Final published version
Licence: CC BY: Creative Commons Attribution 4.0 International License
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Using a model-based geostatistical approach to design and analyse the prevalence of schistosomiasis in Kenya
AU - Okoyo, Collins
AU - Minnery, Mark
AU - Orowe, Idah
AU - Owaga, Chrispin
AU - Wambugu, Christin
AU - Olick, Nereah
AU - Hagemann, Jane
AU - Omondi, Wyckliff P.
AU - Gichuki, Paul M.
AU - McCracken, Kate
AU - Montresor, Antonio
AU - Fronterre, Claudio
AU - Diggle, Peter
AU - Mwandawiro, Charles
PY - 2023/11/2
Y1 - 2023/11/2
N2 - Background: Infections caused by both Schistosoma mansoni and Schistosoma haematobium are endemic in Kenya, with over six million children at risk. A national school-based deworming programme was launched in 2012 with the goal of eliminating parasitic worms as a public health problem. This study used a model-based geostatistical (MBG) approach to design and analyse the impact of the programme and inform treatment strategy changes for schistosomiasis (SCH). Methods: A cross-sectional survey of 200 schools across 27 counties of Kenya was utilised. The study design, selection of the schools, and analysis followed the MBG approach, which incorporated historical data on treatment, morbidity, and environmental covariates. Results: The overall SCH prevalence was 5.0% (95% CI 4.9%–5.2%) and was estimated, with a high predictive probability of 0.999, to be between 1% and< 10%. The predictive probabilities at county level revealed county heterogeneity, with that of four counties estimated to be between 0% and< 1%, that of 20 counties estimated to be between 1% and< 10%, that of two counties estimated to be between 10% and< 20%, and that of one county estimated to be between 20% and< 50%. Conclusion: SCH treatment requirements can now be confidently refined based on the World Health Organization’s guidelines. The four counties with prevalences of between 0% and< 1% may consider suspending treatment only in areas (i.e., sub-counties and wards) where the prevalence is< 1%.
AB - Background: Infections caused by both Schistosoma mansoni and Schistosoma haematobium are endemic in Kenya, with over six million children at risk. A national school-based deworming programme was launched in 2012 with the goal of eliminating parasitic worms as a public health problem. This study used a model-based geostatistical (MBG) approach to design and analyse the impact of the programme and inform treatment strategy changes for schistosomiasis (SCH). Methods: A cross-sectional survey of 200 schools across 27 counties of Kenya was utilised. The study design, selection of the schools, and analysis followed the MBG approach, which incorporated historical data on treatment, morbidity, and environmental covariates. Results: The overall SCH prevalence was 5.0% (95% CI 4.9%–5.2%) and was estimated, with a high predictive probability of 0.999, to be between 1% and< 10%. The predictive probabilities at county level revealed county heterogeneity, with that of four counties estimated to be between 0% and< 1%, that of 20 counties estimated to be between 1% and< 10%, that of two counties estimated to be between 10% and< 20%, and that of one county estimated to be between 20% and< 50%. Conclusion: SCH treatment requirements can now be confidently refined based on the World Health Organization’s guidelines. The four counties with prevalences of between 0% and< 1% may consider suspending treatment only in areas (i.e., sub-counties and wards) where the prevalence is< 1%.
KW - Schistosoma haematobium
KW - Schistosoma mansoni
KW - model-based geostatistics
KW - modelling
KW - prevalence
KW - Kenya
KW - national school-based deworming
KW - schistosomiasis
U2 - 10.3389/fitd.2023.1240617
DO - 10.3389/fitd.2023.1240617
M3 - Journal article
VL - 4
JO - Frontiers in Tropical Diseases
JF - Frontiers in Tropical Diseases
SN - 2673-7515
M1 - 1240617
ER -