Addressing misclassification bias in vaccine effectiveness studies with an application to Covid-19.

Safe and effective vaccines are crucial for the control of Covid-19 and to protect individuals at higher risk of severe disease. The test-negative design is a popular option for evaluating the effectiveness of Covid-19 vaccines. However, the findings could be biased by several factors, including imperfect sensitivity and/or specificity of the test used for diagnosing the SARS-Cov-2 infection. We propose a simple Bayesian modeling approach for estimating vaccine effectiveness that is robust even when the diagnostic test is imperfect. We use simulation studies to demonstrate the robustness of our method to misclassification bias and illustrate the utility of our approach using real-world examples.

Evaluating diagnostic accuracies of Panbio™ test and RT-PCR for the detection of SARS-CoV-2 in Addis Ababa, Ethiopia using Bayesian Latent-Class Models (BLCM).

BACKGROUND: Rapid diagnostics are vital for curving the transmission and control of the COVID-19 pandemic. Although many commercially available antigen-based rapid diagnostic tests (Ag-RDTs) for the detection of SARS-CoV-2 are recommended by the WHO, their diagnostic performance has not yet been assessed in Ethiopia. So far, the vast majority of studies assessing diagnostic accuracies of rapid antigen tests considered RT-PCR as a reference standard, which inevitably leads to bias when RT-PCR is not 100% sensitive and specific. Thus, this study aimed to evaluate the diagnostic performance of Panbio™ jointly with the RT-PCR for the detection of SARS-CoV-2. METHODS: A prospective cross-sectional study was done from July to September 2021 in Addis Ababa, Ethiopia, during the third wave of the pandemic involving two health centers and two hospitals. Diagnostic sensitivity and specificity of Panbio™ and RT-PCR were obtained using Bayesian Latent-Class Models (BLCM). RESULTS: 438 COVID-19 presumptive clients were enrolled, 239 (54.6%) were females, of whom 196 (44.7%) had a positive RT-PCR and 158 (36.1%) were Panbio™ positive. The Panbio™ and RT-PCR had a sensitivity (95% CrI) of 99.6 (98.4-100) %, 89.3 (83.2-97.6) % and specificity (95% CrI) of 93.4 (82.3-100) %, and 99.1 (97.5-100) %, respectively. Most of the study participants, 318 (72.6%) exhibited COVID-19 symptoms; the most reported was cough 191 (43.6%). CONCLUSION: As expected the RT-PCR performed very well with a near-perfect specificity and a high, but not perfect sensitivity. The diagnostic performance of Panbio™ is coherent with the WHO established criteria of having a sensitivity ≥80% for Ag-RDTs. Both tests displayed high diagnostic accuracies in patients with and without symptoms. Hence, we recommend the use of the Panbio™ for both symptomatic and asymptomatic individuals in clinical settings for screening purposes.

Diagnostic accuracy of three commercially available one step RT-PCR assays for the detection of SARS-CoV-2 in resource limited settings.

BACKGROUND: COVID-19 is an ongoing public health pandemic regardless of the countless efforts made by various actors. Quality diagnostic tests are important for early detection and control. Notably, several commercially available one step RT-PCR based assays have been recommended by the WHO. Yet, their analytic and diagnostic performances have not been well documented in resource-limited settings. Hence, this study aimed to evaluate the diagnostic sensitivities and specificities of three commercially available one step reverse transcriptase-polymerase chain reaction (RT-PCR) assays in Ethiopia in clinical setting. METHODS: A cross-sectional study was conducted from April to June, 2021 on 279 respiratory swabs originating from community surveillance, contact cases and suspect cases. RNA was extracted using manual extraction method. Master-mix preparation, amplification and result interpretation was done as per the respective manufacturer. Agreements between RT-PCRs were analyzed using kappa values. Bayesian latent class models (BLCM) were fitted to obtain reliable estimates of diagnostic sensitivities, specificities of the three assays and prevalence in the absence of a true gold standard. RESULTS: Among the 279 respiratory samples, 50(18%), 59(21.2%), and 69(24.7%) were tested positive by TIB, Da An, and BGI assays, respectively. Moderate to substantial level of agreement was reported among the three assays with kappa value between 0 .55 and 0.72. Based on the BLCM relatively high specificities (95% CI) of 0.991(0.973-1.000), 0.961(0.930-0.991) and 0.916(0.875-0.952) and considerably lower sensitivities with 0.813(0.658-0.938), 0.836(0.712-0.940) and 0.810(0.687-0.920) for TIB MOLBIOL, Da An and BGI respectively were found. CONCLUSIONS: While all the three RT-PCR assays displayed comparable sensitivities, the specificities of TIB MOLBIOL and Da An were considerably higher than BGI. These results help adjust the apparent prevalence determined by the three RT-PCRs and thus support public health decisions in resource limited settings and consider alternatives as per their prioritization matrix.

Diagnostic Accuracy Estimates for COVID-19 Real-Time Polymerase Chain Reaction and Lateral Flow Immunoassay Tests With Bayesian Latent-Class Models.

Our objective was to estimate the diagnostic accuracy of real-time polymerase chain reaction (RT-PCR) and lateral flow immunoassay (LFIA) tests for coronavirus disease 2019 (COVID-19), depending on the time after symptom onset. Based on the cross-classified results of RT-PCR and LFIA, we used Bayesian latent-class models, which do not require a gold standard for the evaluation of diagnostics. Data were extracted from studies that evaluated LFIA (immunoglobulin G (IgG) and/or immunoglobulin M (IgM)) assays using RT-PCR as the reference method. The sensitivity of RT-PCR was 0.68 (95% probability interval (PrI): 0.63, 0.73). IgG/M sensitivity was 0.32 (95% PrI :0.23; 0.41) for the first week and increased steadily. It was 0.75 (95% PrI: 0.67; 0.83) and 0.93 (95% PrI: 0.88; 0.97) for the second and third weeks after symptom onset, respectively. Both tests had a high to absolute specificity, with higher point median estimates for RT-PCR specificity and narrower probability intervals. The specificity of RT-PCR was 0.99 (95% PrI: 0.98; 1.00). and the specificity of IgG/IgM was 0.97 (95% PrI: 0.92, 1.00), 0.98 (95% PrI: 0.95, 1.00) and 0.98 (95% PrI: 0.94, 1.00) for the first, second, and third weeks after symptom onset. The diagnostic accuracy of LFIA varies with time after symptom onset. Bayesian latent-class models provide a valid and efficient alternative for evaluating the rapidly evolving diagnostics for COVID-19, under various clinical settings and different risk profiles.