High Death Toll Research Articles

Analytical landslides prone area by using Sentinel-2 Satellite Imagery and geological data in Google Earth Engine (a case study of Cinomati Street, Bantul Regency, Daerah Istimewa Yogyakarta Province, Indonesia)

The incidence of landslides and the fact that a large number of people live in areas vulnerable to landslides lead to a high death toll in Java Island, Indonesia – more than 1,112 people in the period 1999 to 2005. The study site has an area of 55.56 hectares, along Cinomati Street, Dlingo, and Pleret Sub District, Bantul District, Daerah Istimewa Yogyakarta Province, Indonesia. The methods that use in this study are, Sentinel-2 Imagenery and Geological data. The purpose of this study is to determine the landslides prone area in the study site. The methods used in this study are Sentinel-2 Satellite Imagery and geological data. Along the Cinomati road based on geological data, it has a weak area that has the potential for landslides from the continuation of the Opak fault and rock formation boundaries. Landslide area are locations with complex geological conditions and sparse vegetation. In other rare vegetation besides the location of landslides, it also needs to be aware of other potential landslides, because this research is limited to sentinel images with a density of 10m2.

The role of Benue State Anti-Open Grazing and Ranches Establishment Law in enhancing peace-building in Benue State

Perennial clashes between herdsmen and farmers in Nigeria have not only exacerbated inter-ethnic disharmony but have stunted food production and reinforced circles of poverty and hunger in the country. With the increasing number of Internally Displaced Persons (IDPs) in the country, the clashes are becoming potentially dangerous as the Boko-Haram insurgency in North-Eastern Nigeria. Benue State is one of the States in the country that has suffered traumatic attacks from herdsmen with attendant high death toll and large-scale destruction of farmlands, environmental degradation, and pollution caused by open rearing and grazing of livestock. To stem farmers-herders’ clashes, the Benue State government enacted the ‘Open-Grazing Prohibition and Ranches Establishment Law, 2017. This paper assesses the efficacy of the Anti-Open Grazing Law in enhancing peace-building in the State. Anchored on the theory of structural functionalism, the paper relies on documentary sources for the generation of data. The study found out that the law brought momentary peace to the State but it failed to realize its objectives as no ranches were established; and the herdsmen continued to use the border areas with the neighboring states to launch attacks and make incursions into the State to graze in opposition to the law. Amongst other suggestions, the paper recommends that, states adjoining each other should synergize and enact similar law to ward off the threat of herdsmen; government; civil society groups and private investors should collaborate and set up ranches.

How Economists Ignored the Spanish Flu Pandemic in 1918–1920

The current Covid-19 pandemic has attracted significant attention from epidemiologists and economists alike. This differs from the 1918–1920 Spanish influenza pandemic, when academic economists hardly paid attention to its economic features, despite its very high death toll. We examine the reasons for that by contrasting the ways epidemiologists and economists reacted to the Spanish flu at the time and shortly after the pandemic. We also explore, but less extensively, some economic and epidemiologic writings during the twenty-five years that followed.

Disaster of housing care amenities versus COVID-19 in urbanized countries: medication of social science

<div class="translate-tooltip-mtz hidden"><div class="header"><div class="header-controls"><p class="abstract"><span lang="EN-US">In the background of the COVID-19 epidemic, a big portion of developed nations have suffered an exceptionally high human death toll residing in nursing care homes. In order to further explain this process, public epidemiology contributes significantly, due to the biological influence of the pathogen on as a core feature of wellbeing, disadvantaged high-risk communities and to the position of treatment. The catastrophe of deaths associated with COVID-19 in care centers is largely attributed towards its iatrogenic distribution and exacerbated by societal factors. Present segregation and containment measures have struggled to illustrate their efficacy in mitigating these trends, along with the extended alienation of tenants from their companions, and are thus excessive. Reforms that value for both protection interests of all citizens and fundamental rights must be substituted. Now about the dubious feasibility, these initiatives carry substantial costs of chances, because as standard of health and life conditions of isolated inhabitants are adversely impacted. The COVID-19 issue, viewed in specific from the prism of pharmacy as a public study and social epidemiology, creates ability to correctly appreciate and radically strengthen system parameters.</span></p></div></div></div>

The Italian government response to Covid-19 and the making of a prime minister

ABSTRACT Italy was the first European democracy to be hit by the Covid-19 pandemic. The government’s response, especially in the first wave, was confused, dilatory and inadequate, and the country found itself in an unprecedented public health crisis, leading to a national lockdown between March and May. The easing of restrictions in May and an improved situation in the summer did not prevent cases rising again from the autumn onwards, and Italy finished the year in a series of mini-lockdowns. The government was confronted with a debate over Italy’s high death toll and the role of the executive’s own failings in it. Yet, the pandemic did not prompt a political crisis. Rather, it had the effect of blunting the frontal opposition of the League and strengthening the standing of the government with the public. This especially applied to the Prime Minister, Giuseppe Conte, whose personal ratings soared, as the public rallied behind a leader facing the greatest challenge of any peacetime Italian prime minister.

Landslide susceptibility assessment using frequency ratio technique – A case study of NH67 road corridor in the Nilgiris district, Tamilnadu, India

The purpose of this study is to develop landslide susceptibility mapping for NH67 road corridor in the Nilgiris district of Tamilnadu, India, using the Geographic information system (GIS) and multivariate statistical approach. In November 2009, North-East monsoon triggered numerous landslides in the Nilgiris district of Tamilnadu, resulting in a high death toll and considerable damage to property. The landslide-controlling parameters namely lithology, soil type, slope gradient, normalized difference vegetation index (NDVI), proximity to faults, and proximity to road, rainfall and streams were extracted from the spatial database, and the weight coefficient of each factor was computed. Then the landslide hazard was analyzed using the frequency ratio method. For verification of the model, the results of the analyses were then compared with the field verified landslide locations. It was concluded that about 3.86% and 16.23 % of the study area are in the very high and high susceptible zone. Based on this, landslide susceptibility map was then classified as very high, high, moderate, low and very low. In the course of model validation, the results were validated using the ROC curve. The AUC of Frequency ratio model was 67.5%. Therefore, the landslide susceptibility index map of the study area is considered valuable for the decision-makers of the landslide-prone region. This landslide susceptibility map can be used to carry out mitigation measures to reduce the susceptibility associated with landslide hazard.

Building epidemic models for living populations and computer networks.

Accurate modeling of viral outbreaks in living populations and computer networks is a prominent research field. Many researchers are in search for simple and realistic models to manage preventive resources and implement effective measures against hazardous circumstances. The ongoing Covid-19 pandemic has revealed the fact about deficiencies in health resource planning of some countries having relatively high case count and death toll. A unique epidemic model incorporating stochastic processes and queuing theory is presented, which was evaluated by computer simulation using pre-processed data obtained from an urban clinic providing family health services. Covid-19 data from a local corona-center was used as the initial model parameters (e.g. , infection rate, local population size, number of contacts with infected individuals, and recovery rate). A long-run trend analysis for 1 year was simulated. The results fit well to the current case data of the sample corona center. Effective preventive and reactive resource planning basically depends on accurately designed models, tools, and techniques needed for the prediction of feature threats, risks, and mitigation costs. In order to sufficiently analyze the transmission and recovery dynamics of epidemics it is important to choose concise mathematical models. Hence, a unique stochastic modeling approach tied to queueing theory and computer simulation has been chosen. The methods used here can also serve as a guidance for accurate modeling and classification of stages (or compartments) of epidemics in general.

Application of Frequency Ratio and Logistic Regression Model in the Assessment of Landslide Susceptibility Mapping for Nilgiris District, Tamilnadu, India

This study aims to develop landslide susceptibility mapping for Nilgiris district of Tamil Nadu, India using GIS and remote sensing. The Northeast monsoons often trigger numerous landslides in the Nilgiris district of Tami Nadu, resulting in a high death toll and considerable property damage. The landslide causative factors namely elevation, slope, aspect, land use/land cover, rainfall, geology, geomorphology, soil, distance to lineament, distance to road, distance to stream, stream power index and topographic wetness index extracted from the spatial database were incorporated in the analysis, where the correlation between each parameter and landslides were computed using the frequency ratio model and logistic regression model. Finally, the resultant landslide susceptibility zonation maps were obtained from both the models, which were classified as very high, high, moderate, low and very low landslide susceptible zones. The results convey that about 8.78% and 23.22% of the study area were found to be prone to very high landslide susceptibility zones based on the frequency ratio and logistic regression model, respectively. The model validation was carried out using the Receiver Operating Characteristic (ROC) curve by correlating the information obtained from the field verification. The obtained Area Under the Curve (AUC) value of the frequency ratio and logistic regression model was 82.3% and 84.2%, respectively. Therefore, the landslide susceptibility index map of Nilgiris district is claimed to be valuable for the decision-makers to reduce the susceptibility associated with landslide hazard.

Assessment of Annual Cost of Substance Use Disorder in US Hospitals

A persistently high US drug overdose death toll and increasing health care use associated with substance use disorder (SUD) create urgency for comprehensive estimates of attributable direct costs, which can assist in identifying cost-effective ways to prevent SUD and help people to receive effective treatment. To estimate the annual attributable medical cost of SUD in US hospitals from the health care payer perspective. This economic evaluation of observational data used multivariable regression analysis and mathematical modeling of hospital encounter costs, controlling for patient demographic, clinical, and insurance characteristics, and compared encounters with and without secondary SUD diagnosis to statistically identify the total attributable cost of SUD. Nationally representative hospital emergency department (ED) and inpatient encounters from the 2017 Healthcare Cost and Utilization Project Nationwide Emergency Department Sample and National Inpatient Sample were studied. Statistical analysis was performed from March to June 2020. International Statistical Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) principal or secondary SUD diagnosis on the hospital discharge record according to the Clinical Classifications Software categories (disorders related to alcohol, cannabis, hallucinogens, inhalants, opioids, sedatives, stimulants, and other substances). Annual attributable SUD medical cost in hospitals overall and by substance type (eg, alcohol). The number of encounters (ED and inpatient) with SUD diagnosis (principal or secondary) and the mean cost attributable to SUD per encounter by substance type are also reported. This study examined a total of 124 573 175 hospital ED encounters and 33 648 910 hospital inpatient encounters from the 2017 Healthcare Cost and Utilization Project Nationwide Emergency Department Sample and National Inpatient Sample. Total annual estimated attributable SUD medical cost in hospitals was $13.2 billion. By substance type, the cost ranged from $4 million for inhalant-related disorders to $7.6 billion for alcohol-related disorders. This study's results suggest that the cost of effective prevention and treatment may be substantially offset by a reduction in the high direct medical cost of SUD hospital care. The findings of this study may inform the treatment of patients with SUD during hospitalization, which presents a critical opportunity to engage patients who are at high risk for overdose. Aligning incentives such that prevention cost savings accrue to payers and practitioners that are otherwise responsible for SUD-related medical costs in hospitals and other health care settings may encourage prevention investment.

A World of Touch in a No-Touch Pandemic

Touch is essential when living with dementia for communication and remaining connected with the world, and it is also unavoidable when performing body care. Thus, it is impossible to think of living and caring for people with dementia in the absence of touch. Drawing from my ethnographic fieldwork conducted with therapy animals and people living with dementia in Scottish care facilities, in this article I argue that the public health measures taken against the spread of COVID-19 infections need to be reimagined by taking into consideration the role of touch. Furthermore, I try to draw attention to the lessons that we should learn about touch and the role of intimate bodily entanglements in dementia care from the high COVID-19 death tolls amongst British care home residents.

COVID-19 and waste production in households: A trend analysis.

Apart from the health aspects and the high death toll, the COVID-19 pandemic has, since its official recognition in March 2020 caused may social and economic problems. It has also led to many environmental ones. For instance, the lockdowns have led to higher levels of consumption of packaged products, and of take-away food.This paper reports on an international study on the increased consumption and subsequent changes in the amounts of waste produced since the COVID-19 pandemic. The results show that 45–48% of the respondents observed an increased consumption of packed food, fresh food, and food delivery. One of the main reasons for the increased waste generation during the lockdown was the fact that people have spent more time at home. In addition, increases of 43% and 53% in food waste and plastic packaging. Drawing from comparisons on the amount of domestic waste produced before and during the pandemic, the findings suggest that some specific types of municipal waste have visibly increased, putting additional pressure on waste management systems. This characterises one of non-intended effects of the COVID-19 pandemic. The results from this study provide useful insights to city administrations and municipal utilities on consumption patterns during emergency situations. This, in turn, may support more systemic and strategic measures to be taken, so as to curtail the increase of household waste during pandemic situations.

Extensions of the SEIR model for the analysis of tailored social distancing and tracing approaches to cope with COVID-19

In the context of the COVID-19 pandemic, governments worldwide face the challenge of designing tailored measures of epidemic control to provide reliable health protection while allowing societal and economic activity. In this paper, we propose an extension of the epidemiological SEIR model to enable a detailed analysis of commonly discussed tailored measures of epidemic control—among them group-specific protection and the use of tracing apps. We introduce groups into the SEIR model that may differ both in their underlying parameters as well as in their behavioral response to public health interventions. Moreover, we allow for different infectiousness parameters within and across groups, different asymptomatic, hospitalization, and lethality rates, as well as different take-up rates of tracing apps. We then examine predictions from these models for a variety of scenarios. Our results visualize the sharp trade-offs between different goals of epidemic control, namely a low death toll, avoiding overload of the health system, and a short duration of the epidemic. We show that a combination of tailored mechanisms, e.g., the protection of vulnerable groups together with a “trace & isolate” approach, can be effective in preventing a high death toll. Protection of vulnerable groups without further measures requires unrealistically strict isolation. A key insight is that high compliance is critical for the effectiveness of a “trace & isolate” approach. Our model allows to analyze the interplay of group-specific social distancing and tracing also beyond our case study in scenarios with a large number of groups reflecting, e.g., sectoral, regional, or age differentiation and group-specific behavioural responses.

Structural discrimination and abuse: COVID-19 and people in care homes in England and Wales

PurposeThe purpose of this paper is to explore the significant and high death toll of COVID-19 on care home residents and social care staff in England and Wales. These mortality figures, alongside differential treatment of residents and staff during the pandemic, are conceptualized as a form of structural abuse. Arguments are made for the inclusion of structural abuse as a separate category of elder abuse.Design/methodology/approachThis paper is predominantly conceptual but it also draws on available secondary data, such as mortality statistics, media reports and developing research.FindingsThe lack of appropriate personal protective equipment, paucity of guidance and high mortality rate among care home staff and residents during the pandemic is indicative of social discourses that, when underpinned by ageism, reflect structural elder abuse.Research limitations/implicationsThe research is limited by its focus on a specific time period and its recency. It is also limited in not being based on primary empirical research but it remains exploratory and conceptual and provides a base for ongoing research in this area.Social implicationsIf structural elder abuse was to be included in classifications, it demands a rethink of social and health-care services and the policies and practices associated with them and reinforces the government message that safeguarding is everyone’s business.Originality/valueResearch concerning the effects and impact of COVID-19 are still in their early stages. However, the central element of originality in the paper concerns the linking of practices, policies and underlying social assumptions and structural, or societally ingrained, elder abuse.

Effect of COVID-19 on perceived stress among Bangladeshi people

PurposeCOVID-19 pandemic has caused serious threat to peoples’ physical and mental health because of its high death toll all over the world within a very short period. As a result, people may be psychologically stressed, which can affect their quality of life. The main purpose of this study is to quantify the level of stress among the adults (age 18 and above) including all gender, religions and races of Bangladesh during this devastating pandemic.Design/methodology/approachThis online survey-based study collected demographic data and the Perceived Stress Scale (PSS-10) to determine stress levels over past one month. The total numbers of respondents are 1,148 from May 29, 2020 to June 12, 2020; using the PSS to assess stress levels and to identify the potential variables having association with level of psychological stress, multinomial logistic regression analysis was performed.FindingsA scary proportion (81%) of respondents suffered from substantial amount psychological stress during this COVID-19 pandemic. It is an undeniable signal for us that, every 4 out of 5 respondents in our study is suffering from different level of psychological stress during this time. Comparing the level of stress, this study finds that elderly (60 and above), women, front-line workers (doctor and other health-care professionals) and second-line workers (public service holders, police and defense and banks or financial institutes) have high psychological stress compared to the other respondents.Originality/valueThis study will help policymakers to provide relevant mental health intervention strategies to cope with this challenge efficiently.

Milk Oligosaccharides and Lectins as Candidates for Clinical Trials against Covid-19

Background: Covid-19 pandemic is causing a very high death toll around the world and a severe fall in the global economy. Many clinical trials are currently underway to check the effectiveness of some known drugs. The physiopathology associated with the virus infection is currently better understood and good prophylactic drug therapies are implemented, such as antibiotics and blood thinners, though, no specific drugs against SARS-Cov-2 were developed yet. Objective: In the present research work, it is aimed to carry out a bibliographic investigation on some active molecular species that could be used against Covid-19, based on their chemical properties to bind to glycoproteins. In the case of SARS-Cov-2, the targeted glycoprotein is the surface virus spike S glycoprotein, that the virus uses to attach to and invade human cells. It is of high pharmacological value to investigate possible active natural substances endowed with a property to bind glycoproteins. In this line of research, oligosaccharides and lectins are two molecular species that have glycoprotein binding properties. Methods: A bibliographic research was carried out on oligosaccharides and lectins in various sources of scientific publications. Relevant chemical and pharmacological properties of oligosaccharides and lectins were searched and their main natural sources were identified. Results: In the present paper, I summarize some scientific evidence to support the therapeutic potential of camel milk as a source of oligosaccharides and its possible use as a functional diet in parallel to drug therapies of Covid-19. On the other hand, sugar and glycoprotein binding properties of some lectins of plant and seaweed origin are reported, and their pharmaceutical use is underlined. Conclusion: In the present study, scientific evidence was documented that encouraged further clinical investigations on camel milk oligosaccharides and lectins of plant and seaweed origin in the management of Covid-19 physiopathology.

COVID-19 case fatality risk by age and gender in a high testing setting in Latin America: Chile, March\u2013August 2020

BackgroundEarly severity estimates of coronavirus disease 2019 (COVID-19) are critically needed to assess the potential impact of the ongoing pandemic in different demographic groups. Here we estimate the real-time delay-adjusted case fatality rate across nine age groups by gender in Chile, the country with the highest testing rate for COVID-19 in Latin America.MethodsWe used a publicly available real-time daily series of age-stratified COVID-19 cases and deaths reported by the Ministry of Health in Chile from the beginning of the epidemic in March through August 31, 2020. We used a robust likelihood function and a delay distribution to estimate real-time delay-adjusted case-fatality risk and estimate model parameters using a Monte Carlo Markov Chain in a Bayesian framework.ResultsAs of August 31, 2020, our estimates of the time-delay adjusted case fatality rate (CFR) for men and women are 4.16% [95% Credible Interval (CrI): 4.09–4.24%] and 3.26% (95% CrI: 3.19–3.34%), respectively, while the overall estimate is 3.72% (95% CrI: 3.67–3.78%). Seniors aged 80 years and over have an adjusted CFR of 56.82% (95% CrI: 55.25–58.34%) for men and 41.10% (95% CrI: 40.02–42.26%) for women. Results showed a peak in estimated CFR during the June peak of the epidemic. The peak possibly reflects insufficient laboratory capacity, as illustrated by high test positivity rates (33% positive 7-day average nationally in June), which may have resulted in lower reporting rates.ConclusionsSeverity estimates from COVID-19 in Chile suggest that male seniors, especially among those aged ≥ 70 years, are being disproportionately affected by the pandemic, a finding consistent with other regions. The ongoing pandemic is imposing a high death toll in South America, and Chile has one of the highest reported mortality rates globally thus far. These real-time estimates may help inform public health officials' decisions in the region and underscore the need to implement more effective measures to ameliorate fatality.

Pareto-based evaluation of national responses to COVID-19 pandemic shows that saving lives and protecting economy are non-trade-off objectives

Countries worldwide have adopted various strategies to minimize the socio-economic impact of the ongoing COVID-19 pandemic. Stringency of imposed measures universally reflects the standpoint from which protecting public health and avoiding damage to economy are seen as contradictory objectives. Based on epidemic trajectories of 25 highly developed countries and 10 US states in the (mobility reduction)–(reproduction number) plane we showed that delay in imposition of nation-wide quarantine elevates the number of infections and deaths, surge of which inevitably has to be suppressed by stringent and sustained lockdown. As a consequence, cumulative mobility reduction and population-normalized cumulative number of COVID-19-associated deaths are significantly correlated and this correlation increases with time. Overall, we demonstrated that, as long as epidemic suppression is the aim, the trade-off between the death toll and economic loss is illusory: high death toll correlates with deep and long-lasting lockdown causing a severe economic downturn.

Emotion Recognition Ability as a Predictor of Well-Being During the COVID-19 Pandemic

This study examined emotion recognition ability (ERA) as a predictor of positive and negative affect in two Australian and one German-speaking samples (total N = 469) during the first 2 weeks of major public life restrictions in the COVID-19 pandemic in March/April 2020. Individuals with higher ERA did not report more positive affect, but they felt less burdened and reported less negative affect. This association was fully mediated by lower COVID-19-related media consumption and less negative affect after reading an eyewitness report from an Italian city with a high COVID-19 death toll. However, higher ERA was also related to arguing more with close others. For low-to-medium ERA, an adaptive cognitive emotion regulation style predicted lower media consumption and for medium-to-high ERA, a maladaptive regulation style marginally increased the perceived likelihood of experiencing a similar situation as in Italy, suggesting that regulation style may moderate the ERA–affect relationship.

The Rights of Elders in Ireland during COVID-19.

This article reflects on COVID-19 restrictions imposed on elders in Ireland through the lens of the right to private and family life (Article 8 ECHR), focusing on stay at home orders and recommendations advising elders to avoid social contact. Furthermore, we examine restrictions on visiting nursing homes given the high death toll in that setting. In our analysis, we zero in on the principles of foreseeability and proportionality, highlighting areas of concern and aspects that we submit should be considered in a proportionality assessment. Ultimately, we argue that it is a mistake to view the COVID-19 pandemic solely as an emergency. In this manner, the solutions suggested through the law - restrictions on movement and visitation bans - are too narrow and fail to address the underlying structures, such as, issues in the healthcare system, the limited home help for elderly and poor conditions in nursing homes.

Technology Landscape for Epidemiological Prediction and Diagnosis of COVID-19

The COVID-19 outbreak initiated from the Chinese city of Wuhan and eventually affected almost every nation around the globe. From China, the disease started spreading to the rest of the world. After China, Italy became the next epicentre of the virus and witnessed a very high death toll. Soon nations like the USA became severely hit by SARS-CoV-2 virus. The World Health Organisation, on 11th March 2020, declared COVID-19 a pandemic. To combat the epidemic, the nations from every corner of the world has instituted various policies like physical distancing, isolation of infected population and researching on the potential vaccine of SARS-CoV-2. To identify the impact of various policies implemented by the affected countries on the pandemic spread, a myriad of AI-based models have been presented to analyse and predict the epidemiological trends of COVID-19. In this work, the authors present a detailed study of different artificial intelligence frameworks applied for predictive analysis of COVID-19 patient record. The forecasting models acquire information from records to detect the pandemic spreading and thus enabling an opportunity to take immediate actions to reduce the spread of the virus. This paper addresses the research issues and corresponding solutions associated with the prediction and detection of infectious diseases like COVID-19. It further focuses on the study of vaccinations to cope with the pandemic. Finally, the research challenges in terms of data availability, reliability, the accuracy of the existing prediction models and other open issues are discussed to outline the future course of this study.