The Influence of Density and Mixed Land Use on The Spread of Covid-19 in Surakarta City

Covid-19 has a significant risk of spreading in urban areas because of the aglomeration of built-up areas and people. It frequently contains a mix of land uses and is accessible to urban amenities. Due to the area's extensive usage of mixed land uses, it is better able to provide internal urban services on its own. Greater use of area lockdown and social separation strategies could result from this situation. The most populous city in the province of Central Java, Surakarta, has a significant risk of contracting COVID-19. The purpose of this study is to evaluate the impact of density and levels of mixed land use on the Covid-19 distribution in Surakarta City.Population density is used to calculate density. The entropy index approach was used to measure the amount of mixed land use. It is a method for calculating the balance between each form of land use. The availability of current land use data being processed by the spatial analysis with the Arc GIS application provided help for the analysis. Additionally, it makes use of information on Covid-19 cases in relation to the general populace that is supplied by the Surakarta Municipality. The relationship between mixed land use and Covid-19 risk was analyzed using a linear regression approach. The study's findings indicated a minor influence between density and the spread of COVID-19. Meanwhile, the level of mixed land use does not influence the spread of the Covid-19 virus in Surakarta City.

Critical Commentary: Beyond growth and density: Recentring the demographic drivers of urban health and risk in the global south

Debates within urban studies concerning the relationship between urbanisation and infectious disease focus on issues of urban population growth, density, migration and connectivity. However, an effective long-term risk and wellbeing agenda, without which the threat of future pandemics cannot be mitigated, must also take account of demographic forces and changes as critical drivers of transmission and mortality risk within and beyond cities. A better understanding of the dynamics of fertility, mortality and changing age structures – key determinants of urban decline/growth in addition to migration – provides the foundation upon which healthier cities and a healthy global urban system can be developed. The study of how basic demographic attributes and trends are distributed in space and how they interact with risks, including those of infectious disease, must be incorporated as a priority into a post-COVID-19 urban public health agenda. This perspective concurs with recent debates in urban studies emphasising the demographic drivers of urban change. Moreover, it raises critical questions about the microbial and environmental emphasis of much research on the interface of urban health and governance.

Should population density be used to rank social vulnerability in disaster preparedness planning?

The CDC Social Vulnerability Index (SVI) was developed to help public health officials and policymakers to identify geospatial variations in social vulnerability for each community to better respond to hazardous events, including disease outbreaks. However, the SVI does not include information on population density, which is a significant omission when considering the usefulness of the index in allocating scarce resources such as medical supplies and personnel, bedding, food, and water to locations they are most needed. Using county-level data from the initial U.S. COVID-19 outbreak, we provide empirical evidence that the existing SVI underestimates (overestimates) county-level infection rates in densely (sparsely) populated counties if population density is not accounted for. Population density remains significant even after allowing for spatial spillover effects. Going forward, the inclusion of population density to construct SVI can improve its usefulness in aiding policymakers in allocating scarce resources for future disasters, especially those with spatial dependence. © 2022 Elsevier B.V.

Type 1 diabetes and environment . . . and other stories

A linked ecological analysis of environmental and demographic variables identified several factors, including poor air quality, outdoor light at night, and higher population density that were negatively associated with the incidence of diabetes (Diabetologia doi:10.1007/s00125-020-05087-7). A case-control study using a database of people known to have autoimmune disease raises anxiety about central nervous system inflammatory events (JAMA Neurol doi:10.1001/jamaneurol.2020.1162). A history of exposure to TNF inhibitors carried a threefold increase in risk both of demyelinating diseases, such as multiple sclerosis and optic neuritis, and of non-demyelinating conditions, such as encephalitis, neurosarcoidosis, and vasculitis.

Socioeconomic disparities and concentration of the spread of the COVID-19 pandemic in the province of Quebec, Canada.

BACKGROUND: Recent studies suggest that the risk of SARS-CoV-2 infection may be greater in more densely populated areas and in cities with a higher proportion of persons who are poor, immigrant, or essential workers. This study examines spatial inequalities in SARS-CoV-2 exposure in a health region of the province of Quebec in Canada. METHODS: The study was conducted on the 1206 Canadian census dissemination areas in the Capitale-Nationale region of the province of Quebec. The observation period was 21 months (March 2020 to November 2021). The number of cases reported daily in each dissemination area was identified from available administrative databases. The magnitude of inequalities was estimated using Gini and Foster-Greer-Thorbecke (FGT) indices. The association between transmission and socioeconomic deprivation was identified based on the concentration of transmission in socially disadvantaged areas and on nonparametric regressions relating the cumulative incidence rate by area to ecological indicators of spatial disadvantage. Quantification of the association between median family income and degree of exposure of dissemination areas was supplemented by an ordered probit multiple regression model. RESULTS: Spatial disparities were elevated (Gini = 0.265; 95% CI [0.251, 0.279]). The spread was more limited in the less densely populated areas of the Quebec City agglomeration and outlying municipalities. The mean cumulative incidence in the subsample made up of the areas most exposed to the pandemic was 0.093. The spread of the epidemic was concentrated in the most disadvantaged areas, especially in the densely populated areas. Socioeconomic inequality appeared early and increased with each successive pandemic wave. The models showed that areas with economically disadvantaged populations were three times more likely to be among the areas at highest risk for COVID-19 (RR = 3.55; 95% CI [2.02, 5.08]). In contrast, areas with a higher income population (fifth quintile) were two times less likely to be among the most exposed areas (RR = 0.52; 95% CI [0.32, 0.72]). CONCLUSION: As with the H1N1 pandemics of 1918 and 2009, the SARS-CoV-2 pandemic revealed social vulnerabilities. Further research is needed to explore the various manifestations of social inequality in relation to the pandemic.

Population density and SARS-CoV-2 pandemic: Comparing the geography of different waves in the Netherlands.

The COVID-19 pandemic has boosted public and scholarly debate about the relationship between infectious disease and the urban. Cities are considered contagious because they are hubs in (inter)national networks and contain high densities of people. However, the role of the urban and population density in the spread of pathogens is complex and is mediated by the wider bio-social environment. This paper analyses the role of population density in the outbreak of COVID-19 in the densely and highly urbanised context of the Netherlands. It compares the geography of the different phases in the epidemic and assesses when and where density plays a role. Using municipal data on the rate of infections and hospitalisations, this paper reveals that spatial patterns differ substantially in time, which does not appear to be simple diffusion. Using panel regressions, it is demonstrated that population density plays a role in those stages in which containment and mitigation measures were least strict, while in periods of lockdown other factors such as household size are associated with higher infection rates. It concludes that lockdowns may have greater effect in urban areas as key urban elements are temporarily cancelled out.

Uneven domestic tourism demand in times of pandemic

This study investigates the short-run impact of the COVID-19 pandemic on the number of domestic overnight stays at the regional level in the summer season 2020. Official data for 65 regions in four countries are used for the analysis (Austria, the Czech Republic, Germany and Switzerland). Dynamic panel data models are employed to estimate a tourism demand equation (real GDP and price fluctuations) augmented by average temperatures. Estimation results reveal that domestic overnight stays evolve unevenly in the first summer after the outbreak of the COVID-19 pandemic. The short-run effects show that the number of domestic overnight stays in densely populated regions decreases by 27% in July as well as in August 2020, in comparison with the same months in previous years, ceteris paribus. To the contrary, there is a surge of 27 and 10%, respectively, for sparsely populated areas in the same months.JEL: Z3, R11 and R12.

Disparities in exposure and accessibility to health: A Spatial Assessment of Covid 19 Pandemic Situation of South Bengal

Inequality and disparities of health is prevalent in a developing nation like India. The emergence of the Novel Corona virus has further aggravated this existing problem. The major issue that has been observed in dealing with the pandemic situation is the lack of facilities for testing and inadequate health infrastructure to support the huge population of this nation. This infrastructural deficiency has evidently become severe as we move away from the city areas. In this study, we have tried to assess this rural-urban disparity of health infrastructure in the settings of the COVID 19 pandemic situation. The study has been conducted to measure rural-urban disparities of eight districts i.e. Howrah, Hooghly, Kolkata, North 24 Parganas and South 24 Parganas concerning risk factors and access to health care infrastructure. To achieve the desired objectives, we have used a multidisciplinary technique incorporating statistical, GIS techniques, composite index with several aspects e.g., geographical coverage and sufficiency of COVID care and testing facilities (CCF, CTF), economic status of people, medical costs, and susceptibility to covid risk factors i.e., number of infected populations, and population density. A significant correlation between access to CCF and CTF and the proportion of urban inhabitants has been found, i.e., urban populations mostly enjoy better access to treatment and testing with dense CTFs and CCFs over space. The density and serviceability of care facilities over rural regions decrease with less urbanized areas. Urban areas are found to be at higher risk in terms of the number of active cases, population density. The study helps us to geo visualize the current COVID scenario of South Bengal in terms of regional disparities. This will help us identify the nearest testing and care facilities to any location within the study area and will be useful in mitigating infrastructural lacuna.

The COVID-19 pandemic and urban density: a systematic literature review

The role of density in the spread of the coronavirus pandemic is among the most critical concerns of urban designers and planners. To clarify this role, this systematic literature review is conducted on urban density and the COVID-19 infection and mortality rates in the context of urban design and planning. The studies were searched through three databases including Scopus, PubMed, and Web of Science in March 2022 and were screened and reviewed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. In total, 58 of the 3344 studies had pre-defined criteria. The results were categorised into four sections: population density, building density, built environment factors, and sociodemographic factors. Finally, directions are provided for future studies due to research gaps.

Geographical Appraisal of COVID-19 in West Bengal, India.

Study shows that COVID-19 cases, deaths and recoveries vary in macro level. Geographical phenomena may act as potential controlling factor. The present paper investigates spatial pattern of COVID-19 cases and deaths in West Bengal (WB), India and assumes Kolkata is the source region of this disease in WB. Thematic maps on COVID related issues are prepared with the help of QGIS 3.10 software. As on 15th January 2021, WB has 564032 number of COVID-19 cases which is 0.618% to the total population of the state. However, the COVID-19 case for India is 0.843% and for world is 1.341% to its total population. Lorenz Curve shows skewed distribution of the COVID-19 cases in WB. 17 (90%) districts hold 84.11% of the total population and carry 56.30% of the total COVID-19 cases. However, the remaining two districts-Kolkata and North 24 Parganas-hold remaining 43.70% COVID-19 cases. Correlation coefficient with COVID-19 cases and Population Density, Urban Population and Concrete Roof of their house are significant at 1% level of significance.

Coordinated Mobilization Matters: How DidTaiwan do it during the Covid-19 Pandemic?

The Covid-19 pandemic hit the world hard. Ensnared by a large-scale emergency unprecedented in recent history, mobilization, the classic issue of emergency management, is under stress and test. Yet Taiwan stands out in its rather limited cases of infections despite its frequent contact with mainland China and high population density. Could its mobilization have made the difference? This article traces the steps and strategies that Taiwan took to implement a coordinated mobilization. Three strategies were highlighted: awareness mobilization by declaring emergency early on, resource mobilization by preemptively controlling, boldly incentivizing and surgically distributing resources, and agility mobilization via big data and technology to optimize the response system.

Clinical and Epidemiological Characterization of COVID-19 Disease in Sandino Municipality, year 2020.

Introduction: COVID-19 was declared a pandemic by the World Health Organization on March 11, 2020 due to its complexity and rapid global expansion. Sandino municipality presented its first positive case on October 6, 2020. Objective(s): To characterize the clinical-epidemiological behavior of COVID-19 in Sandino municipality, in 2020. Method(s): A descriptive and cross-sectional research was conducted from March 11 to December 31, 2020. With the information obtained from clinical-epidemiological records, virological results, home and work screening, care for acute respiratory infections in clinics and polyclinics, and the daily reports of the Municipal Health Directorate, a statistical analysis was carried out whose information was inserted in an Excel database. Result(s): The incidence rate was 528.23 per 100 000 population;no deaths. Most of the cases occurred in the city of Sandino. There was a higher frequency of patients in the ages from 41 and 60, and the male sex;while 55.73 % were asymptomatic at diagnosis. The most common symptoms were cough, fever and nasal congestion. Between one and 13 cases per day were diagnosed during the 63 days that there was positivity. Family transmission was 68.23 % and occupational transmission was 50.52 % of cases. Conclusion(s): COVID-19 had a high incidence in Sandino municipality, and this predominated in places with higher population density with intense family and work transmission in a short period of time;also, in the male sex, the age group in working ages, and in the asymptomatic patients.Copyright © 2023, Editorial Ciencias Medicas. All rights reserved.

Urbanization and COVID‐19 Prevalence in India

The research questions we answer in this paper pertain to the socio‐economic determinants of coronavirus disease 2019 (COVID‐19), the relationship between urbanization, urban primacy, the proportion of households in slums, urban poverty, health infrastructure, open spaces in cities and COVID prevalence, in India. We find that urbanization, higher workforce participation, higher population density and higher income lead to increased Covid prevalence. We find a positive relationship between urban primacy, slum households and COVID‐19, and a negative association between health infrastructure, parks and COVID‐19. Cities should develop and maintain not only hospital infrastructure such as beds, but also parks in the post‐pandemic world.Alternate :Las preguntas de investigación a las que respondemos en este artículo se relacionan con los determinantes socioeconómicos de la enfermedad por coronavirus 2019 (COVID‐19), la relación entre la urbanización, la primacía urbana, la proporción de hogares en barrios marginales, la pobreza urbana, la infraestructura sanitaria, los espacios abiertos en las ciudades y la prevalencia de COVID, en la India. Se encontró que la urbanización, una mayor participación de la fuerza laboral, una mayor densidad de población y mayores ingresos conducen a una mayor prevalencia de COVID. Se encontró una relación positiva entre la primacía urbana, los hogares de barrios marginales y COVID‐19, y una asociación negativa entre la infraestructura sanitaria, los parques y COVID‐19. En el mundo post‐pandémico, las ciudades deberían desarrollar y mantener no sólo infraestructuras hospitalarias, como las camas, sino también los parques.Alternate :抄録本稿では、インドにおける新型コロナウイルス感染症 (COVID‐19)の社会経済的決定因子に関連する研究課題、すなわち、都市化、都市の優位性、スラム世帯の割合、都市貧困、健康インフラ、都市のオープンスペース、COVID‐19の罹患率、以上の関連性を解明する。都市化、より高い労働参加率、より高い人口密度及びより高い所得がCOVID‐19の罹患率の増加につながることが分かった。その結果、都市の優位性、スラム世帯、COVID‐19には正の関連性があり、保健インフラ、公園、COVID‐19には負の関連性があることがわかった。COVID‐19のパンデミック後の世界では、都市は病床数などの医療インフラだけでなく公園も開発し維持しなければならない。

Thematic evolution of coronavirus disease: a longitudinal co-word analysis

PurposeUsing science mapping analysis approach and co-word analysis, the present study explores and visualizes research fields and thematic evolution of the coronavirus. Based on this method, one can get a picture of the real content of the themes in the mentioned thematic area and identify the main minor and emerging themes.Design/methodology/approachThis study was conducted based on co-word science mapping analysis under a longitudinal study (from 1988 to 2020). The collection of documents in this study was further divided into three subperiods: 1988–1998, 1999–2009 and 2010–2020. In order to perform science mapping analysis based on co-word bibliographic networks, SciMAT was utilized as a bibliometric tool. Moreover, WoS, PubMed and Scopus bibliographic databases were used to download all records.FindingsIn this study, strategic diagrams were demonstrated for the coronavirus research for a chronological period to assess the most relevant themes. Each diagram depended on the sum of documents linked to each research topic. In the first period (1988–1998), the most centralizations were on virology and evaluation of coronavirus structure and its structural and nonstructural proteins. In the second period (1999–2009), with due attention to high population density in eastern Asia and the increasing number of people affected with the new generation of coronavirus (named severe acute respiratory syndrome virus or SARS virus), publications have been concentrated on "antiviral activity.” In the third period (2010–2020), there was a tendency to investigate clinical syndromes, and most of the publications and citations were about hot topics like "severe acute respiratory syndrome,” "coronavirus” and "respiratory tract disease.” Scientometric analysis of the field of coronavirus can be regarded as a roadmap for future research and policymaking in this important area.Originality/valueThe originality of this research can be considered in two ways. First, the strategic diagrams of coronavirus are drawn in four thematic areas including motor cluster, basic and transversal cluster, highly developed cluster and emerging and declining cluster. Second, COVID-19 is mentioned as a hot topic of research.

Changes and correlation of dengue fever epidemic and Aedes albopictus density in Haizhu district, Guangzhou before and after the COVID-19 pandemic

To analyze the population density, seasonal fluctuation of Aedes albopictus in Haizhu District, Guangzhou from 2017 to 2021, so as to provide a scientific basis for the monitoring and prevention and control of mosquito vector density of dengue fever. The data of dengue fever cases and Aedes surveillance data in Haizhu District, Guangzhou from 2017 to 2021 were collected, and the data of 2017-2019 and 2020-2021 were grouped to compare and analyze the characteristics of dengue epidemic and the density fluctuation of Aedes mosquitoes. A total of 517 dengue cases were reported in Haizhu District, Guangzhou from 2017 to 2021, of which only 7 cases were reported from 2020 to 2021, and the peak period of reported cases every year was August to November. Before the COVID-19 pandemic, there was a positive correlation between the number of local cases and the number of imported cases(rs=0.63, P<0.05) and BI(rs=0.73, P<0.05). The peak density of Aedes was from May to October, and the differences of mean BI(X~2=1 143.40,P<0.001), MOI(X~2=188.30,P<0.001), and SSI(X~2=4 499.43,P<0.001)before and after the COVID-19 pandemic were statistically significant. In general, before and after the COVID-19 pandemic, the density of Aedes in high-risk areas was higher than that in low-risk areas. After COVID-19 pandemic, the number of reported cases and the density of Aedes in Haizhu District decreased, but the density of Aedes in the high-risk area was still higher than that in low-risk areas, and a certain risk of outbreak still existed, so the government should continue to take more precise measures to strictly prevent dengue epidemic.

Spatial contagion during the first wave of the COVID‐19 pandemic: Some lessons from the case of Madrid, Spain

This paper analyses the magnitude of the spatial transmission of COVID‐19 through the municipalities of the region of Madrid during the first pandemic wave using a spatial contagion index. The study also provides additional insights into the main factors contributing to the spread of the virus in both time and space by estimating a novel conditional spatial contagion index. Our results reveal high values of spatial contagion before and during the national lockdown enacted on 15 March 2020, becoming medium/low since then. Furthermore, the study confirms the leading role of inter‐municipal mobility and population density in spatial contagion.Alternate :Este artículo analiza la magnitud de la transmisión espacial de COVID‐19 a través de los municipios de la región de Madrid durante la primera ola pandémica, para lo cual utiliza un índice de contagio espacial. El estudio también proporciona información adicional sobre los principales factores que contribuyen a la propagación del virus, tanto en el tiempo como en el espacio, mediante la estimación de un novedoso índice de contagio espacial condicional. Los resultados revelan altos valores de contagio espacial antes y durante el confinamiento nacional promulgado el 15 de marzo de 2020, pasando a ser medios o bajos desde entonces. Además, el estudio confirma el protagonismo de la movilidad intermunicipal y la densidad de población en el contagio espacial.Alternate :抄録本稿では、空間的感染指標を用いて、パンデミックの第一波におけるマドリッド地域の自治体におけるCOVID‐19の空間的伝播の規模を解析する。また、新しい条件付き空間感染指標を推定することにより、時間と空間の両方でウイルスの拡散に寄与する主要因子の解明の手掛かりを提供する。結果から、2020年3月15日に施行された全国的なロックダウン前とロックダウン中の空間的感染のレベルが高く、それ以降は中程度~低程度になっていることが明らかになった。本研究からさらに、都市間の移動性と人口密度が空間的感染の主導的役割となっていることを確認された。

Medición de la calidad en los servicios sanitarios públicos. El caso de Osakidetza – Servicio vasco de salud

Este artículo trata sobre la medición de la calidad en los servicios sanitarios públicos del País Vasco, cuya provisión corresponde al ente público Osakidetza - Servicio vasco de salud. Se describen métodos y herramientas de calidad generales en el ámbito de la gestión empresarial y sanitaria, junto con otras específicas de Osakidetza, a las que, estas últimas, se les dedica un análisis más profundo. En concreto, el concepto de calidad se ha estudiado desde una perspectiva poliédrica, que incluye diferentes aspectos del término, tales como la calidad contratada frente a la calidad financiada;la calidad certificada, comparada, percibida y evaluada. La principal conclusión es la constatación de la importancia que en el Servicio vasco de salud tienen los objetivos orientados a la calidad del servicio sanitario y calidad de la gestión. Estos se consiguen, entre otros, mediante el conocimiento de la percepción que tienen sus pacientes y usuarios de la atención sanitaria recibida a través de encuestas de satisfacción, así como del establecimiento de compromisos de calidad contratados que cuando son alcanzados reciben financiación específica a través de la fórmula de formalización de contratos programa.Alternate :This article deals with the measurement of quality in public health services in the Basque Country, which are provided by the public body Osakidetza - Basque Health Service. It describes general quality methods and tools in the field of business and health management, together with others specific to Osakidetza, the latter of which are analysed in greater depth. Specifically, the concept of quality has been studied from a multi-faceted perspective, which includes different aspects of the term. Such as contracted versus funded quality;certified, comparative, perceived and evaluated quality. The main conclusion is the confirmation of the importance of objectives aimed at the quality of the health service and management quality in the Basque Health Service. These are achieved, among other things, through knowledge of the perception of patients and users of the health care received through satisfaction surveys, as well as the establishment of contracted quality commitments which, when achieved, receive specific funding through the formula of formalising programme contracts.

Molecular identification and characterization of SARS-Co V-2 from the clinical stool and sewage samples to study waste water-based epidemiology and monitoring circulating virus

The Coronaviridae family's severe acute respiratory syndrome corona virus 2 (SARS-Co V-2) outbreak has infected a large number of the population during the COVID- 19 pandemic. The most prominent mode of virus transmission is considered through respiratory droplets of the infected person. Virus-mediated respiratory infection depends upon the binding between spike protein and the Angiotensinconverting enzyme 2 (ACE2) receptor expressed in lung alveolar type 2 cells. But some studies reported that gastrointestinal infection is also one of the prominent symptoms of COVID-19 because of the high expression of the ACE2 receptor in absorptive enterocytes of the small intestine. In a country like India, with high population density and due to unhygienic sanitation, it is crucial to understand the potential fecal-oral transmission route of SARS-CoV-2 during infection because of presence of ACE2 in small intestine. Therefore in our study, we aim to trace the potential fecal-oral transmission route of SARS-Co V-2 by examining human stool (collected from hospital settings) and nearby sewage water systems, followed by molecular characterization and viral load kinetics evaluation of SARSCOV- 2. qRT-PCR and NGS sequencing methods were used. The presence of SARS-COV-2 was reported in around 70% of samples (both clinical and environmental), this will help us to establish the epidemiological link between clinical and environmental samples after genomic analysis to alter the circulation of silent SARS Co V2 in the community.