Estimating the infection horizon of COVID-19 in eight countries with a data-driven approach

Abstract

The COVID-19 pandemic has affected all countries of the world producing a substantial number of fatalities accompanied by a major disruption in their social, financial and educational organization [1]. The strict disciplinary measures implemented by China were very effective and thus were subsequently adopted by most world countries to various degrees. The infection duration and number of infected persons are of critical importance for the battle against the pandemic [2,3]. We use the quantitative landscape of the disease spreading in China as a benchmark and utilize infection data from eight countries to estimate the complete evolution of the infection in each of these countries. This analysis predicts both the expected number of daily infections per country and, perhaps more importantly, the duration of the epidemic in each country. Our predicted data show that Italy, Spain and the Netherlands have passed the highest point of infection while Greece, France and Germany are close to it.

Covid-19 pandemic and the unprecedented mobilisation of scholarly efforts prompted by a health crisis: Scientometric comparisons across SARS, MERS and 2019-nCoV literature

“…Though not shown in Fig. 3 , due to the respective values being smaller than 1%, journals in the following subject areas (those that are deemed minor areas in relation to Covid-19 literature) have each published a relatively considerable number of studies on this topic (a feature that is not necessarily shared by the rest of the literature on coronaviruses): Arts and Humanities (110 items, 2 where the most active journal has been Social Anthropology (24 items) covering topics such as “climate change reactions” (Bychkova 2020 ), or “legal voids linked to declared states of emergency” (Karaseva 2020 )), Economics, Econometrics and Finance (84 items, with Economic and Political Weekly (36 items) being the most active journal of that category, covering topics such as “food supply chains” (Reardon et al 2020 ), “economic stimulus packages” (Mulchandani 2020 ) or “reverse migration” (Dandekar and Ghai 2020 )), Physics and Astronomy (77 items, where Chaos Solitons and Fractals (16 items) has been the most active publication outlet, covering topics such as “mathematical models for forecasting the outbreak” (Barmparis and Tsironis 2020 ; Bekiros and Kouloumpou 2020 ; Boccaletti et al 2020 ; Ndaïrou et al 2020 ; Postnikov 2020 ; Ribeiro et al 2020 ; Zhang et al 2020 )), Energy (67 items, with International Journal of Advanced Science And Technology (44 items) being the most active journal in that category, covering topics such as “Flexible work arrangement in manufacturing” (Sedaju et al 2020 )), Material Sciences (57 items, with ACS Nano (10 items) being the most active outlet in that category, covering topics such as “3-D printed protective equipment” (Wesemann et al 2020 )), Decision Sciences (23 items, with Lancet Digital Health (8 items) and Transportation Research Interdisciplinary Perspectives (4 items) being the most active outlets in that category, covering topics such as “the effect of social distancing on travel behaviour” (De Vos 2020 ) or “the implementation of drive-through and walk-through diagnostic testing” (Lee and Lee 2020 )), Earth and Planetary Sciences (22 items, with Indonesian Journal of Science and Technology (8 items) being most active in that domain, covering topics such as “the deployment of drones in sending drugs and patient blood samples” (Anggraeni et al 2020 )).…”

In the midst of the perfect storm: Swift public health actions needed in order to increase societal safety during the COVID-19 pandemic

“…Biomedical and epidemiological understanding of COVID-19 remains limited, while basic tools such as approved therapeutics or vaccines are still missing (Herper, 2020). As a result, in the societal safety domain proposed measures are draconian and are aimed towards suppressing the pandemic wave by limiting human interaction, through social distancing ( Barmparis and Tsironis, 2020).…”

Modeling, Control, and Prediction of the Spread of COVID-19 Using Compartmental, Logistic, and Gauss Models: A Case Study in Iraq and Egypt

“…In addition, a numerical study has explained that the Gaussian model is a special version of the SEIR model. The introduction of gradual social distancing leads to a linear decrease in the infection rate [30]. In the Gaussian model, epidemics are initially exponential; later, as the population approaches carrying capacity, they approach zero, resulting in bell-shaped daily quantities.…”