Combating COVID-19 Pandemic Research Articles

Early acquisition of S-specific Tfh clonotypes after SARS-CoV-2 vaccination is associated with the longevity of anti-S antibodies.

SARS-CoV-2 vaccines have been used worldwide to combat COVID-19 pandemic. To elucidate the factors that determine the longevity of spike (S)-specific antibodies, we traced the characteristics of S-specific T cell clonotypes together with their epitopes and anti-S antibody titers before and after BNT162b2 vaccination over time. T cell receptor (TCR) αβ sequences and mRNA expression of the S-responded T cells were investigated using single-cell TCR- and RNA-sequencing. Highly expanded 199 TCR clonotypes upon stimulation with S peptide pools were reconstituted into a reporter T cell line for the determination of epitopes and restricting HLAs. Among them, we could determine 78 S epitopes, most of which were conserved in variants of concern (VOCs). After the 2nd vaccination, T cell clonotypes highly responsive to recall S stimulation were polarized to follicular helper T (Tfh)-like cells in donors exhibiting sustained anti-S antibody titers (designated as 'sustainers'), but not in 'decliners'. Even before vaccination, S-reactive CD4+ T cell clonotypes did exist, most of which cross-reacted with environmental or symbiotic microbes. However, these clonotypes contracted after vaccination. Conversely, S-reactive clonotypes dominated after vaccination were undetectable in pre-vaccinated T cell pool, suggesting that highly responding S-reactive T cells were established by vaccination from rare clonotypes. These results suggest that de novo acquisition of memory Tfh-like cells upon vaccination may contribute to the longevity of anti-S antibody titers.

Early acquisition of S-specific Tfh clonotypes after SARS-CoV-2 vaccination is associated with the longevity of anti-S antibodies

SARS-CoV-2 vaccines have been used worldwide to combat COVID-19 pandemic. To elucidate the factors that determine the longevity of spike (S)-specific antibodies, we traced the characteristics of S-specific T cell clonotypes together with their epitopes and anti-S antibody titers before and after BNT162b2 vaccination over time. T cell receptor (TCR) αβ sequences and mRNA expression of the S-responded T cells were investigated using single-cell TCR- and RNA-sequencing. Highly expanded 199 TCR clonotypes upon stimulation with S peptide pools were reconstituted into a reporter T cell line for the determination of epitopes and restricting HLAs. Among them, we could determine 78 S epitopes, most of which were conserved in variants of concern (VOCs). After the 2nd vaccination, T cell clonotypes highly responsive to recall S stimulation were polarized to follicular helper T (Tfh)-like cells in donors exhibiting sustained anti-S antibody titers (designated as ‘sustainers’), but not in ‘decliners’. Even before vaccination, S-reactive CD4+ T cell clonotypes did exist, most of which cross-reacted with environmental or symbiotic microbes. However, these clonotypes contracted after vaccination. Conversely, S-reactive clonotypes dominated after vaccination were undetectable in pre-vaccinated T cell pool, suggesting that highly responding S-reactive T cells were established by vaccination from rare clonotypes. These results suggest that de novo acquisition of memory Tfh-like cells upon vaccination may contribute to the longevity of anti-S antibody titers.

Government Policies in Combating COVID-19 Pandemic in Pakistan: A Gender-based Perspective

Government Policies in Combating COVID-19 Pandemic in Pakistan: A Gender-based Perspective

Prediction and decision making in corona virus using fuzzy mathematical model

During the period of 2019–20, forecasting was of utmost priority for health care planning and to combat COVID-19 pandemic. Almost everyone’s life has been greatly impacted by COVID-19. Understanding how the disease spreads is crucial to know how the disease behaves dynamically. The aim of the research is to construct an SEI Q1Q2 R model for COVID-19 with fuzzy parameters. The fuzzy parameters are the transmission rate, the infection rate, the recovery rate and the death rate. We compute the basic reproduction number, using next-generation matrix method, which will be used further to study the model’s prediction. The COVID-free and endemic equilibrium points attain local and global stability when R0 < 1. A sensitivity analysis of the reproduction number against its internal parameter has been done. The results of this model showed that intervention measures. The numerical simulation along with graphical representations at COVID-free and endemic points are shown. The SEIQ1Q2R model is a successful model to analyse the spreading and controlling the epidemics like COVID-19.

Effectiveness of Covid-19 Vaccine in Pregnant Women: A Systematic Review

The newly developed COVID-19 vaccine faces public's concerns in terms of its effectiveness and safety as an approach in combating COVID-19 pandemic. It is well-established that COVID-19 vaccine is effective alongside being the most promising approach against COVID-19 infection in both general and vulnerable populations. This study aims to evaluate the effectiveness of COVID-19 vaccine in pregnant women as a subgroup of vulnerable population by analysing several important immunological parameters in pregnant women. Specifically, it investigates how effective the COVID-19 vaccine will reduce the infection rate and how it will affect the mothers' antibody levels against SARS-CoV-2. In this study, the immunological parameters investigated are maternal antibody response against SARS-CoV-2 and the transplacental transfer of the antibody. To test the hypothesis that COVID-19 vaccine is effective in pregnant women, a systematic review was conducted on previous studies regarding COVID-19 vaccine and its outcomes in pregnancy. Results were narratively analysed. The results showed reduced COVID-19 infection rate, elevated maternal antibody titre against SARS-CoV-2 and positive transplacental anti-SARS-CoV-2 IgG antibody transfer in vaccinated pregnant women in comparison to unvaccinated pregnant women. These results suggest that COVID-19 vaccine is highly effective against COVID-19 infection in pregnant women. Furthermore, COVID-19 vaccine not only elicits sufficient maternal antibody response as an immunity for mothers against COVID-19 infection but also provides similar protection for infants via passive immunity by means of transplacental antibody transfer. In conclusion, the uptake of COVID-19 vaccine and future booster dose by pregnant women should be strongly encouraged due to its favourable outcomes and protection against COVID-19 disease.

Policies Aimed at Combating COVID-19 Pandemic and Economic Crisis in Poland

Abstract Subject and purpose of work The aim of the paper is to present the course of the COVID-19 pandemic in Poland and measures undertaken in order to prevent the spread of the disease and mitigate its results. The specific objective concerns evaluation of anti-crisis measures enacted during the pandemic in Poland. Materials and methods The paper is based on an analysis of official data provided by state institutions and reports on the course of the pandemic in Poland, as well as academic papers on the subject matter in question. The author employed an analytical and descriptive method in order to outline the course and assess the economic and social phenomena occurring during the pandemic. Results The state of the pandemic in Poland was announced on March 2020 and lifted in May 2023. During that period, Poland experienced two major waves of increased infections and excess deaths, which led to significant biological, economic and social damage, as well as major losses. The state has implemented an efficient and quite effective anti-pandemic measures aimed at protecting the lives and health of citizens, as well as anti-crisis policies to counter and limit the adverse effects of the ongoing pandemic in the form of an extensive financial aid in the form of the so-called Anti-Crisis Fund, which was continuously replenished. Conclusions The COVID-19 pandemic in Poland was an unprecedented and unpredictable phenomenon, which resulted in clear threat to the life and health of the population. It also brought upon a danger of an economic recession and social crisis, which could have resulted in deep economic crisis. The anti-pandemic measures introduced by the Polish government, as well as the anti-crisis measures implemented in quick succession, saved the country from a deep crisis and recession. There is a need for further research into the causes, course, as well as the immediate and long-term impacts of the pandemic.

Artificial Intelligence-Based Chatbots to Combat COVID-19 Pandemic: A Scoping Review

Context: Artificial intelligence (AI) Chatbots are computer programs that simulate human conversation and use artificial intelligence, including machine learning and natural language processing, to interact with users via natural language. With the outbreak of the COVID-19 pandemic, the use of digital health technologies such as chatbots has accelerated. Objectives: This study aims to investigate the application of AI chatbots in combating the COVID-19 pandemic and explore their features. Methods: We reviewed the literature on health chatbots during the COVID-19 pandemic. PubMed, Scopus, Web of Science, and Google Scholar were searched using relevant keywords such as “chatbot”, “conversational agent,” and “artificial intelligence”. To select the relevant articles, we conducted title, abstract, and full-text screening based on inclusion and exclusion criteria. Chatbots, their applications, and design features were extracted from the selected articles. Results: Out of 673 articles initially identified, 17 articles were eligible for inclusion. We categorized the selected AI chatbots based on their roles, applications, and design characteristics. Around 70% of chatbots were designed to play a preventive role. Our review identified 8 key applications of the AI chatbots during the COVID-19 pandemic, which include (1) information dissemination and education, (2) self-assessment and screening, (3) connecting to health centers, (4) combating misinformation and fake news, (5) patient tracking and service delivery (6) mental health (7) monitoring exposure (8) vaccine information and scheduling. AI chatbots were deployed on various platforms, including mobile apps, web, and social media. Mobile-based chatbots were the most frequent. All chatbots used Natural Language Understanding (NLU) methods to understand natural language input and act on the user’s request. More than 50% of AI chatbots used NLU platforms, including Google Dialogflow, Rasa framework, and IBM Watson. Conclusions: AI chatbots can play an effective role in combating the COVID-19 pandemic. Increasing people’s awareness, optimizing the use of health resources, and reducing unnecessary encounters are some of the advantages of using AI chatbots during the COVID-19 outbreak. Using NLU platforms can be a suitable solution for developing AI chatbots in the healthcare domain. With advancements in the field of artificial intelligence, it seems that AI chatbots will have a promising future in healthcare, particularly in public health, chronic disease management, and mental health.

A Study to Assess the Work Stress of Indian Nurses Helping in Combating COVID-19 Pandemic in Sikar

A Study to Assess the Work Stress of Indian Nurses Helping in Combating COVID-19 Pandemic in Sikar

WDCIP: spatio-temporal AI-driven disease control intelligent platform for combating COVID-19 pandemic

ABSTRACT The outbreak and subsequent recurring waves of COVID −19 pose threats on the emergency management and people’s daily life, while the large-scale spatio-temporal epidemiological data have sure come in handy in epidemic surveillance. Nonetheless, some challenges remain to be addressed in terms of multi-source heterogeneous data fusion, deep mining, and comprehensive applications. The Spatio-Temporal Artificial Intelligence (STAI) technology, which focuses on integrating spatial related time-series data, artificial intelligence models, and digital tools to provide intelligent computing platforms and applications, opens up new opportunities for scientific epidemic control. To this end, we leverage STAI and long-term experience in location-based intelligent services in the work. Specifically, we devise and develop a STAI-driven digital infrastructure, namely, WAYZ Disease Control Intelligent Platform (WDCIP), which consists of a systematic framework for building pipelines from automatic spatio-temporal data collection, processing to AI-based analysis and inference implementation for providing appropriate applications serving various epidemic scenarios. According to the platform implementation logic, our work can be performed and summarized from three aspects: (1) a STAI-driven integrated system; (2) a hybrid GNN-based approach for hierarchical risk assessment (as the core algorithm of WDCIP); and (3) comprehensive applications for social epidemic containment. This work makes a pivotal contribution to facilitating the aggregation and full utilization of spatio-temporal epidemic data from multiple sources, where the real-time human mobility data generated by high-precision mobile positioning plays a vital role in sensing the spread of the epidemic. So far, WDCIP has accumulated more than 200 million users who have been served in life convenience and decision-making during the pandemic.

Appraisal of Community’s Sense of Social Support and Social Distancing Measures in Combating COVID-19 Pandemic in Residential Neighbourhoods of Akure, Nigeria

This study used the Sense of Community Index 2 (SCI-2) designed by McMillan & Chavis (1986). However, the SOC indices were slightly modified to account for issues relating to the current pandemic, which was not captured in the McMillian & Chavis study. This paper reports on the relationship between preventive measures to reduce the spread of the pandemic and residents' sense of community in poor neighbourhoods during the COVID-19 pandemic. Questionnaires were administered to household heads of selected poor residential neighbourhoods in Akure, Nigeria, and subjected to frequency distribution and the Pearson moment coefficient analysis to determine the relationship between social distancing and sense of community during the pandemic. The majority of the respondents (99.6%) were aware of the pandemic, and 92.3% adhered to one or more safety measures (personal hygiene, mask, curfew, isolation, and lockdown). The findings also revealed a significant (p=0.05) correlation between a sense of belonging and adherence to pandemic prevention measures in the study area. Therefore, it is essential that decision-makers take into account not only the socioeconomic characteristics of people but also the social concept of their daily existence when determining social policy and service delivery.

The city-wide full-scale interactive application of sewage surveillance programme for assisting real-time COVID-19 pandemic control – A case study in Hong Kong

The paper discusses the implementation of Hong Kong's tailor-made sewage surveillance programme led by the Government, which has demonstrated how an efficient and well-organized sewage surveillance system can complement conventional epidemiological surveillance to facilitate the planning of intervention strategies and actions for combating COVID-19 pandemic in real-time. This included the setting up of a comprehensive sewerage network-based SARS-CoV-2 virus surveillance programme with 154 stationary sites covering 6 million people (or 80 % of the total population), and employing an intensive monitoring programme to take samples from each stationary site every 2 days. From 1 January to 22 May 2022, the daily confirmed case count started with 17 cases per day on 1 January to a maximum of 76,991 cases on 3 March and dropped to 237 cases on 22 May. During this period, a total of 270 “Restriction-Testing Declaration” (RTD) operations at high-risk residential areas were conducted based on the sewage virus testing results, where over 26,500 confirmed cases were detected with a majority being asymptomatic. In addition, Compulsory Testing Notices (CTN) were issued to residents, and the distribution of Rapid Antigen Test kits was adopted as alternatives to RTD operations in areas of moderate risk. These measures formulated a tiered and cost-effective approach to combat the disease in the local setting. Some ongoing and future enhancement efforts to improve efficacy are discussed from the perspective of wastewater-based epidemiology. Forecast models on case counts based on sewage virus testing results were also developed with R2 of 0.9669–0.9775, which estimated that up to 22 May 2022, around 2,000,000 people (~67 % higher than the total number of 1,200,000 reported to the health authority, due to various constraints or limitations) had potentially contracted the disease, which is believed to be reflecting the real situation occurring in a highly urbanized metropolis like Hong Kong.

Ordeals in Combating COVID-19 Pandemic and Acceptability of COVID-19 Vaccine Among Frontliners in Digos City, Davao del Sur

The study primarily focuses on the ordeals in combating COVID-19 pandemic and acceptability of COVID-19 vaccine among frontliners in Digos City, Davao del Sur. The number of respondents was calculated using Stratified Random Sampling and Slovin’s formula at 0.05 margin of error, wherein it resulted to one hundred forty (140) individuals. A survey questionnaire prepared by the researcher was the method utilized for gathering the data. The analysis and computation of data was done through employing the Frequency Count, Mean, and Levene’s Test and ANOVA, which were the statistical tools of this study. The study’s findings revealed that the average mean for the level of ordeals of frontliners in combating COVID-19 pandemic was 3.66 which indicated as high, and for the level of acceptability of COVID-19 vaccine among frontliners, the average mean was 3.36 which indicated as moderate. Therefore, there is no significant difference on the level of ordeals in combating COVID-19 pandemic and the acceptability of COVID-19 vaccine among frontliners in Digos City when grouped according to their profile. This concludes that the null hypothesis of this study was accepted.

Ordeals in Combating COVID-19 Pandemic and Acceptability of COVID-19 Vaccine among Frontliners in Santa Cruz, Davao del Sur

This study was conducted to determine the frontliners ordeals in combating COVID-19 pandemic in Sta. Cruz, Davao del Sur. Analysis of data was done using descriptive statistical tools such as Frequency Count, Mean and Levenes Test/ANOVA. The study employed ninety-two respondents. The study shows that most of the respondents are male (55.4%) that ages 51-80 years old (65.2%). The study revealed in the frontliners level of ordeals is highly difficult in combating the outbreak especially in their social shielding responsibility. On the other hand, the acceptability of COVID-19 vaccine among frontliners, is moderately accepted and they have safety and efficacy concerns, fear of adverse effect and more. The study also concluded that the demographic profile of the respondents does not affect the frontliners level of ordeals and the acceptability of COVID-19 vaccine.

Tinospora Cordifolia (Gurjo) and Its Potential Role to Combat with COVID-19: A Review

Plant-based medicines have been used to maintain health and treat disease since the dawn of civilization. The present review focuses on studies that have been done on the characteristics of T. cordifolia to see if they may be used to combat COVID-19 Pandemic. During the review, various methodological activities were involved from developing the review concept, reviewing the articles, analyzing them, and finally writing the paper. The result shows that herbal medicine is used by 80% of the world’s population for some aspect of basic health care. T. cordifolia is a medicinal plant which is a useful home remedy for chronic fever, as it calms burning sensations and boosts energy and hunger. Glycosides, alkaloids, steroids, diterpenoid lactones, sesquiterpenoid, and aliphatic chemicals are the most common substances found in this herb. Scientific research on this medicine could lead to a novel method as well as knowledge into COVID-19 prevention, management, and the development of a new therapeutic component.

Formal Modeling of IoT-Based Drone Network for Combating COVID-19 Pandemic

Coronavirus biologically named COVID-19 is a disease that is circulating throughout the world due to its viral nature. The interaction of people is a source of spreading of coronavirus. Millions of people have been affected by this virus, and most of them have lost their lives. At present, this viral disease has grown into a worldwide pandemic which is a troubling spot for the whole world. Few technologies are supporting to manage and solve the COVID-19 crisis. In this paper, unified modeling language (UML) will be used to describe requirements and behavior of the proposed system. Unmanned aerial vehicle (UAV) drones are flying mechanical devices without any human pilot that is efficient to reduce the spreading rate of COVID-19. In the proposed IoT-based model, a cluster-based drones’ network will be used to monitor and perform required actions to tackle the violations of standard operating procedures (SOPs). The drones will gather all data through embedded cameras and sensors and will communicate with the control room to operate the actions as required. In this model, a well-maintained and collision-free network of drones will be designed using graph theory. Drones’ network will observe the violation of SOPs in the targeted area and make decisions such as produce alarm sound to alert persons and through communications by sending people warning messages on their smartphones. Further, the persons having COVID symptoms such as high temperature and unbalance respiratory rates will be identified using wearable sensors that are deployed to the targeted area and will send information to the control room to perform required actions. Drones will be able to provide medical kits to the patients’ residences that are identified using wearable sensors to reduce interaction of people. The model will be specified using Vienna Development Method-Specification language (VDM-SL) and validated through the VDM-SL toolbox.

Determinants of COVID-19 vaccine hesitancy: questionnaire development and validation.

Vaccine hesitancy presents one of the critical constraints in combating COVID-19 pandemic. The aim of this study was to develop and validate an instrument for measuring factors that contribute to COVID-19 vaccine hesitancy. The key constructs in the study instrument were factors that constitute the "3C" model of vaccine hesitancy: Confidence, Complacency and Convenience. Using a cross-sectional, online survey design, the 8-item COVID-19 Vaccine Hesitancy Questionnaire was administered to a sample of 667 adult citizens of Serbia in December 2020. We used confirmatory factor analysis to investigate the model that assumes three latent variables. To ensure that the instrument measures the same constructs in different groups, the measurement invariance examination was conducted. To examine criterion validity, Spearman's correlation was applied to determine the association between the instrument total score and the single-item measuring the likelihood of getting vaccinated against SARS-CoV-2. Confirmatory factor analysis established the three-factor structure, with subscales fitting within the "3C" model of vaccine hesitancy comprising confidence, convenience and complacency. The full scalar invariance was found across gender, and the partial scalar invariance was achieved for the age, region and education level. A higher level of the COVID-19 vaccine hesitancy was associated with the lower likelihood to get vaccinated against the SARS-CoV-2 virus. Our scale is brief and consistent, maintaining a good fit across key socio-demographic subgroups. This result implies that the scale could be useful for quick assessment of COVID-19 vaccine hesitancy in various target populations.

Strategies by National Health Systems in the Northern Hemisphere during First Wave of COVID-19: Evaluation and the Way Forward

This paper aims to assess the effectiveness of strategies adopted by national health systems across the globe in different ‘geographical regions’ in the Northern Hemisphere to combat COVID-19 pandemic. Data is included since the first case was reported in November 2019 till mid-April 2020. Sources of information are COVID-19 case repositories, official country websites, university research teams’ perspectives, official briefings, and available published research articles to date. We triangulated all data to formulate a comprehensive illustration of COVID-19 situation in each country included. It has been found that the 2002-2004 SARS outbreak experienced in China, Taiwan, and South Korea saw better strategies adopted by leadership to combat COVID-19 pandemic containment as compared to Iran, Italy, and the United States of America. Saudi Arabia has so far been successful in the implementation of containment strategies as there is no large outbreak in major cities or confined areas as prisons. The situation has yet to unfold in India and Pakistan, which exhibit their own weaknesses in policy formulation or implementation in response to health crises. This review provides conclusive evidence that timely travel bans, early detection of COVID-19 spread through exhaustive and reliable testing, and the establishment of a central, fully authorized body to foresee health trends and implement appropriate containment measures are essential to contain the spread of the virus.

Roles of Heath Education and Promotion in Combating Covid-19 Pandemic in Nigeria

This study was carried to assess the roles of health education and promotion in Nigeria. Coronaviruses belong to a large family of viruses causing a wide spectrum of illness, ranging from very mild i.e. Common cold to severe illness such as Middle East Respiratory Syndrome (MERS-CoV) and Severe Acute Respiratory Syndrome (SARS-CoV).In early August 2020, there were nearly 18 million confirmed cases of Coronavirus Disease (COVID-19), including 686,145 deaths globally; very rapid growth in prevalence since the first case was reported to the World Health Organization in December 2019 (WHO, 2020). In a desperate attempt to contain the further spread of the virus, governments across the world have taken public health interventions that are unprecedented. To prevent the further spread of COVID-19 infection, many countries have taken strict measures such as the complete lockdown of a country restricting the movement of people in public, forcing people to stay at home except for emergencies and certain essential jobs. At the same time countries are also trying to scale up their testing capacity and expand their contract tracing system while scientists around the world are in a race to develop a vaccine against the virus as well as drugs to alleviate its symptoms. It is well-known that public health education plays a crucial role in the prevention and control of emerging infectious diseases, but how health providers should advise families and parents to obtain health education information is a challenging question. With COVID-19 (Coronavirus disease 2019) spreading around the world, this rapid review aims to answer that question and thus to promote evidence-based decision making in health education policy and practice Keywords: SARS-CoV, WHO, Nigeria, Corona Virus, Health Education, COVID 19, Pandemic

Prevalence of Covishield COVID-19 Vaccine (ChAdOx1 nCoV-19) Adverse Effects among Health Care Workers in Sri Lanka

PurposeA Community vaccination programme is the best approach to combat COVID-19 pandemic. The first priority was given to the health care workers (HCWs) with the introduction of Indian Covishield (ChAdOx1 nCoV-19) vaccine to Sri Lanka since February 2021. An independent post-vaccine surveillance is important to identify the occurrence of adverse effects(A/E) in the population.Methods & MaterialsA multicentered cross-sectional survey was conducted in four provinces of Sri Lanka to estimate the prevalence of A/E after covishield vaccination A/E among HCWs after the first dose. A self-administered questionnaire was used to gather demographic data and A/E. Data was analysed using descriptive statistics.ResultsOf 4834 participants, 3500(72.4%) were females. The median age was 42.23(SD±9.64) years. Only 0.8%(n=31) persons has had Covid infection in the past. 2.2% were breastfeeding mothers and 0.2% were pregnant ladies.87.4% of persons had at least one A/E and 53.1% had local A/E. Body aches(68.2%), headaches(63.8%), fever(58%), chills 51.4%), fatigue(41.2%), arthralgia(38.1%) and rigors (32%) were the most commonly reported systemic A/E.Most of the systemic A/E were more prevalent among the ≤42-year-old group, and females. Their duration was mainly 24 hours. Mean duration of onset of fever is 9.76 hours.Pain and redness at the site were the most commonly reported local A/E.All of the local A/E were more prevalent among the ≤42-year-old group and females. Mean duration of pain at the site is 4.47 hours.1.7%(n=61) had reactions within first 20 minutes. 0.08%(n=4) developed anaphylaxis, 0.8%(n=31) had urticaria.15.4% had at least one comorbidities but there were no significant association between having a comorbidity and developing systemic or local.1.3% had history of drug or food allergies, they did not show significant relation to current vaccine induced allergies or anaphylaxis.69.2% attended the routine work despite having minor A/E. 0.13%(n=7) were hospitalised and treated. 22.4% were stayed at home and rested for 24-48 hours due to A/E.ConclusionEventhough more than 60% reported minor A/E, there were only a few serious A/E. A/E were more prevalent in younger age and females. Overall, the first dose of the Covishield vaccine was well-tolerated by HCWs.

A comprehensive Survey on Blockchain-Based Solutions to Combat Covid-19 Pandemic

A comprehensive Survey on Blockchain-Based Solutions to Combat Covid-19 Pandemic