Evidence of Orientia spp. Endemicity among Severe Infectious Disease Cohorts, Uganda.

At 3 severe infection cohort sites in Uganda, Orientia seropositivity was common. We identified 4 seroconversion cases and 1 PCR-positive case. These results provide serologic and molecular support for Orientia spp. circulating in sub-Saharan Africa, possibly expanding its endemic range. Orientia infections could cause severe illness and hospitalizations in this region.

Metagenomic next generation sequencing of plasma RNA for diagnosis of unexplained, acute febrile illness in Uganda.

Metagenomic next generation metagenomic sequencing (mNGS) has proven to be a useful tool in the diagnosis and identification of novel human pathogens and pathogens not identified on routine clinical microbiologic tests. In this study, we applied mNGS to characterize plasma RNA isolated from 42 study participants with unexplained acute febrile illness (AFI) admitted to tertiary referral hospitals in Mubende and Arua, Uganda. Study participants were selected based on clinical criteria suggestive of viral infection (i.e., thrombocytopenia, leukopenia). The study population had a median age of 28 years (IQR:24 to 38.5) and median platelet count of 114 x103 cells/mm3 (IQR:66,500 to 189,800). An average of 25 million 100 bp reads were generated per sample. We identified strong signals from diverse virus, bacteria, fungi, or parasites in 10 (23.8%) of the study participants. These included well recognized pathogens like Helicobacter pylori, human herpes virus-8, Plasmodium falciparum, Neisseria gonorrhoeae, and Rickettsia conorii. We further confirmed Rickettsia conorii infection, the cause of Mediterranean Spotted Fever (MSF), using PCR assays and Sanger sequencing. mNGS was a useful addition for detection of otherwise undetected pathogens and well-recognized non-pathogens. This is the first report to describe the molecular confirmation of a hospitalized case of MSF in sub-Saharan Africa (SSA). Further studies are needed to determine the utility of mNGS for disease surveillance in similar settings.

Distinct blood inflammatory biomarker clusters stratify host phenotypes during the middle phase of COVID-19.

The associations between clinical phenotypes of coronavirus disease 2019 (COVID-19) and the host inflammatory response during the transition from peak illness to convalescence are not yet well understood. Blood plasma samples were collected from 129 adult SARS-CoV-2 positive inpatient and outpatient participants between April 2020 and January 2021, in a multi-center prospective cohort study at 8 military hospitals across the United States. Plasma inflammatory protein biomarkers were measured in samples from 15 to 28 days post symptom onset. Topological Data Analysis (TDA) was used to identify patterns of inflammation, and associations with peak severity (outpatient, hospitalized, ICU admission or death), Charlson Comorbidity Index (CCI), and body mass index (BMI) were evaluated using logistic regression. The study population (n = 129, 33.3% female, median 41.3 years of age) included 77 outpatient, 31 inpatient, 16 ICU-level, and 5 fatal cases. Three distinct inflammatory biomarker clusters were identified and were associated with significant differences in peak disease severity (p < 0.001), age (p < 0.001), BMI (p < 0.001), and CCI (p = 0.001). Host-biomarker profiles stratified a heterogeneous population of COVID-19 patients during the transition from peak illness to convalescence, and these distinct inflammatory patterns were associated with comorbid disease and severe illness due to COVID-19.