SARS-CoV-2 variant transition dynamics are associated with vaccination rates, number of co-circulating variants, and convalescent immunity

BACKGROUND

Throughout the COVID-19 pandemic, the SARS-CoV-2 virus has continued to evolve, with new variants outcompeting existing variants and often leading to different dynamics of disease spread.

METHODS

In this paper, we performed a retrospective analysis using longitudinal sequencing data to characterize differences in the speed, calendar timing, and magnitude of 16 SARS-CoV-2 variant waves/transitions for 230 countries and sub-country regions, between October 2020 and January 2023. We then clustered geographic locations in terms of their variant behavior across several Omicron variants, allowing us to identify groups of locations exhibiting similar variant transitions. Finally, we explored relationships between heterogeneity in these variant waves and time-varying factors, including vaccination status of the population, governmental policy, and the number of variants in simultaneous competition.

FINDINGS

This work demonstrates associations between the behavior of an emerging variant and the number of co-circulating variants as well as the demographic context of the population. We also observed an association between high vaccination rates and variant transition dynamics prior to the Mu and Delta variant transitions.

INTERPRETATION

These results suggest the behavior of an emergent variant may be sensitive to the immunologic and demographic context of its location. Additionally, this work represents the most comprehensive characterization of variant transitions globally to date.

FUNDING

Laboratory Directed Research and Development (LDRD), Los Alamos National Laboratory.

Identification of Novel, Replicable Genetic Risk Loci for Suicidal Thoughts and Behaviors Among US Military Veterans

Importance

Suicide is a leading cause of death; however, the molecular genetic basis of suicidal thoughts and behaviors (SITB) remains unknown.

Objective

To identify novel, replicable genomic risk loci for SITB.

Design, Setting, and Participants

This genome-wide association study included 633 778 US military veterans with and without SITB, as identified through electronic health records. GWAS was performed separately by ancestry, controlling for sex, age, and genetic substructure. Cross-ancestry risk loci were identified through meta-analysis. Study enrollment began in 2011 and is ongoing. Data were analyzed from November 2021 to August 2022.

Main Outcome and Measures

SITB.

Results

A total of 633 778 US military veterans were included in the analysis (57 152 [9%] female; 121 118 [19.1%] African ancestry, 8285 [1.3%] Asian ancestry, 452 767 [71.4%] European ancestry, and 51 608 [8.1%] Hispanic ancestry), including 121 211 individuals with SITB (19.1%). Meta-analysis identified more than 200 GWS (P < 5 × 10-8) cross-ancestry risk single-nucleotide variants for SITB concentrated in 7 regions on chromosomes 2, 6, 9, 11, 14, 16, and 18. Top single-nucleotide variants were largely intronic in nature; 5 were independently replicated in ISGC, including rs6557168 in ESR1, rs12808482 in DRD2, rs77641763 in EXD3, rs10671545 in DCC, and rs36006172 in TRAF3. Associations for FBXL19 and AC018880.2 were not replicated. Gene-based analyses implicated 24 additional GWS cross-ancestry risk genes, including FURIN, TSNARE1, and the NCAM1-TTC12-ANKK1-DRD2 gene cluster. Cross-ancestry enrichment analyses revealed significant enrichment for expression in brain and pituitary tissue, synapse and ubiquitination processes, amphetamine addiction, parathyroid hormone synthesis, axon guidance, and dopaminergic pathways. Seven other unique European ancestry-specific GWS loci were identified, 2 of which (POM121L2 and METTL15/LINC02758) were replicated. Two additional GWS ancestry-specific loci were identified within the African ancestry (PET112/GATB) and Hispanic ancestry (intergenic locus on chromosome 4) subsets, both of which were replicated. No GWS loci were identified within the Asian ancestry subset; however, significant enrichment was observed for axon guidance, cyclic adenosine monophosphate signaling, focal adhesion, glutamatergic synapse, and oxytocin signaling pathways across all ancestries. Within the European ancestry subset, genetic correlations (r > 0.75) were observed between the SITB phenotype and a suicide attempt-only phenotype, depression, and posttraumatic stress disorder. Additionally, polygenic risk score analyses revealed that the Million Veteran Program polygenic risk score had nominally significant main effects in 2 independent samples of veterans of European and African ancestry.

Conclusions and Relevance

The findings of this analysis may advance understanding of the molecular genetic basis of SITB and provide evidence for ESR1, DRD2, TRAF3, and DCC as cross-ancestry candidate risk genes. More work is needed to replicate these findings and to determine if and how these genes might impact clinical care.

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.

Common bacterial responses in six ecosystems exposed to 10 years of elevated atmospheric carbon dioxide

Six terrestrial ecosystems in the USA were exposed to elevated atmospheric CO(2) in single or multifactorial experiments for more than a decade to assess potential impacts. We retrospectively assessed soil bacterial community responses in all six-field experiments and found ecosystem-specific and common patterns of soil bacterial community response to elevated CO(2) . Soil bacterial composition differed greatly across the six ecosystems. No common effect of elevated atmospheric CO(2) on bacterial biomass, richness and community composition across all of the ecosystems was identified, although significant responses were detected in individual ecosystems. The most striking common trend across the sites was a decrease of up to 3.5-fold in the relative abundance of Acidobacteria Group 1 bacteria in soils exposed to elevated CO(2) or other climate factors. The Acidobacteria Group 1 response observed in exploratory 16S rRNA gene clone library surveys was validated in one ecosystem by 100-fold deeper sequencing and semi-quantitative PCR assays. Collectively, the 16S rRNA gene sequencing approach revealed influences of elevated CO(2) on multiple ecosystems. Although few common trends across the ecosystems were detected in the small surveys, the trends may be harbingers of more substantive changes in less abundant, more sensitive taxa that can only be detected by deeper surveys. Representative bacterial 16S rRNA gene clone sequences were deposited in GenBank with Accession No. JQ366086–JQ387568.

Upper limit to magnetism in LaAlO3/SrTiO3 heterostructures

Using polarized neutron reflectometry we measured the neutron spin-dependent reflectivity from four LaAlO(3)/SrTiO(3) superlattices. Our results imply that the upper limit for the magnetization averaged over the lateral dimensions of the sample induced by an 11 T magnetic field at 1.7 K is less than 2 G. SQUID magnetometry of the neutron superlattice samples sporadically finds an enhanced moment, possibly due to experimental artifacts. These observations set important restrictions on theories which imply a strongly enhanced magnetism at the interface between LaAlO(3) and SrTiO(3).

Efficiency of competitions

League competition is investigated using random processes and scaling techniques. In our model, a weak team can upset a strong team with a fixed probability. Teams play an equal number of head-to-head matches and the team with the largest number of wins is declared to be the champion. The total number of games needed for the best team to win the championship with high certainty T grows as the cube of the number of teams N , i.e., T approximately N(3). This number can be substantially reduced using preliminary rounds where teams play a small number of games and subsequently, only the top teams advance to the next round. When there are k rounds, the total number of games needed for the best team to emerge as champion, T(k), scales as follows, T(k) approximately N(gamma(k)) with gamma(k) = [1-(2/3)(k+1)](-1). For example, gamma(k)=95,2719,8165 for k=1,2,3 . These results suggest an algorithm for how to infer the best team using a schedule that is linear in N. We conclude that league format is an ineffective method of determining the best team, and that sequential elimination from the bottom up is fair and efficient.

Estimation of the reproductive number of the Spanish flu epidemic in Geneva, Switzerland

The 1918 influenza pandemic known as the "Spanish Flu" has been the worst in recent history with estimated worldwide mortality ranging from 20 to 100 million deaths. Using epidemic modeling and hospital notification data during the 1918 influenza pandemic in the Canton of Geneva, Switzerland, we estimated the reproductive numbers of the first and second waves of influenza infection to be R(1)=1.49 (95% CI: 1.45-1.53) and R(2)=3.75 (95% CI: 3.57-3.93), respectively. Our estimates indicate that containment of the next influenza pandemic could require strict interventions that include effective isolation strategies in hospitals and reductions in the susceptibility of the general population.

Transmission dynamics of the great influenza pandemic of 1918 in Geneva, Switzerland: Assessing the effects of hypothetical interventions

Recurrent outbreaks of the avian H5N1 influenza virus in Asia represent a constant global pandemic threat. We characterize and evaluate hypothetical public health measures during the 1918 influenza pandemic in the Canton of Geneva, Switzerland. The transmission rate, the recovery rate, the diagnostic rate, the relative infectiousness of asymptomatic cases, and the proportion of clinical cases are estimated through least-squares fitting of the model to epidemic curve data of the cumulative number of hospital notifications. The latent period and the case fatality proportion are taken from published literature. We determine the variance and identifiability of model parameters via a simulation study. Our epidemic model agrees well with the observed epidemic data. We estimate the basic reproductive number for the spring wave R1;=1.49 (95% CI: 1.45-1.53) and the reproductive number for the fall wave R2;=3.75 (95% CI: 3.57-3.93). In addition, we estimate the clinical reporting for these two waves to be 59.7% (95% CI: 55.7-63.7) and 83% (95% CI: 79-87). We surmise that the lower reporting in the first wave can be explained by a lack of initial awareness of the epidemic and the relative higher severity of the symptoms experienced during the fall wave. We found that effective isolation measures in hospital clinics at best would only ensure control with probability 0.87 while reducing the transmission rate by >76.5% guarantees stopping an epidemic.

Predicting scorpion sting incidence in an endemic region using climatological variables

Scorpionism is a public health problem in several regions of the world. The highest mortality, with over 1000 deaths per year, has been reported in Mexico. We analysed the significance of climatological variables to predict the incidence of scorpion stings in humans in the state of Colima (Mexico) for the years 2000-2001. The pluvial precipitation (mm), the evaporation (mm), and the mean, maximum, and minimum temperatures (degrees C) were obtained from local meteorological offices. There are approximately 3 stings/year per 1000 people in municipalities of Colima and Villa de Alvarez and about 18-30 stings/year per 1000 people in the rest of the municipalities. There is very little rain and there are few stings in the winter when the minimum temperature is below about 16 degrees C. The number of scorpion stings is independent of the actual rainfall when this is above 30 mm/month. Using multiple linear regression, we used a backward model selection procedure to estimate that the minimum temperature is correlated with scorpion sting incidence with a statistically significance of 95%. We briefly discuss the application of predictive models of scorpion sting incidence in the appropriate allocation of antivenom serum in hospital clinics.

The role of spatial mixing in the spread of foot-and-mouth disease

A model of epidemic dispersal (based on the assumption that susceptible cattle were homogeneously mixed over space, or non-spatial model) was compared to a partially spatially explicit and discrete model (the spatial model), which was composed of differential equations and used geo-coded data (Euclidean distances between county centroids). While the spatial model accounted for intra- and inter-county epidemic spread, the non-spatial model did not assess regional differences. A geo-coded dataset that resembled conditions favouring homogeneous mixing assumptions (based on the 2001 Uruguayan foot-and-mouth disease epidemic), was used for testing. Significant differences between models were observed in the average transmission rate between farms, both before and after a control policy (animal movement ban) was imposed. They also differed in terms of daily number of infected farms: the non-spatial model revealed a single epidemic peak (at, approximately, 25 epidemic days); while the spatial model revealed two epidemic peaks (at, approximately, 12 and 28 days, respectively). While the spatial model fitted well with the observed cumulative number of infected farms, the non-spatial model did not (P<0.01). In addition, the spatial model: (a) indicated an early intra-county reproductive number R of approximately 87 (falling to <1 within 25 days), and an inter-county R<1; (b) predicted that, if animal movement restrictions had begun 3 days before/after the estimated initiation of such policy, cases would have decreased/increased by 23 or 26%, respectively. Spatial factors (such as inter-farm distance and coverage of vaccination campaigns, absent in non-spatial models) may explain why partially explicit spatial models describe epidemic spread more accurately than non-spatial models even at early epidemic phases. Integration of geo-coded data into mathematical models is recommended.

The basic reproductive number of Ebola and the effects of public health measures: the cases of Congo and Uganda

Despite improved control measures, Ebola remains a serious public health risk in African regions where recurrent outbreaks have been observed since the initial epidemic in 1976. Using epidemic modeling and data from two well-documented Ebola outbreaks (Congo 1995 and Uganda 2000), we estimate the number of secondary cases generated by an index case in the absence of control interventions R0. Our estimate of R0 is 1.83 (SD 0.06) for Congo (1995) and 1.34 (SD 0.03) for Uganda (2000). We model the course of the outbreaks via an SEIR (susceptible-exposed-infectious-removed) epidemic model that includes a smooth transition in the transmission rate after control interventions are put in place. We perform an uncertainty analysis of the basic reproductive number R0 to quantify its sensitivity to other disease-related parameters. We also analyse the sensitivity of the final epidemic size to the time interventions begin and provide a distribution for the final epidemic size. The control measures implemented during these two outbreaks (including education and contact tracing followed by quarantine) reduce the final epidemic size by a factor of 2 relative the final size with a 2-week delay in their implementation.