The co-circulating transmission dynamics of SARS-CoV-2 Alpha and Eta variants in Nigeria: A retrospective modeling study of COVID-19

Extending EpiEstim to estimate the transmission advantage of pathogen variants in real-time: SARS-CoV-2 as a case-study

The evolution of SARS-CoV-2 has demonstrated that emerging variants can set back the global COVID-19 response. The ability to rapidly assess the threat of new variants is critical for timely optimisation of control strategies. We present a novel method to estimate the effective transmission advantage of a new variant compared to a reference variant combining information across multiple locations and over time. Through an extensive simulation study designed to mimic real-time epidemic contexts, we show that our method performs well across a range of scenarios and provide guidance on its optimal use and interpretation of results. We also provide an open-source software implementation of our method. The computational speed of our tool enables users to rapidly explore spatial and temporal variations in the estimated transmission advantage. We estimate that the SARS-CoV-2 Alpha variant is 1.46 (95% Credible Interval 1.44-1.47) and 1.29 (95% CrI 1.29-1.30) times more transmissible than the wild type, using data from England and France respectively. We further estimate that Delta is 1.77 (95% CrI 1.69-1.85) times more transmissible than Alpha (England data). Our approach can be used as an important first step towards quantifying the threat of emerging or co-circulating variants of infectious pathogens in real-time.

Genomic epidemiology of SARS-CoV-2 infections in The Gambia: an analysis of routinely collected surveillance data between March, 2020, and January, 2022

BACKGROUND

COVID-19, caused by SARS-CoV-2, is one of the deadliest pandemics of the past 100 years. Genomic sequencing has an important role in monitoring of the evolution of the virus, including the detection of new viral variants. We aimed to describe the genomic epidemiology of SARS-CoV-2 infections in The Gambia.

METHODS

Nasopharyngeal or oropharyngeal swabs collected from people with suspected cases of COVID-19 and international travellers were tested for SARS-CoV-2 with standard RT-PCR methods. SARS-CoV-2-positive samples were sequenced according to standard library preparation and sequencing protocols. Bioinformatic analysis was done using ARTIC pipelines and Pangolin was used to assign lineages. To construct phylogenetic trees, sequences were first stratified into different COVID-19 waves (waves 1-4) and aligned. Clustering analysis was done and phylogenetic trees constructed.

FINDINGS

Between March, 2020, and January, 2022, 11 911 confirmed cases of COVID-19 were recorded in The Gambia, and 1638 SARS-CoV-2 genomes were sequenced. Cases were broadly distributed into four waves, with more cases during the waves that coincided with the rainy season (July-October). Each wave occurred after the introduction of new viral variants or lineages, or both, generally those already established in Europe or in other African countries. Local transmission was higher during the first and third waves (ie, those that corresponded with the rainy season), in which the B.1.416 lineage and delta (AY.34.1) were dominant, respectively. The second wave was driven by the alpha and eta variants and the B.1.1.420 lineage. The fourth wave was driven by the omicron variant and was predominantly associated with the BA.1.1 lineage.

INTERPRETATION

More cases of SARS-CoV-2 infection were recorded in The Gambia during peaks of the pandemic that coincided with the rainy season, in line with transmission patterns for other respiratory viruses. The introduction of new lineages or variants preceded epidemic waves, highlighting the importance of implementing well structured genomic surveillance at a national level to detect and monitor emerging and circulating variants.

FUNDING

Medical Research Unit The Gambia at London School of Hygiene & Tropical Medicine, UK Research and Innovation, WHO.

Multiple introduced lineages and the single native lineage co-driving the four waves of the COVID-19 pandemic in West Africa

Coronavirus disease 2019 (COVID-19) has become a vast burden on public health and socioeconomics in West Africa, but the epidemic situation is unclear. Therefore, we conducted a retrospective analysis of the positive rate, death rate, and diversity of SARS-CoV-2. As of March 31, 2022, a total of 894,813 cases of COVID-19 have been recorded, with 12,028 deaths, both of which were distributed in all 16 countries. There were four waves of COVID-19 during this period. Most cases were recorded in the second wave, accounting for 34.50% of total cases. These data suggest that although West Africa seems to have experienced a low and relatively slow spread of COVID-19, the epidemic was ongoing, evolving with each COVID-19 global pandemic wave. Most cases and most deaths were both recorded in Nigeria. In contrast, the fewest cases and fewest deaths were reported, respectively, in Liberia and Sierra Leone. However, high death rates were found in countries with low incidence rates. These data suggest that the pandemic in West Africa has so far been heterogeneous, which is closely related to the infrastructure of public health and socioeconomic development (e.g., extreme poverty, GDP per capita, and human development index). At least eight SARS-CoV-2 variants were found, namely, Delta, Omicron, Eta, Alpha, Beta, Kappa, Iota, and Gamma, which showed high diversity, implicating that multiple-lineages from different origins were introduced. Moreover, the Eta variant was initially identified in Nigeria and distributed widely. These data reveal that the COVID-19 pandemic in the continent was co-driven by both multiple introduced lineages and a single native lineage. We suggest enhancing the quarantine measures upon entry at the borders and implementing a genome surveillance strategy to better understand the transmission dynamics of the COVID-19 pandemic in West Africa.

The non-pharmaceutical interventions may affect the advantage in transmission of mutated variants during epidemics: A conceptual model for COVID-19

As the COVID-19 pandemic continues, genetic mutations in SARS-CoV-2 emerge, and some of them are found more contagious than the previously identified strains, acting as the major mechanism for many large-scale epidemics. The transmission advantage of mutated variants is widely believed as an innate biological feature that is difficult to be altered by artificial factors. In this study, we explore how non-pharmaceutical interventions (NPI) may affect transmission advantage. A two-strain compartmental epidemic model is proposed and simulated to investigate the biological mechanism of the relationships among different NPIs, the changes in transmissibility of each strain and transmission advantage. Although the NPIs are effective in flattening the epidemic curve, we demonstrate that NPIs probably lead to a decline in transmission advantage, which is likely to occur if the NPIs become intensive. Our findings uncover the mechanistic relationship between NPIs and transmission advantage dynamically, and highlight the important role of NPIs not only in controlling the intensity of epidemics but also in slowing or even containing the growth of the proportion of variants.