Coverage Estimates Research Articles

Vaccination Coverage Among Adolescents Aged 13-17 Years - National Immunization Survey-Teen, United States, 2022.

Three vaccines are routinely recommended for adolescents to prevent pertussis, meningococcal disease, and cancers caused by human papillomavirus (HPV). CDC analyzed data from the 2022 National Immunization Survey-Teen for 16,043 adolescents aged 13-17 years to assess vaccination coverage. Birth cohort analyses were conducted to assess trends in vaccination coverage by age 13 years (i.e., before the 13th birthday) and by age 14 years (i.e., before the 14th birthday) among adolescents who were due for routine vaccination before and during the COVID-19 pandemic. Cross-sectional analysis was used to assess coverage estimates among adolescents aged 13-17 years. In 2022, vaccination coverage by age 14 years among adolescents born in 2008 continued to lag that of earlier birth cohorts and varied by sociodemographic factors and access to health care compared with coverage among earlier birth cohorts. Vaccination coverage by age 13 years among adolescents born in 2009 was similar to coverage estimates obtained before the COVID-19 pandemic. Among all adolescents aged 13-17 years, 2022 vaccination coverage levels did not differ from 2021 levels; however, initiation of the HPV vaccination series decreased among those who were insured by Medicaid. Coverage with ≥1 dose of tetanus, diphtheria, and acellular pertussis vaccine and ≥1 dose meningococcal conjugate vaccine was high and stable (around 90%). Providers should review adolescent vaccination records, especially among those born in 2008 and those in populations eligible for the Vaccines for Children program, to ensure adolescents are up to date with all recommended vaccines.

Effects of polyethylene microplastics on properties, enzyme activities, and the succession of microbial community in Mollisol: At the aggregate level

Soil, as a heterogeneous body, is composed of different-sized aggregates. There is limited data available on the potential role of microplastics (MPs) in microbial properties at the soil aggregate level. In this study, changes in microbial construction and diversity in farmland bulk soil and aggregates induced by polyethylene MPs (PE-MPs) were investigated at a dose of 0.5% (w/w) through 16s rDNA sequencing and enzyme activity measurements of different particle size aggregates in incubated soil. The presence of low-dose PE-MPs increased the proportion of >1 mm soil aggregates fraction, and decreased soil available nitrogen and available phosphorus in bulk soils. Furthermore, low-dose PE-MPs increased bacterial richness and diversity in 1–0.5 and < 0.25 mm fractions and decreased operational taxonomic unit, abundance-based coverage estimator, and Chao1 indices in bulk soil and >1 mm fractions. The levels of predicted functional genes taking part in the biodegradation and metabolism of exogenous substances also increased. At the phylum level, PE-MPs changed the proportion of Proteobacteria and Actinobacteria. The variations in soil aggregate properties were significantly correlated with the bacterial communities’ composition and diversity. This study deepens our perception of the soil microenvironment, microbial community composition, and diversity in response to PE-MPs.

Using photogrammetry to create virtual permanent plots in rare and threatened plant communities.

Many plant communities across the world are undergoing changes due to climate change, human disturbance, and other threats. These community-level changes are often tracked with the use of permanent vegetative plots, but this approach is not always feasible. As an alternative, we propose using photogrammetry, specifically photograph-based digital surface models (DSMs) developed using structure-from-motion, to establish virtual permanent plots in plant communities where the use of permanent structures may not be possible. In 2021 and 2022, we took iPhone photographs to record species presence in 1-m2 plots distributed across alpine communities in the northeastern United States. We then compared field estimates of percent coverage with coverage estimated using DSMs. Digital surface models can provide effective, minimally invasive, and permanent records of plant species presence and percent coverage, while also allowing managers to mark survey locations virtually for long-term monitoring. We found that percent coverage estimated from DSMs did not differ from field estimates for most species and substrates. In order to continue surveying efforts in areas where permanent structures or other surveying methods are not feasible, photogrammetry and structure-from-motion methods can provide a low-cost approach that allows agencies to accurately survey and record sensitive plant communities through time.

Integrating sex-bias into studies of archaic introgression on chromosome X.

Evidence of interbreeding between archaic hominins and humans comes from methods that infer the locations of segments of archaic haplotypes, or 'archaic coverage' using the genomes of people living today. As more estimates of archaic coverage have emerged, it has become clear that most of this coverage is found on the autosomes- very little is retained on chromosome X. Here, we summarize published estimates of archaic coverage on autosomes and chromosome X from extant human samples. We find on average 7 times more archaic coverage on autosomes than chromosome X, and identify broad continental patterns in this ratio: greatest in European samples, and least in South Asian samples. We also perform extensive simulation studies to investigate how the amount of archaic coverage, lengths of coverage, and rates of purging of archaic coverage are affected by sex-bias caused by an unequal sex ratio within the archaic introgressors. Our results generally confirm that, with increasing male sex-bias, less archaic coverage is retained on chromosome X. Ours is the first study to explicitly model such sex-bias and its potential role in creating the dearth of archaic coverage on chromosome X.

Comparative estimates of crude coverage of the Mexican immunization program: Findings from a national survey

The purpose of the study is to provide estimates for immunization coverage, considering single-dose and schemes (three or five vaccines), by comparing self-report method to immunization cards, while also assessing the timeliness of immunization in Mexico, with reference to Mexican Immunization Program guidelines.Data on immunization was obtained from the Mexican Immunization Survey conducted in 2017 that aimed to assess crude (card-based) coverage at the regional level. Timely immunization was defined with reference to National Immunization Program guidelines, and immunization coverage was defined as a three or five vaccine scheme, based on previous national reports of immunization coverage. Immunization coverage estimates account for sample weights from the complex survey design. We used weighted immunization coverage estimates to assess the extent to which immunization cards and self-reporting concurred.It was found that most Mexican children are not receiving their full vaccine schedule in a timely manner. Concerning children under twelve months of age, the coverage targets for National Immunization of 95 % was not reached for either vaccine, and only 2.94 % (95 % CI 0.92–9.01) who had been receiving a three-vaccine scheme were considered as fully immunized in a timely manner. In contrast, coverage increased to 33.94 % (95 % CI 26.99–41.66), when untimely immunizations were taken into account, and the 95 % target was reached for five vaccines. Likewise, there is little correlation between self-report and immunization cards but rates show more concurrence, when only considering the proportion of true positives.In conclusion it was find that children at a local level are vaccinated in an incomplete and untimely manner. In order to improve immunization systems, a nominal registry of administered doses is thus of paramount importance. There is a need to address underlying health inequalities, as well as the factors associated with these, resulting in improved chances of a disease-free childhood and healthy life.

The potential impact of increased recombinant zoster vaccine coverage on the burden of herpes zoster among adults aged 50–59 years

IntroductionRecombinant zoster vaccine (RZV) is recommended in the US for prevention of herpes zoster (HZ) in adults aged ≥50 years. Vaccination rates remain suboptimal for adults 50–59 years compared with adults ≥50 years overall. The objective of this study was to model changes in outcomes associated with improved RZV vaccination coverage in US adults 50–59 years. MethodsA multicohort Markov model compared a scenario using real-world vaccination coverage for US adults 50–59 years in 2020 versus scenarios assuming higher coverage. Outcomes, based on a lifetime horizon, included HZ cases and complications avoided, quality-adjusted life-years (QALY), and costs. Model inputs included HZ epidemiology, RZV vaccine efficacy, coverage, adverse events, and costs, based on published literature and US sources. Some inputs were updated from previous models, including real-world estimates of RZV coverage, series completion, and reflecting longer-term data on waning of vaccine efficacy. The model utilized a cohort size of 42,756,488 individuals based on the 2020 US population census. ResultsThe model projected that increasing RZV coverage in adults 50–59 years from 7.3 % to 14.6 % (to coverage for adults 60–64 years in 2020) would avoid an additional 504,468 HZ cases, 42,077 postherpetic neuralgia cases, and 56,247 cases of other HZ-associated complications. The increase in vaccine coverage would result in higher vaccination-related costs of $1,172,411,566, but the avoided HZ cases and complications would be expected to result in direct cost savings of $721,973,386 and indirect cost savings of $593,497,480 from avoided productivity loss. Overall, a gain of 5,230 discounted QALYs and cost savings of $143,059,299 from a societal perspective would be realized. ConclusionModestly higher RZV coverage in US adults 50–59 years could reduce the clinical burden associated with HZ and may result in societal cost savings. These findings demonstrate the potential value of increasing RZV vaccination in this population.

Additional Burden Averted in the United States From Use of MF59-Adjuvanted Seasonal Influenza Vaccine Compared With Standard Seasonal Influenza Vaccine Among Adults ≥65 Years.

The MF59-adjuvanted trivalent inactivated influenza vaccine (aIIV3) is designed to overcome immunosenescence and enhance vaccine responses in older adults. We expanded on the Centers for Disease Control and Prevention (CDC) modeling method to estimate the number of additional influenza-related outcomes averted with aIIV3 versus generic quadrivalent inactivated influenza vaccine (IIV4) in adults ≥65 years over 3 influenza seasons (2017-2018 to 2019-2020) in the United States. A static compartmental model was developed based on an existing CDC model with 2 previously recommended calculation methods that increased the accuracy of the model in providing estimates of burden averted. Model inputs included vaccine effectiveness, vaccine coverage, population counts, and disease burden estimates. Additional burden averted (symptomatic cases, outpatient visits, hospitalizations, intensive care unit [ICU] admissions, and deaths) was expressed as total incremental cases averted between the vaccines. Sensitivity analyses tested the resilience of the model results to uncertainties in model inputs. The model estimated that vaccination with aIIV3 versus IIV4 would avert 2.24 times as many symptomatic cases, outpatient visits, hospitalizations, ICU stays, and deaths during 2017-2018; the burden averted in 2018-2019 and 2019-2020 with aIIV3 would be 3.44 and 1.72 times that averted with IIV4, respectively. Disease burden estimates and relative vaccine effectiveness of aIIV3 had the greatest impact on model estimates. Over 3 influenza seasons, the model estimated that aIIV3 was more effective than IIV4 in averting influenza-related outcomes, preventing 1.72 to 3.44 times as many influenza illnesses with proportionate decreases in related healthcare use and complications.

Effect of the oil from the fatty tissues of Crocodylus siamensis on gut microbiome diversity and metabolism in mice.

Dietary fat can alter host metabolism and gut microbial composition. Crocodile oil (CO) was extracted from the fatty tissues of Crocodylus siamensis. CO, rich in monounsaturated- and polyunsaturated fatty acids, has been reported to reduce inflammation, counter toxification, and improve energy metabolism. The aim of this study was to investigate the effect of CO on gut microbiota (GM) in laboratory mice as well as the accompanying metabolic changes in the animals. Forty-five C57BL/6 male mice were randomly divided into five groups and orally administrated either sterile water (control [C]); 1 or 3% (v/w) CO (CO-low [CO-L] and CO-high [CO-H], respectively); or 1 or 3% (v/w) palm oil (PO-low and PO-high, respectively) for 11 weeks. Body weight gain, food intake, energy intake, blood glucose levels, and blood lipid profiles were determined. Samples from colon tissue were collected and the 16S rRNA genes were pyrosequenced to clarify GM analyses. The results showed that there were no differences in body weight and blood glucose levels. Food intake by the mice in the CO-L and CO-H groups was statistically significantly less when compared to that by the animals in the C group. However, neither CO treatment had a statistically significant effect on calorie intake when compared to the controls. The CO-H exhibited a significant increase in serum total cholesterol and low-density lipoprotein but showed a downward trend in triglyceride levels compared to the control. The GM analyses revealed that both CO treatments have no significant influence on bacterial diversity and relative abundance at the phylum level, whereas increases of Choa1 and abundance-based coverage estimator indexes, distinct β-diversity, and Proteobacteria abundance were observed in the PO-high group compared with the C group. Furthermore, the abundance of Azospirillum thiophilum and Romboutsia ilealis was significantly higher in the CO-L and CO-H groups which could be associated with energy metabolic activity. Thus, CO may be an alternative fat source for preserving host metabolism and gut flora.

Effects of grazing prohibition on nirK- and nirS-type denitrifier communities in salt marshes.

Grazing prohibition is an effective management practice to restore salt marsh functioning. However, the effects of grazing exclusion on denitrifying microbial communities and their controlling factors in salt marshes remain unclear. In this study, we surveyed soil physicochemical properties and above- and below-ground biomass and using quantitative polymerase chain reaction and Illumina MiSeq high-throughput sequencing technology to determine the relative abundance, composition, and diversity of nitrite reductase nirS- and nirK-type denitrifying bacterial communities associated with grazing prohibition treatments and elevations. The abundance of nirS-type denitrifiers increased with grazing prohibition time, whereas the abundance of nirK-type denitrifiers remained unaltered. Moreover, nirS-type denitrifiers were more abundant and diverse than nirK-type denitrifiers in all treatments. Grazing prohibition significantly altered the operational taxonomic unit richness, abundance-based coverage estimator, and Chao1 indices of the nirS-type denitrifying bacterial communities, whereas it only minimally affected the structure of the nirK-type denitrifying bacterial community. The results imply that the nirS community, rather than nirK, should be the first candidate for use as an indicator in the process of salt marsh restoration after grazing prohibition. Substances of concern, total nitrogen, and salinity were the key environmental factors affecting the abundance and community composition of nirS and nirK denitrifiers. The findings of this study provide novel insights into the influence of the length of grazing prohibition and elevation on nirS- and nirK-type denitrifying bacterial community composition in salt marshes.

Evolving fuzzy prediction interval for fault detection in a heat exchanger

The objective of this work is to design a novel evolving fuzzy prediction interval for modeling a nonlinear system and to implement a novel interval-based algorithm for fault detection. To achieve these goals, three frameworks are studied to provide the basis for the ideas to be proposed. First, the prediction intervals developed in the literature to characterize the uncertainties in modeling systems. Second, the evolving intelligence systems presented in the literature to improve the predictive models through adaptability to temporal changes. Third, the model-based error detection algorithms that detect anomalies in system behavior based on the error of the models. This work proposes a complete recursive design of the evolving fuzzy prediction interval based on interval coverage estimation. This estimation is based on the accumulated number of past time points in which the interval contained the measurements of the modeled system. Additionally, a new interval-based fault detection algorithm is proposed in this work that determines the activation of alarms based on the increment of the proposed interval failure index. This novel index is similar in structure to the interval coverage estimation. The proposed recursively evolving fuzzy prediction interval and interval-based fault detection algorithm were tested on a heat exchanger system whose characteristics were affected by external changes. The experimental results show the effectiveness of the proposed interval model in representing the dynamics of the heat exchanger. Furthermore, the experiment shows that the proposed fault detection algorithm achieves comparable accurate performance to the results of a previous model-based fault detection method.

Protocol for a cluster randomised placebo-controlled trial of adjunctive ivermectin mass drug administration for malaria control on the Bijagós Archipelago of Guinea-Bissau: the MATAMAL trial

IntroductionAs malaria declines, innovative tools are required to further reduce transmission and achieve elimination. Mass drug administration (MDA) of artemisinin-based combination therapy (ACT) is capable of reducing malaria transmission where...

The Trajectory of Brazilian Immunization Program between 1980 and 2018: From the Virtuous Cycle to the Vaccine Coverage Decline.

Public health policies are crossed by economic and political interests that can affect the maintenance of the immunization programs and their vaccination coverages. The aim was to investigate the political and economic conditions that marked the trajectory of the Brazilian immunization program from 1980 to 2018. Documentary research gathered data on public expenditures with epidemiological surveillance and vaccine procurement and nationwide estimates of vaccine coverage. The scientific literature on the program's implementation and the country's political and economic conditions was examined. The theoretical approach was based on historical institutionalism. The results showed rising, high rates maintaining and falling vaccination coverages in the period. As of 2010, there was a tendency for a reduction in total federal spending on epidemiological surveillance, putting pressure on the budgets of the sub-national governments in their respective areas of coverage, and on federal spending in dollars for the acquisition of immunobiologicals and inputs. The amplitude and complexity of the program's trajectory have been crossed by diverse dynamics conditioned by economic and political interests reflecting at a deeper level the advance of capitalism through fiscal austerity measures over democracy's aspirations for greater balance and justice in the distribution of resources.

Ischaemic stroke patients present sex differences in gut microbiota.

Gut microbiota plays a role in the pathophysiology of ischaemic stroke (IS) through the bidirectional gut-brain axis. Nevertheless, little is known about sex-specific microbiota signatures in IS occurrence. A total of 89 IS patients and 12 healthy controls were enrolled. We studied the taxonomic differences of the gut microbiota between men and women with IS by shotgun metagenomic sequencing. To evaluate the causal effect of several bacteria on IS risk, we performed a two-sample Mendelian randomisation (MR) with inverse-variance weighting (IVW) using genome-wide association analysis (GWAS) summary statistics from two cohorts of 5959 subjects with genetic and microbiota data and 1,296,908 subjects with genetic and IS data, respectively. α-Diversity analysis measured using Observed Species (p = 0.017), Chao1 (p = 0.009) and Abundance-based Coverage Estimator (p = 0.012) indexes revealed that IS men have a higher species richness compared with IS women. Moreover, we found sex-differences in IS patients in relation to the phylum Fusobacteria, class Fusobacteriia, order Fusobacteriales and family Fusobacteriaceae (all Bonferroni-corrected p < 0.001). MR confirmed that increased Fusobacteriaceae levels in the gut are causally associated with an increased risk of IS (IVW p = 0.02, β = 0.32). Our study is the first to indicate that there are gut microbiome differences between men and women with IS, identifying high levels of Fusobacteriaceae in women as a specific risk factor for IS. Incorporating sex stratification analysis is important in the design, analysis and interpretation of studies on stroke and the gut microbiota.

A Trust-Based Reliable Confident Information Coverage Model of Wireless Sensor Networks for Intelligent Transportation

Wireless sensor nodes are vulnerable to interference or intrusion, especially in the tunnel scenario of intelligent transportation, which leads to potential risks to network security and reliability. Reliable coverage can ensure data perception and transmission, which helps to strengthen the reliability and quality of service (QoS) of wireless sensor networks (WSNs). Existing coverage models, such as the disc model, do not consider malicious intrusion, which still has a great gap with the realistic application scenarios. Therefore, it is urgent to study a coverage model considering network intrusion and node reliability. In this paper, a novel trust-based reliable confident information coverage (T-RCIC) model is proposed based on the confident information coverage (CIC) model and trust management. Trust management is adopted to determine whether a node is trusted, critical trusted, or malicious. If a node is identified as malicious, all its functions will be blocked. For critical trusted nodes, the trust value is utilized to determine the trust feature distance to reduce its proportion of coverage estimation. Furthermore, the reliable coverage degree (RCD) is defined to evaluate coverage reliability from node trust value and reliable coverage percentage. Simulation results indicate that the proposed model inherits the advantages of the CIC model in the spatial correlation and can effectively identify malicious nodes. The proposed T-RCIC model can significantly enhance coverage reliability.

Influenza and Tetanus, Diphtheria, and Acellular Pertussis Vaccination Coverage During Pregnancy: Pregnancy Risk Assessment Monitoring System, 2020.

Estimates of vaccination coverage during pregnancy and identification of disparities in vaccination coverage can inform vaccination campaigns and programs. We reported the prevalence of being offered or told to get the influenza vaccine by a health care provider (hereinafter, provider); influenza vaccination coverage during the 12 months before delivery; and tetanus, diphtheria, and acellular pertussis (Tdap) vaccination coverage during pregnancy among women with a recent live birth in the United States. We analyzed 2020 data from the Pregnancy Risk Assessment Monitoring System from 42 US jurisdictions (n = 41 673). We estimated the overall prevalence of being offered or told to get the influenza vaccine by a provider and influenza vaccination coverage during the 12 months before delivery. We estimated Tdap vaccination coverage during pregnancy from 21 jurisdictions with available data (n = 22 020) by jurisdiction and select characteristics. In 2020, 84.9% of women reported being offered or told to get the influenza vaccine, and 60.9% received it, ranging from 35.0% in Puerto Rico to 79.7% in Massachusetts. Influenza vaccination coverage was lower among women who were not offered or told to get the influenza vaccine (21.4%) than among women who were offered or told to get the vaccine (68.1%). Overall, 72.7% of women received the Tdap vaccine, ranging from 52.8% in Mississippi to 86.7% in New Hampshire. Influenza and Tdap vaccination coverage varied by all characteristics examined. These results can inform vaccination programs and strategies to address disparities in vaccination coverage during pregnancy and may inform vaccination efforts for other infectious diseases among pregnant women.

Sample coverage estimation, rarefaction, and extrapolation based on sample-based abundance data.

Sample coverage, the proportion of individuals that belong to observed species in a sample, is a metric used to measure the completeness of a sample. Rather than using equal sample sizes, equal sample coverage has become a widely accepted standard for comparing diversity across multiple assemblages, resulting in a more accurate representation of the true relationship between the richness of the assemblages. In practice, sample-based abundance data are the most frequently used data type for evaluating species diversity. In sample-based abundance data, the sampling unit (e.g., a plot, net, trap, or transect) is randomly selected from the target area, and the number of individuals for each species observed in the sampled unit is recorded. In this case, the individuals in the sample are no longer randomly and independently sampled, and the Good-Turing estimators of abundance-based sample coverage in reference, rarefied, and extrapolated samples may be severely biased when individuals present a highly spatially aggregated pattern. Here, I derive a novel estimator of abundance-based sample coverage based on the Good-Turing frequency formula. Additionally, a new analytical approach is introduced for enabling smooth coverage-based rarefaction and extrapolation to compare richness among assemblages. The near unbiasedness of the proposed estimator and a less biased richness ratio achieved using the newly developed coverage-based standardizing approach are demonstrated by analyzing three ForestGEO permanent forest plot data sets.

Exploring the accuracy of self-reported maternal and newborn care in select studies from low and middle-income country settings: do respondent and facility characteristics affect measurement?

BackgroundAccurate data on the receipt of essential maternal and newborn health interventions is necessary to interpret and address gaps in effective coverage. Validation results of commonly used content and quality of care indicators routinely implemented in international survey programs vary across settings. We assessed how respondent and facility characteristics influenced the accuracy of women’s recall of interventions received in the antenatal and postnatal periods.MethodsWe synthesized reporting accuracy using data from a known sample of validation studies conducted in Sub-Saharan Africa and Southeast Asia, which assessed the validity of women’s self-report of received antenatal care (ANC) (N = 3 studies, 3,169 participants) and postnatal care (PNC) (N = 5 studies, 2,462 participants) compared to direct observation. For each study, indicator sensitivity and specificity are presented with 95% confidence intervals. Univariate fixed effects and bivariate random effects models were used to examine whether respondent characteristics (e.g., age group, parity, education level), facility quality, or intervention coverage level influenced the accuracy of women’s recall of whether interventions were received.ResultsIntervention coverage was associated with reporting accuracy across studies for the majority (9 of 12) of PNC indicators. Increasing intervention coverage was associated with poorer specificity for 8 indicators and improved sensitivity for 6 indicators. Reporting accuracy for ANC or PNC indicators did not consistently differ by any other respondent or facility characteristic.ConclusionsHigh intervention coverage may contribute to higher false positive reporting (poorer specificity) among women who receive facility-based maternal and newborn care while low intervention coverage may contribute to false negative reporting (lower sensitivity). While replication in other country and facility settings is warranted, results suggest that monitoring efforts should consider the context of care when interpreting national estimates of intervention coverage.

Terabase-Scale Coassembly of a Tropical Soil Microbiome.

Petabases of environmental metagenomic data are publicly available, presenting an opportunity to characterize complex environments and discover novel lineages of life. Metagenome coassembly, in which many metagenomic samples from an environment are simultaneously analyzed to infer the underlying genomes' sequences, is an essential tool for achieving this goal. We applied MetaHipMer2, a distributed metagenome assembler that runs on supercomputing clusters, to coassemble 3.4 terabases (Tbp) of metagenome data from a tropical soil in the Luquillo Experimental Forest (LEF), Puerto Rico. The resulting coassembly yielded 39 high-quality (>90% complete, <5% contaminated, with predicted 23S, 16S, and 5S rRNA genes and ≥18 tRNAs) metagenome-assembled genomes (MAGs), including two from the candidate phylum Eremiobacterota. Another 268 medium-quality (≥50% complete, <10% contaminated) MAGs were extracted, including the candidate phyla Dependentiae, Dormibacterota, and Methylomirabilota. In total, 307 medium- or higher-quality MAGs were assigned to 23 phyla, compared to 294 MAGs assigned to nine phyla in the same samples individually assembled. The low-quality (<50% complete, <10% contaminated) MAGs from the coassembly revealed a 49% complete rare biosphere microbe from the candidate phylum FCPU426 among other low-abundance microbes, an 81% complete fungal genome from the phylum Ascomycota, and 30 partial eukaryotic MAGs with ≥10% completeness, possibly representing protist lineages. A total of 22,254 viruses, many of them low abundance, were identified. Estimation of metagenome coverage and diversity indicates that we may have characterized ≥87.5% of the sequence diversity in this humid tropical soil and indicates the value of future terabase-scale sequencing and coassembly of complex environments. IMPORTANCE Petabases of reads are being produced by environmental metagenome sequencing. An essential step in analyzing these data is metagenome assembly, the computational reconstruction of genome sequences from microbial communities. "Coassembly" of metagenomic sequence data, in which multiple samples are assembled together, enables more complete detection of microbial genomes in an environment than "multiassembly," in which samples are assembled individually. To demonstrate the potential for coassembling terabases of metagenome data to drive biological discovery, we applied MetaHipMer2, a distributed metagenome assembler that runs on supercomputing clusters, to coassemble 3.4 Tbp of reads from a humid tropical soil environment. The resulting coassembly, its functional annotation, and analysis are presented here. The coassembly yielded more, and phylogenetically more diverse, microbial, eukaryotic, and viral genomes than the multiassembly of the same data. Our resource may facilitate the discovery of novel microbial biology in tropical soils and demonstrates the value of terabase-scale metagenome sequencing.

Seasonal influenza vaccination in the Americas: Progress and challenges during the COVID-19 pandemic

BackgroundVaccination is one of the most effective measures to prevent influenza illness and its complications; influenza vaccination remained important during the COVID-19 pandemic to prevent additional burden on health systems strained by COVID-19 demand. ObjectivesWe describe policies, coverage, and progress of seasonal influenza vaccination programs in the Americas during 2019–2021 and discuss challenges in monitoring and maintaining influenza vaccination coverage among target groups during the COVID-19 pandemic. MethodsWe used data on influenza vaccination policies and vaccination coverage reported by countries/territories via the electronic Joint Reporting Form on Immunization (eJRF) for 2019–2021. We also summarized country vaccination strategies shared with PAHO. ResultsAs of 2021, 39 (89 %) out of 44 reporting countries/territories in the Americas had policies for seasonal influenza vaccination. Countries/territories adapted health services and immunization delivery strategies using innovative approaches, such as new vaccination sites and expanded schedules, to ensure continuation of influenza vaccination during the COVID-19 pandemic. However, among countries/territories that reported data to eJRF in both 2019 and 2021, median coverage decreased; the percentage point decrease was 21 % (IQR = 0–38 %; n = 13) for healthcare workers, 10 % (IQR = -1.5–38 %; n = 12) for older adults, 21 % (IQR = 5–31 %; n = 13) for pregnant women, 13 % (IQR = 4.8–20.8 %; n = 8) for persons with chronic diseases, and 9 % (IQR = 3–27 %; n = 15) for children. ConclusionsCountries/territories in the Americas successfully adapted influenza vaccination delivery to continue vaccination services during the COVID-19 pandemic; however, reported influenza vaccination coverage decreased from 2019 to 2021. Reversing declines in vaccination will necessitate strategic approaches that prioritize sustainable vaccination programs across the life course. Efforts should be made to improve the completeness and quality of administrative coverage data. Lessons learned from COVID-19 vaccination, such as the rapid development of electronic vaccination registries and digital certificates, might facilitate advances in coverage estimation.

Estimation of coverage and energy in bio inspired wireless sensors using Harris hawk algorithm

Wireless sensor networks have various sensors which are wide spread and also equipped with supplies. For the deployment sensor nodes are used for capturing the information, the region of interest is selected and the nodes are deployed. Lower sensing power degrades the DC supply reducing the life of wireless sensor networks, this can also be due to improper sensor deployment. Based on the above various wireless sensor network algorithms are available to compute and implement the required optimal figures. Harris hawk is among the one such algorithm used in wireless sensors. It works on the principle of the bird Harris hawk which catches the prey from a very high altitude, resemblance to this and many other features it is implemented in wireless sensors. Various wireless sensor characteristics can be found, figured and tabulated which are essential in this domain. The characteristics like coverage, connectivity, location, energy, and can be estimated. In the work the coverage and energy fitness is estimated using Harris hawk algorithm and its results are being illustrated.