Efficient Distribution Of Resources Research Articles

Improving Coordination to Strengthen Operationalization of Malaria Surveillance and Routine Data Quality: Landscape Analysis of Current Surveillance-Related Initiatives.

Improving the visibility and global coordination of malaria surveillance and data quality improvement initiatives is required to optimize sharing of best practices, tools, and approaches and to promote efficient, effective, and equitable distribution of resources. With these aims in mind, Rollback Malaria's Surveillance, Monitoring and Evaluation Working Group established the Surveillance Practice and Data Quality Committee in May 2021. As a priority initiative, the committee conducted a landscape analysis of implementing partners' (IPs') malaria surveillance-related projects. A questionnaire that included questions on current project objectives, activities, geographic scope, and lessons learned was distributed among committee members and other IPs. Three years since its inception, information has been submitted regarding 49 projects by 25 IPs and funded by 17 donors. To present and share the landscaping results, an interactive dashboard was published to the Rollback Malaria's Global Malaria Dashboard website (endmalaria.org) in March 2021. It is the first time that multiple stakeholders have shared such information regarding surveillance projects.

Nursing leadership in disaster preparedness and response lessons learned and future directions

Nursing leadership is integral to effective disaster preparedness and response, demanding agility, strategic planning, and robust resource management. Disasters, both natural and man-made, present unique challenges that require nursing leaders to be adept in rapid decision-making and efficient coordination. The unpredictability of disasters necessitates comprehensive and regularly updated preparedness plans, ensuring nursing teams are well-versed in their roles through continuous training and simulations. Interprofessional collaboration and strong community partnerships are essential, fostering a unified response and efficient resource distribution. Communication remains a cornerstone of disaster management, with clear, timely information dissemination being crucial for coordinating efforts and maintaining public trust. Resource scarcity during disasters, such as shortages of medications and personal protective equipment (PPE), poses significant challenges. Effective resource management strategies are essential to maintain patient care standards and protect healthcare workers. The psychological toll on healthcare providers is another critical issue, with nursing leaders needing to implement support systems that address mental health and promote resilience. Integrating advanced technologies like telehealth and data analytics can enhance disaster response, providing remote care options and enabling predictive modeling for better resource allocation. Innovative approaches in nursing leadership include the use of telehealth for remote consultations and monitoring, data analytics for predictive modeling, and interprofessional education to improve teamwork and coordination. Strengthening community partnerships enhances overall disaster response capacity, ensuring that community-specific needs are addressed. Mental health support for healthcare providers, both immediate and long-term, is vital for maintaining a resilient workforce. Policy advocacy by nursing leaders is crucial to developing robust disaster preparedness frameworks and securing adequate funding. In summary, nursing leadership is pivotal in disaster preparedness and response, with a focus on strategic planning, interprofessional collaboration, effective communication, resource management, mental health support, and the integration of advanced technologies. Emphasizing these areas will enhance the resilience and responsiveness of healthcare systems, ultimately improving outcomes for patients and healthcare providers during disasters.

A systematic literature review on contemporary and future trends in virtual machine scheduling techniques in cloud and multi-access computing

IntroductionThe migration of business and scientific operations to the cloud and the surge in data from IoT devices have intensified the complexity of cloud resource scheduling. Ensuring efficient resource distribution in line with user-specified SLA and QoS demands novel scheduling solutions. This study scrutinizes contemporary Virtual Machine (VM) scheduling strategies, shedding light on the complexities and future prospects of VM design and aims to propel further research by highlighting existing obstacles and untapped potential in the ever-evolving realm of cloud and multi-access edge computing (MEC).MethodImplementing a Systematic Literature Review (SLR), this research dissects VM scheduling techniques. A meticulous selection process distilled 67 seminal studies from an initial corpus of 722, spanning from 2008 to 2022. This critical filtration has been pivotal for grasping the developmental trajectory and current tendencies in VM scheduling practices.ResultThe in-depth examination of 67 studies on VM scheduling has produced a taxonomic breakdown into three principal methodologies: traditional, heuristic, and meta-heuristic. The review underscores a marked shift toward heuristic and meta-heuristic methods, reflecting their growing significance in the advancement of VM scheduling.ConclusionAlthough VM scheduling has progressed markedly, the focus remains predominantly on metaheuristic and heuristic approaches. The analysis enlightens ongoing challenges and the direction of future developments, highlighting the necessity for persistent research and innovation in this sector.

Analysis of decentralized drone control model and interception trajectory calculation

Subject matter: This article is devoted to the study of applying the innovative Cascade DataHub method for optimizing the management of automated mobile systems, especially unmanned aerial vehicles. The work analyzes both theoretical and practical aspects of implementing this method across various application sectors. Goal: The objective of the study is to conduct a comprehensive analysis of contemporary models and methods for managing a group of drones, focusing on decentralized approaches. Additionally, the study aims to develop effective algorithms for optimizing the interception trajectory, with the goal of enhancing the accuracy and reliability of managing complex automated systems through increased real-time data integration. The research is directed towards identifying the potential advantages of this method in reducing system response times and improving decision-making accuracy. Tasks: The main tasks of the research include the development of comprehensive algorithms for rapid processing and analysis of large volumes of data from various sources, creating reliable communication protocols to ensure connection stability under extreme conditions. Another important task is the integration of these developments into practical applications, which will increase their effectiveness in real operational conditions. Methods: To achieve the set goals, advanced techniques of mathematical modeling, statistical analysis, machine learning, and deep learning are used. The application of these techniques ensures high accuracy and reliability of the management systems. Results: During the research, it was found that the Cascade DataHub method significantly reduces the response time of systems to commands, increases the accuracy of task execution, and decreases data loss during their transmission. The implementation of this method also contributes to a more efficient distribution of resources among automated units, which is critically important for missions requiring high coordination and time synchronization. Conclusions: A comprehensive analysis of contemporary models and methods for managing a group of drones with a focus on decentralized approaches has been conducted. Effective algorithms for optimizing the interception trajectory have been developed, aimed at enhancing the accuracy and reliability of managing complex automated systems through real-time data integration. The study revealed the potential advantages of the proposed method in reducing system response times and improving decision-making accuracy, contributing to the more efficient functioning of automated systems.

Energy–Efficient Distribution of Resources in Cyber-Physical Internet of Things with 5G/6G Communication Framework

Energy–Efficient Distribution of Resources in Cyber-Physical Internet of Things with 5G/6G Communication Framework

Financing education spending in the context of interbudgetary relations in the Republic of Kazakhstan

In the current conditions, education is endowed with strategic importance as a sphere of social activity that directly forms the level of intelligence of the population, ensuring competitiveness and innovation in the development of the country's economy. Therefore, the study’s relevance is because the educational capital obtained in the learning process is a combination of theoretical knowledge, practical skills, work experience, and personal characteristics that bring a person income during his career and stimulate further investment in education. Education impacts each citizen’s income and directly affects the economic development of the country, its financial capabilities, and national competitiveness. Thus, this article aims to reveal the critical aspects of republican and local financing of education in Kazakhstan and the prospects for its development. The methodological basis of the research is formed by a system of general scientific and unique research methods: synthesis, system-analytical analysis, and abstract-logical method. The critical result of the work is the systematization of acquisitions within the framework of the researched topic and the study of the features of optimizing the decentralization of education financing in Kazakhstan. Proposed: to increase the efficient distribution of financial resources at all levels of the budget system; increase the opportunities for educational institutions to raise additional funds through educational innovations, expand the list of paid services provided by such institutions; carry out decentralization of education, taking into account the characteristics of the regions, their production potential, the demographic situation and the interests of territorial communities. The results of this scientific study, as well as the conclusions formulated on their basis, are of significant importance both for the scientific community and for financial experts and practitioners from the educational field since they have a structured presentation of the material based on which logical and constructive conclusions are drawn, which may have an impact on the subsequent processes of reforming the financial provision of education in Kazakhstan.

Patient Satisfaction and Healthcare Utilization with the Transition to Virtual Care in a Multidisciplinary Bariatric Program.

The COVID-19 pandemic saw an acceleration in virtual-visits (VV) for healthcare delivery. However, the impact of virtual care in metabolic/bariatric surgery (MBS) programs is not well described. Appointment data from three time-points: pre-pandemic (1/1/19-3/15/20, n = 19,290), pandemic (3/16/20-10/31/21, n = 29,459) and current-state (11/1/21-12/31/2022, n = 24,270) was retrieved in our multi-hospital ambulatory MBS program. Appointments were grouped by health care provider (HCP) (MD, dietician, and psychologist) and type (VV and in-person). Surveys assessing patient satisfaction were distributed electronically. All pre-op and post-op appointment data was analyzed for the time-points above. Appointment completion rates and patient reported preferences were described. Our data showed an increase in scheduled VV from 0.5% for all HCP visits to 81% during the pandemic and a current VV visit of 77%. The number of completed VV increased for all HCPs, most prominently for dieticians. Parallel to this, the percentage of no-show visits also improved for all HCP, with MDs having the lowest no-show rate currently. Survey data revealed 89% of patients experience added benefits with VV and > 90% reported their VV experience as very good. VV were preferred over in-person visits for psychologists and dietitians (> 61%), but the majority preferred to see MDs in-person (70%). Our findings reveal significant changes in healthcare utilization trends since the transition to virtual care. While overall satisfaction with virtual care is high, most patients prefer in-person visits with MDs. Thus, multi-disciplinary MBS care can be performed effectively using a hybrid model to ensure efficient distribution of resources.

Exploring factors influencing time from dispatch to unit availability according to the transport decision in the pre-hospital setting: an exploratory study.

Efficient resource distribution is important. Despite extensive research on response timings within ambulance services, nuances of time from unit dispatch to becoming available still need to be explored. This study aimed to identify the determinants of the duration between ambulance dispatch and readiness to respond to the next case according to the patients' transport decisions. Time from ambulance dispatch to availability (TDA) analysis according to the patients' transport decision (Transport versus Non-Transport) was conducted using R-Studio™ for a data set of 93,712 emergency calls managed by a Middle Eastern ambulance service from January to May 2023. Log-transformed Hazard Ratios (HR) were examined across diverse parameters. A Cox regression model was utilised to determine the influence of variables on TDA. Kaplan-Meier curves discerned potential variances in the time elapsed for both cohorts based on demographics and clinical indicators. A competing risk analysis assessed the probabilities of distinct outcomes occurring. The median duration of elapsed TDA was 173min for the transported patients and 73min for those not transported. The HR unveiled Significant associations in various demographic variables. The Kaplan-Meier curves revealed variances in TDA across different nationalities and age categories. In the competing risk analysis, the 'Not Transported' group demonstrated a higher incidence of prolonged TDA than the 'Transported' group at specified time points. Exploring TDA offers a novel perspective on ambulance services' efficiency. Though promising, the findings necessitate further exploration across diverse settings, ensuring broader applicability. Future research should consider a comprehensive range of variables to fully harness the utility of this period as a metric for healthcare excellence.

Identifying daily water consumption patterns based on K-means Clustering, Agglomerative Hierarchical Clustering, and Spectral Clustering algorithms

ABSTRACT Understanding daily water consumption patterns is crucial for efficient management and distribution of water resources, as well as for promoting energy conservation and achieving carbon peaking and neutrality targets. It compares performance of three clustering algorithms, K-means Clustering (KC), Agglomerative Hierarchical Clustering (AHC), and Spectral Clustering (SC), using Silhouette Coefficient Index (SCI) and Calinski–Harabasz Index (CHI) as evaluation metrics. We conducted a case study using original hourly flow series of a water distribution division. It aims to identify typical daily water consumption patterns and explore factors that influence them. Findings are as follows: (1) among the three algorithms, KC demonstrates the best, with SCI of 0.6315, 0.5922, and 0.6272, and CHI of 305.9207, 274.1120, and 302.4738 for KC, AHC, and SC, respectively. (2) KC successfully identifies three distinct typical daily water consumption patterns. (3) Results indicate a significant impact of seasons on daily water consumption patterns. (4) Conversely, weekdays and holidays have minimal effect on daily water consumption patterns. It highlights the importance of comprehending daily water consumption patterns and underscores the effectiveness of KC in identifying such patterns. Furthermore, it emphasizes the significant influence of seasons while revealing limited impact of weekdays and holidays on daily water consumption patterns.

Allocation of Resources Efficiently in Tactile Ethernet PON’s - Healthcare

Efficient resource allocation plays a critical role in enhancing network performance within healthcare environments. This study focuses on resource allocation within Tactile Ethernet Passive Optical Networks (PONs) specifically designed for healthcare applications. Our investigation delves into the unique challenges and requirements posed by healthcare Local Area Networks (LANs), which encompass the imperative for secure and dependable data transmission, as well as the seamless integration of medical devices and tactile communication capabilities. Drawing upon a thorough review of existing literature and empirical analysis, this paper proposes novel strategies for the efficient distribution of resources within Tactile Ethernet PONs to address the diverse needs of healthcare networks. We explore innovative approaches to integrate tactile feedback seamlessly into network infrastructure, aiming to enhance user experience and streamline interaction with medical devices. Moreover, we examine the broader implications of efficient resource allocation in terms of its potential to elevate patient care standards, improve operational efficiency, and fortify data security and privacy protocols within healthcare settings. The insights gleaned from this research contribute to the ongoing endeavors aimed at optimizing network performance and enhancing usability across healthcare LANs, ultimately striving to elevate the quality of healthcare services delivered. Keywords- Tactile Ethernet, Passive Optical Network, Network Optimization.

Cost Analysis of Short Messaging Service and Peer Navigator Interventions for Linking and Retaining Adults Recently Diagnosed With HIV in Care in South Africa.

Large proportions of people living with HIV (PLHIV) in sub-Saharan Africa are not linked to or retained in HIV care. There is a critical need for cost-effective interventions to improve engagement and retention in care and inform optimal allocation of resources. We estimated costs associated with a short message service (SMS) plus peer navigation (SMS+PN) intervention; an SMS-only intervention; and standard of care (SOC), within the I-Care cluster-randomized trial to improve HIV care engagement for recently diagnosed PLHIV. We employed a uniform cost data-collection protocol to quantify resources used and associated costs for each intervention. Compared with SOC, the SMS+PN intervention cost $1284 ($828-$2859) more per additional patient linked to care within 30 days and $1904 ($1158-$5343) more per additional patient retained in care at 12 months, while improving linkage by 24% (95% CI: 11 to 36) and retention by 16% (95% CI: 6 to 26). By contrast, the SMS-only intervention cost $198 ($93-dominated) more per additional patient linked to care and $697 ($171-dominated) more per additional patient retained in care but was not significantly associated with improvements in linkage (12%; 95% CI: -1 to 25) or retention (3%; 95% CI: -7 to 14) compared with SOC. The efficiency of the SMS+PN intervention could be improved by 46%, to $690 more per additional patient linked and $1023 more per additional patient retained in care, if implemented within the Department of Health using more efficient distribution of staff resources. Findings suggest that scale-up of the SMS+PN intervention could benefit patients, improving care and health outcomes while being cost-effective.

On your own, together: Regional perspectives on community resource-sharing for disaster preparedness in Washington state

ABSTRACT When disasters isolate communities from external support, their members must turn to each other for mutual assistance. This study explores (1) resource management, (2) information sharing, and (3) community leadership and civic participation as dimensions of peer-to-peer sharing for more efficient distribution of local resources under “islanded” conditions. Interviews with members and leaders of three neighborhood-scale communities in Washington state revealed concerns about household preparedness and stockpiling of resources, but also the potential to lever individuals’ community knowledge, social networks, and willingness to participate. Future interventions might include enhancing place-based social infrastructure for resource and information sharing; online local databases and applications that normally maintain privacy but “unlock” important household information for community use in emergencies; and programs that help individuals access and adopt leadership and participation roles. Satisfying these requirements for successful disaster prepared ness also aligns with the goals of everyday community-building and strengthening of collective capacity.

Intelligence Farming Using Machine Learning

Abstract: This research paper delves into the revolutionary role of machine learning in contemporary agriculture, a concept termed as "Intelligence Farming." The study encompasses the application of data in farming, including data related to weather conditions, soil quality, and crop health, and how machine learning contributes to efficient resource distribution and crop management. The paper underscores the significance of predictive yield forecasting, precision farming, and early detection of crop diseases, all facilitated by machine learning. Furthermore, it discusses the socio-economic and environmental outcomes of implementing this technology, such as enhanced productivity and sustainability. In conclusion, the paper strongly recommends the incorporation of machine learning in agricultural decision-making processes, underlining its critical role in the current era of data-driven decision-making.

Determining the minimum required cooling time of profiled assemblies at the Armenian Nuclear Power Plant taking into account the load schedule

Determining the minimum required cooling time of profiled assemblies at the Armenian Nuclear Power Plant, taking into account the load schedule, is an analytical process to establish the shortest required period during which profiled assemblies used in the nuclear power plant energy process must remain in active use. This process considers factors related to changes in the electrical load on the station during different periods. Within the scope of this definition, an analysis of the technical characteristics of profiled assemblies is conducted as well as their impact on the overall performance of the nuclear power plant. Key considerations in the cooling time include operational safety, compliance with regulatory requirements, and efficient distribution of energy resources in accordance with the load schedule. The goal of this process is to ensure optimal and safe operation of profiled assemblies, adapted to changes in the electrical grid and aligned with the load schedule, thereby contributing to the more efficient functioning of the nuclear power plant. This study aims to substantiate the minimum required cooling time for profiled nuclear assemblies characterized by an average uranium enrichment of 3.82% and an average burnup of 45.7 Megawatt-days per kilogram of uranium (MWD/kgU). Calculations are performed using the ORIGEN-ARP program, part of the SCALE software package designed for the analysis and modeling of radioactive and nuclear processes. The study considers parameters such as the composition of nuclear assemblies, fuel burnup, modeling using the ORIGEN-ARP program, and safety analysis. The results obtained aim to make a significant contribution to enhancing the efficiency and safety of nuclear energy installations

Legal regulation of formation of budgets of united territorial communities as key subjects of local self-government

This article is devoted to the study of certain aspects of the formation of local self-government budgets, namely united territorial hromadas. It is summarized that the armed actions of the aggressor led to a deep economic crisis in Ukraine, which affected the financial capacity of the state as a whole and local self-government bodies, in particular.
 Attention is focused on the fact that with the beginning of a full-scale invasion, the process of approving the budget of local self-government has undergone certain changes: the heads of the respective territorial communities can dispose of the funds of local budgets only in the territory where hostilities are not conducted and the military administration of the settlement (settlements) is not formed. The amendments to the Budget Code of Ukraine related to the payment of personal income tax by military personnel are analyzed. Attention is paid to the content of these innovations, namely, to direct to the state budget revenues from the paid tax on the income of an individual from payers- military personnel. It is noted that these changes should contribute to a more efficient distribution of financial resources, in particular, to influence the state's ability to purchase drones and weapons to ensure the country's defense capability.
 Particular attention was paid to the issues of formation of local budgets, their distribution and use. It is emphasized that the process of decentralization of power, proposed by the government to meet the financial needs of hromadas, is based on local budgets, which will ensure financial independence and personalize responsibility for the consequences of ineffective management of local finances. It is emphasized that the successor of the property and duties of territorial communities are the communities themselves, but according to the innovations, the remaining funds received from the community budget over the past year will be directed to activities related to Russia's armed aggression against Ukraine.
 The article focuses on the importance of ensuring transparency in spending budget funds and the right of communities to establish their own mandatory procedures for ensuring publicity in managing local finances.

Financial Management Challenges in Georgia’s Higher Education Institutions

The effective management of financial resources in higher education institutions significantly impacts the overall system’s functionality. The role of education and scientific development in a country’s economic progress cannot be overstated. Georgia possesses the potential to achieve economic growth through its intellectual and educated human capital. However, despite recent reforms, the education system grapples with persistent shortcomings and challenges, hindering the creation of well-prepared and competitive graduates. Strengthening the education system is essential for Georgia to thrive in the global arena. While funding for education has increased over the years, mere financial inflow does not necessarily correlate with improved educational quality. To address this, a strategic and tactical approach to reform, along with efficient distribution of financial resources, is crucial. This paper investigates the impact of existing funding policies on Georgia’s higher education system. It delves into the structure and dynamics of funding for higher education institutions, examining the nature and significance of previously funded projects. Additionally, the study discusses and analyzes the role of education reforms in promoting overall development. Drawing on both qualitative and quantitative analyses, the recommendations put forth within this framework aim to empower stakeholders in overcoming the challenges faced by Georgia’s higher education landscape.

Subcarrier-users nomination process for downlink NOMA system

The non-orthogonal multiple access (NOMA) characteristics of 5G radio access allow for more efficient resource distribution. NOMA improves spectral efficiency by allowing Power domain users to transmit power concurrently with other users of time and spectrum resources. The selection of the subcarrier and the nomination of users to the subcarrier is of the utmost importance to maximize spectral efficiency fairness among the users and improve the data rate of weak users in the downlink NOMA system. The least gain subcarrier First-threshold-based Adaptive user grouping algorithm (LGSF-TBAUGA) has been devised for this purpose. This algorithm maintains a significant channel gain differential based on a threshold, thus avoiding successive interference cancellation (SIC) process imperfections. The computational complexity of the proposed technique is calculated and compared to other approaches. The power coefficients of the selected users are used to allocate power to them. The proposed method improves the weak user data and overall system sum rates. As a result, the spectrum efficiency and user fairness index have been greatly enhanced compared to some existing algorithms.

Application of the multi-criteria analysis method mairca, spotis, comet for the optimisation of sustainable electricity technology development

The development of sustainable electricity technology is of utmost importance in addressing the increasing energy demand while mitigating greenhouse gas emissions. Fossil fuel-based electricity generation is the primary contributor to air pollution and climate change, necessitating a shift towards renewable energy sources. The efficient production, distribution, and utilization of energy resources, along with ensuring affordable energy access and environmental sustainability, are key policy objectives for any country's energy sector. However, assessing sustainable electricity technologies is a complex task due to the diverse range of evaluation criteria and impacts associated with the practical implementation of these solutions. To overcome this challenge, this study proposes a multi-criteria decision-making (MCDM) approach to select the optimal solution for the development of sustainable electricity technology. The study employs several reliable methods, including MAIRCA, SPOTIS, COMET, and the CRITIC weighting method, to perform ranking evaluations. Based on this, an evaluation Table of criteria using linguistic variables is constructed. Furthermore, a ranking of methods for developing sustainable electricity technology is established by combining MCDM optimization methods. The results indicate that future energy policies should prioritize sustainable energy technologies, particularly water and solar thermal solutions. These findings have significant implications for development policymakers as the transition towards a sustainable energy system becomes increasingly crucial. In the future, the findings of this research can be further developed on a regional level, enabling the identification of the most appropriate energy technologies for specific regions based on their unique characteristics and requirements

Efficient and choreographed quality-of- service management in dense 6G verticals with high-speed mobility requirements

Future 6G networks are envisioned to support very heterogeneous and extreme applications (known as verticals). Some examples are further-enhanced mobile broadband communications, where bitrates could go above one terabit per second, or extremely reliable and low-latency communications, whose end-to-end delay must be below one hundred microseconds. To achieve that ultra-high Quality-of-Service, 6G networks are commonly provided with redundant resources and intelligent management mechanisms to ensure that all devices get the expected performance. But this approach is not feasible or scalable for all verticals. Specifically, in 6G scenarios, mobile devices are expected to have speeds greater than 500 kilometers per hour, and device density will exceed ten million devices per square kilometer. In those verticals, resources cannot be redundant as, because of such a huge number of devices, Quality-of-Service requirements are pushing the effective performance of technologies at physical level. And, on the other hand, high-speed mobility prevents intelligent mechanisms to be useful, as devices move around and evolve faster than the usual convergence time of those intelligent solutions. New technologies are needed to fill this unexplored gap. Therefore, in this paper we propose a choreographed Quality-of-Service management solution, where 6G base stations predict the evolution of verticals at real-time, and run a lightweight distributed optimization algorithm in advance, so they can manage the resource consumption and ensure all devices get the required Quality-of-Service. Prediction mechanism includes mobility models (Markov, Bayesian, etc.) and models for time-variant communication channels. Besides, a traffic prediction solution is also considered to explore the achieved Quality-of-Service in advance. The optimization algorithm calculates an efficient resource distribution according to the predicted future vertical situation, so devices achieve the expected Quality-of-Service according to the proposed traffic models. An experimental validation based on simulation tools is also provided. Results show that the proposed approach reduces up to 12% of the network resource consumption for a given Quality-of-Service.

Concepts, objectives and analysis of public health surveillance systems

Public health surveillance (PHS) systems are an important tool to map the distribution and burden of disease as well as enable efficient distribution of resources to fight a disease. The surveillance systems are used to detect, report, track a disease as well as assess the response to the disease and people's attitudes. PHS systems are changing with the rapid change in technology and are becoming more real-time responsive with availability of new type of data such as online content and social media data. This review presents the basics of surveillance systems and develop from it to show the evolution of surveillance systems. The different forms of data available, surveillance methods and surveillance types are also reviewed such as social media based, web-based and clinical data based PHS maps. This review provide comprehensive details of the surveillance systems in terms of data types used, source of data and purpose of the surveillance system.