scholarly journals Author Correction: Development of a model-inference system for estimating epidemiological characteristics of SARS-CoV-2 variants of concern

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Wan Yang ◽  
Jeffrey Shaman
Keyword(s):  
Inference System ◽  
Model Inference ◽  
Epidemiological Characteristics

scholarly journals Development of a model-inference system for estimating epidemiological characteristics of SARS-CoV-2 variants of concern

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Wan Yang ◽  
Jeffrey Shaman
Keyword(s):  
Preventive Measures ◽  
Immune Escape ◽  
Mass Vaccination ◽  
Mortality Data ◽  
Wild Type ◽  
Inference System ◽  
Model Inference ◽  
Pandemic Planning ◽  
Epidemiological Characteristics ◽  
Type Infection

AbstractTo support COVID-19 pandemic planning, we develop a model-inference system to estimate epidemiological properties of new SARS-CoV-2 variants of concern using case and mortality data while accounting for under-ascertainment, disease seasonality, non-pharmaceutical interventions, and mass-vaccination. Applying this system to study three variants of concern, we estimate that B.1.1.7 has a 46.6% (95% CI: 32.3–54.6%) transmissibility increase but nominal immune escape from protection induced by prior wild-type infection; B.1.351 has a 32.4% (95% CI: 14.6–48.0%) transmissibility increase and 61.3% (95% CI: 42.6–85.8%) immune escape; and P.1 has a 43.3% (95% CI: 30.3–65.3%) transmissibility increase and 52.5% (95% CI: 0–75.8%) immune escape. Model simulations indicate that B.1.351 and P.1 could outcompete B.1.1.7 and lead to increased infections. Our findings highlight the importance of preventing the spread of variants of concern, via continued preventive measures, prompt mass-vaccination, continued vaccine efficacy monitoring, and possible updating of vaccine formulations to ensure high efficacy.

scholarly journals SARS-CoV-2 transmission dynamics in South Africa and epidemiological characteristics of the Omicron variant

2021 ◽  
Author(s):  
Wan Yang ◽  
Jeffrey Shaman
Keyword(s):  
South Africa ◽  
Transmission Dynamics ◽  
Gauteng Province ◽  
Inference System ◽  
South Africans ◽  
Model Inference ◽  
Population Immunity ◽  
Novel Variant ◽  
Nonpharmaceutical Interventions ◽  
Epidemiological Characteristics

Within days of first detection, Omicron SARS-CoV-2 variant case numbers grew exponentially and spread globally. To better understand variant epidemiological characteristics, we utilize a model-inference system to reconstruct SARS-CoV-2 transmission dynamics in South Africa and decompose novel variant transmissibility and immune erosion. Accounting for under-detection of infection, infection seasonality, nonpharmaceutical interventions, and vaccination, we estimate that the majority of South Africans had been infected by SARS-CoV-2 before the Omicron wave. Based on findings for Gauteng province, Omicron is estimated 100.3% (95% CI: 74.8 - 140.4%) more transmissible than the ancestral SARS-CoV-2 and 36.5% (95% CI: 20.9 - 60.1%) more transmissible than Delta; in addition, Omicron erodes 63.7% (95% CI: 52.9 - 73.9%) of the population immunity, accumulated from prior infections and vaccination, in Gauteng.

scholarly journals COVID-19 pandemic dynamics in India and impact of the SARS-CoV-2 Delta (B.1.617.2) variant

2021 ◽  
Author(s):  
Wan Yang ◽  
Jeffrey Shaman
Keyword(s):  
Monsoon Season ◽  
Weather Conditions ◽  
Comprehensive Model ◽  
Model Inference ◽  
Population Immunity ◽  
Multiple Datasets ◽  
Intervention Measures ◽  
Inference Methods ◽  
Epidemiological Characteristics ◽  
Pharmaceutical Interventions

The Delta SARS-CoV-2 variant has spread quickly since first being identified. To better understand its epidemiological characteristics and impact, we utilize multiple datasets and comprehensive model-inference methods to reconstruct COVID-19 pandemic dynamics in India, where Delta first emerged. Using model-inference estimates from March 2020 to May 2021, we estimate the Delta variant can escape adaptive immunity induced by prior wildtype infection roughly half of the time and is around 60% more infectious than wildtype SARS-CoV-2. In addition, our analysis suggests that the recent case decline in India was likely due to implemented non-pharmaceutical interventions and weather conditions less conducive for SARS-CoV-2 transmission during March - May, rather than high population immunity. Model projections show infections could resurge as India enters its monsoon season, beginning June, if intervention measures are lifted prematurely.

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