Infectious Disease Epidemics Research Articles

2.Y.2. International Health Regulations – role on disease control and global challenges

Abstract The International Health Regulations (IHR) are a legal instrument aimed to control infectious disease epidemics worldwide and that makes countries accountable for monitoring and promptly notifying the World Health Organization (WHO) of events that are likely to represent a public health emergency. The 196 signatory countries are bound by this international agreement. This workshop aims to present evidence on the role and updates of the IHR as a framework for global health preparedness. It will do that by exploring the main components of the IHR and their practical implications for public health practice, with particular emphasis on their function in preventing, detecting, and responding to cross-border public health threats. The workshop will feature four short presentations, in a total of 15 minutes, beginning with three presentations showcasing the findings of literature reviews covering various aspects of the IHR. These topics include the main challenges to implementation, the effectiveness of the IHR during the COVID-19 pandemic, its relevance to travel medicine and zoonosis prevention, and strategies for controlling vector-borne diseases. The last presentation will delve into the challenges and opportunities associated with implementing the IHR at both national and international levels, in the context of the proposals from the Working Group on Amendments to the International Health Regulations (2005). Throughout the workshop, emphasis will be placed on understanding how the IHR facilitate collaboration and coordination among countries during health emergencies, as well as the importance of capacity-building, information sharing, and multisectoral collaboration. This structure will allow for discussion aimed at areas for improvement to the IHR, especially in the context of its revision process and global health governance. We believe the added value of this workshop will be creating a platform for critical analysis and dialogue, sharing insights into the evolution of the IHR, ongoing debates, controversies, and emerging trends in global health regulations. Key messages • This workshop provides a platform for in-depth exploration of the IHR’s role in global health preparedness, offering evidence on its components and practical implications. • Through analysis of challenges and discussions on disease control, attendees will engage in critical dialogue aimed at improving the IHR and enhancing global health governance.

Maailman terveysjärjestön legitimiteetti ja legitimiteettikriisit COVID-19-pandemian valossa

The legitimacy of the World Health Organization in light of the COVID-19 pandemic This article provides an overview of the legitimacy and the legitimacy crises of the World Health Organization (WHO). During the COVID-19 pandemic, in the era of social media, WHO’s legitimacy crisis has appeared to be historically strong. Based on previous quantitative and qualitative research, the article assesses factors influencing the legitimacy of the WHO. The article identifies the most significant legitimacy crises of the WHO, and examines the similarities and differences between the crises. The legitimacy crises of the WHO are intertwined with infectious disease epidemics. In these situations, the WHO, with its measures and recommendations, becomes under public scrutiny due to increased media visibility. Moreover, the WHO gets merged into international and national political struggles. With the COVID-19 pandemic, research on the legitimacy of the WHO is timely and necessary. Through this comprehensive overview of the...

Extreme precipitation, exacerbated by anthropogenic climate change, drove Peru's record-breaking 2023 dengue outbreak.

Anthropogenic climate change is increasing the risk of extreme events that can lead to infectious disease epidemics, but few studies have directly measured this health cost of climate change. We do so by focusing on Cyclone Yaku, which affected northwestern Peru in March 2023, and was immediately followed by a dengue epidemic. Cyclone Yaku caused 67% of cases reported over six months in the affected region. Industrial-era climate forcing has increased the likelihood of extreme March precipitation like that associated with Cyclone Yaku by 42%. Assessing the linkages between climate change, extreme weather, and outbreaks of dengue and other infectious diseases is crucial for understanding the impact that climate change has already had and preparing for future health risks.

Influenza Virus Genomic Mutations, Host Barrier and Cross-Species Transmission

Abstract: Influenza is a global epidemic infectious disease that causes a significant number of illnesses and deaths annually. Influenza exhibits high variability and infectivity, constantly jumping from birds to mammals. Genomic mutations of the influenza virus are a central mechanism leading to viral variation and antigenic evolution. These are crucial in facilitating the virus to cross species barriers and cause human infection. This review summarizes the types of genomic mutations in the influenza virus, their roles and mechanisms in crossing species barriers, and analyzes the impact of these mutations on human health.

Simulation of Epidemic Dynamics Using a Multi-Agent Model: Analysis of Social Distancing Strategies and Their Impacts on Public Health and Economy

Infectious disease epidemics have played a crucial role in shaping public health responses, particularly in global health crises. This study emerges as part of the efforts to prepare effective responses to potential future pandemics, leveraging lessons learned during the COVID-19 crisis. The research uses an adapted compartmental epidemiological model and a synthetic multi-agent community to investigate how social variables influence epidemic forecasts in socioeconomically vulnerable regions. Focusing on the simulation of epidemic dynamics in the socio-economically disadvantaged neighbourhood of Ilha Joana Bezerra in Recife, this study examines the impacts of social distancing strategies and other control measures, such as face masks and moderate social isolation. Through the adapted SEPAI3R3O model, which includes compartments for pre-symptomatic and asymptomatic states, this study provides a detailed analysis of disease dynamics in contexts characterised by high social vulnerability. The results underscore the importance of public health policies adapted to socio-economic factors, emphasising the need for continuous preparedness to manage future epidemic threats in vulnerable communities effectively.

Scale-Up of COVID-19 Testing Services in NYC, 2020-2021: Lessons Learned to Maximize Reach, Equity and Timeliness.

During infectious disease epidemics, accurate diagnostic testing is key to rapidly identify and treat cases, and mitigate transmission. When a novel pathogen is involved, building testing capacity and scaling testing services at the local level can present major challenges to healthcare systems, public health agencies, and laboratories. This mixed methods study examined lessons learned from the scale-up of SARS-CoV-2 testing services in New York City (NYC), as a core part of NYC's Test & Trace program. Using quantitative and geospatial analyses, the authors assessed program success at maximizing reach, equity, and timeliness of SARS-CoV-2 diagnostic testing services across NYC neighborhoods. Qualitative analysis of key informant interviews elucidated key decisions, facilitators, and barriers involved in the scale-up of SARS-CoV-2 testing services. A major early facilitator was the ability to establish working relationships with private sector vendors and contractors to rapidly procure and manufacture necessary supplies locally. NYC residents were, on average, less than 25min away from free SARS-CoV-2 diagnostic testing services by public transport, and services were successfully directed to most neighborhoods with the highest transmission rates, with only one notable exception. A key feature was to direct mobile testing vans and rapid antigen testing services to areas based on real-time neighborhood transmission data. Municipal leaders should prioritize fortifying supply chains, establish cross-sectoral partnerships to support and extend testing services, plan for continuous testing and validation of assays, ensure open communication feedback loops with CBO partners, and maintain infrastructure to support mobile services during infectious disease emergencies.

One Step Forward, How Many Steps Back? Benchmarking the US Covid-19 Pandemic Response Against United Nations Sustainable Development Target 3.3

In 2015, the United Nations adopted 17 sustainable development goals (SDGs), mapping out specific targets to work toward in order to achieve worldwide peace and prosperity. SDG 3 promotes healthy living, while target 3.3 strives to end epidemics of various infectious diseases. In this project, I examine how the Covid-19 outbreak impacted the US’s progress toward SDG target 3.3, analyzing both academic literature and government documents in the form of a literature review. I discuss trends and flaws in the US pandemic response, briefly contrasting US containment measures with Singapore’s, before examining the pandemic’s effects on incidence rates and service outcomes for two communicable diseases — tuberculosis and HIV. Although a lack of internal and external coordination, the federalist structure of the US government, inflexible funding, and politicization of infectious disease control prevented the CDC from responding to the pandemic effectively, tuberculosis incidence rates dropped in 2020 due to less face-to-face contact and possible missed diagnoses, while HIV services experienced a rebound in late 2020 due to self test, telehealth, and antiretroviral therapy home delivery services. While Covid-19 did not dismantle the US’s progress toward UN SDG target 3.3, greater communication, deeper public understanding, and an ability to expect the unexpected would accelerate the US’s movement toward effective management of communicable diseases.

Mapping the Characteristics of Respiratory Infectious Disease Epidemics in China Based on the Baidu Index from November 2022 to January 2023.

Infectious diseases pose a significant global health and economic burden, underscoring the critical need for precise predictive models. The Baidu index provides enhanced real-time surveillance capabilities that augment traditional systems. Baidu search engine data on the keyword "fever" were extracted from 255 cities in China from November 2022 to January 2023. Onset and peak dates for influenza epidemics were identified by testing various criteria that combined thresholds and consecutive days. The most effective scenario for indicating epidemic commencement involved a 90th percentile threshold exceeded for seven consecutive days, minimizing false starts. Peak detection was optimized using a 7-day moving average, balancing stability and precision. The use of internet search data, such as the Baidu index, significantly improves the timeliness and accuracy of disease surveillance models. This innovative approach supports faster public health interventions and demonstrates its potential for enhancing epidemic monitoring and response efforts.

Estimated Deaths Averted in Adults by COVID-19 Vaccination in Select Latin American and Caribbean Countries.

The coronavirus disease 2019 (COVID-19) pandemic has had a significant impact on global health, with millions of lives lost worldwide. Vaccination has emerged as a crucial strategy in mitigating the impact of the disease. This study aims to estimate the number of deaths averted through vaccination in Latin America and the Caribbean region (LAC) during the first year and a half of vaccination rollout (January 2021-May 2022). Publicly available data on COVID-19 deaths and vaccination rates were used to estimate the total number of deaths averted via vaccination in LAC. Using estimates for number of deaths, number of vaccinated, and vaccine effectiveness, a counterfactual estimated number of deaths observed without vaccination was calculated. Vaccine effectiveness estimates were obtained from published studies. The analysis focused on 17 countries in LAC and considered adults aged 18 years and older. After accounting for underreporting, the analysis estimated that >1.49 million deaths were caused by COVID-19 in the selected countries during the study period. Without vaccination, the model estimated that between 2.10 and 4.11 million COVID-19 deaths would have occurred. Consequently, vaccination efforts resulted in ∼610 000 to 2.61 million deaths averted. This study represents the first large-scale, multicenter estimate of population-level vaccine impact on COVID-19 mortality in LAC. The findings underscore the substantial impact of timely and widespread vaccination in averting COVID-19 deaths. These results provide crucial support for vaccination programs aimed at combating epidemic infectious diseases in the region and future pandemics.

Evaluating information management system in epidemic infectious diseases in Iran

Health information management is a vital and constructive component of the health system, refers to the process of producing and collecting, organising and storing, analysing, disseminating and using information. The aim of this study was to evaluate the strengths and weaknesses of the information management system in epidemic infectious diseases in Iran, specifically focusing on the registration, reporting, quality, confidentiality, and security of infectious disease data. This assessment was conducted from the perspective of policymakers and experts responsible for data registration and reporting. After examining the processes of registering and reporting infectious disease data and interviewing experts, a researcher-designed questionnaire was prepared to evaluate the infectious disease information management system. To assess the content validity of the Content Validity Index and Content Validity Ratio Index, a questionnaire was utilized. The reliability of the questionnaire was confirmed using Cronbach's alpha. By employing purposeful sampling and adhering to the inclusion criteria, 150 participants were included in the study. Questionnaires were distributed via email, WhatsApp, or Telegram to employees at various levels of Iran's health and treatment systems who were responsible for registering and reporting infectious disease data. The study encompassed 100 participants who successfully concluded the research. The results highlight that the key strength of healthcare data registration lies in its ability to "depict the epidemic curve during outbreaks of infectious diseases." Conversely, a notable weakness was the "insufficient collaboration from non-academic sectors (e.g., clinics, private laboratories) in registering and reporting infectious diseases. The present study's findings suggest that the issue lies not in the framework itself, but rather in the execution and functionality of the strategies. We can cultivate a repository of reliable and beneficial data by incorporating initiatives like training programs, enforcing regulations with consequences for inadequate data documentation, offering both material and motivational rewards, and streamlining all data collection and reporting systems.

Evaluating the Healthcare System Responsiveness for COVID-19 Care in Southeast Iran

Background: Health system responsiveness is critical in managing infectious disease epidemics. Objectives: The purpose of this study was to evaluate the responsiveness of the health system during the Coronavirus disease 2019 (COVID-19) pandemic. Methods: A cross-sectional study was conducted among 350 patients who had been discharged from hospitals after recovering from COVID-19 during 2021 - 2022 in Sistan-Baluchistan province, located in the southeastern region of Iran. Data were collected using the World Health Organization health system responsiveness tool through telephone interviews. Descriptive statistics methods were used to determine the responsiveness score. T-tests and one-way analysis of variance were also used to compare the means between groups. Results: The overall score for health system responsiveness was 110.12 ± 13.12, indicating a moderate level of responsiveness. The communication dimension received the highest mean score (30.12 ± 4.73), while the choice of provider dimension had the lowest mean score (5.65 ± 2.37). Significant relationships were found between health system responsiveness and variables such as place of residence (P = 0.01), city of residence (P = 0.001), and household size (P = 0.05). Conclusions: The study identified areas for improvement in health system responsiveness within Sistan-Baluchistan's hospitals during the COVID-19 pandemic. To enhance patient care and strengthen the healthcare system's responsiveness, health policymakers should implement measures such as developing responsiveness guidelines, establishing a dedicated responsiveness unit, and providing training programs for healthcare professionals. Regular evaluation of responsiveness in hospitals is also crucial.

Factors Contributing to Emergence of infectious viral diseases in India: Issues and Challenges after COVID-19 Pandemic

Emerging and re-emerging viral infections are major cause of morbidity and mortality in humans and animals. India had experienced numerous infectious disease outbreaks and epidemics in past years. However, tremendous strides have been achieved in the past in the fight against serious epidemic diseases. It has been found that a wide range of complex factors, such as pathogen evolution, human invasion, commerce in wild animals, microbial adaptation, changes in the environment and dynamic interactions between humans and animals influence the emergence and transmission of infectious viral diseases. As the COVID-19 pandemic demonstrated, India's secondary and tertiary health-care system is quite advanced. The study of infectious diseases, in particular their pathogenesis, genetic profile and diagnosis has fundamentally changed with the advent of genome sequencing and nucleic acid detection technology. Additionally, advance therapy and vaccination led to best possible patient management and care. Further scientific investigations and research are needed to discover neglected diseases that have the potential to cause epidemics as well as to develop updated vaccines, modern treatment strategy and diagnostics at molecular level. This evaluation will aid for policymakers, academics and researchers to redesign the course of action to combat the deadly emerging pathogenic viruses and also preserve the ecosystem.

신문기사에 대한 의미연결망 분석을 통한 의료 시장화 논리와 의료 보장성 논리 분석

There is a lack of research analyzing the formation and change of institutional logics in the Korean healthcare sector. This study examines the major institutional changes that occurred from 1990 to 2018 and explores institutional logics by conducting semantic network analysis on Korean newspaper articles. The analysis identified the 'medical marketization logic' and the 'medical coverage logic' as the main competing logics, and six groups of institutional vocabularies were found to support these two logics. The medical marketization logic has been strengthened primarily during conservative governments, while the medical coverage logic has been strengthened during liberal governments, and large-scale infectious disease epidemics have been shown to be important catalysts for changes in institutional logics. This study contributes to understanding the complexity and dynamics of institutional logics, suggests prospects and possibilities for institutional logic change in healthcare, and suggests directions for future research.

Outbreak detector: a web application to boost disease surveillance systems and timely detection of infectious disease epidemics

ObjectiveDigital technologies have improved the performance of surveillance systems through early detection of outbreaks and epidemic control. The aim of this study is to introduce an outbreak detection web application called OBDETECTOR (Outbreak Detector), which as a professional web application has the ability to process weekly or daily reported data from disease surveillance systems and facilitates the early detection of disease outbreaks.ResultsOBDETECTOR generates a histogram that exhibits the trend of infection within a time range selected by the user. The output comprises red triangles and plus signs, where the former denotes outbreak days determined by the algorithm applied to the data, and the latter represents days identified as outbreaks by the researcher. The graph also displays threshold values and its symbols enable researchers to compute evaluation criteria for outbreak detection algorithms, including sensitivity and specificity. OBDETECTOR allows users to modify algorithm parameters based on their research objectives immediately after loading data. The implementation of automatic web applications results in immediate reporting, precise analysis, and prompt alert notification. Moreover, Public Health authorities and other stakeholders of surveillance can benefit from the widespread accessibility and user-friendliness of these tools, enhancing their knowledge and skills for better engagement in surveillance programs.

Development of a core outcome set for maternal and perinatal health research and surveillance in light of emerging and ongoing epidemic threats.

Maternal and perinatal health is often directly and indirectly affected during infectious disease epidemics. Yet, a lack of evidence on epidemics' impact on women and their offspring delays informed decision-making for healthcare providers, pregnant women, women in the post-pregnancy period and policy-makers. To rapidly generate evidence in these circumstances, we aim to develop a Core Outcome Set (COS) for maternal and perinatal health research and surveillance in light of emerging and ongoing epidemic threats. We will conduct a Systematic Review and a four-stage modified Delphi expert consensus. The systematic literature will aim to inform experts on outcomes reported in maternal and perinatal research and surveillance during previous epidemics. The expert consensus will involve two individual, anonymous online surveys to rate outcomes' importance and suggest new ones, one virtual meeting to discuss disagreements, and one in-person meeting to agree on the final COS, outcomes definitions and measurement methods. Four panels will be established to participate in the modified Delphi with expertise in (a) maternal and perinatal health, (b) neonatal health, (c) public health and emergency response, and (d) representation of civil society. We will recruit at least 20 international experts for each stakeholder group, with diverse backgrounds and gender, professional, and geographic balance. Only highly-rated outcomes (with at least 80% of ratings being 7-9 on a 9-point Likert scale) and no more than 10% of low ratings (1-3) will be included in the final COS. Implementing this COS in future maternal and perinatal research and surveillance, especially in the context of emerging and ongoing epidemic threats, will facilitate the rapid and systematic generation of evidence. It will also enhance the ability of policy-makers, healthcare providers, pregnant women and women in the post-pregnancy period and their families to make well-informed choices in challenging circumstances.

WITHDRAWN: Inhibitory effect of Jingfang Mixture on Staphylococcus aureus α-hemolysin

Staphylococcus aureus (S. aureus) is a kind of gram-positive bacteria, and its virulence factors can cause many kinds of infections. Traditional antibiotics can not only kill bacteria, but also easily lead to bacterial resistance. Jingfang Mixture (JFM) is commonly used in clinic to prevent and treat epidemic diseases and infectious diseases. The main purpose of this study is to explore the inhibitory effect of JFM on alpha-hemolysin (Hla) of S. aureus and to alleviate the damage caused by Hla. We found that JFM could inhibit the hemolytic activity, gene and protein level and neutralizing activity of Hla in a dose-dependent manner at the concentrations of 125, 250 and 500 μg/mL, without affecting the growth of bacteria. In addition, JFM reduced the damage of Hla to A549 cells and the release of lactate dehydrogenase (LDH). We also observed that in the S. aureus - induced pneumonia mouse model, JFM could significantly prolong the life of mice, reduce the bacterial load in the lungs, significantly improve the pathological state of the lungs and alleviate the damage caused by inflammatory factors, and the pathogenicity of gene deletion strain DU 1090 of S. aureus to pneumonia mice was also significantly reduced. In conclusion, this study proved that JFM is a potential drug against S. aureus infection, and this study provided a preliminary study for better guidance of clinical drug use.

Inhibitory effect of Jingfang mixture on Staphylococcus aureus α-hemolysin.

Staphylococcus aureus is a gram-positive bacteria, and its virulence factors can cause many kinds of infections, such as pneumonia, sepsis, enteritis and osteomyelitis. Traditional antibiotics can not only kill bacteria, but also easily lead to bacterial resistance. Jingfang Mixture (JFM) has the effects of inducing sweating and relieving the exterior, dispelling wind and eliminating dampness, and is commonly used in clinic to prevent and treat epidemic diseases and infectious diseases. The main purpose of this study is to explore the inhibitory effect of JFM on alpha-hemolysin (Hla) of S. aureus and to alleviate the damage caused by Hla. We found that JFM could inhibit the hemolytic activity, transcription level and neutralizing activity of Hla in a dose-dependent manner at the concentrations of 125, 250 and 500µg/mL, without affecting the growth of bacteria. In addition, JFM reduced the damage of Hla to A549 cells and the release of lactate dehydrogenase (LDH). We also observed that in the S. aureus - induced pneumonia mouse model, JFM could significantly prolong the life of mice, reduce the bacterial load in the lungs, significantly improve the pathological state of the lungs and alleviate the damage caused by inflammatory factors, and the pathogenicity of gene deletion strain DU 1090 of S. aureus to pneumonia mice was also significantly reduced. In conclusion, this study proved that JFM is a potential drug against S. aureus infection, and this study provided a preliminary study for better guidance of clinical drug use.

Diabetes mellitus in sub-saharan Africa during the COVID-19 pandemic: A scoping review.

The COVID-19 pandemic impacted the healthcare and outcomes of individuals with various chronic diseases. However, there is a paucity of data on the impact of the COVID-19 pandemic on diabetes mellitus (DM) in low-resource settings. To address this, we conducted a scoping review to explore the literature published on diabetes-related COVID-19 outcomes and care during the COVID-19 pandemic in countries of sub-Saharan Africa. We applied our search strategy to PubMed, Web of Science, CINAHL, African Index Medicus, Google Scholar, Cochrane Library, Scopus, Science Direct, ERIC and Embase to obtain relevant articles published from January 2020 to March 2023. Two independent reviewers were involved in screening the retrieved articles. Data from eligible articles were extracted from quantitative, qualitative and mixed-methods studies. Quantitative evidence was summarised using descriptive statistics, while a thematic framework was used to identify and categorise themes from qualitative evidence. We found 42 of the retrieved 360 articles eligible, mainly from South Africa, Ethiopia and Ghana (73.4%). The incidence of DM among COVID-19 cases was 13.7/1,000 person-days observation. COVID-19 was associated with increased odds of death (OR 1.30-9.0, 95% CI), hospitalisation (OR 3.30-3.73: 95% CI), and severity (OR: 1.30-4.05, 95% CI) in persons with DM. Challenges in caring for DM during the pandemic were inadequate patient self-management, difficulties in healthcare access, and inadequate healthcare resources. The COVID-19 pandemic was characterised by a high incidence of DM in persons infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and high COVID-19-associated mortality, severity, and hospitalisation among people persons with DM. The pandemic also created difficulties in DM self-management and worsened the quality of DM care services. Policymakers should devise preventive and management strategies for DM during emerging and re-emerging infectious disease epidemics and outbreaks, given that such occurrences are increasingly frequent in the region.

Red Blood Cell Distribution Width Predicts Mortality in Hospitalized Patients with Severe Fever with Thrombocytopenia Syndrome.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging epidemic infectious disease with high mortality rate. This study aimed to investigate the association of red blood cell distribution width (RDW) and mortality risk in hospitalized SFTS patients. Clinical data of SFTS patients was retrospectively collected from three hospitals between October 2010 and August 2022. Cox proportional hazards model was used to identity the risk factors for fatal outcome. The predictive value of RDW for fatal outcome was evaluated by the receiver operating characteristic (ROC) analysis and Kaplan-Meier methods. Of 292 patients, the median age was 61.5 years. Non-survivors showed higher RDW value than survivors (13.6% vs.13.0%, P < 0.001). The mortality rate was 44.8% in patients with elevated RDW compared to 18.4% of patients with normal RDW, with a relative risk (RR) of 2.439. Elevated RDW was an independent risk factor of mortality (hazards ratio: 1.167, P = 0.019). Patients with elevated RDW had a higher cumulative mortality than patients with normal RDW. The area under the ROC curve (AUC) of RDW for the prediction of mortality was 0.690 (P < 0.001). Elevated RDW was associated with higher mortality risk for patients hospitalized for SFTS. RDW may be helpful for risk stratification in SFTS patients.

Nursing students’ willingness to respond in disasters: a cross sectional study of facilitators and barriers

IntroductionThe preparedness of the healthcare system to address emergency situations is contingent on the inclination of healthcare personnel. Nursing students can serve as valuable resources to supplement the workforce during major incidents and disasters. This study investigated the facilitators and barriers of nursing students’ willingness to respond to disasters at the Alborz University of Medical Sciences in 2022.MethodsIn this cross-sectional descriptive study, 234 nursing students were recruited using convenience sampling. A deductive-inductive questionnaire was developed and distributed through an online self-administered survey comprising demographic information and questions on barriers, facilitators, various disaster scenarios, preferred activities, and reasons for pursuing a nursing career.ResultsThe mean willingness scores of nursing students in response to various disasters were as follows: 3.15 for natural disasters, 2.60 for man-made disasters, 2.94 for pandemics, and 3.32 overall. Among the disaster scenarios, the earthquake response obtained the highest willingness score, while infectious disease epidemics received the lowest score. The most and least willingness to perform activities during disaster response were related to bedside care and participation in patients’ personal hygiene, respectively. Key determinants of participation included the possibility of immunization and concerns for family safety.ConclusionThe findings indicated that nursing students are generally willing to assist as members of the healthcare team during disasters. However, the willingness to respond to infectious disease epidemics and man-made disasters was below the norm. Concerns about family health and the risk of disease transmission were identified as primary barriers. Addressing these concerns is crucial to enhance nursing students’ participation in disaster response.