. CONCLUSION: The value of routine health data on TPR can be enhanced when adjusting for underlying population and spatial structures of the data, highlighting small-scale heterogeneities in malaria risk often masked in broad national stratifications. Future research should aim at relating these heterogeneities in TPR with traditional community-level prevalence to improve tailoring malaria control activities at sub-national levels.
BACKGROUND: There is an increasing need for finer spatial resolution data on malaria risk to provide micro-stratification to guide sub-national strategic plans. Here, spatial-statistical techniques are used to exploit routine data to depict sub-national heterogeneities in test positivity rate (TPR) for malaria among patients attending health facilities in Kenya. METHODS: Routine data from health facilities (n = 1804) representing all ages over 24 months (2018-2019) were assembled across 8 counties (62 sub-counties) in Western Kenya. Statistical model-based approaches were used to quantify heterogeneities in TPR and uncertainty at fine spatial resolution adjusting for missingness, population distribution, spatial data structure, month, and type of health facility. RESULTS: The overall monthly reporting rate was 78.7% (IQR 75.0-100.0) and public-based health facilities were more likely than private facilities to report ≥ 12 months (OR 5.7, 95% CI 4.3-7.5). There was marked heterogeneity in population-weighted TPR with sub-counties in the north of the lake-endemic region exhibiting the highest rates (exceedance probability > 70% with 90% certainty) where approximately 2.7 million (28.5%) people reside. At micro-level the lowest rates were in 14 sub-counties (exceedance probability < 30% with 90% certainty) where approximately 2.2 million (23.1%) people lived and indoor residual spraying had been conducted since 2017. CONCLUSION: The value of routine health data on TPR can be enhanced when adjusting for underlying population and spatial structures of the data, highlighting small-scale heterogeneities in malaria risk often masked in broad national stratifications. Future research should aim at relating these heterogeneities in TPR with traditional community-level prevalence to improve tailoring malaria control activities at sub-national levels.
Entities:
Keywords:
Malaria; Routine data; Test positivity rate
Authors: Robi M Okara; Marianne E Sinka; Noboru Minakawa; Charles M Mbogo; Simon I Hay; Robert W Snow Journal: Malar J Date: 2010-03-04 Impact factor: 2.979
Authors: Joseph Maina; Paul O Ouma; Peter M Macharia; Victor A Alegana; Benard Mitto; Ibrahima Socé Fall; Abdisalan M Noor; Robert W Snow; Emelda A Okiro Journal: Sci Data Date: 2019-07-25 Impact factor: 6.444