SARS-CoV-2 BW lineage, a fast-growing Omicron variant from southeast Mexico bearing relevant escape mutations.

PURPOSE: The swift expansion of the BW.1 SARS-CoV-2 variant coincided with a rapid increase of COVID-19 cases occurring in Southeast Mexico in October, 2022, which marked the start of Mexico's sixth epidemiological wave. In Yucatan, up to 92% (58 of 73) of weekly sequenced genomes between epidemiological week 42 and 47 were identified as either BW.1 or its descendant, BW.1.1 in the region, during the last trimester of 2022. In the current study, a comprehensive genomic comparison was carried out to characterize the evolutionary history of the BW lineage, identifying its origins and its most important mutations. METHODS: An alignment of all the genomes of the BW lineage and its parental BA.5.6.2 variant was carried out to identify their mutations. A phylogenetic and ancestral sequence reconstruction analysis with geographical inference, as well as a longitudinal analysis of point mutations, were performed to trace back their origin and contrast them with key RBD mutations in variant BQ.1, one of the fastest-growing lineages to date. RESULTS: Our ancestral reconstruction analysis portrayed Mexico as the most probable origin of the BW.1 and BW.1.1 variants. Two synonymous substitutions, T7666C and C14599T, support their Mexican origin, whereas other two mutations are specific to BW.1: S:N460K and ORF1a:V627I. Two additional substitutions and a deletion are found in its descending subvariant, BW.1.1. Mutations found in the receptor binding domain, S:K444T, S:L452R, S:N460K, and S:F486V in BW.1 have been reported to be relevant for immune escape and are also key mutations in the BQ.1 lineage. CONCLUSIONS: BW.1 appears to have arisen in the Yucatan Peninsula in Southeast Mexico sometime around July 2022 during the fifth COVID-19 wave. Its rapid growth may be in part explained by the relevant escape mutations also found in BQ.1.

Socio-demographic variables can guide prioritized testing strategies for epidemic control in resource-limited contexts.

BACKGROUND: Targeted surveillance allows public health authorities to implement testing and isolation strategies when diagnostic resources are limited, and can be implemented via the consideration of social network topologies. Yet, it remains unclear how to implement such surveillance and control when network data are unavailable. METHODS: We evaluated the ability of socio-demographic proxies of degree centrality to guide prioritized testing of infected individuals compared to known degree centrality. Proxies were estimated via readily-available socio-demographic variables (age, gender, marital status, educational attainment, and household size). We simulated SARS-CoV-2 epidemics via a SEIR individual-based model on two contact networks from rural Madagascar to further test the applicability of these findings to low-resource contexts. RESULTS: Targeted testing using socio-demographic proxies performed similarly to targeted testing using known degree centralities. At a low testing capacity, using the proxies reduced the infection burden by 22-33% while using 20% fewer tests, compared to random testing. By comparison, using known degree centrality reduced the infection burden by 31-44% while using 26-29% fewer tests. CONCLUSIONS: We demonstrate that incorporating social network information into epidemic control strategies is an effective countermeasure to low testing capacity and can be implemented via socio-demographic proxies when social network data are unavailable.

[Biodiversity loss, first step for viral emergences]. / Perte de biodiversité, prélude aux émergences virales.

Today, the emergence of zoonoses is one of the biggest concerns for human health. With the recent examples of the Ebola virus, avian flus or coronaviruses, this threat is intensifying and raising fears of pandemics of the same magnitude as Covid-19. In this article, we review the state of knowledge about the mechanisms involved in these emergences, especially the impact of human activities on ecosystems, the intensive breeding of domestic animals or wildlife trade. We conclude on the importance of adopting a real integrated "One Health" approach in order to implement solutions at the beginning of this process of emergence and thus prevent new catastrophes.

Title: Perte de biodiversité, prélude aux émergences virales. Abstract: Aujourd'hui, l'émergence de zoonoses est un phénomène des plus préoccupants. Avec les exemples récents du virus Ebola, des virus responsables des grippes aviaires, ou des coronavirus, cette menace s'intensifie et fait craindre des pandémies de la même ampleur que celle de la Covid-19. Dans cette synthèse, nous dressons l'état des connaissances sur les mécanismes impliqués dans ces émergences, que ce soit l'impact de l'homme sur les écosystèmes, l'élevage intensif d'animaux domestiques, ou encore le commerce de la faune sauvage. Nous concluons sur l'importance d'adopter une réelle approche intégrée « Une seule santé ¼ (One health) afin d'implémenter des solutions au début de ce processus d'émergence et ainsi de prévenir de nouvelles catastrophes.

Omicron-BA.1 Dispersion Rates in Mexico Varied According to the Regional Epidemic Patterns and the Diversity of Local Delta Subvariants.

PURPOSE: The Omicron subvariant BA.1 of SARS-CoV-2 was first detected in November 2021 and quickly spread worldwide, displacing the Delta variant. In this work, a characterization of the spread of this variant in Mexico is presented. METHODS: The time to fixation of BA.1, the diversity of Delta sublineages, the population density, and the level of virus circulation during the inter-wave interval were determined to analyze differences in BA.1 spread. RESULTS: BA.1 began spreading during the first week of December 2021 and became dominant in the next three weeks, causing the fourth COVID-19 epidemiological surge in Mexico. Unlike previous variants, BA.1 did not exhibit a geographically distinct circulation pattern. However, a regional difference in the speed of the replacement of the Delta variant was observed. CONCLUSIONS: Viral diversity and the relative abundance of the virus in a particular area around the time of the introduction of a new lineage seem to have influenced the spread dynamics, in addition to population density. Nonetheless, if there is a significant difference in the fitness of the variants, or if the time allowed for the competition is sufficiently long, it seems the fitter virus will eventually become dominant, as observed in the eventual dominance of the BA.1.x variant in Mexico.

Retrospective analysis of SARS-CoV-2 omicron invasion over delta in French regions in 2021-22: a status-based multi-variant model.

BACKGROUND: SARS-CoV-2 is a rapidly spreading disease affecting human life and the economy on a global scale. The disease has caused so far more then 5.5 million deaths. The omicron outbreak that emerged in Botswana in the south of Africa spread around the globe at further increased rates, and caused unprecedented SARS-CoV-2 infection incidences in several countries. At the start of December 2021 the first omicron cases were reported in France. METHODS: In this paper we investigate the spreading potential of this novel variant relatively to the delta variant that was also in circulation in France at that time. Using a dynamic multi-variant model accounting for cross-immunity through a status-based approach, we analyze screening data reported by Santé Publique France over 13 metropolitan French regions between 1st of December 2021 and the 30th of January 2022. During the investigated period, the delta variant was replaced by omicron in all metropolitan regions in approximately three weeks. The analysis conducted retrospectively allows us to consider the whole replacement time window and compare regions with different times of omicron introduction and baseline levels of variants' transmission potential. As large uncertainties regarding cross-immunity among variants persist, uncertainty analyses were carried out to assess its impact on our estimations. RESULTS: Assuming that 80% of the population was immunized against delta, a cross delta/omicron cross-immunity of 25% and an omicron generation time of 3.5 days, the relative strength of omicron to delta, expressed as the ratio of their respective reproduction rates, [Formula: see text], was found to range between 1.51 and 1.86 across regions. Uncertainty analysis on epidemiological parameters led to [Formula: see text] ranging from 1.57 to 2.34 on average over the metropolitan French regions, weighted by population size. CONCLUSIONS: Upon introduction, omicron spread rapidly through the French territory and showed a high fitness relative to delta. We documented considerable geographical heterogeneities on the spreading dynamics. The historical reconstruction of variant emergence dynamics provide valuable ground knowledge to face future variant emergence events.

Prioritizing COVID-19 vaccination efforts and dose allocation within Madagascar.

BACKGROUND: While mass COVID-19 vaccination programs are underway in high-income countries, limited availability of doses has resulted in few vaccines administered in low and middle income countries (LMICs). The COVID-19 Vaccines Global Access (COVAX) is a WHO-led initiative to promote vaccine access equity to LMICs and is providing many of the doses available in these settings. However, initial doses are limited and countries, such as Madagascar, need to develop prioritization schemes to maximize the benefits of vaccination with very limited supplies. There is some consensus that dose deployment should initially target health care workers, and those who are more vulnerable including older individuals. However, questions of geographic deployment remain, in particular associated with limits around vaccine access and delivery capacity in underserved communities, for example in rural areas that may also include substantial proportions of the population. METHODS: To address these questions, we developed a mathematical model of SARS-CoV-2 transmission dynamics and simulated various vaccination allocation strategies for Madagascar. Simulated strategies were based on a number of possible geographical prioritization schemes, testing sensitivity to initial susceptibility in the population, and evaluating the potential of tests for previous infection. RESULTS: Using cumulative deaths due to COVID-19 as the main outcome of interest, our results indicate that distributing the number of vaccine doses according to the number of elderly living in the region or according to the population size results in a greater reduction of mortality compared to distributing doses based on the reported number of cases and deaths. The benefits of vaccination strategies are diminished if the burden (and thus accumulated immunity) has been greatest in the most populous regions, but the overall strategy ranking remains comparable. If rapid tests for prior immunity may be swiftly and effectively delivered, there is potential for considerable gain in mortality averted, but considering delivery limitations modulates this. CONCLUSION: At a subnational scale, our results support the strategy adopted by the COVAX initiative at a global scale.

On the need for integrating cancer into the One Health perspective.

Recent pandemics have highlighted the urgency to connect disciplines studying animal, human, and environment health, that is, the "One Health" concept. The One Health approach takes a holistic view of health, but it has largely focused on zoonotic diseases while not addressing oncogenic processes. We argue that cancers should be an additional key focus in the One Health approach based on three factors that add to the well-documented impact of humans on the natural environment and its implications on cancer emergence. First, human activities are oncogenic to other animals, exacerbating the dynamics of oncogenesis, causing immunosuppressive disorders in wildlife with effects on host-pathogen interactions, and eventually facilitating pathogen spillovers. Second, the emergence of transmissible cancers in animal species (including humans) has the potential to accelerate biodiversity loss across ecosystems and to become pandemic. It is crucial to understand why, how, and when transmissible cancers emerge and spread. Third, translating knowledge of tumor suppressor mechanisms found across the Animal Kingdom to human health offers novel insights into cancer prevention and treatment strategies.

A mechanistic and data-driven reconstruction of the time-varying reproduction number: Application to the COVID-19 epidemic.

The effective reproduction number Reff is a critical epidemiological parameter that characterizes the transmissibility of a pathogen. However, this parameter is difficult to estimate in the presence of silent transmission and/or significant temporal variation in case reporting. This variation can occur due to the lack of timely or appropriate testing, public health interventions and/or changes in human behavior during an epidemic. This is exactly the situation we are confronted with during this COVID-19 pandemic. In this work, we propose to estimate Reff for the SARS-CoV-2 (the etiological agent of the COVID-19), based on a model of its propagation considering a time-varying transmission rate. This rate is modeled by a Brownian diffusion process embedded in a stochastic model. The model is then fitted by Bayesian inference (particle Markov Chain Monte Carlo method) using multiple well-documented hospital datasets from several regions in France and in Ireland. This mechanistic modeling framework enables us to reconstruct the temporal evolution of the transmission rate of the COVID-19 based only on the available data. Except for the specific model structure, it is non-specifically assumed that the transmission rate follows a basic stochastic process constrained by the observations. This approach allows us to follow both the course of the COVID-19 epidemic and the temporal evolution of its Reff(t). Besides, it allows to assess and to interpret the evolution of transmission with respect to the mitigation strategies implemented to control the epidemic waves in France and in Ireland. We can thus estimate a reduction of more than 80% for the first wave in all the studied regions but a smaller reduction for the second wave when the epidemic was less active, around 45% in France but just 20% in Ireland. For the third wave in Ireland the reduction was again significant (>70%).

Parallel trends in the transmission of SARS-CoV-2 and retail/recreation and public transport mobility during non-lockdown periods.

Recent literature strongly supports the hypothesis that mobility restriction and social distancing play a crucial role in limiting the transmission of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). During the first wave of the coronavirus disease 2019 (COVID-19) pandemic, it was shown that mobility restriction reduced transmission significantly. This study found that, in the period between the first two waves of the COVID-19 pandemic, there was high positive correlation between trends in the transmission of SARS-CoV-2 and mobility. These two trends oscillated simultaneously, and increased mobility following the relaxation of lockdown rules was significantly associated with increased transmission. From a public health perspective, these results highlight the importance of tracking changes in mobility when relaxing mitigation measures in order to anticipate future changes in the spread of SARS-CoV-2.

The impact of lockdown strategies targeting age groups on the burden of COVID-19 in France.

Due to the COVID-19 pandemic, many countries have implemented a complete lockdown of their population that may not be sustainable for long. To identify the best strategy to replace this full lockdown, sophisticated models that rely on mobility data have been developed. In this study, using the example of France as a case-study, we develop a simple model considering contacts between age classes to derive the general impact of partial lockdown strategies targeted at specific age groups. We found that epidemic suppression can only be achieved by targeting isolation of young and middle age groups with high efficiency. All other strategies tested result in a flatter epidemic curve, with outcomes in (e.g. mortality and health system over-capacity) dependent of the age groups targeted and the isolation efficiency. Targeting only the elderly can decrease the expected mortality burden, but in proportions lower than more integrative strategies involving several age groups. While not aiming to provide quantitative forecasts, our study shows the benefits and constraints of different partial lockdown strategies, which could help guide decision-making.

Reconciling model predictions with low reported cases of COVID-19 in Sub-Saharan Africa: insights from Madagascar.

COVID-19 has wreaked havoc globally with particular concerns for sub-Saharan Africa (SSA), where models suggest that the majority of the population will become infected. Conventional wisdom suggests that the continent will bear a higher burden of COVID-19 for the same reasons it suffers from other infectious diseases: ecology, socio-economic conditions, lack of water and sanitation infrastructure, and weak health systems. However, so far SSA has reported lower incidence and fatalities compared to the predictions of standard models and the experience of other regions of the world. There are three leading explanations, each with different implications for the final epidemic burden: (1) low case detection, (2) differences in epidemiology (e.g. low R 0 ), and (3) policy interventions. The low number of cases have led some SSA governments to relaxing these policy interventions. Will this result in a resurgence of cases? To understand how to interpret the lower-than-expected COVID-19 case data in Madagascar, we use a simple age-structured model to explore each of these explanations and predict the epidemic impact associated with them. We show that the incidence of COVID-19 cases as of July 2020 can be explained by any combination of the late introduction of first imported cases, early implementation of non-pharmaceutical interventions (NPIs), and low case detection rates. We then re-evaluate these findings in the context of the COVID-19 epidemic in Madagascar through August 2020. This analysis reinforces that Madagascar, along with other countries in SSA, remains at risk of a growing health crisis. If NPIs remain enforced, up to 50,000 lives may be saved. Even with NPIs, without vaccines and new therapies, COVID-19 could infect up to 30% of the population, making it the largest public health threat in Madagascar for the coming year, hence the importance of clinical trials and continually improving access to healthcare.

Was the COVID-19 pandemic avoidable? A call for a "solution-oriented" approach in pathogen evolutionary ecology to prevent future outbreaks.

Concerns about the prospect of a global pandemic have been triggered many times during the last two decades. These have been realised through the current COVID-19 pandemic, due to a new coronavirus SARS-CoV2, which has impacted almost every country on Earth. Here, we show how considering the pandemic through the lenses of the evolutionary ecology of pathogens can help better understand the root causes and devise solutions to prevent the emergence of future pandemics. We call for better integration of these approaches into transdisciplinary research and invite scientists working on the evolutionary ecology of pathogens to contribute to a more "solution-oriented" agenda with practical applications, emulating similar movements in the field of economics in recent decades.