scholarly journals Combining Rapid Antigen Testing and Syndromic Surveillance Improves Community-Based COVID-19 Detection in Low-to-Middle-Income Countries

2022 ◽  
Author(s):  
Fergus Chadwick ◽  
Jessica Clark ◽  
Shayan Chowdhury ◽  
Tasnuva Chowdhury ◽  
David Pascall ◽  
...  
Keyword(s):  
Low Income ◽  
Syndromic Surveillance ◽  
Classification Performance ◽  
Test Results ◽  
Rapid Diagnostics ◽  
Antigen Test ◽  
Middle Income ◽  
Middle Income Countries ◽  
Antigen Tests ◽  
Antigen Testing

Abstract Diagnostics for COVID-19 detection are limited in many settings. Syndromic surveillance is often the only means to identify cases, but lacks specificity. Rapid antigen testing is inexpensive and easy-to-deploy but concerns remain about sensitivity. We examine how combining these approaches can improve surveillance for guiding interventions in low-income communities in Dhaka, Bangladesh. Rapid-antigen-tests and PCR validation was performed on 1172 symptomatically-identified individuals at home. Statistical models were fit to predict PCR status using rapid-antigen-test results, syndromic data, and their combination. Model predictive and classification performance was examined under contrasting epidemiological scenarios to evaluate their potential for improving diagnoses. Models combining rapid-antigen-test and syndromic data yielded equal-to-better performance to rapid-antigen-test-only models across all scenarios. These results show that drawing on complementary strengths across two rapid diagnostics, improves COVID-19 detection, and reduces false-positive and -negative diagnoses to match local requirements; improvements achievable without additional expense, or changes for patients or practitioners.

scholarly journals Comparison of Antigen Tests and qPCR in Rapid Diagnostics of Infections Caused by SARS-CoV-2 Virus

Viruses ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 17
Author(s):  
Adrianna Klajmon ◽  
Aldona Olechowska-Jarząb ◽  
Dominika Salamon ◽  
Agnieszka Sroka-Oleksiak ◽  
Monika Brzychczy-Włoch ◽  
...  
Keyword(s):  
Quantitative Polymerase Chain Reaction ◽  
Molecular Techniques ◽  
Nucleic Acid Amplification ◽  
Laboratory Diagnostics ◽  
Test Results ◽  
Rapid Diagnostics ◽  
Antigen Test ◽  
Qualified Personnel ◽  
Replication Phase ◽  
Antigen Tests

Diagnostics of the coronavirus disease 2019 (COVID-19) using molecular techniques from the collected respiratory swab specimens requires well-equipped laboratory and qualified personnel, also it needs several hours of waiting for results and is expensive. Antigen tests appear to be faster and cheaper but their sensitivity and specificity are debatable. The aim of this study was to compare a selected antigen test with quantitative polymerase chain reaction (qPCR) tests results. Nasopharyngeal swabs were collected from 192 patients with COVID-19 symptoms. All samples were tested using Vitassay qPCR SARS-CoV-2 kit and the Humasis COVID-19 Ag Test (MedSun) antigen immunochromatographic test simultaneously. Ultimately, 189 samples were tested; 3 samples were excluded due to errors in taking swabs. The qPCR and antigen test results were as follows: 47 positive and 142 negative, and 45 positive and 144 negative, respectively. Calculated sensitivity of 91.5% and specificity of 98.6% for the antigen test shows differences which are not statistically significant in comparison to qPCR. Our study showed that effectiveness of the antigen tests in rapid laboratory diagnostics is high enough to be an alternative and support for nucleic acid amplification tests (NAAT) in the virus replication phase in the course of COVID-19.

scholarly journals Pooling of samples for SARS-CoV-2 detection using rapid antigen tests

2021 ◽  
Author(s):  
Nol Salcedo ◽  
Alexander Harmon ◽  
Bobby Brooke Herrera
Keyword(s):  
Positive Sample ◽  
Diagnostic Efficiency ◽  
Rt Pcr ◽  
Middle Income ◽  
Pooled Testing ◽  
Middle Income Countries ◽  
Pooling Strategy ◽  
Polymerase Chain ◽  
Antigen Tests ◽  
Antigen Testing

AbstractWhile molecular assays, such as reverse-transcription polymerase chain reaction (RT- PCR), have been widely used throughout the coronavirus disease 2019 (COVID-19) pandemic, the technique is resource intensive and costly. As a means to reduce costs and expand diagnostic efficiency, pooled testing using RT-PCR has been implemented. However, pooled testing using rapid antigen tests has not been evaluated. Here, we propose a pooling strategy for rapid antigen testing that would significantly expand COVID-19 surveillance, especially for low-to-middle income countries, and schools and workplaces. Our data demonstrate that combining of up to 20 samples per pool can expand surveillance with rapid antigen tests, even if a pool contains only one positive sample.

scholarly journals Pooling of Samples for SARS-CoV-2 Detection Using a Rapid Antigen Test

2021 ◽  
Vol 2 ◽  
Author(s):  
Nol Salcedo ◽  
Alexander Harmon ◽  
Bobby Brooke Herrera
Keyword(s):  
Positive Sample ◽  
Diagnostic Efficiency ◽  
Rt Pcr ◽  
Middle Income ◽  
Pooled Testing ◽  
Middle Income Countries ◽  
Pooling Strategy ◽  
Polymerase Chain ◽  
Antigen Tests ◽  
Antigen Testing

While molecular assays, such as reverse-transcription polymerase chain reaction (RT-PCR), have been widely used throughout the coronavirus disease 2019 (COVID-19) pandemic, the technique is costly and resource intensive. As a means to reduce costs and increase diagnostic efficiency, pooled testing using RT-PCR has been implemented. However, pooling samples for antigen testing has not been evaluated. Here, we propose a proof-of-concept pooling strategy for antigen testing that would significantly expand SARS-CoV-2 surveillance, especially for low-to-middle income countries, schools, and workplaces. Our laboratory-based testing demonstrates that combining of up to 20 nasal swab specimens per pool can expand surveillance with antigen tests, even if a pool contains only one positive sample.

scholarly journals Tuberculosis and Non-Communicable Disease Multimorbidity: An Analysis of the World Health Survey in 48 Low- and Middle-Income Countries

2021 ◽  
Vol 18 (5) ◽  
pp. 2439
Author(s):  
Brendon Stubbs ◽  
Kamran Siddiqi ◽  
Helen Elsey ◽  
Najma Siddiqi ◽  
Ruimin Ma ◽  
...  
Keyword(s):  
Health Survey ◽  
Low Income ◽  
World Health ◽  
Low Income Countries ◽  
Multivariable Logistic Regression Analysis ◽  
World Health Survey ◽  
Middle Income ◽  
Middle Income Countries ◽  
The World ◽  
Low And Middle Income

Tuberculosis (TB) is a leading cause of mortality in low- and middle-income countries (LMICs). TB multimorbidity [TB and ≥1 non-communicable diseases (NCDs)] is common, but studies are sparse. Cross-sectional, community-based data including adults from 21 low-income countries and 27 middle-income countries were utilized from the World Health Survey. Associations between 9 NCDs and TB were assessed with multivariable logistic regression analysis. Years lived with disability (YLDs) were calculated using disability weights provided by the 2017 Global Burden of Disease Study. Eight out of 9 NCDs (all except visual impairment) were associated with TB (odds ratio (OR) ranging from 1.38–4.0). Prevalence of self-reported TB increased linearly with increasing numbers of NCDs. Compared to those with no NCDs, those who had 1, 2, 3, 4, and ≥5 NCDs had 2.61 (95% confidence interval (CI) = 2.14–3.22), 4.71 (95%CI = 3.67–6.11), 6.96 (95%CI = 4.95–9.87), 10.59 (95%CI = 7.10–15.80), and 19.89 (95%CI = 11.13–35.52) times higher odds for TB. Among those with TB, the most prevalent combinations of NCDs were angina and depression, followed by angina and arthritis. For people with TB, the YLDs were three times higher than in people without multimorbidity or TB, and a third of the YLDs were attributable to NCDs. Urgent research to understand, prevent and manage NCDs in people with TB in LMICs is needed.

scholarly journals Gestational weight gain in low-income and middle-income countries: a modelling analysis using nationally representative data

2020 ◽  
Vol 5 (11) ◽  
pp. e003423
Author(s):  
Dongqing Wang ◽  
Molin Wang ◽  
Anne Marie Darling ◽  
Nandita Perumal ◽  
Enju Liu ◽  
...  
Keyword(s):  
Weight Gain ◽  
North Africa ◽  
Low Income ◽  
Sub Saharan Africa ◽  
Middle Income ◽  
Middle Income Countries ◽  
Gestational Weight ◽  
Latin America And Caribbean ◽  
Nationally Representative ◽  
Sub Saharan

IntroductionGestational weight gain (GWG) has important implications for maternal and child health and is an ideal modifiable factor for preconceptional and antenatal care. However, the average levels of GWG across all low-income and middle-income countries of the world have not been characterised using nationally representative data.MethodsGWG estimates across time were computed using data from the Demographic and Health Surveys Program. A hierarchical model was developed to estimate the mean total GWG in the year 2015 for all countries to facilitate cross-country comparison. Year and country-level covariates were used as predictors, and variable selection was guided by the model fit. The final model included year (restricted cubic splines), geographical super-region (as defined by the Global Burden of Disease Study), mean adult female body mass index, gross domestic product per capita and total fertility rate. Uncertainty ranges (URs) were generated using non-parametric bootstrapping and a multiple imputation approach. Estimates were also computed for each super-region and region.ResultsLatin America and Caribbean (11.80 kg (95% UR: 6.18, 17.41)) and Central Europe, Eastern Europe and Central Asia (11.19 kg (95% UR: 6.16, 16.21)) were the super-regions with the highest GWG estimates in 2015. Sub-Saharan Africa (6.64 kg (95% UR: 3.39, 9.88)) and North Africa and Middle East (6.80 kg (95% UR: 3.17, 10.43)) were the super-regions with the lowest estimates in 2015. With the exception of Latin America and Caribbean, all super-regions were below the minimum GWG recommendation for normal-weight women, with Sub-Saharan Africa and North Africa and Middle East estimated to meet less than 60% of the minimum recommendation.ConclusionThe levels of GWG are inadequate in most low-income and middle-income countries and regions. Longitudinal monitoring systems and population-based interventions are crucial to combat inadequate GWG in low-income and middle-income countries.

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