Spread Of Infectious Diseases Research Articles

Leveraging 4-H to Address Emergent Health Needs during the Covid-19 Pandemic: Epidemiology Pilot Project

4-H academics responded to the Covid pandemic by rapidly adapting CDC and other resources for virtual delivery. A statewide epidemiology project was taught to 48 youth with the goal of minimizing fears and confusion, increasing prevention measures, leveraging current topics for education, and bolstering the social-emotional health of youth participants. Results indicated that youth enjoyed the project and adopted behaviors to reduce the spread of infectious diseases, such as increased mask-wearing.

Vaccination strategies in the disease–behavior evolution model

Previous studies on the co-evolving between vaccination strategies and epidemics mainly assumed that the vaccination strategies were made in the period between two spreading seasons. However, individual cognition during the spreading seasons might also alter the vaccination strategy and inversely influence the epidemic spreading. We propose a coupled disease–behavior model to describe the dynamic evolution of vaccination behavior during the spread of infectious diseases. The model integrates a susceptible–infected–vaccinated (SIV) model with the diffusion of vaccination behavior. We focus on the trade-off between perceptions of infection risk and the vaccination behaviors of neighbors, characterizing individual vaccination opinions. We introduce an opinion-critical value to map vaccination opinions into vaccination behavior. The vaccination coverage of the disease–behavior model is studied in network models and real-world networks. In addition, when societal costs are measured based on the degree of initial vaccinees, the cost of randomly selecting initial vaccinees is lower than selecting individuals with high or low degrees as vaccinees. Evaluating an individual’s ability to transmit vaccination behavior based on the neighbor’s number is inappropriate. We find that the impact of effective spreading rates on group vaccination is not one-sided and that reducing fear and highlighting the dangers of infectious diseases are crucial to increasing vaccination coverage.

Impact of the COVID-19 outbreak and interventions on hand, foot and mouth disease in Zhengzhou, China, 2014–2022: a retrospective study

BackgroundSince December 2019, COVID-19 has spread rapidly around the world, and studies have shown that measures to prevent COVID-19 can largely reduce the spread of other infectious diseases. This study explored the impact of the COVID-19 outbreak and interventions on the incidence of HFMD.MethodsWe gathered data on the prevalence of HFMD from the Children’s Hospital Affiliated to Zhengzhou University. An autoregressive integrated moving average model was constructed using HFMD incidence data from 2014 to 2019, the number of cases predicted from 2020 to 2022 was predicted, and the predicted values were compared with the actual measurements.ResultsFrom January 2014 to October 2022, the Children’s Hospital of Zhengzhou University admitted 103,995 children with HFMD. The average number of cases of HFMD from 2020 to 2022 was 4,946, a significant decrease from 14,859 cases from 2014 to 2019. We confirmed the best ARIMA (2,0,0) (1,1,0)12 model. From 2020 to 2022, the yearly number of cases decreased by 46.58%, 75.54%, and 66.16%, respectively, compared with the forecasted incidence. Trends in incidence across sexes and ages displayed patterns similar to those overall.ConclusionsThe COVID-19 outbreak and interventions reduced the incidence of HFMD compared to that before the outbreak. Strengthening public health interventions remains a priority in the prevention of HFMD.

Availability, storage, handling and administration of vaccines in community pharmacies: Southwest Nigeria as a case study

Background: Vaccines have been instrumental in thwarting the spread of infectious diseases and have been a major public health success. Community pharmacies are a critical resource for success of any immunization programme. However, pharmacists’ involvement in immunization programme in Nigeria has not been thoroughly investigated. This study assessed the involvement of pharmacists in immunization services.Methodology: A cross-sectional survey was conducted among community pharmacists, using a structured pre-tested questionnaire. The survey tool, which consisted of 72-item questions spread over five different domains, assessed vaccine availability in community pharmacies and pharmacist’s knowledge on vaccine. This (knowledge) addresses vaccine handling and administration as well as storage. The questionnaire was administered to selected community pharmacies by a combination of physical interview and electronic version through Google form link sent to pharmacist’s WhatsApp platform. Association between patients’ socio-demographics and some variables of interest was determined using Chi-square statistic.Result: One hundred and ninety-one (191) pharmacists responded to the questionnaire (99.5% response rate). About half, one hundred and three (53.93%) of the respondents were aged between 31 and 50 years. One hundred and twenty-nine (67.54%) of the pharmacists had B.Pharm degree as the highest level of education. There was a significant association between pharmacists’ age (χ2 = 30.5, p<0.01), years of experience (χ2 = 25.9, p<0.01), level of education (χ2 = 19.6, p<0.05) and knowledge on vaccine handling and administration. Also, significant association (p<0.01) existed between pharmacists’ age (χ2 = 45.1), years of experience (χ2 = 45.3), level of education (χ2 = 31.6) and knowledge of vaccine storage. Furthermore, there was a significant association (p<0.01) between being trained as a vaccine administrator and level of knowledge on vaccine storage (χ2 = 57.8) as well as handling and administration (χ2 = 45.2).Conclusion: Pharmacists’ level of education and training (as vaccine administrator) were key factors in pharmacists’ involvement in immunization care service.

Evaluation of the spatial distribution of aerosols produced by various respiratory activities

This study investigated the dispersion and evaporation characteristics of droplets and droplet nuclei emitted during human respiratory activities. A specially designed wind tunnel was filled with purified air, wherein selected subjects performed various respiratory activities with their heads positioned inside. An optical particle sizer was used to collect particles with sizes of 0.3–10 μm at 63 points in front of the mouth. The dilution factors were analyzed to investigate the impact of combining the exhaled airflow with ambient air on droplet evaporation. At a distance of 0.01 m from the mouth opening, the volume concentration of the particles was the highest during breathing, followed by coughing and speaking. The volumetric concentration of particles decreased with an increase in the distance from the inlet for all activities. The spatial volume concentration distribution of particles showed that coughing tended to disperse the particles in the forward direction, whereas speaking tended to disperse them laterally. Utilizing these findings in CFD analysis can provide in-depth insights into dispersion and evaporation dynamics. This can contribute significantly to the development of preventive measures through the implementation of proactive HVAC systems to effectively remove infectious particles and control the spread of infectious diseases. Future studies should explore a wider range of particle sizes and advanced sampling techniques for a clear understanding of respiratory particle dynamics and infection control strategies.

Hand Washing Practice among Secondary School Students in a Rural Area of Bangladesh

Background: Human hands play a significant role in the spread of diseases, especially respiratory and diarrheal diseases, which continue to be the leading cause of morbidity and mortality among children worldwide. Hand washing is the most widely used preventive measure to lessen the spread of infectious diseases. It involves washing hands with ordinary or antimicrobial soap and water.  This is especially important for school-age children, since they may be more susceptible to diseases associated with poor hygiene than adults’ age. There is evidence linking the promotion of hand washing habits through health education to a lower incidence of communicable diseases in school-age children. Objectives: To determine the socio-demographic characteristics of the respondents and to find out the practice of hand washing among the secondary school children. Materials & Methods: A cross sectional study was conducted on 340 school students from 1st June 2022 to 30th November 2022 in Alekjan Memorial High School and College, Durgapur, Adarsha Sadar, Cumilla. Purposive sampling was used to gather all pertinent data using a structured questionnaire. Results: In schools, 69.7% of the respondents washed their hands properly. 96.7% of them used soap to wash their hands. About 98.2%, 95%, 86.8%, 82.9% and 80.3% of school children reported that they wash their hands before eating, after using the restroom, after eating, after playing and after working. Conclusion: According to the study, having access to soap and water is necessary for good hand washing technique as the majority of the students used   soap during hand washing.  By installing hand washing stations in schools, the regional government, that is, the education and health bureaus-should enhance the hand washing practices in schools. It is important for parents and other family members to focus more on behavior guidance related to hand washing. Eastern Med Coll J. July 2023; 8 (2): 40-44

INFLUENCE OF THE ENVIRONMENT ON HUMAN HEALTH AND QUALITY OF LIFE (ON THE EXAMPLE OF THE GREATER CAUCASUS OF THE REPUBLIC OF AZERBAIJAN)

Health occupies an important place in the system of indicators determining the quality of life. Issues of improving health indicators are especially relevant for the Greater Caucasus province, which plays an important role in the socio-economic development of the Azerbaijan Republic and has a high standard of living, demographic and labor potential. The territorial organization of health care in the Greater Caucasus province, environmental peculiarities and their impact on the quality of life have been studied. On the basis of statistical materials the indicators of disease spread among the population living in the region are studied. Atmospheric air pollution is mainly responsible for the spread of infectious diseases, so the relationship between them has been studied. The relationship between the human development index and the environment and its impact on the quality of life has been studied. It is found that the amount of waste from stationary sources in the region has decreased. Air pollution directly affects the health of the population. Thus, the low amount of waste emitted into the atmosphere corresponds to high values of the Human Development Index. More precisely, the correlation between them is negative, and the coefficient of determination is equal to 0.857, i.e. the dependence is determined at the level of 85%.

Children's experiences of mask-wearing: a systemic review and narrative synthesis.

Masks have been widely used as a preventative tool during the COVID-19 pandemic. However, the use of masks by children has been controversial, with international guidelines recommending a risk-based approach to national policymakers. We aimed to conduct a systematic review that explores children's experiences of mask-wearing, drawing on an evidence base that describes mask-wearing in different contexts including air pollution, and to prevent the spread of infectious disease. We searched MEDLINE, Embase and PsycINFO in June 2021, with repeat searches in August 2022 and January 2024, for primary research studies exploring children's experiences of masks. Included studies reported on participants between 4 and 14 years (inclusive), with no restrictions on language where an English translation was available. Two reviewers independently screened titles and abstracts and reviewed full texts, with discrepancies resolved by a third reviewer. We used the Mixed Methods Appraisal Tool for quality appraisal and narrative synthesis to identify key findings. We also conducted stakeholder consultation (Patient and Public Involvement (PPI)) with nine children, where they submitted annotated drawings of their preferred masks to complement our review findings. We screened 982 titles and abstracts and reviewed 94 full texts. 45 studies were included in the synthesis. Children's experiences of mask-wearing were influenced by their perceived necessity, social norms around their use and parental attitudes. Challenges related to mask-wearing were described, including difficulty reading facial expressions and physical discomfort. Children found it easier to wear masks when sitting and in cooler environments, and they benefited from unmasking during outdoor break time at school. As part of the PPI consultation, children highlighted the importance of mask design and the environmental impact of masks. Children's experiences of mask-wearing were varied and context-dependent, with several mask-design challenges raised. Future policy on mask-wearing needs to consider the context in which mask-wearing would be most beneficial, and how local adaptations to policy can respond to children's needs.

Environmental Sanitation in Porto Alegre City, Brazil: A Basic Step towards Sustainable Development

Porto Alegre city, the capital of Rio Grande do Sul State, is an important medical, educational, and technological hub in Brazil. However, Porto Alegre faces critical challenges in achieving adequate environmental sanitation, hampering the development of the city, and negatively impacting the most socially vulnerable segments of the population. Although Porto Alegre’s sanitation plan aims at universal access to sewage collection and treatment services by 2035, some of the city’s sanitation indicators have deteriorated in recent years compared to other Brazilian cities. The inadequate or lack of proper sanitation (e.g., shortcomings in sewage collection and treatment, suboptimal management of solid waste, deficiencies in the distribution of treated water) contribute to the proliferation of disease vectors like mosquitoes and to the spread of infectious and parasitic diseases (e.g., toxoplasmosis, leishmaniasis, arboviral diseases). Recently, Porto Alegre’s population experienced a significant number of dengue infection cases. Climate change, social issues, and unplanned urbanization will further favor disease transmission in the region. In this Review, we provide an overview concerning the ecological, socio-economic, and public health aspects of Porto Alegre, drawing attention to the insufficient environmental sanitation in the city, a neglected problem by local authorities. We argue that this issue needs to be seriously addressed if Porto Alegre wants to realistically achieve sustainable development, protecting ecosystems and human health.

Effect of the COVID-19 Pandemic on Rotavirus Infection Frequency in Children

Aims: During the COVID-19 pandemic, measures such as the wearing of masks, social distancing, enhanced hygiene practices, closures of workplaces and schools, and lockdowns influenced the spread of various infectious diseases. This study aimed to compare the frequency of rotavirus infections during the pandemic to that of the pre-pandemic period.
 Methods: This retrospective study included 2912 patients diagnosed with acute gastroenteritis who were admitted to the Pediatric Health and Diseases Department of Hisar Intercontinental Hospital between January 2018 and August 2022. For the diagnosis of rotavirus infection, the Rota-Adeno Ag Rapid Test-Cassette was applied to stool samples as an immunochromatographic method. Patients were divided into two groups based on their hospital admission dates: before the COVID-19 pandemic (1 January 2018 to 10 March 2020) and during the COVID-19 pandemic (11 March 2020 to 30 August 2022).
 Results: The prevalence of rotavirus infection in the entire population was 9.5% (n=277). The rate of cases of rotavirus infection was higher among patients during the COVID-19 pandemic compared to the group of patients before the COVID-19 pandemic (10.9% vs. 8.7%, p=0.050). A sharp decline in the frequency of rotavirus infection was observed at the beginning of the COVID-19 pandemic compared to the pre-COVID-19 pandemic period, followed by a sharp increase. In 2022, the frequency of rotavirus infections exceeded the pre-COVID-19 pandemic levels.
 Conclusion: The provision of the rotavirus vaccine for free by health authorities, especially for at-risk infants, together with adherence to hand washing, hygiene, and sanitation rules can significantly reduce the frequency of rotavirus infections during both pandemic and non-pandemic periods.

SNN-PDE: Learning Dynamic PDEs from Data with Simplicial Neural Networks

Dynamics of many complex systems, from weather and climate to spread of infectious diseases, can be described by partial differential equations (PDEs). Such PDEs involve unknown function(s), partial derivatives, and typically multiple independent variables. The traditional numerical methods for solving PDEs assume that the data are observed on a regular grid. However, in many applications, for example, weather and air pollution monitoring delivered by the arbitrary located weather stations of the National Weather Services, data records are irregularly spaced. Furthermore, in problems involving prediction analytics such as forecasting wildfire smoke plumes, the primary focus may be on a set of irregular locations associated with urban development. In recent years, deep learning (DL) methods and, in particular, graph neural networks (GNNs) have emerged as a new promising tool that can complement traditional PDE solvers in scenarios of the irregular spaced data, contributing to the newest research trend of physics informed machine learning (PIML). However, most existing PIML methods tend to be limited in their ability to describe higher dimensional structural properties exhibited by real world phenomena, especially, ones that live on manifolds. To address this fundamental challenge, we bring the elements of the Hodge theory and, in particular, simplicial convolution defined on the Hodge Laplacian to the emerging nexus of DL and PDEs. In contrast to conventional Laplacian and the associated convolution operation, the simplicial convolution allows us to rigorously describe diffusion across higher order structures and to better approximate the complex underlying topology and geometry of the data. The new approach, Simplicial Neural Networks for Partial Differential Equations (SNN PDE) offers a computationally efficient yet effective solution for time dependent PDEs. Our studies of a broad range of synthetic data and wildfire processes demonstrate that SNN PDE improves upon state of the art baselines in handling unstructured grids and irregular time intervals of complex physical systems and offers competitive forecasting capabilities for weather and air quality forecasting.

Water-in-oil adjuvant challenges in fish vaccination: An experimental inactivated adjuvanted vaccine against betanodavirus infection in Senegalese sole.

The extensive growth of intensive fish farming has led to a massive spread of infectious diseases. Nervous necrosis virus (NNV) is the causative agent of the viral encephalo- and retinopathy disease which has become a major threat for fish farming all over the globe. The devastating mortality rates recorded in disease outbreaks, especially when infected specimens are at early stages of development, have a high economic impact on the sector. Currently, vaccines are the most cost-effective preventing tool in the fight against viruses. Inactivated vaccines have the advantage of simplicity in their development at the same time as present the antigen in a similar manner than the natural infection in the host. Nevertheless, they usually trigger weaker immune responses needing adjuvants to boost their effectiveness. In this work, we have intraperitoneally vaccinated Senegalese sole juveniles (Solea senegalensis) with a previously designed inactivated vaccine against NNV based on binary ethylenimine (BEI), mixed or not with an oil-adjuvant. Our results demonstrated the potential activation of different immune pathways when the vaccine was administered alone compared to the oil-adjuvanted vaccine, both resulting in an equivalent partial improvement in survival following a NNV challenge. However, whilst the vaccine alone led to a significant increase in specific antibodies, in the adjuvanted version those antibodies were kept basal although with a slight improvement in their neutralization capacity. At transcriptional level, neither vaccine (adjuvanted or not) triggered the immune system activation during the vaccination period. However, after NNV infection, the BEI-inactivated vaccines alone and oil-adjuvanted both elicited the stimulation of antiviral responsive genes (rtp3, herc4), antigen presentation molecules (mhcii) and T-cell markers (cd8a) in the head-kidney. Additionally, the oil-adjuvanted vaccine appears to stimulate mediator cytokines (il6) and B-cell markers (ight and ighm). Surprisingly, when the adjuvant was administered alone, fish showed the highest survival rates concomitantly with a lack of NNV-IgM production, pointing to the possible induction of different immune pathways than the B-cell responses via antibodies by the adjuvant. Since this combined vaccine did not succeed in the full extension of protection against the pathogen, further studies should be performed focusing on unravelling the molecular mechanisms through which adjuvants trigger the immune response, both independently and when added to a vaccine antigen.

Explosive epidemic transitions induced by quarantine fatigue

Quarantine measures are one of the first lines of defense against the spread of infectious diseases. However, maintaining these measures over extended periods can be challenging due to a phenomenon known as quarantine fatigue. In this paper, we investigate the impact of quarantine fatigue on the spread of infectious diseases by using an epidemic model on random networks with cliques. In our model, susceptible individuals can be quarantined up to n times, after which they stop complying with quarantine orders due to fatigue. Our results show that quarantine fatigue may induce a regime in which increasing the probability of detecting and isolating infected individuals (along with their close contacts) could subsequently increase the expected number of cases at the end of an outbreak. Moreover, we observe that quarantine fatigue can trigger an abrupt phase transition at the critical reproduction number R0=1. Finally, we explore a scenario where a non-negligible number of individuals are infected at the beginning of an epidemic, and our results show that, depending on the value of n, an abrupt transition between a controlled epidemic and a large epidemic event can occur for R0<1.

REAL-TIME FACE MASK DETECTION SYSTEM

In real-time face mask detection system developed using Python, TensorFlow, and Keras, designed to enhance public health safety during the COVID-19 pandemic. Leveraging computer vision techniques, the system detects faces in video streams and accurately classifies the presence and correct positioning of face masks. Green and red rectangular signs overlaying individuals' faces provide real-time feedback on mask compliance. The system's versatility enables seamless integration into various surveillance infrastructures, making it a practical solution for enforcing mask-wearing mandates in high-traffic public spaces. Its implementation using widely accessible libraries enhances its potential for widespread adoption, highlighting the role of technology in mitigating the spread of infectious diseases. Key Words: face mask detection, real-time, Python, TensorFlow, Keras, computer vision, machine learning, public health safety, COVID-19, surveillance.

Antibacterial performance of a copper nanoparticle thin film

AbstractThe prevalence of the SARS‐CoV‐2 virus has led to an increased focus on cleaning and disinfecting surfaces in the community and hospitals. An inherently antibacterial thin film is reported to combat the transmission of microbes on glass surfaces that could be accessed by the public, reducing the need for constant cleaning. The copper nanoparticle thin film is synthesized via a sol–gel method and deposited using a dip‐coater to create a transparent, rugged film resistant to scratching. The antibacterial performance is tested by a droplet and an aerosol deposition technique, where Escherichia coli and Staphylococcus aureus are sprayed directly onto the thin film, replicating coughs and sneezes: a common form of microbial transmission. The mechanism of antibacterial performance is studied by introducing reactive oxygen species quenchers to the thin film. This research presents copper nanoparticle thin films as an effective solution in reducing the transmission of microbes on glass surfaces and their potential as a valuable tool in preventing the spread of infectious diseases.

Disease X epidemic control using a stochastic model and a deterministic approximation: Performance comparison with and without parameter uncertainties

Background: The spread of infectious diseases can be modeled using deterministic or stochastic models. A deterministic approximation of a stochastic model can be appropriate under some conditions, but is unable to capture the discrete nature of populations. We look into the choice of a model from the perspective of decision making.Method: We consider an emerging disease (Disease X) in a closed population modeled by a stochastic SIR model or its deterministic approximation. The objective of the decision maker is to minimize the cumulative number of symptomatic infected-days over the course of the epidemic by picking a vaccination policy. We consider four decision making scenarios: based on the stochastic model or the deterministic model, and with or without parameter uncertainty. We also consider different sample sizes for uncertain parameter draws and stochastic model runs. We estimate the average performance of decision making in each scenario and for each sample size.Results: The model used for decision making has an influence on the picked policies. The best achievable performance is obtained with the stochastic model, knowing parameter values, and for a large sample size. For small sample sizes, the deterministic model can outperform the stochastic model due to stochastic effects. Resolving uncertainties may bring more benefit than switching to the stochastic model in our example.Conclusion: This article illustrates the interplay between the choice of a type of model, parameter uncertainties, and sample sizes. It points to issues to be considered when optimizing a stochastic model.

The Role of Seasonal Influenza in Compounding the Outbreak of Infectious Diseases: A Critical Review

Infectious diseases continue to pose a persistent threat to public health globally. Amidst the array of factors contributing to the complexity of infectious disease outbreaks, the role of seasonal influenza stands out as a significant amplifier. Seasonal influenza, commonly known as the flu, not only inflicts its burden on communities but also plays a crucial role in compounding the spread and impact of other infectious diseases. This review delves into the various ways in which seasonal influenza contributes to the complexity of infectious disease outbreaks. The role of seasonal influenza in compounding the outbreak of infectious diseases is a multifaceted challenge that demands attention from public health authorities worldwide. Addressing this compounding effect requires a holistic approach that encompasses vaccination campaigns, strengthened healthcare infrastructure, and improved diagnostic capabilities. By understanding and mitigating the various ways in which seasonal influenza contributes to the complexity of infectious disease outbreaks, communities can enhance their resilience and responsiveness in the face of evolving public health threats. Recognizing and understanding these dynamics is essential for designing effective public health strategies. By implementing comprehensive vaccination programs, improving diagnostic capabilities, and enhancing overall preparedness, communities can better navigate the complexities of infectious disease outbreaks exacerbated by the presence of seasonal influenza.

AI-Based Medical Chatbot for Disease Prediction By IJISRT

This research paper presents the development and implementation of an AI-based medical chatbot for disease prediction. Leveraging machine learning and artificial intelligence technologies, the chatbot utilizes natural language processing (NLP) to understand user queries and provide accurate information, guidance, and assistance for various infectious diseases. Motivated by the global spread of infectious diseases and the need for accessible healthcare support, the paper outlines the objectives, algorithm design, dataset description, and application of the chatbot. The algorithm involves receiving user input, extracting symptoms, classifying diseases, and suggesting prevention measures. The dataset, structured in JSON format, facilitates training and pattern recognition. The chatbot interface, accessible across platforms, offers information on symptoms, prevention measures, hospital bed availability, and medication options. In conclusion, the research highlights the potential of AI-based chatbots in revolutionizing healthcare accessibility and personalized diagnosis, thereby bridging the gap between users and healthcare systems.

100 Years of the American Public Health Association's Public Health Education and Health Promotion Section: Celebrating the Past, Forging the Future.

The American Public Health Association's Public Health Education and Health Promotion (APHA PHEHP) Section celebrates its 100th anniversary by reflecting on its humble beginnings and early contributions to the field of health education. This article highlights the often-unsung history of our field and its fledgling beginnings, which is important to scholars and students alike. First codified as the Health Education and Publicity Section in the early 1920s, we trace the history and challenges of using new modes of publicity such as motion pictures and innovative exhibits to help curb the spread of infectious diseases (e.g., tuberculosis, venereal disease). Evart G. Routzahn, credited as the Section's father, worked tirelessly to increase the Section's visibility (renamed the Health Education Section in 1927 and the Public Health Education and Health Promotion Section in 1990) and in advancing the professionalization of health education during a time when there were no formal professional preparation programs in health education. Over the years, the Section has played significant roles in strengthening the practice of health education and communication; advancing APHA's overall leadership, infrastructure, and governance; and contributing to the unified voice and advocacy for the health education profession and health equity. We conclude by describing contemporary initiatives that reflect the continued spirit and vibrancy of the Section in setting the stage for the next 100 years.

Approximate and Parametric Solutions to SIR Epidemic Model

This article provides a detailed exploration of the SIR epidemic model, starting with its meticulous formulation. The study employs a novel approach called the upper and lower bounds technique to approximate the solution to the SIR model, providing insights into the dynamic interplay between susceptible S, infected I, and recovered R populations. A new parametric solution to this model has been presented. Applying the Adomian decomposition method (ADM) allows for the attaining of highly accurate approximate solutions in the context of the SIR epidemic model. To validate the accuracy and robustness of the proposed approach, a numerical exploration is conducted, considering a diverse range of experimental parameters. This numerical analysis provides valuable insights into the sensitivity and responsiveness of the SIR epidemic model under varying conditions, contributing to the broader understanding of infectious disease dynamics. The interplay between theoretical formulation and numerical exploration establishes a comprehensive framework for studying the SIR model, with implications for refining our ability to predict and manage the spread of infectious diseases.