Overview
Our team carried out a comparative analysis of the COVID-19 diffusion in North African countries, Algeria, Egypt, Morocco and Tunisia with the aim to study the effects of the containment efforts in different nations and the reliability of the predictions. The complete study covered six months of weekly data analysis. The comparison with data shows that the Coronavirus spreading has often different phases: an initial exponential behaviour, followed by a Gompertz one and/or by a logistic phase, due to containment effort.
The applied macroscopic deterministic growth models (Gompertz, logistic) have a clear advantage with respect to microscopic ones in the strong reduction of the free parameters driving the time evolution of the spread. This is a crucial aspect in predicting the behaviour of disease diffusion.
The ex-post verification of our short term predictions, weekly done for about five months (June-October 2020), shows an agreement with observed data within 5%.
Objectives & Challenges
The study of the growth phases of the disease permits to verify the restarting of the spreading after a stationarity period due to new outbreaks or to the weakness of the social control measures. The response of the National Health Systems to the emergency has been discussed and some short-term predictions on the cumulative number of confirmed infected, the hospitalizations and the total number of deaths have been carried out weekly from June to October 2020. The possible correlation with immigration in other Mediterranean Countries has been analyzed. Stable (or unstable) conditions of the spreading can quickly change due to a stronger or weaker application of the lockdown measures and short-term predictions turn out to be reliable.
The problem of reliable data did not allow an analogous study for Libya.
Main Findings
Long term predictions on the evolution of the spread of Covid-19 are often unreliable, but short term ones are extremely useful to understand the pressure on the National Health Systems and the effects of the political decisions on social isolations. This conclusion has been verified during 5 months of data analysis. The macroscopic growth laws applied in the study are an easy-to-use method for fast monitoring of the evolution of the disease. The results have been published in an international journal ( see the previous link). The stable (or unstable) condition of the spreading in North Africa can quickly change due to a stronger or weaker application of the lockdown measures. Tunisia and Egypt are clear examples of different phases, which produce strong effects on the National Health Systems.
The correlation between sea immigration and Covid-19 spreading follows, in a broad sense, the lockdown period of the European Countries, although there is a clear overlap with the political agreements among the European and North Africa Nations.
Main Recommendations
The FAIR principles, which describe how research outputs should be organised so they can be more easily accessed, understood, exchanged and reused, are a particular challenge for the Covid-19 spread data. We used the available data from the WHO, but other specific data ( for different nations and various stratified sectors) are difficult to obtain from the Local Governments. In this respect, the role of EOCS should be enhanced in the future, with precise collaboration networks among scientific organizations and local Governments from the very beginning of the projects.
The second point concerns the correlation between Covid-19/immigration. Although a quantitative study is possible based on the UNHCR data, the underlying social aspects
(local conditions and international decisions) od the effects of the pandemic on the immigrants from North Africa requires a detailed analysis to suggest correct political decision from European Union.
