+44 203 318 3300 +61 2 7908 3995 help@nativeassignmenthelp.co.uk

Pages: 21

Words: 5181

Critical Review Of The Covid-19 Spread Analysis

Introduction:Critical Review Of The Covid-19 Spread Analysis

Native Assignment Help provides assignment help to assist students in research, writing and proofreading process.

In the situation of Covid-19, "World Health Organisation (WHO)" has transmitted people that have been indicted in the Corona Virus in various ranges of countries. The objective of this research is to determine the accurate ranges of problems and critically reviewed the peer review journals by effectively analysing the key findings. In the situation of the Covid-19 pandemic, data science has become a much more powerful weapon that has combated infectious diseases arguably and epidemic diseases for determining the diseases and generating future growth perspectives sustainably. 

Discussion 

Stability analysis, the spread of Covid-19 and Fuzzy association effect of socio-demographic factors in Covid-19

As opined by Wei et al. (2021), the initial spread of epidemics has been treated as an essential part that has reasonably judged the cultures of improvements of trending cultures and that can also be created an effective range of containments. The authors have been using the "City-based epidemic and mobility model (CEMM)" models for stimulating the situations of Covid-19 spatiotemporal. In addition, the method related to "Intercity transmission" have also been critically used in this peer review by taking the help of the secondary analysis and that has also maintained the data authenticity and reduced the chances of population mobility sustainably. In the year 2020, nearly 138,824 have transformed the rate of infectious cases in China and that has reduced the cultures of population mobility, as the effects of Hubei are greater than the integrity of populations through mobility and spreading the negativity by enhancing the ultimate ranges of lockdown cases. 

However, Annas et al. (2020) have argued that by using the SEIR model in the situation of Covid-19 and taking the help of the numerical model the chances of integrity and actual conditions in Indonesia have been sustainably determined. In this context, the stimulation of protection has also provided protections that have created positive results in developing the cultures of human beings in Indonesia. Taking the help of vaccinations, the chances of acceleration and rate of spread of cultures have also been effectively diminished and the proportion of accurate ranges of the ultimate rates of prevention cultures can be effectively increased. The authors have also been using the "Matlab software" for predicting the numbers and making an effective range of measurements for preventing the accurate ranges of Covid-19 in Indonesia. The usages of numerical simulations have been made in obtaining and collecting reliable information for prevention and developing cultures of efficiency modules by using the Secondary analysis effectively. 

As opined by Chatterjee et al. (2022), the analysis of fuzzy associations has also created identifications that have improved the two kinds of factors related to demographic and socio cultures in the situations of Covid-19. Thus, the persistent rules have also demonstrated streamlined activity rates as well as improved the cultures of the time management attributes by generating the specific outbreak intensity cultures and created a positive effect based on the experimental results. This research aims to develop the cultures of demographic conditions and make a density for increasing the rates of collection process that can be focusing on the multiple ranges of aspects related to temperature, and population density based on religion and humidity. Therefore, the fuzzy associations can also be tried to develop the structures of streamlined activities, as the Apriori algorithm has been briefly used in this research paper for quantifying the intervals and considering the coarser granularity and making differentiation in the linguistics variables. 

Statistical analysis, tracking the emergence of disparities and effects of mobility in Covid-19

As opined by Alotaibi (2021), the countries related to Saudi Arabia have been briefly affected by the situation of Covid-19 thus the rates of economic stability have also been sustainably diminished based on the economical conditions. The authors have also been using the Adams-“Bashforth method” has been critically evaluate the values of numerical solutions in effectively and easily interpreting the solutions that have developed the attributes of environmental functions by making an existence to generate uniqueness. In addition, taking the help of the mathematically based modelling structures related to SIR the chances of crossover displayed speeded cultures have also been effectively identified that can be focused on the multiple ranges of attributes related to averages of death, infected people and recovery rates sustainably. 

However, Mee et al. (2022), have argued that tracking the disparities of emergencies of sub-national speeded the cultures in the situation of Covid-19 around Brazil the usages of online applications have also developed cultural attributes regarding Visualisations. In addition, the development of interventions rate and the ultimate rates of challenges and opportunities have been sustainably decreased based on the structures and population sizes. The countries related to Brazil have been creating a negative effect due to the increasing rates of death cases and that have hampered the cultures of intervention modules effectively. In the year 2021, around 20 million cases and 557,000 death cases have created an effect in the situations of Covid-19 and that has reduced the cultures of real-time visualisations and regression analysis effectively. Taking the help of the Analytical method related to the CLIC-Brazil app the chances of environmental sustainability can also be effectively developed, that have made a demographic index and partially improved the cultures of associations based on the graphical segmentation sustainably. 

As opined by Zargari et al. (2022), the effects of mobility in the situations of Covid-19 have supported the empirical information by taking the help of Tehran and analysing the performance rates based on time management that have been created transitions by implementing the policies and creating effective results based on the controlling process. The authors have also helped to achieve the ultimate ranges of determinations that means long and short-term goal by transiting the transportation variables and sustainably maintaining the protocols. Therefore, "Integrated models (I)", "Autoregressive models (AR)", and "Moving average models (MA)" have been briefly used in this research article that has been renowned as "Autoregressive integrated moving average models (ARIMA)", and "Autoregressive moving average models (ARMA)". In this context, the independent and dependent variables have also been identified at the timing of Covid-19 effectively. 

Discussion of relevant data ecology and impacts of data science

Data ecology is the process that provides better data analysis for the measurement or building a better framework in terms of a conceptual framework.  Data science is a proper analysis of the data with effective insists of data. This process gives an effective process for analysing the data that has various impacts on society. It is a set collection of informative data that gives a better analysis of the data and provides effective insights into the issues and solutions. The data collection in different research processes includes data science and big data analysis. 

According to Wei et al. (2021), data collected and analysed is done with technology based on the location-based service which includes data science. Data science helped in the proper analysis of data in Hubei province and the cases of Covid were recognised with the help of data science and analysed by data science. Corona virus has various impacts on the economy and has various methods implemented for calculating the economic return. The economic return was calculated by a power function method, which is termed as Douglas Production Function. This analysis is conducted in different regions of china generating data for the calculation of returns to mobility scale. The formula for the conduction of research in terms of economical loss is calculated with the help of population and the loss incurred according to the regional basis. Power function gives a clear description of the data with the help of Y and Njti, "when γ (ratio of the outflow to the total city population) increases by 1%, the value of Nj, ti→ increases by 0.5%". These projects to the effect of migration will increase with the increase with a lower rate as compared to migration scale. However, according to Annas et al (2020), the case of Covid was noticed fin Indonesia conducted a mathematical analysis using a different model, which includes "SIR, SIRS, SEIR and SEIR" where the SEIR model is used to analyse through isolation and vaccination process using the Matlab software. 

Effect of covid19 on different regions

According to Wei et al. (2021), the increase in the spread of the virus is done to the increase in the interaction among the people or the migrants. The implementation of the network as a support to reduce the spread of the virus has a huge impact on stopping the spread of covid. Social interaction among the people was noticed and the spread of the pandemic was computed and calculated data-wise. This has increased in number gradually and has increased the data to the highest extent, the data controlling has reduced to its lowest, and this was controlled with the help of data ecology and data science. The proper analysis of spread cases according to the city network process in various regions of china. Data collection was conducted by a data science, which includes persons with respiratory illness, fever and weakness. This was conducted all over the world in 100 countries and the cases were noted accordingly.  The process of noting the data was done with the help of data science as it is large data to be controlled in a general process. The process is controlled with the help of data science and data ecology. However, according to Annas et al (2020), the software is used to analyse data regarding various viral diseases such as dengue fever, diabetes, tuberculosis and HIV-AIDS with the help of mathematic models and mathematical software. The numbers were calculated by mathematical software and Matlab software.  

According to Chatterjee et al. (2022), data collection is done with the help of machine learning technology and various models, which include various models such as SIR, SIRS, SEIR and SEIR. These are the data collection method that helps in properly analysing the data rather than using data science and data ecology. This research process includes gathering data from government websites where data science was used as an effective process of managing the data. The data introduced in this research process was gathered from different websites, which include mohfw.gov.in and coronavirus.jhu.edu these websites were used for various rule-based machines learning technology. This research process includes a machine learning process that includes a large data set with biological content in it. This process includes the “problem of identifying important climatic and socio-demographic factors responsible for the intensity of the COVID-19 outbreak in a particular country, state, or region”. The research focuses on the climate and social demographical factors of different regions, which also include temperature, humidity and predictor and population density.  

However, according to  Alotaibi, N., (2021), the data provided gives a statistical representation that provides an effective process of data science analysis as well as data ecology. It provides data on Indian infected in different regions and data was provided in various aspects, which include count, summation average and variance. The data was represented in a statistical method that includes estimated density and data in a graphical representation process. This calculation and data representation is conducted by the data science process and data ecology. ARIMA (“Autoregressive integrated moving average”) process is also been used for examining the covid representation in Saudi Arabia.

Provide a graphical representation of the data

Figure 1: Provide a graphical representation of the data

However, according to Mee et al. (2022), the process various data collection processes were used for the collection and data analysing process. This process also includes data science methods of data analysing and data management the software used for the data analysis process in this research process includes "PMI, NA, OJB & FdJCG" This software was used for the first draft and manuscript. The supporting applications that have a great influence on the contribution of data analysis in statistical methods include SA, KP & CAPJ. This helped in the proper analysis of the data collected for research purposes. 

Relationship between data ecology and data science

Data ecology can be recognised as a branch of biological, environmental, and Earth sciences that has entered into the world of big data. Big data is a significant presence of data science that is associated with opportunities and challenges for the environment and society. In this aspect, increasing rates of data generation, interpretation, and aggregation based on ecological sustainability and its integration are responsible for the growth of data volumes. The rapid growth of data volumes concerning ecological data collection helps to increase the effectiveness of analytical aspects concerning the utilisation of computational approaches. During the COVID-19 pandemic situation, data science enables to achieve remarkable growth due to adopting multi-agent technology and networking concerning the utilisation of big data. This growing utilisation of big data in different activities for overcoming ecological challenges plays a   crucial role in constructing and developing a “city-based epidemic and mobility model” to deal with the spatiotemporal of COVID-19.

According to Wei et al. (2021) "City-based epidemic and mobility model   refers to the implementation of the transformational network through increasing spread rate without concerning geographical differentiation such as urban and rural that contribute to spreading connectivity and transportation among intercity. Apart from that, it can be stated that the integration of data science with the implementation of Big data contribute to evaluating transportation system without concerning environmental issues and maintaining control measure during COVID-19 such as social distancing, lockdown and reduction of population mobility. 

However, according to Annas et al (2020), on the other hand, innovation and up-gradation of the SEIR model are based on the utilization of big data and artificial intelligence which is defined as a part of data science. SEIR model is responsible for simulating the time histories concerning events and pandemic situations and epidemic phenomena concerning ecological uncertainty. The classical form namely the SEIR model works as a medium for conducting mutual and dynamic communication and interaction among people that are associated with four different conditions including susceptible, exposed, infective, and recovered. 

According to Annas et al (2020), the SEIR model helps to measure different parameters such as isolation factors and vaccination during the COVID19 pandemic situation and its generation matrix method helps to analyse the increasing rate of COVID patients with numerical simulation. Therefore, the SEIR model plays a significant role in global stability by providing information and delivering a dynamic interaction during the COVID-19 pandemic situation. 

Hypotheses: Data analysis must be conducted with the help of data science and data ecology as it provides an effective and easy way to analyse the data. 

Impact of Covid on country socio demography 

According to Chatterjee et al. (2022), Covid 19 badly impact the country's economic condition, it badly influenced the company supply chain management process and influences the country's health care systems.  After the spread of this various impact on the country's demographic condition, it increased the rate of mortality and also affects the adult person health statutes. Its outs break the social groups and populations in the country, reduce the prevalence of poverty, and affect the country's population and the country's economic condition. The high mortality rate imbalances any country's socio-demographic.

According to Drefahl et al. (2020), this study was performed on the climatic and the country's social demographic conditions impacts during this world pandemic situation. This study is based on quantitative research and its analysis of the socio-demographic condition and climatic. The socio-demographic depends on the recovery, death and infection rate.  After this study analysis, and discusses the rate of country death, during this pandemic situation country death rate is too increased and the recovery rate is low. More significantly process the importance of the digit of recoveries, deaths and infections hanging on the time of lockdown, the availability of vaccination process in the country.  The most interesting part notices that the infection is low when the country temperature is high, but also the infection is increased when the country temperature is low.   

According to Hradsky (2021), the different socio-demographic condition is depends on the high and low temperatures and humidity in the country.  Comprehending this kind of research, mining this type of rule Fuzzy association could be the primary part of the explanation. Interestingly, the study of additional patient-wise data such as age variety among the digit of persons infected, the mortality rate is could be a valuable factor.  This study identifies fascinating societies among socio-demographic and climatic elements reliable for the outbreak intensity of the region-specific. It Forecasts potential region-specific future flare-ups and comprehends the fuzzy connections between different points in the fuzzy contain. 

Impact of Mobility on Covid 19 

According to Zargari, et al. (2022), this pandemic situation badly impact the country's mobility rate and ratio.   It badly impacts the country's travel and transportation business, mostly in the Covid 19, this lockdown process badly influences the country's travel chain management.  This study describes the relationship between intra-city and inter-city mobility activities. The effects notice that the movements passenger-kilometres variable stand for statistically meaningful for the long-term lags, though the inter-city travel changing stands for statistically meaningful for twice the long-term and short-term. It affects the country's transportation rate, this Covid 19 country transportation businesses were highly affected by the lockdown, and this country's travel chain is badly imbalanced. During this Covid 19, the travel ban increased and it negatively influenced the country's mobility rate and ratio.  It hampers the country's economic condition and also affects the country's travel and transportation. Travels to general transportation stations dropped especially in every nation without any exceptions. The bulk of nations has experienced a decrease between “-60 and -80%”.  It affected the country's earning revenue and the social factors, its hamper the $9.8 trillion of the total economy.  Its affects the middle-class country's economic condition and this Covid 19 infection is increased the demographical mortality rate but also affects the country's overall parts. 

According to Kuo (2021), this Covid19 impacts the present mobility rate, in this Covid 19 situation, each country's education system is badly hampered and also hampered the country's financial or economic condition.  In mid-march, the lockdown is affects the country's mobility rate and hampered the country's dedication systems. The remote conditions heavily affect the course's current situation.   During this lockdown situation Covid, 19-infection spread ratio is low and also decreased in the future week. It has influenced the food chain and impacts agricultural management. It decreased the work culture and increased the mortality rate in any country.  Its effect the public health, condition, and the country's management plan.  In this pandemic situation, the machine learning process is to identify the patient's data and information.  In this Covid, 19 million of person faces a jobless situation;   this machine learning collects the patient's data and information and identifies the patient's medical resources during this Covid 19 hospitalization. The weakened prime with weekly practices for mobility or daily issues also indicated high conditions this weekend.  Millions of companies encounter an existential hazard, almost half of the world’s 3.3 billion global workforce’s stand at the hazard of failing their livelihoods. Casual economising workers are especially weak the reason of the lack of majority social security and key to the quality of health maintenance and maintaining the lost key to effective assets. 

Lima et al.  (2021) according to this study, effects shown for various classes of mobility conditions indicate that the capacity decreases as the mobility decreases, while there is an expansion of closeness between’s for some web nodes. Normally, the simulation indicated that decreasing mobility is useful in floating the Covid 19 disease infection curve. In this situation, the person wearing the mask reduces the spread of the Covid infection to the low fight of the person.  These study scenarios have mentioned the flattening of the graph without restriction mobility.  It improved the mobility rate in the country and reduces the country Covid 19 infection effects, This study tracing and the testing condition are vital to make the mobility limitation more adaptable and flexible.  This Covid 109 badly impacts the company and the country's supply chain management process. It badly influences the country's economic condition and company management. During this coding 19 situation, the world health policy is badly affected; it is breaking the world demographic rate and the ratio. 

The emergencies are disparities uses of online applications in Brazil

According to Mee et al. (2022) during this Covid 19 Brazil’s country death rate are too increased and the economic condition is badly hampered.  The online application is helping during this Covid 19, this online application collected real-time data and measure Brazil’s death rate or recovery rate.  This web application is helpful in the Covid 19 pandemic situation, in the lockdown situation country's economic condition is too low and the customer mortality rate is this high. This online application is good for the work from the home condition and it recovers the country's economic condition and increases the country's earning revenue.  This online application is decreased the spread of infection and balances the mortality rate, it is also beneficial for the business and company policy. This study provided the country with monitoring, analysing and standardising the developments of the epidemic at the social levels, and understandings can be achieved in temporal and spatial heterogeneity. It affects the large numbers of the country's employment conditions and the health or social care management sectors.  The online application simply evaluates the country's economic management in the Brazil country.   During this Covid 19 Brazil country uses a variety type of apps it reduces the Covid 19 infection and increases the recovery rate. This online application uses is beneficial for the Covid 10 situations and it helps to improve the county's death rate and the birth rate ratio. 

Identification of climatic changes in Covid 19 

According to Hepburn et al. (2020), during this Covid 19 situation and the outbreak of the county climatic factors, this spread of infection badly impacts the country's climatic change. In this Covid 19 situation climate population is too increase and it negatively influences the Covid-19 infection. After analysis of this study, when the temperature is low this pandemic disease is high and if the temperature is high this Covid 19 infection spread is low. Mainly this Covid 19 infection has highly influenced the country and world environment temperature and humidity. According to Jaspal, (2020) Covid 19 creates various types of impacts on climatic changes, this infection depends on the climate, and this infection is influenced by population density. The impacts of Covid-19 have been creating a negative effect on the different kinds of countries related to Tehran, and Iran that have been making indicators and developing the cultures of relationship modules by generating the ultimate ranges of values. According to Barouki et al. (2021), the authors have created interpretations by transacting the intercity trips data and making a discussion of the mobility and controlling rates. After analysing the impacts of the research context it can be stated that the in the era of Covid-19 situations the usage of government control boards and adaptations of effective policies have increased the rates of environmental infrastructures module.  This disease is not only an infectious disease it is also the connection between climate and environmental factors.  This disease is linked to climatic changes; this disease damages the environmental systems and the epidemic disease. It impacts the wide-reaching climate changes and the environmental damage of the reserve. 

Conclusion 

 A preview of ecological aspects and integration of data science helps to conclude that data science plays a vital role in managing different ecological obstacles through the utilization of technology-based innovation namely the SEIR model and the "City-based epidemic and mobility model". SEIR model was developed through utilized AI technology for learning about updated information on COVID-19. “City-based epidemic and mobility model” developed by big data for encouraging transportation systems during the COVID-19 pandemic situation. The data collection process has various methods for the analysis of data which includes data science and data ecology processes. The various research processes include different types of data collection processes such as statistical processes and data analysing by different websites which ultimately leads to an effective way of data representation. 

References

Alotaibi, N., 2021. Statistical and deterministic analysis of covid-19 spread in Saudi Arabia. Results in Physics28, p.104578. https://doi.org/10.1016/j.rinp.2021.104578 

Annas, S., Pratama, M.I., Rifandi, M., Sanusi, W. and Side, S., 2020. Stability analysis and numerical simulation of SEIR model for pandemic COVID-19 spread in Indonesia. Chaos, Solitons & Fractals139, p.110072. https://doi.org/10.1016/j.chaos.2020.110072 

Barouki, R., Kogevinas, M., Audouze, K., Belesova, K., Bergman, A., Birnbaum, L., Boekhold, S., Denys, S., Desseille, C., Drakvik, E. and Frumkin, H., 2021. The COVID-19 pandemic and global environmental change: Emerging research needs. Environment international146, p.106272. https://www.sciencedirect.com/science/article/pii/S0160412020322273

Chatterjee, S., Chakrabarty, D. and Mukhopadhyay, A., 2022. Fuzzy association analysis for identifying climatic and socio-demographic factors impacting the spread of COVID-19. Methods203, pp.511-522. https://doi.org/10.1016/j.ymeth.2021.08.005 

Chatterjee, S., Chakrabarty, D., & Mukhopadhyay, A. (2022). Fuzzy association analysis for identifying climatic and socio-demographic factors impacting the spread of COVID-19. Methods, 203, 511-522. https://doi.org/10.1016/j.ymeth.2021.08.005

Drefahl, S., Wallace, M., Mussino, E., Aradhya, S., Kolk, M., Brandén, M., Malmberg, B. and Andersson, G., 2020. A population-based cohort study of socio-demographic risk factors for COVID-19 deaths in Sweden. Nature communications11(1), pp.1-7. https://www.nature.com/articles/s41467-020-18926-3

Hepburn, C., O’Callaghan, B., Stern, N., Stiglitz, J. and Zenghelis, D., 2020. Will COVID-19 fiscal recovery packages accelerate or retard progress on climate change?. Oxford Review of Economic Policy36(Supplement_1), pp.S359-S381. https://academic.oup.com/oxrep/article-abstract/36/Supplement_1/S359/5832003

Hradsky, O. and Komarek, A., 2021. Demographic and public health characteristics explain large part of variability in COVID-19 mortality across countries. European journal of public health31(1), pp.12-16. https://academic.oup.com/eurpub/article-abstract/31/1/12/6106197

Jaspal, R. and Nerlich, B., 2020. Social representations, identity threat, and coping amid COVID-19. Psychological Trauma: Theory, Research, Practice, and Policy12(S1), p.S249. https://psycnet.apa.org/record/2020-37262-001

Kuo, C.P. and Fu, J.S., 2021. Evaluating the impact of mobility on COVID-19 pandemic with machine learning hybrid predictions. Science of The Total Environment758, p.144151. https://www.sciencedirect.com/science/article/pii/S0048969720376828

Lima, L.L. and Atman, A.P.F., 2021. Impact of mobility restriction in COVID-19 superspreading events using agent-based model. Plos one16(3), p.e0248708. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0248708

Mee, P., Alexander, N., Mayaud, P., González, F. D. J. C., Abbott, S., Santos, A. A. D. S., Acosta, A. L., Parag, K. V., Pereira, R. H., Prete, C. A., Sabino, E. C., Faria, N. R., & Brady, O. J. (2022). Tracking the emergence of disparities in the subnational spread of COVID-19 in Brazil using an online application for real-time data visualisation: A longitudinal analysis. The Lancet Regional Health - Americas, 5, 100119. https://doi.org/10.1016/j.lana.2021.100119

Mee, P., Alexander, N., Mayaud, P., Gonzalez, F.D.J.C., Abbott, S., de Souza Santos, A.A., Acosta, A.L., Parag, K.V., Pereira, R.H., Prete Jr, C.A. and Sabino, E.C., 2022. Tracking the emergence of disparities in the subnational spread of COVID-19 in Brazil using an online application for real-time data visualisation: A longitudinal analysis. The Lancet Regional Health-Americas5, p.100119. https://doi.org/10.1016/j.lana.2021.100119 

Wei, Y., Wang, J., Song, W., Xiu, C., Ma, L. and Pei, T., 2021. Spread of COVID-19 in China: analysis from a city-based epidemic and mobility model. Cities110, p.103010. https://doi.org/10.1016/j.cities.2020.103010 

Zargari, F., Aminpour, N., Ahmadian, M. A., Samimi, A., & Saidi, S. (2022). Impact of mobility on COVID-19 spread – A time series analysis. Transportation Research Interdisciplinary Perspectives, 13, 100567. https://doi.org/10.1016/j.trip.2022.100567 

Zargari, F., Aminpour, N., Ahmadian, M.A., Samimi, A. and Saidi, S., 2022. Impact of mobility on COVID-19 spread–A time series analysis. Transportation Research Interdisciplinary Perspectives13, p.100567. https://doi.org/10.1016/j.trip.2022.100567

Recently Downloaded Case Studies by Customers
Our Exceptional Advantages
Complete your order here
54000+ Project Delivered
Get best price for your work

Ph.D. Writers For Best Assistance

Plagiarism Free

No AI Generated Content

offer valid for limited time only*