Search results

1 – 10 of over 2000
Article
Publication date: 13 January 2022

Zeinab Rahimi Rise and Mohammad Mahdi Ershadi

This paper aims to analyze the socioeconomic impacts of infectious diseases based on uncertain behaviors of social and effective subsystems in the countries. The economic impacts…

Abstract

Purpose

This paper aims to analyze the socioeconomic impacts of infectious diseases based on uncertain behaviors of social and effective subsystems in the countries. The economic impacts of infectious diseases in comparison with predicted gross domestic product (GDP) in future years could be beneficial for this aim along with predicted social impacts of infectious diseases in countries.

Design/methodology/approach

The proposed uncertain SEIAR (susceptible, exposed, infectious, asymptomatic and removed) model evaluates the impacts of variables on different trends using scenario base analysis. This model considers different subsystems including healthcare systems, transportation, contacts and capacities of food and pharmaceutical networks for sensitivity analysis. Besides, an adaptive neuro-fuzzy inference system (ANFIS) is designed to predict the GDP of countries and determine the economic impacts of infectious diseases. These proposed models can predict the future socioeconomic trends of infectious diseases in each country based on the available information to guide the decisions of government planners and policymakers.

Findings

The proposed uncertain SEIAR model predicts social impacts according to uncertain parameters and different coefficients appropriate to the scenarios. It analyzes the sensitivity and the effects of various parameters. A case study is designed in this paper about COVID-19 in a country. Its results show that the effect of transportation on COVID-19 is most sensitive and the contacts have a significant effect on infection. Besides, the future annual costs of COVID-19 are evaluated in different situations. Private transportation, contact behaviors and public transportation have significant impacts on infection, especially in the determined case study, due to its circumstance. Therefore, it is necessary to consider changes in society using flexible behaviors and laws based on the latest status in facing the COVID-19 epidemic.

Practical implications

The proposed methods can be applied to conduct infectious diseases impacts analysis.

Originality/value

In this paper, a proposed uncertain SEIAR system dynamics model, related sensitivity analysis and ANFIS model are utilized to support different programs regarding policymaking and economic issues to face infectious diseases. The results could support the analysis of sensitivities, policies and economic activities.

Highlights:

  • A new system dynamics model is proposed in this paper based on an uncertain SEIAR model (Susceptible, Exposed, Infectious, Asymptomatic, and Removed) to model population behaviors;

  • Different subsystems including healthcare systems, transportation, contacts, and capacities of food and pharmaceutical networks are defined in the proposed system dynamics model to find related sensitivities;

  • Different scenarios are analyzed using the proposed system dynamics model to predict the effects of policies and related costs. The results guide lawmakers and governments' actions for future years;

  • An adaptive neuro-fuzzy inference system (ANFIS) is designed to estimate the gross domestic product (GDP) in future years and analyze effects of COVID-19 based on them;

  • A real case study is considered to evaluate the performances of the proposed models.

A new system dynamics model is proposed in this paper based on an uncertain SEIAR model (Susceptible, Exposed, Infectious, Asymptomatic, and Removed) to model population behaviors;

Different subsystems including healthcare systems, transportation, contacts, and capacities of food and pharmaceutical networks are defined in the proposed system dynamics model to find related sensitivities;

Different scenarios are analyzed using the proposed system dynamics model to predict the effects of policies and related costs. The results guide lawmakers and governments' actions for future years;

An adaptive neuro-fuzzy inference system (ANFIS) is designed to estimate the gross domestic product (GDP) in future years and analyze effects of COVID-19 based on them;

A real case study is considered to evaluate the performances of the proposed models.

Details

Journal of Economic and Administrative Sciences, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1026-4116

Keywords

Article
Publication date: 21 June 2013

Burcu Adivar and Ebru Selin Selen

This study aims to analyze the epidemic modeling applications and policy‐making strategies for six different infectious diseases in a number of countries, thus comparing and…

1340

Abstract

Purpose

This study aims to analyze the epidemic modeling applications and policy‐making strategies for six different infectious diseases in a number of countries, thus comparing and contrasting research in underdeveloped, developing, and developed countries.

Design/methodology/approach

A systematic review has been conducted by identifying relevant studies for six diseases from different sources and selecting 74 publications for inclusion. These selected publications are classified and analyzed based on infectious disease, control policies, theme and objective, methodology, origin of population data, publication year and results.

Findings

Review results indicate that disaster preparedness and surveillance plans for epidemics are available mostly for developed countries. There is a need for further research in both developing and developed countries because of the ease of dispersion, which constitutes a universal threat. Analysis of the publications suggests that epidemic disasters are mostly studied by researchers in the field of medicine or biology with the aim of assessing the potential impact of an epidemic. The authors highlight the need for further research in operations research and disaster management fields and propose further research directions in the area of disaster management.

Social implications

This review emphasizes the importance of epidemic disaster modeling for the preparedness stage of disaster management and policy making. Disease and population‐specific intervention policies (e.g. vaccination) reported in this review should set an example and help policy makers during their decision making.

Originality/value

Potential use of the epidemiological modeling on further planning and decision‐making issues in the context of disaster management is studied for the first time.

Details

Disaster Prevention and Management: An International Journal, vol. 22 no. 3
Type: Research Article
ISSN: 0965-3562

Keywords

Article
Publication date: 30 June 2021

Harsuminder Kaur Gill, Vivek Kumar Sehgal and Anil Kumar Verma

Epidemics not only affect the public health but also are a threat to a nation's growth and economy as well. Early prediction of epidemic can be beneficial to take preventive…

Abstract

Purpose

Epidemics not only affect the public health but also are a threat to a nation's growth and economy as well. Early prediction of epidemic can be beneficial to take preventive measures and to reduce the impact of epidemic in an area.

Design/methodology/approach

A deep neural network (DNN) based context aware smart epidemic system has been proposed to prevent and monitor epidemic spread in a geographical area. Various neural networks (NNs) have been used: LSTM, RNN, BPNN to detect the level of disease, direction of spread of disease in a geographical area and marking the high-risk areas. Multiple DNNs collect and process various data points and these DNNs are decided based on type of data points. Output of one DNN is used by another DNN to reach to final prediction.

Findings

The experimental evaluation of the proposed framework achieved the accuracy of 87% for the synthetic dataset generated for Zika epidemic in Brazil in 2016.

Originality/value

The proposed framework is designed in a way that every data point is carefully processed and contributes to the final decision. These multiple DNNs will act as a single DNN for the end user.

Details

Library Hi Tech, vol. 40 no. 5
Type: Research Article
ISSN: 0737-8831

Keywords

Article
Publication date: 7 December 2021

Oluwole Owoye and Olugbenga A. Onafowora

The purpose of this paper is to empirically examine whether the massive spreads and fatalities of the COVID-19 pandemic in the USA, the country with the most advanced medical…

Abstract

Purpose

The purpose of this paper is to empirically examine whether the massive spreads and fatalities of the COVID-19 pandemic in the USA, the country with the most advanced medical technology in the world, are symptomatic of leadership failure. The authors posit that when political leaders, such as the President of the USA, in conjunction with a group of state governors and city mayors, employed conspiracy theories and disinformation to achieve their political goals, they contributed to the massive spreads and fatalities of the virus, and they also undermined the credibility of the Centers for Disease Control and Prevention (CDC) and the health-care professionals in providing the pertinent control guidelines and true scientific-based medical information.

Design/methodology/approach

The authors conducted a review of current studies that address the handling of global infectious diseases to build a better understanding of the issue of pandemics. They then employed a theoretical framework to link the massive spreads and fatalities of the COVID-19 pandemic to political leaders, such as President Trump and the group of obsequious state governors and city mayors, who propagated conspiracy theories and disinformation through social media platforms to downplay the severity of the virus. The authors compared the massive spreads and fatalities of the COVID-19 pandemic in the USA under President Trump to President Obama who handled H1N1, Ebola, Zika and Dengue. More importantly, the authors compared President Trump's handling of the COVID-19 pandemic to other political leaders in advanced countries where there were no concerted efforts to spread conspiracy theories and disinformation about the health risks of COVID-19 pandemic.

Findings

The authors' theoretical analysis alluded to the fact that political leaders, such as President Trump, who are engulfed in self-deceptions, self-projections and self-aggrandizements would engage in self-promotion and avoid accountability for their missteps in handling global pandemic shocks. In contrast, political leaders in other advanced countries did not downplay the severity thus their ability to curtail the spreads and fatalities of the COVID-19 pandemic.

Research limitations/implications

The theoretical viewpoints presented in this paper along with the derivations of the spreads–fatalities curtailment coefficients and the spread–fatality upsurge coefficients under Presidents Obama and Trump, respectively, may not be replicable. Given this plausible limitation, future research may need to provide a deep analysis of the amplifications of conspiracy theories and disinformation because they are now deeply rooted in the political economy of the USA. Furthermore, since scientists and medical professionals may not be able to forecast future epidemics or pandemics with pin-point accuracy nor predict how political leaders would disseminate health risks information associated with different pathogens, it is imperative that future research addresses the positive or adverse effects of conspiracy theories and disinformation that are now easily propagated simultaneously through different social media platforms, which are currently protected under Section 230 of the Communications Decency Act. The multiplier effects of conspiracy theories and disinformation will continue to amplify the division about the authenticity of COVID-19 pandemic and the emergence or reemergence of other pathogens in the foreseeable future.

Originality/value

The authors derived the unique spreads-fatalities curtailment coefficients to demonstrate how President Obama used effective collaboration and coordination at all levels of government in conjunction with medical experts to curtail the spreads and fatalities associated with H1N1, Ebola, Zika and Dengue. They further derived the spreads-fatalities upsurge coefficients to highlight how President Trump contributed to the spreads and fatalities of COVID-19 pandemic through his inability to collaborate and coordinate with state governors, city mayors and different health-care agencies at the national and international levels.

Details

International Journal of Public Leadership, vol. 18 no. 2
Type: Research Article
ISSN: 2056-4929

Keywords

Book part
Publication date: 9 November 2006

Matthew K. Wynia, Jacob F. Kurlander and Shane K. Green

Physicians are instrumental to our national defense against epidemics, whether natural or bioterror-related. Broadly speaking, they are obligated to help rapidly identify threats…

Abstract

Physicians are instrumental to our national defense against epidemics, whether natural or bioterror-related. Broadly speaking, they are obligated to help rapidly identify threats, prevent the spread of disease, and care for infected patients. Each task presents ethical challenges, including the need to address access to care, balance the medical needs of individuals and communities, and ensure that health professionals continue to treat infectious patients in spite of the risk they present. If physicians can acknowledge these duties and meet these challenges, they have an opportunity to strengthen medicine's public trust and professional identity.

Details

Ethics and Epidemics
Type: Book
ISBN: 978-1-84950-412-6

Article
Publication date: 11 November 2021

Elise E. Racine and Joanna J. Bryson

As illustrated by coronavirus disease 2019 (COVID-19), epidemic models are powerful health policy tools critical for disease prevention and control, i.e. if they are fit for…

Abstract

Purpose

As illustrated by coronavirus disease 2019 (COVID-19), epidemic models are powerful health policy tools critical for disease prevention and control, i.e. if they are fit for purpose. How do people ensure this is the case and where does health education fit in?

Design/methodology/approach

This research takes a multidisciplinary approach combining qualitative secondary and primary data from a literature review, interviews and surveys. The former spans academic literature, grey literature and course curriculum, while the latter two involve discussions with various modeling stakeholders (educators, academics, students, modeling experts and policymakers) both within and outside the field of epidemiology.

Findings

More established approaches (compartmental models) appear to be favored over emerging techniques, like agent-based models. This study delves into how formal and informal education opportunities may be driving this preference. Drawing from other fields, the authors consider how this can be addressed.

Practical implications

This study offers concrete recommendations (course design routed in active learning pedagogies) as to how health education and, by extension, policy can be reimagined post-COVID to make better use of the full range of epidemic modeling methods available.

Originality/value

There is a lack of research exploring how these methods are taught and how this instruction influences which methods are employed. To fill this gap, this research uniquely engages with modeling stakeholders and bridges disciplinary silos to build complimentary knowledge.

Details

Health Education, vol. 122 no. 1
Type: Research Article
ISSN: 0965-4283

Keywords

Article
Publication date: 8 July 2020

Joseph Kimuli Balikuddembe

This paper attempts to discuss the synergies between the sustainable development goals (SDGs) and Ebola preparedness and response – with a specific outlook about how the five (5…

Abstract

Purpose

This paper attempts to discuss the synergies between the sustainable development goals (SDGs) and Ebola preparedness and response – with a specific outlook about how the five (5) targets in SDG.3 can be prioritized and integrated into the measures taken against the battle of Ebola virus disease (EVD) in the Democratic Republic Congo (DRC) as well as any other sporadic health disasters and emergencies elsewhere.

Design/methodology/approach

This paper draws on the published literature, including reports, peer-reviewed articles, statistical data and relevant documents identified from authenticated sources.

Findings

Sustainable development, which is the nitty-gritty of SDGs, is underscored as a germane in almost all regional and international frameworks. However, as traditional natural hazards persist, alongside the persistence of civil conflicts and instability, socioeconomic challenges such as EVD pose serious hindrances to SDGs, and achieving them by 2030 might be a deferred dream, especially in low- and middle-income countries such as DRC.

Practical implications

This paper will help to inform the decisions of bureaucrats at different levels, especially those aimed at promoting and integrating health into sustainable development.

Originality/value

The recent 2018 EVD outbreaks in DRC, which galvanized the regional and global attention, call for an approach that elucidates an interaction between the SDGs and countermeasures of responding to this deadly disease in the DRC and elsewhere.

Details

Disaster Prevention and Management: An International Journal, vol. 29 no. 5
Type: Research Article
ISSN: 0965-3562

Keywords

Book part
Publication date: 21 April 2010

Maya K. Gislason

Purpose – The purpose of this chapter is to illustrate that when produced through relations of power, West Nile virus (WNV), as it exists on the Public Health Agency of Canada's…

Abstract

Purpose – The purpose of this chapter is to illustrate that when produced through relations of power, West Nile virus (WNV), as it exists on the Public Health Agency of Canada's (PHAC) website, is an effect of the kinds of knowledge, techniques of power, and disciplinary apparatuses that operate on the website and in society.

Methodology/approach – The approach used in the in-depth research project which informs this chapter is an elaboration of Michel Foucault's work on relations of power which offers an effective way of studying the PHAC's website as a collection of authoritative knowledges and as a product of a set of systems, structures, and processes which have helped to assemble and distribute knowledge about WNV.

Findings – The findings discussed in this chapter offer a critical reading of the PHAC's overall production of WNV, focusing particularly on its initial emergence starting in 2001. Cumulatively, this chapter argues that myriad relations of power have produced WNV as a bio-socio-administrative construct.

Contribution to the field – This research illustrates one way that Foucault's theories of power can be used to conduct a critical analysis of both the discursive and material dimensions of the production of contemporary public health issues. Such an approach is useful to scholars who wish to place the emergence of a disease phenomenon within political, institutional, economic, cultural, and social relations of power; thereby drawing attention to how specific spaces, places, individuals, and institutions contribute to the production of contemporary health alarms.

Details

Understanding Emerging Epidemics: Social and Political Approaches
Type: Book
ISBN: 978-1-84855-080-3

Article
Publication date: 30 April 2021

Marcin Roszkowski and Bartłomiej Włodarczyk

The paper aims to present the development of conceptualization of coronavirus disease 2019 (COVID-19) based on associations with other articles on English edition of Wikipedia…

Abstract

Purpose

The paper aims to present the development of conceptualization of coronavirus disease 2019 (COVID-19) based on associations with other articles on English edition of Wikipedia. The main goal of the paper is to study the social organization of knowledge about COVID-19 within the Wikipedia community of practice.

Design/methodology/approach

The methodological approach taken in this study was based on the application of Moscovici's theory of social representations to Wikipedia's knowledge organization system (KOS). Internal links in the Wikipedia article about COVID-19 were considered anchors in its social representations. Each link in the introductory part of the article was considered an indicator of the semantic relationship between COVID-19 and other concepts from Wikipedia's knowledge base. The subject of this study was links extracted from all revisions of the COVID-19 article between February and September 2020. Qualitative and quantitative analyses were performed on these conceptual structures using both synchronic and diachronic approaches.

Findings

It was found that the evolution of anchors in the Wikipedia article on COVID-19 was in line with the mechanism of symbolic coping related to infectious disease. It went through stages of divergence, convergence and normalization. It shows that this mechanism governs the social organization of knowledge related to COVID-19 on Wikipedia.

Originality/value

No studies have been devoted to the image of COVID-19 as presented by the evolution of links in Wikipedia and its implications for knowledge organization (KO).

Details

Journal of Documentation, vol. 78 no. 2
Type: Research Article
ISSN: 0022-0418

Keywords

Book part
Publication date: 16 August 2014

Parnali Dhar Chowdhury and C. Emdad Haque

The purpose of this chapter is to offer reflections on conventional theories concerning causes and determinants of diseases. It also intends to examine both theoretical and…

Abstract

Purpose

The purpose of this chapter is to offer reflections on conventional theories concerning causes and determinants of diseases. It also intends to examine both theoretical and empirical bases for adopting an Integrated Social-Ecological Systems (ISES) lens as a tool for understanding complexities related to drivers, determinants and causes of diseases.

Design/methodology/approach

We assessed the theoretical underpinnings of a range of historical and contemporary lenses for viewing infectious disease drivers and the implications of their use when used to explain both personal (i.e. individual) and population health. We examined these issues within the empirical context of the City of Dhaka (Bangladesh) by adopting an ISES lens. Within this study an emphasis has been placed on illustrating how feedback loops and non-linearity functions in systems have a direct bearing upon various aspects of infectious disease occurrences.

Findings

A brief triumph over microbes during the last century stemmed in part from our improved understanding of disease causation which was built using disciplinary-specific, monocausal approaches to the study of disease emergence. Subsequently, empirical inquiries into the multi-factorial aetiology and the ‘web of causation’ of disease emergence have extended frameworks beyond simplistic, individualistic descriptions of disease causation. Nonetheless, much work is yet to be done to understand the roles of complex, intertwined, multi-level, social-ecological factors in affecting disease occurrence. We argue, a transdisciplinary-oriented, ISES lens is needed to explain the complexities of disease occurrence at various and interacting levels. More theoretical and empirical formulations, with evidence derived from various parts of the world, is also required to further the debate.

Originality/value

Our study advances the theoretical as well as empirical basis for considering an integrated human-nature systems approach to explaining disease occurrence at all levels so that factors at the individual, household/neighbourhood, local, regional and global levels are not treated in isolation.

Details

Ecological Health: Society, Ecology and Health
Type: Book
ISBN: 978-1-78190-323-0

Keywords

1 – 10 of over 2000