Spatial scales, patterns, and positivity trends of SARS-CoV-2 pandemics in mass rapid antigen testing in Slovakia.
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ABSTRACT:
SUBMITTER: Bodova K
PROVIDER: S-EPMC8386854 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Despite the accuracy of nucleic acid amplification tests (NAATs), rapid antigen tests (RATs) for severe acute respiratory syndrome coronavirus-2 are widely used as point-of-care tests. A total of 282 pairs of reverse transcription-polymerase chain reaction and Standard Q COVID-19 Ag tests were serially conducted for 68 patients every 3-4 days until their discharge. Through a field evaluation of RATs using direct nasopharyngeal swabs, the sensitivities were 84.6% and 87.3% for E and RNA-dependent RNA polymerase (RdRp) genes, respectively, for specimens with cycle thresholds (Cts) < 25. The Ct values of E and RdRp genes for 95% detection rates by RATs were 16.9 and 18.1, respectively. The sensitivity of RAT was 48.4% after the onset of symptoms, which was not sufficient. RAT positivity gradually decreased with increased time after symptom onset and had continuously lower sensitivity than NAATs.
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Project description:Understanding spatiotemporal population trends and their drivers is a key aim in population ecology. We further need to be able to predict how the dynamics and sizes of populations are affected in the long term by changing landscapes and climate. However, predictions of future population trends are sensitive to a range of modeling assumptions. Deadwood-dependent fungi are an excellent system for testing the performance of different predictive models of sessile species as these species have different rarity and spatial population dynamics, the populations are structured at different spatial scales, and they utilize distinct substrates. We tested how the projected large-scale occupancies of species with differing landscape-scale occupancies are affected over the coming century by different modeling assumptions. We compared projections based on occupancy models against colonization-extinction models, conducting the modeling at alternative spatial scales and using fine- or coarse-resolution deadwood data. We also tested effects of key explanatory variables on species occurrence and colonization-extinction dynamics. The hierarchical Bayesian models applied were fitted to an extensive repeated survey of deadwood and fungi at 174 patches. We projected higher occurrence probabilities and more positive trends using the occupancy models compared to the colonization-extinction models, with greater difference for the species with lower occupancy, colonization rate, and colonization:extinction ratio than for the species with higher estimates of these statistics. The magnitude of future increase in occupancy depended strongly on the spatial modeling scale and resource resolution. We encourage using colonization-extinction models over occupancy models, modeling the process at the finest resource-unit resolution that is utilizable by the species, and conducting projections for the same spatial scale and resource resolution at which the model fitting is conducted. Further, the models applied should include key variables driving the metapopulation dynamics, such as the availability of suitable resource units, habitat quality, and spatial connectivity.
| S-EPMC7083660 | biostudies-literature
Project description:Diagnostic yield of a next-generation sequencing gene panel in Slovak cardiomyopathy patients
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Project description:In public health research, it has been well established that geographic location plays an important role in influencing health outcomes. In recent years, there has been an increased emphasis on the impact of neighborhood or contextual factors as potential risk factors for childhood obesity. Some neighborhood factors relevant to childhood obesity include access to food sources, access to recreational facilities, neighborhood safety, and socioeconomic status (SES) variables. It is common for neighborhood or area-level variables to be available at multiple spatial scales (SS) or geographic units, such as the census block group and census tract, and selection of the spatial scale for area-level variables can be considered as a model selection problem. In this paper, we model the variation in body mass index (BMI) in a study of pediatric patients of the Virginia Commonwealth University (VCU) Medical Center, while considering the selection of spatial scale for a set of neighborhood-level variables available at multiple spatial scales using four recently proposed spatial scale selection algorithms: SS forward stepwise regression, SS incremental forward stagewise regression, SS least angle regression (LARS), and SS lasso. For pediatric BMI, we found evidence of significant positive associations with visit age and black race at the individual level, percent Hispanic white at the census block group level, percent Hispanic black at the census tract level, and percent vacant housing at the census tract level. We also found significant negative associations with population density at the census tract level, median household income at the census tract level, percent renter at the census tract level, and exercise equipment expenditures at the census block group level. The SS algorithms selected covariates at different spatial scales, producing better goodness-of-fit in comparison to traditional models, where all area-level covariates were modeled at the same scale. These findings underscore the importance of considering spatial scale when performing model selection.
| S-EPMC5877018 | biostudies-literature
Project description:ImportanceLongitudinal mass testing using rapid antigen detection tests (RADT) for serial screening of asymptomatic persons has been proposed for preventing SARS-CoV-2 community transmission. The feasibility of this strategy relies on accurate self-testing.ObjectiveTo quantify the adequacy of serial self-performed SARS-CoV-2 RADT testing in the workplace, in terms of the frequency of correct execution of procedural steps and accurate interpretation of the range of possible RADT results.Design, setting, and participantsThis prospective repeated cross-sectional study was performed from July to October 2021 at businesses with at least 2 active cases of SARS-CoV-2 infection in Montreal, Canada. Participants included untrained persons in their workplace, not meeting Public Health quarantine criteria (ie, required quarantine for 10 days after a moderate-risk contact with someone infected with SARS-CoV-2). Interpretation and performance were compared between participants who received instructions provided by the manufacturer vs those who received modified instructions that were informed by the most frequent or most critical errors we observed. Data were analyzed from October to November 2021.ExposuresRADT testing using a modified quick reference guide compared with the original manufacturer's instructions.Main outcomes and measuresThe main outcome was the difference in correctly interpreted RADT results. Secondary outcomes included difference in proportions of correctly performed procedural steps. Additional analyses, assessed among participants with 2 self-testing visits, compared the second self-test visit with the first self-test visit using the same measures.ResultsOverall, 1892 tests were performed among 647 participants, of whom 278 participants (median [IQR] age, 43 [31-55] years; 156 [56.1%] men) had at least 1 self-testing visit. For self-test visit 1, significantly better accuracy in test interpretation was observed among participants using the modified quick reference guide than those using the manufacturer's instructions for reading results that were weak positive (64 of 115 participants [55.6%] vs 20 of 163 participants [12.3%]; difference, 43.3 [95% CI, 33.0-53.8] percentage points), positive (103 of 115 participants [89.6%] vs 84 of 163 participants [51.5%]; difference, 38.1 [95% CI, 28.5-47.5] percentage points), strong positive (219 of 229 participants [95.6%] vs 274 of 326 participants [84.0%]; difference, 11.6 [95% CI, 6.8-16.3] percentage points), and invalid (200 of 229 participants [87.3%] vs 252 of 326 participants [77.3%]; difference, 10.0 [95% CI, 3.8-16.3] percentage points). Use of the modified guide was associated with improvements on self-test visit 2 for results that were weak positive (difference, 15.4 [95% CI, 0.7-30.1] percentage points), positive (difference, 19.0 [95% CI, 7.2-30.9] percentage points), and invalid (difference, 8.0 [95% CI, 0.8-15.4] percentage points). For procedural steps identified as critical for test validity, adherence to procedural testing steps did not differ meaningfully according to instructions provided or reader experience.Conclusions and relevanceIn this cross-sectional study of self-performed SARS-CoV-2 RADT in an intended-use setting, a modified quick reference guide was associated with significantly improved accuracy in RADT interpretations.
| S-EPMC9077488 | biostudies-literature
Project description:ImportanceCharacterizing the clinical symptoms and evolution of community-based SARS-CoV-2 infections may inform health practitioners and public health officials in a rapidly changing landscape of population immunity and viral variants.ObjectivesTo compare COVID-19 symptoms among people testing positive with a rapid antigen test (RAT) during the Omicron BA.1 variant period (December 1, 2021, to January 30, 2022) with the pre-Delta (January 10 to May 31, 2021) and Delta (June 1 to November 30, 2021) variant periods and to assess the duration of RAT positivity during the Omicron BA.1 surge.Design, setting, and participantsThis cross-sectional study was conducted from January 10, 2021, to January 31, 2022, at a walk-up community COVID-19 testing site in San Francisco, California. Participants included children and adults seeking COVID-19 testing with an RAT, regardless of age, vaccine status, or symptoms.Main outcomes and measuresFisher exact tests or χ2 tests were used to compare COVID-19 symptoms during the Omicron BA.1 period with the pre-Delta and Delta periods for vaccination status and age group. Among people returning for repeated testing during the Omicron period, the proportion with a positive RAT between 4 and 14 days from symptom onset or since first positive test if asymptomatic was estimated.ResultsAmong 63 277 persons tested (median [IQR] age, 32 [21-44] years, with 12.0% younger than 12 years; 52.0% women; and 68.5% Latinx), a total of 18 301 people (28.9%) reported symptoms, of whom 4565 (24.9%) tested positive for COVID-19. During the Omicron BA.1 period, 3032 of 7283 symptomatic participants (41.6%) tested positive, and the numbers of these reporting cough and sore throat were higher than during pre-Delta and Delta periods (cough: 2044 [67.4%] vs 546 [51.3%] of 1065 participants, P < .001 for pre-Delta, and 281 [60.0%] of 468 participants, P = .002, for Delta; sore throat: 1316 [43.4%] vs 315 [29.6%] of 1065 participants, P < .001 for pre-Delta, and 136 [29.1%] of 468 participants, P < .001, for Delta). Compared with the 1065 patients with positive test results in the pre-Delta period, congestion among the 3032 with positive results during the Omicron BA.1 period was more common (1177 [38.8%] vs 294 [27.6%] participants, P < .001), and loss of taste or smell (160 [5.3%] vs 183 [17.2%] participants, P < .001) and fever (921 [30.4%] vs 369 [34.7%] participants, P = .01) were less common. In addition, during the Omicron BA.1 period, fever was less common among the people with positive test results who had received a vaccine booster compared with those with positive test results who were unvaccinated (97 [22.5%] of 432 vs 42 [36.2%] of 116 participants, P = .003), and fever and myalgia were less common among participants who had received a booster compared with those with positive results who had received only a primary series (fever: 97 [22.5%] of 432 vs 559 [32.8%] of 1705 participants, P < .001; myalgia: 115 [26.6%] of 432 vs 580 [34.0%] of 1705 participants, P = .003). During the Omicron BA.1 period, 5 days after symptom onset, 507 of 1613 people (31.1%) with COVID-19 stated that their symptoms were similar, and 95 people (5.9%) reported worsening symptoms. Among people testing positive, 80.2% of participants who were symptomatic and retested remained positive 5 days after symptom onset.Conclusions and relevanceIn this cross-sectional study, COVID-19 upper respiratory tract symptoms were more commonly reported during the Omicron BA.1 period than during the pre-Delta and Delta periods, with differences by vaccination status. Rapid antigen test positivity remained high 5 days after symptom onset, supporting guidelines requiring a negative test to inform the length of the isolation period.
| S-EPMC9552893 | biostudies-literature
Project description:Measurements of the specificity and affinity of antigen-antibody interactions are critically important for medical and research applications. In this protocol, we describe the implementation of a new single-molecule technique, mass photometry (MP), for this purpose. MP is a label- and immobilization-free technique that detects and quantifies molecular masses and populations of antibodies and antigen-antibody complexes on a single-molecule level. MP analyzes the antigen-antibody sample within minutes, allowing for the precise determination of the binding affinity and simultaneously providing information on the stoichiometry and the oligomeric state of the proteins. This is a simple and straightforward technique that requires only picomole quantities of protein and no expensive consumables. The same procedure can be used to study protein-protein binding for proteins with a molecular mass larger than 50 kDa. For multivalent protein interactions, the affinities of multiple binding sites can be obtained in a single measurement. However, the single-molecule mode of measurement and the lack of labeling imposes some experimental limitations. This method gives the best results when applied to measurements of sub-micromolar interaction affinities, antigens with a molecular mass of 20 kDa or larger, and relatively pure protein samples. We also describe the procedure for performing the required fitting and calculation steps using basic data analysis software.
| S-EPMC8056393 | biostudies-literature
Project description:BackgroundWhile invasive social distancing measures have proven efficient to control the spread of pandemics failing wide-scale deployment of vaccines, they carry vast societal costs. The development of a diagnostic methodology for identifying COVID-19 infection through simple testing was a reality only a few weeks after the novel virus was officially announced. Thus, we were interested in exploring the ability of regular testing of non-symptomatic people to reduce cases and thereby offer a non-pharmaceutical tool for controlling the spread of a pandemic.MethodsWe developed a data-driven individual-based epidemiological network model in order to investigate epidemic countermeasures. This models is based on high-resolution demographic data for each municipality in Norway, and each person in the model is subject to Susceptible-Exposed-Infectious-Recovered (SEIR) dynamics. The model was calibrated against hospitalization data in Oslo, Norway, a city with a population of 700k which we have used as the simulations focus.ResultsFinding that large households function as hubs for the propagation of COVID-19, we assess the intervention efficiency of targeted pooled household testing (TPHT) repeatedly. For an outbreak with reproductive number R=1.4, we find that weekly TPHT of the 25% largest households brings R below unity. For the case of R=1.2, our results suggest that TPHT with the largest 25% of households every three days in an urban area is as effective as a lockdown in curbing the outbreak. Our investigations of different disease parameters suggest that these results are markedly improved for disease variants that more easily infect young people, and when compliance with self-isolation rules is less than perfect among suspected symptomatic cases. These results are quite robust to changes in the testing frequency, city size, and the household-size distribution. Our results are robust even with only 50% of households willing to participate in TPHT, provided the total number of tests stay unchanged.ConclusionsPooled and targeted household testing appears to be a powerful non-pharmaceutical alternative to more invasive social-distancing and lock-down measures as a localized early response to contain epidemic outbreaks.
| S-EPMC8189703 | biostudies-literature
Project description:Influenza infections are associated with thousands of hospital admissions and deaths each year. Rapid detection of influenza is important for prompt initiation of antiviral therapy and appropriate patient triage. In this study the Cepheid Xpert Flu assay was compared with two rapid antigen tests, BinaxNOW Influenza A & B and BD Directigen EZ Flu A+B, as well as direct fluorescent antibody testing for the rapid detection of influenza A and B. Using real-time, hydrolysis probe-based, reverse transcriptase PCR as the reference method, influenza A sensitivity was 97.3% for Xpert Flu, 95.9% for direct fluorescent antibody testing, 62.2% for BinaxNOW, and 71.6% for BD Directigen. Influenza B sensitivity was 100% for Xpert Flu and direct fluorescent antibody testing, 54.5% for BinaxNOW, and 48.5% for BD Directigen. Specificity for influenza A was 100% for Xpert Flu, BinaxNOW, and BD Directigen, and 99.2% for direct fluorescent antibody testing. All methods demonstrated 100% specificity for influenza B. These findings support the use of the Xpert Flu assay in settings requiring urgent diagnosis of influenza A and B.
| S-EPMC4075941 | biostudies-literature
Project description:BackgroundPreliminary evidence has shown inequities in coronavirus disease 2019 (COVID-19)-related cases and deaths in the United States.ObjectiveTo explore the emergence of spatial inequities in COVID-19 testing, positivity, confirmed cases, and mortality in New York, Philadelphia, and Chicago during the first 6 months of the pandemic.DesignEcological, observational study at the ZIP code tabulation area (ZCTA) level from March to September 2020.SettingChicago, New York, and Philadelphia.ParticipantsAll populated ZCTAs in the 3 cities.MeasurementsOutcomes were ZCTA-level COVID-19 testing, positivity, confirmed cases, and mortality cumulatively through the end of September 2020. Predictors were the Centers for Disease Control and Prevention Social Vulnerability Index and its 4 domains, obtained from the 2014-2018 American Community Survey. The spatial autocorrelation of COVID-19 outcomes was examined by using global and local Moran I statistics, and estimated associations were examined by using spatial conditional autoregressive negative binomial models.ResultsSpatial clusters of high and low positivity, confirmed cases, and mortality were found, co-located with clusters of low and high social vulnerability in the 3 cities. Evidence was also found for spatial inequities in testing, positivity, confirmed cases, and mortality. Specifically, neighborhoods with higher social vulnerability had lower testing rates and higher positivity ratios, confirmed case rates, and mortality rates.LimitationsThe ZCTAs are imperfect and heterogeneous geographic units of analysis. Surveillance data were used, which may be incomplete.ConclusionSpatial inequities exist in COVID-19 testing, positivity, confirmed cases, and mortality in 3 large U.S. cities.Primary funding sourceNational Institutes of Health.
| S-EPMC8029592 | biostudies-literature