Dissertation Proposal – Global Homework Experts

 

 

Digital technologies in the public-health response to COVID-19

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Assessment 1 – Dissertation Proposal (Draft )

 

                         Student Name: Aneesh Sama

         Student ID: 2011790

                       Module Code: 7ET023/UM4

                      Module Name: Dissertation

                                           Course Name: MSc in Computer science with professional practice

                            Supervisor- Dr. Rupert Simpson

 

 

 

 

 

 

Table of Contents

Introduction. 2

Background. 3

Aim.. 6

Research Questions. 6

Deliverables. 7

Artefact 8

Evaluation. 8

Dissertation Plan. 11

Hardware/Software needed. 12

References. 13

 

 

 

Contact tracing, case identification, population monitoring, and treatment evaluation based on mobility data and public messaging are all being used to help “the public health response to COVID-19” (Wang et al., 2021). Rapid responses are now possible because of the convergence of a wide range of technologies, including mobile phones, networked devices, large internet databases, and low-cost computing resources. When it comes to COVID-19’s public health response to digital innovations, there were ethical, legal, and privacy difficulties, and organizational and workforce issues that impeded implementation, according to Budd and colleagues (2020). In order to improve management and prepare for “COVID-19 and other infectious diseases” in the future, it is necessary to assemble international approaches and strategies for the evaluation, regulation, and usage of digital technology. Digital technologies employed in COVID-19 are shown in the following image.

Figure 1: Digital technologies used for COVID-19

(Source: Budd et al., 2020)

COVID-19 pandemic has received significant assistance from IT businesses. Most of the world’s finest digital technology professionals joined in a virtual roundtable to aid WHO’s (World Health Organization) joint response to COVID-19. Due to the enormous need for digital health technology solutions created by the present pandemic, innovative approaches to prioritizing resource allocation, population screening, monitoring the infection, and planning tailored interventions have emerged (Zimmerling and Chen, 2021).

Hence, the present research is proposed to enlighten several “digital technologies in the public health response to COVID-19 worldwide”. At the same time, it will also state how technological adoption has contributed to the fast detection and treatment of COVID-19. Consequently, a summary of digital technology application issues in public health is provided. There are four key causes of these problems: data sluggishness, privacy concerns, data fragmentation, and data security holes (Fagherazzi et al., 2020). Last but not least, this research aims to explore the potential uses of digital healthcare shortly.

In order to evaluate how digital technologies are being used to combat COVID-19 in public health throughout the globe, it is to add that the usage of digital technologies has allowed researchers, medical practitioners, and several other associated individuals to allow the emergence of adequate solutions with a fast pace (Fahey, and Hino, 2020). Big data, AI,5G, and cloud computing, are the most powerful digital arms used in the fight against the COVID-19 pandemic (Chettri, Debnath, and Devi, 2020). It is clear from real-world examples that these tools are vital in preventing the COVID-19 from spreading. This study is proposed to showcase that to avert the second COVID-19 pandemic, the countries that were affected mostly must combine digital technology and public health on an extensive scale without reluctance.

In the face of the COVID-19 pandemic, digital technology mainly changed how individuals responded and outlasted the evident cultural shifts of the information age. The government portals showcased significant support to individuals by providing adequate information (www.un.org, 2020) (Fig 2). Information is abundant in today’s world, which necessitates the adoption of innovative approaches to organizing data, reporting, operational planning, and epidemiological monitoring, among other “public health-related operations”. Digital change in health care was accelerated by the COVID-19 pandemic, which provided a rare chance to introduce new technology into health care systems. Using digital technology to innovate in response to a public health emergency requires cultural change and a commitment to improving quality and user happiness while advancing the cause of health promotion and preservation.

Figure 2: Percentage of government portals with COVID-19 information

(Source: www.un.org, 2020)

In today’s health care environment, statistics are an integral part of every organization. The cost and time required to build scientific evidence for therapies might be dramatically reduced with its utilization. Although these data might be used to enhance evidence-based decision-making, they have already been documented in the literature. Public health infrastructure is required to adequately monitor and control such data, which requires the acceptance and use of digital technologies (Fagherazzi et al., 2020). “Cross-sectional data on Internet use and epidemic risk for 180 economies” indicates nations with more access to the internet and more secure internet infrastructure are more robust to epidemics like COVID (JIANG, and RYAN, 2020) (Fig 3).

Figure 3: “Safer internet servers and wider internet access are strongly correlated with lower risk for epidemics”

(Source: JIANG, and RYAN, 2020)

The proposed research aims to state how further disasters like the COVID-19 storm will need individuals to depend on digital technologies increasingly. People might access official information, accept online jobs, participate in e-courses, transact digital money, and even get telemedicine. Evaluating the applied digital technologies during COVID-19 will highlight how the broad adoption of digital tools can help develop more resilient communities (JIANG and RYAN, 2020). Fig 4 illustrated the connection between community engagement and health equity and outcomes as well as collaboration across sectors and showcased a resilience framework.

Figure 4: “Determinants of health systems resilience framework”

(Source: Haldane et al., 2021)

The research will identify and evaluate the application of digital technologies and evaluate its benefits and challenges in “the public-health response to COVID-19” in the context of the countries where COVID-19 impacts were more significant compared to other countries.

By the end of the research, the answers to the following questions should be achieved,

  • Did the applied digital technologies contribute to the fast detection and treatment of COVID-19 through,
    • Accelerating digital health technology solutions
    • Successful information management circulation across different nations
    • Created challenges in digital healthcare
  • Did the technological influences during COVID 19 acquires potentials to develop successful,
    • Digital communication artefacts
    • Information communication among different nations
    • Successful usage of online forms in order to trace pandemic
  • How the emergence of online forms increased effectiveness under national communication in terms of,
    • Monitoring effects of particular diseases
    • Collecting first hand information regarding particular healthcare services
    • Enhanced informational backings to healthcare centres

The proposed work will summarise the overall research around the usage of digital technologies to fight COVID-19, and the research will be presented in the form of a dissertation, which will be a written document and mobile application development . Public and private enterprises throughout the world are promoting data collecting and processing via digital public health technology as key solutions for combating the COVID-19 epidemic and relaxing lockdown restrictions. However, the ethical and legal bounds of using digital technologies for disease surveillance and control are unknown, and a global discussion over the benefits and hazards of using digital tools for public health has erupted. Proximity and contact tracing, symptom monitoring, quarantine control, and flow modelling are all examples. We go over context-specific dangers, cross-sectional challenges, and ethical considerations for each one. Forecasting new outbreaks, promptly alerting, and isolating exposed individuals, thereby preventing or reducing new infections, improving quarantine measures, improving the efficiency of social care and vaccine development, and improving how information is communicated to citizens are all possible benefits associated with these technologies.

As stated by Bryson, (2018), artefacts refer to the factors that societies and cultures creates for their own use. In the context of the present research artefacts can be indicated towards the online forms like Trace COVID and Microsoft forms created by a number of healthcare centres in order to monitor COVID-19 patients and create issues mitigating strategies accordingly. The present research aim to mainly track and trace the users health condition through mobile Application. Mobile application is developed by using react. It will be therefore stated how such development impacted in the mitigating actions of COVID pandemic. Such application was mainly created using firebase, google Api. It helped majorly with the monitoring process through individual responses. Therefore, the research traced the development processes of such forms, their applications and results.

The evaluation will take place through a narrative analysis method as research is mainly based on qualitative strategy. A number of findings will be gathered following the research aim and objectives. Therefore in order to evaluate these findings, the narrative analysis will be applied.

Narrative data analysis will assess the information that existing research papers have provided (Feely, 2020). Hence with the help of narrative analysis, it will be possible to find what their statement indicated about the subject as well as about the problem the research has attempted to state. Several literature subjects will mainly be the core of the analysis process.

As the proposed research is attempting to find and follow a process to analyses the importance and relevance of information, the utilization of the narrative data analysis method is justified.

The narrative analysis method will help the researcher to take into consideration the bias of existing researchers will also be included in this evaluation, as well as any misplaced importance will be addressed by the researcher and by putting own opinion (Debnath et al., 2020).   As an example, the researcher can observe that in a pre-existing study, a certain survey respondents’ information was collected. The respondents overestimated the severity of their condition after collecting data from many individuals. In this case,  to perform the narrative data analysis, the researcher needs to analyse how much weight the previous researcher gave to their perception and whether or not that weight is justified (Rashid et al., 2021). The following figure in this case showcases a framework for distinct narrative analysis.

Figure 5: Crash Narrative analysis framework

(Source: Das et al., 2020)

 

In order to specifically showcase how the proposed research will evaluate data, in this case, the proposed data analysis is showcased here briefly.

From the study of Prado et al., (2021), a certain finding emerged that creating digital online care pathways that combine digital symptom checkers, fast testing with contact tracking, long-term clinical follow-up, and epidemiological information, is essential in terms of reducing costs and ensuring the sustainability of digital health care.

 

The study has stated that Covid-19 has highlighted the importance of “data sharing and rigorous assessment” and “ethical frameworks with community engagement” are necessary for the burgeoning area of mobile digital healthcare (Ienca, and Vayena,2020). It is also established that public confidence has been increased by using effective communication techniques across all digital platforms and by showcasing a commitment to reasonable privacy protections.

 

With the usage of the narrative analysis method, it can be stated that the researcher has perceived the information of digital technology adoption effectively and positively. Through the research perception, it becomes clear that digital technology has not only been brought in by COVID-19 but its implications in healthcare were rather lagging behind significantly and the wave of COVID-19 and its requirements has boosted digital health care significantly. Hence, the overall research was focused on discovering how digital technology applications aided significant development.

On the other hand, Islam et al., (2020), have highlighted the matter of misinformation spreading and social media fatigue (SMF). The researcher stated that deficient self-regulation (DS-R) and religion all predicted social media distribution of unsubstantiated COVID-19 material, as did small and medium businesses and other exploratory, self-promotional, entertaining, and entertainment factors (Islam et al., 2020). The researcher stated that it was the DS-R constructs of exploration and self-promotion that had the most significant influence on the participants. Exploration had a detrimental impact, but self-regulation and self-promotion have been efficient influences.

The researcher emphasized the factor that the spread of unconfirmed information was mostly unaffected by any of the other variables. As a result, the researcher uncovered more influences on the spread of COVID-19 disinformation (Apuke, and Omar, 2021). Furthermore, confidence in online information and information overload are stated as the most important aspects. When it comes to spreading unverified information, the researcher discovered that the most important elements were self-regulation, exploration, and self-promotion. These findings showcased that the spread of false information has influenced these variables as well.

According to the study, information and communication overload might be the two most essential elements that contribute to SMF.  On the contrary, it was found that self-regulation and exploration were the most significant predictors of misinformation spread by social media. PLS-SEM and NN methods were used in the present investigation to support these results.

 

With the use of narrative analysis technique, it can be analysed that, on one side, existing research papers stated that digital technologies have brought significant benefits to health care. On the other side, the use of social media fatigue has also been brought in by existing research papers that have highlighted how individuals mis-used the application of digital technologies in healthcare (Whelan, Islam, and Brooks, 2020). Hence, the researchers’ perception on this matter can be narrated as a vivid perception that digital technology application during COVID-19 not only highlighted the potentials of health care but also highlighted the adverse behaviour of individuals and their capabilities in terms of utilizing information in a negative way.

This is how narrative analysis will help the research to evaluate the collected data and reach the aim and objectives properly.

 

Ethical Consideration-

The present research is proposed to be conducted based on the existing findings from previously conducted research papers. Therefore, the overall research is mainly based on data available on the internet. This is the reason why the research is needed to follow ethics around using internet based research and follow the anti-plagiarism ethics in this case. Consequently, all of the borrowed information will be cited properly following appropriate referencing format, adhering to the copyright ethics. The amount of fabricated data is higher on the internet. Hence, the researcher requires going through all the critical aspects while using the data and making sure that the data is not fabricated. No individual participants involved. One of the ways to make sure that copied or fabricated information are not used in the research is to use articles that are cited less than seven times. Human data is not collected from the individuals for examples, names, phone number, email address, IP addresses, physical characteristics, photos and videos Furthermore, the researcher will only use information presented in the English language so that any and all chances of creating any confusion can be avoided.

Tasks Start Date End Date Duration
Submitting Proposal 15-02-22 25-02-22 09
Gathering required instruments 26-02-22 04-03-22 06
Creating research structure 05-03-22 15-03-22 15
Data Collection 16-03-22 24-03-22 08
Literature Review 25-03-22 02-04-22 08
Mobile Application Development 03-04-22 14-04-22 11
Data Analysis and Findings 15-04-22 21-04-22 06
Results gathering and Discussion 22-04-22 28-04-22 06
Conclusion 29-04-22 04-05-22 06
Completing the research 05-05-22 10-05-22 05
Submission 11-05-22 15-05-22 04

Table: Timeline

(Source: Created by the learner)

 

 

Figure 6: Giant Chart

(Source: Created by the learner)

As the research will be secondary qualitative research, resources required for the study are all aligned perfectly with the term “desk-based research”. The following the very few resources in terms of hardware and software required for the study,

  1. Visual Code Editor
  2. React Native
  3. Expo
  4. Github
  5. MySQL

 

 

References

Apuke, O.D. and Omar, B., 2021. Fake news and COVID-19: modeling the predictors of fake news sharing among social media users. Telematics and Informatics56, p.101475.

Bryson, J.J., 2018. Patiency is not a virtue: the design of intelligent systems and systems of ethics. Ethics and Information Technology20(1), pp.15-26.

Budd, J., Miller, B.S., Manning, E.M., Lampos, V., Zhuang, M., Edelstein, M., Rees, G., Emery, V.C., Stevens, M.M., Keegan, N. and Short, M.J., 2020. Digital technologies in the public-health response to COVID-19. Nature medicine26(8), pp.1183-1192.

Chettri, S., Debnath, D. and Devi, P., 2020. Leveraging digital tools and technologies to alleviate the COVID-19 pandemic. Available at SSRN 3626092.

Das, S., Dutta, A., Dey, K., Jalayer, M., and Mudgal, A., 2020. Vehicle involvements in hydroplaning crashes: Applying interpretable machine learning. Transportation research interdisciplinary perspectives6, p.100176.

Debnath, R., Darby, S., Bardhan, R., Mohaddes, K. and Sunikka-Blank, M., 2020. A nested computational social science approach for deep-narrative analysis in energy policy research.

Fagherazzi, G., Goetzinger, C., Rashid, M.A., Aguayo, G.A. and Huiart, L., 2020. Digital health strategies to fight COVID-19 worldwide: challenges, recommendations, and a call for papers. Journal of Medical Internet Research22(6), p.e19284.

Fagherazzi, G., Goetzinger, C., Rashid, M.A., Aguayo, G.A. and Huiart, L., 2020. Digital health strategies to fight COVID-19 worldwide: challenges, recommendations, and a call for papers. Journal of Medical Internet Research22(6), p.e19284.

Fahey, R.A. and Hino, A., 2020. COVID-19, digital privacy, and the social limits on data-focused public health responses. International Journal of Information Management55, p.102181.

Feely, M., 2020. Assemblage analysis: An experimental new-materialist method for analysing narrative data. Qualitative Research20(2), pp.174-193.

Haldane, V., De Foo, C., Abdalla, S.M., Jung, A.S., Tan, M., Wu, S., Chua, A., Verma, M., Shrestha, P., Singh, S. and Perez, T., 2021. Health systems resilience in managing the COVID-19 pandemic: lessons from 28 countries. Nature Medicine27(6), pp.964-980.

Ienca, M. and Vayena, E., 2020. On the responsible use of digital data to tackle the COVID-19 pandemic. Nature medicine26(4), pp.463-464.

Islam, A.N., Laato, S., Talukder, S. and Sutinen, E., 2020. Misinformation sharing and social media fatigue during COVID-19: An affordance and cognitive load perspective. Technological forecasting and social change159, p.120201.

JIANG, N. and RYAN, J., 2020. How does digital technology help fight against COVID-19?. [online] World Bank Blogs. Available at: <https://blogs.worldbank.org/developmenttalk/how-does-digital-technology-help-fight-against-covid-19> [Accessed 22 February 2022].

Prado, N.M.D.B.L., Biscarde, D.G.D.S., Pinto Junior, E.P., Santos, H.L.P.C.D., Mota, S.E.D.C., Menezes, E.L.C.D., Oliveira, J.S. and Santos, A.M.D., 2021. Primary care-based health surveillance actions in response to the COVID-19 pandemic: contributions to the debate. Ciência & Saúde Coletiva26, pp.2843-2857.

Rashid, R., Chen, Y.A., Hoffer, J., Muhlich, J.L., Lin, J.R., Krueger, R., Pfister, H., Mitchell, R., Santagata, S. and Sorger, P.K., 2021. Narrative online guides for the interpretation of digital-pathology images and tissue-atlas data. Nature Biomedical Engineering, pp.1-12.

Saunders, M., Lewis, P. and Thornhill, A., 2003. Research methods for business students. Essex: Prentice Hall: Financial Times.

Wang, Q., Su, M., Zhang, M. and Li, R., 2021. Integrating digital technologies and public health to fight Covid-19 pandemic: key technologies, applications, challenges and outlook of digital healthcare. International Journal of Environmental Research and Public Health18(11), p.6053.

Whelan, E., Islam, A.N. and Brooks, S., 2020. Is boredom proneness related to social media overload and fatigue? A stress–strain–outcome approach. Internet Research.

www.un.org, 2020. [online] Available at: <https://www.un.org/development/desa/dpad/publication/un-desa-policy-brief-61-covid-19-embracing-digital-government-during-the-pandemic-and-beyond/> [Accessed 22 February 2022].

Zimmerling, A. and Chen, X., 2021. Innovation and possible long-term impact driven by COVID-19: Manufacturing, personal protective equipment and digital technologies. Technology in Society65, p.101541.