Influence of environmental factors on the spread of COVID-19 in Saudi Arabia

Background Coronavirus disease 2019 (COVID-19) has affected millions of people worldwide. The infection is mostly spread through the inhalation of infected droplets. Saudi Arabia is a vast country having different climatic conditions. Methods The study evaluated the influence of environmental factors on the spread of COVID-19. Six zones (A to F) were classified depending on the climatic conditions. The study was conducted by retrospective analysis of COVID-19 records from the ministry of health between the months of September 2020 and August 2021. The environmental data such as average temperature (°C), humidity (%), wind speed (m/s) and sun exposure (kwh/m2) were retrieved from official sites. The data was analyzed to determine the effect of these factors on the spread of COVID-19. SPSS IBM 25 software was used to conduct the analysis and p < 0.05 was considered to indicate the significance of the results. Results According to the findings, the rate of infection was greater between April and July 2021. Six climatic zones experienced high temperatures, little humidity, consistent wind flow, and intense sun exposure throughout this time. The correlation study revealed a significant (p < 0.05) relationship between the environmental factors and the spread of COVID-19. The data suggested that during summer condition when the weather is hot, less humid, and steady wind flow with lots of sun exposure, the COVID-19 infection rate got augmented in Saudi Arabia. Poor ventilation and closed-door habitats in an air-conditioned atmosphere during this period could have played a role in human transmission. More research on air quality, population mobility and diseased condition is essential, so that precise proactive measures can be designed to limit the spread of infection in specific climatic seasons.

Refugee Policies and Narratives in the Globalised Era

One of the effects of globalisation has been population mobility as a result of famine, climate warming and war conflicts, among other things. This flow of refugees, however, is often seen as a menace to the rule of law and human rights concomitant with the Western lifestyle. Refugees are no longer regarded as human beings and victims, but rather as danger, even as potential terrorists, which has led many governments, including the Australian, to detain them indefinitely in detention centres where they are confined in inhuman conditions. The main aim of this paper will be to describe Australian immigration policies and how contemporary Australian narratives on and by refugees are reflecting this situation, mainly by analysing a selection of texts from three recently published collections, namely, A Country Too Far (2013), They Cannot Take the Sky (2017) and Seabirds Crying in the Harbour Dark (2017), and Behrouz Boochani’s No Friend but the Mountains (2018).

Evaluation of urban and rural population flow and spatial planning effect under the background of big data

In order to improve the effect of urban and rural regional spatial planning and resource allocation, we need to focus on the factor of urban and rural population flow. Therefore, this paper evaluates the effect of urban and rural population mobility and spatial planning under the background of big data. Based on the evaluation of the effect of urban-rural population migration, according to the evaluation principle of the effect of urban-rural population migration after the reform and opening up, the evaluation index system is constructed, the dimensionless processing of the evaluation index system is carried out, the evaluation index weight is calculated, and the evaluation index is quantified, so as to complete the effect evaluation of spatial planning. Finally, taking Tianjin as an example, the application effect of this design method is verified.

Geographic Disparities and Determinants of COVID-19 Incidence Risk in the Greater St. Louis Area, Missouri

Background: Evidence suggests that the risk of Coronavirus Disease 2019 (COVID-19) varies geographically due to differences in population characteristics. Therefore, the objectives of this study were to identify: (a) geographic disparities of COVID-19 risk in the Greater St. Louis area of Missouri, USA; (b) predictors of the identified disparities. Methods: Data on COVID-19 incidence and chronic disease hospitalizations were obtained from the Departments of Health and Missouri Hospital Association, respectively. Socioeconomic and demographic data were obtained from the 2018 American Community Survey while population mobility data were obtained from the SafeGraph website. Choropleth maps were used to identify geographic disparities of COVID-19 risk and its predictors at the ZIP Code Tabulation Area (ZCTA) spatial scale. Global negative binomial and local geographically weighted negative binomial models were used to identify predictors of ZCTA-level geographic disparities of COVID-19 risk. Results: There were geographic disparities in COVID-19 risk. Risks tended to be higher in ZCTAs with high percentages of the population with a bachelors degree (p<0.0001) and obesity hospitalizations (p<0.0001). Conversely, risks tended to be lower in ZCTAs with high percentages of the population working in agriculture (p<0.0001). However, the association between agricultural occupation and COVID-19 risk was modified by per capita between ZCTA visits. Areas that had both high per capita between ZCTA visits and high percentages of the population employed in agriculture had high COVID-19 risks. The strength of association between agricultural occupation and COVID-19 risk varied by geographic location. Conclusions: Geographic Information Systems, global and local models are useful for identifying geographic disparities and predictors of COVID-19 risk. Geographic disparities of COVID-19 risk exist in the St. Louis area and are explained by differences in sociodemographic factors, population movements, and obesity hospitalization risks. The latter is particularly concerning due to the growing prevalence of obesity and the known immunological impairments among obese individuals. Therefore, future studies need to focus on improving our understanding of the relationships between COVID-19 vaccination efficacy, obesity and waning of immunity among obese individuals so as to better guide vaccination regimens, reduce disparities and improve population health for all.

Effects of population mobility on the COVID-19 spread in Brazil

This article proposes a study of the SARS-CoV-2 virus spread and the efficacy of public policies in Brazil. Using both aggregated (from large Internet companies) and fine-grained (from Departments of Motor Vehicles) mobility data sources, our work sheds light on the effect of mobility on the pandemic situation in the Brazilian territory. Our main contribution is to show how mobility data, particularly fine-grained ones, can offer valuable insights into virus propagation. For this, we propose a modification in the SENUR model to add mobility information, evaluating different data availability scenarios (different information granularities), and finally, we carry out simulations to evaluate possible public policies. In particular, we conduct a case study that shows, through simulations of hypothetical scenarios, that the contagion curve in several Brazilian cities could have been milder if the government had imposed mobility restrictions soon after reporting the first case. Our results also show that if the government had not taken any action and the only safety measure taken was the population’s voluntary isolation (out of fear), the time until the contagion peak for the first wave would have been postponed, but its value would more than double.

Domestic and international mobility trends in the United Kingdom during the COVID-19 pandemic: an analysis of facebook data

Background Since early March 2020, the COVID-19 epidemic across the United Kingdom has led to a range of social distancing policies, which resulted in changes to mobility across different regions. An understanding of how these policies impacted travel patterns over time and at different spatial scales is important for designing effective strategies, future pandemic planning and in providing broader insights on the population geography of the country. Crowd level data on mobile phone usage can be used as a proxy for population mobility patterns and provide a way of quantifying in near-real time the impact of social distancing measures on changes in mobility. Methods Here we explore patterns of change in densities, domestic and international flows and co-location of Facebook users in the UK from March 2020 to March 2021. Results We find substantial heterogeneities across time and region, with large changes observed compared to pre-pademic patterns. The impacts of periods of lockdown on distances travelled and flow volumes are evident, with each showing variations, but some significant reductions in co-location rates. Clear differences in multiple metrics of mobility are seen in central London compared to the rest of the UK, with each of Scotland, Wales and Northern Ireland showing significant deviations from England at times. Moreover, the impacts of rapid changes in rules on international travel to and from the UK are seen in substantial fluctuations in traveller volumes by destination. Conclusions While questions remain about the representativeness of the Facebook data, previous studies have shown strong correspondence with census-based data and alternative mobility measures, suggesting that findings here are valuable for guiding strategies.

The deuce-ace of Lassa Fever, Ebola virus disease and COVID-19 simultaneous infections and epidemics in West Africa: clinical and public health implications

Globally, the prevailing COVID-19 pandemic has caused unprecedented clinical and public health concerns with increasing morbidity and mortality. Unfortunately, the burden of COVID-19 in Africa has been further exacerbated by the simultaneous epidemics of Ebola virus disease (EVD) and Lassa Fever (LF) which has created a huge burden on African healthcare systems. As Africa struggles to contain the spread of the second (and third) waves of the COVID-19 pandemic, the number of reported cases of LF is also increasing, and recently, new outbreaks of EVD. Before the pandemic, many of Africa’s frail healthcare systems were already overburdened due to resource limitations in staffing and infrastructure, and also, multiple endemic tropical diseases. However, the shared epidemiological and pathophysiological features of COVID-19, EVD and LF as well their simultaneous occurrence in Africa may result in misdiagnosis at the onset of infection, an increased possibility of co-infection, and rapid and silent community spread of the virus(es). Other challenges include high population mobility across porous borders, risk of human-to-animal transmission and reverse zoonotic spread, and other public health concerns. This review highlights some major clinical and public health challenges toward responses to the COVID-19 pandemic amidst the deuce-ace of recurrent LF and EVD epidemics in Africa. Applying the One Health approach in infectious disease surveillance and preparedness is essential in mitigating emerging and re-emerging (co-)epidemics in Africa and beyond.

Population mobility and sustainable development in the Mamminasata Metropolitan South Sulawesi, Indonesia

Economic growth and urban agglomeration have triggered an increase in the size and mobility of the Metropolitan Mamminasata urban population. This study aims to analyse spatial interactions working as a determinant of connectivity of the transportation system and the growth of suburban areas toward smart and sustainable cities in the Mamminasata Metropolitan urban system and the effects that spatial expansion, spatial integration, urban agglomeration, spatial use, and the transportation system have on population mobility. The research method used is a sequential explanatory design that combines quantitative and qualitative research methods. The results show that the coefficients of determination are as follows: spatial expansion to population mobility – 4.90%, spatial integration to population mobility – 2.99%, spatial interaction to population mobility – 4.87%, urban agglomeration to population mobility – 2.09%, space use to population mobility – 2.64%, and transportation system to population mobility – 5.15%. The results of this study will assist in the formulation of development policies, management of the urban transportation system, and allocation of space utilisation going forward.