Assessment of malaria transmission in Kenya using multilevel logistic regression
The study's multilevel logistic regression model, which includes random effects, identified two SEA-level and eight individual/household risk factors for malaria infection. Thus, increasing the availability of insecticide-treated bed nets is one crucial element that public health policymakers should consider. Furthermore, health planners can organize spatially targeted initiatives to prevent malaria transmission with the help of spatial clustering data.
Authors
- Mohammed Omar Musa Mohammed (ORCID: https://orcid.org/0000-0002-5014-8690)
- Dawit Getnet Ayele (ORCID: https://orcid.org/0000-0002-6499-5698)
- Gemechis A. Wacho
- Ahmed Saied Rahama Abdallah
Institutions
- Prince Sattam Bin Abdulaziz University (SA)
- Office of the Assistant Secretary for Planning and Evaluation (US)
- Universities at Shady Grove (US)
- Adventist HealthCare Shady Grove Medical Center (US)
- University of Business and Technology (SA)
- Shady Grove Fertility Center (US)
Publication Details
- Journal
- Heliyon
- Published
- 2024-10-24
- DOI
- https://doi.org/10.1016/j.heliyon.2024.e39835
- Citations
- 3
- Primary Topic
- Animal Disease Management and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 1.70
Funders
- Prince Sattam bin Abdulaziz University