Contact tracing of COVID-19 in Karnataka, India: Superspreading and determinants of infectiousness and symptomatic infection.

BACKGROUND: India has experienced the second largest outbreak of COVID-19 globally, yet there is a paucity of studies analysing contact tracing data in the region which can optimise public health interventions (PHI's). METHODS: We analysed contact tracing data from Karnataka, India between 9 March and 21 July 2020. We estimated metrics of transmission including the reproduction number (R), overdispersion (k), secondary attack rate (SAR), and serial interval. R and k were jointly estimated using a Bayesian Markov Chain Monte Carlo approach. We studied determinants of risk of further transmission and risk of being symptomatic using Poisson regression models. FINDINGS: Up to 21 July 2020, we found 111 index cases that crossed the super-spreading threshold of ≥8 secondary cases. Among 956 confirmed traced cases, 8.7% of index cases had 14.4% of contacts but caused 80% of all secondary cases. Among 16715 contacts, overall SAR was 3.6% [95% CI, 3.4-3.9] and symptomatic cases were more infectious than asymptomatic cases (SAR 7.7% vs 2.0%; aRR 3.63 [3.04-4.34]). As compared to infectors aged 19-44 years, children were less infectious (aRR 0.21 [0.07-0.66] for 0-5 years and 0.47 [0.32-0.68] for 6-18 years). Infectors who were confirmed ≥4 days after symptom onset were associated with higher infectiousness (aRR 3.01 [2.11-4.31]). As compared to asymptomatic cases, symptomatic cases were 8.16 [3.29-20.24] times more likely to cause symptomatic infection in their secondary cases. Serial interval had a mean of 5.4 [4.4-6.4] days, and case fatality rate was 2.5% [2.4-2.7] which increased with age. CONCLUSION: We found significant heterogeneity in the individual-level transmissibility of SARS-CoV-2 which could not be explained by the degree of heterogeneity in the underlying number of contacts. To strengthen contact tracing in over-dispersed outbreaks, testing and tracing delays should be minimised and retrospective contact tracing should be implemented. Targeted measures to reduce potential superspreading events should be implemented. Interventions aimed at children might have a relatively small impact on reducing transmission owing to their low symptomaticity and infectivity. We propose that symptomatic cases could cause a snowballing effect on clinical severity and infectiousness across transmission generations; further studies are needed to confirm this finding.

SARS-CoV-2 spike E156G/Δ157-158 mutations contribute to increased infectivity and immune escape.

Breakthrough infections by emerging SARS-CoV-2 variants raise significant concerns. Here, we sequence-characterized the spike gene from breakthrough infections that corresponded to B.1.617 sublineage. Delineating the functional impact of spike mutations revealed that N-terminal domain (NTD)-specific E156G/Δ157-158 contributed to increased infectivity and reduced sensitivity to vaccine-induced antibodies. A six-nucleotide deletion (467-472) in the spike-coding region introduced this change in the NTD. We confirmed the presence of E156G/Δ157-158 from cases concurrently screened, in addition to other circulating spike (S1) mutations such as T19R, T95I, L452R, E484Q, and D614G. Notably, E156G/Δ157-158 was present in more than 90% of the sequences reported from the USA and UK in October 2021. The spike-pseudotyped viruses bearing a combination of E156G/Δ157-158 and L452R exhibited higher infectivity and reduced sensitivity to neutralization. Notwithstanding, the post-recovery plasma robustly neutralized viral particles bearing the mutant spike. When the spike harbored E156G/Δ157-158 along with L452R and E484Q, increased cell-to-cell fusion was also observed, suggesting a combinatorial effect of these mutations. Our study underscores the importance of non-RBD changes in determining infectivity and immune escape.

The burden of active infection and anti-SARS-CoV-2 IgG antibodies in the general population: Results from a statewide sentinel-based population survey in Karnataka, India.

OBJECTIVE: To estimate the burden of active infection and anti-SARS-CoV-2 IgG antibodies in Karnataka, India, and to assess variation across geographical regions and risk groups. METHODS: A cross-sectional survey of 16,416 people covering three risk groups was conducted between 3-16 September 2020 using the state of Karnataka's infrastructure of 290 healthcare facilities across all 30 districts. Participants were further classified into risk subgroups and sampled using stratified sampling. All participants were subjected to simultaneous detection of SARS-CoV-2 IgG using a commercial ELISA kit, SARS-CoV-2 antigen using a rapid antigen detection test (RAT) and reverse transcription-polymerase chain reaction (RT-PCR) for RNA detection. Maximum-likelihood estimation was used for joint estimation of the adjusted IgG, active and total prevalence (either IgG or active or both), while multinomial regression identified predictors. RESULTS: The overall adjusted total prevalence of COVID-19 in Karnataka was 27.7% (95% CI 26.1-29.3), IgG 16.8% (15.5-18.1) and active infection fraction 12.6% (11.5-13.8). The case-to-infection ratio was 1:40 and the infection fatality rate was 0.05%. Influenza-like symptoms or contact with a COVID-19-positive patient were good predictors of active infection. RAT kits had higher sensitivity (68%) in symptomatic people compared with 47% in asymptomatic people. CONCLUSION: This sentinel-based population survey was the first comprehensive survey in India to provide accurate estimates of the COVID-19 burden. The findings provide a reasonable approximation of the population immunity threshold levels. Using existing surveillance platforms coupled with a syndromic approach and sampling framework enabled this model to be replicable.

Optimization Rules for SARS-CoV-2 Mpro Antivirals: Ensemble Docking and Exploration of the Coronavirus Protease Active Site.

Coronaviruses are viral infections that have a significant ability to impact human health. Coronaviruses have produced two pandemics and one epidemic in the last two decades. The current pandemic has created a worldwide catastrophe threatening the lives of over 15 million as of July 2020. Current research efforts have been focused on producing a vaccine or repurposing current drug compounds to develop a therapeutic. There is, however, a need to study the active site preferences of relevant targets, such as the SARS-CoV-2 main protease (SARS-CoV-2 Mpro), to determine ways to optimize these drug compounds. The ensemble docking and characterization work described in this article demonstrates the multifaceted features of the SARS-CoV-2 Mpro active site, molecular guidelines to improving binding affinity, and ultimately the optimization of drug candidates. A total of 220 compounds were docked into both the 5R7Z and 6LU7 SARS-CoV-2 Mpro crystal structures. Several key preferences for strong binding to the four subsites (S1, S1', S2, and S4) were identified, such as accessing hydrogen binding hotspots, hydrophobic patches, and utilization of primarily aliphatic instead of aromatic substituents. After optimization efforts using the design guidelines developed from the molecular docking studies, the average docking score of the parent compounds was improved by 6.59 -log10(Kd) in binding affinity which represents an increase of greater than six orders of magnitude. Using the optimization guidelines, the SARS-CoV-2 Mpro inhibitor cinanserin was optimized resulting in an increase in binding affinity of 4.59 -log10(Kd) and increased protease inhibitor bioactivity. The results of molecular dynamic (MD) simulation of cinanserin-optimized compounds CM02, CM06, and CM07 revealed that CM02 and CM06 fit well into the active site of SARS-CoV-2 Mpro [Protein Data Bank (PDB) accession number 6LU7] and formed strong and stable interactions with the key residues, Ser-144, His-163, and Glu-166. The enhanced binding affinity produced demonstrates the utility of the design guidelines described. The work described herein will assist scientists in developing potent COVID-19 antivirals.