ABSTRACT
BackgroundInfections represent highly dynamic processes, characterized by evolutionary changes and events that involve both the pathogen and the host. Among infectious agents, viruses, such as the "Severe Acute Respiratory Syndrome-related Coronavirus type 2" (SARS-CoV-2), the infectious agent responsible for the currently ongoing "Coronavirus disease 2019" (COVID-2019) pandemic, have a particularly high mutation rate. Taking into account the mutational landscape of an infectious agent, it is important to shed light on its evolution capability over time. As new, more infectious strains of COVID-19 emerge around the world, it is imperative to estimate when these new strains may overtake the wild-type strain in different populations. Therefore, we developed a general-purpose framework to estimate the time at which a mutant variant is able to takeover a wild-type strain during an emerging infectious diseases outbreak. In this study, we used COVID-19 as a case-study, but the model is adaptable to any emerging pathogens. Methods and findingsWe devise a two-strain mathematical framework, to model a wild- and a mutant-type viral population and fit cumulative case data to parameterize the model, using Ontario as a case study. We found that, in the context of under-reporting and the current case levels, a variant strain is unlikely to dominate until March/April 2021. Current non-pharmaceutical interventions in Ontario need to be kept in place longer even with vaccination in order to prevent another outbreak. The spread of a variant strain in Ontario will mostly likely be observed by a widened peak of the daily reported cases. If vaccine efficacy is maintained across strains, then it is still possible to have an immune population by end of 2021. ConclusionsOur findings have important practical implications in terms of public health as policy-and decision-makers are equipped with a mathematical tool that can enable the estimation of the take-over of a mutant strain of an emerging infectious disease.
ABSTRACT
BackgroundRecently, two "Coronavirus disease 2019" (COVID-19) vaccine products have been authorized in Canada. It is of crucial importance to model an integrated/combined package of non-pharmaceutical (physical/social distancing) and pharmaceutical (immunization) public health control measures. MethodsA modified epidemiological, compartmental SIR model was utilized and fit to the cumulative COVID-19 case data for the province of Ontario, Canada, from September 8, 2020 to December 8, 2020. Different vaccine roll-out strategies were simulated until 75 percent of the population is vaccinated, including a no-vaccination scenario. We compete these vaccination strategies with relaxation of non-pharmaceutical interventions. Non-pharmaceutical interventions were supposed to remain enforced and began to be relaxed on either January 31, March 31, or May 1, 2021. ResultsBased on projections from the data and long-term extrapolation of scenarios, relaxing the public health measures implemented by re-opening too early would cause any benefits of vaccination to be lost by increasing case numbers, increasing the effective reproduction number above 1 and thus increasing the risk of localized outbreaks. If relaxation is, instead, delayed and 75 percent of the Ontarian population gets vaccinated by the end of the year, re-opening can occur with very little risk. InterpretationRelaxing non-pharmaceutical interventions by re-opening and vaccine deployment is a careful balancing act. Our combination of model projections from data and simulation of different strategies and scenarios, can equip local public health decision- and policy-makers with projections concerning the COVID-19 epidemiological trend, helping them in the decision-making process.
ABSTRACT
BackgroundPublic health recommendations and governmental measures during the COVID-19 pandemic have enforced numerous restrictions on daily living including social distancing, isolation and home confinement. While these measures are imperative to abate the spreading of COVID-19, the impact of these restrictions on health behaviours and lifestyle at home is undefined. Therefore, an international online survey was launched in April 2020 in seven languages to elucidate the behavioral and lifestyle consequences of COVID-19 restrictions. This report presents the preliminary results from the first thousand responders on physical activity (PA) and nutrition behaviours. MethodsThirty-five research organisations from Europe, North-Africa, Western Asia and the Americas promoted the survey through their networks to the general society, in English, German, French, Arabic, Spanish, Portugese, and Slovenian languages. Questions were presented in a differential format with questions related to responses "before" and "during" confinement conditions. Results1047 replies (54% women) from Asia (36%), Africa (40%), Europe (21%) and other (3%) were included into a general analysis. The COVID-19 home confinement had a negative effect on all intensities of PA (vigorous, moderate, walking and overall). Conversely, daily sitting time increased from 5 to 8 hours per day. Additionally, food consumption and meal patterns (the type of food, eating out of control, snacks between meals, number of meals) were more unhealthy during confinement with only alcohol binge drink decreasing significantly. ConclusionWhile isolation is a necessary measure to protect public health, our results indicate that it alters physical activity and eating behaviours in a direction that would compromise health. A more detailed analysis of survey data will allow for a segregation of these responses in different age groups, countries and other subgroups which will help develop bespoke interventions to mitigate the negative lifestyle behaviors manifest during the COVID-19 confinement.
