Incorporating false negative tests in epidemiological models for SARS-CoV-2 transmission and reconciling with seroprevalence estimates

AbstractSusceptible-Exposed-Infected-Removed (SEIR)-type epidemiologic models, modeling unascertained infections latently, can predict unreported cases and deaths assuming perfect testing. We apply a method we developed to account for the high false negative rates of diagnostic RT-PCR tests for detecting an active SARS-CoV-2 infection in a classic SEIR model. The number of unascertained cases and false negatives being unobservable in a real study, population-based serosurveys can help validate model projections. Applying our method to training data from Delhi, India, during March 15–June 30, 2020, we estimate the underreporting factor for cases at 34–53 (deaths: 8–13) on July 10, 2020, largely consistent with the findings of the first round of serosurveys for Delhi (done during June 27–July 10, 2020) with an estimated 22.86% IgG antibody prevalence, yielding estimated underreporting factors of 30–42 for cases. Together, these imply approximately 96–98% cases in Delhi remained unreported (July 10, 2020). Updated calculations using training data during March 15-December 31, 2020 yield estimated underreporting factor for cases at 13–22 (deaths: 3–7) on January 23, 2021, which are again consistent with the latest (fifth) round of serosurveys for Delhi (done during January 15–23, 2021) with an estimated 56.13% IgG antibody prevalence, yielding an estimated range for the underreporting factor for cases at 17–21. Together, these updated estimates imply approximately 92–96% cases in Delhi remained unreported (January 23, 2021). Such model-based estimates, updated with latest data, provide a viable alternative to repeated resource-intensive serosurveys for tracking unreported cases and deaths and gauging the true extent of the pandemic.

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Seroepidemiological Study of Novel Corona Virus (CoVID-19) in Tehran, Iran

10.1101/2021.01.18.20248911 ◽

2021 ◽

Author(s):

Zeinab Tabanejad ◽

Sorena Darvish ◽

Zeinab Borjian Boroujeni ◽

Seyed Saeed Asadi ◽

Morteza Mesri ◽

...

Keyword(s):

False Negative ◽

Underlying Disease ◽

Population Based ◽

Immunological Methods ◽

Age Group ◽

Igg Antibodies ◽

Rt Pcr ◽

Igg Antibody ◽

Cross Sectional ◽

Exposed Population

AbstractA novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has now spread to all countries of the world, including Iran. Although new anti-coronavirus antibodies in patients may be identified by immunological methods with sufficient sensitivity and specificity, the conclusive diagnosis of the disease is by the molecular RT-PCR process. We used a population-based seroepidemiological survey to quantify the proportion of the exposed population with SARS-CoV-2 antibodies and evaluated whether the antibodies are a marker of total or partial immunity to the proportion of the population that remains susceptible to the virus. This cross-sectional study was conducted to investigate the seroprevalence of CoVID-19 in Tehran, the capital of Iran, between April and end of October 2020. Specimens of clotted and heparinized blood (2ml) were collected from the patients. The serum and plasma were separated and stored at − 80LJ°C until use. We examined serum anti-SARS-CoV-2 IgG and IgM antibodies from 1375 in-patients admitted to our hospitals using ELISA kits. In total, 1375 participants were enrolled in this study, and SARS-CoV-2 antibodies were detected using IgM-IgG antibody assay in 291 patients. Among the seropositive patients studied, 187 were men (64.3%), and 104 were women (35.7%) (P<0.05). The mean age of the patients was 49±8.4 years; the majority (27%) were in age group 31-40 years. Also, the lowest frequency of cases was reported in the age group of 1-10 years (P <0.05). We determined the seroprevalence of SARS-CoV-2 for IgM or IgG antibodies to be 21.2%. Diabetes mellitus was the most common underlying disease among SARS-CoV-2 patients [P=0.05; Odd Ratio=1.61(0.90-2.91)]. Conventional serological assays in SARS-CoV-2 cases, such as the enzyme-linked immunoassay (ELISA) for specific IgM and IgG antibodies, have a high-throughput advantage and minimize false-negative rates that occur with the RT-PCR method. This study determined the seroprevalence of SARS-CoV-2 antibodies to be 21%. Control of diabetes among other cases factors shall play important role in management and control of COVID-19.

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SARS-CoV2 Testing: The Limit of Detection Matters

10.1101/2020.06.02.131144 ◽

2020 ◽

Cited By ~ 10

Author(s):

Ramy Arnaout ◽

Rose A. Lee ◽

Ghee Rye Lee ◽

Cody Callahan ◽

Christina F. Yen ◽

...

Keyword(s):

Limit Of Detection ◽

Diagnostic Testing ◽

False Negative ◽

False Negative Rate ◽

Fold Increase ◽

Test Results ◽

Rt Pcr ◽

False Negatives ◽

Healthcare Network ◽

Negative Rate

AbstractResolving the COVID-19 pandemic requires diagnostic testing to determine which individuals are infected and which are not. The current gold standard is to perform RT-PCR on nasopharyngeal samples. Best-in-class assays demonstrate a limit of detection (LoD) of ~100 copies of viral RNA per milliliter of transport media. However, LoDs of currently approved assays vary over 10,000-fold. Assays with higher LoDs will miss more infected patients, resulting in more false negatives. However, the false-negative rate for a given LoD remains unknown. Here we address this question using over 27,500 test results for patients from across our healthcare network tested using the Abbott RealTime SARS-CoV-2 EUA. These results suggest that each 10-fold increase in LoD is expected to increase the false negative rate by 13%, missing an additional one in eight infected patients. The highest LoDs on the market will miss a majority of infected patients, with false negative rates as high as 70%. These results suggest that choice of assay has meaningful clinical and epidemiological consequences. The limit of detection matters.

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A comparison of five epidemiological models for transmission of SARS-CoV-2 in India

10.1101/2020.09.19.20198010 ◽

2020 ◽

Author(s):

Soumik Purkayastha ◽

Rupam Bhattacharyya ◽

Ritwik Bhaduri ◽

Ritoban Kundu ◽

Xuelin Gu ◽

...

Keyword(s):

Correlation Coefficient ◽

Prediction Error ◽

Pearson Correlation ◽

False Negative ◽

False Negative Rate ◽

Correlation Coefficients ◽

Epidemiological Models ◽

Baseline Model ◽

Seir Model ◽

Active Case

Many popular disease transmission models have helped nations respond to the COVID-19 pandemic by informing decisions about pandemic planning, resource allocation, implementation of social distancing measures and other non-pharmaceutical interventions. We compare five epidemiological models for forecasting and assessing the course of the pandemic. We compare how the models analyze case-recovery-death count data in India, the country with second highest reported case-counts in a world where a large proportion of infections remain undetected. A baseline curve-fitting model is introduced, in addition to three compartmental models: an extended SIR (eSIR) model, an expanded SEIR model developed to account for infectiousness of asymptomatic and pre-symptomatic cases (SAPHIRE), another SEIR model to handle high false negative rate and symptom-based administration of tests (SEIR-fansy). A semi-mechanistic Bayesian hierarchical model developed at the Imperial College London (ICM) is also examined. Using COVID-19 data for India from March 15 to June 18 to train the models, we generate predictions from each of the five models from June 19 to July 18. To compare prediction accuracy with respect to reported cumulative and active case counts and cumulative death counts, we compute the symmetric mean absolute prediction error (SMAPE) and mean squared relative prediction error (MSRPE) for each of the five models. For active case counts, SEIR-fansy yields an SMAPE value of 0.72, and the eSIR model yields a value of 33.83. For cumulative case counts, SMAPE values are 1.76 for baseline model, 23.10 for eSIR, 2.07 for SAPHIRE and 3.20 for SEIR-fansy. For cumulative death counts, the SEIR-fansy model performs the best, with an SMAPE of 7.13, as compared to 26.30 for the eSIR model. Using Pearson correlation coefficient and Lin concordance correlation coefficient, for cumulative case counts, the baseline model exhibits highest correlation (both Pearson as well as Lin coefficients), while for cumulative death counts, projections from SEIR-fansy exhibit the best performance: For cumulative cases, correlation coefficients computed for the baseline model are 1 (Pearson) and 0.991 (Lin). For eSIR, those values are 0.985 (Pearson) and 0.316 (Lin). For SAPHIRE, we compute 1 (Pearson) and 0.975 (Lin). Finally, for SEIR-fansy we have those values at 1 (Pearson) and 0.965 (Lin). Similarly, for cumulative deaths, correlation coefficients computed for eSIR is 0.978 (Pearson) and 0.206 (Lin), and for SEIR-fansy we have those values at 0.999 (Pearson) and 0.742 (Lin). Three models (SAPHIRE, SEIR-fansy and ICM) return total (sum of reported and unreported) counts as well. We compute underreporting factors on two specific dates (June 30 and July 10) and note that on both dates, the SEIR-fansy model reports the highest underreporting factor for active cases (June 30: 6.10 and July 10: 6.24) and cumulative deaths (June 30: 3.62 and July 10: 3.99) for both dates, while the SAPHIRE model reports the highest underreporting factor for cumulative cases (June 30: 27.79 and July 10: 26.74).

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Real-life clinical sensitivity of SARS-CoV-2 RT-PCR test in symptomatic patients

PLoS ONE ◽

10.1371/journal.pone.0251661 ◽

2021 ◽

Vol 16 (5) ◽

pp. e0251661

Author(s):

Elisa Kortela ◽

Vesa Kirjavainen ◽

Maarit J. Ahava ◽

Suvi T. Jokiranta ◽

Anna But ◽

...

Keyword(s):

Clinical Decision Making ◽

False Negative ◽

Real Life ◽

Clinical Decision ◽

Population Based ◽

Clinical Suspicion ◽

Rt Pcr ◽

Clinical Sensitivity ◽

High Clinical Suspicion ◽

Pcr Test

Background Understanding the false negative rates of SARS-CoV-2 RT-PCR testing is pivotal for the management of the COVID-19 pandemic and it has implications for patient management. Our aim was to determine the real-life clinical sensitivity of SARS-CoV-2 RT-PCR. Methods This population-based retrospective study was conducted in March–April 2020 in the Helsinki Capital Region, Finland. Adults who were clinically suspected of SARS-CoV-2 infection and underwent SARS-CoV-2 RT-PCR testing, with sufficient data in their medical records for grading of clinical suspicion were eligible. In addition to examining the first RT-PCR test of repeat-tested individuals, we also used high clinical suspicion for COVID-19 as the reference standard for calculating the sensitivity of SARS-CoV-2 RT-PCR. Results All 1,194 inpatients (mean [SD] age, 63.2 [18.3] years; 45.2% women) admitted to COVID-19 cohort wards during the study period were included. The outpatient cohort of 1,814 individuals (mean [SD] age, 45.4 [17.2] years; 69.1% women) was sampled from epidemiological line lists by systematic quasi-random sampling. The sensitivity (95% CI) for laboratory confirmed cases (repeat-tested patients) was 85.7% (81.5–89.1%) inpatients; 95.5% (92.2–97.5%) outpatients, 89.9% (88.2–92.1%) all. When also patients that were graded as high suspicion but never tested positive were included in the denominator, the sensitivity (95% CI) was: 67.5% (62.9–71.9%) inpatients; 34.9% (31.4–38.5%) outpatients; 47.3% (44.4–50.3%) all. Conclusions The clinical sensitivity of SARS-CoV-2 RT-PCR testing was only moderate at best. The relatively high false negative rates of SARS-CoV-2 RT-PCR testing need to be accounted for in clinical decision making, epidemiological interpretations, and when using RT-PCR as a reference for other tests.

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Serological immunochromatographic approach in diagnosis with SARS-CoV-2 infected COVID-19 patients

10.1101/2020.03.13.20035428 ◽

2020 ◽

Cited By ~ 7

Author(s):

Yunbao Pan ◽

Xinran Li ◽

Gui Yang ◽

Junli Fan ◽

Yueting Tang ◽

...

Keyword(s):

Real Time ◽

Early Stage ◽

False Negative ◽

False Negative Rate ◽

Intermediate Stage ◽

Rt Pcr ◽

Igg Antibody ◽

Blood Samples ◽

Icg Strip ◽

Stage 1

AbstractAn outbreak of new coronavirus SARS-CoV-2 was occurred in Wuhan, China and rapidly spread to other cities and nations. The standard diagnostic approach that widely adopted in the clinic is nuclear acid detection by real-time RT-PCR. However, the false-negative rate of the technique is unneglectable and serological methods are urgently warranted. Here, we presented the colloidal gold-based immunochromatographic (ICG) strip targeting viral IgM or IgG antibody and compared it with real-time RT-PCR. The sensitivity of ICG assay with IgM and IgG combinatorial detection in nuclear acid confirmed cases were 11.1%, 92.9% and 96.8% at the early stage (1-7 days after onset), intermediate stage (8-14 days after onset), and late stage (more than 15 days), respectively. The ICG detection capacity in nuclear acid-negative suspected cases was 43.6%. In addition, the consistencies of whole blood samples with plasma were 100% and 97.1% in IgM and IgG strips, respectively. In conclusion, serological ICG strip assay in detecting SARS-CoV-2 infection is both sensitive and consistent, which is considered as an excellent supplementary approach in clinical application.

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Real-life clinical sensitivity of SARS-CoV-2 RT-PCR test in symptomatic patients

10.1101/2020.11.01.20223107 ◽

2020 ◽

Author(s):

Elisa Kortela ◽

Vesa Kirjavainen ◽

Maarit J. Ahava ◽

Suvi T. Jokiranta ◽

Anna But ◽

...

Keyword(s):

Clinical Decision Making ◽

False Negative ◽

Real Life ◽

Clinical Decision ◽

Population Based ◽

Clinical Suspicion ◽

Rt Pcr ◽

Clinical Sensitivity ◽

High Clinical Suspicion ◽

Pcr Test

AbstractImportanceUnderstanding the false negative rates of SARS-CoV-2 RT-PCR testing is pivotal for the management of the COVID-19 pandemic and it has practical implications for patient management in healthcare facilities.ObjectiveTo determine the real-life clinical sensitivity of SARS-CoV-2 RT-PCR testing.DesignA retrospective study on case series from 4 March – 15 April 2020.SettingA population-based study conducted in primary and tertiary care in the Helsinki Capital Region, Finland.ParticipantsAdults who were clinically suspected of SARS-CoV-2 infection and underwent SARS-CoV-2 RT-PCR testing, and who had sufficient data for grading of clinical suspicion of COVID-19 in their medical records were eligible. All 1,194 inpatients admitted to COVID-19 cohort wards during the study period were included. The outpatient cohort of 1,814 individuals was sampled from epidemiological line lists by systematic quasi-random sampling. Altogether 83 eligible outpatients (4.6%) and 3 inpatients (0.3%) were excluded due to insufficient data for grading of clinical suspicion.ExposuresHigh clinical suspicion for COVID-19 was used as the reference standard for the RT-PCR test. Patients were considered to have high clinical suspicion of COVID-19 if the physician in charge recorded the suspicion on clinical grounds, or the patient fulfilled specifically defined clinical and exposure criteria.Main measuresSensitivity of SARS-CoV-2 RT-PCR by using manually curated clinical characteristics as the gold standard.ResultsThe study population included 1,814 outpatients (mean [SD] age, 45.4 [17.2] years; 69.1% women) and 1,194 inpatients (mean [SD] age, 63.2 [18.3] years; 45.2% women). The sensitivity (95% CI) for laboratory confirmed cases, i.e. repeatedly tested patients were as follows: 85.7% (81.5–89.1%) inpatients; 95.5% (92.2–97.5%) outpatients, 89.9% (88.2–92.1%) all. When also patients that were graded as high suspicion but never tested positive were included in the denominator, the following sensitivity values (95% CI) were observed: 67.5% (62.9–71.9%) inpatients; 34.9% (31.4–38.5%) outpatients; 47.3% (44.4–50.3%) all.Conclusions and relevanceThe clinical sensitivity of SARS-CoV-2 RT-PCR testing was only moderate at best. The relatively high false negative rates of SARS-CoV-2 RT-PCR testing need to be accounted for in clinical decision making, epidemiological interpretations and when using RT-PCR as a reference for other tests.Key PointsQuestionWhat is the clinical sensitivity of SARS-CoV-2 RT-PCR test?FindingsIn this population-based retrospective study on medical records of 1,814 outpatients and 1,194 inpatients, the clinical sensitivity of SARS-CoV-2 RT-PCR was 47.3–89.9%.MeaningThe false negative rates of SARS-CoV-2 RT-PCR testing need to be accounted for in clinical decision making, epidemiological interpretations and when using RT-PCR as a reference for other tests.

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Frequency of serological non-responders and false-negative RT-PCR results in SARS-CoV-2 testing: a population-based study

Clinical Chemistry and Laboratory Medicine (CCLM) ◽

10.1515/cclm-2020-0978 ◽

2020 ◽

Vol 0 (0) ◽

Cited By ~ 3

Author(s):

Rita Christiane Baron ◽

Lorenz Risch ◽

Myriam Weber ◽

Sarah Thiel ◽

Kirsten Grossmann ◽

...

Keyword(s):

Disease Duration ◽

Validation Cohort ◽

Clinical Symptoms ◽

False Negative ◽

Population Based ◽

Initial Presentation ◽

Rt Pcr ◽

Antibody Testing ◽

Disease Symptoms

AbstractObjectivesThe sensitivity of molecular and serological methods for COVID-19 testing in an epidemiological setting is not well described. The aim of the study was to determine the frequency of negative RT-PCR results at first clinical presentation as well as negative serological results after a follow-up of at least 3 weeks.MethodsAmong all patients seen for suspected COVID-19 in Liechtenstein (n=1921), we included initially RT-PCR positive index patients (n=85) as well as initially RT-PCR negative (n=66) for follow-up with SARS-CoV-2 antibody testing. Antibodies were detected with seven different commercially available immunoassays. Frequencies of negative RT-PCR and serology results in individuals with COVID-19 were determined and compared to those observed in a validation cohort of Swiss patients (n=211).ResultsAmong COVID-19 patients in Liechtenstein, false-negative RT-PCR at initial presentation was seen in 18% (12/66), whereas negative serology in COVID-19 patients was 4% (3/85). The validation cohort showed similar frequencies: 2/66 (3%) for negative serology, and 16/155 (10%) for false negative RT-PCR. COVID-19 patients with negative follow-up serology tended to have a longer disease duration (p=0.05) and more clinical symptoms than other patients with COVID-19 (p<0.05). The antibody titer from quantitative immunoassays was positively associated with the number of disease symptoms and disease duration (p<0.001).ConclusionsRT-PCR at initial presentation in patients with suspected COVID-19 can miss infected patients. Antibody titers of SARS-CoV-2 assays are linked to the number of disease symptoms and the duration of disease. One in 25 patients with RT-PCR-positive COVID-19 does not develop antibodies detectable with frequently employed and commercially available immunoassays.

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EVALUATION OF PERFORMANCE OF NINE SEROLOGICALASSAYS FOR THE DETECTION OF SARS-COV-2 ANTIBODIES.

10.36106/ijsr/1335520 ◽

2021 ◽

pp. 60-62

Author(s):

Tagajdid Mohamed Rida ◽

Konzi Clémence ◽

El Kochri Safae ◽

Elannaz Hicham ◽

Abi Rachid ◽

...

Keyword(s):

Clinical Performance ◽

Current Knowledge ◽

False Negative ◽

Antibody Test ◽

Antibody Detection ◽

Rt Pcr ◽

Igg Antibody ◽

Serological Tests ◽

Blood Samples ◽

Test Kit

Introduction: Currently, polymerase chain reaction (PCR) based viral RNAdetection is the standard for COVID-19 diagnosis [2]. Though, RNA testing based on throat or nasopharyngeal swabs has shown a number of false-negative results. Antibody detection tests have been developed to detect specic antibodies, IgM and IgG, to SRAS-CoV-2 virus. The clinical relevance of these tests is still under evaluation and is highly related to their clinical performance. Our objective is to assess analytical performances of nine SARS-CoV-2 antibodies immunoassays. Materiel and Method: We collected 80 blood samples from PCR-conrmed COVID-19 patients diagnosed in our Virology department (20 samples collected at day 10 after the onset of symptoms, 60 collected after day 14 following the onset of symptoms) and 20 blood samples from patients SARS-CoV-2 RT-PCR negative. All sera were tested with nine SARS-CoV-2 antibodies immunoassays ARCHITECT SARS-CoV-2 IgG® (Abbott), COVID-19 VIRCLIA® IgG MONOTEST (Vircell), COVID-19 VIRCLIA® IgM+IgA MONOTEST (Vircell), COVID-19 ELISA IgG® (Vircell), COVID-19 ELISA IgM+IgA® (Vircell), Elecsys® Anti-SARS-CoV-2 (Roche), FREND® COVID-19 IgG/IgM Duo (NanoEntek), COVID-PRESTO® (AAZ) and COVID-19 (SARS-CoV-2) IgM/IgG Antibody Test Kit® (Labnovation Technologies). Results: Sensitivity of tests increases once the seroconversion to anti-SARS-CoV-2 IgG positive in most individuals occurs toward the end of week 2 post-infection. COVID-19 PRESTO had the best accuracy in our study showing 100% sensitivity after day 14 following the onset of symptoms. All of the tests had a specicity of 100%. Conclusion: Serological tests are sensitive for the latest stages of COVID-19 infection. Recommendations on using SRAS-COV-2 antibody detection tests are continuously improving based on current knowledge of host antibody responses during infection. They are of great value in cases presenting COVID-19 symptoms with negative RT-PCR.

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Potential False-Negative Nucleic Acid Testing Results for Severe Acute Respiratory Syndrome Coronavirus 2 from Thermal Inactivation of Samples with Low Viral Loads

Clinical Chemistry ◽

10.1093/clinchem/hvaa091 ◽

2020 ◽

Vol 66 (6) ◽

pp. 794-801 ◽

Cited By ~ 76

Author(s):

Yang Pan ◽

Luyao Long ◽

Daitao Zhang ◽

Tingting Yuan ◽

Shujuan Cui ◽

...

Keyword(s):

Nucleic Acid ◽

Severe Acute Respiratory Syndrome ◽

Thermal Inactivation ◽

Rna Virus ◽

False Negative ◽

Heat Inactivation ◽

Nucleic Acid Testing ◽

Rt Pcr ◽

False Negatives ◽

Viral Loads

Abstract Background Coronavirus disease-2019 (COVID-19) has spread widely throughout the world since the end of 2019. Nucleic acid testing (NAT) has played an important role in patient diagnosis and management of COVID-19. In some circumstances, thermal inactivation at 56°C has been recommended to inactivate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) before NAT. However, this procedure could theoretically disrupt nucleic acid integrity of this single-stranded RNA virus and cause false negatives in real-time polymerase chain reaction (RT-PCR) tests. Methods We investigated whether thermal inactivation could affect the results of viral NAT. We examined the effects of thermal inactivation on the quantitative RT-PCR results of SARS-CoV-2, particularly with regard to the rates of false-negative results for specimens carrying low viral loads. We additionally investigated the effects of different specimen types, sample preservation times, and a chemical inactivation approach on NAT. Results Our study showed increased Ct values in specimens from diagnosed COVID-19 patients in RT-PCR tests after thermal incubation. Moreover, about half of the weak-positive samples (7 of 15 samples, 46.7%) were RT-PCR negative after heat inactivation in at least one parallel testing. The use of guanidinium-based lysis for preservation of these specimens had a smaller impact on RT-PCR results with fewer false negatives (2 of 15 samples, 13.3%) and significantly less increase in Ct values than heat inactivation. Conclusion Thermal inactivation adversely affected the efficiency of RT-PCR for SARS-CoV-2 detection. Given the limited applicability associated with chemical inactivators, other approaches to ensure the overall protection of laboratory personnel need consideration.

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Reconciling epidemiological models with misclassified case-counts for SARS-CoV-2 with seroprevalence surveys: A case study in Delhi, India

10.1101/2020.07.31.20166249 ◽

2020 ◽

Cited By ~ 3

Author(s):

Rupam Bhattacharyya ◽

Ritwik Bhaduri ◽

Ritoban Kundu ◽

Maxwell Salvatore ◽

Bhramar Mukherjee

Keyword(s):

Diagnostic Tests ◽

False Negative ◽

False Negative Rate ◽

Antibody Test ◽

Population Based ◽

National Capital Region ◽

Rt Pcr ◽

High False Negative Rate ◽

True Number ◽

National Capital

Underreporting of COVID-19 cases and deaths is a hindrance to correctly modeling and monitoring the pandemic. This is primarily due to limited testing, lack of reporting infrastructure and a large number of asymptomatic infections. In addition, diagnostic tests (RT-PCR tests for detecting current infection) and serological antibody tests for IgG (to assess past infections) are imperfect. In particular, the diagnostic tests have a high false negative rate. Epidemiologic models with a latent compartment for unascertained infections like the Susceptible-Exposed-Infected-Removed (SEIR) models can provide predictions for unreported cases and deaths under certain assumptions. Typically, the number of unascertained cases is unobserved and thus we cannot validate these estimates for a real study except for simulation studies. Population-based seroprevalence studies can provide a rough estimate of the total number of infections and help us check epidemiologic model projections. In this paper, we develop a method to account for high false negative rates in RT-PCR in an extension to the classic SEIR model. We apply this method to Delhi, the national capital region of India, with a population of 19.8 million and a COVID-19 hotspot of the country, obtaining estimates of underreporting factor for cases at 34-53 times and that for deaths at 8-13 times. Based on a recently released serological survey for Delhi with an estimated 22.86% seroprevalence, we compute adjusted estimates of the true number of infections reported by the survey (after accounting for misclassification of the antibody test results) which is largely consistent with the model outputs, yielding an underreporting factor for cases from 30-42. Together with the model and the serosurvey, this implies approximately 96-98% cases in Delhi remained unreported and whereas only 109,140 cases were reported on July 10, the true number of infections varied somewhere between 4.4-4.6 million across different estimates. While repeated serological monitoring is resource intensive, model-based adjustments, run with the most up to date data, can provide a viable option to keep track of the unreported cases and deaths and gauge the true extent of transmission of this insidious virus.

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