Comparison of one single-antigen assay and three multi-antigen SARS-CoV-2 IgG assays in Nigeria.

Objectives: Determining an accurate estimate of SARS-CoV-2 seroprevalence has been challenging in African countries where malaria and other pathogens are endemic. We compared the performance of one single-antigen assay and three multi-antigen SARS-CoV-2 IgG assays in a Nigerian population endemic for malaria. Methods: De-identified plasma specimens from SARS-CoV-2 RT-PCR positive, dried blood spot (DBS) SARS-CoV-2 RT-PCR positive, and pre-pandemic negatives were used to evaluate the performance of the four SARS-CoV-2 assays (Tetracore, SARS2MBA, RightSign, xMAP). Results: Results showed higher sensitivity with the multi-antigen (81% (Tetracore), 96% (SARS2MBA), 85% (xMAP)) versus the single-antigen (RightSign (64%)) SARS-CoV-2 assay. The overall specificities were 98% (Tetracore), 100% (SARS2MBA and RightSign), and 99% (xMAP). When stratified based on <15 days to ≥15 days post-RT-PCR confirmation, the sensitivities increased from 75% to 88.2% for Tetracore; from 93% to 100% for the SARS2MBA; from 58% to 73% for RightSign; and from 83% to 88% for xMAP. With DBS, there was no positive increase after 15-28 days for the three assays (Tetracore, SARS2MBA, and xMAP). Conclusion: Multi-antigen assays performed well in Nigeria, even with samples with known malaria reactivity, and might provide more accurate measures of COVID-19 seroprevalence and vaccine efficacy.

Drivers of COVID-19 policy stringency in 175 countries and territories: COVID-19 cases and deaths, gross domestic products per capita, and health expenditures.

Background: New data on COVID-19 may influence the stringency of containment policies, but these potential effect are not understood. We aimed to understand the associations of new COVID-19 cases and deaths with policy stringency globally and regionally. Methods: We modelled the marginal effects of new COVID-19 cases and deaths on policy stringency (scored 0-100) in 175 countries and territories, adjusting for gross domestic product (GDP) per capita and health expenditure (% of GDP), and public expenditure on health. The time periods examined were March to August 2020, September 2020 to February 2021, and March to August 2021. Results: Policy response to new cases and deaths was faster and more stringent early in the COVID-19 pandemic (March to August 2020) compared to subsequent periods. New deaths were more strongly associated with stringent policies than new cases. In an average week, one new death per 100 000 people was associated with a stringency increase of 2.1 units in the March to August 2020 period, 1.3 units in the September 2020 to February 2021 period, and 0.7 units in the March to August 2021 period. New deaths in Africa and the Western Pacific were associated with more stringency than in other regions. Higher health expenditure as a percentage of GDP was associated with less stringent policies. Similarly, higher public expenditure on health by governments was mostly associated with less stringency across all three periods. GDP per capita did not have consistent patterns of associations with stringency. Conclusions: The stringency of COVID-19 policies was more strongly associated with new deaths than new cases. Our findings demonstrate the need for enhanced mortality surveillance to ensure policy alignment during health emergencies. Countries that invest less in health or have a lower public expenditure on health may be inclined to enact more stringent policies. This new empirical understanding of COVID-19 policy drivers can help public health officials anticipate and shape policy responses in future health emergencies.

Validation of xMAP SARS-CoV-2 Multi-Antigen IgG assay in Nigeria.

OBJECTIVE: There is a need for reliable serological assays to determine accurate estimates of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence. Most single target antigen assays have shown some limitations in Africa. To assess the performance of a multi-antigen assay, we evaluated a commercially available SARS-CoV-2 Multi-Antigen IgG assay for human coronavirus disease 2019 (COVID-19) in Nigeria. METHODS: Validation of the xMAP SARS-CoV-2 Multi-Antigen IgG assay was carried out using well-characterized SARS-CoV-2 reverse transcription polymerase chain reactive positive (97) and pre-COVID-19 pandemic (86) plasma panels. Cross-reactivity was assessed using pre-COVID-19 pandemic plasma specimens (213) from the 2018 Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS). RESULTS: The overall sensitivity of the xMAP SARS-CoV-2 Multi-Antigen IgG assay was 75.3% [95% CI: 65.8%- 82.8%] and specificity was 99.0% [95% CI: 96.8%- 99.7%]. The sensitivity estimate increased to 83.3% [95% CI: 70.4%- 91.3%] for specimens >14 days post-confirmation of diagnosis. However, using the NAIIS pre-pandemic specimens, the false positivity rate was 1.4% (3/213). CONCLUSIONS: Our results showed overall lower sensitivity and a comparable specificity with the manufacturer's validation. There appears to be less cross-reactivity with NAIIS pre-pandemic COVID-19 specimens using the xMAP SARS-CoV-2 Multi-Antigen IgG assay. In-country SARS-CoV-2 serology assay validation can help guide the best choice of assays in Africa.

Cross-Reactivity of Two SARS-CoV-2 Serological Assays in a Setting Where Malaria Is Endemic.

Accurate SARS-CoV-2 serological assays are critical for COVID-19 serosurveillance. However, previous studies have indicated possible cross-reactivity of these assays, including in areas where malaria is endemic. We tested 213 well-characterized prepandemic samples from Nigeria using two SARS-CoV-2 serological assays, Abbott Architect IgG and Euroimmun NCP IgG assay, both targeting SARS-CoV-2 nucleocapsid protein. To assess antibody binding strength, an avidity assay was performed on these samples and on plasma from SARS-CoV-2 PCR-positive persons. Thirteen (6.1%) of 212 samples run on the Abbott assay and 38 (17.8%) of 213 run on the Euroimmun assay were positive. Anti-Plasmodium IgG levels were significantly higher among false positives for both Abbott and Euroimmun; no association was found with active Plasmodium falciparum infection. An avidity assay using various concentrations of urea wash in the Euroimmun assay reduced loosely bound IgG: of 37 positive/borderline prepandemic samples, 46%, 86%, 89%, and 97% became negative using 2 M, 4 M, 5 M, and 8 M urea washes, respectively. The wash slightly reduced avidity of antibodies from SARS-CoV-2 patients within 28 days of PCR confirmation; thereafter, avidity increased for all urea concentrations except 8 M. This validation found moderate to substantial cross-reactivity on two SARS-CoV-2 serological assays using samples from a setting where malaria is endemic. A simple urea wash appeared to alleviate issues of cross-reactivity.

Malaria and Parasitic Neglected Tropical Diseases: Potential Syndemics with COVID-19?

The COVID-19 pandemic, caused by SARS-CoV-2, have surpassed 5 million cases globally. Current models suggest that low- and middle-income countries (LMICs) will have a similar incidence but substantially lower mortality rate than high-income countries. However, malaria and neglected tropical diseases (NTDs) are prevalent in LMICs, and coinfections are likely. Both malaria and parasitic NTDs can alter immunologic responses to other infectious agents. Malaria can induce a cytokine storm and pro-coagulant state similar to that seen in severe COVID-19. Consequently, coinfections with malaria parasites and SARS-CoV-2 could result in substantially worse outcomes than mono-infections with either pathogen, and could shift the age pattern of severe COVID-19 to younger age-groups. Enhancing surveillance platforms could provide signals that indicate whether malaria, NTDs, and COVID-19 are syndemics (synergistic epidemics). Based on the prevalence of malaria and NTDs in specific localities, efforts to characterize COVID-19 in LMICs could be expanded by adding testing for malaria and NTDs. Such additional testing would allow the determination of the rates of coinfection and comparison of severity of outcomes by infection status, greatly improving the understanding of the epidemiology of COVID-19 in LMICs and potentially helping to mitigate its impact.