Entire expressed peripheral blood transcriptome in pediatric severe malarial anemia.

This study on severe malarial anemia (SMA: Hb < 6.0 g/dL), a leading global cause of childhood morbidity and mortality, compares the entire expressed whole blood host transcriptome between Kenyan children (3-48 mos.) with non-SMA (Hb ≥ 6.0 g/dL, n = 39) and SMA (n = 18). Differential expression analyses reveal 1403 up-regulated and 279 down-regulated transcripts in SMA, signifying impairments in host inflammasome activation, cell death, and innate immune and cellular stress responses. Immune cell profiling shows decreased memory responses, antigen presentation, and immediate pathogen clearance, suggesting an immature/improperly regulated immune response in SMA. Module repertoire analysis of blood-specific gene signatures identifies up-regulation of erythroid genes, enhanced neutrophil activation, and impaired inflammatory responses in SMA. Enrichment analyses converge on disruptions in cellular homeostasis and regulatory pathways for the ubiquitin-proteasome system, autophagy, and heme metabolism. Pathway analyses highlight activation in response to hypoxic conditions [Hypoxia Inducible Factor (HIF)-1 target and Reactive Oxygen Species (ROS) signaling] as a central theme in SMA. These signaling pathways are also top-ranking in protein abundance measures and a Ugandan SMA cohort with available transcriptomic data. Targeted RNA-Seq validation shows strong concordance with our entire expressed transcriptome data. These findings identify key molecular themes in SMA pathogenesis, offering potential targets for new malaria therapies.

Estimating multiplicity of infection, allele frequencies, and prevalences accounting for incomplete data.

BACKGROUND: Molecular surveillance of infectious diseases allows the monitoring of pathogens beyond the granularity of traditional epidemiological approaches and is well-established for some of the most relevant infectious diseases such as malaria. The presence of genetically distinct pathogenic variants within an infection, referred to as multiplicity of infection (MOI) or complexity of infection (COI) is common in malaria and similar infectious diseases. It is an important metric that scales with transmission intensities, potentially affects the clinical pathogenesis, and a confounding factor when monitoring the frequency and prevalence of pathogenic variants. Several statistical methods exist to estimate MOI and the frequency distribution of pathogen variants. However, a common problem is the quality of the underlying molecular data. If molecular assays fail not randomly, it is likely to underestimate MOI and the prevalence of pathogen variants. METHODS AND FINDINGS: A statistical model is introduced, which explicitly addresses data quality, by assuming a probability by which a pathogen variant remains undetected in a molecular assay. This is different from the assumption of missing at random, for which a molecular assay either performs perfectly or fails completely. The method is applicable to a single molecular marker and allows to estimate allele-frequency spectra, the distribution of MOI, and the probability of variants to remain undetected (incomplete information). Based on the statistical model, expressions for the prevalence of pathogen variants are derived and differences between frequency and prevalence are discussed. The usual desirable asymptotic properties of the maximum-likelihood estimator (MLE) are established by rewriting the model into an exponential family. The MLE has promising finite sample properties in terms of bias and variance. The covariance matrix of the estimator is close to the Cramér-Rao lower bound (inverse Fisher information). Importantly, the estimator's variance is larger than that of a similar method which disregards incomplete information, but its bias is smaller. CONCLUSIONS: Although the model introduced here has convenient properties, in terms of the mean squared error it does not outperform a simple standard method that neglects missing information. Thus, the new method is recommendable only for data sets in which the molecular assays produced poor-quality results. This will be particularly true if the model is extended to accommodate information from multiple molecular markers at the same time, and incomplete information at one or more markers leads to a strong depletion of sample size.

Repurposing FDA-approved drugs to target malaria through inhibition of dihydrofolate reductase in the folate biosynthesis pathway: A prospective approach.

Dihydrofolate reductase (DHFR) is a ubiquitous enzyme that regulates the biosynthesis of tetrahydrofolate among various species of Plasmodium parasite. It is a validated target of the antifolate drug pyrimethamine (Pyr) in Plasmodium falciparum (Pf), but its clinical efficacy has been hampered due to the emergence of drug resistance. This has made the attempt to screen Food & Drug Administration-approved drugs against wild- and mutant PfDHFR by employing an in-silico pipeline to identify potent candidates. The current study has followed a virtual screening approach for identifying potential DHFR inhibitors from DrugBank database, based on a structure similarity search of candidates, followed by absorption, distribution, metabolism, and excretion estimation. The screened drugs were subjected to various parameters like docking, molecular mechanics with generalized born and surface area solvation calculations, and molecular simulations. We have thus identified two potential drug candidates, duloxetine and guanethidine, which can be repurposed to be tested for their efficacy against wild type and drug resistant falciparum malaria.

Antimicrobial stewardship capacity and antibiotic utilisation practices in the Cape Coast Teaching Hospital, Ghana: A point prevalence survey study.

INTRODUCTION: Antimicrobial resistance (AMR) is a global threat that necessitates coordinated strategies to improve antibiotic prescribing and reduce AMR. A key activity is ascertaining current prescribing patterns in hospitals to identify targets for quality improvement programmes. METHODS: The World Health Organisation point prevalence survey methodology was used to assess antibiotic prescribing in the Cape Coast Teaching Hospital. All core variables identified by the methodology were recorded. RESULTS: A total of 78.8% (82/104) patients were prescribed at least one antibiotic, with the majority from adult surgical wards (52.14%). Significantly longer hospital stays were associated with patients who underwent surgery (p = 0.0423). "Access" antibiotics dominated total prescriptions (63.8%, 132/207) with ceftriaxone, cefuroxime, and ciprofloxacin being the most prescribed "Watch" antibiotics. The most common indications were for medical prophylaxis (59.8%, 49/82) and surgical prophylaxis (46.3%, 38/82). Over one-third of surgical prophylaxis (34.2%, 13/38) indications extended beyond one day. There was moderate documentation of reasons for antibiotic treatment in patient notes (65.9%, 54/82), and targeted therapy after samples were taken for antimicrobial susceptibility testing (41.7%, 10/24). Guideline compliance was low (25%) where available. CONCLUSIONS: There was high use of antibiotics within the hospital which needs addressing. Identified quality targets include developing surgical prophylaxis guidelines, reviewing "Watch" antibiotic prescribing, and assessing antibiotic durations for patients on two or more antibiotics. Organizational-level deficiencies were also identified that need addressing to help instigate ASPs. These can be addressed by developing local prescribing protocols and antibiotic stewardship policies in this hospital and wider in Ghana and across Africa.

Low prevalence of antimalarial-resistance mutations in India during 2014-15: Impact of combining first-line therapy with primaquine.

BACKGROUND: Antimalarial drug resistance surveillance and containment are crucial for countries aiming to eliminate malaria. Monitoring resistance evolution through studies before and after treatment policy changes is crucial. METHOD: A total of 939 P. falciparum-positive blood samples were collected between 2014 and 2015 across ten sites in India, categorized into four geographic clusters. PCR-amplified products were sequenced to identify point mutations at drug-resistance-conferring genes (Pfdhfr, Pfdhps, Pfmdr1, Pfk13). RESULT: Triple Pfdhfr mutants were found only in northeast India bordering Myanmar, while the wildtype was dominant in central India. Pfdhps wildtypes were prevalent in all areas, and no double mutants were found. Except in Northwest India, Pfmdr1 wildtype was dominant in all clusters. Nonsynonymous double mutations were only found in northwest India. Only synonymous mutations occurred in Pfk13. These were found in Central India at low frequency. The pattern of linkage disequilibrium and principal component analysis reflects low pressure for drug resistance and heterogeneity between the geographic clusters. CONCLUSION: Resistance levels were highest in Northeast India, close to the Myanmar border, where resistance is common. Primaquine has been widely used as a gametocidal and schizonticidal drug, has likely contributed to maintaining low drug resistance levels and preventing strong selection for resistance.

Human NCR3 gene variants rs2736191 and rs11575837 alter longitudinal risk for development of pediatric malaria episodes and severe malarial anemia.

BACKGROUND: Plasmodium falciparum malaria is a leading cause of pediatric morbidity and mortality in holoendemic transmission areas. Severe malarial anemia [SMA, hemoglobin (Hb) < 5.0 g/dL in children] is the most common clinical manifestation of severe malaria in such regions. Although innate immune response genes are known to influence the development of SMA, the role of natural killer (NK) cells in malaria pathogenesis remains largely undefined. As such, we examined the impact of genetic variation in the gene encoding a primary NK cell receptor, natural cytotoxicity-triggering receptor 3 (NCR3), on the occurrence of malaria and SMA episodes over time. METHODS: Susceptibility to malaria, SMA, and all-cause mortality was determined in carriers of NCR3 genetic variants (i.e., rs2736191:C > G and rs11575837:C > T) and their haplotypes. The prospective observational study was conducted over a 36 mos. follow-up period in a cohort of children (n = 1,515, aged 1.9-40 mos.) residing in a holoendemic P. falciparum transmission region, Siaya, Kenya. RESULTS: Poisson regression modeling, controlling for anemia-promoting covariates, revealed a significantly increased risk of malaria in carriers of the homozygous mutant allele genotype (TT) for rs11575837 after multiple test correction [Incidence rate ratio (IRR) = 1.540, 95% CI = 1.114-2.129, P = 0.009]. Increased risk of SMA was observed for rs2736191 in children who inherited the CG genotype (IRR = 1.269, 95% CI = 1.009-1.597, P = 0.041) and in the additive model (presence of 1 or 2 copies) (IRR = 1.198, 95% CI = 1.030-1.393, P = 0.019), but was not significant after multiple test correction. Modeling of the haplotypes revealed that the CC haplotype had a significant additive effect for protection against SMA (i.e., reduced risk for development of SMA) after multiple test correction (IRR = 0.823, 95% CI = 0.711-0.952, P = 0.009). Although increased susceptibility to SMA was present in carriers of the GC haplotype (IRR = 1.276, 95% CI = 1.030-1.581, P = 0.026) with an additive effect (IRR = 1.182, 95% CI = 1.018-1.372, P = 0.029), the results did not remain significant after multiple test correction. None of the NCR3 genotypes or haplotypes were associated with all-cause mortality. CONCLUSIONS: Variation in NCR3 alters susceptibility to malaria and SMA during the acquisition of naturally-acquired malarial immunity. These results highlight the importance of NK cells in the innate immune response to malaria.

Disproportionate impact of COVID-19 severity and mortality on hospitalized American Indian/Alaska Native patients.

Epidemiological data across the United States of America illustrate health disparities in COVID-19 infection, hospitalization, and mortality by race/ethnicity. However, limited information is available from prospective observational studies in hospitalized patients, particularly for American Indian or Alaska Native (AI/AN) populations. Here, we present risk factors associated with severe COVID-19 and mortality in patients (4/2020-12/2021, n = 475) at the University of New Mexico Hospital. Data were collected on patient demographics, infection duration, laboratory measures, comorbidities, treatment(s), major clinical events, and in-hospital mortality. Severe disease was defined by COVID-related intensive care unit requirements and/or death. The cohort was stratified by self-reported race/ethnicity: AI/AN (30.7%), Hispanic (47.0%), non-Hispanic White (NHW, 18.5%), and Other (4.0%, not included in statistical comparisons). Despite similar timing of infection and comparable comorbidities, admission characteristics for AI/AN patients included younger age (P = 0.02), higher invasive mechanical ventilation requirements (P = 0.0001), and laboratory values indicative of more severe disease. Throughout hospitalization, the AI/AN group also experienced elevated invasive mechanical ventilation (P < 0.0001), shock (P = 0.01), encephalopathy (P = 0.02), and severe COVID-19 (P = 0.0002), consistent with longer hospitalization (P < 0.0001). Self-reported AI/AN race/ethnicity emerged as the highest risk factor for severe COVID-19 (OR = 3.19; 95% CI = 1.70-6.01; P = 0.0003) and was a predictor of in-hospital mortality (OR = 2.35; 95% CI = 1.12-4.92; P = 0.02). Results from this study highlight the disproportionate impact of COVID-19 on hospitalized AI/AN patients, who experienced more severe illness and associated mortality, compared to Hispanic and NHW patients, even when accounting for symptom onset and comorbid conditions. These findings underscore the need for interventions and resources to address health disparities in the COVID-19 pandemic.

Entire Expressed Peripheral Blood Transcriptome in Pediatric Severe Malarial Anemia.

This study on severe malarial anemia (SMA: Hb < 6.0 g/dL), a leading global cause of childhood morbidity and mortality, analyzed the entire expressed transcriptome in whole blood from children with non-SMA (Hb ≥ 6.0 g/dL, n = 41) and SMA (n = 25). Analyses revealed 3,420 up-regulated and 3,442 down-regulated transcripts, signifying impairments in host inflammasome activation, cell death, innate immune responses, and cellular stress responses in SMA. Immune cell profiling showed a decreased antigenic and immune priming response in children with SMA, favoring polarization toward cellular proliferation and repair. Enrichment analysis further identified altered neutrophil and autophagy-related processes, consistent with neutrophil degranulation and altered ubiquitination and proteasome degradation. Pathway analyses highlighted SMA-related alterations in cellular homeostasis, signaling, response to environmental cues, and cellular and immune stress responses. Validation with a qRT-PCR array showed strong concordance with the sequencing data. These findings identify key molecular themes in SMA pathogenesis, providing potential targets for new malaria therapies.

A flexible age-dependent, spatially-stratified predictive model for the spread of COVID-19, accounting for multiple viral variants and vaccines.

BACKGROUND: After COVID-19 vaccines received approval, vaccination campaigns were launched worldwide. Initially, these were characterized by a shortage of vaccine supply, and specific risk groups were prioritized. Once supply was guaranteed and vaccination coverage saturated, the focus shifted from risk groups to anti-vaxxers, the under-aged population, and regions of low coverage. At the same time, hopes to reach herd immunity by vaccination campaigns were put into perspective by the emergence and spread of more contagious and aggressive viral variants. Particularly, concerns were raised that not all vaccines protect against the new-emerging variants. The objective of this study is to introduce a predictive model to quantify the effect of vaccination campaigns on the spread of SARS-CoV-2 viral variants. METHODS AND FINDINGS: The predictive model introduced here is a comprehensive extension of the one underlying the pandemic preparedness tool CovidSim 2.0 (http://covidsim.eu/). The model is age and spatially stratified, incorporates a finite (but arbitrary) number of different viral variants, and incorporates different vaccine products. The vaccines are allowed to differ in their vaccination schedule, vaccination rates, the onset of vaccination campaigns, and their effectiveness. These factors are also age and/or location dependent. Moreover, the effectiveness and the immunizing effect of vaccines are assumed to depend on the interaction of a given vaccine and viral variant. Importantly, vaccines are not assumed to immunize perfectly. Individuals can be immunized completely, only partially, or fail to be immunized against one or many viral variants. Not all individuals in the population are vaccinable. The model is formulated as a high-dimensional system of differential equations, which is implemented efficiently in the programming language Julia. As an example, the model was parameterized to reflect the epidemic situation in Germany until November 2021 and future dynamics of the epidemic under different interventions were predicted. In particular, without tightening contact reductions, a strong epidemic wave is predicted during December 2021 and January 2022. Provided the dynamics of the epidemic in Germany, in late 2021 administration of full-dose vaccination to all eligible individuals (e.g. by mandatory vaccination) would be too late to have a strong effect on reducing the number of infections in the fourth wave in Germany. However, it would reduce mortality. An emergency brake, i.e., an incidence-based stepwise lockdown, would be efficient to reduce the number of infections and mortality. Furthermore, to specifically account for mobility between regions, the model was applied to two German provinces of particular interest: Saxony, which currently has the lowest vaccine rollout in Germany and high incidence, and Schleswig-Holstein, which has high vaccine rollout and low incidence. CONCLUSIONS: A highly sophisticated and flexible but easy-to-parameterize model for the ongoing COVID-19 pandemic is introduced. The model is capable of providing useful predictions for the COVID-19 pandemic, and hence provides a relevant tool for epidemic decision-making. The model can be adjusted to any country, and the predictions can be used to derive the demand for hospital or ICU capacities.

Predicting the combined effects of case isolation, safe funeral practices, and contact tracing during Ebola virus disease outbreaks.

BACKGROUND: The recent outbreaks of Ebola virus disease (EVD) in Uganda and the Marburg virus disease (MVD) in Ghana reflect a persisting threat of Filoviridae to the global health community. Characteristic of Filoviridae are not just their high case fatality rates, but also that corpses are highly contagious and prone to cause infections in the absence of appropriate precautions. Vaccines against the most virulent Ebolavirus species, the Zaire ebolavirus (ZEBOV) are approved. However, there exists no approved vaccine or treatment against the Sudan ebolavirus (SUDV) which causes the current outbreak of EVD. Hence, the control of the outbreak relies on case isolation, safe funeral practices, and contact tracing. So far, the effectiveness of these control measures was studied only separately by epidemiological models, while the impact of their interaction is unclear. METHODS AND FINDINGS: To sustain decision making in public health-emergency management, we introduce a predictive model to study the interaction of case isolation, safe funeral practices, and contact tracing. The model is a complex extension of an SEIR-type model, and serves as an epidemic preparedness tool. The model considers different phases of the EVD infections, the possibility of infections being treated in isolation (if appropriately diagnosed), in hospital (if not properly diagnosed), or at home (if the infected do not present to hospital for whatever reason). It is assumed that the corpses of those who died in isolation are buried with proper safety measures, while those who die outside isolation might be buried unsafely, such that transmission can occur during the funeral. Furthermore, the contacts of individuals in isolation will be traced. Based on parameter estimates from the scientific literature, the model suggests that proper diagnosis and hence isolation of cases has the highest impact in reducing the size of the outbreak. However, the combination of case isolation and safe funeral practices alone are insufficient to fully contain the epidemic under plausible parameters. This changes if these measures are combined with contact tracing. In addition, shortening the time to successfully trace back contacts contribute substantially to contain the outbreak. CONCLUSIONS: In the absence of an approved vaccine and treatment, EVD management by proper and fast diagnostics in combination with epidemic awareness are fundamental. Awareness will particularly facilitate contact tracing and safe funeral practices. Moreover, proper and fast diagnostics are a major determinant of case isolation. The model introduced here is not just applicable to EVD, but also to other viral hemorrhagic fevers such as the MVD or the Lassa fever.

Screening of potential antiplasmodial agents targeting cysteine protease-Falcipain 2: a computational pipeline.

The spread of antimalarial drug resistance is a substantial challenge in achieving global malaria elimination. Consequently, the identification of novel therapeutic candidates is a global health priority. Malaria parasite necessitates hemoglobin degradation for its survival, which is mediated by Falcipain 2 (FP2), a promising antimalarial target. In particular, FP2 is a key enzyme in the erythrocytic stage of the parasite's life cycle. Here, we report the screening of approved drugs listed in DrugBank using a computational pipeline that includes drug-likeness, toxicity assessments, oral toxicity evaluation, oral bioavailability, docking analysis, maximum common substructure (MCS) and molecular dynamics (MD) Simulations analysis to identify capable FP2 inhibitors, which are hence potential antiplasmodial agents. A total of 45 drugs were identified, which have positive drug-likeness, no toxic features and good bioavailability. Among these, six drugs showed good binding affinity towards FP2 compared to E64, an epoxide known to inhibit FP2. Notably, two of them, Cefalotin and Cefoxitin, shared the highest MCS with E64, which suggests that they possess similar biological activity as E64. In an investigation using MD for 100 ns, Cefalotin and Cefoxitin showed adequate protein compactness as well as satisfactory complex stability. Overall, these computational approach findings can be applied for designing and developing specific inhibitors or new antimalarial agents for the treatment of malaria infections.Communicated by Ramaswamy H. Sarma.

Evolutionary genetics of malaria.

Many standard-textbook population-genetic results apply to a wide range of species. Sometimes, however, population-genetic models and principles need to be tailored to a particular species. This is particularly true for malaria, which next to tuberculosis and HIV/AIDS ranks among the economically most relevant infectious diseases. Importantly, malaria is not one disease-five human-pathogenic species of Plasmodium exist. P. falciparum is not only the most severe form of human malaria, but it also causes the majority of infections. The second most relevant species, P. vivax, is already considered a neglected disease in several endemic areas. All human-pathogenic species have distinct characteristics that are not only crucial for control and eradication efforts, but also for the population-genetics of the disease. This is particularly true in the context of selection. Namely, fitness is determined by so-called fitness components, which are determined by the parasites live-history, which differs between malaria species. The presence of hypnozoites, i.e., dormant liver-stage parasites, which can cause disease relapses, is a distinct feature of P. vivax and P. ovale sp. In P. malariae inactivated blood-stage parasites can cause a recrudescence years after the infection was clinically cured. To properly describe population-genetic processes, such as the spread of anti-malarial drug resistance, these features must be accounted for appropriately. Here, we introduce and extend a population-genetic framework for the evolutionary dynamics of malaria, which applies to all human-pathogenic malaria species. The model focuses on, but is not limited to, the spread of drug resistance. The framework elucidates how the presence of dormant liver stage or inactivated blood stage parasites that act like seed banks delay evolutionary processes. It is shown that, contrary to standard population-genetic theory, the process of selection and recombination cannot be decoupled in malaria. Furthermore, we discuss the connection between haplotype frequencies, haplotype prevalence, transmission dynamics, and relapses or recrudescence in malaria.

Nonsynonymous amino acid changes in the α-chain of complement component 5 influence longitudinal susceptibility to Plasmodium falciparum infections and severe malarial anemia in kenyan children.

Background: Severe malarial anemia (SMA; Hb < 5.0 g/dl) is a leading cause of childhood morbidity and mortality in holoendemic Plasmodium falciparum transmission regions such as western Kenya. Methods: We investigated the relationship between two novel complement component 5 (C5) missense mutations [rs17216529:C>T, p(Val145Ile) and rs17610:C>T, p(Ser1310Asn)] and longitudinal outcomes of malaria in a cohort of Kenyan children (under 60 mos, n = 1,546). Molecular modeling was used to investigate the impact of the amino acid transitions on the C5 protein structure. Results: Prediction of the wild-type and mutant C5 protein structures did not reveal major changes to the overall structure. However, based on the position of the variants, subtle differences could impact on the stability of C5b. The influence of the C5 genotypes/haplotypes on the number of malaria and SMA episodes over 36 months was determined by Poisson regression modeling. Genotypic analyses revealed that inheritance of the homozygous mutant (TT) for rs17216529:C>T enhanced the risk for both malaria (incidence rate ratio, IRR = 1.144, 95%CI: 1.059-1.236, p = 0.001) and SMA (IRR = 1.627, 95%CI: 1.201-2.204, p = 0.002). In the haplotypic model, carriers of TC had increased risk of malaria (IRR = 1.068, 95%CI: 1.017-1.122, p = 0.009), while carriers of both wild-type alleles (CC) were protected against SMA (IRR = 0.679, 95%CI: 0.542-0.850, p = 0.001). Conclusion: Collectively, these findings show that the selected C5 missense mutations influence the longitudinal risk of malaria and SMA in immune-naïve children exposed to holoendemic P. falciparum transmission through a mechanism that remains to be defined.

Genetic variation in CSF2 (5q31.1) is associated with longitudinal susceptibility to pediatric malaria, severe malarial anemia, and all-cause mortality in a high-burden malaria and HIV region of Kenya.

Plasmodium falciparum infections remain among the leading causes of morbidity and mortality in holoendemic transmission areas. Located within region 5q31.1, the colony-stimulating factor 2 gene (CSF2) encodes granulocyte-macrophage colony-stimulating factor (GM-CSF), a hematopoietic growth factor that mediates host immune responses. Since the effect of CSF2 variation on malaria pathogenesis remains unreported, we investigated the impact of two genetic variants in the 5q31.1 gene region flanking CSF2:g-7032 G > A (rs168681:G > A) and CSF2:g.64544T > C (rs246835:T > C) on the rate and timing of malaria and severe malarial anemia (SMA, Hb < 5.0 g/dL) episodes over 36 months of follow-up. Children (n = 1654, aged 2-70 months) were recruited from a holoendemic P. falciparum transmission area of western Kenya. Decreased incidence rate ratio (IRR) for malaria was conferred by inheritance of the CSF2:g.64544 TC genotype (P = 0.0277) and CSF2 AC/GC diplotype (P = 0.0015). Increased IRR for malaria was observed in carriers of the CSF2 AT/GC diplotype (P = 0.0237), while the inheritance of the CSF2 AT haplotype increased the IRR for SMA (P = 0.0166). A model estimating the longitudinal risk of malaria showed decreased hazard rates among CSF2 AC haplotype carriers (P = 0.0045). Investigation of all-cause mortality revealed that inheritance of the GA genotype at CSF2:g-7032 increased the risk of mortality (P = 0.0315). Higher risk of SMA and all-cause mortality were observed in younger children (P < 0.0001 and P = 0.0015), HIV-1(+) individuals (P < 0.0001 and P < 0.0001), and carriers of HbSS (P = 0.0342 and P = 0.0019). Results from this holoendemic P. falciparum area show that variation in gene region 5q31.1 influences susceptibility to malaria, SMA, and mortality, as does age, HIV-1 status, and inheritance of HbSS.

Investigating the impact of multiple feeding attempts on mosquito dynamics via mathematical models.

A deterministic differential equation model for the dynamics of terrestrial forms of mosquito populations is studied. The model assesses the impact of multiple probing attempts by mosquitoes that quest for blood within human populations by including a waiting class for mosquitoes that failed a blood feeding attempt. The equations are derived based on the idea that the reproductive cycle of the mosquito can be viewed as a set of alternating egg laying and blood feeding outcomes realised on a directed path called the gonotrophic cycle pathway. There exists a threshold parameter, the basic offspring number for mosquitoes, whose nature is affected by the way we interpret the transitions involving the different classes on the gonotrophic cycle path. The trivial steady state for the system, which always exists, can be globally asymptomatically stable whenever the threshold parameter is less than unity. The non-trivial steady state, when it exists, is stable for a range of values of the threshold parameter but can also be driven to instability via a Hopf bifurcation. The model's output reveals that the waiting class mosquitoes do contribute positively to sustain mosquito populations as well as increase their interactions with humans via increased frequency and initial amplitude of oscillations. We conclude that to understand human-mosquito interactions, it is informative to consider multiple probing attempts; known to occur when mosquitoes quest for blood meals within human populations.

Elevated SARS-CoV-2 in peripheral blood and increased COVID-19 severity in American Indians/Alaska Natives.

Epidemiological data across the United States show health disparities in COVID-19 infection, hospitalization, and mortality by race/ethnicity. While the association between elevated SARS-CoV-2 viral loads (VLs) (i.e. upper respiratory tract (URT) and peripheral blood (PB)) and increased COVID-19 severity has been reported, data remain largely unavailable for some disproportionately impacted racial/ethnic groups, particularly for American Indian or Alaska Native (AI/AN) populations. As such, we determined the relationship between SARS-CoV-2 VL dynamics and disease severity in a diverse cohort of hospitalized patients. Results presented here are for study participants (n = 94, ages 21-88 years) enrolled in a prospective observational study between May and October 2020 who had SARS-CoV-2 viral clades 20A, C, and G. Based on self-reported race/ethnicity and sample size distribution, the cohort was stratified into two groups: (AI/AN, n = 43) and all other races/ethnicities combined (non-AI/AN, n = 51). SARS-CoV-2 VLs were quantified in the URT and PB on days 0-3, 6, 9, and 14. The strongest predictor of severe COVID-19 in the study population was the mean VL in PB (OR = 3.34; P = 2.00 × 10-4). The AI/AN group had the following: (1) comparable co-morbidities and admission laboratory values, yet more severe COVID-19 (OR = 4.81; P = 0.014); (2) a 2.1 longer duration of hospital stay (P = 0.023); and (3) higher initial and cumulative PB VLs during severe disease (P = 0.025). Moreover, self-reported race/ethnicity as AI/AN was the strongest predictor of elevated PB VLs (ß = 1.08; P = 6.00 × 10-4) and detection of SARS-CoV-2 in PB (hazard ratio = 3.58; P = 0.004). The findings presented here suggest a strong relationship between PB VL (magnitude and frequency) and severe COVID-19, particularly for the AI/AN group.