IDENTIFIABILITY OF INFECTION MODEL PARAMETERS EARLY IN AN EPIDEMIC.

It is known that the parameters in the deterministic and stochastic SEIR epidemic models are structurally identifiable. For example, from knowledge of the infected population time series I(t) during the entire epidemic, the parameters can be successfully estimated. In this article we observe that estimation will fail in practice if only infected case data during the early part of the epidemic (prepeak) is available. This fact can be explained using a well-known phenomenon called dynamical compensation. We use this concept to derive an unidentifiability manifold in the parameter space of SEIR that consists of parameters indistinguishable from I(t) early in the epidemic. Thus, identifiability depends on the extent of the system trajectory that is available for observation. Although the existence of the unidentifiability manifold obstructs the ability to exactly determine the parameters, we suggest that it may be useful for uncertainty quantification purposes. A variant of SEIR recently proposed for COVID-19 modeling is also analyzed, and an analogous unidentifiability surface is derived.

mirTarRnaSeq: An R/Bioconductor Statistical Package for miRNA-mRNA Target Identification and Interaction Analysis.

We introduce mirTarRnaSeq, an R/Bioconductor package for quantitative assessment of miRNA-mRNA relationships within sample cohorts. mirTarRnaSeq is a statistical package to explore predicted or pre-hypothesized miRNA-mRNA relationships following target prediction.We present two use cases applying mirTarRnaSeq. First, to identify miRNA targets, we examined EBV miRNAs for interaction with human and virus transcriptomes of stomach adenocarcinoma. This revealed enrichment of mRNA targets highly expressed in CD105+ endothelial cells, monocytes, CD4+ T cells, NK cells, CD19+ B cells, and CD34 cells. Next, to investigate miRNA-mRNA relationships in SARS-CoV-2 (COVID-19) infection across time, we used paired miRNA and RNA sequenced datasets of SARS-CoV-2 infected lung epithelial cells across three time points (4, 12, and 24 hours post-infection). mirTarRnaSeq identified evidence for human miRNAs targeting cytokine signaling and neutrophil regulation immune pathways from 4 to 24 hours after SARS-CoV-2 infection. Confirming the clinical relevance of these predictions, three of the immune specific mRNA-miRNA relationships identified in human lung epithelial cells after SARS-CoV-2 infection were also observed to be differentially expressed in blood from patients with COVID-19. Overall, mirTarRnaSeq is a robust tool that can address a wide-range of biological questions providing improved prediction of miRNA-mRNA interactions.

Cytomegalovirus infections in infants in Uganda: Newborn-mother pairs, neonates with sepsis, and infants with hydrocephalus.

OBJECTIVES: To estimate the prevalence of cytomegalovirus (CMV) infections among newborn-mother pairs, neonates with sepsis, and infants with hydrocephalus in Uganda. DESIGN AND METHODS: Three populations-newborn-mother pairs, neonates with sepsis, and infants (≤3 months) with nonpostinfectious (NPIH) or postinfectious (PIH) hydrocephalus-were evaluated for CMV infection at 3 medical centers in Uganda. Quantitative PCR (qPCR) was used to characterize the prevalence of CMV. RESULTS: The overall CMV prevalence in 2498 samples across all groups was 9%. In newborn-mother pairs, there was a 3% prevalence of cord blood CMV positivity and 33% prevalence of maternal vaginal shedding. In neonates with clinical sepsis, there was a 2% CMV prevalence. Maternal HIV seropositivity (adjusted odds ratio [aOR] 25.20; 95% confidence interval [CI] 4.43-134.26; p = 0.0001), residence in eastern Uganda (aOR 11.06; 95% CI 2.30-76.18; p = 0.003), maternal age <25 years (aOR 4.54; 95% CI 1.40-19.29; p = 0.02), and increasing neonatal age (aOR 1.08 for each day older; 95% CI 1.00-1.16; p = 0.05), were associated risk factors for CMV in neonates with clinical sepsis. We found a 2-fold higher maternal vaginal shedding in eastern (45%) vs western (22%) Uganda during parturition (n = 22/49 vs 11/50, the Fisher exact test; p = 0.02). In infants with PIH, the prevalence in blood was 24% and in infants with NPIH, it was 20%. CMV was present in the cerebrospinal fluid (CSF) of 13% of infants with PIH compared with 0.5% of infants with NPIH (n = 26/205 vs 1/194, p < 0.0001). CONCLUSIONS: Our findings highlight that congenital and postnatal CMV prevalence is substantial in this African setting, and the long-term consequences are uncharacterized.

Pan-African evolution of within- and between-country COVID-19 dynamics.

The coronavirus disease 2019 (COVID-19) pandemic is heterogeneous throughout Africa and threatening millions of lives. Surveillance and short-term modeling forecasts are critical to provide timely information for decisions on control strategies. We created a strategy that helps predict the country-level case occurrences based on cases within or external to a country throughout the entire African continent, parameterized by socioeconomic and geoeconomic variations and the lagged effects of social policy and meteorological history. We observed the effect of the Human Development Index, containment policies, testing capacity, specific humidity, temperature, and landlocked status of countries on the local within-country and external between-country transmission. One-week forecasts of case numbers from the model were driven by the quality of the reported data. Seeking equitable behavioral and social interventions, balanced with coordinated country-specific strategies in infection suppression, should be a continental priority to control the COVID-19 pandemic in Africa.