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serological tests for coronavirus | 7 | [Sensitivity, specificity, predictive values in serological Covid-19 tests]. | ck8boz7i |
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serological tests for coronavirus | 7 | [Effect of heat inactivation of blood samples on the efficacy of three detection methods of SARS-CoV-2 antibodies]. | OBJECTIVE To evaluate the effects of heat inactivation of blood samples at 56℃ for 30 min on the results of SARS-CoV-2 antibody detection using different methods. METHODS This retrospective study was conducted in 11 patients with established diagnosis of COVID-19 and 10 patients with diseases other than COVID- 19 in our hospital. We collected samples of serum, plasma and whole blood from each patient between February, 12 and 18, 2020, and with a double- blind design, the samples were examined for SARS-CoV-2 antibodies before and after heat inactivation at 56 ℃ for 30 min. In all the samples, the total SARS-CoV-2 antibodies were detected using immunochromatography, and the IgM antibodies were detected using fluorescence immunochromatography; the IgM and IgG antibodies in the serum and plasma samples detected with chemiluminescence immunoassay. We compared the detection results and analyzed the correlation of semi-quantitative detection results of IgM and IgG antibodies before and after heat inactivation of the samples. RESULTS With immuno-chromatography, the coincidence rate of the total SARS-CoV-2 antibody detection before and after heat inactivation of the serum and plasma samples was 90.0% in COVID-19 cases and 100.0% in the negative cases, resulting in a total coincidence rate 95.2%; for the whole blood samples, the total coincidence rates of the total SARS-CoV-2 antibodies were 100.0%. For detection of IgM antibodies in the serum, plasma and whole blood samples using fluorescence immunochromatography, the coincidence rates in SARS-CoV-2-positive and negative cases and the total coincidence rate before and after inactivation were 100.0%, 0 and 47.6%, respectively. For detection of serum IgM and IgG antibodies and plasma IgG antibodies with chemiluminescence immunoassay, the coincidence rates in SARS-CoV-2-positive and negative cases and the total coincidence rate before and after inactivation were all 100.0%, and the total coincidence rate of plasma IgM antibodies was 95.2%. Pearson correlation analysis of the semi-quantitative results of IgM and IgG detection in the serum and plasma samples showed a correlation coefficient of 0.9999 (95%CI: 0.9998-1.000, P < 0.001) between the results before and after sample inactivation. CONCLUSIONS Heat inactivation of blood samples at 56 ℃ for 30 min does not obviously affect the results of immunochromatography and chemiluminescent immunoassay for detection of SARS-COV-2 antibodies but can reduce the risk of infection for the operators. Heat-inactivated samples can not be used in fluorescence immunochromatography for SARS-CoV-2 antibody detection. | ekytw2io |
serological tests for coronavirus | 7 | Association between SARS-CoV-2 neutralizing antibodies and commercial serological assays | Introduction Commercially available SARS-CoV-2 serological assays based on different viral antigens have been approved for the qualitative determination of anti-SARS-CoV-2 antibodies. However, there is limited published data associating the results from commercial assays with neutralizing antibodies. Methods 67 specimens from 48 patients with PCR-confirmed COVID-19 and a positive result by the Roche Elecsys SARS-CoV-2, Abbott SARS-CoV-2 IgG, or EUROIMMUN SARS-CoV-2 IgG assays and 5 control specimens were analyzed for the presence of neutralizing antibodies to SARS-CoV-2. Correlation, concordance, positive percent agreement (PPA), and negative percent agreement (NPA) were calculated at several cutoffs. Results were compared in patients categorized by clinical outcomes. Results The correlation between SARS-CoV-2 neutralizing titer (EC50) and the Roche, Abbott, and EUROIMMUN assays was 0.29, 0.47, and 0.46 respectively. At an EC50 of 1:32, the concordance kappa with Roche was 0.49 (95% CI; 0.23-0.75), with Abbott was 0.52 (0.28-0.77), and with EUROIMMUN was 0.61 (0.4-0.82). At the same neutralizing titer, the PPA and NPA for the Roche was 100% (94-100) & 56% (30-80); Abbott was 96% (88-99) & 69% (44-86); and EUROIMMUN was 91% (80-96) & 81% (57-93) for distinguishing neutralizing antibodies. Patients who died, were intubated, or had a cardiac injury from COVID-19 infection had significantly higher neutralizing titers relative to those with mild symptoms. Conclusion COVID-19 patients generate an antibody response to multiple viral proteins such that the calibrator ratios on the Roche, Abbott, and EUROIMMUN assays are all associated with SARS-CoV-2 neutralization. Nevertheless, commercial serological assays have poor NPA for SARS-CoV-2 neutralization, making them imperfect proxies for neutralization. | 38bz0acw |
serological tests for coronavirus | 7 | Clinical validation and performance evaluation of the automated Vitros Total Anti-SARS-CoV-2 Antibodies assay for screening of serostatus in COVID-19 | Objectives: Evaluation of serostatus against SARS-CoV-2 has emerged as an important tool in identification of exposure to COVID-19. We report on the validation of the Vitros Anti-SARS-CoV-2 Total (CoV2T) assay for qualitative serological testing of SARS-CoV-2 antibodies. Methods: We performed validation studies according to COLA guidelines, using samples previously tested for SARS-CoV-2 by RT-PCR. We evaluated precision, analytical interferences, and cross-reactivity with other viral infections. We also evaluated concordance with molecular and other serological testing, and evaluated seroconversion. Results: The Vitros CoV2T assay exhibited acceptable precision, was resistant to analytical interference, and did not exhibit cross-reactivity with samples positive for other respiratory viruses. The CoV2T assay exhibited 100% negative predictive agreement (56/56) and 71% positive predictive agreement (56/79) with RT-PCR across all patient samples, and was concordant with other serological assays. Concordance with RT-PCR was 97% > 7 days after symptom onset. Conclusions: The Vitros CoV2T assay was successfully validated in our laboratory. We anticipate it will be a useful tool in screening for exposure to SARS-CoV-2, however, the use of the CoV2T and other serological assays in clinical management of COVID-19 patients is yet unknown, and must be evaluated in future studies. | 3hsptk9x |
serological tests for coronavirus | 7 | Indication for SARS-CoV-2 serology: first month follow-up | SARS-CoV-2 detection is mainly performed by RT-PCR but recently serological tests were made available. A first one month follow-up of the SARS-CoV-2 serology records was performed in our laboratory to precise the diversity and proportion of the SARS-CoV-2 serology test indications and to identify new valid indications (meningoencephalitis, vasculitis, etc) | 8fuj9td2 |
serological tests for coronavirus | 7 | Clinical Sensitivity and Interpretation of PCR and Serological COVID-19 Diagnostics for Patients Presenting to the Hospital | Introduction: The diagnosis of COVID-19 requires integration of clinical and laboratory data. SARS-CoV-2 diagnostic assays play a central role in diagnosis and have fixed technical performance metrics. Interpretation becomes challenging because the clinical sensitivity changes as the virus clears and the immune response emerges. Our goal was to examine the clinical sensitivity of two most common SARS-CoV-2 diagnostic test modalities, polymerase chain reaction (PCR) and serology, over the disease course to provide insight into their clinical interpretation in patients presenting to the hospital. Methods: A single-center, retrospective study. To derive clinical sensitivity of PCR, we identified 209 PCR-positive SARS-CoV-2 patients with multiple PCR test results (624 total PCR tests) and calculated daily sensitivity from date of symptom onset or first positive test. To calculate daily clinical sensitivity by serology, we utilized 157 PCR-positive patients with a total of 197 specimens tested by enzyme-linked immunosorbent assay for IgM, IgG, and IgA anti-SARS-CoV-2 antibodies. Results: Clinical sensitivity of PCR decreased with days post symptom onset with >90% clinical sensitivity during the first 5 days after symptom onset, 70-71% from days 9-11, and 30% at day 21. In contrast, serological sensitivity increased with days post symptom onset with >50% of patients seropositive by at least one antibody isotype after day 7, >80% after day 12, and 100% by day 21. Conclusion: PCR and serology are complimentary modalities that require time-dependent interpretation. Superimposition of sensitivities over time indicate that serology can function as a reliable diagnostic aid indicating recent or prior infection. | g0fam0fm |
serological tests for coronavirus | 7 | Evaluation of ELISA tests for the qualitative determination of IgG, IgM and IgA to SARS-CoV-2 | Serological assays for anti-SARS-CoV-2 antibodies are now of critical importance to support diagnosis, guide epidemiological intervention, and understand immune response to natural infection and vaccine administration. We developed and validated new anti-SARS-CoV-2 IgG, IgM and IgA ELISA tests (ENZY-WELL SARS-CoV-2 ELISA, DIESSE Diagnostica Senese S.p.a.) based on whole-virus antigens. We used a total of 553 serum samples including samples from COVID-19 suspected and confirmed cases, healthy donors, and patients positive for other infections or autoimmune conditions. Overall, the assays showed good concordance with the indirect immunofluorescence reference test in terms of sensitivity and specificity. Especially for IgG and IgA, we observed high sensitivity (92.5 and 93.6%, respectively); specificity was high (>96%) for all antibody types ELISAs. In addition, sensitivity was linked to the days from symptoms onset (DSO) due to the seroconversion window, and for ENZY-WELL SARS-CoV-2 IgG and IgA ELISAs resulted 100% in those samples collected after 10 and 12 DSO, respectively. The results showed that ENZY-WELL SARS-CoV-2 ELISAs may represent a valid option for both diagnostic and epidemiological purposes, covering all different antibody types developed in SARS-CoV-2 immune response. | 0w7tq79d |
serological tests for coronavirus | 7 | A how-to-guide to building a robust SARS-CoV-2 testing program at a university-based health system | When South Florida became a hotspot for COVID-19 disease in March 2020, we faced an urgent need to develop test capability to detect SARS-CoV-2 infection. We assembled a transdisciplinary team of knowledgeable and dedicated physicians, scientists, technologists and administrators, who rapidly built a multi-platform, PCR- and serology- based detection program, established drive-thru facilities and drafted and implemented guidelines that enabled efficient testing of our patients and employees. This process was extremely complex, due to the limited availability of needed reagents, but outreach to our research scientists and to multiple diagnostic laboratory companies and government officials enabled us to implement both FDA authorized and laboratory developed testing (LDT)-based testing protocols. We analyzed our workforce needs and created teams of appropriately skilled and certified workers, to safely process patient samples and conduct SARS-CoV-2 testing and contact tracing. We initiated smart test ordering, interfaced all testing platforms with our electronic medical record, and went from zero testing capacity, to testing hundreds of healthcare workers and patients daily, within three weeks. We believe our experience can inform the efforts of others, when faced with a crisis situation. | 23q7c15b |
serological tests for coronavirus | 7 | Seroprevalence of antibodies against SARS-CoV-2 among public community and health-care workers in Alzintan City of Libya | Abstract A study was conducted to determine the seroprevalence of antibodies against SARS-CoV-2 among public community and health care workers in Alzintan City, Libya. During the period from 2/4/2020 to 18/5/2020, a total of 219 blood samples were collected and analyzed for the presence of antibodies against SARS-CoV-2. Collection of samples were divided in two categories; random samples from public community and samples from health care workers belong to two Governmental hospitals and one private clinic. One Step Novel Coronavirus (COVID-19) IgM/IgG Antibody Test was used. Out of the 219 samples tested, 6 (2.74%) samples were seropositive for SARS-CoV-2. All health-care workers were tested negative. All positive cases were females and 5 of them aged between 44 to 75 years and one aged 32 years. The prevalence in young females ([≤]40 years) was 1.4% in total young females tested in the study and 1.75% in young females taken from public community. The prevalence in older females aged ( 40 years), was 11.1% in total females tested and 13.9% in females taken from public community. In conclusion, the preliminary investigation of SARS-CoV-2 revealed considerable prevalence in Alzintan City although the disease seems to be in its mild form. Active surveillance studies with high number of samples using both virological and serological tests are in urgent need. | b7dxkgo8 |
serological tests for coronavirus | 7 | Reliability of serological tests for COVID-19: Comparison of three immunochromatography test kits for SARS-CoV-2 antibodies. | Background: Several immunochromatographic serological test kits have been developed to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) specific antibodies, but their relative performance and potential clinical utility is unclear. Methods: Three commercially available serological test kits were evaluated using 99 serum samples collected from 29 patients diagnosed with coronavirus disease 2019 (COVID-19). Results: The IgM antibody-positive rates of the three serological test kits for samples taken at the early stage of the disease (0-6 days after onset) were 19.0%, 23.8%, and 19.0%, respectively. The IgM antibody-positive rates over the entire period were 21.2%, 60.6%, and 15.2%, respectively. The IgG antibody-positive rates for samples taken after 13 days of onset were 100.0%, 97.6%, and 97.6%, respectively. Conclusion: There were large differences among the results of the three test kits. Only few cases showed positive results for IgM in the early stage of disease and the IgM antibody-positive rates over the entire period were low, suggesting that the kits used in this study were unsuitable for diagnosis of COVID-19. The IgG antibody was positive in almost all samples after 13 days of onset, suggesting that it may be useful for determining infections in the recent past. | fn9t38as |
serological tests for coronavirus | 7 | Joint Detection of Serum IgM/IgG Antibody is An Important Key to Clinical Diagnosis of SARS-COV-2 Infection | Background: This study was aimed to investigate the application of SARS- COV-2 IgM and IgG antibodies in diagnosis of COVID-19 infection. Method: This study enrolled a total of 178 patients at Huangshi Central Hospital from January to February, 2020. Among them, 68 patients were SARS-COV-2 infected confirmed with nucleic acid test (NAT) and CT imaging. 9 patients were in the suspected group (NAT negative) with fever and other respiratory symptoms. 101 patients were in the control group with other diseases and negative to SARS-COV-2 infection. After serum samples were collected, SARS-COV-2 IgG and IgM antibodies were tested by chemiluminescence immunoassay (CLIA) for all patients. Results: The specificity of serum IgM and IgG antibodies to SARS-COV-2 were 99.01% (100/101) and 96.04% (97/101) respectively, and the sensitivity were 88.24% (60/68) and 97.06% (66/68) respectively. The combined detection rate of SARS-COV-2 IgM and IgG antibodies were 98.53% (67/68). Conclusion: Combined detection of serum SARS-COV-2 IgM and IgG antibodies had better sensitivity compared with single IgM or IgG test, which can be used as an important diagnostic tool for SARS-COV-2 infection and a screening tool of potential SARS-COV-2 carriers in clinics, hospitals and accredited scientific laboratory. | 60vmohgq |
serological tests for coronavirus | 7 | Comparative assessment of multiple COVID-19 serological technologies supports continued evaluation of point-of-care lateral flow assays in hospital and community healthcare settings | There is a clear requirement for an accurate SARS-CoV-2 antibody test, both as a complement to existing diagnostic capabilities and for determining community seroprevalence. We therefore evaluated the performance of a variety of antibody testing technologies and their potential as diagnostic tools. A highly specific in-house ELISA was developed for the detection of anti-spike (S), -receptor binding domain (RBD) and -nucleocapsid (N) antibodies and used for the cross-comparison of ten commercial serological assays - a chemiluminescence-based platform, two ELISAs and seven colloidal gold lateral flow immunoassays (LFIAs) - on an identical panel of 110 SARS-CoV-2-positive samples and 50 pre-pandemic negatives. There was a wide variation in the performance of the different platforms, with specificity ranging from 82% to 100%, and overall sensitivity from 60.9% to 87.3%. However, the head to head comparison of multiple serodiagnostic assays on identical sample sets revealed that performance is highly dependent on the time of sampling, with sensitivities of over 95% seen in several tests when assessing samples from more than 20 days post onset of symptoms. Furthermore, these analyses identified clear outlying samples that were negative in all tests, but were later shown to be from individuals with mildest disease presentation. Rigorous comparison of antibody testing platforms will inform the deployment of point of care technologies in healthcare settings and their use in the monitoring of SARS-CoV-2 infections. | c2bwky6e |
serological tests for coronavirus | 7 | Evaluation of the performance of SARS-CoV-2 serological tools and their positioning in COVID-19 diagnostic strategies | Rapid and accurate diagnosis is crucial for successful outbreak containment. During the current coronavirus disease 2019 (COVID-19) public health emergency, the gold standard for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection diagnosis is the detection of viral RNA by reverse transcription (RT)-PCR. Additional diagnostic methods enabling the detection of current or past SARS-CoV-2 infection would be highly beneficial to ensure the timely diagnosis of all infected and recovered patients. Here, we investigated several serological tools, i.e., two immunochromatographic lateral flow assays (LFA-1 (Biosynex COVID-19 BSS) and LFA-2 (COVID-19 Sign IgM/IgG)) and two enzyme-linked immunosorbent assays (ELISAs) detecting IgA (ELISA-1 Euroimmun), IgM (ELISA-2 EDI) and/or IgG (ELISA-1 and ELISA-2) based on well-characterized panels of serum samples from patients and healthcare workers with PCR-confirmed COVID-19 and from SARS-CoV-2-negative patients. A total of 272 serum samples were used, including 62 serum samples from hospitalized patients (panel 1 and panel 3), 143 serum samples from healthcare workers (panel 2) diagnosed with COVID-19 and 67 serum samples from negative controls. Diagnostic performances of each assay were assessed according to days after symptom onset (dso) and the antigenic format used by manufacturers. We found overall sensitivities ranging from 69% to 93% on panels 1 and 2 and specificities ranging from 83% to 98%. The clinical sensitivity varied greatly according to the panel tested and the dso. The assays we tested showed poor mutual agreement. A thorough selection of serological assays for the detection of ongoing or past infections is advisable. | chuaqnl2 |
serological tests for coronavirus | 7 | A preliminary study on analytical performance of serological assay for SARS-CoV-2 IgM/IgG and application in clinical practice | Objective: To investigate the performance of serological test and dynamics of serum antibody with the progress of SARS-CoV-2 infections. Methods: A total of 419 patients were enrolled including 19 confirmed cases and 400 patients from fever clinics. Their serial serum samples collected during the hospitalization were menstruated for IgM and IgG against SARS-CoV-2 using gold immunochromatographic assay and chemiluminescence immunoassay. We investigated whether thermal inactivation could affect the results of antibody detection. The dynamics of antibodies with the disease progress and false positive factors for antibody testing were also analyzed. Results: The positive rate of IgG detection was 91.67% and 83.33% using two CLIA, respectively. However, the IgM positive rate was dramatically declined might due to the lack of blood samples at early stages of the disease. The chemiluminescence immunoassay had a favorable but narrow linear range. Our work showed increased IgG values in serums from virus-negative patients and four negative samples were IgG weak-positive after thermal incubation. Our data showed the specificity of viral N+S proteins was higher than single antigen. Unlike generally thought that IgM appeared earlier than IgG, there is no certain chronological order of IgM and IgG seroconversion in COVID-19 patients. It was difficult to detect antibodies in asymptomatic patients suggesting that their low viral loads were not enough to cause immune response. Analysis of common interferent in three IgG false-positive patients, such as rheumatoid factor, proved that false positives were not caused by these interfering substances and antigenic cross-reaction. Conclusions: Viral serological test is an effective means for SARS-CoV-2 infect detection using both chemiluminescence immunoassay and gold immunochromatographic assay. Chemiluminescence immunoassay against multi-antigens has obvious advantages but still need improve in reducing false positives. | bboi6l69 |
serological tests for coronavirus | 7 | SARS-CoV-2-specific antibody detection for sero-epidemiology: a multiplex analysis approach accounting for accurate seroprevalence | Background The COVID-19 pandemic demands detailed understanding of the kinetics of antibody production induced by infection with SARS-CoV-2. We aimed to develop a high throughput multiplex assay to detect antibodies to SARS-CoV-2 to assess immunity to the virus in the general population. Methods Spike protein subunits S1 and RBD, and Nucleoprotein were coupled to distinct microspheres. Sera collected before the emergence of SARS-CoV-2 (N=224), and of non-SARS-CoV-2 influenza-like illness (N=184), and laboratory-confirmed cases of SARS-CoV-2 infection (N=115) with various severity of COVID-19 were tested for SARS-CoV-2-specific concentrations of IgG. Results Our assay discriminated SARS-CoV-2-induced antibodies and those induced by other viruses. The assay obtained a specificity between 95.1 and 99.0% with a sensitivity ranging from 83.6-95.7%. By merging the test results for all 3 antigens a specificity of 100% was achieved with a sensitivity of at least 90%. Hospitalized COVID-19 patients developed higher IgG concentrations and the rate of IgG production increased faster compared to non-hospitalized cases. Conclusions The bead-based serological assay for quantitation of SARS-CoV-2-specific antibodies proved to be robust and can be conducted in many laboratories. Finally, we demonstrated that testing of antibodies against different antigens increases sensitivity and specificity compared to single antigen-specific IgG determination. | 0beno5o5 |
serological tests for coronavirus | 7 | Validation of a commercially available SARS-CoV-2 serological Immunoassay | Aims: To validate the diagnostic accuracy of a Euroimmun SARS-CoV-2 IgG and IgA immunoassay for COVID-19 disease. Methods: In this unmatched (1:1) case-control validation study, we used sera of 181 laboratory-confirmed SARS-CoV-2 cases and 176 negative controls collected before the emergence of SARS-CoV-2. Diagnostic accuracy of the immunoassay was assessed against a whole spike protein-based recombinant immunofluorescence assay (rIFA) by receiver operating characteristic (ROC) analyses. Discrepant cases between ELISA and rIFA were further tested by pseudo-neutralization assay. Results: COVID-19 patients were more likely to be male and older than controls, and 50.3% of them were hospitalized. ROC curve analyses indicated that IgG and IgA had a high diagnostic accuracy with AUCs of 0.992 (95% Confidence Interval [95%CI]: 0.986-0.996) and 0.977 (95%CI: 0.963-0.990), respectively. IgG assays outperformed IgA assays (p=0.008). Considering optimized cut-offs taking the 15% inter-assay imprecision assessed into account, an IgG ratio cut-off > 1.5 displayed a 100% specificity (95%CI: 98-100) and a 100% positive predictive value (95%CI: 97-100). A 0.5 cut-off displayed a 97% sensitivity (95%CI: 93-99) and a 97% negative predictive value (95%CI: 93-99). Adopting these thresholds, rather than those of the manufacturer, improved assay performance, leaving 12% of IgG ratios ranging between 0.5-1.5 as indeterminate. Conclusions: The Euroimmun assay displays a nearly optimal diagnostic accuracy using IgG against SARS-CoV-2 in a samples of patients, without any obvious gains from considering IgA serology. The optimized cut-offs are fit for rule-in and rule-out purposes, allowing determination of whether individuals have been exposed to SARS-CoV-2 or not in our study population. They should however not be considered as a surrogate of protection at this stage. | 0dgmfeak |
serological tests for coronavirus | 7 | Correlation of ELISA based with random access serologic immunoassays for identifying adaptive immune response to SARS-CoV-2 | Public health emergency of SARS-CoV-2 has facilitated diagnostic testing as a related medical countermeasure against COVID-19 outbreak. Numerous serologic antibody tests have become available through an expedited federal emergency use only process. This paper highlights the analytical characteristic of an ELISA based assay by AnshLabs and three random access immunoassay (RAIA) by DiaSorin, Roche, and Abbott that have been approved for emergency use authorization (EUA), at a tertiary academic center in a low disease-prevalence area. The AnshLabs gave higher estimates of sero-prevalence, over the three RAIA methods. For positive results, AnshLabs had 93.3% and 100% concordance with DiaSorin or Abbott and Roche respectively. For negative results, AnshLabs had 69.7% and 73.0% concordance with DiaSorin and Roche or Abbott respectively. All discrepant samples that were positive by AnshLabs and negative by RAIA tested positive by all-in-one step SARS-CoV-2 Total (COV2T) assay performed on the automated Siemens Advia Centaur XPT analyzer. None of these methods, however, are useful in early diagnosis of SARSCoV- 2. | 4vr4cm1s |
serological tests for coronavirus | 7 | Estimating Force of Infection from Serologic Surveys with Imperfect Tests | The force of infection, or the rate at which susceptible individuals become infected, is an important public health measure for assessing the extent of outbreaks and the impact of control programs. Here we present methods for estimating force of infection from serological surveys of infections which produce lasting immunity, taking into account imperfections in the test used, and uncertainty in such imperfections. The methods cover both single serological surveys, in which age is a proxy for time at risk, and repeat surveys in the same people, in which the force of infection is estimated more directly. Fixed values can be used for the sensitivity and specificity of the tests, or existing methods for belief elicitation can be used to include uncertainty in these values. The latter may be applicable, for example, when the specificity of a test depends on co-circulating pathogens, which may not have been well characterized in the setting of interest. We illustrate the methods using data from two published serological studies of dengue. | 7w3mvhqa |
serological tests for coronavirus | 7 | Rapid response flow cytometric assay for the detection of antibody responses to SARS-CoV-2 | SARS-CoV-2 has emerged as a previously unknown zoonotic coronavirus that spread worldwide causing a serious pandemic. While reliable nucleic acid-based diagnostic assays were rapidly available, there exists only a limited number of validated serological assays. Here, we evaluated a novel flow cytometric approach based on antigen-expressing HEK 293T cells to assess spike-specific IgG and IgM antibody responses. Analyses of 201 pre-COVID-19 sera proved a high assay specificity in comparison to commercially available CLIA and ELISA systems, while also revealing the highest sensitivity in specimens from PCR-confirmed SARS-CoV-2 infected patients. Additionally, a soluble Angiotensin-Converting-Enzyme 2 (ACE-2) variant was established as external standard to quantify spike-specific antibody responses on different assay platforms. In conclusion, our newly established flow cytometric assay allows sensitive and quantitative detection of SARS-CoV-2-specific antibodies, which can be easily adopted in different laboratories and does not rely on external supply of assay kits. | 2r9jlejw |
serological tests for coronavirus | 7 | Laboratory diagnosis of SARS. | The emergence of new viral infections of man requires the development of robust diagnostic tests that can be applied in the differential diagnosis of acute illness, or to determine past exposure, so as to establish the true burden of disease. Since the recognition in April 2003 of the severe acute respiratory syndrome coronavirus (SARS-CoV) as the causative agent of severe acute respiratory syndrome (SARS), enormous efforts have been applied to develop molecular and serological tests for SARS which can assist rapid detection of cases, accurate diagnosis of illness and the application of control measures. International progress in the laboratory diagnosis of SARS-CoV infection during acute illness has led to internationally agreed World Health Organization criteria for the confirmation of SARS. Developments in the dissection of the human immune response to SARS indicate that serological tests on convalescent sera are essential to confirm SARS infection, given the sub-optimal predictive value of molecular detection tests performed during acute SARS illness. | 7ayg3typ |
serological tests for coronavirus | 7 | Monoclonal antibody-based antigen capture enzyme-linked immunosorbent assay reveals high sensitivity of the nucleocapsid protein in acute-phase sera of severe acute respiratory syndrome patients. | Accurate and timely diagnosis of severe acute respiratory syndrome coronavirus (SARS-CoV) infection is a critical step in preventing another global outbreak. In this study, 829 serum specimens were collected from 643 patients initially reported to be infected with SARS-CoV. The sera were tested for the N protein of SARS-CoV by using an antigen capture enzyme-linked immunosorbent assay (ELISA) based on monoclonal antibodies against the N protein of SARS-CoV and compared to 197 control serum samples from healthy donors and non-SARS febrile patients. The results of the N protein detection analysis were directly related to the serological analysis data. From 27 SARS patients who tested positive with the neutralization test, 100% of the 24 sera collected from 1 to 10 days after the onset of symptoms were positive for the N protein. N protein was not detected beyond day 11 in this group. The positive rates of N protein for sera collected at 1 to 5, 6 to 10, 11 to 15, and 16 to 20 days after the onset of symptoms for 414 samples from 298 serologically confirmed patients were 92.9, 69.8, 36.4, and 21.1%, respectively. For 294 sera from 248 serological test-negative patients, the rates were 25.6, 16.7, 9.3, and 0%, respectively. The N protein was not detected in 66 patients with cases of what was initially suspected to be SARS but serologically proven to be negative for SARS and in 197 serum samples from healthy donors and non-SARS febrile patients. The specificity of the assay was 100%. Furthermore, of 16 sera collected from four patients during the SARS recurrence in Guangzhou, 5 sera collected from 7 to 9 days after the onset of symptoms were positive for the N protein. N protein detection exhibited a high positive rate, 96 to 100%, between day 3 and day 5 after the onset of symptoms for 27 neutralization test-positive SARS patients and 298 serologically confirmed patients. The N protein detection rate continually decreased beginning with day 10, and N protein was not detected beyond day 19 after the onset of symptoms. In conclusion, an antigen capture ELISA reveals a high N protein detection rate in acute-phase sera of patients with SARS, which makes it useful for early diagnosis of SARS. | 8e8h7bo3 |
serological tests for coronavirus | 7 | Use of antibody avidity assays for diagnosis of severe acute respiratory syndrome coronavirus infection. | An indirect immunofluorescent assay (Euroimmun AG, Luebeck, Germany) was used to investigate the avidity of immunoglobulin G (IgG), IgM, IgA, and total Ig (IgGAM) antibody responses to severe acute respiratory syndrome coronavirus (SARS CoV) infections. Serial serum samples from eight patients collected during the first, third, and ninth months after the onset of infection were evaluated. It was found that low-avidity IgG antibodies were detected in 15/15 (100%), 1/5 (20%), and 0/8 (0%) serum samples collected during the first, third, and ninth months after the onset of symptoms, respectively. Low-avidity antibodies of IgA and IgM subclasses were detected in 14/14 (100%) and 3/14 (21%) serum samples, respectively, collected in the first month after the onset of infection. However, IgA antibodies remained low in avidity in a proportion of patients even during late convalescence. As a consequence, IgG antibody avidity assays gave better discrimination between acute-phase and late-convalescent-phase serum samples than IgM, IgA, or IgGAM assays. In two of these patients, sequential serum samples were also tested for IgG avidity against human CoV strains OC43 and 229E in parallel. While SARS CoV infections induced an anamnestic IgG antibody response to the 229E and OC43 viruses, these cross-reactive antibodies remained of high avidity from early (the first month) postinfection. The results showed that assays to detect low-avidity antibody may be useful for discriminating early from late antibody responses and also for distinguishing anamnestic cross-reactive antibody responses from primary specific responses. This may be useful in some clinical situations. | 4rbtif2y |
serological tests for coronavirus | 7 | Specific serology for emerging human coronaviruses by protein microarray. | We present a serological assay for the specific detection of IgM and IgG antibodies against the emerging human coronavirus hCoV-EMC and the SARS-CoV based on protein microarray technology. The assay uses the S1 receptor-binding subunit of the spike protein of hCoV-EMC and SARS-CoV as antigens. The assay has been validated extensively using putative cross-reacting sera of patient cohorts exposed to the four common hCoVs and sera from convalescent patients infected with hCoV-EMC or SARS-CoV. | 79bzd4nl |
serological tests for coronavirus | 7 | Detection of specific antibodies to severe acute respiratory syndrome (SARS) coronavirus nucleocapsid protein for serodiagnosis of SARS coronavirus pneumonia. | We report the evaluation of recombinant severe acute respiratory syndrome (SARS) coronavirus (SARS-CoV) nucleocapsid protein enzyme-linked immunosorbent assay (ELISA)-based antibody tests for serodiagnosis of SARS-CoV pneumonia and compare the sensitivities and specificities of this ELISA for detection of immunoglobulin G (IgG), IgM, IgA, and their combinations with serum samples from 149 healthy blood donors who donated blood 3 years ago as controls and 106 SARS-CoV pneumonia patients in Hong Kong. The specificities of the ELISA for IgG, IgM, and IgA detection were 95.3, 96.6, and 96.6%, respectively, with corresponding sensitivities of 94.3, 59.4, and 60.4%, respectively. The present ELISA appears to be a sensitive test for serodiagnosis of SARS-CoV pneumonia, is much more economical and less labor-intensive than the indirect immunofluorescence assay, and does not require cultivation of SARS-CoV. | b1qnfl41 |
serological tests for coronavirus | 7 | Laboratory Tests for COVID-19: A Review of Peer-Reviewed Publications and Implications for Clinical UIse. | Diagnostic tests for the coronavirus infection 2019 (COVID-19) are critical for prompt diagnosis, treatment and isolation to break the cycle of transmission. A positive real-time reverse-transcriptase polymerase chain reaction (RT-PCR), in conjunction with clinical and epidemiologic data, is the current standard for diagnosis, but several challenges still exist. Serological assays help to understand epidemiology better and to evaluate vaccine responses but they are unreliable for diagnosis in the acute phase of illness or assuming protective immunity. Serology is gaining attention, mainly because of convalescent plasma gaining importance as treatment for clinically worsening COVID-19 patients. We provide a narrative review of peer-reviewed research studies on RT-PCR, serology and antigen immune-assays for COVID-19, briefly describe their lab methods and discuss their limitations for clinical practice. | ey34e59f |
serological tests for coronavirus | 7 | [Rapid point-of-care serology testing for sars-cov-2]. | Increasing evidence indicates immunity against severe acute respiratory syndrome coronavirus 2 (sars-cov-2) after covid-19, but it remains unclear for how long the protection remains. Serology testing seems to have a higher sensitivity than molecular diagnostics from 8 days after onset of symtoms, and should be part of risk assessment and epidemiological studies of COVID-19. The performance of commercial serological point-of-care (POC) lateral flow tests are highly manufacturer-dependant. Low sensitivity increases the risk of false negative results and could result in unnecessary quarantine of test persons with developed antibodies. Low specificity increases the risk of false positive results and could lead to false assumptions of immunity. Carefully selected serological POC tests for sars-cov-2 can be used in large scale testing but should only be used by licensed medical staff able to understand their limitations and interpret the results. | 91872v0l |
serological tests for coronavirus | 7 | Use of viral lysate antigen combined with recombinant protein in Western immunoblot assay as confirmatory test for serodiagnosis of severe acute respiratory syndrome. | A Western immunoblot assay for confirmatory serodiagnosis of severe acute respiratory syndrome (SARS) was developed utilizing viral lysate antigens combined with a recombinant nucleocapsid protein, GST-N (glutathione S-transferase-nucleocapsid) of the SARS coronavirus (SARS-CoV). The viral lysate antigens were separated by electrophoresis and transblotted onto nitrocellulose membranes. The resultant membrane was subsequently added with the GST-N recombinant protein at a specific location. The positions of bands corresponding to some of the structural proteins immobilized on the membrane were then located and verified with mouse or rabbit antisera specific to the respective proteins. The Western immunoblot assay was able to detect antibodies to SARS-CoV in all 40 serum specimens from SARS patients and differentiate the SARS-positive samples from those of the healthy donor or non-SARS patient controls (150 samples) when set criteria were followed. In addition, when the immunoblot was used to test samples considered falsely positive by an in-house-developed SARS-specific enzyme-linked immunosorbent assay, band patterns different from those with samples from SARS patients were obtained. | bkp5pvir |
serological tests for coronavirus | 7 | Comparison of serologic assays for measurement of antibody response to coronavirus in cats. | Serologic virus neutralization tests, indirect immunofluorescence tests, and ELISA, using tissue culture-adapted feline infectious peritonitis virus (FIPV) or feline enteric coronavirus (FECV) were compared for their ability to distinguish specific virus exposure in cats. Sera of specific-pathogen-free cats inoculated with virulent or modified FIPV or FECV were used to compare the sensitivity and specificity of the homologous assays to a heterologous assay that measures antibody reactivity with transmissible gastroenteritis virus of swine. The geometric means of the serologic titers in FIPV and FECV assays were higher for FIPV- or FECV-infected specific-pathogen-free cats than the geometric means of the transmissible gastroenteritis virus assays for most groups. None of the assays was specific enough to discern the virus to which a cat had been exposed. However, the FIPV virus neutralization test appeared to be more sensitive for detection of an early response to FIPV infection than did the FIPV immunofluorescence test or FIPV-ELISA. | 8g5s381b |
serological tests for coronavirus | 7 | Detection of coronavirus 229E antibody by indirect hemagglutination. | Tannic-acid treated sheep erythrocytes (fresh or glutaraldehyde preserved) were sensitized with 229E antigens from human embryonic lung (RU-1) cell cultures. Indirect hemagglutination (IHA) antigen titers in 229E-infected cell cultures paralleled virus infectivity and complement fixation (CF) antigen titers. The identity of the IHA antigen was confirmed by testing extracts from inoculated and control cell cultures for ability to inhibit IHA. Also, significant increases in IHA antibody were demonstrated with acute and convalescent serum pairs from patients with proven 229E infections. A comparison of IHA, neutralization and CF titers for 229E antibodies was made on human sera drawn from different populations. The IHA and neutralization results were in agreement on 93% of the 129 sera found to be positive by at least one of three tests. The number of antibody titers detected by the CF test was insufficient to permit comparison. Hyperimmune sera from animals immunized with OC 43 did not react with 229E by IHA. Also no increase in IHA antibody was demonstrated with acute and convalescent serum pairs from patients with seroconversions to OC 43. These findings suggest that the IHA test provides (i) a rapid and sensitive method for serodiagnosis of 229E infections and (ii) a simple and inexpensive method for seroepidemiological studies. | cy10ei1c |
serological tests for coronavirus | 7 | The value of hospital personnel serological screening in an integrated COVID-19 infection prevention and control strategy | 2sytrto5 |
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serological tests for coronavirus | 7 | Antikörpertests bei COVID-19 - Was uns die Ergebnisse sagen./ [Antibody tests for COVID-19: What the results tell us] | INTRODUCTION: In the context of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, the detection of virus-specific antibodies (AB) will play an increasing role. The presence or absence of such antibodies can potentially lead to considerations regarding immunity and infection. ISSUE: How reliable are inferences from positive or negative test results regarding the actual presence of SARS-CoV-2 specific antibodies? METHODS: Calculation of the probability that, depending on the pretest probability (prevalence of SARS-CoV-2 infection) and test properties, antibodies are present or absent in the case of positive or negative test results. RESULTS: Sensitivity and specificity of different SARS-CoV-2 AB test systems vary between 53 % and 94 % and between 91 % and 99.5 %, respectively. When using a test with high test quality, the positive predictive value (PPV) is 42 % and 7 9%, respectively, with a pre-test probability of 1 % to 5 %, as can currently be assumed for the general population in Austria or Germany. For persons with an increased pre-test probability of 20 %, e. g. persons from high-risk professions, the PPW is 95 %, with a pre-test probability of 80 % the PPW is almost 100 %. The negative predictive value (NPV) is at least 99.7 % for persons with a low pre-test probability of up to 5 % and 79.1 % for persons with a pre-test probability of 80 %. When using test systems with lower sensitivity and specificity, the reliability of the results decreases considerably. The PPV is 5.9 % with a pre-test probability of 1 %. CONCLUSIONS: A sufficiently high sensitivity and specificity are prerequisites for the application of antibody test systems. Positive test results are often false if the pre-test probability is low. Depending on the assumed prevalence of a SARS-CoV-2 infection, there are substantial differences in the significance of a concrete test result for the respective affected persons. | 4bdn6xje |
serological tests for coronavirus | 7 | Covid-19: Antibody tests will not be rolled out in UK until at least May, MPs hear | 7agfi6ao |
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serological tests for coronavirus | 7 | Diagnostic value and dynamic variance of serum antibody in coronavirus disease 2019 | OBJECTIVE: To investigate the diagnostic value of serological testing and dynamic variance of serum antibody in coronavirus disease 2019 (COVID-19). METHODS: This study retrospectively included 43 patients with a laboratory-confirmed infection and 33 patients with a suspected infection, in whom the disease was eventually excluded. The IgM/IgG titer of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was measured by chemiluminescence immunoassay analysis. RESULTS: Compared to molecular detection, the sensitivities of serum IgM and IgG antibodies to diagnose COVID-19 were 48.1% and 88.9%, and the specificities were 100% and 90.9%, respectively.In the COVID-19 group, the IgM-positive rate increased slightly at first and then decreased over time; in contrast, the IgG-positive rate increased to 100% and was higher than IgM at all times. The IgM-positive rate and titer were not significantly different before and after conversion to virus-negative. The IgG-positive rate was up to 90% and not significantly different before and after conversion to virus-negative. However, the median IgG titer after conversion to virus-negative was double that before, and the difference was significant. CONCLUSIONS: Viral serological testing is an effective means of diagnosis for SARS-CoV-2 infection. The positive rate and titer variance of IgG are higher than those of IgM in COVID-19. | 5ig5upot |
serological tests for coronavirus | 7 | Prevalence of SARS-CoV-2 in Spain (ENE-COVID): a nationwide, population-based seroepidemiological study | BACKGROUND: Spain is one of the European countries most affected by the COVID-19 pandemic. Serological surveys are a valuable tool to assess the extent of the epidemic, given the existence of asymptomatic cases and little access to diagnostic tests. This nationwide population-based study aims to estimate the seroprevalence of SARS-CoV-2 infection in Spain at national and regional level. METHODS: 35â883 households were selected from municipal rolls using two-stage random sampling stratified by province and municipality size, with all residents invited to participate. From April 27 to May 11, 2020, 61â075 participants (75·1% of all contacted individuals within selected households) answered a questionnaire on history of symptoms compatible with COVID-19 and risk factors, received a point-of-care antibody test, and, if agreed, donated a blood sample for additional testing with a chemiluminescent microparticle immunoassay. Prevalences of IgG antibodies were adjusted using sampling weights and post-stratification to allow for differences in non-response rates based on age group, sex, and census-tract income. Using results for both tests, we calculated a seroprevalence range maximising either specificity (positive for both tests) or sensitivity (positive for either test). FINDINGS: Seroprevalence was 5·0% (95% CI 4·7-5·4) by the point-of-care test and 4·6% (4·3-5·0) by immunoassay, with a specificity-sensitivity range of 3·7% (3·3-4·0; both tests positive) to 6·2% (5·8-6·6; either test positive), with no differences by sex and lower seroprevalence in children younger than 10 years (<3·1% by the point-of-care test). There was substantial geographical variability, with higher prevalence around Madrid (>10%) and lower in coastal areas (<3%). Seroprevalence among 195 participants with positive PCR more than 14 days before the study visit ranged from 87·6% (81·1-92·1; both tests positive) to 91·8% (86·3-95·3; either test positive). In 7273 individuals with anosmia or at least three symptoms, seroprevalence ranged from 15·3% (13·8-16·8) to 19·3% (17·7-21·0). Around a third of seropositive participants were asymptomatic, ranging from 21·9% (19·1-24·9) to 35·8% (33·1-38·5). Only 19·5% (16·3-23·2) of symptomatic participants who were seropositive by both the point-of-care test and immunoassay reported a previous PCR test. INTERPRETATION: The majority of the Spanish population is seronegative to SARS-CoV-2 infection, even in hotspot areas. Most PCR-confirmed cases have detectable antibodies, but a substantial proportion of people with symptoms compatible with COVID-19 did not have a PCR test and at least a third of infections determined by serology were asymptomatic. These results emphasise the need for maintaining public health measures to avoid a new epidemic wave. FUNDING: Spanish Ministry of Health, Institute of Health Carlos III, and Spanish National Health System. | d8ddjzon |
serological tests for coronavirus | 7 | Comparison of four new commercial serologic assays for determination of SARS-CoV-2 IgG | BACKGROUND: Facing the ongoing pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there is an urgent need for serological assays identifying individuals with past coronavirus disease 2019 (COVID-19). STUDY DESIGN: Our study is the first to compare four new commercially available assays using 75 sera from patients tested positive or negative by SARS-CoV-2 PCR: the anti SARS-CoV-2 ELISA (IgG) (Euroimmun, Germany), the EDI New Coronavirus COVID-19 IgG ELISA, (Epitope diagnostics (EDI), USA), the recomWell SARS-CoV-2 IgG ELISA (Mikrogen, Germany), and the SARS-CoV-2 Virachip IgG (Viramed, Germany). RESULTS: We found a sensitivity of 86.4 %, 100 %, 86.4 %, and 77.3 % and a specificity of 96,2 %, 88,7 %, 100 %, and 100 % for the Euroimmun assay, the EDI assay, the Mikrogen assay, and the Viramed assay, respectively. CONCLUSIONS: Commercially available SARS-CoV-2 IgG assays have a sufficient specificity and sensitivity for identifying individuals with past SARS-CoV-2 infection. | 7e79o2gy |
serological tests for coronavirus | 7 | Serology assays to manage COVID-19 | 31qbazhh |
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serological tests for coronavirus | 7 | The receptor binding domain of the viral spike protein is an immunodominant and highly specific target of antibodies in SARS-CoV-2 patients | The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that first emerged in late 2019 is responsible for a pandemic of severe respiratory illness. People infected with this highly contagious virus can present with clinically inapparent, mild, or severe disease. Currently, the virus infection in individuals and at the population level is being monitored by PCR testing of symptomatic patients for the presence of viral RNA. There is an urgent need for SARS-CoV-2 serologic tests to identify all infected individuals, irrespective of clinical symptoms, to conduct surveillance and implement strategies to contain spread. As the receptor binding domain (RBD) of the spike protein is poorly conserved between SARS-CoVs and other pathogenic human coronaviruses, the RBD represents a promising antigen for detecting CoV-specific antibodies in people. Here we use a large panel of human sera (63 SARS-CoV-2 patients and 71 control subjects) and hyperimmune sera from animals exposed to zoonotic CoVs to evaluate RBD's performance as an antigen for reliable detection of SARS-CoV-2-specific antibodies. By day 9 after the onset of symptoms, the recombinant SARS-CoV-2 RBD antigen was highly sensitive (98%) and specific (100%) for antibodies induced by SARS-CoVs. We observed a strong correlation between levels of RBD binding antibodies and SARS-CoV-2 neutralizing antibodies in patients. Our results, which reveal the early kinetics of SARS-CoV-2 antibody responses, support using the RBD antigen in serological diagnostic assays and RBD-specific antibody levels as a correlate of SARS-CoV-2 neutralizing antibodies in people. | 4cqjqwk9 |
serological tests for coronavirus | 7 | Analysis of the diagnostic value of serum specific antibody testing for coronavirus disease 2019 | The coronavirus disease 2019 (COVID-19) pandemic has spread to various regions worldwide. As of 27 April 2020, according to real-time statistics released by the World Health Organization, there have been 84,341 confirmed cases and 4,643 deaths in China, with more than 2,979,484 confirmed cases and 206,450 deaths outside China. The detection of antibodies produced during the immune response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has become an important laboratory method for the diagnosis of COVID-19. However, at present, little research on these specific antibodies has been conducted. In this study, retrospective analysis was used to explore the dynamic changes of serum IgM and IgG antibody and factors affecting diagnostic efficacy, so as to provide a theoretical basis for clinical diagnosis and treatment. This article is protected by copyright. All rights reserved. | 40txr2du |
serological tests for coronavirus | 7 | Comparison of test performance of commercial anti-SARS-CoV-2 immunoassays in serum and plasma samples | BACKGROUND: For epidemiologic, social and economic reasons, assessment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection prevalence and immunity are important to adapt decisions to current demands. Hence, immunoassays for detection of anti-SARS-CoV-2 antibodies are introduced rapidly without requiring FDA emergency use authorization approval. Thus, evaluation of test performance predominantly relies on laboratories. This study aimed to evaluate the test performance of recently launched commercial immunoassays in serum and plasma samples. METHODS: 51 serum samples from 26 patients with confirmed SARS-CoV-2 infection after end of quarantine and 25 control patients were analyzed using anti-SARS-CoV-2 IgG immunoassays from Roche, Euroimmun and Epitope to assess diagnostic sensitivity and specificity. 20 matching pairs of serum and plasma samples were included to analyze comparability between different specimens. RESULTS: Overall, a diagnostic sensitivity of 92.3%, 96.2-100% and 100% with a respective diagnostic specificity of 100%, 100% and 84-86% for the immunoassays from Roche, Euroimmun and Epitope were determined. In total, 84-96 % of samples were correctly classified as negative and 92.3-95.2% as positive. The level of concordance between plasma- and serum-based testing diverged between the assays (Epitope r2=0.97; Euroimmun r2=0.91; Roche r2=0.76). CONCLUSIONS: The immunoassays from Euroimmun and Roche revealed a higher specificity than the Epitope assay without a substantial drop of diagnostic sensitivity. Significant differences between plasma- and serum-based testing highlights the need for determination of appropriate cut-offs per specimen type. Hence, there is an urgent need for test harmonization and establishment of quality standards for an appropriate use of COVID-19 serological tests. | bis8m5f0 |
coronavirus under reporting | 8 | COVID-19-New Insights on a Rapidly Changing Epidemic. | 63aoc5vp |
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coronavirus under reporting | 8 | COVID-19 Fatality Rate and Performed Swabs in Italy: a Misleading Perception. | BACKGROUND CoronaVirus Disease 2019 (COVID-19) fatality rate in Italy is controversial and is largely affecting discussion on the impact of containment measures that are straining the world's social and economic fabric, such as large-scale use of isolation and quarantine, closing borders, imposing limits on public gatherings, and implementing nationwide lockdowns. OBJECTIVE The scientific community, citizens, politicians and mass media are arguing over data that seem to suggest that Italy has a significantly higher number of COVID-19-related deaths than in the rest of the world. Moreover, Italian citizens have a misleading perception related to the number of actually performed swab tests. Citizens and mass media denounce that the coverage obtained by COVID-19 swab testing in Italy is not in line with other countries all over the world. METHODS In this paper, we try to clarify, with a set of statistical analysis conducted world-wide, both aspects by highlighting the actual numbers and by comparing them with the official data available. RESULTS The analysis clearly shows that the Italian COVID-19 fatality and mortality rate are in line with the official world scenario, and these findings are true also for the number of COVID-19 swabs performed in Italy and in Lombardy Region. CONCLUSIONS Up-to-date analysis of this type may simplify the understanding of the pandemic evolution. CLINICALTRIAL | 8esaz4or |
coronavirus under reporting | 8 | Covid-19: "Illogical" lack of testing is causing healthy staff to self-isolate, BMA chief warns. | 5tpbb765 |
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coronavirus under reporting | 8 | Underestimation of COVID-19 cases in Japan: an analysis of RT-PCR testing for COVID-19 among 47 prefectures in Japan. | BACKGROUND Under the unique Japanese policy to restrict reverse transcriptase-polymerase chain reaction (RT-PCR) testing against severe acute respiratory syndrome coronavirus 2, a nationwide number of its confirmed cases and mortality remains to be low. Yet the information is lacking on geographical differences of these measures and their associated factors. AIM Evaluation of prefecture-based geographical differences and associated predictors for the incidence and number of RT-PCR tests for COVID-19. DESIGN Cross-sectional study using regression and correlation analysis. METHODS We retrieved domestic laboratory-confirmed cases, deaths, and the number of RT-PCR testing for COVID-19 from January 15 to April 6, 2020 in 47 prefectures in Japan, using publicly-available data by the Ministry of Health, Labour and Welfare. We did descriptive analyses of these three measures and identified significant predictors for the incidence and RT-PCR testing through multiple regression analyses and correlates with the number of deaths through correlation analysis. RESULTS The median prefectural-level incidence and number of RT-PCR testing per 100,000 population were 1.14 and 38.6, respectively. Multiple regression analyses revealed that significant predictors for the incidence were prefectural-level population (p < 0.001) and the number of RT-PCR testing (p = 0.03); and those for RT-PCR testing were the incidence (p = 0.025), available beds (p = 0.045) and cluster infections (p = 0.034). CONCLUSION Considering bidirectional association between the incidence and RT-PCR testing, there may have been an underdiagnosed population for the infection. The restraint policy for RT-PCR testing should be revisited to meet the increasing demand under the COVID-19 epidemic. | 7gmacx72 |
coronavirus under reporting | 8 | Transmission in Latent Period Causes A Large Number of Infected People in the United States | By April 29, 2020, the cumulative number of confirmed cases in the United States has exceeded one million, becoming the country with the most serious pandemic in the world. It is urgent to analyze the real situation and follow-up trend of the epidemic in the United States. The proposed model divides the time period into two different phases, before and after March 21, 2020. The results show that the basic reproduction number in the early period of propagation in the United States is estimated to be 4.06 (95% CI: 1.86-6.73) based on the confirmed cases data ranging from January 21, 2020 to March 21, 2020. The normalized contributions to R_0 for three different categories of communicators were estimated, including the numbers of the latent population (in incubation period) L, the documented infectious population Id, and the undocumented infectious population Iu. The results show that L contributes 16.17% (95% CI: 12.86% - 21.60%) to R_0, Id contributes 55.13% (95% CI: 43.15% - 63.97%), and Iu contributes 28.70% (95% CI: 19.29% - 40.07%) to R0. The metapopulation network was used to simulate the true spread of COVID-19 in the United States, and the Bayesian inference was applied to estimate the key parameters including the rate of the number of the susceptibles and the infected beta, the infection ratio between undocumented and documented transmission 1, the infection ratio between latent and documented transmission 2, the proportion of confirmed cases in the infectious population x, and the duration of latent period (incubation period) TL . From the analysis of phase one, 1 was estimated to be 0.40 (95% CI: 0.17 - 0.54), 2 was estimated to be 0.06 (95% CI: 0.02 - 0.11), x was estimated to be 0.70 (95% CI: 0.55 - 0.78), T_L was estimated to be 8.41 (95% CI: 6.64 - 9.42). As of April 13, 2020, it was estimated that only 45% (95% CI: 35% - 73%) of symptom onset cases in the United States have been documnented. The infectivity of undocumented infectious population was 0.59 (95% CI: 0.21 - 0.70) of that of the documented infectious population, while that of the latent population was 0.19 (95% CI: 0.11 - 0.27) of that of the documented infectious population. The incubation period of COVID-19 was estimated to be 10.69 days (95% CI: 10.02 - 11.74). We estimated that if the current control interventions are continued, the pandemic situation in the United States is likely to keep climbing up, and the cumulative number of confirmed cases is expected to reach more than 1.7 million in July and continue to grow. We also performed component analysis and sensitivity analysis, researching the compositions of the people with COVID-19, and considering that there is only a random time delay between the number of patients in the incubation period and the actual number of patients. | nkrwyq89 |
coronavirus under reporting | 8 | COVID-19: Recovering estimates of the infected fatality rate during an ongoing pandemic through partial data | In an ongoing epidemic, the case fatality rate is not a reliable estimate of a disease's severity. This is particularly so when a large share of asymptomatic or pauci-symptomatic patients escape testing, or when overwhelmed healthcare systems are forced to limit testing further to severe cases only. By leveraging data on COVID-19, we propose a novel way to estimate a disease's infected fatality rate, the true lethality of the disease, in the presence of sparse and partial information. We show that this is feasible when the disease has turned into a pandemic and data comes from a large number of countries, or regions within countries, as long as testing strategies vary sufficiently. For Italy, our method estimates an IFR of 1.1% (95% CI: 0.2% - 2.1%), which is strongly in line with other methods. At the global level, our method estimates an IFR of 1.6% (95% CI: 1.1% - 2.1%). This method also allows us to show that the IFR varies according to each country's age structure and healthcare capacity. | a1c7bfr4 |
coronavirus under reporting | 8 | COVID-19 Spread in India: Dynamics, Modeling, and Future Projections | COVID-19 is an extremely infectious disease with a relatively large virus incubation period in the affected people who may be asymptomatic. Therefore, to reduce the transmission of this pathogen, several countries have taken many intervention measures. In this paper, we show that the impact of these measures in India is different from several other countries. It is shown that an early lockdown in late March 2020 changed the initial exponential growth curve of COVID-19 to a linear one, but a surge in the number of cases from late April 2020 brought India back to a quadratic trajectory. A regional analysis shows the disparate impact of the intervention in different states. It is further shown that the number of reported infections correlates with the number of tests, and therefore regions with limited diagnostics resources may not have a realistic estimate of the virus spread. This insufficiency of diagnostic test data is also reflected in an increasing positivity rate for India nearly 2.5 months after the lockdown, inconsistent with the trends observed for other geographical regions. Nonetheless, future projections are made using different epidemiological models based on the available data, and a comparative study is presented. In the absence of a reliable estimate of the true number of infections, these projections will have a limited accuracy: with that limitation, the most optimistic prediction suggests a continuing virus transmission through September 2020. | qk5z84xd |
coronavirus under reporting | 8 | Reconciling early-outbreak estimates of the basic reproductive number and its uncertainty: framework and applications to the novel coronavirus (SARS-CoV-2) outbreak | A novel coronavirus (SARS-CoV-2) has recently emerged as a global threat. As the epidemic progresses, many disease modelers have focused on estimating the basic reproductive number Ro -- the average number of secondary cases caused by a primary case in an otherwise susceptible population. The modeling approaches and resulting estimates of Ro vary widely, despite relying on similar data sources. Here, we present a novel statistical framework for comparing and combining different estimates of Ro across a wide range of models by decomposing the basic reproductive number into three key quantities: the exponential growth rate $r$, the mean generation interval $\bar G$, and the generation-interval dispersion $\kappa$. We then apply our framework to early estimates of Ro for the SARS-CoV-2 outbreak. We show that many early Ro estimates are overly confident. Our results emphasize the importance of propagating uncertainties in all components of Ro, including the shape of the generation-interval distribution, in efforts to estimate Ro at the outset of an epidemic. | p5aj5k2g |
coronavirus under reporting | 8 | Maybe not an overreaction | 3imi635m |
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coronavirus under reporting | 8 | Multi-parametric disease dynamics study and analysis of the COVID-19 epidemic and implementation of population-wide intrusions: The Indian perspective | The outbreak of COVID-19 had spread at a deadly rate since its onset at Wuhan, China and is now spread across 216 countries and has affected more than 6 million people all over the world. The global response throughout the world has been primarily the implementation of lockdown measures, testing and contact tracing to minimise the spread of the disease. The aim of the present study was to predict the COVID-19 prevalence and disease progression rate in Indian scenario in order to provide an analysis that can shed light on comprehending the trends of the outbreak and outline an impression of the epidemiological stage for each state of a diverse country like India. In addition, the forecast of COVID-19 incidence trends of these states can help take safety measures and policy design for this epidemic in the days to come. In order to achieve the same, we have utilized an approach where we test modelling choices of the spatially unambiguous kind, proposed by the wave of infections spreading from the initial slow progression to a higher curve. We have estimated the parameters of an individual state using factors like population density and mobility. The findings can also be used to strategize the testing and quarantine processes to manipulate the spread of the disease in the future. This is especially important for a country like India that has several limitations about healthcare infrastructure, diversity in socioeconomic status, high population density, housing conditions, health care coverage that can be important determinants for the overall impact of the pandemic. The results of our 5-phase model depict a projection of the state wise infections/disease over time. The model can generate live graphs as per the change in the data values as the values are automatically being fetched from the crowd-sourced database. | g8pu6x4c |
coronavirus under reporting | 8 | Covid-19 prevalence estimation by random sampling in the wider population - Optimal sample pooling under varying assumptions about true prevalence | The number of confirmed Covid-19 cases in a population is used as a coarse measurement for the burden of disease. However, this number depends heavily on the sampling intensity and the various test criteria used in different jurisdictions. A wide range of sources indicate that a large fraction of cases go undetected. Estimates of the true prevalence of Covid-19 can be made by random sampling in the wider population. Here we use simulations to explore confidence intervals of prevalence estimates under different sampling intensities and degrees of sample pooling. | zbax2vk7 |
coronavirus under reporting | 8 | Reconstructing the global dynamics of under-ascertained COVID-19 cases and infections | Background: Asymptomatic or subclinical SARS-CoV-2 infections are often unreported, which means that confirmed case counts may not accurately reflect underlying epidemic dynamics. Understanding the level of ascertainment (the ratio of confirmed symptomatic cases to the true number of symptomatic individuals) and undetected epidemic progression is crucial to informing COVID-19 response planning, including the introduction and relaxation of control measures. Estimating case ascertainment over time allows for accurate estimates of specific outcomes such as seroprevalence, which is essential for planning control measures. Methods: Using reported data on COVID-19 cases and fatalities globally, we estimated the proportion of symptomatic cases (i.e. any person with any of fever >= to 37.5C, cough, shortness of breath, sudden onset of anosmia, ageusia or dysgeusia illness) that were reported in 210 countries and territories, given those countries had experienced more than ten deaths. We used published estimates of the case fatality ratio (CFR) as an assumed baseline. We then calculated the ratio of this baseline CFR to an estimated local delay-adjusted CFR to estimate the level of under-ascertainment in a particular location. We then fit a Bayesian Gaussian process model to estimate the temporal pattern of under-ascertainment. Results: We estimate that, during March 2020, the median percentage of symptomatic cases detected across the 84 countries which experienced more than ten deaths ranged from 2.38% (Bangladesh) to 99.6% (Chile). Across the ten countries with the highest number of total confirmed cases as of 6th July 2020, we estimated that the peak number of symptomatic cases ranged from 1.4 times (Chile) to 17.8 times (France) larger than reported. Comparing our model with national and regional seroprevalence data where available, we find that our estimates are consistent with observed values. Finally, we estimated seroprevalence for each country. Despite low case detection in some countries, our results that adjust for this still suggest that all countries have had only a small fraction of their populations infected as of July 2020. Conclusions: We found substantial under-ascertainment of symptomatic cases, particularly at the peak of the first wave of the SARS-CoV-2 pandemic, in many countries. Reported case counts will therefore likely underestimate the rate of outbreak growth initially and underestimate the decline in the later stages of an epidemic. Although there was considerable under-reporting in many locations, our estimates were consistent with emerging serological data, suggesting that the proportion of each country's population infected with SARS-CoV-2 worldwide is generally low. | no0xh7t0 |
coronavirus under reporting | 8 | A novel comprehensive metric to assess COVID-19 testing outcomes: Effects of geography, government, and policy response | Testing and case identification are key strategies in controlling the COVID-19 pandemic. Contact tracing and isolation are only possible if cases have been identified. The effectiveness of testing must be tracked, but a single comprehensive metric is not available to assess testing effectiveness, and no timely estimates of case detection rate are available globally, making inter-country comparisons difficult. The purpose of this paper was to propose a single, comprehensive metric, called the COVID-19 Testing Index (CovTI) scaled from 0 to 100, that incorporated several testing metrics. The index was based on case-fatality rate, test positivity rate, active cases, and an estimate of the detection rate. It used parsimonious modeling to estimate the true total number of COVID-19 cases based on deaths, testing, health system capacity, and government transparency. Publicly reported data from 188 countries and territories were included in the index. Estimates of detection rates aligned with previous estimates in literature (R2=0.97). As of June 3, 2020, the states with the highest CovTI included Iceland, Australia, New Zealand, Hong Kong, and Thailand, and some island nations. Globally, CovTI increased from April 20 ([x]=43.2) to June 3 ([x]=52.2) but declined in ca. 10% of countries. Bivariate analyses showed the average in countries with open public testing policies (59.7, 95% CI 55.6-63.8) were significantly higher than countries with no testing policy (30.2, 95% CI 18.1-42.3) (p<0.0001). A multiple linear regression model assessed the association of independent grouping variables with CovTI. Open public testing and extensive contact tracing were shown to significantly increase CovTI, after adjusting for extrinsic factors, including geographic isolation and centralized forms of government. This tool may be useful for policymakers to assess testing effectiveness, inform decisions, and identify model countries. It may also serve as a tool for researchers in analyses by combining it with other databases. | 6ed3two6 |
coronavirus under reporting | 8 | Early trends for SARS-CoV-2 infection in central and north Texas and impact on other circulating respiratory viruses | Introduction: Rapid diagnosis and isolation are key to containing the rapid spread of a pandemic agent like SARS-CoV-2, which has spread globally since its initial outbreak in Wuhan province in China. SARS-CoV-2 is novel to most parts of the world including USA and the effect on normally prevalent viruses is just becoming apparent. We present our initial data on the prevalence of respiratory viruses in the month of March, 2020. Methods: This is a retrospective cohort study post launching of SARS-CoV-2 testing at BSWH, Temple TX. Testing for SARS-CoV-2 was performed by real-time RT-PCR assay and results were shared with State public health officials for immediate interventions. Results: More than 3500 tests were performed during the first two weeks of testing for SARS-CoV-2 and identified 168 (4.7%) positive patients. Sixty-two (3.2%) of the 1,912 ambulatory patients and 106 (6.3%) of the 1,659 ED/inpatients were tested positive. Higher rate of infection (6.9%) were noted in the patients belonging to age group 25-34 years and least number of positive cases were noted in <25 years old (2%) group. The TX State county specific patient demographic information was shared with respective public health departments for epidemiological interventions. Incidentally, this study showed that there was a sudden decrease in the occurrence of other infections due to seasonal viruses, perhaps due to increased epidemiological awareness, about SARS-CoV-2, among general public. Authors would also like to share a small study on SARS-CoV-2 serological assay for the detection of IgG antibodies. Conclusions: This study was intended to provide an initial experience of dealing with a pandemic and the role of laboratories in crisis management. Epidemiological interventions depend on timely availability of accurate diagnostic tests and throughput capacity of such systems during large outbreaks like SARS-CoV-2. | 5fz8ef4f |
coronavirus under reporting | 8 | Bayesian nowcasting with adjustment for delayed and incomplete reporting to estimate COVID-19 infections in the United States | Real-time estimates of the true size and trajectory of local COVID-19 epidemics are key metrics to guide policy responses. We developed a Bayesian nowcasting approach that explicitly accounts for reporting delays and secular changes in case ascertainment to generate real-time estimates of COVID-19 epidemiology on the basis of reported cases and deaths. Using this approach, we estimate time trends in infections, symptomatic cases, and deaths for all 50 US states and the District of Columbia from early-March through June 11, 2020. At the beginning of June, our best estimates of the effective reproduction number (Rt) are close to 1 in most states, indicating a stabilization of incidence, but there is considerable variability in the level of incidence and the estimated proportion of the population that has already been infected. | bge7btzz |
coronavirus under reporting | 8 | Is tracking and modeling Covid-19 infection dynamics for Bangladesh using daily data feasible? | Given the low Covid-19 testing coverage in the country, this study tested whether the daily change in the number of new Covid-19 cases is due to increase (or decrease) in the number of tests done daily. We performed Granger causality test based on vector autoregressive models on Bangladesh case and test numbers between 8 March and 5 June 2020, using publicly available data. The test results show that the daily number of tests Granger-cause the number of new cases (p <0.001), meaning the daily number of new cases is perhaps due to an increase in test capacity rather than a change in the infection rates. From the results of this test we can infer that if the number of daily tests does not increase substantially, data on new infections will not give much information for understanding covid-19 infection dynamics in Bangladesh. | ettclw13 |
coronavirus under reporting | 8 | COVID-19: The unreasonable effectiveness of simple models | When the novel coronavirus disease SARS-CoV2 (COVID-19) was officially declared a pandemic by the WHO in March 2020, the scientific community had already braced up in the effort of making sense of the fast-growing wealth of data gathered by national authorities all over the world. However, despite the diversity of novel theoretical approaches and the comprehensiveness of many widely established models, the official figures that recount the course of the outbreak still sketch a largely elusive and intimidating picture. Here we show unambiguously that the dynamics of the COVID-19 outbreak belongs to the simple universality class of the SIR model and extensions thereof. Our analysis naturally leads us to establish that there exists a fundamental limitation to any theoretical approach, namely the unpredictable non-stationarity of the testing frames behind the reported figures. However, we show how such bias can be quantified self-consistently and employed to mine useful and accurate information from the data. In particular, we describe how the time evolution of the reporting rates controls the occurrence of the apparent epidemic peak, which typically follows the true one in countries that were not vigorous enough in their testing at the onset of the outbreak. The importance of testing early and resolutely appears as a natural corollary of our analysis, as countries that tested massively at the start clearly had their true peak earlier and less deaths overall. | nda1toup |
coronavirus under reporting | 8 | Time Course of COVID-19 epidemic in Algeria: Retrospective estimate of the actual burden | Since December 2019, the five continents have been incrementally invaded by SARS-CoV-2. Africa is the last and least affected to date. However, Algeria is among the first countries affected since February 25, 2020. In order to benefit from its experience in the least affected countries, this study aims to describe the current situation of the epidemic and then retrospectively estimate its real burden. As a first part of the study, we described the indicators of the epidemic as; the cumulative and daily reported cases and deaths, and we computed the R0 evolution. Secondly, we used the New York City cases-fatality rate standardized by Algerian age structure, to retrospectively estimate the actual burden. We found that reported cases are in a clear diminution, but, the epidemic epicentre is moving from Blida to other cities. We noted a clear peak in daily cases-fatality from March 30, to April 17, 2020, Fig. 3, due to underestimating the actual infections of the first 25 days. Since May 8, 2020, the daily R0 is around one, Fig. 4. Moreover, we noticed 31% reduction of its mean value from 1,41 to 0,97 between the last two months. The Algerian Age-Standardized Infection Fatality Rate we found is 0,88%. Based on that, we demonstrated that only 1,5% of actual infections were detected and reported before March 30, and 20% after March 31, Fig. 5. Therefore, the actual infections burden is currently five times higher than reported. At the end, we found that at least 0,2 % of the population have been infected until May 27. Consequently, the acquired herd immunity to date is therefore not sufficient to avoid a second wave. We believe that, the under estimation of the actual burden of the epidemic is probably due to the lack of testing capacities, however, all the indicators show that the situation is currently controlled. This requires more vigilance for the next weeks during the gradual easing of the preventive measures. | pymowl6n |
coronavirus under reporting | 8 | Testing for tracing or testing just for treating? A comparative analysis between strategies to face COVID-19 pandemic. | There is some consensus in Europe and Asia about testing rates being crucial to controlling COVID-19 pandemics. There are though misconceptions on what means an effective high testing rate. This paper demonstrates that the rate of tests per detected case (Tests/Case) is the important variable, correlating negatively with the number of deaths. The higher the Tests/Case rate, the lower the death rate, as this predictor is causally related to contact tracing and isolation of the vectors of the disease. Doubling Tests/Case typically divides by three the number of deaths. On the other hand, per capita testing rate is a poor predictor for the performance of policies to fight the pandemics. The number of tests per 1,000 inhabitants (Tests/1,000) tends to correlate positively with the number of deaths. In some cases, high levels of Tests/1,000 just mean an epidemic that ran out of control, with an explosion of cases that demands high testing rates just to confirm the diagnosis of the very sick. | rjzther1 |
coronavirus under reporting | 8 | Estimation of SARS-CoV-2 Infection Prevalence in Santa Clara County | To reliably estimate the demand on regional health systems and perform public health planning, it is necessary to have a good estimate of the prevalence of infection with SARS-CoV-2 (the virus that causes COVID-19) in the population. In the absence of wide-spread testing, we provide one approach to infer prevalence based on the assumption that the fraction of true infections needing hospitalization is fixed and that all hospitalized cases of COVID-19 in Santa Clara are identified. Our goal is to estimate the prevalence of SARS-CoV-2 infections, i.e. the true number of people currently infected with the virus, divided by the total population size. Our analysis suggests that as of March 17, 2020, there are 6,500 infections (0.34% of the population) of SARS-CoV-2 in Santa Clara County. Based on adjusting the parameters of our model to be optimistic (respectively pessimistic), the number of infections would be 1,400 (resp. 26,000), corresponding to a prevalence of 0.08% (resp. 1.36%). If the shelter-in-place led to R0 < 1, we would expect the number of infections to remain about constant for the next few weeks. However, even if this were true, we expect to continue to see an increase in hospitalized cases of COVID-19 in the short term due to the fact that infection of SARS-CoV-2 on March 17th can lead to hospitalizations up to 14 days later. | 6vt60348 |
coronavirus under reporting | 8 | COVID-19 Antibody Seroprevalence in Santa Clara County, California | Background Addressing COVID-19 is a pressing health and social concern. To date, many epidemic projections and policies addressing COVID-19 have been designed without seroprevalence data to inform epidemic parameters. We measured the seroprevalence of antibodies to SARS-CoV-2 in Santa Clara County. Methods On 4/3-4/4, 2020, we tested county residents for antibodies to SARS-CoV-2 using a lateral flow immunoassay. Participants were recruited using Facebook ads targeting a representative sample of the county by demographic and geographic characteristics. We report the prevalence of antibodies to SARS-CoV-2 in a sample of 3,330 people, adjusting for zip code, sex, and race/ethnicity. We also adjust for test performance characteristics using 3 different estimates: (i) the test manufacturer's data, (ii) a sample of 37 positive and 30 negative controls tested at Stanford, and (iii) a combination of both. Results The unadjusted prevalence of antibodies to SARS-CoV-2 in Santa Clara County was 1.5% (exact binomial 95CI 1.11-1.97%), and the population-weighted prevalence was 2.81% (95CI 2.24-3.37%). Under the three scenarios for test performance characteristics, the population prevalence of COVID-19 in Santa Clara ranged from 2.49% (95CI 1.80-3.17%) to 4.16% (2.58-5.70%). These prevalence estimates represent a range between 48,000 and 81,000 people infected in Santa Clara County by early April, 50-85-fold more than the number of confirmed cases. Conclusions The population prevalence of SARS-CoV-2 antibodies in Santa Clara County implies that the infection is much more widespread than indicated by the number of confirmed cases. Population prevalence estimates can now be used to calibrate epidemic and mortality projections. | zpv5f8pr |
coronavirus under reporting | 8 | New blood tests for antibodies could show true scale of coronavirus pandemic | How many COVID-19 cases have gone undetected? And are those who had mild cases of the disease—perhaps so mild they dismissed it as a cold or allergies—immune to new infections? If so, they could slow the spread of the burgeoning pandemic Labs and companies around the world have raced to develop antibody tests, and a few have been used in small studies and received commercial approval, including several from China But so far, large-scale data from such tests—for example showing what fraction of people in the hard-hit city of Wuhan, China, might now be immune—is still lacking or at least not public Scientists hope that will soon change as more tests become available | ecxji8x8 |
coronavirus under reporting | 8 | Substantial underestimation of SARS-CoV-2 infection in the United States due to incomplete testing and imperfect test accuracy | Accurate estimates of the burden of SARS-CoV-2 infection are critical to informing pandemic response. Current confirmed COVID-19 case counts in the U.S. do not capture the total burden of the pandemic because testing has been primarily restricted to individuals with moderate to severe symptoms due to limited test availability. Using a semi-Bayesian probabilistic bias analysis to account for incomplete testing and imperfect diagnostic accuracy, we estimated 6,275,072 cumulative infections compared to 721,245 confirmed cases (1.9% vs. 0.2% of the population) as of April 18, 2020. Accounting for uncertainty, the number of infections was 3 to 20 times higher than the number of confirmed cases. 86% (simulation interval: 64-99%) of this difference was due to incomplete testing, while 14% (0.3-36%) was due to imperfect test accuracy. Estimates of SARS-CoV-2 infections that transparently account for testing practices and diagnostic accuracy reveal that the pandemic is larger than confirmed case counts suggest. | ehcikhnw |
coronavirus under reporting | 8 | On the true numbers of COVID-19 infections: behind the available data | In December-2019 China reported several cases of a novel coronavirus later called COVID-19. In this work, we will use a probabilistic method for approximating the true daily numbers of infected. Based on two distribution functions to describe the spontaneous recovered cases on the one hand and the detected cases on the other hand. The impact of the underlying variables of these functions is discussed. The detected rate is predicted to be between 5.3% and 10,8%, which means that there would be about 38 million infected until now (10-May 2020), rather than the officially declared number of 3.99 million worldwide cases. | o66rchhw |
coronavirus under reporting | 8 | Estimation of Undetected Covid-19 Infections in India | Background and Objectives: While the number of detected COVID-19 infections are widely available, an understanding of the extent of undetected COVID- 19 cases is urgently needed for an effective tackling of the pandemic and as a guide to lifting the lockdown. The aim of this work is to estimate and predict the true number of COVID-19 (detected and undetected) infections in India for short to medium forecast horizons. In particular, using publicly available COVID-19 infection data upto 16th April 2020, we predict the true number of infections in India during and upto the end of the formal lockdown period (21st April 2020). Methods: The high death rate observed in most COVID-19 hit countries is suspected to be a function of the undetected infections existing in the population. An estimate of the age weighted infection fatality rate (IFR) of the disease of 0.41%, specifically calculated by taking into account the age structure of Indian population, is already available in the literature. In addition, the recorded case fatality rate (CFR= 0.70%) of Kerala, the only state in India to report single digit new infections over the second week of April, is used as a second estimate of the IFR. These estimates are used to formulate a relationship between deaths recorded and the true number of infections. The estimated undetected and detected cases time series based on these two IFR estimates are then used to fit a discrete time multivariate infection model to predict the total infections at the end of the formal lockdown period. Results: In two consecutive fortnights during the lockdown, it was noted that the rise in detected infections has decreased by 2.7 times. For an IFR of 0.41%, the rise in undetected infections decreased by 3.2 times and the predicted number of total infections in India is 3.14 lakhs. While for an IFR of 0.70%, the rise in undetected cases decreased by 3.3 times and the total number of infections predicted on 21st April is 1.75 lakhs. Interpretation and Conclusions: The behaviour of the undetected cases over time effectively illustrates the effects of lockdown and increased testing. From our estimates, it is found that the lockdown has brought down the undetected to detected cases ratio, and has consequently dampened the increase in the number of total cases. However, even though the rate of rise in total infections has fallen, the lifting of the lockdown should be done keeping in mind that 1.75 to 3 lakhs undetected cases will already exist in the population on 21st April. | t4d2ibng |
coronavirus under reporting | 8 | The usefulness of SARS-CoV-2 test positive proportion as a surveillance tool | Comparison of COVID-19 case numbers over time and between locations is complicated by limits to virologic testing confirm SARS-CoV-2 infection, leading to under-reporting of incidence, and by variations in testing capacity between locations and over time. The proportion of tested individuals who have tested positive (test positive proportion, TPP) can potentially be used to qualitatively assess the testing capacity of a location; a high TPP could provide evidence that too few people are tested, leading to more under-reporting. In this study we propose a simple model for testing in a population experiencing an epidemic of COVID-19, and derive an expression for TPP in terms of well-defined parameters in the model, related to testing and presence of other pathogens causing COVID-19 like symptoms. We use simulations to show situations in which the TPP is higher or lower than we expect based on these parameters, and the effect of testing strategies on the TPP. In our simulations, we find in the absence of dramatic shifts of testing practices in time or between spatial locations, the TPP is positively correlated with the incidence of infection. As a corollary, the TPP can be used to distinguish between a decline in confirmed cases due to decline in incidence (in which case TPP should decline) and a decline in confirmed cases due to testing constraints (in which case TPP should remain constant). We show that the proportion of tested individuals who present COVID-19 like symptoms (test symptomatic proportion, TSP) encodes similar information to the TPP but has different relationships with the testing parameters, and can thus provide additional information regarding dynamic changes in TPP and incidence. Finally, we compare data on confirmed cases and TPP from US states. We conjecture why states may have higher or lower TPP than average. We suggest that collection of symptom status and age/risk category of tested individuals can aid interpretation of changes in TPP and increase the utility of TPP in assessing the state of the pandemic in different locations and times. | ole70vk0 |
coronavirus under reporting | 8 | Estimating the global spread of COVID-19 | Limited and inconsistent testing and differences in age distribution, health care resources, social distancing, and policies have caused large variations in the extent and dynamics of the COVID-19 pandemic across nations, complicating the estimation of prevalence, the infection fatality rate (IFR), and other factors important to care providers and policymakers. Using data for all 84 countries with reliable testing data (spanning 4.75 billion people) we develop a dynamic epidemiological model integrating data on cases, deaths, excess mortality and other factors to estimate how asymptomatic transmission, disease acuity, hospitalization, and behavioral and policy responses to risk condition prevalence and IFR across nations and over time. For these nations we estimate IFR averages 0.68% (0.64%-0.7%). Cases and deaths through June 18, 2020 are estimated to be 11.8 and 1.48 times official reports, respectively, at 88.5 (85-95.3) million and 600 (586-622) thousand. Prevalence and IFR vary substantially, e.g., Ecuador (18%; 0.61%), Chile (15.5%; 0.57%), Mexico (8.8%; 0.69%), Iran (7.9%; 0.44%), USA (5.3%; 0.99%), UK (5.2%; 1.59%), Iceland (1.65%, 0.56%), New Zealand (0.1%, 0.64%), but all nations remain well below the level needed for herd immunity. By alerting the public earlier and reducing contacts, extensive testing when the pandemic was declared could have averted 35.3 (32.7-42.7) million cases and 197 (171-232) thousand deaths. However, future outcomes are less dependent on testing and more contingent on the willingness of communities and governments to reduce transmission. Absent breakthroughs in treatment or vaccination and with mildly improved responses we project 249 (186-586) million cases and 1.75 (1.40-3.67) million deaths in the 84 countries by Spring 2021. | 837qlk8y |
coronavirus under reporting | 8 | Estimating the true (population) infection rate for COVID-19: A Backcasting Approach with Monte Carlo Methods | Differences in COVID-19 testing and tracing across countries, as well as changes in testing within each country over time, make it difficult to estimate the true (population) infection rate based on the confirmed number of cases obtained through RNA viral testing. We applied a backcasting approach, coupled with Monte Carlo methods, to estimate a distribution for the true (population) cumulative number of infections (infected and recovered) for 15 countries where reliable data are available. We find a positive relationship between the testing rate per 1,000 people and the implied true detection rate of COVID-19, and a negative relationship between the proportion who test positive and the implied true detection rate. Our estimates suggest that the true number of people infected across our sample of 15 developed countries is 18.2 (5-95% CI: 11.9-39.0) times greater than the reported number of cases. In individual countries, the true number of cases exceeds the reported figure by factors that range from 1.7 (5-95% CI: 1.1-3.6) for Australia to 35.6 (5-95% CI: 23.2-76.3) for Belgium. | vq7k0gma |
coronavirus under reporting | 8 | Application of pooled testing in screening and estimating the prevalence of Covid-19 | The recent emergence of the COVID-19 pandemic has posed an unprecedented healthcare challenge and catastrophic economic and social consequences to the countries across the world. The situation is even worse for emerging economies like India. WHO recommends mass scale testing as one of the most effective ways to contain its spread and fight the pandemic. But, due to the high cost and shortage of test kits, specifically in India, the testing is restricted to only those who are symptomatic. In this context, pooled testing is recommended by some experts as a partial solution to overcome this problem. In this article, we explain the basic statistical theory behind the pooled testing procedure for screening as well as prevalence estimation. In real world situations, the tests are imperfect, and lead to false positive and false negative results. We provide theoretical explanation of the impact of these diagnostic errors on the performances of individual testing and pooled testing procedures. Finally, we study the effect of misspecification of sensitivity and specificity of tests on the estimate of prevalence, an issue, which is debated a lot among the scientists in the context of COVID-19. Our theoretical investigations lead to some interesting and precise understanding of some of these issues. | dbzpcy5v |
coronavirus under reporting | 8 | Coronavirus cases have dropped sharply in South Korea. What’s the secret to its success? | Europe is now the epicenter of the COVID-19 pandemic Case counts and deaths are soaring in Italy, Spain, France, and Germany, and many countries have imposed lockdowns and closed borders Meanwhile, the United States, hampered by a fiasco with delayed and faulty test kits, is just guessing at its COVID-19 burden, though experts believe it is on the same trajectory as countries in Europe | 722hm18k |
coronavirus under reporting | 8 | The Mathematics of Testing with Application to Prevalence of COVID-19 | We formulate three basic assumptions that should ideally guide any well-designed COVID-19 prevalence study. We provide, on the basis of these assumptions alone, a full derivation of mathematical formulas required for statistical analysis of testing data. In particular, we express the disease prevalence in a population through those for its homogeneous subpopulations. Although some of these formulas are routinely employed in prevalence studies, the study design often contravenes the assumptions upon which these formulas vitally depend. We also designed a natural prevalence estimator from the testing data and studied some of its properties. The results are equally valid for diseases other than COVID-19 as well as in non-epidemiological settings. | 39jcr69r |
coronavirus under reporting | 8 | SCALE19: A scalable and cost-efficient method for testing Covid-19 based on hierarchical group testing | Containment of Covid-19 requires an extensive testing of the affected population. Some propose global testing to effectively contain Covid-19. Current tests for Covid-19 are administered individually. These tests for Covid-19 are expensive and are limited due to the lack of resources and time. We propose a simple and efficient group testing method for Covid-19. We propose a group testing method where test subjects are grouped and tested. Depending on the result of the group test, subsequent sub groups are formed and tested recursively based on a quartery search algorithm. We designed and built an evaluation model that simulates test subject population, infected test subjects according to available Covid-19 statistics, and the group testing processes in SCALE19. We considered several population models including USA and the world. Our results show that we can significantly reduce the required number of tests up to 89% without sacrificing the accuracy of the individual test of the entire population. For USA, up to 280 million tests can be reduced from the total US population of 331 million and it would be equivalent saving of $28 billion assuming a cost of $100 per test. For the world, 6.96 billion tests can be reduced from the total population of 7.8 billion and it would be equivalent to saving $696 billion. We propose SCALE19 can significantly reduce the total required number of tests compared to individual tests of the entire population. We believe SCALE19 is efficient and simple to be deployed in containment of Covid-19. | 1bhv9snq |
coronavirus under reporting | 8 | Extrapolation of Infection Data for the CoVid-19 Virus and Estimate of the Pandemic Time Scale. | Predictions about the further development of the Corona pandemic are widely diverging. Here, a simple yet powerful algorithm is introduced for extrapolating infection rate and number of total infections from available data. The calculation predicts that under present conditions the infection rate in Germany will culminate in a few weeks and decrease to low values by mid-June 2020. Total number of infections will reach several 100,000 though. | kcx8cnco |
coronavirus under reporting | 8 | Bayesian modeling of COVID-19 cases with a correction to account for under-reported cases | The novel of COVID-19 disease started in late 2019 making the worldwide governments came across a high number of critical and death cases, beyond constant fear of the collapse in their health systems. Since the beginning of the pandemic, researchers and authorities are mainly concerned with carrying out quantitative studies (modeling and predictions) overcoming the scarcity of tests that lead us to under- reporting cases. To address these issues, we introduce a Bayesian approach to the SIR model with correction for under-reporting in the analysis of COVID-19 cases in Brazil. The proposed model was enforced to obtain estimates of important quantities such as the reproductive rate and the average infection period, along with the more likely date when the pandemic peak may occur. Several under-reporting scenarios were considered in the simulation study, showing how impacting is the lack of information in the modeling. | orh8fd1c |
coronavirus under reporting | 8 | Is reporting many cases of COVID-19 in Iran due to strength or weakness of iran’s health system? | ezfm64j9 |
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coronavirus under reporting | 8 | Influenza-Negative Influenza-Like Illness (fnILI) Z-Score as a Proxy for Incidence and Mortality of COVID-19 | Though ideal for determining the burden of disease, SARS-CoV2 test shortages preclude its implementation as a robust surveillance system in the US. We correlated the use of the derivative influenza-negative influenza-like illness (fnILI) z-score from the CDC as a proxy for incident cases and disease-specific deaths. For every unit increase of fnILI z-score, the number of cases increased by 70.2 (95%CI[5.1,135.3]) and number of deaths increased by 2.1 (95%CI[1.0,3.2]). FnILI data may serve as an accurate outcome measurement to track the spread of the and allow for informed and timely decision-making on public health interventions. | 6g7mijbz |
coronavirus under reporting | 8 | ‘These are answers we need.’ WHO plans global study to discover true extent of coronavirus infections | In an effort to understand how many people have been infected with the new coronavirus, the World Health Organization (WHO) is planning a coordinated study to test blood samples for the presence of antibodies to the virus Called Solidarity II, the program, which will involve more than half a dozen countries around the globe, will launch in the coming days, says Maria Van Kerkhove, who is helping coordinate WHO’s COVID-19 response Knowing the true number of cases—including mild ones—will help pin down the prevalence and mortality rate of COVID-19 in different age groups It will also help policymakers decide how long shutdowns and quarantines should last “These are answers we need, and we need the right answers to drive policy,” WHO’s executive director for health emergencies, Michael Ryan, told a press briefing on 27 March | 0klg8yvs |
coronavirus under reporting | 8 | Using viral genomics to estimate undetected infections and extent of superspreading events for COVID-19 | Asymptomatic infections and limited testing capacity have led to under-reporting of SARS-CoV-2 cases. This has hampered the ability to ascertain true infection numbers, evaluate the effectiveness of surveillance strategies, determine transmission dynamics, and estimate reproductive numbers. Leveraging both viral genomic and time series case data offers methods to estimate these parameters. Using a Bayesian inference framework to fit a branching process model to viral phylogeny and time series case data, we estimated time-varying reproductive numbers and their variance, the total numbers of infected individuals, the probability of case detection over time, and the estimated time to detection of an outbreak for 12 locations in Europe, China, and the United States. The median percentage of undetected infections ranged from 13% in New York to 92% in Shanghai, China, with the length of local transmission prior to two cases being detected ranging from 11 days (95% CI: 4-21) in California to 37 days (9-100) in Minnesota. The probability of detection was as low as 1% at the start of local epidemics, increasing as the number of reported cases increased exponentially. The precision of estimates increased with the number of full-length viral genomes in a location. The viral phylogeny was informative of the variance in the reproductive number with the 32% most infectious individuals contributing 80% of total transmission events. This is the first study that incorporates both the viral genomes and time series case data in the estimation of undetected COVID-19 infections. Our findings suggest the presence of undetected infections broadly and that superspreading events are contributing less to observed dynamics than during the SARS epidemic in 2003. This genomics-informed modeling approach could estimate in near real-time critical surveillance metrics to inform ongoing COVID-19 response efforts. | 1jf2zz5q |
coronavirus under reporting | 8 | The true case fatality of COVID19: An analytical solution | The exact risk of dying from COVID-19 has remained elusive and a topic of debate. The observed case fatality rates of 46 different countries are hypothesized to be dependent on their testing rates. An analytical test to this hypothesis suggests that the case fatality rate of COVID-19 could be consistent to a certain degree across all countries and states. The current global fatality rate is estimated to be around 1% and expected to converge between 1-3% when the pandemic ends. This model can be helpful to estimate the true infection rate for individual countries. | 2zf9rmbf |
coronavirus under reporting | 8 | Estimate of COVID-19 case prevalence in India based on surveillance data of patients with severe acute respiratory illness | In absence of extensive testing for SARS-CoV-2, true prevalence of COVID-19 cases in India remain unknown. In this study, a conservative estimate of prevalence of COVID-19 is calculated based on the age wise COVID-19 positivity rate among patients with severe respiratory illness as reported by Indian Council of Medical Research. Calculations in the study estimates a cumulative number of 17151 COVID-19 positive cases by the end of April 2, 2020. | 0gikppdh |
coronavirus under reporting | 8 | Disentangling Increased Testing From Covid-19 Epidemic Spread | To design effective disease control strategies, it is critical to understand the incidence of diseases. In the Covid-19 epidemic in the United States (caused by outbreak of the SARS-CoV-2 virus), testing capacity was initially very limited and has been increasing at the same time as the virus has been spreading. When estimating the incidence, it can be difficult to distinguish whether increased numbers of positive tests stem from increases in the spread of the virus or increases in testing. This has made it very difficult to identify locations in which the epidemic poses the largest public health risks. Here, we use a probabilistic model to quantify beliefs about testing strategies and understand implications regarding incidence. We apply this model to estimate the incidence in each state of the United States, and find that: (1) the Covid-19 epidemic is likely to be more widespread than reported by limited testing, (2) the Covid-19 epidemic growth in the summer months is likely smaller than it was during the spring months, and (3) the regions which are at highest risk of Covid-19 epidemic outbreaks are not always those with the largest number of positive test results. | l7jme343 |
coronavirus under reporting | 8 | Using early data to estimate the actual infection fatality ratio from COVID-19 in France | Background. The number of screening tests carried out in France and the methodology used to target the patients tested do not allow for a direct computation of the actual number of cases and the infection fatality ratio (IFR). The main objective was to estimate the actual number of people infected with COVID-19 during the observation window in France and to deduce the IFR. Methods. We develop a 'mechanistic-statistical' approach coupling a SIR epidemiological model describing the unobserved epidemiological dynamics, a probabilistic model describing the data acquisition process and a statistical inference method. Results. The actual number of infected cases in France is probably higher than the observations: we find here a factor x 8 (95%-CI: 5-12) which leads to an IFR in France of 0.5% (95%-CI: 0.3-0.8) based on hospital death counting data. Adjusting for the number of deaths in nursing homes, we obtain an IFR of 0.8% (95%-CI: 0.45-1.25). Conclusions. This IFR is consistent with previous findings in China (0.66%) and in the UK (0.9%) and lower than the value previously computed on the Diamond Princess cruse ship data (1.3%). | dqg8fkca |
coronavirus under reporting | 8 | Basic prediction methodology for covid-19: estimation and sensitivity considerations | The purpose of the present paper is to present simple estimation and prediction methods for basic quantities in an emerging epidemic like the ongoing covid-10 pandemic. The simple methods have the advantage that relations between basic quantities become more transparent, thus shedding light to which quantities have biggest impact on predictions, with the additional conclusion that uncertainties in these quantities carry over to high uncertainty also in predictions. A simple non-parametric prediction method for future cumulative case fatalities, as well as future cumulative incidence of infections (assuming a given infection fatality risk f), is presented. The method uses cumulative reported case fatalities up to present time as input data. It is also described how the introduction of preventive measures of a given magnitude ρ will affect the two incidence predictions, using basic theory of epidemic models. This methodology is then reversed, thus enabling estimation of the preventive magnitude ρ, and of the resulting effective reproduction number RE. However, the effects of preventive measures only start affecting case fatalities some 3-4 weeks later, so estimates are only available after this time has elapsed. The methodology is applicable in the early stage of an outbreak, before, say, 10% of the community have been infected. Beside giving simple estimation and prediction tools for an ongoing epidemic, another important conclusion lies in the observation that the two quantities f (infection fatality risk) and ρ (the magnitude of preventive measures) have very big impact on predictions. Further, both of these quantities currently have very high uncertainty: current estimates of f lie in the range 0.2% up to 2% ([9], [7]), and the overall effect of several combined preventive measures is clearly very uncertain. The two main findings from the paper are hence that, a) any prediction containing f, and/or some preventive measures, contain a large amount of uncertainty (which is usually not acknowledged well enough), and b) obtaining more accurate estimates of in particular f, should be highly prioritized. Seroprevalence testing of random samples in a community where the epidemic has ended are urgently needed. | hsgzkpg4 |
coronavirus under reporting | 8 | Testing for COVID-19: a few points to remember. | Diagnostic approaches to COVID-19 include clinical history, PCR tests for the presence of SARS-CoV-2 virus and detection of antibodies. By combining these three approaches, the seroprevalence of anti-SARS-CoV-2 antibodies can be examined in healthcare teams. The aim of the study was to examine the seroprevalence of anti-SARS-CoV-2 antibodies in a population of healthcare professionals 6 - 8 weeks after the first COVID-19 case was detected in the Czech Republic. A total of 269 subjects were enrolled in the study (187 women, 82 men) with a median age of 45.9 years (21 - 71 years). We used a questionnaire to ascertain travel history and clinical signs of any respiratory tract infection. Blood samples were collected, and IgG levels were analysed in all samples. The level of IgA antibodies was analysed in those positive for IgG. PCR testing was performed in cases testing positive for presence of antibodies. The enzyme-linked immunosorbent assay (ELISA) test system for SARS-CoV-2 from Euroimmun (Germany) was used to analyse immunoglobulin levels. 17 % of the tested cohort reported symptoms compatible with COVID-19 and 35.8 % reported history of international travel. There were 5 subjects positive IgG cases (of 269; 1.85 %), and one IgA positive and IgG borderline positive subject (0.37 %). There was only one PCR positive subject. Anti SARS-CoV-2 antibodies were thus detected in 2.22% of participating health professionals. This article shows the pitfalls of the testing methods and highlights the necessity of using a correct testing algorithm, considering the character of the tested population and the expected low prevalence. | 6gar1zyl |
coronavirus under reporting | 8 | Counting Coronavirus Disease 2019 (COVID-19) Cases: Case Definitions, Screened Populations and Testing Techniques Matter. | While counting cases of disease appears straightforward, there are issues to consider when enumerating disease counts during an epidemic. For example, for Coronavirus Disease-2019 (COVID-19), how is a case defined? Hubei province in China changed its case definition twice in a fortnight-from laboratory-confirmed cases to clinically-confirmed cases without laboratory tests, and back to laboratory-confirmed cases. This caused confusion in the reported number of cases. If a confirmed case requires laboratory testing, what is the population who are laboratory-tested? Due to limited laboratory testing capacity in the early phase of an emerging epidemic, only "suspected cases" are laboratory-tested in most countries. This will result in underdiagnosis of confirmed cases and also raises the question: how is a "suspect case" defined? With the passage of time and increased capability to perform laboratory tests, more people can be screened and the number of confirmed cases will increase. What are the technical considerations of laboratory testing? This includes specimen collection (variable collection methods), samples collected (upper or lower respiratory tract biospecimens), time of collection in relation to course of disease, different laboratory test methods and kits (not all of which may be standardised or approved by authorities such as the Food and Drug Administration). Are approved laboratory facilities and trained manpower available, and how are test results interpreted and false-negatives excluded? These issues will affect the accuracy of disease counts, which in turn will have implications on how we mount an appropriate response to the outbreak. | 63ihwrpe |
coronavirus under reporting | 8 | Are official confirmed cases and fatalities counts good enough to study the COVID-19 pandemic dynamics? A critical assessment through the case of Italy | As the COVID-19 outbreak is developing the two most frequently reported statistics seem to be the raw confirmed case and case fatalities counts. Focusing on Italy, one of the hardest hit countries, we look at how these two values could be put in perspective to reflect the dynamics of the virus spread. In particular, we find that merely considering the confirmed case counts would be very misleading. The number of daily tests grows, while the daily fraction of confirmed cases to total tests has a change point. It (depending on region) generally increases with strong fluctuations till (around, depending on region) 15th-22nd March and then decreases linearly after. Combined with the increasing trend of daily performed tests, the raw confirmed case counts are not representative of the situation and are confounded with the sampling effort. This we observe when regressing on time the logged fraction of positive tests and for comparison the logged raw confirmed count. Hence, calibrating model parameters for this virus's dynamics should not be done based only on confirmed case counts (without rescaling by the number of tests), but take also fatalities and hospitalization count under consideration as variables not prone to be distorted by testing efforts. Furthermore, reporting statistics on the national level does not say much about the dynamics of the disease, which are taking place at the regional level. These findings are based on the official data of total death counts up to 15th April 2020 released by ISTAT and up to 10th May 2020 for the number of cases. In this work we do not fit models but we rather investigate whether this task is possible at all. This work also informs about a new tool to collect and harmonize official statistics coming from different sources in the form of a package for the R statistical environment and presents the COVID-19 Data Hub. | 58b7m1b8 |
coronavirus under reporting | 8 | Estimating the COVID-19 infection rate: Anatomy of an inference problem | As a consequence of missing data on tests for infection and imperfect accuracy of tests, reported rates of cumulative population infection by the SARS CoV-2 virus are lower than actual rates of infection. Hence, reported rates of severe illness conditional on infection are higher than actual rates. Understanding the time path of the COVID-19 pandemic has been hampered by the absence of bounds on infection rates that are credible and informative. This paper explains the logical problem of bounding these rates and reports illustrative findings, using data from Illinois, New York, and Italy. We combine the data with assumptions on the infection rate in the untested population and on the accuracy of the tests that appear credible in the current context. We find that the infection rate might be substantially higher than reported. We also find that the infection fatality rate in Illinois, New York, and Italy is substantially lower than reported. | 8wg27hcu |
coronavirus under reporting | 8 | Test, test, test for COVID-19 antibodies: the importance of sensitivity, specificity and predictive powers | Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody tests of varying specificity and sensitivity are now available. For informing individuals whether they have had coronavirus disease 2019 (COVID-19), they need to be very accurate. For measuring population prevalence of past infection, the numbers of false positives and negatives need to be roughly equal. With a series of worked examples for a notional population of 100,000 people, we show that even test systems with a high specificity can yield a large number of false positive results, especially where the population prevalence is low. For example, at a true population prevalence of 5%, using a test with 99% sensitivity and specificity, 16% of positive results will be false and thus 950 people will be incorrectly informed they have had the infection. Further confirmatory testing may be needed. Giving false reassurance on which personal or societal decisions might be based could be harmful for individuals, undermine public confidence and foster further outbreaks. | hzi3kvw5 |
coronavirus under reporting | 8 | Covid-19 pandemic by the "real-time" monitoring: the Tunisian case and lessons for global epidemics in the context of 3PM strategies | Covid-19 is neither the first nor the last viral epidemic which societies around the world are, were and will be affected by. Which lessons should be taken from the current pandemic situation? The Covid-19 disease is still not well characterised, and many research teams all over the world are working on prediction of the epidemic scenario, protective measures to populations and sub-populations, therapeutic and vaccination issues, amongst others. Contextually, countries with currently low numbers of Covid-19-infected individuals such as Tunisia are intended to take lessons from those countries which already reached the exponential phase of the infection distribution as well as from those which have the exponential phase behind them and record a minor number of new cases such as China. To this end, in Tunisia, the pandemic wave has started with a significant delay compared with Europe, the main economic partner of the country. In this paper, we do analyse the current pandemic situation in this country by studying the infection evolution and considering potential protective strategies to prevent a pandemic scenario. The model is predictive based on a large number of undetected Covid-19 cases that is particularly true for some country regions such as Sfax. Infection distribution and mortality rate analysis demonstrate a highly heterogeneous picture over the country. Qualitative and quantitative comparative analysis leads to a conclusion that the reliable "real-time" monitoring based on the randomised laboratory tests is the optimal predictive strategy to create the most effective evidence-based preventive measures. In contrast, lack of tests may lead to incorrect political decisions causing either unnecessary over-protection of the population that is risky for a long-term economic recession, or under-protection of the population leading to a post-containment pandemic rebound. Recommendations are provided in the context of advanced predictive, preventive and personalised (3P) medical approach. | fls35tpb |
coronavirus under reporting | 8 | How Reliable are Test Numbers for Revealing the COVID-19 Ground Truth and Applying Interventions? | The number of confirmed cases of COVID-19 is often used as a proxy for the actual number of ground truth COVID-19 infected cases in both public discourse and policy making. However, the number of confirmed cases depends on the testing policy, and it is important to understand how the number of positive cases obtained using different testing policies reveals the unknown ground truth. We develop an agent-based simulation framework in Python that can simulate various testing policies as well as interventions such as lockdown based on them. The interaction between the agents can take into account various communities and mobility patterns. A distinguishing feature of our framework is the presence of another `flu'-like illness with symptoms similar to COVID-19, that allows us to model the noise in selecting the pool of patients to be tested. We instantiate our model for the city of Bengaluru in India, using census data to distribute agents geographically, and traffic flow mobility data to model long-distance interactions and mixing. We use the simulation framework to compare the performance of three testing policies: Random Symptomatic Testing (RST), Contact Tracing (CT), and a new Location Based Testing policy (LBT). We observe that if a sufficient fraction of symptomatic patients come out for testing, then RST can capture the ground truth quite closely even with very few daily tests. However, CT consistently captures more positive cases. Interestingly, our new LBT, which is operationally less intensive than CT, gives performance that is comparable with CT. In another direction, we compare the efficacy of these three testing policies in enabling lockdown, and observe that CT flattens the ground truth curve maximally, followed closely by LBT, and significantly better than RST. | 7bvsf5dk |
coronavirus in Canada | 9 | SARS back in Canada | n97bfo0j |
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coronavirus in Canada | 9 | Canada and COVID-19: learning from SARS | c7cd91pg |
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coronavirus in Canada | 9 | Market Area Delineation for Airports to Predict the Spread of Infectious Disease | Air travel facilitates the international spread of infectious disease. While global air travel data represent the volume of travel between airports, identifying which airport an infected individual might use, or where a disease might spread after an infected passenger deplanes, remains a largely unexplored area of research and public health practice. This gap can be addressed by estimating airport catchment areas. This research aims to determine how existing market area delineation techniques estimate airport catchments differently, and which techniques are best suited to anticipate where infectious diseases may spread. Multiple techniques were tested for airports in the Province of Ontario, Canada: circular buffers, drive-time buffers, Thiessen polygons, and the Huff model, with multiple variations tested for some techniques. The results were compared qualitatively and quantitatively based on spatial patterns as well as area and population of each catchment area. There were notable differences, specifically between deterministic and probabilistic approaches. Deterministic techniques may only be suitable if all airports in a study area are similar in terms of attractiveness. The probabilistic Huff model appeared to produce more realistic results because it accounted for variation in airport attractiveness. Additionally, the Huff model requires few inputs and therefore would be efficient to execute in situations where time, resources, and data are limited. | 6apsd91c |
coronavirus in Canada | 9 | Risk of a second wave of Covid-19 infections: using artificial intelligence to investigate stringency of physical distancing policies in North America. | PURPOSE Accurately forecasting the occurrence of future covid-19-related cases across relaxed (Sweden) and stringent (USA and Canada) policy contexts has a renewed sense of urgency. Moreover, there is a need for a multidimensional county-level approach to monitor the second wave of covid-19 in the USA. METHOD We use an artificial intelligence framework based on timeline of policy interventions that triangulated results based on the three approaches-Bayesian susceptible-infected-recovered (SIR), Kalman filter, and machine learning. RESULTS Our findings suggest three important insights. First, the effective growth rate of covid-19 infections dropped in response to the approximate dates of key policy interventions. We find that the change points for spreading rates approximately coincide with the timelines of policy interventions across respective countries. Second, forecasted trend until mid-June in the USA was downward trending, stable, and linear. Sweden is likely to be heading in the other direction. That is, Sweden's forecasted trend until mid-June appears to be non-linear and upward trending. Canada appears to fall somewhere in the middle-the trend for the same period is flat. Third, a Kalman filter based robustness check indicates that by mid-June the USA will likely have close to two million virus cases, while Sweden will likely have over 44,000 covid-19 cases. CONCLUSION We show that drop in effective growth rate of covid-19 infections was sharper in the case of stringent policies (USA and Canada) but was more gradual in the case of relaxed policy (Sweden). Our study exhorts policy makers to take these results into account as they consider the implications of relaxing lockdown measures. | 6ar58ea6 |
coronavirus in Canada | 9 | Baseline characteristics and outcomes of patients with COVID-19 admitted to intensive care units in Vancouver, Canada: a case series. | BACKGROUND Pandemic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is associated with high intensive care unit (ICU) mortality. We aimed to describe the clinical characteristics and outcomes of critically ill patients with coronavirus disease 2019 (COVID-19) in a Canadian setting. METHODS We conducted a retrospective case series of critically ill patients with laboratory-confirmed SARS-CoV-2 infection consecutively admitted to 1 of 6 ICUs in Metro Vancouver, British Columbia, Canada, between Feb. 21 and Apr. 14, 2020. Demographic, management and outcome data were collected by review of patient charts and electronic medical records. RESULTS Between Feb. 21 and Apr. 14, 2020, 117 patients were admitted to the ICU with a confirmed diagnosis of COVID-19. The median age was 69 (interquartile range [IQR] 60-75) years, and 38 (32.5%) were female. At least 1 comorbidity was present in 86 (73.5%) patients. Invasive mechanical ventilation was required in 74 (63.2%) patients. The duration of mechanical ventilation was 13.5 (IQR 8-22) days overall and 11 (IQR 6-16) days for patients successfully discharged from the ICU. Tocilizumab was administered to 4 patients and hydroxychloroquine to 1 patient. As of May 5, 2020, a total of 18 (15.4%) patients had died, 12 (10.3%) remained in the ICU, 16 (13.7%) were discharged from the ICU but remained in hospital, and 71 (60.7%) were discharged home. INTERPRETATION In our setting, mortality in critically ill patients with COVID-19 admitted to the ICU was lower than in previously published studies. These data suggest that the prognosis associated with critical illness due to COVID-19 may not be as poor as previously reported. | dw2kljya |
coronavirus in Canada | 9 | Laboratory-confirmed COVID-19 in children and youth in Canada, January 15-April 27, 2020. | Understanding the epidemiology of COVID-19 among children and youth in Canada will help to inform public health measures in settings where children gather. As of April 27, 2020, provinces and territories provided the Public Health Agency of Canada with detailed information on 24,079 cases, of which 3.9% (n=938) were younger than 20 years of age. The detection rate per 100,000 population was lower in this age group (11.9 per 100,000), compared with those aged 20-59 years (72.4 per 100,000) and 60 and older (113.6 per 100,000). The median age among those younger than 20 years of age was 13 years, and cases were distributed equally across male and female genders. Among provinces and territories with more than 100 cases, 1.6% to 9.8% of cases were younger than 20 years of age. Cases in this age group were more likely to be asymptomatic: 10.7% compared with 2.4% in those aged 20-59 years and 4.1% in those aged 60 and older. Children and youth experienced severe outcomes less often, but 2.2% (n=15/672) of cases within this age group were severe enough to require hospitalization. Based on available exposure information, 11.3% (n=59/520) of cases aged younger than 20 years had no known contact with a case. Canadian findings align with those of other countries. | xzoleks8 |
coronavirus in Canada | 9 | Communication, transparency key as Canada faces new coronavirus threat. | 0ujw0gak |
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coronavirus in Canada | 9 | Open access epidemiologic data and an interactive dashboard to monitor the COVID-19 outbreak in Canada. | 6a6m7ye5 |
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coronavirus in Canada | 9 | Projecting demand for critical care beds during COVID-19 outbreaks in Canada. | BACKGROUND Increasing numbers of coronavirus disease 2019 (COVID-19) cases in Canada may create substantial demand for hospital admission and critical care. We evaluated the extent to which self-isolation of mildly ill people delays the peak of outbreaks and reduces the need for this care in each Canadian province. METHODS We developed a computational model and simulated scenarios for COVID-19 outbreaks within each province. Using estimates of COVID-19 characteristics, we projected the hospital and intensive care unit (ICU) bed requirements without self-isolation, assuming an average number of 2.5 secondary cases, and compared scenarios in which different proportions of mildly ill people practised self-isolation 24 hours after symptom onset. RESULTS Without self-isolation, the peak of outbreaks would occur in the first half of June, and an average of 569 ICU bed days per 10 000 population would be needed. When 20% of cases practised self-isolation, the peak was delayed by 2-4 weeks, and ICU bed requirement was reduced by 23.5% compared with no self-isolation. Increasing self-isolation to 40% reduced ICU use by 53.6% and delayed the peak of infection by an additional 2-4 weeks. Assuming current ICU bed occupancy rates above 80% and self-isolation of 40%, demand would still exceed available (unoccupied) ICU bed capacity. INTERPRETATION At the peak of COVID-19 outbreaks, the need for ICU beds will exceed the total number of ICU beds even with self-isolation at 40%. Our results show the coming challenge for the health care system in Canada and the potential role of self-isolation in reducing demand for hospital-based and ICU care. | 9ffvdgon |
coronavirus in Canada | 9 | Temporal estimates of case-fatality rate for COVID-19 outbreaks in Canada and the United States. | BACKGROUND Estimates of the casefatality rate (CFR) associated with coronavirus disease 2019 (COVID-19) vary widely in different population settings. We sought to estimate and compare the COVID-19 CFR in Canada and the United States while adjusting for 2 potential biases in crude CFR. METHODS We used the daily incidence of confirmed COVID-19 cases and deaths in Canada and the US from Jan. 31 to Apr. 22, 2020. We applied a statistical method to minimize bias in the crude CFR by accounting for the survival interval as the lag time between disease onset and death, while considering reporting rates of COVID-19 cases less than 50% (95% confidence interval 10%-50%). RESULTS Using data for confirmed cases in Canada, we estimated the crude CFR to be 4.9% on Apr. 22, 2020, and the adjusted CFR to be 5.5% (credible interval [CrI] 4.9%-6.4%). After we accounted for various reporting rates less than 50%, the adjusted CFR was estimated at 1.6% (CrI 0.7%-3.1%). The US crude CFR was estimated to be 5.4% on Apr. 20, 2020, with an adjusted CFR of 6.1% (CrI 5.4%-6.9%). With reporting rates of less than 50%, the adjusted CFR for the US was 1.78 (CrI 0.8%-3.6%). INTERPRETATION Our estimates suggest that, if the reporting rate is less than 50%, the adjusted CFR of COVID-19 in Canada is likely to be less than 2%. The CFR estimates for the US were higher than those for Canada, but the adjusted CFR still remained below 2%. Quantification of case reporting can provide a more accurate measure of the virulence and disease burden of severe acute respiratory syndrome coronavirus 2. | glah2z2m |
coronavirus in Canada | 9 | Healthcare Worker COVID-19 Cases in Ontario, Canada: A Cross-sectional Study | Background: Our objectives were to describe and compare healthcare worker (HCW) and non-HCW COVID-19 cases in Ontario, as well as the frequency of COVID-19 among HCWs household members. Methods: Using reportable disease data at Public Health Ontario which captures COVID-19 cases in Ontario, we conducted a cross-sectional study comparing demographic, exposure, and clinical variables between HCWs and non-HCWs with COVID-19 as of 14 May 2020. We calculated rates of infections over time and determined the frequency of within household transmissions using natural language processing. Results: There were 4,230 (17.5%) HCW COVID-19 cases in Ontario, of whom 20.2% were nurses, 2.3% were physicians, and the remaining 77.4% other specialties. HCWs were more likely to be between 30-60 years of age and female. HCWs were more likely to present asymptomatically (8.1% versus 7.0%, p=0.010) or with atypical symptoms (17.8% versus 10.5%, p<0.001). The mortality among HCWs was 0.2% compared to 10.5% of non-HCWs. HCWs commonly had exposures to a confirmed case or outbreak (74.1%), however only 3.1% were confirmed to be nosocomial. The rate of new infections was 5.5 times higher in HCWs than non-HCWs, but mirrored the epidemic curve. We identified 391 (9.8%) probable secondary household transmissions. Interpretation: HCWs represent a disproportionate number of COVID-19 cases in Ontario but with low confirmed numbers of nosocomial transmission. The data support substantial testing bias and under-ascertainment of general population cases. Protecting HCWs through appropriate personal protective equipment and physician distancing from colleagues is paramount. | 4rutnzbu |