Country Case Research Articles

Deep learning-based approach for COVID-19 spread prediction

AbstractSpread prediction models are vital tools to help health authorities and governments fight against infectious diseases such as COVID-19. The availability of historical daily COVID-19 cases, in conjunction with other datasets such as temperature and humidity (which are believed to play a key role in the spread of the disease), has opened a window for researchers to investigate the potential of different techniques to model and thereby expand our understanding of the factors (e.g., interaction or exposure resulting from mobility) that govern the underlying dynamics of the spread. Traditionally, infectious diseases are modeled using compartmental models such as the SIR model. However, this model shortcoming is that it does not account for mobility, and the resulting mixing or interactions, which we conjecture are a key factor in the dynamics of the spread. Statistical analysis and deep learning-based approaches such as autoregressive integrated moving average (ARIMA), gated recurrent units, variational autoencoder, long short-term memory (LSTM), convolution LSTM, stacked LSTM, and bidirectional LSTM have been tested with COVID-19 historical data to predict the disease spread mainly in medium- and high-income countries with good COVID-19 testing capabilities. However, few studies have focused on low-income countries with low access to COVID-19 testing and, hence, highly biased historical datasets. In addition to this, the arguable best model (BiLSTM) has not been tested with an arguably good set of features (people mobility data, temperature, and relative humidity). Therefore, in this study, the multi-layer BiLSTM model is tested with mobility trend data from Google, temperature, and relative humidity to predict daily COVID-19 cases in low-income countries. The performance of the proposed multi-layer BiLSTM is evaluated by comparing its RMSE with the one from multi-layer LSTM (with the same settings as BiLSTM) in four developing countries namely Mozambique, Rwanda, Nepal, and Myanmar. The proposed multi-layer BiLSTM outperformed the multi-layer LSTM in all four countries. The proposed multi-layer BiLSTM was also evaluated by comparing its root mean-squared error (RMSE) with multi-layer LSTM models, ARIMA- and stacked LSTM-based models in eight countries, namely Italy, Turkey, Australia, Brazil, Canada, Egypt, Japan, and the UK. Finally, the proposed multi-layer BiLSTM model was evaluated at the city level by comparing its average relative error with the other four models, namely the LSTM-based model considering multi-layer architecture, Google Cloud Forecasting, the LSTM-based model with mobility data only, and the LSTM-based model with mobility, temperature, and relative humidity data for 7 periods (of 28 days each) in six highly populated regions in Japan, namely Tokyo, Aichi, Osaka, Hyogo, Kyoto, and Fukuoka. The proposed multi-layer BiLSTM model outperformed the multi-layer LSTM model and other previous models by up to 1.6 and 0.6 times in terms of RMSE and ARE, respectively. Therefore, the proposed model enables more accurate forecasting of COVID-19 cases and can support governments and health authorities in their decisions, mainly in developing countries with limited resources.

Brief overview of mpox: To worry or to ignore?

Mpox was first discovered in the Democratic Republic of Congo as a zoonotic infectious disease with various possible transmission routes. Currently, it is a reemerging disease being monitored by the World Health Organization (WHO) after a surge of reported cases in several non-endemic countries in May 2022 and August 2023. This study probes into the issue of whether mpox should or should not be concerned as a potential threat during and after the current COVID-19 pandemic. Literature reviews were conducted using PubMed, DOAJ, and Cochrane to understand and synthesize more information on the virulence and lethality of mpox. The keywords used included “monkeypox”, “outbreak”, “reemerging infectious disease”, “southeast asia”, “smallpox”, “sars cov”, and “transmission”, which were all associated with the Boolean operators “AND” and “OR”. A total of 30 articles acquired from various journals and international official websites were included in this study. The sudden outbreaks across the Asia-Pacific region may be attributed to countries lifting their travel restrictions. Studies have shown that mpox has similar transmission routes to COVID-19 and manifests similar symptoms to smallpox. However, mpox needs prolonged contact for its transmission and has a lower case fatality rate (CFR). Several studies highlighted that current outbreaks have different epidemiological and clinical characteristics from classic cases. Mpox is not as highly transmissible as COVID-19 and not as severe as smallpox, but it still poses a potential threat to human health and needs further observation and immediate containment to prevent further transmission worldwide. The preparation of smallpox vaccination in case of emergency and further clinical trials of smallpox drugs are recommended.

Optimization of the replication of hepatitis E virus genotype 3 in vitro.

Hepatitis E virus (HEV) is responsible for ∼20 million human infections worldwide every year. The genotypes HEV-3 and HEV-4 are zoonotic and are responsible for most of the autochthonous HEV cases in high-income countries. There are several cell culture systems that allow for propagation of different HEV genotypes in vitro. One of these systems uses human lung carcinoma cells (A549), and was further optimized for propagation of HEV-3 47832c strain. In this study, we investigated the effect of different media supplements as well as microRNA-122 (miR-122) on improving the replication of HEV-3 47832c in A549 cells. We observed that supplementation of maintenance media with 5% fetal bovine serum was sufficient for efficient replication of HEV-3, and verified the positive effect of media supplementation with Amphotericin B, MgCl2, and dimethyl sulfoxide on replication of HEV-3. We have also demonstrated that adding miR-122 mimics to the culture media does not have any significant effect on the replication of HEV-3 47832c. Herein, we detected over a 6-fold increase in HEV-3 replication in A549/D3 cells by adding all three supplements: Amphotericin B, MgCl2, and dimethyl sulfoxide to the culture media, while demonstrating that miR-122 might not play a key role in replication of HEV-3 47832c.

Comparative life cycle assessment of excreta management systems through composting and biomethanization: Case of a low-income tropical country.

Low-income tropical regions, such as Haiti, grapple with environmental issues stemming from inadequate sanitation infrastructure for fecal sludge management. This study scrutinizes on-site sanitation systems in these regions, evaluating their environmental impacts and pinpointing improvement opportunities. The focus is specifically on systems integrating excreta valorization through composting and/or anaerobic digestion. Each system encompasses toilet access, evacuation, and sludge treatment. A comparative life cycle assessment was undertaken, with the functional unit managing one ton of excreta in Haiti over a year. Six scenarios representing autonomous sanitation systems were devised by combining three toilet types (container-based toilets (CBTs), ventilated improved pit (VIP) latrines, and flush toilets (WC)) with two sludge treatment processes (composting and biomethanization). Biodigester-based systems exhibited 1.05 times higher sanitary impacts and 1.03 times higher ecosystem impacts than those with composters. Among toilet types, CBTs had the lowest impacts, followed by VIP latrines, with WCs having the highest impacts. On average, WC scenarios were 3.85 times more impactful than VIP latrines and 4.04 times more impactful than those with CBTs regarding human health impact. Critical variables identified include the use of toilet paper, wood shavings, greenhouse gas emissions, and construction materials.

Risk factors of breast cancer among patients from a lower- and middle-income country: A case-control study from Nepal.

e12502 Background: Although breast cancer occurs overwhelmingly in high-income countries, there has been a recent increase in the incidence of breast cancer cases in low and middle-income countries. Reports from hospital-based registries showed that breast cancer is second most common cancer in Nepalese women. The study aimed to find the risk factors associated with breast cancer among breast cancer patients at a tertiary care hospital from Nepal. Methods: An Institutional-based 1:1 unmatched case-control study with a sample of 100 women was conducted at Patan Academy of Health Sciences, Patan Hospital, Kathmandu, Nepal, between May to October 2023. Women aged 20-84 years with histologically confirmed breast cancer within the last 4 years of the interview date were identified retrospectively as a study cases. Semi-structured questionnaire was used for data collection. Multivariate logistic regression model was used to calculate the adjusted odds ratio with 95%CI. Results: The significantly associated risk factors included age (41-50yrs: OR 5.03, >50 years: OR31.11), marital status (married: OR9.23), age at menarche (13-15 yrs: OR 3.79), and oral contraception use (OC user: OR 4.26). Conclusions: Emphasizing regular breast cancer screening programs above 40 years of age and adequate counselling and awareness about that risks and benefits of hormonal contraception among high-risk groups might help to mitigate the risk of breast cancer.

Deep learning based COVID and Pneumonia detection using chest X-ray

<p class="Abstract">Since the outbreak, the novel coronavirus (COVID-19) has infected more than 180 million people and has taken a toll of 3.91 million lives globally as of June 2021. This virus causes symptoms like fever, cold, and fatigue, and can develop into Pneumonia which can be detected using chest X-rays (CXRs). Therefore, early detection of COVID-19 can help get early medical attention. However, a sudden rise in the number of cases in many countries caused by COVID waves increases the burden on their testing facilities. As a result, they sometimes fail to perform enough testing to contain the spread. This work proposes a deep learning model to detect COVID-19 and Pneumonia based on CXRs. The dataset for our COVID model contains a total of 3,400 CXRs images of COVID-19 patients and 3,400 normal CXRs. The dataset for our Pneumonia model contains 1,300 CXR images of Pneumonia patients and 1,300 normal CXRs. We use convolutional neural network provided by TensorFlow to build our model, which gave 94.17% and 93.55% accuracy for COVID model and Pneumonia model, respectively. Finally, we deployed our model on the web and added a web tracker, which gives us the cases, deaths, and recoveries state-wise and nationwide.</p>

TEMPORARY REMOVAL: Factors Affecting Anemia among Women of Reproductive Age in Mexico: A Mixed-Methods Country Case Study

BackgroundIn Mexico, anemia prevalence among women of reproductive age (WRA) decreased from 16.4% in 2006 to 11.6% in 2012, only to increase to 18.3% in 2016. The factors associated with this fluctuation are uncertain. ObjectiveWe conducted a systematic in-depth assessment of the quantitative and qualitative determinants of anemia among WRA in Mexico between 2006 and 2018. MethodsUsing multivariate stepwise linear regression, we analyzed Mexico’s Encuesta Nacional de Salud y Nutrición (ENSANUT) surveys from 2006, 2012, and 2018 to identify determinants of WRA anemia. We also conducted a review of anemia-relevant programs and policies, including financing documents, and conducted in-depth interviews and focus group discussions with key stakeholders in Mexico. ResultsAmong non-pregnant women (NPW) 15-49 years, mean hemoglobin (Hb) increased from 13.8 g/dL in 2006 to 14.0 g/dL in 2012, decreasing to 13.2 g/dL in 2018 (p<0.001). Inequities by geographical region and household wealth persisted throughout this period, with household wealth, urban residence and gravidity emerging as significant predictors of Hb among NPW. Qualitative analyses generally supported these findings. The most discussed program was Progresa-Oportunidades-Prospera (POP), where most resources for health were invested and most participants acknowledged that its cancellation in 2019 would lead to worsening in health and nutrition among the poor. Financing analyses showed a drop of funding for nutrition-related programs between 2014 and 2018. Cultural norms around gender roles were still prevalent, along with increasing rates of teenage pregnancy. ConclusionsAnemia prevention efforts need to refocus on poverty alleviation, continuity of adequate coverage and financing of nutrition programs, especially with safety nets, and increase in uptake of family planning, especially among adolescent girls.

TEMPORARY REMOVAL: Drivers of Anemia Reduction among Women of Reproductive Age in Senegal: A Country Case Study

BackgroundIn Senegal, anemia prevalence among women of reproductive age (WRA) decreased from 59% in 2005 to 54% in 2017. However, determinants of reduction in disease burden under challenging public health conditions have not been studied. ObjectiveTo conduct a systematic in-depth assessment of the quantitative and qualitative determinants of anemia reduction among WRA in Senegal between 2005 and 2017. MethodsStandard Exemplars in Global Health methodology was used for quantitative analyses using Senegal’s Demographic and Health Surveys. Qualitative analyses included a systematic literature review, program/policy analysis, and interviews with key stakeholders. A final Oaxaca-Blinder decomposition analysis (OBDA) evaluated the relative contribution of direct and indirect factors. ResultsAmong non-pregnant women (NPW), mean hemoglobin (Hb) increased from 11.4 g/dL in 2005 to 11.7 g/dL in 2017 (p<0.0001), corresponding to a 5%-point decline in anemia prevalence (58% to 53%). However, inequities by geographical region, household wealth, women’s educational attainment, urban compared to rural residence, and antenatal care (ANC) during last pregnancy continue to persist. During this time period, several indirect nutrition programs were implemented, with stakeholders acknowledging the importance of these programs, but agreeing there needs to be more consistency, evaluation, and oversight for them to be effective. Our OBDA explained 59% of the observed change in mean Hb, with family planning (25%), malaria prevention programs (17%), use of iron and folic acid (IFA) during last pregnancy (17%), and improvement in women’s empowerment (12%) emerging as drivers of anemia decline, corroborating our qualitative and policy analyses. ConclusionsDespite a reduction in anemia prevalence, anemia remains a severe public health problem in Senegal. To protect the gains achieved to date, as well as accelerate reduction in WRA anemia burden, focused efforts to reduce gender and social disparities, and improve coverage of health services, such as family planning, IFA, and antimalarial programs, are needed.

TEMPORARY REMOVAL: Drivers of Anemia Reduction among Women of Reproductive Age in the Philippines: A Country Case Study

BackgroundAnemia prevalence among women of reproductive age (WRA) in the Philippines was 25% in 2000, decreasing to 13% in 2018. To date, an in-depth assessment of the determinants associated with this decline has not been conducted. ObjectiveTo conduct a systematic in-depth assessment of the quantitative and qualitative determinants of anemia among WRA in the Philippines between 2008 and 2018. MethodsEmploying standard Exemplars methodology, we conducted quantitative analyses using the Philippines’ National Nutrition Survey, the Expanded National Nutrition Survey, and the Philippines National Demographic and Health Surveys. Qualitative analyses included a comprehnsive literature review, program/policy analysis, and interviews with stakeholders to understand country-level enablers and barriers to WRA anemia decline in the Philippines. A final Oaxaca-Blinder decomposition analysis (OBDA) evaluated the relative contribution of direct and indirect factors. ResultsAmong non-pregnant women (NPW), mean hemoglobin (Hb) increased from 12.7 g/dL in 2008 to 13.1 g/dL in 2018 (p<0.01), corresponding to an 11%-point decline in anemia prevalence (23% to 12%). Inequities by geographical region, household wealth, and women’s educational attainment narrowed considerably during this time. Important direct and indirect nutrition programs were introduced during our study period, including universal healthcare and food fortification. Country experts interviewed credited programs focused on alleviating micronutrient deficiencies and poverty, and improvements in women’s health and well-being, for the country's extraordinary success. OBDA explained ∼50% of the observed change in mean Hb among NPW, with family planning (35%), household socio-demographics (29%), and improvement in women’s nutrition (23%) emerging as critical drivers of anemia decline, corroborating our qualitative and policy analyses. ConclusionsTo protect these gains, WRA anemia prevention efforts in the Philippines should continue to focus on universal healthcare access, women’s empowerment, and poverty alleviation.

Comparative Analysis of GDP Per Capita, Logistic Performance, and Carbon Dioxide Emissions: A Case of SAARC Countries

This study investigated the association between economic growth, environmental sustainability, and social development in SAARC countries. The study uses robust and balanced panel data from 2008 to 2021. The advanced econometric techniques used for empirical analyses, specifically Dynamic Ordinary Least Squares (DOLS). It provided valuable observations on the relationships between economic and environmental factors. The independent variable logistic infrastructure, gross capital formation, labour force participation rate, and carbon dioxide emission significantly affect our dependent variable growth rate The study results showed that logistic infrastructure positively affected our GDP per capita. Similarly, LAB and GCF also directly impacted your GDP per capita while CO2 negatively impacted the GDP per capita of the projected economies. These findings suggest that policymakers must adopt holistic approaches that prioritize sustainable development goals, mitigate environmental degradation, and promote inclusive economic growth to ensure a prosperous and resilient future for all.

THE ROLE OF FINANCIAL DEVELOPMENT ON THE SHARE OF RENEWABLE ENERGY IN JAPAN: A COMPREHENSIVE TIME-SERIES ANALYSIS

The purpose of this study is to analyze the effect of financial development (FD) on the share of renewable energy (RE) usage in Japan. The existing theoretical literature and empirical analyses covering different country cases reveal that FD might have positive, negative, or insignificant effect on RE use. Since there is no empirical investigation of the issue for Japan, the study aims to contribute to the literature. To that end, we used several time-series techniques to detect the association between RE usage and FD in Japan over the 1970–2020 period. The results obtained from the ARDL, Hatemi-J, Maki, Tsong et al. and NARDL cointegration tests showed that there is a significant cointegrated relationship between the share of RE use, FD, GDP per capita and trade openness. As for the long-run coefficients obtained from the ARDL, FMOLS, CCR and NARDL estimators revealed that increases in FD and trade openness raise the share of RE usage while increases in GDP per capita reduce it. Briefly, for the Japan case, we may suggest that improving the financial market structure of the country will bear fruit in terms of the share of cleaner and sustainable energy usage.

Alzheimer's disease and its treatment-yesterday, today, and tomorrow.

Alois Alzheimer described the first patient with Alzheimer's disease (AD) in 1907 and today AD is the most frequently diagnosed of dementias. AD is a multi-factorial neurodegenerative disorder with familial, life style and comorbidity influences impacting a global population of more than 47 million with a projected escalation by 2050 to exceed 130 million. In the USA the AD demographic encompasses approximately six million individuals, expected to increase to surpass 13 million by 2050, and the antecedent phase of AD, recognized as mild cognitive impairment (MCI), involves nearly 12 million individuals. The economic outlay for the management of AD and AD-related cognitive decline is estimated at approximately 355 billion USD. In addition, the intensifying prevalence of AD cases in countries with modest to intermediate income countries further enhances the urgency for more therapeutically and cost-effective treatments and for improving the quality of life for patients and their families. This narrative review evaluates the pathophysiological basis of AD with an initial focus on the therapeutic efficacy and limitations of the existing drugs that provide symptomatic relief: acetylcholinesterase inhibitors (AChEI) donepezil, galantamine, rivastigmine, and the N-methyl-D-aspartate receptor (NMDA) receptor allosteric modulator, memantine. The hypothesis that amyloid-β (Aβ) and tau are appropriate targets for drugs and have the potential to halt the progress of AD is critically analyzed with a particular focus on clinical trial data with anti-Aβ monoclonal antibodies (MABs), namely, aducanumab, lecanemab and donanemab. This review challenges the dogma that targeting Aβ will benefit the majority of subjects with AD that the anti-Aβ MABs are unlikely to be the "magic bullet". A comparison of the benefits and disadvantages of the different classes of drugs forms the basis for determining new directions for research and alternative drug targets that are undergoing pre-clinical and clinical assessments. In addition, we discuss and stress the importance of the treatment of the co-morbidities, including hypertension, diabetes, obesity and depression that are known to increase the risk of developing AD.

Konsep Industrialisasi, Transformasi Struktural

This research explores the concepts of industrialization and structural transformation, two phenomena that are interrelated and have a crucial role in the economic development of a country. Industrialization is the process by which a country or region shifts its economy from an agricultural to an industrial basis, involving increased production of goods and services through the introduction of new technologies and increased production capacity. Structural transformation, on the other hand, refers to fundamental changes in the structure of the economy, involving a shift from the primary sector (agriculture) to the secondary (industry) and tertiary (services) sectors. This study highlights how industrialization drives structural transformation by creating new jobs, increasing productivity, and changing consumption patterns and income distribution. This research also discusses factors that influence these two processes, including government policy, foreign investment, and technological innovation. Through analysis of various cases of countries that have successfully carried out industrialization and structural transformation, this research provides insight into effective strategies that can be implemented by developing countries to achieve sustainable and inclusive economic growth.

Inflationary threshold effect on the nexus between economic growth and public debt: The case of Asian countries

Our study is carried out in an attempt to investigate the causal relationship between economic growth and public debt under the influence of inflation in Asia. To achieve our research objectives, we used a threshold regression model and data collected from Asian countries from 2010 to 2021. The study results show that there is an inflation threshold of 10.4907% at which the influence of inflation changes and the increase in public debt harms the growth rate. Additionally, regression results on the relationship between public debt and economic growth show different results between developed and developing countries. The research results confirm previous researchers' theories and empirical findings on the relationship between inflation and economic growth. In addition, government spending negatively impacts economic growth, while population growth, capital stock, and trade scale positively impact economic growth. Studying the relationship between economic growth and public debt can provide a helpful reference for Asian policymakers. Accordingly, governments should pay special attention to maintaining moderate inflation and limiting public debt to promote economic growth.

Selection versus transmission: Quantitative and organismic biology in antibiotic resistance

We aimed to determine the importance of selection (mostly dependent on the anthropogenic use of antimicrobials) and transmission (mostly dependent on hygiene and sanitation) as drivers of the spread of antibiotic-resistant bacterial populations. The first obstacle to estimating the relative weight of both independent variables is the lack of detailed quantitative data concerning the number of bacterial cells, potentially either pathogenic or harmless, and bacterial species exposed to antimicrobial action in the microbiotas of specific environments. The second obstacle is the difficulty of considering the relative importance of the transmission and selection exerting their combined effects on antibiotic resistance across eco-biological levels. As a consequence, advances are urgently required in quantitative biology and organismic biology of antimicrobial resistance. The absolute number of humans exposed to antibiotics and the absolute number of potentially pathogenic and commensal bacteria in their microbiomes should influence both the selection and transmission of resistant bacterial populations. The “whole Earth” microbiome, with astonishingly high numbers of bacterial cells and species, which are also exposed to anthropogenic antimicrobials in various biogeographical spaces, shapes the antibiotic resistance landscape. These biogeographical spaces influence various intensities of selection and transmission of potentially pathogenic bacteria. While waiting for more precise data, biostatistics analysis and mathematical or computational modeling can provide proxies to compare the influence of selection and transmission in resistant bacteria. In European countries with lower sanitation levels, antibiotic consumption plays a major role in increasing antibiotic resistance; however, this is not the case in countries with high sanitation levels. Although both independent variables are linked, their relative influence on the level of antibiotic resistance varies according to the particular location. Therefore, interventions directed to decrease antibiotic resistance should be designed “a la carte” for specific locations with particular ecological conditions, including sanitation facilities.

Progress Toward Poliomyelitis Eradication - Worldwide, January 2022-December 2023.

In 1988, poliomyelitis (polio) was targeted for eradication. Global efforts have led to the eradication of two of the three wild poliovirus (WPV) serotypes (types 2 and 3), with only WPV type 1 (WPV1) remaining endemic, and only in Afghanistan and Pakistan. This report describes global polio immunization, surveillance activities, and poliovirus epidemiology during January 2022-December 2023, using data current as of April 10, 2024. In 2023, Afghanistan and Pakistan identified 12 total WPV1 polio cases, compared with 22 in 2022. WPV1 transmission was detected through systematic testing for poliovirus in sewage samples (environmental surveillance) in 13 provinces in Afghanistan and Pakistan, compared with seven provinces in 2022. The number of polio cases caused by circulating vaccine-derived polioviruses (cVDPVs; circulating vaccine virus strains that have reverted to neurovirulence) decreased from 881 in 2022 to 524 in 2023; cVDPV outbreaks (defined as either a cVDPV case with evidence of circulation or at least two positive environmental surveillance isolates) occurred in 32 countries in 2023, including eight that did not experience a cVDPV outbreak in 2022. Despite reductions in paralytic polio cases from 2022, cVDPV cases and WPV1 cases (in countries with endemic transmission) were more geographically widespread in 2023. Renewed efforts to vaccinate persistently missed children in countries and territories where WPV1 transmission is endemic, strengthen routine immunization programs in countries at high risk for poliovirus transmission, and provide more effective cVDPV outbreak responses are necessary to further progress toward global polio eradication.

Cultural institutions as knowledge-intensive public organisations (KIPOs) and their role: how digitalisation can change them providing sustainable and accessible public services

PurposeThis exploratory research seeks to clarify the role of cultural organisations as knowledge-intensive public organisations (KIPOs) and the trend of digital content creation in museum sectors and national strategies through a country case study. It aims to provide a deeper understanding and analysis of museums' roles as KIPOs, specifically focusing on their digitalisation and digital content development for service delivery. Digital technology utilisation in the museum sector has amplified the significance of digital content, not only because of the increasing use of digital technologies among the public but also because it provides attractive new content to appeal to customers, as well as more efficient knowledge management and knowledge reproduction tools for KIPOs. Thus, this paper analyses digital content creation in the museum sector and policy frameworks to provide insights into the role of museums as KIPOs by utilising digital technologies.Design/methodology/approachWe conducted literature review on six keywords, combination of “cultural institution”, “museum”, “digitalization”, “digital content”, and “ICT” to understand the digitalisation of museums amongst academic papers, then used a case study to figure out the common issues as well as case-specific features of these digital offerings through analysis of the digital platforms of museums. Specifically, we choose the case of South Korea, its national strategies and budget allocations and the museum sectors in the country. Thus, the secondary data analysis was provided by the official channels, such as documents from government agencies, media sources, such as articles from newspapers and magazines and academic works of literature, such as papers in scientific journals.FindingsThis paper reveals the research trend in museums' digitalisation, especially through the case study, how the South Korean government has argued digital content development in museum sectors through their national strategies and budget allocations, and the trend of museums' digital offerings since 2021. This paper thus presents a novel contribution to the field by delving into the research trend in digitalisation and digital content development in the museum sector and analysing the South Korean government's national strategies and budget allocation in this context. The literature review shows that the digitalisation of museums has increased research interest in the last few years in limited areas. South Korea has allocated budgets and policies to encourage digital content creation in museums, and this study identifies an increase in digital content creation in the museum sector.Research limitations/implicationsThe paper chose one-country case study, that of South Korea; thus, there are representative limitations and thus in terms of generalisation of the results. Further research with case studies from other countries and comparative studies are required.Practical implicationsThis study highlights the importance of digitalisation and digital content development in the museum sector through government policies, strategies and financial investment.Social implicationsIt highlights the importance of digitalisation and the introduction of digital contents amongst museums to gain new visitors and change the relationship between the institutions and the customers.Originality/valueIt deals with the digitalisation of museums as KIPOs and it is a new and relevant topic per se. This study enhances the understanding of the museum sector’s digital content development and national policies to support its activities. It provides insights into the utilisation of digital technologies in cultural institutions for digital service delivery in public organisations.

Role of institutions in public management: developing case studies for divergent policy systems

Public policy management has an intractable nature, and the institutional complexity of governance further exacerbates its practice. Transnational learning cutting across countries and policy areas can contribute to this policy knowledge in dealing with multifarious issues in public management. Understanding the institutional mix in public management in various contexts enhances the existing comprehension of how the national pattern of public management works differently in different socio-economic, cultural, and political settings. The present research aims to study the institutional framework in the form of state structure (unitary or federal) and the nature of executive government (majoritarian or consensual) in delineating the influence of institutions on public management processes in divergent policy systems. The paper undertakes four in-depth country case studies and the public management reforms as a response to institutional pressure are examined using the 4 M strategy–Maintain (holding on to existing administrative structures and processes), Modernize (keeping service delivery and regulation up to date), Marketize (efficiency and user-responsive public management), and Minimize (reducing state-led regulation). The case studies highlight the differences in the broad direction and energy of implementation that characterize a particular policy style. The results of the study indicate that even though the institutional dimensions are not present in strict polarization, the impact of the institutional mix is evident in the dominant strategies of public management reforms adopted at the national level.

Country-report pattern corrections of new cases allow accurate 2-week predictions of COVID-19 evolution with the Gompertz model

Accurate short-term predictions of COVID-19 cases with empirical models allow Health Officials to prepare for hospital contingencies in a two–three week window given the delay between case reporting and the admission of patients in a hospital. We investigate the ability of Gompertz-type empiric models to provide accurate prediction up to two and three weeks to give a large window of preparation in case of a surge in virus transmission. We investigate the stability of the prediction and its accuracy using bi-weekly predictions during the last trimester of 2020 and 2021. Using data from 2020, we show that understanding and correcting for the daily reporting structure of cases in the different countries is key to accomplish accurate predictions. Furthermore, we found that filtering out predictions that are highly unstable to changes in the parameters of the model, which are roughly 20%, reduces strongly the number of predictions that are way-off. The method is then tested for robustness with data from 2021. We found that, for this data, only 1–2% of the one-week predictions were off by more than 50%. This increased to 3% for two-week predictions, and only for three-week predictions it reached 10%.

School Principals’ Distributed Leadership Style, Teachers’ Job Satisfaction And Organizational Commitment: A Case Of Low-Income And Underdeveloped Country

School Principals’ Distributed Leadership Style, Teachers’ Job Satisfaction And Organizational Commitment: A Case Of Low-Income And Underdeveloped Country