Rwanda is a malaria endemic country and a focal point for emerging Plasmodium falciparum artemisinin partial resistance (ART-R). While Demographic and Health Surveys (DHS) provide both national and province-level representative data, malaria testing in Rwandan DHS (RDHS) studies has been limited to a subset of adult women and children under 5 years using RDT and/or microscopy. Recent work using ultra-sensitive quantitative real time PCR on residual dried blood spots (DBS) from the 2014-15 RDHS revealed a significantly higher P. falciparum prevalence than detected by standard DHS diagnostics. Building on this study, we analyzed 7,127 adult DBS samples collected for HIV testing in the 2019-20 RDHS to generate updated prevalence measures. We found a national P. falciparum infection prevalence of 7.7% (95%CI [6.8%, 8.7%]), with predominantly low-density infections (median parasitemia: 7.3 parasites/uL). We assessed covariates of P. falciparum malaria infection, identifying male sex, lower household wealth, lower educational achievement, and residence at lower elevation as significant predictors. Notably, national P. falciparum prevalence decreased 53% relative to the parallel 2014-15 RDHS study, despite reports of increasing ART-R-associated mutations in Rwanda. These findings demonstrate the utility of ultra-sensitive molecular surveillance, and suggest that national malaria control efforts have substantially reduced malaria burden in Rwanda even amid rising antimalarial parasite prevalence. Subsequent studies on this data set will provide measures of minor Plasmodium species prevalence, as well as temporospatial analysis of antimalarial resistance markers in P. falciparum positive samples.
Assessing nurses’ attitudes toward artificial intelligence in Kazakhstan: psychometric validation of a nine-item scale
BackgroundArtificial intelligence (AI) is increasingly integrated into healthcare, yet the attitudes and knowledge of nurses, who are the key mediators of AI implementation, remain underexplored.


