Spread Of Infectious Diseases Research Articles

A guided twin delayed deep deterministic reinforcement learning for vaccine allocation in human contact networks

This manuscript introduces an innovative approach to optimizing the distribution of a limited vaccine resource within a population modeled as a contact network, aiming to mitigate the spread of infectious diseases. The study develops a novel methodology that combines reinforcement learning and graph neural networks. To understand the dynamics of disease propagation, the study constructs an analytical model that outlines conditions for disease eradication or endemic states. This model supports a series of simulation experiments across various scenarios, demonstrating the proposed method’s superiority over random and centrality-based approaches in reducing the average number of infections per individual during an outbreak. The adaptability of the proposed method is further emphasized by its robust performance across networks of diverse sizes and configurations, highlighting its real-world applicability. The findings of this study have significant implications for public health policy and resource allocation, offering a promising framework for managing infectious disease outbreaks in complex and dynamic environments.

Relationship between COVID-19 Cases and Environmental Contaminants in Quito, Ecuador.

The relationship between COVID-19 infections and environmental contaminants provides insight into how environmental factors can influence the spread of infectious diseases. By integrating epidemiological and environmental variables into a mathematical framework, the interaction between virus spread and the environment can be determined. The aim of this study was to evaluate the impact of atmospheric contaminants on the increase in COVID-19 infections in the city of Quito through the application of statistical tests. The data on infections and deaths allowed to identify the periods of greatest contagion and their relationship with the contaminants O3, SO2, CO, PM2.5, and PM10. A validated database was used, and statistical analysis was applied through five models based on simple linear regression. The models showed a significant relationship between SO2 and the increase in infections. In addition, a moderate correlation was shown with PM2.5, O3, and CO, and a low relationship was shown for PM10. These findings highlight the importance of having policies that guarantee air quality as a key factor in maintaining people's health and preventing the proliferation of viral and infectious diseases.

Coevolution of non-pharmaceutical interventions and infectious disease spreading in age-structured populations

In the face of emerging major infectious diseases, non-pharmaceutical interventions (NPIs) such as mask-wearing are the primary means of disease control in the early stages due to the lack of effective pharmaceutical interventions. Yet the current understanding of the dynamic feedback loop between NPIs and infectious disease spreading remains limited. In this study, we proposed an asymmetrically coupled dynamic model of the coevolution of mask-wearing behaviour and infectious disease spreading in an age-structured population to describe the bidirectional relationship between NPIs such as mask-wearing and infectious disease spreading. A theoretical analysis framework was developed by extending the microscopic Markov chain method. To reflect the spreading process more realistically, we conducted numerical simulations from a mesoscopic perspective through an age-contact data-driven approach. Critical transition, multi-wave epidemics, multi-transitions, and mixed-phase transitions resulting from the coevolution of mask and disease are observed. The results highlight the critical role of NPIs in controlling disease spreading. The mask-wearing can effectively reduce the daily peak infection density and prevent large-scale outbreaks within a short period. However, it will also prolong the duration of the epidemic and cause the disease to exist in the population for a long time. There is a trade-off between the two. For certain diseases with specific spreading capabilities, pharmaceutical interventions such as vaccination, which can directly reduce the disease’s infectiousness, may result in more people being infected if NPIs are not implemented as early as possible. In addition, results from Anhui indicate that people aged 42 years are at high risk of being infected because of their large population base, which suggests that priority should be given to the prevention and control of this group.

Optimal control strategies for infectious disease management: Integrating differential game theory with the SEIR model

The rapid spread of infectious diseases poses a critical threat to global public health. Traditional frameworks, such as the Susceptible–Exposed–Infectious–Recovered (SEIR) model, have been crucial in elucidating disease dynamics. Nonetheless, these models frequently overlook the strategic interactions between public health authorities and individuals. This research extends the classic SEIR model by incorporating differential game theory to analyze optimal control strategies. By modeling the conflicting objectives of public health authorities aiming to minimize infection rates and intervention costs, and individuals seeking to reduce their infection risk and inconvenience, we derive a Nash equilibrium that provides a balanced approach to disease management. Using Picard’s iterative method, we solve the extended model to determine dynamic, optimal control strategies, revealing oscillatory behavior in public health interventions and individual preventive measures. This comprehensive approach offers valuable insights into the dynamic interactions essential for effective infectious disease control.

Sex differences in COVID-19 vaccine confidence in people living with HIV in Canada

BackgroundUnderstanding the roots of vaccine confidence in vulnerable populations, such as persons living with HIV (PLWH), is important to facilitate vaccine uptake, thus mitigating infection and spread of vaccine-preventable infectious diseases. In an online survey of PLWH conducted in Canada during winter 2022 (AIDS and Behav 2023), we reported that the overall COVID-19 vaccination uptake rate in PLWH was similar by sex. Here, we examined attitudes and beliefs towards vaccination against COVID-19 based on sex. MethodsBetween February and May 2022, PLWH across Canada were recruited via social media and community-based organizations to complete an online survey consisting of a modified Vaccine Hesitancy Scale (VHS) questionnaire with items from the National Advisory Committee on Immunization Acceptability Matrix. Descriptive statistics were used to summarize participant characteristics and responses to the VHS questionnaire by biological sex. The effect of biological sex on total VHS score, two subscales (“lack of confidence” and “perceived risk”) was assessed separately by linear regression adjusting for other key baseline variables. ResultsOf 259 PLWH, 69 (27 %) were females and 189 (73 %) were males. Sixty-six (26 %) of participants self-identified as a woman, 163(63 %) as a man and 28(11 %) as trans/two-spirited/queer/non-binary/agender/other. The mean age (SD) was 47 ± 14 years. Females were less likely to believe that COVID-19 vaccination was: important for his/her own health (71 % vs. 86 %); a good way to protect themselves from infection (68 % vs. 86 %); that getting the COVID-19 vaccine was important for the health of others in his/her community (78 % vs. 91 %); believed recommendations by their doctor/health care provider about COVID-19 vaccines (78 % vs. 88 %); that information about COVID-19 vaccines from public health officials was reliable and trustworthy (56 % vs. 75 % vs); COVID-19 vaccines are effective in preventing COVID-19 infections (61 % vs. 82 %) and that all COVID-19 vaccines offered by government programs in their communities were important for good health (70 % vs. 87 %). Although more males than females felt that new vaccines generally carry more risks than older vaccines (19 % vs 16 %,), fewer males than females endorsed concern about serious side effects of COVID-19 vaccines (33 % vs 45 %).The linear regression model showed females had a significantly higher VHS total score than males (adjusted mean difference 0.38; 95 % confidence interval (CI) 0.13–0.64; p = 0.004), indicating greater COVID-19 vaccine hesitancy among females. It was observed that females had a greater “lack of confidence in vaccines” score than males (adjusted mean difference 0.43; 95 % CI 0.14–0.73; p = 0.004). We did not observe a significant difference in “perceived risk in vaccines” between males and females (adjusted mean difference 0.20; 95 % CI −0.07–0.46; p = 0.1). The inadequate number of participants self-identifying as different from biological sex at birth prevented us from analyzing the VHS score based on gender identity. ConclusionsAmong PLWH, females showed greater COVID-19 vaccine hesitancy than males. Specifically, compared with males, females had a higher level of lack of confidence in vaccines. Fewer females than males believed that COVID-19 vaccines had health benefits at both the personal and societal level and that recommendations made by their doctor/health care provider and public health officials are reliable and trustworthy. Further investigation into reasons for this difference in opinion still needs to be elucidated. Educational interventions targeted toward females living with HIV are especially needed to increase confidence in vaccination.

Amplification‐free sub-femtomolar monitoring of SARS-CoV-2-RNA in serum samples using cDNA-modified MoS2 field-effect transistor

The rapid spread of infectious diseases, exemplified by the well-known case of COVID-19, which has led to a global pandemic, has garnered increasing attention toward the development of simple and efficient biosensors for diagnosis. In this study, a field-effect transistor (FET)-based biosensor offers an alternative and promising solution for the diagnosis of clinical COVID-19. Molybdenum disulfide (MoS2) in a channel FET modified with a probe complementary DNA (cDNA) can sensitively detect selected specific sequences from SARS-CoV-2 through hybridization. MoS2 was modified with probe cDNA and exhibited a linear concentration range of 1 fM to 0.1 nM in both phosphate-buffered saline (PBS) and serum samples, with low limits of detection (LOD) of 0.21 and 0.73 fM, respectively. In addition, it demonstrated a rapid response time of 3 min in clinical samples. The developed biosensor is capable of analyzing RNA from 19 clinical samples. These results indicate that the biosensor successfully distinguished between healthy and infected samples, which is consistent with the RT-PCR results (kappa coefficient = 1). Additionally, a notable difference was observed between the RdRp samples of SARS-CoV-2 and SARS-CoV. Therefore, we believe that this study offers a reliable and appealing option for the diagnosis of COVID-19.

COVID-19 hand hygiene practices and its barriers among health care workers in a low-resource setting: a cross-sectional study in Nigeria

Abstract Background Poor hand hygiene (HH) among health care workers (HCWs) in low-resource healthcare settings has continued to increase the spread of infectious diseases, including COVID-19. The present study aimed to assess the knowledge, attitude, adherence, and barriers to HH practices among HCWs during the COVID-19 pandemic in Nigeria. Methods The study was an online cross-sectional survey using a tailored questionnaire distributed through chain referral sampling among southern Nigerian HCWs during the first wave of the COVID-19 pandemic (February to August 2020). The primary outcomes were knowledge, attitude, adherence to HH guidelines, and the barriers limiting compliance with the guidelines. Data were analysed using percentage, frequency, mean, standard deviation, one-way ANOVA, and multiple linear regression. The study timeline was from 15 April to 31 July 2020. Results Four hundred and fifty-four HCWs (236 males and 218 females) participated in the study. The participants had a moderate knowledge of standard HH protocol (mean ± SD) 62.45 ± 10.82%, positive attitude 84.34 ± 11.32%, and high adherence to the standard guidelines 81.21 ± 9.49%. There was no significant difference in knowledge, attitude, and adherence across the healthcare professions. Increasing age (β = 0.186, p < 0.003) and knowledge (β = 0.229, p < 0.001), and decreasing negligence (β = − 0.178, p = 0.004), and forgetfulness (β = − 0.159, p = 0.012) were the significant predictors of effective HH practices. Conclusion Nigerian HCWs had moderate knowledge, a positive attitude, and adhered to the standard HH practices during the COVID-19 pandemic. However, the major barriers were institutional-based factors such as the inadequate supply of HH items, competing job demands, emergencies, increased workload, and personal characteristics such as age, poor knowledge, negligence, and forgetfulness. We recommend that hospital management provide their staff with adequate HH materials and continued infectious disease training.

The Relationship Between Individual Characteristics, Religius, And Social Support And Infectious Disease Prevention Behaviors In Islamic Boarding School “X”, 2022

Background: Islamic boarding schools are places that have a high risk of spreading infectious diseases. This can be caused because Islamic boarding schools have very dense housing and low cleanliness in the Islamic boarding school environment. Objective: To determine the relationship between individual characteristics, social support and religiosity with infectious disease prevention behavior at the Al-Kahfi Integrated Islamic Boarding School in 2022. Method: This research uses quantitative research methods with a cross-sectional study design , the number of respondents in this study was 116 respondents, and the sampling technique used in this research was simple random sampling. The data analysis carried out was univariate analysis and bivariate analysis using the chi-square test and OR value. Results: It is known that of the total respondents, only 50% of respondents had good behavior. Of all the variables studied, only gender and knowledge variables did not have a significant relationship with infectious disease prevention behavior. In the attitude variable (p=0.015), religiosity (p=0.016), peer support (p=0.09), support from ustadz or uztadzah (p=0.016) have a significant relationship to infectious disease prevention behavior at the Al Al Integrated Islamic Boarding School -Kahfi. Conclusion: There are several research variables that have a significant relationship with infectious disease prevention behavior at the Al-Kahfi Integrated Islamic Boarding School, including attitude, religiosity, peer support, and support from ustadz or ustadzah. Suggestion: Managers at the Al-Kahfi Integrated Islamic Boarding School can maximize the facilities available in an effort to prevent infectious diseases, such as providing nutritious food for students, creating regular joint sports programs, creating award programs and carrying out punishments for students who violate agae motivating students to prevent infectious diseases in the Islamic boarding school environment.

The Forecasting of the Spread of Infectious Diseases Based on Conditional Generative Adversarial Networks

New epidemics encourage the development of new mathematical models of the spread and forecasting of infectious diseases. Statistical epidemiology data are characterized by incomplete and inexact time series, which leads to an unstable and non-unique forecasting of infectious diseases. In this paper, a model of a conditional generative adversarial neural network (CGAN) for modeling and forecasting COVID-19 in St. Petersburg is constructed. It takes 20 processed historical statistics as a condition and is based on the solution of the minimax problem. The CGAN builds a short-term forecast of the number of newly diagnosed COVID-19 cases in the region for 5 days ahead. The CGAN approach allows modeling the distribution of statistical data, which allows obtaining the required amount of training data from the resulting distribution. When comparing the forecasting results with the classical differential SEIR-HCD model and a recurrent neural network with the same input parameters, it was shown that the forecast errors of all three models are in the same range. It is shown that the prediction error of the bagging model based on three models is lower than the results of each model separately.

Guardians of health: School nurses and their leadership roles in the fight against the COVID-19 pandemic in education<sup></sup>

This study investigated school health nurses’ critical role and importance in managing infectious diseases during the COVID-19 pandemic. The pandemic has had negative impacts on schools and educational institutions. In light of these impacts, the assistance of school health nurses in overcoming difficulties in accessing health services for students and their families was examined globally. The study aimed to explore the status of school nursing practices in various countries in response to the challenges posed by the COVID-19 pandemic, assess the situation in Turkey, and examine how these nurses contribute to health management in educational settings. To identify pertinent literature, relevant publications were reviewed using key terms such as ‘school nursing,’ ‘infectious disease management,’ ‘COVID-19,’ ‘safe school,’ and ‘public health’. The search focused on studies analysing the role of school health nurses during the pandemic. Sources included academic databases, public health reports, and public health organisation publications. Due to the lack of precise data on the employment of school health nurses in Turkey, specific information on their role during the pandemic could not be found. However, the relevant literature was comprehensively reviewed, and the study analysed global publications highlighting the critical role of school nurses in managing infectious diseases in educational settings. The study highlights that school health nurses play significant roles in preventing and controlling communicable diseases and contribute notably to health education for students and staff during the pandemic. School health nurses protect children and adolescents’ physical, psychological, and spiritual well-being. Findings suggest that structural changes in health and education systems are needed to enhance the effectiveness of school nurses. This study underscores the critical importance of school health nurses in pandemic management and public health protection. Strengthening their role is vital for preventing the spread of infectious diseases in schools and ensuring the well-being of students. Recommendations include increasing the employment of school health nurses, improving their professional development, and integrating their expertise into pandemic management strategies.

A Stochastic Approach in the Analysis of Compartmental Models in Epidemiology

The spread of infectious diseases is a significant public health issue. Mathematical modeling is being used to find appropriate answers to this question. In this paper we propose a stochastic approach to compartmental models. A new model allows to rely on the fokker-planck equation with a SEIR model, with constant rates, to take into account the random environment in the propagation of a disease, markov and kolmogorov properties have been used in the modeling of the process. We have also determined the basic reproduction rate R0 of our new stochastic model using the new generation matrix.

Social networks and COVID-19 vaccination intention in Dutch middle-aged and older adults in 2020: Insights into individual, interpersonal, community, and societal determinants – The SaNAE study

BackgroundSocial networks, our social relationships, influence the spread of infectious diseases and preventive behaviors such as vaccination. Here, we aimed to assess which individual, interpersonal (social network characteristics), community and societal factors are associated with coronavirus disease 2019 (COVID-19) vaccination intention during the second wave of the COVID-19 pandemic in 2020, prior to vaccine availability. MethodsThis cross-sectional study collected primary data from 5,001 community-dwelling adults aged 40 years and older in the Netherlands, using an online questionnaire from August and November 2020. COVID-19 vaccination intention was measured by assessing whether respondents were willing to receive a COVID-19 vaccination if the vaccines became available. Associations between individual (sociodemographic variables, health, health concerns), interpersonal (social network characteristics including structure, function, and quality), community (social and labor participation) and societal factors (degree of urbanization), and the outcome variables COVID-19 vaccination intention (yes vs no, yes vs unsure, unsure vs no) were assessed in stepwise multivariable logistic regression analyses. p-values < 0.05 indicated statistical significance. ResultsAmong participants (N = 3,396), 59 % reported a positive intention to vaccinate, 35 % were unsure, and 6 % had no intention. Men, individuals of older age, those with a college or university degree, those concerned about their personal and family health, and knowledge about protecting oneself from the virus were more likely to have the intention to vaccinate (versus no intention). Interpersonal factors associated included having a larger network size (social network structure) and a larger proportion of informational supporters (social network function). Living outside of urban areas, a societal factor, was associated with vaccination intention (versus no intention). ConclusionThis study identified key factors influencing COVID-19 vaccination intention. Health promotion efforts should address not only individual factors but also incorporate the social environment. Our findings highlight the importance of organizing social networks to mobilize social support for pandemic preparedness.

Bioaerosol Inactivation by a Cold Plasma Ionizer Coupled with an Electrostatic Precipitator.

Despite best efforts in air purification, airborne infectious diseases will continue to spread due to the continuous emission of bioaerosols by the host/infected person. Hence, a shift in focus from air purification to bioaerosol inactivation is urgently needed. To explore the potential of the cold plasma technology for preventing rapid spread of airborne infectious diseases, we studied a cold plasma ionizer (CPI) device and an electrostatic precipitator (ESP)-coupled CPI (CPI-ESP) device for the inactivation and cleaning of surface-spread microorganisms and bioaerosols, using porcine respiratory coronavirus (PRCV), Escherichia coli (E. coli), and aerosolized E. coli as representatives. We firstly demonstrated that CPI coupled with ESP is an effective technology for inactivating virus and bacteria spread on surfaces in an in-house test chamber. We then demonstrated the efficacy of CPI-coupled ESP for the inactivation of aerosolized E. coli in the same chamber. Furthermore, we have demonstrated the efficiency of a CPI-ESP coupled device for the inactivation of naturally occurring airborne microbials in a few indoor settings (i.e., a living room, a discussion room, a schoolroom, and an office) to determine the treatment duration- and human activity-dependent efficacy. To understand the disinfection mechanism, we conducted a fluorescence microscopy study to reveal different degrees of E. coli bacteria cell membrane damage under CPI treatment.

SIR models with vital dynamics, reinfection, and randomness to investigate the spread of infectious diseases

We investigate SIR models with vital dynamics, reinfection, and randomness at the transmission coefficient and recruitment rate. Initially, we conduct an extensive analysis of the autonomous scenario, covering aspects such as local and global well-posedness, the existence and internal structure of attractors, and the presence of gradient dynamics. Subsequently, we explore the implications of small nonautonomous random perturbations, establishing the continuity of attractors and ensuring their topological structural stability. Additionally, we study scenarios in which both the transmission coefficient and the recruitment rate exhibit time-dependent or random behavior. For each scenario, we establish the existence of attractors and delineate conditions that determine whether the disease is eradicated or reaches an endemic state. Finally, we depict numerical simulations to illustrate the theoretical results.

Experimental and numerical study on upper-room Far-UVC system under different ventilation schemes to disinfect airborne microorganisms in indoor environments

Many deadly infectious diseases are transmitted through airborne routes in indoor environments. Far UV upper-room system combined with proper ventilation is regarded as an effective approach to disinfect airborne microorganisms. Despite the current advances in the far UV upper-room system, various types of data are still lacking to guide the efficient design and the safe operation. This study combines field air sampling, laboratory experiments and computational fluid dynamics simulations to advance the knowledge on the potential of far UV radiation for disinfection and its safety design. Our findings reveal that seven out of the eight measured room spaces are categorised as slightly polluted (1201–2000 CFU m−3) or polluted (>2000 CFU m−3). Proteobacteria and Firmicutes constitute 65.2 ± 10.6 % and 21.2 ± 5.68 % of the bacterial composition in congregate settings, respectively. Ultraviolet radiation proves effective in deactivating pathogenic microorganisms, characterized by a decay rate constant ranging from 0.0446 m2 J−1 to 0.464 m2 J−1, depending on the wavelength and the type of pathogenic microorganisms. The time response of Ultraviolet radiation is up to 12 min to achieve 92.1 % sterilisation. Despite the reduction in the sterilisation ratio of Ultraviolet radiation, maintaining a high ventilation rate is highly recommended to eliminate genetic material from pathogenic microorganisms. When the excimer lamp is installed higher than 1.9 m above the floor level, the radiation intensities at both standing and sitting height become lower than the safety threshold value of 0.166 W m−2. A combination of UV radiation at 222 nm and ventilation is effective for neutralising both gram-positive and -negative bacteria and can contribute to stop the spread of infectious diseases in congregate settings.

PROBLEMS OF MANAGING THE IMMUNE RESPONSE UNDER CONDITIONS OF COMPETITIVE ADSORPTION, DIFFUSION PERTURBATIONS AND TEMPERATURE RESPONSE OF THE ORGANISM

Analysis of the problems associated with the rapid spread of infectious diseases indicates the need for new approaches to the diagnosis and develop- ment of effective personalized treatment programs. One of the important aspects of solving this problem is the creation of a mathematical modeling toolkit for predicting the dynamics of infectious diseases, taking into account spatial effects, concentrated effects, various mechanisms of body protec- tion in the conditions of the application of various types of therapeutic methods of treatment. An important component of complex methods of treat- ment of a wide range of infectious diseases is the use of adsorption drugs, which, along with detoxification of the body, are able to provide an addi- tional mechanism of neutralization of viral elements. In the process of using such means, not only pathogenic elements and toxins will be adsorbed, but also various types of immune agents, which will affect the dynamics of the immune response. In the paper the infectious disease model is generalized to take into account the features of competitive adsorption of antigens and immune agents in the conditions of diffusion perturbations, concentrated influences and temperature reaction of the body. By synthesizing the ideas of step-by-step procedures, asymptotic and numerical methods, an effective computational technology of step-by-step approximation of the solution of the original model singularly perturbed problem was built. The results of the computer experiments presented in the paper illustrate the features of reducing the predicted concentration of viral elements during their competi- tive adsorption together with immune agents, in particular, the effect of reducing the efficiency of the use of non-specific adsorbents. It is emphasized that taking into account the features of the action of competitive adsorption is important for making decisions regarding the formation of rational treatment programs with the complex use of adsorbing substances and immunological drugs.

История эпидемий в России: от чумы до Covid-19

The article provides a historical review of the epidemics that swept Russia from the Middle Ages to the present day, spanning from the plague to the coronavirus. It presents detailed information on the primary measures taken by government officials, medical personnel, and public organizations to counteract the spread of infec-tious diseases. The article examines the causes, prevention strategies, and consequences of these epidemics, analyzing the factors that influenced the scale and spread of diseases. The analysis of scientific literature and historical documents reveals how societal development was impacted by the spread of infections and the high mortality rates, as well as how medical practices and treatment methods for various diseases have evolved over time. Conclusion dwells upon the fact that the experience of past epidemics has played a crucial role in humanity's ongoing battle against many illnesses and has significantly altered perceptions regarding the im-portance of preventive measures during epidemics.

A Modified SIVR Mathematical Model of Covid-19 Post-vaccination Stability Analysis in Kenya

In this paper, the study focused on carrying out a stability analysis on a modified SIR model for the COVID-19 pandemic for the period after vaccination in Kenya. The purpose of the work was to show that whereas the rate and the extent of disease spread amongst the Kenyan people was not as wide spread as happened in other parts of the world, it was necessary for government and policy makers to roll out a robust civic education to convince the majority of the Kenyan population to embrace vaccination as a major containment measure in curbing the spread of COVID-19 and other infectious diseases since the study revealed that the infections drastically reduced to near zero after vaccination except for a few isolated cases that were and still continue to exhibit mild symptoms to none at all. This was attributed to the development of the vaccine which upon a massive campaign by the Kenyan government, led into a significant portion of the population being vaccinated. It is believed this vaccination drive enhanced herd immunity amongst the population. This development has had a significant effect in the control of more recent COVID-19 variants like JN-1 that have remained largely mild and undetected in the country. Both local and global post vaccination stabilities were analyzed for the system using the Lyapunov function. The main objective of the study was therefore to carry out a post vaccination stability analysis by estimating key parameters such as the basic reproduction number, ( R0) and herd immunity threshold (HIT) for infectious diseases by fitting data into the model to enable predictions of future dynamics of the disease. The study used the Next Generation matrix and the least square method besides the Python software to solve generated differential equations of the model for and HIT parameters. Results obtained showed that, there was a significant reduction in infections due to enhanced herd immunity attributed largely to the roll out of vaccination.

Infectious diseases and global security: Analysis of global control and vaccination strategies

Introduction: Given the recent experience with the COVID-19 vaccine campaign, an optimal global policy to control future pandemics and ensure infectious security globally is highly relevant. Objective: The study aims to determine the optimal vaccination strategy to reduce COVID-19 morbidity and mortality during a pandemic.Methods: A systematic search of studies on infectious disease control and vaccination strategies for the period 2000-2023 in PubMed, Scopus, Web of Science and Google Scholar databases using keywords was conducted for the review. Relevant publications, data extraction and systematisation were selected.Results: The findings of the analysis highlight the importance of integrated interventions in global vaccination strategies, including health systems strengthening, innovative technologies for outbreak detection and international collaboration. Vaccination, as an effective preventive measure, significantly reduces the spread of infectious diseases. Vaccination with different types of vaccines has been shown to improve immune response compared to the use of the same type of vaccine. This approach, where the first and second vaccine doses are different, may increase the effectiveness of the immune response.Conclusions: Studies confirm that vaccination reduces the number of cases and deaths, reducing the economic burden. A variety of vaccines, including mRNA, vector, and inactivated vaccines, provide high efficacy in preventing COVID-19 infection and mortality, especially when a heterologous vaccination regimen is used. This review identifies the most effective infectious disease control strategies for the development of global health recommendations

Global pandemic governance: A multilevel concept for managing pandemic crises worldwide

This article examines how countries can effectively respond to global health pandemics in six stages. Previous research has assumed that human social and economic activities affect the spread of viral infectious diseases, and it has been noted that countries fight global pandemics independently, making the response inefficient. As no comprehensive governing guidelines exist for managing global public health pandemics, this article argues for the need for an international, integrated governance framework, offering theoretical reflections on a novel integrated, multilevel governance concept, the Global Governance of Pandemic Crises (GGPC), which is centered around crisis management theory at an international level. The article differentiates four pandemic governance processes—risk, emergence, recovery, and goal governance—in six pandemic periods that are linked to different processes of public health pandemic governance. The GGPC concept may prove useful to organisations responsible for governing pandemics and implementing relevant measures in affected countries.