Study on Spatial Changes in PM2.5 before and after the COVID-19 Pandemic in Southwest China

Coronavirus disease 2019 (COVID-19) swept the world at the beginning of 2020, and strict activity control measures were adopted in China's concentrated and local outbreak areas, which led to social shutdown. This study was conducted in southwest China from 2019 to 2021, and was divided into the year before COVID-19 (2019), the year of COVID-19 outbreak (2020), and the year of normalization of COVID-19 prevention and control (2021). A geographically and temporally weighted regression (GTWR) model was used to invert the spatial distribution of PM2.5 by combining PM2.5 on-site monitoring data and related driving factors. At the same time, a multiple linear regression (MLR) model was constructed for comparison with the GTWR model. The results showed that: (1) The inversion accuracy of the GTWR model was higher than that of the MLR model. In comparison with the commonly used PM2.5 datasets "CHAP” and "ACAG”, PM2.5 inverted by the GTWR model had higher data accuracy in southwest China. (2) The average PM2.5 concentrations in the entire southwest region were 32.1, 26.5, and 28.6 μg/m3 over the three years, indicating that the society stopped production and work and the atmospheric PM2.5 concentration reduced when the pandemic control was highest in 2020. (3) The winter and spring of 2020 were the relatively strict periods for pandemic control when the PM2.5 concentration showed the most significant drop. In the same period of 2021, the degree of control was weakened, and the PM2.5 concentration showed an upward trend.

House prices and COVID-19 pandemic shocks in India: a nonlinear ARDL analysis

PurposeIndia is one of those countries that are severely affected by the COVID-19 pandemic. With the upsurge in the cases, the country recorded high unemployment rates, economic uncertainties and slugging growth rates. This adversely affected the real estate sector in India. As the relation of the housing market with the gross domestic product is quite lasting thus, the decline in housing prices has severely impacted the economic growth of the nation. Hence, the purpose of this paper is to gauge the asymmetric impact of COVID-19 shocks on housing prices in India.Design/methodology/approachStudies revealed the symmetric impact of macroeconomic variables, and contingencies on housing prices dominate the literature. However, the assumption of linearity fails to apprehend the asymmetric dynamics of the housing sector. Thus, the author uses a nonlinear autoregressive distributed lag model to address this limitation and test the existence of short- and long-run asymmetry.FindingsThe findings revealed the long- and short-run asymmetric impact of the COVID-19 outbreak and the peak of the COVID-19 on housing prices. The results indicate that the peak of COVID-19 had a greater impact on housing prices in comparison to the outbreak of COVID-19. This can be explained as prices will revert to normal at a speed of 0.978% with the decline in the number of COVID-19 cases. Whereas the housing prices rise at a rate of 0.714 as a result of government intervention to deal with the ill effects of the COVID-19 outbreak. Moreover, it can be inferred that both the outbreak and peak of COVID-19 will lead to a minimal decline in housing prices, while with the decline in the number of cases and reduction in the impact of the outbreak of COVID, the housing prices will rise at an increasing rate.Originality/valueTo the best of the authors' knowledge, this is the first study to understand the impact of the outbreak and peak of COVID-19 on the housing prices separately.

Analysis of the socioeconomic barriers in implementing public health measures to contain COVID-19 transmission in Pakistan: a DELPHI–DEMATEL-based approach

PurposeThe present study aims to identify and evaluate the socioeconomic barriers to effective COVID-19 pandemic transmission control in Pakistan.Design/methodology/approachThe study identifies multiple socio-economic barriers through an extensive literature review. The preliminary analysis unveiled 15 socio-economic barriers. Nine experts were contacted to collect data and finalize the most prominent barriers to COVID-19 transmission control using the DELPHI method. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was used to process and interpret the data collected and a cause–effect relationship was established among the barriers.FindingsThe finalized barriers to effective COVID-19 pandemic transmission control were evaluated using DEMATEL which grouped criteria into two grouped criteria – cause and effect. The DEMATEL analysis shows that poor safety culture, lack of strategy and goal setting, lack of resources, late realization and recognition of the pandemic problem and lack of expertise and capacity in disaster and risk management fall into the cause group. These factors are critical as they directly affect the remaining barriers identified in the study.Originality/valueDespite the collective global efforts, the national economies have been struggling to completely control COVID-19 transmission control. Pakistan's economy has been facing the third wave of the pandemic. It is mandatory to identify the barriers and evaluate them to develop a comprehensive strategy ensuring that there would be no fourth wave. The study identifies and evaluates the barriers to COVID-19 transmission control in Pakistan using the integrated DELPHI-DEMATEL framework. The findings would help the government, experts and strategists to develop a comprehensive disaster and risk management strategy.

Impact of mobility on COVID-19 spread - A time series analysis.

In this paper, we investigate the impact of mobility on the spread of COVID-19 in Tehran, Iran. We have performed a time series analysis between the indicators of public transit use and inter-city trips on the number of infected people. Our results showed a significant relationship between the number of infected people and mobility variables with both short-term and long-term lags. The long-term effect of mobility showed to have a consistent lag correlation with the weekly number of new COVID-19 positive cases. In our statistical analysis, we also investigated key non-transportation variables. For instance, the mandatory use of masks in public transit resulted in observing a 10% decrease in the number of infected people. In addition, the results confirmed that super-spreading events had significant increases in the number of positive cases. We have also assessed the impact of major events and holidays throughout the study period and analyzed the impacts of mobility patterns in those situations. Our analysis shows that holidays without inter-city travel bans have been associated with a 27% increase in the number of weekly positive cases. As such, while holidays decrease transit usage, it can overall negatively affect spread control if proper control measures are not put in place. The result and discussions in this paper can help authorities understand the effects of different strategies and protocols with a pandemic control and choose the most beneficial ones.

Optimizing Large-Scale COVID-19 Nucleic Acid Testing with a Dynamic Testing Site Deployment Strategy.

The COVID-19 epidemic has spread worldwide, infected more than 0.6 billion people, and led to about 6 million deaths. Conducting large-scale COVID-19 nucleic acid testing is an effective measure to cut off the transmission chain of the COVID-19 epidemic, but it calls for deploying numerous nucleic acid testing sites effectively. In this study, we aim to optimize the large-scale nucleic acid testing with a dynamic testing site deployment strategy, and we propose a multiperiod location-allocation model, which explicitly considers the spatial-temporal distribution of the testing population and the time-varied availability of various testing resources. Several comparison models, which implement static site deployment strategies, are also developed to show the benefits of our proposed model. The effectiveness and benefits of our model are verified with a real-world case study on the Chenghua district of Chengdu, China, which indicates that the optimal total cost of the dynamic site deployment strategy can be 15% less than that of a real plan implemented in practice and about 2% less than those of the other comparison strategies. Moreover, we conduct sensitivity analysis to obtain managerial insights and suggestions for better testing site deployment in field practices. This study highlights the importance of dynamically deploying testing sites based on the target population's spatial-temporal distribution, which can help reduce the testing cost and increase the robustness of producing feasible plans with limited medical resources.

Interruption of Influenza Transmission under Public Health Emergency Response for COVID-19: a Study Based on Real-World Data from Beijing, China.

To estimate the effect of the corona virus disease 2019 (COVID-19) control measures taken to mitigate community transmission in many regions, we analyzed data from the influenza surveillance system in Beijing from week 27 of 2014 to week 26 of 2020. We collected weekly numbers of influenza-like illness (ILI) cases, weekly positive proportion of ILI cases, weekly ILI case proportion in outpatients, and the dates of implementation of COVID-19 measures. We compared the influenza activity indicators of the 2019/2020 season with the preceding five seasons and built two ARIMAX models to estimate the effectiveness of COVID-19 measures declared since January 24, 2020 by the emergency response. Based on the observed data, compared to the preceding five influenza seasons, ILIs, positive proportion of ILIs, and duration of the influenza epidemic period in 2019/2020 had increased from 13% to 54%; in particular, the number of weeks from the peak to the end of the influenza epidemic period had decreased from 12 to 1. According to ARIMAX model forecasting, after considering natural decline, weekly ILIs had decreased by 48.6%, weekly positive proportion had dropped by 15% in the second week after the emergency response was declared, and COVID-19 measures had reduced by 83%. We conclude that the public health emergency response can significantly interrupt the transmission of influenza.

Assessing Age-Specific Vaccination Strategies and Post-vaccination Reopening Policies for COVID-19 Control Using SEIR Modeling Approach.

As the availability of COVID-19 vaccines, it is badly needed to develop vaccination guidelines to prioritize the vaccination delivery in order to effectively stop COVID-19 epidemic and minimize the loss. We evaluated the effect of age-specific vaccination strategies on the number of infections and deaths using an SEIR model, considering the age structure and social contact patterns for different age groups for each of different countries. In general, the vaccination priority should be given to those younger people who are active in social contacts to minimize the number of infections, while the vaccination priority should be given to the elderly to minimize the number of deaths. But this principle may not always apply when the interaction of age structure and age-specific social contact patterns is complicated. Partially reopening schools, workplaces or households, the vaccination priority may need to be adjusted accordingly. Prematurely reopening social contacts could initiate a new outbreak or even a new pandemic out of control if the vaccination rate and the detection rate are not high enough. Our result suggests that it requires at least nine months of vaccination (with a high vaccination rate > 0.1%) for Italy and India before fully reopening social contacts in order to avoid a new pandemic.

Effect of endodontist knowledge and risk perception on COVID-19 infection control

Background: The pandemic condition felt by all parts of the world due to the very fast spread of COVID-19 threatens the safety of various health care sectors. Until now, the pandemic has been going on and has given rise to various new variants of COVID-19. Dental and oral health services are not spared from this, this condition is exacerbated by the fact that the virus spreads more easily through aerosols produced during treatment, especially by endodontists. Therefore, the researcher wanted to know the effect of knowledge and perception of endodontic risk on the control of COVID-19. Metods: This study uses an analytical descriptive research design with a cross-sectional study approach. Samples were obtained from all endodontists registered with IKORGI and completed filling out the questionnaire to completion. Questionnaires were distributed online via google forms. The research was carried out in November 2021. Result: Based on the results of research conducted on endodontists throughout Indonesia, it was found that the difference in perception on criterion control was sufficient with a mean value of 9.84 and a median value of 10.0, the difference in knowledge on criterion control was sufficient with a mean value of 6.99 and a median value of 7.0. The results of the statistical test show a value of p = 0.000 for the knowledge variable and risk perception of COVID-19 control. Conclusions: Based on the results of research on the influence of knowledge and perception on the control of covid-19 in endodontists throughout Indonesia. © 2022 Eurosurveillance. All rights reserved.

A machine learning-driven spatio-temporal vulnerability appraisal based on socio-economic data for COVID-19 impact prevention in the U.S. counties.

A mature and hybrid machine-learning model is verified by mature empirical analysis to measure county-level COVID-19 vulnerability and track the impact of the imposition of pandemic control policies in the U.S. A total of 30 county-level social, economic, and medical variables and a timeline of the imposed policies constitutes a COVID-19 database. A hybrid feature-selection model composed of four machine-learning algorithms is developed to emphasize the regional impact of community features on the case fatality rate (CFR). A COVID-19 vulnerability index (COVULin) is proposed to measure the county's vulnerability, the effects of model's parameters on mortality, and the efficiency of control policies. The results showed that the dense counties in which minority groups represent more than 45% of the population and those with poverty rates greater than 24% were the most vulnerable counties during the first and the last pandemic peaks, respectively. Highly-correlated CFR and COVULin scores indicated a close agreement between the model outcomes and COVID-19 impacts. Counties with higher poverty and uninsured rates were the most resistant to government intervention. It is anticipated that the proposed model can play an essential role in identifying vulnerable communities and help reduce damages during long-term alike disasters.

Performance of upper-room ultraviolet germicidal irradiation (UVGI) system in learning environments: Effects of ventilation rate, UV fluence rate, and UV radiating volume

Previous studies show that upper-room ultraviolet germicidal irradiation (UVGI) systems can help contain infectious airborne viruses indoors. However, there has been a lack of research on the performance of an upper-room UVGI system in learning environments such as a school classroom. Since classrooms are more vulnerable to airborne transmission of diseases due to high occupancy for long hours, airborne infection characteristics are different from other occupied indoor environments (e.g., offices and residences). The objective of this study is to investigate UVGI system performance in a classroom considering detailed effects of ventilation rate, UV fluence rate, and UV radiating volume. Two analytical models, a one-zone and a two-zone material balance model, along with computational fluid dynamics (CFD) simulations, were employed to analyze viral aerosol concentrations under a representative range of classroom operating conditions. The CFD results show that increasing ventilation rate from 1.1 h–1 to 5 h–1 yields about 85% of airborne disinfection while doubling UV radiating volume results in a 60% disinfection. However, increasing UV fluence rate from 25 μW∙cm–2 to 50 μW∙cm–2 yields a moderate additional disinfection of 18%. Overall, the study results reveal that operating a UVGI system in an occupied classroom can markedly disinfect airborne viruses up to 96%, which is as effective as increasing ventilation rate more than five times. Furthermore, the results suggest that the one-zone and two-zone analytical models used in several previous studies could result in notably meaningful errors in analyzing viral aerosol concentrations, especially in occupied rooms with a highly non-uniform airflow distribution.

The impact of social welfare and COVID-19 stringency on the perceived utility of food apps: A hybrid MCDM approach.

The COVID-19 pandemic has created enormous challenges for society due to the various ways of impacting health. This paper focuses on the impact of the COVID-19 pandemic on people's food consumption patterns in the online environment. We investigate food app reviews and examine whether countries with a high rate of success with COVID-19 control consume more unhealthy food through mobile apps. We also investigate whether the population of countries with low social welfare eat more unhealthy food during the COVID-19 pandemic compared to countries with high social welfare. We take a hybrid multi-criteria decision making (MCDM) approach to calculate indexes based on the technique for order of preference by similarity to an ideal solution, complex proportional assessment, and VlseKriterijuska Optimizacija I Komoromisno Resenje. Results show that country social welfare and success in COVID-19 control negatively affect the perceived utility of the apps. Also, success in COVID-19 control and the perceived utility of food apps positively affect the proportion of unhealthy reviews, whereas social welfare has a negative impact. The results have important implications for public health policymakers, showing that the online food environment can be an important setting for interventions that seek to incentivize healthy eating.

IoT Enabled Geofencing-Based System for Monitoring and Enforcing COVID-19 Control Measures in Workplaces, Service Areas and Distributed Home Quarantine

Due to the outbreak of COVID-19, the whole world is thinking of new mechanisms, preventive measures to protect human life from the widespread of the pandemic. Many countries imposed COVID-19 control measures to limit further infection spread. However, controlling the spread of COVID-19 without taking severe measures (e.g. lockdown and full quarantine) that have undesirable economic effects becomes a major challenge. By exploiting the modern and available information and communication technologies, innovative solutions may emerge to face and deal with this crisis. In this paper, an innovative and flexible solution based on the exploitation and integration of geofencing, and Internet of Things (IoT) technologies is proposed to enhance the crisis management framework in response to the COVID-19 pandemic. The proposed solution is designed to monitor and impose COVID-19 control measures in different environments such as distributed home quarantine, workplaces, service areas, and COVID-19 infected zones. © 2022 IEEE.

Past local government health spending was not correlated with COVID-19 control in US counties.

CONTEXT: Wide variation in state and county health spending prior to 2020 enables tests of whether historically better state and locally funded counties achieved faster control over COVID-19 in the first 6 months of the pandemic in the Unites States prior to federal supplemental funding. OBJECTIVE: We used time-to-event and generalized linear models to examine the association between pre-pandemic state-level public health spending, county-level non-hospital health spending, and effective COVID-19 control at the county level. We include 2,775 counties that reported 10 or more COVID-19 cases between January 22, 2020, and July 19, 2020, in the analysis. MAIN OUTCOME MEASURE: Control of COVID-19 was defined by: (i) elapsed time in days between the 10th case and the day of peak incidence of a county's local epidemic, among counties that bent their case curves, and (ii) doubling time of case counts within the first 30 days of a county's local epidemic for all counties that reported 10 or more cases. RESULTS: Only 26% of eligible counties had bent their case curve in the first 6 months of the pandemic. Government health spending at the county level was not associated with better COVID-19 control in terms of either a shorter time to peak in survival analyses, or doubling time in generalized linear models. State-level public spending on hazard preparation and response was associated with a shorter time to peak among counties that were able to bend their case incidence curves. CONCLUSIONS: Increasing resource availability for public health in local jurisdictions without thoughtful attention to bolstering the foundational capabilities inside health departments is unlikely to be sufficient to prepare the country for future outbreaks or other public health emergencies.

Effect of the COVID-19 pandemic on malaria intervention coverage in Nigeria: Analysis of the Premise Malaria COVID-19 Health Services Disruption Survey 2020

INTRODUCTION The study aimed to assess the uptake of malaria intervention services in Nigeria before and during the COVID-19 pandemic. METHODS This study utilized secondary data collected in the COVID-19 Health Services Disruption Survey. The data collected included sociodemographic characteristics, the number of insecticide-treated nets, visit to healthcare facilities, enrollment in malaria tests, and treatment for malaria. Data analysis was performed using SPSS version 25.0. The association between visit to healthcare facilities and sociodemographic characteristics was determined using chi-squared tests. Binary logistic regression tests were conducted, and p<0.05 was considered statistically significant. RESULTS Among the 1985 respondents, 960 (48.4%) were aged ≤25 years. Before the COVID-19 pandemic, 485 (50.5%) people aged ≤25 years visited healthcare facilities (χ2=15.923, p≤0.001), while 385 (39.9%) persons aged ≤25 years visited healthcare facilities during the pandemic (χ2=15.53, p≤0.001). Among those with graduate/postgraduate education who visited healthcare facilities, 593 (45.9%) paid visits before the pandemic (χ2=7.33, p=0.026), while 445 (44.4%) paid visits during the pandemic (χ2=16.37, p≤0.001). Individuals aged 26–35 years had 21% less odds (AOR=0.79;95% CI: 0.65–0.97, p=0.021) of visiting healthcare facilities before the pandemic, and 23% less odds of visiting healthcare facilities during the pandemic (AOR=0.77;95% CI: 0.63–0.95, p=0.013). CONCLUSIONS The COVID-19 pandemic has had a negative impact on visits to healthcare facilities for malarial treatment. To promote malaria intervention during the pandemic, malaria diagnosis should be linked with COVID-19 screening and testing. © 2021. All Rights Reserved.

Progression of the Pathway for Public Health Care during the COVID-19 Outbreak at District Health Office.

Public health activities under district health offices (DHOs) play a major role in Malaysia's fight against COVID-19. This article aims to describe and illustrate the public health activity pathway in combating the COVID-19 pandemic, and a team of public health workers who are familiar with DHO work settings was created in April 2020 for that purpose. Review of documents and the Ministry of Health's updates was carried out, followed by a series of discussions with stakeholders. Based on the steps in the outbreak investigation tasks, the flow of activities from January to May 2020 was listed in line with the phases of the country's National Movement Control Order 2020. Results show that the activities can be classified into three different sections-namely, the main action areas, category of cases, and level of care. The main process flow of activities comprised the case management and support activities. Case management flow was split into tasks for patients under investigation and persons under surveillance, while the support services existed throughout the phases. The pathways illustrate that the progression of the pandemic translated directly to changes in the pattern of activities, with additional subgroups of activities in accordance with all imposed guidelines.

Effective COVID-19 Control: A Comparative Analysis of the Stringency and Timeliness of Government Responses in Asia.

AIM: Many governments in East and Southeast Asia responded promptly and effectively at the onset of the COVID-19 pandemic. Synthesizing and analyzing these responses is vital for disease control evidence-based policymaking. METHODS: An extensive review of COVID-19 control measures was conducted in selected Asian countries and subregions, including Mainland China, Hong Kong, Taiwan, South Korea, Singapore, Japan, and Vietnam from 1 January to 30 May 2020. Control measures were categorized into administrative, public health, and health system measures. To evaluate the stringency and timeliness of responses, we developed two indices: the Initial Response Index (IRI) and the Modified Stringency Index (MSI), which builds on the Oxford COVID-19 Government Response Tracker (OxCGRT). RESULTS: Comprehensive administrative, public health, and health system control measures were implemented at the onset of the outbreak. Despite variations in package components, the stringency of control measures across the study sites increased with the acceleration of the outbreak, with public health control measures implemented the most stringently. Variations in daily average MSI scores are observed, with Mainland China scoring the highest (74.2), followed by Singapore (67.4), Vietnam (66.8), Hong Kong (66.2), South Korea (62.3), Taiwan (52.1), and Japan (50.3). Variations in IRI scores depicting timeliness were higher: Hong Kong, Taiwan, Vietnam, and Singapore acted faster (IRI > 50.0), while Japan (42.4) and Mainland China (4.2) followed. CONCLUSIONS: Timely setting of stringency of the control measures, especially public health measures, at dynamically high levels is key to optimally controlling outbreaks.

Removal of SARS-CoV-2 using UV+Filter in built environment.

Air cleaning is an effective and reliable method in indoor airborne SARS-CoV-2 (Severe Acute Respiratory Syndrome Corona-Virus 2) control, with ability of aerosol removal or disinfection. However, traditional air cleaning systems (e.g. fibrous filter, electrostatic removal system) have some risks in operation process, including re-aerosolization and electric breakdown. To avoid these risks, the current study proposed an UV+Filter (ultraviolet and fibrous pleated filter) system to efficiently capture airborne SARS-CoV-2 aerosols and deactivate them in filter medium. It is challenging to quantitatively design UV+Filter due to complex characteristics of SARS-CoV-2 aerosols (e.g. aerodynamic size, biological susceptibility) and hybrid filtration/disinfection processes. This study numerically investigated the overall performances of different air cleaning devices (e.g. Fibrous-filter, UV+Filter, two-stage ESP (electrostatic precipitator) et al.) for control of SARS-CoV-2 aerosols and compared them in term of filtration efficiency, energy consumption and secondary pollution. The prediction of developed models was validated with the experimental data from literature. UV+Filter is the most reliable and safest, while its energy consumption is highest. The newly proposed design method of air cleaning systems could provide essential tools for airborne diseases control.

The coSIR model predicts effective strategies to limit the spread of SARS-CoV-2 variants with low severity and high transmissibility.

Multiple new variants of SARS-CoV-2 have been identified as the COVID-19 pandemic spreads across the globe. However, most epidemic models view the virus as static and unchanging and thus fail to address the consequences of the potential evolution of the virus. Here, we built a competitive susceptible-infected-removed (coSIR) model to simulate the competition between virus strains of differing severities or transmissibility under various virus control policies. The coSIR model predicts that although the virus is extremely unlikely to evolve into a "super virus" that causes an increased fatality rate, virus variants with less severe symptoms can lead to potential new outbreaks and can cost more lives over time. The present model also demonstrates that the protocols restricting the transmission of the virus, such as wearing masks and social distancing, are the most effective strategy in reducing total mortality. A combination of adequate testing and strict quarantine is a powerful alternative to policies such as mandatory stay-at-home orders, which may have an enormous negative impact on the economy. In addition, building Mobile Cabin Hospitals can be effective and efficient in reducing the mortality rate of highly infectious virus strains. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11071-021-06705-8.

The impact of COVID-19 on the tuberculosis control activities in Addis Ababa.

The first COVID-19 case was reported in Ethiopia on 13th March 2020 and series of announcements of set of measures, proclamation and directives have been enacted to fight the coronavirus pandemic. These have implications for the regular health services including the TB control program. This brief communication assesses the impact of the COVID-19 response on the TB control activities of Addis Ababa health centers based on research project data. We compared the patient flows in pre-COVID-19 period (quarter 1, Q1) and during COVID-19 (quarter 2, Q2 and quarter 3, Q3) of 2020 at 56 health centers in Addis Ababa from all 10 sub-cities per sub-city. The patient flow declined from 3,473 in Q1 to 1,062 in Q2 and 1,074 in Q3, which is a decrease by 62-76% and 52-80% in Q2 and Q3 respectively as compared to that of Q1. In Q2, Kolfe keranio and Kirkos sub-cities recorded the biggest decline (76 and 75% respectively) whereas Yeka sub-city had the least decline (62%). In Q3, Kirkos sub-city had the biggest decline (80%) and Addis ketema sub-city had the lowest (52%). We conclude that the series of measures, state of emergency proclamation and government directives issued to counter the spread of COVID-19 and the public response to these significantly affected the TB control activities in Addis Ababa city as attested by the decrease in the patient flow at the clinics. Health authorities may inform the public that essential health services are still available and open to everyone in need of these services.

Emerging materials for the electrochemical detection of COVID-19.

The SARS-CoV-2 virus is still causing a dramatic loss of human lives worldwide, constituting an unprecedented challenge for the society, public health and economy, to overcome. The up-to-date diagnostic tests, PCR, antibody ELISA and Rapid Antigen, require special equipment, hours of analysis and special staff. For this reason, many research groups have focused recently on the design and development of electrochemical biosensors for the SARS-CoV-2 detection, indicating that they can play a significant role in controlling COVID disease. In this review we thoroughly discuss the transducer electrode nanomaterials investigated in order to improve the sensitivity, specificity and response time of the as-developed SARS-CoV-2 electrochemical biosensors. Particularly, we mainly focus on the results appeard on Au-based and carbon or graphene-based electrodes, which are the main material groups recently investigated worldwidely. Additionally, the adopted electrochemical detection techniques are also discussed, highlighting their pros and cos. The nanomaterial-based electrochemical biosensors could enable a fast, accurate and without special cost, virus detection. However, further research is required in terms of new nanomaterials and synthesis strategies in order the SARS-CoV-2 electrochemical biosensors to be commercialized.