Klebsiella pneumoniae is a globally significant opportunistic pathogen causing healthcare-associated and community-acquired infections. This study examined the epidemiology and the distribution of resistance and virulence genes in clinical K. pneumoniae strains in Kenya. A total of 89 K. pneumoniae isolates were collected over six years from five counties in Kenya and were analyzed using whole-genome sequencing and bioinformatics. These isolates were obtained from community-acquired (62/89) and healthcare-associated infections (21/89), and from the hospital environment (6/89). Genetic analysis revealed the presence of bla_NDM-1 and bla_OXA-181 carbapenemase genes and the armA and rmtF genes known to confer pan-aminoglycoside resistance. The most abundant extended-spectrum beta-lactamase genes identified were bla_CTX-M-15 (36/89), bla_TEM (35/89), and bla_OXA (18/89)_. In addition, one isolate had a mobile colistin resistance gene (mcr-8). Fluoroquinolone resistance-conferring mutations in gyrA and parC genes were also observed. The most notable virulence factors were those associated with hyper-virulence (rmpA/A2 and magA), yersiniabactin (ybt), salmochelin (iro), and aerobactin (iuc and iutA). A total of 38 distinct sequence types were identified, including known global lineages ST14, ST15, ST147, and ST307, and a regional clone ST17 implicated in regional outbreaks. In addition, this study genetically characterized two potential hypervirulent isolates and two community-acquired ST147 high-risk clones that contained carbapenemase genes, yersiniabactin, and other multidrug resistance genes. These results demonstrate that the resistome and virulome of Kenyan clinical and hospital environmental K. pneumoniae isolates are diverse. The reservoir of high-risk clones capable of spreading resistance, and virulence factors have the potential to cause unmanageable infection outbreaks with high morbidity and mortality.

The emergence and spread of drug resistance threatens malaria control in Uganda. This study reports new data on key polymorphisms associated with antimalarial drug sensitivity at 32 malaria reference centers in Uganda in 2023 and 2024. Samples were collected from patients aged >6 months presenting with uncomplicated falciparum malaria, sequenced using the MAD ⁴ HatTeR panel and Illumina platforms. Multiple validated or candidate K13 mutations associated with artemisinin partial resistance were detected at ≥20% prevalence at one or more sites across multiple timepoints. The K13 mutations A675V and C469Y predominated in northern Uganda, P441L was most common in western Uganda, and R561H and C469F were confined to southwestern Uganda. After rapid increases in earlier years, prevalences of K13 mutations plateaued at most sites, with A675V, C469Y and P441L reaching maximum site prevalences of 40%, 58%, and 46%, respectively. Prevalence of the chloroquine resistance marker CRT K76T was generally low but increased substantially at three sites in northwestern Uganda, rising to 38% at the last timepoint, with CRT H97L, newly reported in Africa, following a similar trend. The antifolate resistance quintuple mutant haplotype remained highly prevalent nationwide. In addition, DHPS A581G and DHFR I164L, markers of higher-level antifolate resistance, were most common in southwestern Uganda with prevalences up to 64% and 76%, respectively; DHFR I164L also expanded into central and eastern regions. These results highlight continued geographic heterogeneity and underscore the need for continued, nationwide molecular surveillance to guide treatment and chemoprevention policies.

The emergence and spread of drug resistance threaten malaria control in Uganda. This study reports new data on key polymorphisms associated with antimalarial drug sensitivity at 32 malaria reference centers in Uganda in 2023 and 2024. Ten thousand thirty samples were collected from patients aged >6 months presenting with uncomplicated falciparum malaria and sequenced using the MAD ⁴ HatTeR panel and Illumina platforms; of these, 8,518 passed quality control and were analyzed. Multiple validated or candidate K13 mutations associated with artemisinin partial resistance were detected at ≥20% prevalence at one or more sites across multiple timepoints. The K13 mutations A675V and C469Y predominated in northern Uganda, P441L was most common in western Uganda, and R561H and C469F were confined to southwestern Uganda. After rapid increases in earlier years, prevalences of K13 mutations plateaued at most sites, with A675V, C469Y, and P441L reaching maximum site prevalences of 40%, 58%, and 46%, respectively. Prevalence of the chloroquine resistance marker CRT K76T was generally low but increased substantially at three sites in northwestern Uganda, rising to 38% at the last timepoint, with CRT H97L, newly reported in Africa, following a similar trend. The antifolate resistance quintuple mutant haplotype remained highly prevalent nationwide. In addition, DHPS A581G and DHFR I164L, markers of higher-level antifolate resistance, were most common in southwestern Uganda with prevalences up to 64% and 76%, respectively; DHFR I164L also expanded into central and eastern regions. These results highlight continued geographic heterogeneity and underscore the need for continued, nationwide molecular surveillance to guide treatment and chemoprevention policies.

Genetic metrics derived from Plasmodium falciparum infections offer a potential complement to conventional malaria surveillance by utilizing features of pa

Background: Genetic metrics derived from Plasmodium falciparum infections offer a potential complement to conventional malaria surveillance by utilizing features of parasite diversity and relatedness to estimate transmission intensity. However, the performance of molecular metrics to predict epidemiologic metrics across a wide range of transmission settings remains understudied. Methods: Dried blood spots from 3563 symptomatic malaria cases were collected from 26 sentinel health facilities across Uganda during two collections in 2023. Amplicon deep sequencing of 165 polyallelic microhaplotypes was performed using MAD⁴HatTeR. Within-host diversity metrics (complexity of infection (COI), effective complexity of infection (eCOI), percent polyclonality, within-host relatedness) and between-host relatedness metrics were calculated. Associations with prevalence and recent incidence were evaluated using correlation and regression analyses, and estimation accuracy was examined using nested grouped cross-validation. Results: Marked geographic heterogeneity in malaria burden was evident across sites; parasite prevalence ranged from 5.0% to 49.23% in Round 1, while incidence ranged from 91-1062 cases per 1,000 person-years (PY) in Round 1 and 33-1667 cases per 1,000 PY in Round 2. COI and eCOI were strongly and consistently positively associated with parasite prevalence. The proportion of highly related infection pairs was negatively associated with both prevalence and incidence and was the genetic metric most consistently associated with incidence. Nested grouped cross-validation identified single-predictor models using COI or eCOI as optimal for estimating prevalence, yielding a pooled cross-validated correlation of r = 0.79. Models estimating incidence showed weaker performance, with models incorporating both diversity and relatedness metrics achieving a pooled correlation of r = 0.37. Conclusions: Microhaplotype-based metrics of within-host diversity, particularly COI and eCOI, reliably reflected spatial variation in malaria prevalence across Uganda, while between-host relatedness provided complementary information and was the strongest predictor of incidence. These findings indicate that parasite genomic metrics derived from polyallelic microhaplotypes can capture broad differences in transmission intensity reflected by parasite prevalence, but may have more limited ability to predict incidence. Integration of genomic metrics with harmonized epidemiologic data and expanded sampling of asymptomatic infections will be important next steps to understand the potential utility of parasite genetic metrics for malaria surveillance and subnational stratification.

Malaria transmission in southwestern Uganda is low, but persists despite control efforts. Identifying whether infections are locally sustained or imported by travelers is critical for guiding interventions. We integrated epidemiologic surveillance with parasite genomics to characterize imported malaria episodes at three health facilities in southwestern Uganda. Between January 2023 and June 2024, we enrolled microscopy-confirmed malaria cases at three health facilities, Maziba and Muko (very low transmission) and Kamwezi (low-to-moderate transmission), administered travel history questionnaires, and collected dried blood spots for genotyping. 348 Plasmodium falciparum infections were genotyped using MAD ⁴ HatTeR, a multiplex amplicon sequencing panel targeting 165 diversity markers and 38 drug resistance loci. Complexity of infection and pairwise relatedness were estimated using MOIRE and Dcifer, respectively. Plasmotrack, a transmission network framework, was used to infer transmission networks and importation rates. Amongst malaria cases, travel was common in Maziba (87%) and Muko (96%) but infrequent in Kamwezi (12%). Most travel in Maziba and Muko was from high-transmission regions in northern and eastern Uganda. Parasites in Maziba and Muko exhibited higher within-host diversity and lower within-site relatedness compared to those in Kamwezi, with the proportion of significant related infection pairs substantially lower in Maziba (0.59%) and Muko (0.17%) than in Kamwezi (6.36%). Transmission network inference identified most infections in Maziba and Muko as imported, with the majority of inferred secondary transmission linked to recent travelers. In contrast, Kamwezi showed multiple highly related clusters, indicating sustained local transmission. Validated markers of artemisinin resistance (K13 P441L and R561H) were more prevalent in Kamwezi. Malaria in Maziba and Muko was driven largely by importation from other parts of Uganda, while local transmission predominated in Kamwezi. Tailored interventions addressing travel-associated risks and local transmission, supported by travel histories and genetic data will be valuable to advance malaria elimination in this region.