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Policymakers must make management decisions despite incomplete knowledge and conflicting model projections. Little guidance exists for the rapid, representative, and unbiased collection of policy-relevant scientific input from independent modeling teams. Integrating approaches from decision analysis, expert judgment, and model aggregation, we convened multiple modeling teams to evaluate COVID-19 reopening strategies for a mid-sized United States county early in the pandemic. Projections from seventeen distinct models were inconsistent in magnitude but highly consistent in ranking interventions. The 6-mo-ahead aggregate projections were well in line with observed outbreaks in mid-sized US counties. The aggregate results showed that up to half the population could be infected with full workplace reopening, while workplace restrictions reduced median cumulative infections by 82%. Rankings of interventions were consistent across public health objectives, but there was a strong trade-off between public health outcomes and duration of workplace closures, and no win-win intermediate reopening strategies were identified. Between-model variation was high; the aggregate results thus provide valuable risk quantification for decision making. This approach can be applied to the evaluation of management interventions in any setting where models are used to inform decision making. This case study demonstrated the utility of our approach and was one of several multimodel efforts that laid the groundwork for the COVID-19 Scenario Modeling Hub, which has provided multiple rounds of real-time scenario projections for situational awareness and decision making to the Centers for Disease Control and Prevention since December 2020.

This study employs landscape genetics to investigate the environmental drivers of a deadly vector-borne disease, malaria caused by Plasmodium falciparum, in a more spatially comprehensive manner than any previous work. With 1804 samples from 44 sites collected in western Kenya in 2012 and 2013, we performed resistance surface analysis to show that Lake Victoria acts as a barrier to transmission between areas north and south of the Winam Gulf. In addition, Mantel correlograms clearly showed significant correlations between genetic and geographic distance over short distances (less than 70 km). In both cases, we used an identity-by-state measure of relatedness tailored to find highly related individual parasites in order to focus on recent gene flow that is more relevant to disease transmission. To supplement these results, we performed conventional population genetics analyses, including Bayesian clustering methods and spatial ordination techniques. These analyses revealed some differentiation on the basis of geography and elevation and a cluster of genetic similarity in the lowlands north of the Winam Gulf of Lake Victoria. Taken as a whole, these results indicate low overall genetic differentiation in the Lake Victoria region, but with some separation of parasite populations north and south of the Winam Gulf that is explained by the presence of the lake as a geographic barrier to gene flow. We recommend similar landscape genetics analyses in future molecular epidemiology studies of vector-borne diseases to extend and contextualize the results of traditional population genetics.

Background Coronavirus Disease 2019 (COVID-19) continues to cause significant hospitalizations and deaths in the United States. Its continued burden and the impact of annually reformulated vaccines remain unclear. Here, we present projections of COVID-19 hospitalizations and deaths in the United States for the next 2 years under 2 plausible assumptions about immune escape (20% per year and 50% per year) and 3 possible CDC recommendations for the use of annually reformulated vaccines (no recommendation, vaccination for those aged 65 years and over, vaccination for all eligible age groups based on FDA approval). Methods and findings The COVID-19 Scenario Modeling Hub solicited projections of COVID-19 hospitalization and deaths between April 15, 2023 and April 15, 2025 under 6 scenarios representing the intersection of considered levels of immune escape and vaccination. Annually reformulated vaccines are assumed to be 65% effective against symptomatic infection with strains circulating on June 15 of each year and to become available on September 1. Age- and state-specific coverage in recommended groups was assumed to match that seen for the first (fall 2021) COVID-19 booster. State and national projections from 8 modeling teams were ensembled to produce projections for each scenario and expected reductions in disease outcomes due to vaccination over the projection period. From April 15, 2023 to April 15, 2025, COVID-19 is projected to cause annual epidemics peaking November to January. In the most pessimistic scenario (high immune escape, no vaccination recommendation), we project 2.1 million (90% projection interval (PI) [1,438,000, 4,270,000]) hospitalizations and 209,000 (90% PI [139,000, 461,000]) deaths, exceeding pre-pandemic mortality of influenza and pneumonia. In high immune escape scenarios, vaccination of those aged 65+ results in 230,000 (95% confidence interval (CI) [104,000, 355,000]) fewer hospitalizations and 33,000 (95% CI [12,000, 54,000]) fewer deaths, while vaccination of all eligible individuals results in 431,000 (95% CI: 264,000-598,000) fewer hospitalizations and 49,000 (95% CI [29,000, 69,000]) fewer deaths. Conclusions COVID-19 is projected to be a significant public health threat over the coming 2 years. Broad vaccination has the potential to substantially reduce the burden of this disease, saving tens of thousands of lives each year., Author(s): Sung-mok Jung 1, Sara L. Loo 2, Emily Howerton 3, Lucie Contamin 4, Claire P. Smith 2, Erica C. Carcelén 2, Katie Yan 3, Samantha J. Bents 5, John [...]

Plasmodium vivax malaria was thought to be rare in Africa, but an increasing number of P. vivax cases reported across Africa and in Duffy-negative individuals challenges this dogma. The genetic characteristics of P. vivax in Duffy-negative infections, the transmission of P. vivax in East Africa, and the impact of environments on transmission remain largely unknown. This study examined genetic and transmission features of P. vivax from 107 Duffy-negative and 305 Duffy-positive individuals in Ethiopia and Sudan. No clear genetic differentiation was found in P. vivax between the 2 Duffy groups, indicating between-host transmission. P. vivax from Ethiopia and Sudan showed similar genetic clusters, except samples from Khartoum, possibly due to distance and road density that inhibited parasite gene flow. This study is the first to show that P. vivax can transmit to and from Duffy-negative individuals and provides critical insights into the spread of P. vivax in sub-Saharan Africa.

Plasmodium vivax malaria is much less common in Africa than the rest of the world because the parasite relies primarily on the Duffy antigen/chemokine receptor (DARC) to invade human erythrocytes, and the majority of Africans are Duffy negative. Recently, there has been a dramatic increase in the reporting of P. vivax cases in Africa, with a high number of them being in Duffy negative individuals, potentially indicating P. vivax has evolved an alternative invasion mechanism that can overcome Duffy negativity. Here, we analyzed single nucleotide polymorphism (SNP) and copy number variation (CNV) in Whole Genome Sequence (WGS) data from 44 P. vivax samples isolated from symptomatic malaria patients in southwestern Ethiopia, where both Duffy positive and Duffy negative individuals are found. A total of 123,711 SNPs were detected, of which 22.7% were nonsynonymous and 77.3% were synonymous mutations. The largest number of SNPs were detected on chromosomes 9 (24,007 SNPs; 19.4% of total) and 10 (16,852 SNPs, 13.6% of total). There were particularly high levels of polymorphism in erythrocyte binding gene candidates including merozoite surface protein 1 (MSP1) and merozoite surface protein 3 (MSP3.5, MSP3.85 and MSP3.9). Two genes, MAEBL and MSP3.8 related to immunogenicity and erythrocyte binding function were detected with significant signals of positive selection. Variation in gene copy number was also concentrated in genes involved in host-parasite interactions, including the expansion of the Duffy binding protein gene (PvDBP) on chromosome 6 and MSP3.11 on chromosome 10. Based on the phylogeny constructed from the whole genome sequences, the expansion of these genes was an independent process among the P. vivax lineages in Ethiopia. We further inferred transmission patterns of P. vivax infections among study sites and showed various levels of gene flow at a small geographical scale. The genomic features of P. vivax provided baseline data for future comparison with those in Duffy-negative individuals and allowed us to develop a panel of informative Single Nucleotide Polymorphic markers diagnostic at a micro-geographical scale.

SummaryIn exploring the epidemiology of infectious diseases, networks have been used to reconstruct contacts among individuals and/or populations. Summarizing networks using pathogen metadata (e.g. host species and place of isolation) and a phylogenetic tree is a nascent, alternative approach. In this paper, we introduce a tool for reconstructing transmission networks in arbitrary space from phylogenetic information and metadata. Our goals are to provide a means of deriving new insights and infection control strategies based on the dynamics of the pathogen lineages derived from networks and centrality metrics. We created a web-based application, called StrainHub, in which a user can input a phylogenetic tree based on genetic or other data along with characters derived from metadata using their preferred tree search method. StrainHub generates a transmission network based on character state changes in metadata, such as place or source of isolation, mapped on the phylogenetic tree. The user has the option to calculate centrality metrics on the nodes including betweenness, closeness, degree and a new metric, the source/hub ratio. The outputs include the network with values for metrics on its nodes and the tree with characters reconstructed. All of these results can be exported for further analysis.Availability and implementationstrainhub.io and https://github.com/abschneider/StrainHub.

Plasmodium vivax invasion of human erythrocytes depends on the Duffy Binding Protein (PvDBP) which interacts with the Duffy antigen. PvDBP copy number has been recently shown to vary between P. vivax isolates in Sub-Saharan Africa. However, the extent of PvDBP copy number variation, the type of PvDBP multiplications, as well as its significance across broad samples are still unclear. We determined the prevalence and type of PvDBP duplications, as well as PvDBP copy number variation among 178 Ethiopian P. vivax isolates using a PCR-based diagnostic method, a novel quantitative real-time PCR assay and whole genome sequencing. For the 145 symptomatic samples, PvDBP duplications were detected in 95 isolates, of which 81 had the Cambodian and 14 Malagasy-type PvDBP duplications. PvDBP varied from 1 to >4 copies. Isolates with multiple PvDBP copies were found to be higher in symptomatic than asymptomatic infections. For the 33 asymptomatic samples, PvDBP was detected with two copies in two of the isolates, and both were the Cambodian-type PvDBP duplication. PvDBP copy number in Duffy-negative heterozygotes was not significantly different from that in Duffy-positives, providing no support for the hypothesis that increased copy number is a specific association with Duffy-negativity, although the number of Duffy-negatives was small and further sampling is required to test this association thoroughly.

Single nucleotide polymorphisms (SNPs) have been shown to be useful in revealing population structure with continental-and regional-scale samples. In epidemiological study, a careful selection of SNPs to track disease spread in local communities would provide an important addition to traditional disease surveillance. This study used SNPs and microsatellites to examine population structure of Plasmodium falciparum at fine- scale in malaria-endemic areas of Western Kenya. A set of high performance (HP) SNPs were selected from a large SNP panel based on BELS ranking, FST values and minor allele frequency criteria. The discriminative power and assignment accuracy of different SNP panels including nonsynonymous SNPs, silent SNPs, previously published barcode SNPs, and the HP SNPs were evaluated together with microsatellites. Among all SNP panels, HP SNPs showed the highest level of differentiation and self-assignment accuracy on average among sites. Clear distinction was observed between the northern and southern P. falciparum samples, whereas samples from the south were least diverged from one another. These results were comparable to those by microsatellites. Nonsynonymous, silent, and barcode SNPs all showed similar levels of genetic variability to one another and weaker structure than the HP SNPs. We described here the procedure of selecting a set of HP SNPs from a large panel of SNPs that resolve population structure of P. falciparum between the northern and southern regions of Western Kenya. Future work is needed to determine if this procedure can result in SNPs panels capable of tracing Plasmodium spread at finer geographical scales.

BackgroundRecent genomic information has revealed that neuroglobin and cytoglobin are the two principal lineages of vertebrate hemoglobins, with the latter encompassing the familiar myoglobin and α-globin/β-globin tetramer hemoglobin, and several minor groups. In contrast, very little is known about hemoglobins in echinoderms, a phylum of exclusively marine organisms closely related to vertebrates, beyond the presence of coelomic hemoglobins in sea cucumbers and brittle stars. We identified about 50 hemoglobins in sea urchin, starfish and sea cucumber genomes and transcriptomes, and used Bayesian inference to carry out a molecular phylogenetic analysis of their relationship to vertebrate sequences, specifically, to assess the hypothesis that the neuroglobin and cytoglobin lineages are also present in echinoderms.ResultsThe genome of the sea urchin Strongylocentrotus purpuratus encodes several hemoglobins, including a unique chimeric 14-domain globin, 2 androglobin isoforms and a unique single androglobin domain protein. Other strongylocentrotid genomes appear to have similar repertoires of globin genes. We carried out molecular phylogenetic analyses of 52 hemoglobins identified in sea urchin, brittle star and sea cucumber genomes and transcriptomes, using different multiple sequence alignment methods coupled with Bayesian and maximum likelihood approaches. The results demonstrate that there are two major globin lineages in echinoderms, which are related to the vertebrate neuroglobin and cytoglobin lineages. Furthermore, the brittle star and sea cucumber coelomic hemoglobins appear to have evolved independently from the cytoglobin lineage, similar to the evolution of erythroid oxygen binding globins in cyclostomes and vertebrates.ConclusionThe presence of echinoderm globins related to the vertebrate neuroglobin and cytoglobin lineages suggests that the split between neuroglobins and cytoglobins occurred in the deuterostome ancestor shared by echinoderms and vertebrates.

BackgroundSocial media plays a critical role in health communications, especially during global health emergencies such as the current COVID-19 pandemic. However, there is a lack of a universal analytical framework to extract, quantify, and compare content features in public discourse of emerging health issues on different social media platforms across a broad sociocultural spectrum. ObjectiveWe aimed to develop a novel and universal content feature extraction and analytical framework and contrast how content features differ with sociocultural background in discussions of the emerging COVID-19 global health crisis on major social media platforms. MethodsWe sampled the 1000 most shared viral Twitter and Sina Weibo posts regarding COVID-19, developed a comprehensive coding scheme to identify 77 potential features across six major categories (eg, clinical and epidemiological, countermeasures, politics and policy, responses), quantified feature values (0 or 1, indicating whether or not the content feature is mentioned in the post) in each viral post across social media platforms, and performed subsequent comparative analyses. Machine learning dimension reduction and clustering analysis were then applied to harness the power of social media data and provide more unbiased characterization of web-based health communications. ResultsThere were substantially different distributions, prevalence, and associations of content features in public discourse about the COVID-19 pandemic on the two social media platforms. Weibo users were more likely to focus on the disease itself and health aspects, while Twitter users engaged more about policy, politics, and other societal issues. ConclusionsWe extracted a rich set of content features from social media data to accurately characterize public discourse related to COVID-19 in different sociocultural backgrounds. In addition, this universal framework can be adopted to analyze social media discussions of other emerging health issues beyond the COVID-19 pandemic.

Two juvenile specimens of anew species of Oreaster were collected at Parque Nacional Arrecife Alacranes and Triangulos Oeste in the southern Gulf of Mexico. DNA of mitochondrial loci identifies them as members of the same clade as cloning larvae of Oreaster found abundantly in waters of the Florida Current-Gulf Stream system, and distinct from Oreaster clavatus and Oreaster reticulatus, the two known Oreasteridae species in the North Atlantic. Larvae from the new species of Oreaster persist as clones but also metamorphose and settle to the benthos with typical asteroid morphology., Introduction Several clades of echinoderms clone as larvae (reviewed in Allen et al., 2018). Bosch et al. (1989) discovered cloning asteroid larvae in the Gulf Stream and in the Sargasso [...]