Disruption Of Essential Services Research Articles

Flood Prediction System Using IOT & Artificial Neural Network

Floods pose significant challenges as one of nature's most devastating disasters, making the development of accurate forecast model’s complex. This issue has led to severe consequences such as crop loss, population displacement, damage to infrastructure, and disruption of essential services. Advanced research on flood prediction models has played a crucial role in providing policy recommendations, mitigating risks, reducing human casualties, and minimizing property damage caused by floods. In this context, we propose an Internet of Things (IoT)-based flood prediction and forecasting model that prioritizes energy efficiency. Given the limited battery and memory capacity of IoT sensor nodes, we employ an energy-saving strategy within the fog layer, leveraging data diversity to minimize energy consumption. Additionally, cloud technology offers an effective storage solution. To accurately calibrate flood phases, we investigate climatic factors such as humidity, temperature, rainfall, as well as water body parameters including water flow and elevation. Neural networks are commonly used in constructing forecast systems, as they can replicate the complex calculations involved in flood physical processes, resulting in improved performance and cost-effectiveness. In our approach, the Artificial Neural Network (ANN) technique is employed for flood forecasting, and the effectiveness of different algorithms, such as Logistic Regression and Decision Tree, is assessed by comparing them to ANN. Accuracy values are computed using a classification report assessment, and graph parameters are carefully evaluated. Ultimately, our proposed system utilizes the ANN technique to train a predictive model by examining the dataset. This model generates real-time flood risk forecasts through a user-friendly graphical interface.

Cyberterrorism as a global threat: a review on repercussions and countermeasures.

An act of cyberterrorism involves using the internet and other forms of information and communication technology to threaten or cause bodily harm to gain political or ideological power through threat or intimidation. Data theft, data manipulation, and disruption of essential services are all forms of cyberattacks. As digital infrastructure becomes more critical and entry barriers for malicious actors decrease, cyberterrorism has become a growing concern. Detecting, responding, and preventing this crime presents unique challenges for law enforcement and governments, which require a multifaceted approach. Cyberterrorism can have devastating effects on a wide range of people and organizations. A country's reputation and stability can be damaged, financial losses can occur, and in some cases, even lives can be lost. As a result of cyberattacks, critical infrastructure, such as power grids, hospitals, and transportation systems, can also be disrupted, leading to widespread disruptions and distress. The past ten years have seen several cyber-attacks around the globe including WannaCry attack (2017), Yahoo data breaches (2013-2014), OPM data breach (2015), SolarWinds supply chain attack (2020) etc. This study covers some of the cyberterrorism events that have happened in the past ten years, their target countries, their devastating effects, their impacts on nation's economy, political instability, and measures adopted to counter them over the passage of time. Our survey-based research on cyberterrorism will complement existing literature by providing valuable empirical data, understanding of perceptions and awareness, and insights into targeted populations. It can contribute to the development of better measurement tools, strategies, and policies for countering cyberterrorism.

Mental Health Disorders Due to Disaster Exposure: A Systematic Review and Meta-Analysis.

Natural disasters are complex, global issues that affect people individually, families, and communities, upsetting their emotional wellbeing. This research aims to comprehend the connections between disasters and their effects on mental health.We conducted a systemic review and meta-analysis on the effect of disasters on mental health disorders using defined search terms across three major databases. The search technique adhered to the PECO framework. The study locations were dispersed across Asia, Europe, and America. An electronic search was established in the Cochrane Central Register of Controlled Trials in the Cochrane Library, PubMed, and Medline databases. A random-effects meta-analysis was carried out. The I2 statistic was used to explore heterogeneity. In the random-effects analysis, Tau-squared, τ2, or Tau2 evaluates the effects seen between the study variances. Publication bias was examined. The outcomes of the included studies on mental health issues (n = 48,170) brought on by catastrophic disasters were pooled using a random-effects meta-analysis. The three main mental health illnesses attributed to the disaster catastrophe in most studies weregeneralized anxiety disorder (GAD), depression,substance use, adjustment disorder, and post-traumatic stress disorder (PTSD). Storms, including cyclones and snowstorms, had an impact on 5,151 individuals. 38,456 people were harmed by flooding, and 4,563 people were affected by the earthquake. The included studies showed prevalence rates for mental health disorders ranging from 5.8% to 87.6%. The prevalence rates were between 2.2% and 84% for anxiety, 3.23% and 52.70% for depression, and 2.6% and 52% for PTSD, respectively. The point effect estimates of studies included the flood, storm/cyclone, and earthquake were 0.07 (95% confidence interval [CI]: 0.02-0.12), 0.18 (95% CI: 0.03-0.32), and 0.15 (95% CI: 0.03-0.27), respectively, which revealed a statistically significant positive effect (p-value: < 0.05) with a narrow 95% CI indicating more precise population estimates. However, the pooled effect estimates were not of a large effect size of 0.129 (95% CI: 0.05-0.20). This study found a link between disaster and poorer outcomes for mental health. The risk of psychological morbidity and fatalities increased with relocation and disruption of essential services. Flooding was the most frequent calamity. The "medium human development countries" were found to have the highest prevalence rate of mental health disorders in our meta-analysis. The "very high human development" and "high human development" nations, however, also had a higher prevalence rate of mental health disorders following catastrophic events.This study could aid in the creation of thorough strategies for the mitigation and avoidance of mental health problems during natural disasters. Increased community resilience, improved access to healthcare services, and a suitable mitigation strategy can all help to improve the situation of the disaster's vulnerable population.

Cybersecurity in Algeria

Cybersecurity is an important issue for individuals, organizations, and governments in Algeria and around the world. Cyberattacks can have serious consequences, including financial loss, theft of sensitive information, damage to reputation, and disruption of essential services. To help protect against these types of threats, it is important for individuals and organizations to take steps to secure their systems and data. This can include using strong passwords, keeping software and security protocols up to date, and being cautious when interacting with unfamiliar websites or individuals online. Governments may also have policies and regulations in place to help protect against cyber threats and to respond to incidents when they do occur. Algeria is currently not among the countries that prioritize cyber security sufficiently.

The impact of Covid-19 on malaria services in three high endemic districts in Rwanda: a mixed-method study

BackgroundRwanda has achieved impressive reductions in malaria morbidity and mortality over the past two decades. However, the disruption of essential services due to the current Covid-19 pandemic can lead to a reversal of these gains in malaria control unless targeted, evidence-based interventions are implemented to mitigate the impact of the pandemic. The extent to which malaria services have been disrupted has not been fully characterized. This study was conducted to assess the impact of Covid-19 on malaria services in Rwanda.MethodsA mixed-methods study was conducted in three purposively selected districts in Rwanda. The quantitative data included malaria aggregated data reported at the health facility level and the community level. The data included the number of malaria tests, uncomplicated malaria cases, severe malaria cases, and malaria deaths. The qualitative data were collected using focus group discussions with community members and community health workers, as well as in-depth interviews with health care providers and staff working in the malaria programme. Interrupted time series analysis was conducted to compare changes in malaria presentations between the pre-Covid-19 period (January 2019 to February 2020) and Covid-19 period (from March 2020 to November 2020). The constant comparative method was used in qualitative thematic analysis.ResultsCompared to the pre-Covid-19 period, there was a monthly reduction in patients tested in health facilities of 4.32 per 1000 population and a monthly increase in patients tested in the community of 2.38 per 1000 population during the Covid-19 period. There was no change in the overall presentation rate for uncomplicated malaria. The was a monthly reduction in the proportion of severe malaria of 5.47 per 100,000 malaria cases. Additionally, although healthcare providers continued to provide malaria services, they were fearful that this would expose them and their families to Covid-19. Covid-19 mitigation measures limited the availability of transportation options for the community to seek care in health facilities and delayed the implementation of some key malaria interventions. The focus on Covid-19-related communication also reduced the amount of health information for other diseases provided to community members.ConclusionThe Covid-19 pandemic resulted in patients increasingly seeking care in the community and poses challenges to maintaining delivery of malaria services in Rwanda. Interventions to mitigate these challenges should focus on strengthening programming for the community and home-based care models and integrating malaria messages into Covid-19-related communication. Additionally, implementation of the interrupted interventions should be timed and overlap with the malaria transmission season to mitigate Covid-19 consequences on malaria.

Abstract LB-154: Disruption of essential services after Hurricanes Irma and Maria and quality of life among women with gynecological cancer receiving care in Puerto Rico

Abstract Objectives: Cancer patients have increased risk of poor outcomes after disasters. On September 2017 Hurricanes Irma and María affected Puerto Rico (PR), causing the population to experience major stressors. We describe the disruption of essential services among women with gynecologic cancer in PR after hurricanes Irma and Maria and its impact on quality of life (QoL). We also compare QoL of these women before and after the hurricanes. Methods: This ongoing cross-sectional study is recruiting women aged ≥21 years diagnosed between September 2016-September 2018 and receiving care in PR; we have conducted 110 phone interviews from September 2019-December 2019. Patients' interviews address stressors (including disruptions and time in essential services such as power, electricity and telecommunications) and multilevel responses experienced by the women in the aftermath of the hurricanes. QoL was measured by using a scale from the BRFSS, which includes six items within two domains: physical and mental health; these items were assessed at two time periods (30 days and 3 months) before and after the hurricanes. The association between disruption of essential services and QoL was evaluated with the Chi-square test. Paired McNemar's test was used to compare women's QoL before and after the hurricanes. Results: Mean age of study participants is 63.7±12.1 years; 64.5% of women had a diagnosis of endometrial cancer, 15.5% cervical, 15.5% ovarian, 3.6% vulvar, and 1.0% vaginal. 100% of patients reported disruptions in electric power, 84.5% in potable water, and 75.2% in telecommunications. On average, patients endured 114 days (±88.8) without electric power, 63 days (±62.8) without potable water, and 62 days (±56.3) without telecommunications. We did not find significant differences between the disruption of essential services and QoL indicators (p&amp;gt;0.05). Nonetheless, QoL indicators were worst after the hurricanes than before. Frequent activity limitations (before=22.3% vs. after=39.1%), frequent mental distress (before=26.4% vs. after= 59.1%) and feeling dissatisfied/very dissatisfied with life (before=6.2% vs. after= 21.7%) increased (p&amp;lt;0.001). Frequent physical distress (33.6% vs. 40.9%) and fair/poor general health status (33.9% vs. 50.9%) also increased after the hurricanes, these results were marginally significant (p&amp;lt;0.10). Conclusion: Most of the patients experienced long interruptions in essential services, after hurricanes. The fact that all patients experienced some kind of disruption may explain the lack of association of these variables with QoL. Nonetheless, this study shows that participant's QoL worsened after the hurricanes. Study results should guide the development of a disaster management plan for cancer patients that focuses on minimizing the adverse effects on QoL in the aftermath of a catastrophic event. Acknowledgement: NCI Grant #R21CA239457 Citation Format: Ana P. Ortiz, Sandra García-Camacho, Andrea Pacheco-Díaz, William Calo, Sharee A. Umpierre, Pablo Méndez-Lazaro, Istoni DaLuz-Santana, Lianeris Estremera-Rodriguez, Mirza Rivera, Guillermo Tortolero-Luna. Disruption of essential services after Hurricanes Irma and Maria and quality of life among women with gynecological cancer receiving care in Puerto Rico [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-154.

Management of mother–newborn dyads in the COVID-19 era

Management of mother–newborn dyads in the COVID-19 era

Estimating the uninsured losses due to extreme weather events and implications for informal sector vulnerability: a case study of Mumbai, India

Extreme weather events lead to significant physical, economic and social impacts with short- and long-term consequences for affected regions. The methodologies used to assess the impacts often focus on the insured losses associated with private capital and public infrastructure. However, these estimates do not reflect the losses, monetary and non-monetary, associated with damage to uninsured assets. In addition, in the absence of systematic methods for measuring and recording impacts experienced by the informal sector—both households and small businesses—losses experienced by these segments are not reported, particularly in the developing world. This paper uses primary data collected from a survey of households and small businesses to estimate the uninsured losses due to a major flood event in the city of Mumbai, India. A detailed characterization of the losses is attempted, by disaggregating losses into monetary damage to property, physical capital, assets, equipment and inventory as well as loss of income, investment and disruption of essential services. Aggregate estimates of losses at the city level are computed and compared with the insured private and public losses traditionally reported in the literature. Our results indicate that the uninsured private losses suffered by individuals and small businesses significantly exceed the damage to public infrastructure. In the absence of insurance or government assistance, these costs represent a significant out-of-pocket expenses for the households and businesses. These findings have significant policy implications in terms of highlighting the vulnerability of the informal sector to extreme weather events in cities of the developing world.

Resilience and Vulnerability to the Psychological Harm From Flooding: The Role of Social Cohesion.

We examined the role of social cohesion as a component of vulnerability and resilience to the psychological distress of flooding. A survey collected data from 2238 individuals living in flood-affected areas of England (South Yorkshire and Worcestershire) in 2007. We used Bayesian structural equation modeling to assess factors relating to the latent variables of resilience (years in area, family nearby, and social cohesion) and vulnerability (disruption of essential services, flood risk, and previous flood experience). Flooding was strongly associated with poor mental health; however, resilience factors (associated with the ability to cope with natural disasters), but not vulnerability, were strongly associated with a reduction in psychological distress. Resilience and social cohesion were important influences on the risk of developing poor mental health following flooding. Increasing resilience of communities by strengthening social cohesion through measures that increase civic participation and changing land use should be considered as potentially inexpensive and effective defenses against avoidable mental harm that will result from increased climate instability.

Cooperative detection and protection against network attacks using decentralized information sharing

Network attacks, such as distributed denial of service (DDoS) and Internet worms, are highly distributed and well coordinated offensive assaults on services, hosts, and the infrastructure of the Internet, and can have disastrous effects including financial losses and disruption of essential services. Consequently, effective defensive countermeasures against these attacks must provide equally sophisticated and well coordinated mechanisms for monitoring, analysis, and response. In this paper, we investigate techniques for cooperative attack detection and countermeasures using decentralized information sharing. The key underlying idea is the use of epidemic algorithms to share attack information and achieve quasi-global knowledge about attack behaviors. This paper first presents a conceptual model that defines the relationships between the level of knowledge in the distributed system and the accuracy of attack detection. The design of a cooperative attack detection and defense framework is then presented, and its use for detecting and defending against DDoS attacks and Internet worms is described. Simulation results are presented to demonstrate the feasibility and effectiveness of the framework against these attacks.