Life Threat Research Articles

Arduino Uno-based Brake Safety Design for Matic Motorcycles

Failed brakes are an event or damage to a motorized vehicle component that can cause an accident as well as be a life threat to the driver. There are several factors that can cause brake failure, including thin or worn brake pads, and clogged brake fluid hoses. The problem that often occurs is overheating in the brake system which causes brake failure (fading). Failed brake events are more common in hilly descent areas, these accidents make brake failure the second most common accident after driver negligence such as drowsiness. One of the efforts to prevent the failure of the brakes to occur is to make a brake safety system on an automatic Arduino Uno motorbike. The method applied includes planning, manufacturing, and testing of tools. This detector uses the DS18B20 sensor as input, Arduino uno as a microcontroller, 16 x 2 LCD as direct monitoring, and the output is an LED light and a buzzer. The working principle of this tool is that the temperature of the brake calipers has started to heat up, so the DS18B20 sensor works by generating data that will be displayed on the LCD, and when it reaches the temperature limit of 100 degrees Celsius at the same time the buzzer sounds and the LED light turns on and the water pump functions which will spray part of the system. braking. During the heating process, the temperature will be monitored via the LCD display on the vehicle. The test results of this tool will be affected by the hot temperature of the DS18B20 sensor.

Fabrication of a Chitosan-Based Wound Dressing Patch for Enhanced Antimicrobial, Hemostatic, and Wound Healing Application.

Wounds are a serious life threat that occurs in daily life. The complex cascade of synchronized cellular and molecular phases in wound healing is impaired by different means, involving infection, neuropathic complexes, abnormal blood circulation, and cell proliferation at the wound region. Thus, to overcome these problems, a multifunctional wound dressing material is fabricated. In the current research work, we have fabricated a wound dressing polymeric patch, with poly(vinyl alcohol) (PVA) and chitosan (Cs) incorporated with a photocatalytic graphene nanocomposite (GO/TiO2(V-N)) and curcumin by a gel casting method, that focuses on multiple stages of the healing process. The morphology, swelling, degradation, moisture vapor transmission rate (MVTR), porosity, light-induced antibacterial activity, hemolysis, blood clotting, blood abortion, light-induced biocompatibility, migration assay, and drug release were analyzed for the polymeric patches under in vitro conditions. PVA/Cs/GO/TiO2(V-N)/Cur patches have shown enhanced wound healing in in vivo wound healing experiments on Wister rats. They show higher collagen deposition, thicker granulation tissue, and higher fibroblast density than conventional dressing. A histological study shows excellent re-epithelialization ability and dense collagen deposition. In vitro and in vivo analysis confirmed that PVA/Cs/GO/TiO2(V-N) and PVA/Cs/GO/TiO2(V-N)/Cur patches enhance the wound healing process.

The American Psychiatric Association Practice Guideline for the Treatment of Patients With Eating Disorders.

The American Psychiatric Association Practice Guideline for the Treatment of Patients With Eating Disorders.

A Hybrid Generic Framework for Heart Problem Diagnosis Based on a Machine Learning Paradigm.

The early, valid prediction of heart problems would minimize life threats and save lives, while lack of prediction and false diagnosis can be fatal. Addressing a single dataset alone to build a machine learning model for the identification of heart problems is not practical because each country and hospital has its own data schema, structure, and quality. On this basis, a generic framework has been built for heart problem diagnosis. This framework is a hybrid framework that employs multiple machine learning and deep learning techniques and votes for the best outcome based on a novel voting technique with the intention to remove bias from the model. The framework contains two consequent layers. The first layer contains simultaneous machine learning models running over a given dataset. The second layer consolidates the outputs of the first layer and classifies them as a second classification layer based on novel voting techniques. Prior to the classification process, the framework selects the top features using a proposed feature selection framework. It starts by filtering the columns using multiple feature selection methods and considers the top common features selected. Results from the proposed framework, with 95.6% accuracy, show its superiority over the single machine learning model, classical stacking technique, and traditional voting technique. The main contribution of this work is to demonstrate how the prediction probabilities of multiple models can be exploited for the purpose of creating another layer for final output; this step neutralizes any model bias. Another experimental contribution is proving the complete pipeline's ability to be retrained and used for other datasets collected using different measurements and with different distributions.

Otonomi Daerah dalam Pengembangan Kesejahteraan Sosial Anak Terlantar di Kota Serang Berdasarkan Undang-Undang Nomor 23 Tahun 2014

Children are national assets who have the right to grow and develop optimally. Living on the streets is very dangerous for children. The aim of the research is to determine the application of the principle of regional autonomy in developing social welfare for neglected children and the obstacles in overcoming the problems of abandoned children in Serang City. The research uses qualitative methods with a case study approach. This research concludes that the Regional Government of Serang City, in implementing the principle of regional autonomy for the welfare of neglected children based on Law Number 23 of 2014, has the authority to make regional policies that have an impact on prosperity and general welfare in its region. The Serang City Government is responsible for providing social services to neglected children by providing children's rights and protecting them from the risks and threats of life on the streets. The obstacle to handling the problem of abandoned children is the mindset of abandoned children and families which are still oriented towards financial conditions as the main reference, thereby ignoring risks and other threats of danger. Problems with the level of education, habits of abandoned children and limited budgets provided also become obstacles to the implementation of handling abandoned children..

Strategies for the Remediation of Cadmium and Chromium From Industrial Effluents in Response to Amaranthus Cruentus, Spinacia Oleracea And Amaranthus Viridis of Bangladesh

Discharge of industrial effluents and their remediation in relation to crop production are the major concerns. Accordingly, the color, pH, EC, total dissolved solids (TDS), dissolved oxygen (DO), chemical oxygen demand (COD), total hardness, chloride, CO3, HCO3, alkalinity, Cu, Cd, Pb, Mn, Zn, and Cr contents in the effluents discharged from Hazaribagh tannery and Tejgaon textile industries in Dhaka were determined. These effluents had no significant (p≤0.05) effects on soil pH but exerted significant positive effects on the CEC of the soil. The TDS of the effluents were also high but it decreased by alum [K2SO4 Al2 (SO4)3 24 H2O] treatment (0.1%). The DO of the effluents was low and the COD was high leading to a serious threat for aquatic lives. The concentrations of Cd, Pb, Zn, Mn and Cr were high. Filtration through natural sand-gravity-filter acts like Effluent Treatment Plant-ETP and coagulation of effluents by alum decreased the concentrations of Cd and Cr below the permissible limits. The treated effluents were used for the production of vegetables of red amaranth (Amarunthus cruentus), green spinach (Spinacia oleracea) and green amaranth (Amarunthus viridis) grown in a non-polluted soil under pot experiments. Application of treated effluents was found to have significant (p≤0.05) positive effects on the biomass production of the vegetables. The highest amounts of assimilation of Cd in plants were recorded for the Green spinach followed by Green amaranth and for Cr, the order was green spinach followed by red amaranth and green amaranth vegetables grown under the treated effluents of tannery and textile industries. The present study revealed that the natural sand-gravity-filter (i.e., Economic ETP) and alum treatments were found to be effective not only for the remediation of polluted effluents but also improved the growth of vegetables. The use of natural filter and/or alum treatment can be practiced for the remediation of pollution of industrial effluents before discharging from industries. J. Biodivers. Conserv. Bioresour. Manag. 2022, 8(2): 109-118

Heart Disease Diagnosis and Prediction using Multi Linear Regression

The correct prediction of heart disease can prevent life threats, and incorrect prediction can prove to be fatal at the same time. In this paper machine learning algorithm is applied to compare the results and analysis of primary dataset. The dataset consists of 46 attributes among these Information gain is used to select 24 features for performing the analysis. Various promising results are achieved and are validated using accuracy and confusion matrix. The dataset consists of some irrelevant features which are handled and data are also normalized for getting better results. Using machine learning approach, 77.78% accuracy was obtained. Multiple linear regressions are used to construct and validate the prediction system. Our experimental result shows that multiple linear regressions are suitable for modelling and predicting cholesterol.

Зависимость продуктивных и физиологических показателей у постнатальных поросят от срока объединения гнезд

However, the experience of her work has shown that modern technology has violated to a certain extent the relationship of the body of pigs with the environment with traditional conditions of keeping and feeding. But recently, the latest technical developments in the provision of methods for keeping pigs of different technological groups, methods and means of ventilation of premises, which have a significant impact on the level of metabolic processes and productivity of animals, have been rapidly introduced in pig breeding. This is especially true for such a vulnerable technological group as weaned piglets, during the growing period of which there are a number of critical life threats. Therefore, the only effective way is to optimize the technological parts of keeping pigs under the conditions of industrial pork production technology. The two-phase technology is characterized by the fact that, after weaning from sows, piglets are grown in nests, in the same pens where they were born, up to 90–120 days of age. Until they have a mass of 30–40 kg. And only then the animals are transferred to fattening. When growing according to the accepted technological scheme, young animals change only two production premises, therefore such a system of animal fattening is called two-phase. It reduces the stress on the animals, both due to the minimum movement of young animals, and because there is no struggle for leadership in newly formed groups of piglets. The criterion for evaluating various production technologies is the correspondence of physiological needs and genetic characteristics of farm animals to artificial environmental conditions. The article considers the influence of different terms of combining nests in the suckling period on individual productivity indicators, as well as on the ethological and hematological indicators of piglets. The expediency of combining three nests of piglets at the age of 21 days for subsequent rearing by one group has been proved. Although this method of combining nests predetermines a certain physiological stress in the animal organism, as evidenced by hematological parameters, however, it does not go beyond the normal range and no stress state is observed.

Unsupervised Deep Learning Approach for In-Vehicle Intrusion Detection System

The controller area network (CAN) is a standard communication protocol used for sending messages between electronic control unit of a modern automotive system. CAN protocol does not have any in-built security mechanisms and, hence, various attacks can affect the vehicle and cause life threats to the passengers. This article presents an unsupervised deep learning architecture for detecting intrusions on a CAN bus. The CAN intrusion detection system (IDS) architecture has an autoencoder that helps to learn the optimal features from CAN packets to differentiate between the normal and attacks. The optimal features are passed as input to the Gaussian mixture model, which helps us to cluster the CAN network packet data samples into normal and attacks. A detailed analysis of the proposed architecture is done on the CAN IDS dataset. To develop a robust CAN IDS system and achieve generalization, the proposed method is evaluated on the other two computer network intrusion datasets and a wireless sensor network dataset. In all the experiments, the proposed method has performed better than the existing unsupervised method and mainly showed a performance gain of 6.4% on the CAN IDS dataset. This indicates that the proposed method is robust and generalizable across detecting various attacks in a CAN bus and most importantly, the method can be used in real time to effectively monitor the CAN network traffic to proactively alert possible attacks.

PATHOPHYSIOLOGY, RISK ASSESSMENT, AND MANAGEMENT FOR ASTHMA PATIENTS DURING THE COVID-19 PANDEMIC OUTBREAK

Innumerable personages are associated with susceptibility to the COVID-19 pandemic viral infection evolution, which has globally overblown the healthcare facilities. Following the emergence of respiratory syndrome coronavirus, 2019- nCoV delineates as a third major emergence of a novel coronavirus. β-coronavirus having suspected origin from bat comprehend congestion of the respiratory system, indicating a worldwide life threat to around 235 million asthma patients’ existents as per WHO records. This review aims to investigate the risk constituents involved in virus-induced asthma, its management and prevention, origin, and transmission of coronavirus, including the relationship between different CoV infections. This review culminated the role of cytokines and chemokines and others found in COVID19 patients, which could directly or indirectly affect the smooth muscle contractility reasoned to promote asthma severity, but this still remains unknown. The research highlights how essential it is to regularly wash your hands and clean surfaces that are touched by your hands in order to prevent illness. Some pre-clinical data suggests the preferred use of a PDE4 inhibitor like Roflumilast in case of uncontrolled virus-induced asthma exacerbations. Although there is a lack of particular asthma management so far, that is why the rectification of the consequences can only be done by taking supportive treatment.

There's something in the water: an overview of jellyfish, their stings, and treatment.

An increasing presence on many beaches worldwide, jellyfish are a diverse group of Cnidarians equipped with stinging cells termed cnidocytes. Though few of the over 10,000 species are dangerous to humans, and most that are produce no more than a painful sting, some jellyfish can produce systemic symptoms and even death. Chironex fleckeri, the Australian box jellyfish, has a venom potent enough to kill in less than 10 minutes, and for which there is an antivenom of debatable efficacy. Stings from Carukia barnesi can cause Irukandji syndrome, characterised by severe pain and hypertension. Jellyfish stings have also been associated with Guillain-Barre syndrome and anaphylaxis. Though optimal treatment of stings remains controversial, after removal from the water and addressing any immediate life threats, the tentacles should be removed and the area washed, with seawater being the best choice due to its low likelihood of inducing further cnidocyte discharge. Hot water immersion may be beneficial for pain control for non-tropical jellyfish stings, and cold packs for tropical stings. In general, there is no consensus for the optimal treatment of jellyfish stings, and so further research is needed into species-specific guidelines and whether there are any overarching rules.

Team Stress and Its Impact on Interprofessional Teams: A Narrative Review

Phenomenon: Interprofessional healthcare team (IHT) collaboration can produce powerful clinical benefits for patients; however, these benefits are difficult to harness when IHTs work in stressful contexts. Research about stress in healthcare typically examines stress as an individual psychological phenomenon, but stress is not only a person-centered experience. Team stress also affects the team’s performance. Unfortunately, research into team stress is limited and scattered across many disciplines. We cannot prepare future healthcare professionals to work as part of IHTs in high-stress environments (e.g., emergency medicine, disaster response) unless we review how this dispersed literature is relevant to medical education. Approach: The authors conducted a narrative review of the literature on team stress experienced by interprofessional teams. The team searched five databases between 1 Jan 1990 and 16 August 2021 using the search terms: teams AND stress AND performance. Guided by four research questions, the authors reviewed and abstracted data from the 22 relevant manuscripts. Findings: Challenging problems, time pressure, life threats, environmental distractors, and communication issues are the stressors that the literature reports that teams faced. Teams reacted to team stress with engagement/cohesion and communication/coordination. Stressors impact team stress by either hindering or improving team performance. Critical thinking/decision-making, team behaviors, and time for task completion were the areas of performance affected by team stress. High-quality communication, non-technical skills training, and shared mental models were identified as performance safeguards for teams experiencing team stress. Insights: The review findings adjust current models explaining drivers of efficient and effective teams within the context of interprofessional teams. By understanding how team stress impacts teams, we can better prepare healthcare professionals to work in IHTs to meet the demands placed on them by the ever-increasing rate of high-stress medical situations.

Relationship between attitudes toward COVID-19 infection, depression and anxiety: a cross-sectional survey in Japan

BackgroundAlthough negative attitudes are known to develop with experiences of COVID-19 infection, it remains unclear whether such attitudes contribute to depression and anxiety as sequelae of COVID-19. We aimed to investigate the relationships between attitude towards COVID-19 infection and post-COVID-19 depression and anxiety.MethodsA cross-sectional survey of COVID-19 recovered patients was conducted from July to September 2021 in Japan. Outcome variables, depression and anxiety were assessed using the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7); scores of 10 and above were identified as having symptoms of depression and anxiety, respectively. Exposure variables were whether participants were experiencing the following attitude strongly: threat to life due to COVID-19 infection, helplessness regarding COVID-19 infection, blaming a third party who did not restrain from going outside, blaming themselves for their COVID-19 infection, worry about spreading the infection to others, and self-stigma (Self-Stigma Scale-Short). Modified Poisson regression analyses were performed to analyze the findings.ResultsA total of 6016 responses were included in the analyses. The proportion of depression was 19.88%, and anxiety was 11.47%. The threat of life due to COVID-19 infection, helplessness regarding COVID-19 infection, blaming oneself for their COVID-19 infection, and self-stigma were significantly associated with depression and anxiety after adjusting covariates. Blaming the third party who did not restrain from going outside was associated with anxiety. There was no association between the worry about spreading infection to others and depression or anxiety.ConclusionNegative attitudes, including self-stigma with the experience of COVID-19 infection, were related to depression and anxiety. Further studies confirming whether countermeasures for preventing or decreasing the negative attitude towards COVID-19 infection mitigate these symptoms are needed.

Influence of slab deflection on the out-of-plane capacity of unreinforced masonry partition walls

Severe damage of non-structural elements is noticed in previous earthquakes, causing high economic losses and posing a life threat for the people. Masonry partition walls are one of the most commonly used non-structural elements. Therefore, their behaviour under earthquake loading in out-of-plane (OOP) direction is investigated by several researches in the past years. However, none of the existing experimental campaigns or analytical approaches consider the influence of prior slab deflection on OOP response of partition walls. Moreover, none of the existing construction techniques for the connection of partition walls with surrounding reinforced concrete (RC) is investigated for the combined slab deflection and OOP loading. However, the inevitable time-dependent behaviour of RC slabs leads to high values of final slab deflections which can further influence boundary conditions of partition walls. Therefore, a comprehensive study on the influence of slab deflection on the OOP capacity of masonry partitions is conducted. In the first step, experimental tests are carried out. Results of experimental tests are further used for the calibration of the numerical model employed for a parametric study. Based on the results, behaviour under combined loading for different construction techniques is explained. The results show that slab deflection leads either to severe damage or to a high reduction of OOP capacity. Existing practical solutions do not account for these effects. In this contribution, recommendations to overcome the problems of combined slab deflection and OOP loading on masonry partition walls are given. Possible interaction of in-plane (IP) loading, with the combined slab deflection and OOP loading on partition walls, is not investigated in this study.

Intrusion Detection System for Internet of Vehicles Based on Ensemble Learning and CNN

With the combination of network and automotive technology, more and more modern cars are controlled based on electronic control units (ECUs). And multiple ECUs in modern cars are interconnected and cooperate through the in-vehicle network. But such in-vehicle networks do not consider potential security issues, which might lead to property damage and life threat. An intrusion Detection System (IDS) is a method to detect anomalies and warn about network intrusions. In this study, an IDS model based on Convolutional Neural Networks (CNNs) and ensemble learning is proposed. Meanwhile, to further improve the capability of the proposed IDS model, the structure of some CNN basic models is modified. Finally, the proposed model is validated on a representative standard Internet of Vehicles (IoV) dataset Car-Hacking Dataset. In the experiment, the proposed model achieves 100% accuracy and fl-score, and the detection time is from 1.0ms to 2.8ms, which demonstrates that the proposed IDS model detects the effectiveness of network intrusions.

Heart Disease Prediction using Machine Learning

The correct prediction of cardiovascular disease can prevent life threats, and incorrect prediction can prove to be fatal at the same time. Heart disease, also known as cardiovascular disease is one of the complex diseases and globally many people suffered from this disease. It is one of the major causes of mortality worldwide, can be mitigated by early heart disease diagnosis. However, the mortality rate can be drastically controlled if the disease is detected at early stage and preventive measures are adopted as soon as possible. In the modern world, there are some revolutionary advancements within the field of medical science and research and this can be no totally different for ECG. Electrocardiogram (ECG) gives useful information about morphological and functional details of heart which is used to predict various cardiac diseases. In this article, we proposed an efficient and accurate system to diagnosis heart disease which is based on machine learning techniques. Raw ECG signal contains useful features which can be used to detect different heart diseases. The various ECG parameters like heart rate, age, sex, cholesterol level, blood pressure, ST interval of ECG signal are used for analysis. Several machine learning (ML) algorithms have been used for cardiovascular disease prediction. Machine Learning is employed across several ranges around the world. The healthcare business isn't any exclusion.

How can infectious medical waste be forecasted and transported during the COVID-19 pandemic? A hybrid two-stage method

The COVID-19 pandemic has caused an unforeseen collapse of infectious medical waste (IMW) and an abrupt smite of the conveying chain. Hospitals and related treatment centers face great challenges during the pandemic because mismanagement may lead to more severe life threats and enlarge environmental pollution. Opportune forecasting and transportation route optimization, therefore, are crucial to coping with social stress meritoriously. All related hospitals and medical waste treatment centers (MWTCs) should make decisions in perspective to reduce the economic pressure and infection risk immensely. This study proposes a hybrid dynamic method, as follows: first to forecast confirmed cases via infectious disease modeling and analyze the association between IMW outflows and cases; next to construct a model through time-varying factors and the lagging factor to predict the waste quantity; and then to optimize the transportation network route from hospitals to MWTCs. For demonstration intentions, the established methodology is employed to an illustrative example. Based on the obtained results, in finding the process of decision making, cost becomes the common concern of decision-makers. Actually, the infection risk among publics has to be considered simultaneously. Therefore, realizing early warning and safe waste management has an immensely positive effect on epidemic stabilization and lifetime health.

Post-traumatic stress disorder as a nosological unit: Difficulties of the past and challenges of the future

Introduction. The impact of traumatic experiences has always been a part of human life. According to Judith Herman, an American psychotherapist, and professor at Harvard Medical School, "traumatic events overload a person's usual strategies for adapting to life, his usual security systems that give a sense of control, connection, and meaning." Also, traumatic events, for the most part, contain close personal contact with violence and death and pose a threat to life or physical integrity. For almost one year of the war, Ukrainian society faced a large number of negative phenomena capable of causing severe psychological trauma: disruption of the usual lifestyle, loss of family friends, and property, lack of many vital needs for a person, forced migration, uncertainty, a constant threat for health and life, etc. The purpose of the study was to analysis of scientific and literary data reflecting the history of the formation of the concept of "post-traumatic stress disorder" as a nosological unit, as well as the peculiarities of its manifestation and prevalence, diagnostic criteria. Materials and methods: A systematic search was conducted in the main electronic medical databases, such as PubMed, Scopus, Web of Science, Google Scholar, and processed publications that studied the history of the formation of "post-traumatic stress disorder" as a nosological unit, the features of its manifestation and prevalence. diagnostic criteria. Eligible studies were identified using keywords: post-traumatic stress disorder, psychotraumatology, trauma, physioneurosis, history of medicine. All types of articles were reviewed, including original studies, systematic reviews, and meta-analyses. Review and discussion: For a long time, there was a stigmatization of combat-related disorders in society. The path to the development of PTSD as a psychiatric diagnosis is long and thorny. After the World War II, there was an urgent need to introduce a standard unified nomenclature that would enable doctors from all over the world to have a common language for discussing the psychopathology of this disorder, establishing a diagnosis and determining disability. Over 60 years, starting in 1952, when the American Psychiatric Association (APA) introduced the concept of "brutal stress reaction" in its first edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-I) and up to 2013 (DSM-5) formation of post-traumatic stress disorder as a nosological unit was taking place. Conclusions: Despite the non-acceptance, stigmatization, indifference and other difficulties, PTSD finally achieved official status in the recognized list of diagnoses

Contrast-induced nephropathy (CIN) - epidemiology, risk factors and prevention

Introduction: Contrast-induced nephropathy is one of the most serious adverse effects of radiocontrast agents usage. It is currently listed in the literature as the third most common cause of iatrogenic acute kidney injury. Aim of the study: The aim of this study is to provide an overview of the extent, severity and prevention of CIN. It is to shed a broader light on this disease entity and be a helpful resource in the future for other clinicians struggling with CIN. Methods and materials: A literature review was conducted using the PubMed database, using the keywords: "contrast-induced nephropathy"; "acute kidney injury"; "contrast media". Results: Pathogenesis of CIN is not entirely clear. There are many risk factors being e.g. diabetes, chronic kidney disease, advanced age (patients over 75 years old). Prevention methods include restricting contrast volume to a minimum, balancing the patient's volaemia before contrast administration or perioperative saline hydration to normalise volaemia. Conclusion: CIN is a significant health problem, which can be a life threat. Despite the fact that the exact pathogenesis of the condition still remains unknown, the CIN prophylaxis becomes more and more effective due to better recognition of risk factors and the usage of adequate prevention measures appropriate to the patients' condition. More studies, with larger test groups, are needed to better define both the pathomechanism of contrast-induced acute kidney injury and new, more effective ways of prevention and treatment of this condition.

Post-traumatic stress disorder and associated factors among people who experienced traumatic events in Dessie town, Ethiopia, 2022: A community based study

Posttraumatic stress disorder (PTSD) may develop as a serious long-term consequence of traumatic experiences, even many years after trauma exposure. Dessie town residents have experienced prolonged armed conflict due to inter-communal conflict in 2021. Those people are exposed to different kinds of trauma, and violence, making them more prone to psychological disorders. Despite the highest number of people affected due to conflict and its negative impact on mental health, post-traumatic stress disorders among people are overlooked in Ethiopia. This study aimed to assess the prevalence and associated factors of post-traumatic stress disorder among people who experienced traumatic events in Dessie town, Ethiopia, 2022. Community based cross-sectional study was conducted on June 8-July 7, 2022, by using a multi-stage cluster sampling with a total sample of 785. Pretested, structured questionnaires and face-to-face interviews were used for data collection. PTSD was assessed by the Post-traumatic stress disorder Checklist for DSM-5 (PCL-5). Data was entered using Epi-data version 3.1 and, then exported to SPSS version 26 for analysis. The association between outcome and independent variables was analyzed with bi-variable and multivariable logistic regression. P-values less than 0.05 was considered statistically significant. The prevalence of PTSD among Dessie town residents was found to be 19.4% (95% CI, 16.7, 22.0). In multivariable analysis, being females (AOR = 1.63, 95% CI 1.10-2.44), previous history of mental illness (AOR = 3.14, 95% CI 1.14-7.06) depressive symptoms (AOR = 3.12, 95% CI 1.92-5.07), witnessing a serious physical injury of a family member or friend (AOR = 2.82, 95% CI 1.18-6.70) and high perceived life threats (AOR = 5.73, 95% CI 3.05-10.78) were found to be significant predictors of PTSD. The prevalence of PTSD among Dessie town residents was found to be huge. Being female, having a previous history of mental illness, depressive symptoms, witnessing a serious physical injury of a family member or friend, and high perceived life threats were variables that are independent predictors of PSTD. People who have experienced such a severe traumatic event require psychosocial support to aid in their recovery from the terrible experiences.