Considered an essential activity, the production coming from slaughterhouses did not stop its activities in the midst of the new coronavirus pandemics (SARS COV-19) in Brazil. South and Southeast regions of Pará are examples of how such activity is associated to the worldwide production circuit. Nevertheless, the spatial circulation of the supplies coming from the slaughterhouses becomes one of the covid-19 transmission vectors, due to the intense mobility of workers in the sector.

Objective To estimate the effect of airline travel restrictions on the risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) importation. Methods We extracted passenger volume data for the entire global airline network, as well as the dates of the implementation of travel restrictions and the observation of the first case of coronavirus disease (COVID-19) in each country or territory, from publicly available sources. We calculated effective distance between every airport and the city of Wuhan, China.

Introduction: Portugal took early action to control the COVID-19 epidemic, initiating lockdown measures on March 16th when it recorded only 62 cases of COVID-19 per million inhabitants and reported no deaths. The Portuguese public complied quickly, reducing their overall mobility by 80%. The aim of this study was to estimate the initial impact of the lockdown in Portugal in terms of the reduction of the burden on the healthcare system.

Background and Aim: The use of geophysical analysis of the epidemiology to identify geographical factors affecting the prevalence of the disease can be effective on community health policies to control the prevalence of the virus. Therefore, the present study is a geographical analysis of the COVID-19 epidemiology in Iran. Therefore, the purpose of this study is the geographical analysis of coronavirus transmission in the country. Methods: This is a descriptive-analytical study and ArcGIS and GeoDa software has been used to analyze the data.

COVID-19 has had a rapid dissemination. Departing from China, the virus has traveled all around the world. With the use of accurate mathematical models, the global spread of the disease was anticipated. Some additional information to these predictive models could be provided by the comparison of freely available maps depicting commercial air travel routes and disease spread. This analysis informs on what seems to be a direct relationship between the initially unequal worldwide distribution of the disease and the density of the commercial air traffic.

In this paper, a simple susceptible-infected (SI) model is build for simulating the early phase of COVID-19 transmission process. By using the data collected from the newest epidemiological investigation, the parameters of SI model is estimated and compared with those from some other studies. The population migration data during Spring festival in China are collected from Baidu.

In this paper, we provide a statistical analysis of population movements leaving Wuhan based on mass population movement information which is collected by geographic services of Tencent and Baidu. Firstly, we find that the five million people leaving Wuhan before the official announcement that they will close the exits are not much different from the normal population movement during the previous Spring Festival travel rush. However, small portion of the population poured out of Wuhan in the last period before the exits closed.

The epidemic situation in the novel coronavirus input areas represented by Shenzhen has quickly stabilized under various prevention and control measures, since the novel coronavirus outbreak in China. In this paper, we use the SIQR (susceptible infection quarantined recovered) model of transmission dynamics to simulate the real epidemic development of Shenzhen, and score the strength of various control measures, simulate the epidemic development under different measures scores.

The statistical characteristics of the human mobility among different cities in the spreading of COVID-19 can be described by SI spreading model. P-SI models are presented to investigate how COVID-19 spreads or diffuses in Hubei and the other 4 provinces. Based on empirical data, some experiments are then conducted under the framework of the P-SI models. The experimental results demonstrate that the P-SI models can describe the number of daily new infected people caused by COVID-19 in Hubei and the other 4 provinces according to the empirical data.

The rapid spread of the novel coronavirus (COVID-19) from late 2019 to early 2020 poses a huge challenge to the public health of China and the world. The risk assessment of COVID-19 plays an essential role in the decision making of epidemic prevention. As one of the most important metropolitan areas in China, Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is seriously affected by COVID-19. A massive number of returnees after the holidays further poses potential COVID-19 risks.