Influence of health literacy of rural junior middle school students on knowledge, attitudes and practices of COVID-19 protection in Jiangxi Province

Objective: To understand the influence of junior middle school students' health literacy on knowledge, belief and behavior of COVID-19 in rural areas of Jiangxi Province, and to enhance junior middle school students' ability to deal with public health emergencies. Methods: Stratified cluster random sampling was used to investigate the health literacy, knowledge level and behavior of COVID-19 protection of 4 311 grade 7 to grade 8 students in rural areas of Jiangxi Province;Chi-square test and Logistic regression analysis were used to analyze the correlation between junior high school students' health literacy and COVID-19 protection knowledge, belief and behavior. Results: The rate of health literacy of junior middle school students in rural areas was 18.21%(n=785), the reported rate of intermediate level was high (n=2 454, 56.92%), and the reported rate of junior high school students at a low level of health literacy was 24.87%(n=1 072). The rate of junior middle school students in rural areas with good COVID-19 protection knowledge was 63.49%, the rate of positive protection attitude was 74.25%, and the rate of good protection behavior was 85.36%;Rate of COVID-19 protection knowledge (OR=4.85, 95%CI=3.80-6.18) and positive rate of protection attitude of high-level health literacy (OR=44.07, 95%CI=24.57-79.05), protective behavior possession rate (OR=25.99, 95%CI=19.67-34.35) were higher than those with low level of health literacy(P < 0.01). Conclusion: Health literacy is associated with COVID-19 protection knowledge, belief and behavior in rural junior high school students of Jiangxi Province, the findings provide direction for junior middle school students to improve their ability to deal with public health emergencies.

Analysis of avian disease transmission risk and prevention measures in China

Many zoonotic diseases are found in wild animals and present a serious risk to human health, in particularly the virus carried by birds flying freely around the world is hard to control. There are three main bird migration routes which cover the most areas of China. It is important to investigate and fully understand the types of avian transmitted diseases in key areas on the bird migration routines and its impacts on both birds and human health. However, no literature is available in how about the risk of virus carried by migrating birds, and how to predict and reduce this risk of virus spreading to human being so far. In this paper, we first reviewed the main pathogen types carried by birds, including coronaviruses, influenza viruses, parasites, Newcastle disease virus (NDV), etc., and then discussed the spread risk of avian viruses to human being and animals in key areas of biosafety prevention. We also analyzed and discussed the risk of cross-spread of diseases among different bird species in nature reserves located on bird migration routes which provide sufficient food sources for migratory birds and attract numerous birds. Diseases transmitted by wild birds pose a serious threat to poultry farms, where high density of poultry may become avian influenza virus (AIV) reservoirs, cause a risk of avian influenza outbreaks. Airports are mostly built in suburban areas or remote areas with good ecological environment. There are important transit places for bird migration and densely populated areas, which have serious risk of disease transmission. Finally, this paper puts forward the following prevention suggestions from three aspects. First, establish and improve the monitoring and prediction mechanism of migratory birds, and use laser technology to prevent contact between wild birds and poultry. Second, examine and identify virus types carried by birds in their habitats and carry out vaccination. Third, protect the ecological environment of bird habitat, and keep wild birds in their natural habitat, so as to reduce the contact between wild birds and human and poultry, and thus reduce the risk of virus transmission.

Effect of marine economic development pilot policies on regional economic resilience: Based on quasi-natural experiments from coastal areas in China

China began to implement marine economic development pilot policies from 2011 in order to promote land and marine development in a coordinated way, transform and optimize marine industrial layout, formulate and improve the policy and institutional construction of ocean development, promote marine economic power strategy, and improve the level of regional economic resilience in coastal area. Tourism industry is an important part of regional economy of coastal areas. Taking the marine economic development pilot policies as a quasi-natural experiment and based on the panel data of cities in coastal areas of China from 2007 to 2020, a multi-period difference-in-differences (DID) model was used to assess the impact of these pilot policies on regional economic resilience and tourism economic resilience. The results show that the implementation of marine economic development pilot policies can significantly promote regional economic resilience and tourism economic resilience. COVID-19, as a moderating variable, has significantly weakened the effect of marine economic development pilot policies on regional economic resilience. In terms of regional heterogeneity, the establishment of marine economic development pilots has a more significant policy effect on regional economic resilience in the central and southern coastal areas, while the policy effect on tourism economic resilience is more significant in the eastern coastal areas. In view of these findings, it is of great significance for cities to prevent systemic risks and improve regional economic resilience, by means of reasonably expanding marine economic development pilots and planning coastal regional economic systems according to local conditions. © 2023, Editorial office of PROGRESS IN GEOGRAPHY. All rights reserved.

Farmers' willingness to stabilize the land contract relationship facing the upcoming expiry of land contracts

On the verge of the expiry of land contracts, it is theoretically and practically important to explore the willingness and motivations of farmers to stabilize the land contract relationship, with regards to protecting their land contract rights, addressing potential contradictions during the land contract extension, and maintaining the stability of contracted land. Using China Land Economic Survey Data in 2020, this paper explores the impact of differences in areas per capita of household contracted land on farmers' willingness to stabilize land contract relationship. The findings show that most farmers support the stability of land contract relationship;the smaller areas per capita of contracted land are occupied by households than the average in the village, the weaker of the farmers' willingness to stabilize the land contract relationship. The difference between the areas per capita of contracted land ownership of a household and the average in the village has a greater impact on the willingness to stabilize land contract relationship for middle-and low-income farmers, while the development of land transfer market does not increased the willingness. Affected by the COVID-19 pandemic, the land plays a more important role of employment security, which reduces farmers' willingness to stabilize the land contract relationship. Furthermore, the promotion of socialized agricultural service has also mitigated the willingness of farmers o stabilize the land contract relationship.

Automatic Detection of Lung Ultrasound Artifacts using a Deep Neural Networks approach

The COVID-19 pandemic has challenged many of the healthcare systems around the world. Many patients who have been hospitalized due to this disease develop lung damage. In low and middle-income countries, people living in rural and remote areas have very limited access to adequate health care. Ultrasound is a safe, portable and accessible alternative;however, it has limitations such as being operator-dependent and requiring a trained professional. The use of lung ultrasound volume sweep imaging is a potential solution for this lack of physicians. In order to support this protocol, image processing together with machine learning is a potential methodology for an automatic lung damage screening system. In this paper we present an automatic detection of lung ultrasound artifacts using a Deep Neural Network, identifying clinical relevant artifacts such as pleural and A-lines contained in the ultrasound examination taken as part of the clinical screening in patients with suspected lung damage. The model achieved encouraging preliminary results such as sensitivity of 94%, specificity of 81%, and accuracy of 89% to identify the presence of A-lines. Finally, the present study could result in an alternative solution for an operator-independent lung damage screening in rural areas, leading to the integration of AI-based technology as a complementary tool for healthcare professionals. © 2023 SPIE.

Impacts of the COVID-19 pandemic on the tourism industry in Quebec. An analysis focused on outdoor organizations

This study was conducted with the aim of empirically analyzing the impacts of the pandemic of the Covid-19 on the Quebec tourism industry, with a particular focus on the outdoor sector, given that the latter seems to have been a form of escape in several countries and for many citizens. Based on a quantitative approach and a self-administered survey in the summer of 2020 (n = 1210), this study made it possible to analyze the organizational situation of this industry, the tourism performance of the organizations surveyed, their human resources concerns, their short- and medium-term development prospects, as well as the structural and organizational elements where the organizations are the most vulnerable. Overall, it can be seen that the outdoor sector, thanks to its 40 intrinsic characteristics, stands out very positively in this industry, in particular in contrast to organizations located in large urban centers that depend on clients from outside Quebec.

Food festival research review in contemporary tourism

PurposeFood festivals are prevalent for those passionate about food experience globally. More importantly, feedback from food reviewers on mass media platforms has been becoming a critical factor in facilitating the decision-making process of tourists in particular cities. Moreover, stimulating local tourism activities, thanks to food festivals, prove advantageous to the well-being of local habitants. The purpose of this paper is to provide readers with a general overview of food festival research trends in tourist cities, as tourism has the potential to contribute to targets in Goals 8, 12 and 14 on sustainable consumption and production and the sustainable use of resources, respectively, (UNWTO: World Tourism Organization).Design/methodology/approachThis study searched and filtered documents from the Scopus and Web of Science databases, as well as used bibliometric analysis and other mathematical and statistical methods, to better understand the food festival research context between 1970 and 2021. The carriers with mathematical and statistical methods. VOSviewer algorithm was used to identify critical input for visualizing bibliometric networks and to create a framework for this academic food festival research.FindingsThe findings are primarily related to pre and post-COVID-19 research on food festivals worldwide. Furthermore, using an inductive approach, this paper reveals the impact of food festivals in cities and tourist behaviors. According to the findings, the food festival research trends are about "food festivals,” "slow food festivals” and "local food festivals.” Factor analysis is one of the most common analyses in this type of research. Other studies could use the findings and limitations to select appropriate themes and analysis approaches for their research topics.Research limitations/implicationsResearch data sets are mainly from articles that may not account for all actual trends during this pandemic.Originality/valueThis review expects to provide insights into food festivals and help future researchers to recognize several research gaps such as the lack of research on food festival manufacturers and producers or the consistency in visitors' aspect research of quality service, visitors' loyal intentions, satisfaction and culinary experience. The tourism industry can find research trends of food festivals and issues following COVID-19 to find their management styles to fit the context of the post-COVID-19 pandemic, facilitating organizing a safe and effective food festival.

Performance, Trust, or both? COVID-19 Diagnosis and Prognosis using Deep Ensemble Transfer Learning on X-ray Imagesg±

The COVID-19 pandemic still affects most parts of the world today. Despite a lot of research on diagnosis, prognosis, and treatment, a big challenge today is the limited number of expert radiologists who provide diagnosis and prognosis on X-Ray images. Thus, to make the diagnosis of COVID-19 accessible and quicker, several researchers have proposed deep-learning-based Artificial Intelligence (AI) models. While most of these proposed machine and deep learning models work in theory, they may not find acceptance among the medical community for clinical use due to weak statistical validation. For this article, radiologists' views were considered to understand the correlation between the theoretical findings and real-life observations. The article explores Convolutional Neural Network (CNN) classification models to build a four-class viz. "COVID-19", "Lung Opacity", "Pneumonia", and "Normal"classifiers, which also provide the uncertainty measure associated with each class. The authors also employ various pre-processing techniques to enhance the X-Ray images for specific features. To address the issues of over-fitting while training, as well as to address the class imbalance problem in our dataset, we use Monte Carlo dropout and Focal Loss respectively. Finally, we provide a comparative analysis of the following classification models - ResNet-18, VGG-19, ResNet-152, MobileNet-V2, Inception-V3, and EfficientNet-V2, where we match the state-of-the-art results on the Open Benchmark Chest X-ray datasets, with a sensitivity of 0.9954, specificity of 0.9886, the precision of 0.9880, F1-score of 0.9851, accuracy of 0.9816, and receiver operating characteristic (ROC) of the area under the curve (AUC) of 0.9781 (ROC-AUC score). © 2022 ACM.

Neighborhood-Level Particle Pollution Assessment during the COVID-19 Pandemic via a Novel IoT Solution

In recent years, the concentration levels of various air pollutants have been constantly increasing, primarily due to the high vehicle flow. In 2020, however, severe lockdowns in Greece were imposed to reduce the spread of the COVID-19 pandemic, which led to a rapid reduction in the concentration levels of air pollutants such as PM2.5 and PM10 in the atmosphere. Initially, this paper seeks to identify the correlation between the concentration levels of PM10 and the traffic flow by acquiring data from low-cost IoT devices which were placed in Thessaloniki, Greece, from March to August 2020. The correlation and the linearity between the two parameters were further investigated by applying descriptive analytics, regression techniques, Pearson correlation, and independent T-testing. The obtained results indicate that the concentration levels of PM10 are strongly correlated to the vehicle flow. Therefore, the results hint that the decrease in the vehicle flow could result in improving the quality of environmental air. Finally, the acquired results point out that the temperature and humidity are weakly correlated with the concentration levels of PM10 present in the atmosphere.

Epidemiological and clinical profile of COVID-19 cases attending rural health training centre of one of the medical colleges of Ahmedabad, Gujarat, India

Introduction : Understanding the epidemiological and clinical profile of COVID-19 cases and pattern of disease is very much required for future preparedness. Objective : To assess the epidemiological and clinical profile of cases of COVID 19 Method : Cross sectional descriptive study was carried out at a Rural Health Training Centre (RHTC). All cases reported in the month of January 2022were included in the study. The information about the epidemiological and clinical profile was collected from RHTC records by conducting telephonic interview. Results : Total 83 cases were reported. Among them, 43 (54.4%) cases were in age group 20-39 years. Male: Female ratiowas 1.37:1. Therewas one death and patient had ovarian cancer as co-morbidity. Total 71 patients could be contacted for telephonic interview. Fever was most common symptom andwas presenting symptom on first day followed by cough/cold and sore throat. None had shortness of breath or chest pain. Hospitalization rate was 5.63% and none required oxygen supplementation or intensive care. Recovery period was 3-5 days. Out of total, 90% cases were fully vaccinated and 95.8% had knowledge of CAB. Diabetes and hypertension were most common comorbidities andwere statistically significantlymore in age > 40 years. Conclusions : The COVID-19 cases in the beginning of year 2022 had clinical presentation different than the earlier waves. Periodic situational analysis can guide in policymaking for handling this pandemic in future.

Characteristics of COVID-19 patients and risk factors of mortality in the early times of pandemic, Herat-Afghanistan

Objective: Coronaviruses are a large family of viruses that cause different types of diseases. This study aims to evaluate the risk factors for mortality based on comorbidity and sociodemographic characteristics among COVID-19 patients. Methods: This cross-sectional study conducted in Herat, Afghanistan, from February 24 to July 5, 2020, used data provided by the public health department, including sociodemographics, symptoms, comorbidities, hospitalization, contact history, and COVID-19 test type. The Chi-square test was used to observe differences between categorical variables. In bivariate analysis, all independent variables with a significant p-value were put into the model. Odds ratios and 95% confidence intervals were calculated, and a p-value less than 0.05 was considered statistically significant. Results: The study analyzed 11,183 COVID-19 cases, with a 53.5% positivity rate. Recovery rates in the city and Herat province districts were 96.2% and 94.7%, respectively. Case-fatality rates varied with age, with 0.4% for those aged 1-29 and 33% for those aged 80-105. Mortality rates were highest for those with COPD and cancer, at 12.5% and 18.2%, respectively. In the logistic regression results, age, gender, and COPD were significant variables for COVID-19 mortality. Conclusion: By providing more health service facilities to people in risk groups, especially in rural areas, the mortality rate of COVID-19 and other diseases can be decreased.

Impact of COVID-19 on the Territory and Demographic Processes: A View from Spanish Rural and Urban Areas

The current physiognomy and problems of rural and urban territories in Spain are directly related to the demographic processes linked to the rural exodus of the 1960s. In the year 2020, a new problem and/or conditioning factor arose, COVID-19, which has modified dynamics, routines, and aspects of the daily life of the population. The objectives of this research are to check whether there are differences in the effect of COVID-19 between urban and rural municipalities and, in turn, to analyse the demographic dynamics of the population between 2020 and 2022, as well as territorial distribution patterns. To this end, population data were extracted from the Population Register and Residential Variation data for the period 2010 and 2022 and demographic and statistical calculations (Student's t-test and Pearson's correlation) were carried out. Among the main results, it is observed that COVID-19 has less of an effect in Spanish rural areas. Moreover, these areas show a positive demographic trend for the period 2020-2022. Population growth has had a direct influence on the improvement of demographic data, although with differences according to autonomous communities. This fact represents a break in the trend in rural areas, but is beginning to show signs of exhaustion and a return to the pre-pandemic trend.

Face Mask Detector for Raspberry Pi Based on Computer Vision and Edge Computing

The pandemic of the coronavirus disease 2019 has shown weakness and threats in various fields of human activity. In turn, the World Health Organization has recommended different preventive measures to decrease the spreading of coronavirus. Nonetheless, the world community ought to be ready for worldwide pandemics in the closest future. One of the most productive approaches to prevent spreading the virus is still using a face mask. This case has required staff who would verify visitors in public areas to wear masks. The aim of this paper was to identify persons remotely who wore masks or not, and also inform the personnel about the status through the message queuing telemetry transport as soon as possible using the edge computing paradigm. To solve this problem, we proposed to use the Raspberry Pi with a camera as an edge device, as well as the TensorFlow framework for pre-processing data at the edge. The offered system is developed as a system that could be introduced into the entrance of public areas. Experimental results have shown that the proposed approach was able to optimize network traffic and detect persons without masks. This study can be applied to various closed and public areas for monitoring situations. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

Micro plastic: an imperceptible threat on Agua Dulce Beach, Chorrillos District

The use of plastics in the world is increasing, but their proper final arrangement is limited. Peru made regulatory efforts to reduce its use;however, they are isolated activities that have not represented a significant change in their management. This study allows to identify the presence of microplastic on one of the busiest beaches of the city of Lima Metropolitana, during the emergency period caused by the SARS-COV-2 pandemic. To achieve the objectives of the research, it has been sampled in high tide and supra-coastal areas, applying the methodology proposed in the Ministry of the Environment's Soil Sampling Guide. This study shows the presence of microplastics, with an abundance of 43 pieces per m2, and found that the predominance of the type of microplastic found is of secondary origin (polystyrene and polypropylene);however, 20.9% correspond to primary microplastics (pellets) whose source could not be determined. Finally, it is indicated that despite restrictions on the state of emergency the number of microplastics per m2 in Agua Dulce Beach between 2019 (40 pieces) and 2020 (43 pieces) increased by 7.5%.

Surveillance for SARS-CoV-2 in Norway Rats (Rattus norvegicus) from Southern Ontario

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from wildlife has raised concerns about spillover from humans to animals, the establishment of novel wildlife reservoirs, and the potential for future outbreaks caused by variants of wildlife origin. Norway rats (Rattus norvegicus) are abundant in urban areas and live in close proximity to humans, providing the opportunity for spillover of SARS-CoV-2. Evidence of SARS-CoV-2 infection and exposure has been reported in Norway rats. We investigated SARS-CoV-2 infection and exposure in Norway rats from Southern Ontario, Canada. From October 2019 to June 2021, 224 rats were submitted by collaborating pest control companies. The majority of samples were collected in Windsor (79.9%;n = 179), Hamilton (13.8%;n = 31), and the Greater Toronto Area (5.8%;n = 13). Overall, 50.0% (n = 112) were female and most rats were sexually mature (55.8%;n = 125). Notably, 202 samples were collected prior to the emergence of variants of concern (VOC) and 22 were collected while the Alpha variant (B.1.1.7) was the predominant circulating VOC in humans. Nasal turbinate (n = 164) and small intestinal (n = 213) tissue samples were analyzed for SARS-CoV-2 RNA by RT-PCR. Thoracic cavity fluid samples (n = 213) were tested for neutralizing antibodies using a surrogate virus neutralization test (sVNT) (GenScript cPass);confirmatory plaque reduction neutralization test (PRNT) was conducted on presumptive positive samples. We did not detect SARS-CoV-2 RNA in any samples tested. Two out of eleven samples positive on sVNT had neutralizing antibodies confirmed positive by PRNT (1 : 40 and 1 : 320 PRNT70);both were collected prior to the emergence of VOC. It is imperative that efforts to control and monitor SARS-CoV-2 include surveillance of rats and other relevant wildlife species as novel variants continue to emerge.

Reviving Smallholder Hill Farming by Involving Rural Youth in Food System Transformation and Promoting Community-Based Agri-Ecotourism: A Case of Uttarakhand State in North-Western India

Until recent decades, labour-intensive subsistence farming was a way of life and livelihood in the hill communities of Uttarakhand, India. However, the nature of agriculture falls far short of the expectations of the main labour force, the rural youth, leading to their mass migration to non-agricultural occupations. The large-scale youth migration has left many hill farming landscapes depopulated and farmlands abandoned. As youth have special stakes in food systems, they must be included in the sustainable transformation of food systems. By doing so, the migration-prone hill region may be transformed into a place where rural youth have more options for work and income. Therefore, the agriculture sector needs to change and develop into a more engaging and youthful workplace. There are opportunities to explore and barriers to be removed. Besides identifying priority research areas on local food systems, in this exploratory research, we investigate opportunities to involve rural young people in the transformation of the food system. We document information by conducting focus group discussion (FGD) meetings in about 100 villages in the Uttarakhand hills, representing all major farming landscapes. This study mainly focuses on improving the production and consumption aspects of local food, which not only benefits the health and wellbeing of local communities but also has many positive economic, social, and environmental effects. In addition, we explore opportunities for reviving mountain agriculture through agri-ecotourism, which is a symbiotic relationship between tourism and agriculture. Making home- or farm stays in agri-ecotourism a subsistence strategy for local youth will contribute to a more prosperous rural economy. Recognising Uttarakhand's rich culture and heritage while exploring the culinary travel opportunities in homestays will provide opportunities to focus more on traditional food systems, exposing various tangible and intangible aspects of the host region's food culture to tourists. The findings of this study will aid in identifying specific policy issues for consideration by planners and policymakers at the local and state levels. Additionally, this exploratory study will assist young, motivated researchers in conducting follow-up, in-depth investigations and producing empirical data in their specialised fields.

Factors prompting augmented reality adoption in sacred places

There is evidence that sacred places across the world are launching augmented reality (AR) applications. This application of AR is somehow prompted by the most recent Covid-19 pandemic where in-person experiences are altered by the virtual. AR, as an innovative technology, augments the physical environment with digitally generated imagery that can generate privileges for tourists in sacred places and become the reason to trigger cultural conflicts and religious controversy. This in-depth interview-based research aims to explore the tourists' views and ideas of applying AR in the Mosque City of Bagerhat of Bangladesh, a UNESCO World Heritage Site in terms of possibilities, cultural conflicts, and religious controversy. Findings show that the application of AR in a sacred place can support tourists in many useful ways, can offer them positive experiences, and help in sustainability concerns of the site. However, the application of AR in a sacred place can be an element of conflicting interests between the religious and general tourists. Adequate attention is thus required from the parties involved in terms of applying AR in the Mosque City of Bagerhat of Bangladesh, a sacred religious site.

Long-Term Urban Epidemic and Disaster Resilience: The Planning and Assessment of a Comprehensive Underground Resilience Core

This study utilizes the enclosed and stable environment of underground space for long-term sustainable planning for urban epidemics and disasters. Owing to the COVID-19 epidemic, cities require long-term epidemic-disaster management. Therefore, this study proposed a strategy for integrating multiple functions to plan a comprehensive Underground Resilience Core (URC). A planning and assessment methods of URC were proposed. With this methodology, epidemic- and disaster- URCs were integrated to construct a comprehensive-URC in underground spaces. The results show: (1) Epidemic-resilient URCs adopting a joint progressive approach with designated hospitals can rapidly suppress an epidemic outbreak. (2) The regularity of the morphology of underground spaces determines the area of the URC. Bar-shaped underground spaces have the potential for planning disaster-URCs. (3) The URC planning efficiency ranking is as follows: Bar shapes lead overall, T shapes are second under seismic resilience, and Cross shapes are second under epidemic resilience. (4) The potential analysis of planning a comprehensive-URC in the underground parking in Chinese cities showed that the recovery time can be advanced from 29% to 39% and the comprehensive resilience can be improved by 37.63%. The results of this study can serve as sustainable urban planning strategies and assessment tools for long-term epidemic-disaster management.

Traffic Impacts of the COVID-19 Pandemic: Statewide Analysis of Social Separation and Activity Restriction

The COVID-19 pandemic resulted in significant social and economic impacts throughout the world. In addition to the health consequences, the impacts on travel behavior have also been sudden and wide ranging. This study describes the drastic changes in human behavior using the analysis of highway volume data as a representation of personal activity and interaction. Same-day traffic volumes for 2019 and 2020 across Florida were analyzed to identify spatial and temporal changes in behavior resulting from the disease or fear of it and statewide directives to limit person-to-person interaction. Compared to similar days in 2019, overall statewide traffic volume dropped by 47.5%. Although decreases were evident across the state, there were also differences between rural and urban areas and between highways and arterials both in terms of the timing and extent. The data and analyses help to demonstrate the early impacts of the pandemic and may be useful for operational and strategic planning of recovery efforts and for dealing with future pandemics.

Proximity tourism: an observational analysis of the use of Instagram to promote the northeast of Brazil. (Special Issue: Tourism in the northeast.)

With the changes in consumer profile, especially in tourism activity, facing the issues brought by globalization, greater access to and use of Technologies, and more recently, the restrictions imposed by the protocols to prevent contamination by the Covid-19 virus and its consequences, it has been necessary to change the way of experiencing tourism, leading the market to adapt to the new reality. Thus, the incentive to implement so-called Proximity Tourism has gathered strength, prompting the following research question: how has this type of tourism been addressed and how have the cities of the Brazilian Northeast have been working with this theme to promote their potential on the social network platform Instagram? The main objective of this study was to perform an observational analysis of what is being posted on this social network concerning proximity tourism, by investigating the use of the hashtag #turismodeproximity, and whether the cities of the Northeast of Brazil are using this Instagram tool. As the result of this research, it was found that of the total posts indexed with this hashtag, only a small number are directly related to this region, indicating a lack of dissemination, and consequently, failure to generate greater visibility for this tourism modality.