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monstrated a prophylactic effect of garlic in the prevention of widespread viral infections in humans through enhancing the immune response. This review highlights that garlic possesses significant antiviral activity and can be used prophylactically in the prevention of viral infections.
In humanitarian contexts, ensuring access to safe, nutritious, good quality and culturally appropriate food in the right quantity at the right time and place during an emergency or a protracted crisis is an enormous challenge, which is likely to increase given uncertainties such as climate change, global political and economic instability and emerging pandemics like COVID-19. Several international organizations and non-government organizations have well established systems to respond to food security emergencies. However, the role of food science and technology in humanitarian response is not well understood and is seldom considered in humanitarian circles.

The role of food science and technology in humanitarian response and the importance of addressing the requirements of the local consumers within the local food systems are discussed.

Humanitarian food aid policies focus on immediate and short-term assistance to save lives. The implementation of emergency programs and projects tends to induce dependene needs to be a move beyond rehabilitating and increasing agricultural production to addressing the whole food system with a view to link humanitarian assistance and longer-term support to sustainable livelihoods and resilience.
Currently, there is great concern about the consequences of COVID-19 on health and also on food supply globally. Ceasas are important food distribution centers in Brazil that have great economic importance in Brazilian agribusiness.

In this work, the price of fruits and vegetables sold in four Ceasas in different regions affected by COVID-19 in the first quarter of 2020 were evaluated, with the aim of verifying the possible effects of the pandemic on food supply chains. Data were collected from the institutions' websites and subjected to analysis of variance and Tukey's test (p≤0.05), principal component analysis and Cluster analysis (Euclidean distance).

The regions affected by COVID-19 showed great variations in the prices of products sold in the studied Ceasas. Statistical analysis showed that food prices were dependent on the regions and the period in which they were traded. In general, the month of March proved to have the greatest impact on the consumer's pocket. The strengthening of Ceasas as platforms for supplying food from short supply chains is essential to guarantee internal food security during crises such as that caused by the new coronavirus.
The regions affected by COVID-19 showed great variations in the prices of products sold in the studied Ceasas. Statistical analysis showed that food prices were dependent on the regions and the period in which they were traded. In general, the month of March proved to have the greatest impact on the consumer's pocket. The strengthening of Ceasas as platforms for supplying food from short supply chains is essential to guarantee internal food security during crises such as that caused by the new coronavirus.Started in Wuhan, China, the COVID-19 has been spreading all over the world. We calibrate the logistic growth model, the generalized logistic growth model, the generalized Richards model and the generalized growth model to the reported number of infected cases for the whole of China, 29 provinces in China, and 33 countries and regions that have been or are undergoing major outbreaks. We dissect the development of the epidemics in China and the impact of the drastic control measures both at the aggregate level and within each province. We quantitatively document four phases of the outbreak in China with a detailed analysis on the heterogeneous situations across provinces. The extreme containment measures implemented by China were very effective with some instructive variations across provinces. Linsitinib purchase Borrowing from the experience of China, we made scenario projections on the development of the outbreak in other countries. We identified that outbreaks in 14 countries (mostly in western Europe) have ended, while resurgences of cases have been identified in several among them. The modeling results clearly show longer after-peak trajectories in western countries, in contrast to most provinces in China where the after-peak trajectory is characterized by a much faster decay. We identified three groups of countries in different level of outbreak progress, and provide informative implications for the current global pandemic.Since the outbreak of coronavirus disease in 2019 (COVID-19), the disease has rapidly spread to the world, and the cumulative number of cases is now more than 2.3 million. We aim to study the spread mechanism of rumors on social network platform during the spread of COVID-19 and consider education as a control measure of the spread of rumors. Firstly, a novel epidemic-like model is established to characterize the spread of rumor, which depends on the nonautonomous partial differential equation. Furthermore, the registration time of network users is abstracted as 'age,' and the spreading principle of rumors is described from two dimensions of age and time. Specifically, the susceptible users are divided into higher-educators class and lower-educators class, in which the higher-educators class will be immune to rumors with a higher probability and the lower-educators class is more likely to accept and spread the rumors. Secondly, the existence and uniqueness of the solution is discussed and the stability of steady-state solution of the model is obtained. Additionally, an interesting conclusion is that the education level of the crowd is an essential factor affecting the final scale of the spread of rumors. Finally, some control strategies are presented to effectively restrain the rumor propagation, and numerical simulations are carried out to verify the main theoretical results.An epidemiological model for COVID-19 was developed and implemented in MATLAB/GNU Octave for use by public health practitioners, policy makers, and the general public. The model distinguishes four stages in the disease infected, sick, seriously sick, and better. The model was preliminarily parameterized based on observations of the spread of the disease. The model assumes a case mortality rate of 1.5%. Preliminary simulations with the model indicate that concepts such as "herd immunity" and containment ("flattening the curve") are highly misleading in the context of this virus. Public policies based on these concepts are inadequate to protect the population. Only reducing the R0 of the virus below 1 is an effective strategy for maintaining the death burden of COVID-19 within the normal range of seasonal flu. The model is illustrated with the cases of Italy, France, and Iran and is able to describe the number of deaths as a function of time in all these cases although future projections tend to slightly overestimate the number of deaths when the analysis is made early on.
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