Guidance for Implementing COVID-19 Prevention Strategies in the Context of Varying Community Transmission Levels and Vaccination Coverage

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in Europe: Longitudinal Trend Analysis

BACKGROUND

In this study, we built upon our initial research published in 2020 by incorporating an additional 2 years of data for Europe. We assessed whether COVID-19 had shifted from the pandemic to endemic phase in the region when the World Health Organization (WHO) declared the end of the public health emergency of international concern on May 5, 2023.

OBJECTIVE

We first aimed to measure whether there was an expansion or contraction in the pandemic in Europe at the time of the WHO declaration. Second, we used dynamic and genomic surveillance methods to describe the history of the pandemic in the region and situate the window of the WHO declaration within the broader history. Third, we provided the historical context for the course of the pandemic in Europe in terms of policy and disease burden at the country and region levels.

METHODS

In addition to the updates of traditional surveillance data and dynamic panel estimates from the original study, this study used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data to identify the appearance and duration of variants of concern. We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Finally, we conducted a 1-tailed t test for whether regional weekly speed was greater than an outbreak threshold of 10. We ran the test iteratively with 6 months of data across the sample period.

RESULTS

Speed for the region had remained below the outbreak threshold for 4 months by the time of the WHO declaration. Acceleration and jerk were also low and stable. While the 1-day and 7-day persistence coefficients remained statistically significant, the coefficients were moderate in magnitude (0.404 and 0.547, respectively; P<.001 for both). The shift parameters for the 2 weeks around the WHO declaration were small and insignificant, suggesting little change in the clustering effect of cases on future cases at the time. From December 2021 onward, Omicron was the predominant variant of concern in sequenced viral samples. The rolling t test of speed equal to 10 became insignificant for the first time in April 2023.

CONCLUSIONS

While COVID-19 continues to circulate in Europe, the rate of transmission remained below the threshold of an outbreak for 4 months ahead of the WHO declaration. The region had previously been in a nearly continuous state of outbreak. The more recent trend suggested that COVID-19 was endemic in the region and no longer reached the threshold of the pandemic definition. However, several countries remained in a state of outbreak, and the conclusion that COVID-19 was no longer a pandemic in Europe at the time is unclear.

Sub-Saharan Africa Surveillance Metrics and History of the COVID-19 Pandemic: Updated Epidemiological Assessment

BACKGROUND

This study updates the COVID-19 pandemic surveillance in Sub-Saharan Africa (SSA) we first conducted in 2020 by providing two additional years of data for the region.

OBJECTIVE

First, we aim to measure whether there was an expansion or contraction in the pandemic in SSA when the World Health Organization (WHO) declared the end of the public health emergency for the COVID-19 pandemic on May 5, 2023. Second, we use dynamic and genomic surveillance methods to describe the history of the pandemic in the region and situate the window of the WHO declaration within the broader history. Third, we aim to provide historical context for the course of the pandemic in SSA.

METHODS

In addition to updates of traditional surveillance data and dynamic panel estimates from the original study by Post et al. (2021), this study used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID) to identify the appearance and duration of variants of concern. We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Finally, we conducted a one-sided t-test for whether regional weekly speed was greater than an outbreak threshold of ten. We ran the test iteratively with a rolling, six month-window of data across the sample period.

RESULTS

Speed for the region remained well below the outbreak threshold before and after the WHO declaration. Acceleration and jerk were also low and stable. The 7-day persistence coefficient remained somewhat large (1.11) and statistically significant. However, both shift parameters for the weeks around the WHO declaration were negative, meaning the clustering effect of new COVID-19 cases had become recently smaller. From November 2021 onward, Omicron was the predominant variant of concern in sequenced viral samples. The rolling t-test of speed equal to ten was insignificant for the entire sample period.

CONCLUSIONS

While COVID-19 continues to circulate in SSA, the region never reached outbreak status, and the weekly transmission rate had remained below one case per 100,000 population for well over one year ahead of the WHO declaration. COVID-19 is endemic in the region and no longer reaches the threshold of a pandemic definition. Both standard and enhanced surveillance metrics confirm that the pandemic had ended in SSA by the time of the WHO declaration.

CLINICALTRIAL

South Asia's COVID-19 History and Surveillance: Updated Epidemiological Assessment

BACKGROUND

This study updates the COVID-19 pandemic surveillance in South Asia we first conducted in 2020 with two additional years of data for the region. We assess whether COVID-19 had transitioned from pandemic to endemic at the point the World Health Organization (WHO) ended the publication health emergency status for COVID-19 on May 5, 2023.

OBJECTIVE

First, we aim to measure whether there was an expansion or contraction in the pandemic in South Asia around the WHO declaration. Second, we use dynamic and genomic surveillance methods to describe the history of the pandemic in the region and situate the window of the WHO declaration within the broader history. Third, we aim to provide historical context for the course of the pandemic in South Asia.

METHODS

In addition to updates of traditional surveillance data and dynamic panel estimates from the original study Welch et al. (2021), this study used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID) to identify the appearance and duration of variants of concern. We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Finally, we conducted a one-sided t-test for whether regional weekly speed or transmission rate per 100,000 population was greater than an outbreak threshold of ten. We ran the test iteratively with six months of data across the sample period.

RESULTS

Speed for the region remained below the outbreak threshold for over a year by the time of the WHO declaration. Acceleration and jerk were also low and stable. While the 1-day persistence coefficients remained statistically significant and positive (1.168), the 7-day persistence coefficient was negative (-0.185), suggesting limited cluster effects in which cases on a given day predict cases seven days forward. Furthermore, the shift parameters for either of the two most recent weeks around May 5, 2023, did not indicate any overall change in the persistence measure around the time of WHO declaration. From December of 2021 onward, Omicron was the predominant variant of concern in sequenced viral samples. The rolling t-test of speed equal to ten was statistically insignificant across the entire pandemic.

CONCLUSIONS

While COVID-19 continues to circulate in South Asia, the rate of transmission had remained below the outbreak threshold for well over a year ahead of the WHO declaration. COVID-19 is endemic in the region and no longer reaches the threshold of the pandemic definition. Both standard and enhanced surveillance metrics confirm that the pandemic had ended by the time of the WHO declaration. Prevention policies should be a focus ahead of future pandemics. On that point, policy should emphasize an epidemiological task force with widespread testing and a contact-tracing system.

CLINICALTRIAL

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in the Middle East and North Africa: Longitudinal Trend Analysis

BACKGROUND

This study updates the COVID-19 pandemic surveillance in the Middle East and North Africa (MENA) we first conducted in 2020 with 2 additional years of data for the region.

OBJECTIVE

The objective of this study is to determine whether the MENA region meets the criteria for moving from a pandemic to endemic. In doing so, this study considers pandemic trends, dynamic and genomic surveillance methods, and region-specific historical context for the pandemic. These considerations continue through the World Health Organization (WHO) declaration of the end of the public health emergency for the COVID-19 pandemic on May 5, 2023.

METHODS

In addition to updates to traditional surveillance data and dynamic panel estimates from the original study by Post et al, this study used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID) to identify the appearance and duration of variants of concern. We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Finally, we conducted a 1-sided t test to determine whether regional weekly speed of COVID-19 spread was greater than an outbreak threshold of 10. We ran the test iteratively with 6 months of data from September 4, 2020, to May 12, 2023.

RESULTS

The speed of COVID-19 spread for the region had remained below the outbreak threshold for 7 continuous months by the time of the WHO declaration. Acceleration and jerk were also low and stable. Although the 1- and 7-day persistence coefficients remained statistically significant and positive, the weekly shift parameters suggested the coefficients had most recently turned negative, meaning the clustering effect of new COVID-19 cases became even smaller in the 2 weeks around the WHO declaration. From December 2021 onward, Omicron was the predominant variant of concern in sequenced viral samples. The rolling t test of the speed of spread equal to 10 became entirely insignificant from October 2022 onward.

CONCLUSIONS

The COVID-19 pandemic had far-reaching effects on MENA, impacting health care systems, economies, and social well-being. Although COVID-19 continues to circulate in the MENA region, the rate of transmission remained well below the threshold of an outbreak for over 1 year ahead of the WHO declaration. COVID-19 is endemic in the region and no longer reaches the threshold of the pandemic definition. Both standard and enhanced surveillance metrics confirm that the pandemic had transitioned to endemic by the time of the WHO declaration.

Utilizing disease transmission and response capacities to optimize covid-19 control in Malaysia

OBJECTIVES

Public Health Social Measures (PHSM) such as movement restriction movement needed to be adjusted accordingly during the COVID-19 pandemic to ensure low disease transmission alongside adequate health system capacities based on the COVID-19 situational matrix proposed by the World Health Organization (WHO). This paper aims to develop a mechanism to determine the COVID-19 situational matrix to adjust movement restriction intensity for the control of COVID-19 in Malaysia.

METHODS

Several epidemiological indicators were selected based on the WHO PHSM interim guidance report and validated individually and in several combinations to estimate the community transmission level (CT) and health system response capacity (RC) variables. Correlation analysis between CT and RC with COVID-19 cases was performed to determine the most appropriate CT and RC variables. Subsequently, the CT and RC variables were combined to form a composite COVID-19 situational matrix (SL). The SL matrix was validated using correlation analysis with COVID-19 case trends. Subsequently, an automated web-based system that generated daily CT, RC, and SL was developed.

RESULTS

CT and RC variables were estimated using case incidence and hospitalization rate; Hospital bed capacity and COVID-19 ICU occupancy respectively. The estimated CT and RC were strongly correlated [ρ = 0.806 (95% CI 0.752, 0.848); and ρ = 0.814 (95% CI 0.778, 0.839), p < 0.001] with the COVID-19 cases. The estimated SL was strongly correlated with COVID-19 cases (ρ = 0.845, p < 0.001) and responded well to the various COVID-19 case trends during the pandemic. SL changes occurred earlier during the increase of cases but slower during the decrease, indicating a conservative response. The automated web-based system developed produced daily real-time CT, RC, and SL for the COVID-19 pandemic.

CONCLUSIONS

The indicators selected and combinations formed were able to generate validated daily CT and RC levels for Malaysia. Subsequently, the CT and RC levels were able to provide accurate and sensitive information for the estimation of SL which provided valuable evidence on the progression of the pandemic and movement restriction adjustment for the control of Malaysia.

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in Latin America and the Caribbean: Longitudinal Trend Analysis

BACKGROUND

In May 2020, the World Health Organization (WHO) declared Latin America and the Caribbean (LAC) the epicenter of the COVID-19 pandemic, with over 40% of worldwide COVID-19-related deaths at the time. This high disease burden was a result of the unique circumstances in LAC.

OBJECTIVE

This study aimed to (1) measure whether the pandemic was expanding or contracting in LAC when the WHO declared the end of COVID-19 as a public health emergency of international concern on May 5, 2023; (2) use dynamic and genomic surveillance methods to describe the history of the pandemic in the region and situate the window of the WHO declaration within the broader history; and (3) provide, with a focus on prevention policies, a historical context for the course of the pandemic in the region.

METHODS

In addition to updates of traditional surveillance data and dynamic panel estimates from the original study, we used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID) to identify the appearance and duration of variants of concern (VOCs). We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Additionally, we conducted a 1-sided t test for whether the regional weekly speed (rate of novel COVID-19 transmission) was greater than an outbreak threshold of 10. We ran the test iteratively with 6 months of data across the period from August 2020 to May 2023.

RESULTS

The speed of pandemic spread for the region had remained below the outbreak threshold for 6 months by the time of the WHO declaration. Acceleration and jerk were also low and stable. Although the 1- and 7-day persistence coefficients remained statistically significant for the 120-day period ending on the week of May 5, 2023, the coefficients were relatively modest in magnitude (0.457 and 0.491, respectively). Furthermore, the shift parameters for either of the 2 most recent weeks around May 5, 2023, did not indicate any change in this clustering effect of cases on future cases. From December 2021 onward, Omicron was the predominant VOC in sequenced viral samples. The rolling t test of speed=10 became entirely insignificant from January 2023 onward.

CONCLUSIONS

Although COVID-19 continues to circulate in LAC, surveillance data suggest COVID-19 is endemic in the region and no longer reaches the threshold of the pandemic definition. However, the region experienced a high COVID-19 burden in the early stages of the pandemic, and prevention policies should be an immediate focus in future pandemics. Ahead of vaccination development, these policies can include widespread testing of individuals and an epidemiological task force with a contact-tracing system.

Revealing Decision-Making Strategies of Americans in Taking COVID-19 Vaccination

Efficient coverage for newly developed vaccines requires knowing which groups of individuals will accept the vaccine immediately and which will take longer to accept or never accept. Of those who may eventually accept the vaccine, there are two main types: success-based learners, basing their decisions on others' satisfaction, and myopic rationalists, attending to their own immediate perceived benefit. We used COVID-19 vaccination data to fit a mechanistic model capturing the distinct effects of the two types on the vaccination progress. We proved the identifiability of the population proportions of each type and estimated that 47 % of Americans behaved as myopic rationalists with a high variation across the jurisdictions, from 31 % in Mississippi to 76 % in Vermont. The proportion was correlated with the vaccination coverage, proportion of votes in favor of Democrats in 2020 presidential election, and education score.

Information processing style and institutional trust as factors of COVID vaccine hesitancy

This study investigates the factors contributing to COVID vaccine hesitancy. Vaccine hesitancy has commonly been attributed to susceptibility to misinformation and linked to particular socio-demographic factors and personality traits. We present a new perspective, emphasizing the interplay between individual cognitive styles and perceptions of public health institutions. In January 2020, before the COVID-19 pandemic, 318 participants underwent a comprehensive assessment, including self-report measures of personality and clinical characteristics, as well as a behavioral task that assessed information processing styles. During 2021, attitudes towards vaccines, scientists, and the CDC were measured at three time points (February-October). Panel data analysis and structural equation modeling revealed nuanced relationships between these measures and information processing styles over time. Trust in public health institutions, authoritarian submission, and lower information processing capabilities together contribute to vaccine acceptance. Information processing capacities influenced vaccination decisions independently from the trust level, but their impact was partially mediated by authoritarian tendencies. These findings underscore the multifactorial nature of vaccine hesitancy, which emerges as a product of interactions between individual cognitive styles and perceptions of public health institutions. This novel perspective provides valuable insights into the underlying mechanisms that drive this complex phenomenon.

Central Asian Surveillance Metrics and History of the COVID-19 Pandemic: Longitudinal Analyses

BACKGROUND

This study updates the COVID-19 pandemic surveillance in Central Asia we first conducted in 2020 by providing two additional years of data for the region. The historical context provided through additional data can inform regional preparedness and early responses to infectious outbreaks of either the SARS-CoV-2 virus or future pathogens in Central Asia.

OBJECTIVE

First, we aim to measure whether there was an expansion or contraction in the pandemic in Central Asia when the World Health Organization (WHO) declared the end of the public health emergency for the COVID-19 pandemic on May 5, 2023. Second, we use dynamic and genomic surveillance methods to describe the history of the pandemic in the region and situate the window of the WHO declaration within the broader history. Third, we aim to provide historical context for the course of the pandemic in Central Asia.

METHODS

Traditional surveillance metrics, including counts and rates of COVID-19 transmissions and deaths, and enhanced surveillance indicators, including speed, acceleration, jerk, and persistence, were used to measure shifts in the pandemic. To identify the appearance and duration of variants of concern, we used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID). We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Finally, we conducted a one-sided t-test for whether regional speed was greater than an outbreak threshold of ten. We ran the test iteratively with six months of data across the sample period.

RESULTS

Speed for the region had remained below the outbreak threshold for seven months by the time of the WHO declaration. Acceleration and jerk were also low and stable. While the 1- and 7-day persistence coefficients remained statistically significant, the coefficients were relatively small in magnitude (0.125 and 0.347, respectively). Furthermore, the shift parameters for either of the two most recent weeks around May 5, 2023, were both significant and negative, meaning the clustering effect of new COVID-19 cases became even smaller in the two weeks around the WHO declaration. From December 2021 onward, Omicron was the predominant variant of concern in sequenced viral samples. The rolling t-test of speed equal to ten became entirely insignificant for the first time in March of 2023.

CONCLUSIONS

While COVID-19 continues to circulate in Central Asia, the rate of transmission remained well below the threshold of an outbreak for seven months ahead of the WHO declaration. COVID-19 appeared to be endemic in the region and no longer reached the threshold of pandemic. Both standard and enhanced surveillance metrics suggest the pandemic had ended by the time of the WHO declaration.

Predicting COVID-19 Vaccination Intentions to Inform Evidence-Based Messaging for Building Vaccine Confidence Among Rural Americans

PURPOSE

Examine possible message topics to promote rural vaccination using psychosocial antecedents of vaccination.

DESIGN

Cross-sectional survey administered by Research America, Inc.

SETTING

West Virginia (WV).

SAMPLE

756 WV adults via convenience sample (n = 370; ∼2% response rate from online panel of ∼20 000 WV residents), and random digit dial of landlines (n = 174; ∼1% response rate from 18 432 numbers) and cellphones (n = 212; ∼1% response rate from 20 486 numbers).

MEASURES

Outcome measures included self-reported vaccination intention and behavior. Predictor measures, rooted in theories of social and behavioral science that have been found to be predictive of vaccination outcomes (i.e., Reasoned Action Approach, Extended Parallel Process Model), included perceived severity and susceptibility, negative affect, instrumental and affective attitudes, social norms, self-efficacy, response efficacy, and perceived control.

ANALYSIS

Multivariate linear regression for intention and logistic regression for behavior.

RESULTS

Intention was positively predicted by affective attitude, β = .30, P < .05, instrumental attitude, β = .19, P < .05, response efficacy, β = .19, P < .05, negative affect, β = .16, P < .05, self-efficacy, β = .13, P < .05, and subjective norm, β = .13, P < .05, F(10, 267) = 30.12, Adj. R2 = .53. Vaccination status was predicted by instrumental attitude, exp(B) = 2.09, and subjective norm, exp(B) = 2.00, Pseudo R2 = .29, log likelihood = 125.11, χ2(10) = 38.34, P < .05. Promising message targets were instrumental attitude, M = 3.21, SD = 1.46, and subjective norms, M = 3.76, SD = 1.71.

CONCLUSION

COVID-19 vaccine confidence messages should address (1) positive feelings and safety perceptions, (2) vaccination's effectiveness in preventing serious COVID-19, and (3) subjective vaccination norms.

Examining nurses' understanding and knowledge about preparation for COVID-19 in Ardabil hospitals in Iran

AIMS

The purpose of this study was to evaluate the preparedness of Iranian nurses for potential pandemics.

BACKGROUND

Nurses play a critical role in managing pandemics. They require adequate training, proper equipment, and organizational support to be well-prepared.

METHODS

A descriptive cross-sectional study was conducted in Ardabil, Iran, from July to September 2023, involving 233 nurses from five hospitals. The number of nurses required for each hospital was calculated based on the proportion of nurses in each hospital. Data was collected through a paper-based form that included information about the participants' demographic characteristics and their level of pandemic preparedness in health services. The collected data was analyzed using descriptive statistics to determine the demographic characteristics and levels of pandemic preparedness. Pearson's test was also conducted to establish a relationship between different dimensions of pandemic preparedness.

RESULTS

Most participants relied on clinical measures and supported using human resources and environmental methods to curb the transmission of a pandemic. They felt assured in their ability to explain the preventive measures against the pandemic. However, fewer respondents had access to healthcare improvement programs, and only a few worked remotely from home.

CONCLUSIONS

According to our study, 90.1% of nurses believe hand washing is the most effective way to prevent spreading infections. Additionally, healthcare professionals can use various tools to respond to the pandemic, including screening for COVID-19 at work, health and wellness programs, telecommuting, COVID-19 Safe programs, social media, and posters. Nurses need continuous education in hand hygiene, health programs, remote work options, and pandemic-safe programs to control infections, reduce risks, and optimize patient care during the pandemic.

Assessing the perceived effect of non-pharmaceutical interventions on SARS-Cov-2 transmission risk: an experimental study in Europe

We conduct a large (N = 6567) online experiment to measure the features of non-pharmaceutical interventions (NPIs) that citizens of six European countries perceive to lower the risk of transmission of SARS-Cov-2 the most. We collected data in Bulgaria (n = 1069), France (n = 1108), Poland (n = 1104), Italy (n = 1087), Spain (n = 1102) and Sweden (n = 1097). Based on the features of the most widely adopted public health guidelines to reduce SARS-Cov-2 transmission (mask wearing vs not, outdoor vs indoor contact, short vs 90 min meetings, few vs many people present, and physical distancing of 1 or 2 m), we conducted a discrete choice experiment (DCE) to estimate the public's perceived risk of SARS-CoV-2 transmission in scenarios that presented mutually exclusive constellations of these features. Our findings indicate that participants' perception of transmission risk was most influenced by the NPI attributes of mask-wearing and outdoor meetings and the least by NPI attributes that focus on physical distancing, meeting duration, and meeting size. Differentiating by country, gender, age, cognitive style (reflective or intuitive), and perceived freight of COVID-19 moreover allowed us to identify important differences between subgroups. Our findings highlight the importance of improving health policy communication and citizens' health literacy about the design of NPIs and the transmission risk of SARS-Cov-2 and potentially future viruses.

Examining associations between social vulnerability indices and COVID-19 incidence and mortality with spatial-temporal Bayesian modeling

This study compares two social vulnerability indices, the U.S. CDC SVI and SoVI (the Social Vulnerability Index developed at the Hazards Vulnerability & Resilience Institute at the University of South Carolina), on their ability to predict the risk of COVID-19 cases and deaths. We utilize COVID-19 cases and deaths data for the state of Indiana from the Regenstrief Institute in Indianapolis, Indiana, from March 1, 2020, to March 31, 2021. We then aggregate the COVID-19 data to the census tract level, obtain the input variables, domains (components), and composite measures of both CDC SVI and SoVI data to create a Bayesian spatial-temporal ecological regression model. We compare the resulting spatial-temporal patterns and relative risk (RR) of SARS-CoV-2 infection (COVID-19 cases) and associated death. Results show there are discernable spatial-temporal patterns for SARS-CoV-2 infections and deaths with the largest contiguous hotspot for SARS-CoV-2 infections found in the southwest of the Indianapolis metropolitan area. We also observed one large contiguous hotspot for deaths that stretches across Indiana from the Cincinnati area in the southeast to just east and north of Terre Haute (southeast to west central). The spatial-temporal Bayesian model shows that a 1-percentile increase in CDC SVI was significantly (p ≤ 0.05) associated with an increased risk of SARS-CoV-2 infection by 6 % (RR = 1.06, 95 %CI = 1.04 -1.08). Whereas a 1-percentile increase in SoVI was significantly predicted to increase the risk of COVID-19 death by 45 % (RR = 1.45, 95 %CI =1.38 - 1.53). Domain-specific variables related to socioeconomic status, age, and race/ethnicity were shown to increase the risk of SARS-CoV-2 infections and deaths. There were notable differences in the relative risk estimates for SARS-CoV-2 infections and deaths when each of the two indices were incorporated in the model. Observed differences between the two social vulnerability indices and infection and death are likely due to alternative methodologies of formation and differences in input variables. The findings add to the growing literature on the relationship between social vulnerability and COVID-19 and further the development of COVID-19-specific vulnerability indices by illustrating the utility of local spatial-temporal analysis.

"Back to the future" projections for COVID-19 surges

We argue that information from countries who had earlier COVID-19 surges can be used to inform another country's current model, then generating what we call back-to-the-future (BTF) projections. We show that these projections can be used to accurately predict future COVID-19 surges prior to an inflection point of the daily infection curve. We show, across 12 different countries from all populated continents around the world, that our method can often predict future surges in scenarios where the traditional approaches would always predict no future surges. However, as expected, BTF projections cannot accurately predict a surge due to the emergence of a new variant. To generate BTF projections, we make use of a matching scheme for asynchronous time series combined with a response coaching SIR model.

Looking beyond vaccines: Cultural tightness-looseness moderates the relationship between immunization coverage and disease prevention vigilance

Advancements in vaccination technologies mitigate disease transmission risks but may inadvertently suppress the behavioral immune system, an evolved disease avoidance mechanism. Applying behavioral immune system theory and utilizing robust big data analytics, we examined associations between rising vaccination coverage and government policies, public mobility, and online information seeking regarding disease precautions. We tested whether cultural tightness-looseness moderates the relationship between mass immunization and disease prevention vigilance. Comprehensive time series analyses were conducted using American data (Study 1) and international data (Study 2), employing transfer function modeling, cross-correlation function analysis, and meta-regression analysis. Across both the US and global analyses, as vaccination rates rose over time, government COVID-19 restrictions significantly relaxed, community mobility increased, and online searches for prevention information declined. The relationship between higher vaccination rates and lower disease prevention vigilance was stronger in culturally looser contexts. Results provide initial evidence that mass immunization may be associated with attenuated sensitivity and enhanced flexibility of disease avoidance psychology and actions. However, cultural tightness-looseness significantly moderates this relationship, with tighter cultures displaying sustained vigilance amidst immunization upticks. These findings offer valuable perspectives to inform nuanced policymaking and public health strategies that balance prudent precautions against undue alarm when expanding vaccine coverage worldwide.

Dynamically adjustable SVEIR(MH) model of multiwave epidemics: Estimating the effects of public health measures against COVID-19

The COVID-19 pandemic was characterized by multiple subsequent, overlapping outbreaks, as well as extremely rapid changes in viral genomes. The information about local epidemics spread and the epidemic control measures was shared on a daily basis (number of cases and deaths) via centralized repositories. The vaccines were developed within the first year of the pandemic. New modes of monitoring and sharing of epidemic data were implemented using Internet resources. We modified the basic SEIR compartmental model to include public health measures, multiwave scenarios, and the variation of viral infectivity and transmissibility reflected by the basic reproduction number R0 of emerging viral variants. SVEIR(MH) model considers the capacity of the medical system, lockdowns, vaccination, and changes in viral reproduction rate on the epidemic spread. The developed model uses daily infection reports for assessing the epidemic dynamics, and daily changes of mobility data from mobile phone networks to assess the lockdown effectiveness. This model was deployed to six European regions Baden-Württemberg (Germany), Belgium, Czechia, Lombardy (Italy), Sweden, and Switzerland for the first 2 years of the pandemic. The correlation coefficients between observed and reported infection data showed good concordance for both years of the pandemic (ρ = 0.84-0.94 for the raw data and ρ = 0.91-0.98 for smoothed 7-day averages). The results show stability across the regions and the different epidemic waves. Optimal control of epidemic waves can be achieved by dynamically adjusting epidemic control measures in real-time. SVEIR(MH) model can simulate different scenarios and inform adjustments to the public health policies to achieve the target outcomes. Because this model is highly representative of actual epidemic situations, it can be used to assess both the public health and socioeconomic effects of the public health measures within the first 7 days of the outbreak.

Association of a promotional campaign for local dining facilities with the occurrence of COVID-19 in Asahikawa City, Japan, in November 2021

Objectives

As social restrictions of COVID-19 are being eased worldwide, preventing SARS-CoV-2 transmission among staff members and customers in dining facilities is essential to continuously running business because restaurants and bars are high-risk locations for COVID-19 outbreaks. In 2021, COVID-19 outbreaks occurred at restaurants or bars in Asahikawa city, Japan two weeks after the launch of a promotional campaign for local dining facilities. We investigated this event to assess the association between the promotional campaign and the occurrence of SARS-CoV-2 infection.

Study design

Cohort study.

Methods

We assessed the association between the occurrence of COVID-19 cases in the restaurants and bars and their participation in the campaign by calculating risk ratio and 95% confidence interval.

Results

Cases were identified among workers or customers in 4.0% (4/101) of the participating restaurants or bars and in 1.2% (39/3257) of the non-participating restaurants or bars. The risk ratio was 3.3 (95% confidence interval 1.2-9.0).

Conclusion

The association between the occurrence of SARS-CoV-2 infection in the restaurants or bars and participation in the campaign is undeniable. Promotional campaigns to vitalize dining facilities should be accompanied by enhanced infection prevention measures, especially ventilation.

Health and education concerns about returning to campus and online learning during the COVID-19 pandemic among US undergraduate STEM majors

OBJECTIVE

We examined undergraduates' concerns about returning to campus and online learning from home.

PARTICIPANTS

Undergraduates majoring in STEM (Science, Technology, Engineering, and Mathematics) at US universities/colleges.

METHODS

Participants completed an online survey in July 2020. We content-analyzed responses to open-ended questions about concerns about fall 2020.

RESULTS

Students (N = 64) were 52% women, 47% low socioeconomic status (SES), and 27% non-Hispanic white. Concerns about returning to campus included student noncompliance with university COVID-19 prevention guidelines (28%), infection risk (28%), poor instructional quality (26%), inadequate university plans for preventing/handling outbreaks (25%), negative impacts on social interactions (11%), and transportation/commuting (11%). Concerns about learning from home included difficulty focusing on schoolwork (58%), lack of hands-on/experiential learning (24%), negative impacts on social interactions (19%), family/home environment (15%), concerns that online learning wastes time/money (10%), and inadequate technology/Internet access (5%).

CONCLUSIONS

Universities should address student concerns and provide resources to overcome barriers to effective learning.

Reactogenicity, immunogenicity and breakthrough infections following heterologous or fractional second dose COVID-19 vaccination in adolescents (Com-COV3): A randomised controlled trial

BACKGROUND

This was the first study to investigate the reactogenicity and immunogenicity of heterologous or fractional second dose COVID-19 vaccine regimens in adolescents.

METHODS

A phase II, single-blind, multi-centre, randomised-controlled trial recruited across seven UK sites from September to November 2021, with follow-up visits to August 2022. Healthy 12-to-16 years olds were randomised (1:1:1) to either 30 µg BNT162b2 (BNT-30), 10 µg BNT162b2 (BNT-10), or NVX-CoV2373 (NVX), 8 weeks after a first 30 µg dose of BNT162b2. The primary outcome was solicited systemic reactions in the week following vaccination. Secondary outcomes included immunogenicity and safety. 'Breakthrough infection' analyses were exploratory.

FINDINGS

148 participants were recruited (median age 14 years old, 62% female, 26% anti-nucleocapsid IgG seropositive pre-second dose); 132 participants received a second dose. Reactions were mostly mild-to-moderate, with lower rates in BNT-10 recipients. No vaccine-related serious adverse events occurred. Compared to BNT-30, at 28 days post-second dose anti-spike antibody responses were similar for NVX (adjusted geometric mean ratio [aGMR]) 1.09 95% confidence interval (CI): 0.84, 1.42] and lower for BNT-10 (aGMR 0.78 [95% CI: 0.61, 0.99]). For Omicron BA.1 and BA.2, the neutralising antibody titres for BNT-30 at day 28 were similar for BNT-10 (aGMR 1.0 [95% CI: 0.65, 1.54] and 1.02 [95% CI: 0.71, 1.48], respectively), but higher for NVX (aGMR 1.7 [95% CI: 1.07, 2.69] and 1.43 [95% CI: 0.96, 2.12], respectively). Compared to BNT-30, cellular immune responses were greatest for NVX (aGMR 1.73 [95% CI: 0.94, 3.18]), and lowest for BNT-10 (aGMR 0.65 [95% CI: 0.37, 1.15]) at 14 days post-second dose. Cellular responses were similar across the study arms by day 236 post-second dose. Amongst SARS-CoV-2 infection naïve participants, NVX participants had an 89% reduction in risk of self-reported 'breakthrough infection' compared to BNT-30 (adjusted hazard ratio [aHR] 0.11 [95% CI: 0.01, 0.86]) up until day 132 after second dose. BNT-10 recipients were more likely to have a 'breakthrough infection' compared to BNT-30 (aHR 2.14 [95% CI: 1.02, 4.51]) up to day 132 and day 236 post-second dose. Antibody responses at 132 and 236 days after second dose were similar for all vaccine schedules.

INTERPRETATION

Heterologous and fractional dose COVID-19 vaccine schedules in adolescents are safe, well-tolerated and immunogenic. The enhanced performance of the heterologous schedule using NVX-CoV2373 against the Omicron SARS-CoV-2 variant suggests this mRNA prime and protein-subunit boost schedule may provide a greater breadth of protection than the licensed homologous schedule.

FUNDING

National Institute for Health Research and Vaccine Task Force.

TRIAL REGISTRATION

International Standard Randomised Controlled Trial Number registry: 12348322.

Bayesian sequential approach to monitor COVID-19 variants through test positivity rate from wastewater

Deployment of clinical testing on a massive scale was an essential control measure for curtailing the burden of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and the magnitude of the COVID-19 (coronavirus disease 2019) pandemic during its waves. As the pandemic progressed, new preventive and surveillance mechanisms emerged. Implementation of vaccine programs, wastewater (WW) surveillance, and at-home COVID-19 antigen tests reduced the demand for mass SARS-CoV-2 testing. Unfortunately, reductions in testing and test reporting rates also reduced the availability of public health data to support decision-making. This paper proposes a sequential Bayesian approach to estimate the COVID-19 test positivity rate (TPR) using SARS-CoV-2 RNA concentrations measured in WW through an adaptive scheme incorporating changes in virus dynamics. The proposed modeling framework was applied to WW surveillance data from two WW treatment plants in California; the City of Davis and the University of California, Davis campus. TPR estimates are used to compute thresholds for WW data using the Centers for Disease Control and Prevention thresholds for low (<5% TPR), moderate (5%-8% TPR), substantial (8%-10% TPR), and high (>10% TPR) transmission. The effective reproductive number estimates are calculated using TPR estimates from the WW data. This approach provides insights into the dynamics of the virus evolution and an analytical framework that combines different data sources to continue monitoring COVID-19 trends. These results can provide public health guidance to reduce the burden of future outbreaks as new variants continue to emerge. IMPORTANCE We propose a statistical model to correlate WW with TPR to monitor COVID-19 trends and to help overcome the limitations of relying only on clinical case detection. We pose an adaptive scheme to model the nonautonomous nature of the prolonged COVID-19 pandemic. The TPR is modeled through a Bayesian sequential approach with a beta regression model using SARS-CoV-2 RNA concentrations measured in WW as a covariable. The resulting model allows us to compute TPR based on WW measurements and incorporates changes in viral transmission dynamics through an adaptive scheme.

Investigating the effects of vaccine on COVID-19 disease propagation using a Bayesian approach

The causal impact of COVID-19 vaccine coverage on effective reproduction number R(t) under the disease control measures in the real-world scenario is understudied, making the optimal reopening strategy (e.g., when and which control measures are supposed to be conducted) during the recovery phase difficult to design. In this study, we examine the demographic heterogeneity and time variation of the vaccine effect on disease propagation based on the Bayesian structural time series analysis. Furthermore, we explore the role of non-pharmaceutical interventions (NPIs) and the entrance of the Delta variant of COVID-19 in the vaccine effect for U.S. counties. The analysis highlights several important findings: First, vaccine effects vary among the age-specific population and population densities. The vaccine effect for areas with high population density or core airport hubs is 2 times higher than for areas with low population density. Besides, areas with more older people need a high vaccine coverage to help them against the more contagious variants (e.g., the Delta variant). Second, the business restriction policy and mask requirement are more effective in preventing COVID-19 infections than other NPI measures (e.g., bar closure, gather ban, and restaurant restrictions) for areas with high population density and core airport hubs. Furthermore, the mask requirement consistently amplifies the vaccine effects against disease propagation after the presence of contagious variants. Third, areas with a high percentage of older people are suggested to postpone relaxing the restaurant restriction or gather ban since they amplify the vaccine effect against disease infections. Such empirical insights assist recovery phases of the pandemic in designing more efficient reopening strategies, vaccine prioritization, and allocation policies.

Geographic and Socioeconomic Determinants of Full Coverage COVID-19 Vaccination in Peru: Findings from a National Population-Based Study

Despite the fact that vaccination coverage against COVID-19 has made great progress in Peru, there is still a quarter of the population that has not been fully vaccinated. This study aims to determine the factors associated with complete vaccination in Peruvian adults. An analysis of the National Household Survey 2022 in Peru was performed. Prevalence ratios with their 95% confidence intervals (95% CI) were estimated to assess the factors associated with vaccination with three or more doses of the COVID-19 vaccine. A total of 58,471 participants were included in the study and 75.8% of the surveyed population were found to have received full vaccination. Significant differences in complete coverage were observed according to sex, age, educational level, ethnicity, poverty status, and geographic location. In the adjusted analysis, individuals aged 60 years or older, those with higher educational attainment, the non-poor, and those living in urban areas were more likely to be fully vaccinated. Native individuals and people who live in households without media are less likely to be fully covered. These results highlight the importance of considering demographic and socioeconomic factors when analyzing COVID-19 vaccination coverage. Additional strategies are needed to address vaccination gaps and ensure better vaccination coverage.

Differential COVID-19 preventive behaviors among Asian subgroups in the United States

BACKGROUND

Given the observed within-Asian disparity in COVID-19 incidence, we aimed to explore the differential preventive behaviors among Asian subgroups in the United States.

METHODS

Based on data from the Asian subsample (N = 982) of the 2020 Health, Ethnicity, and Pandemic survey, we estimated the weighted proportion of noncompliance with Centers for Disease Control and Prevention (CDC) guidelines on preventive behaviors and COVID-19 testing by Asian subgroups (Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, Other Asian). We examined these subgroup differences after adjusting for demographic factors and state-level clustering.

RESULTS

Filipinos demonstrated the lowest rate of noncompliance for mask-wearing, social distancing, and handwashing. As compared with the Filipinos, our logistic models showed that the Chinese and the 'other Asians' subgroup had significantly higher risk of noncompliance with mask-wearing, while the Japanese, the Vietnamese, and other Asians were significantly more likely to report noncompliance with social distancing.

CONCLUSIONS

The significant variation of preventive behavior across Asian subgroups signals the necessity of data disaggregation when it comes to understanding the health behavior of Asian Americans, which is critical for future pandemic preparedness. The excess behavioral risk among certain Asian subgroups (especially those 'other Asians') warrants further investigation and interventions about the driving forces behind these disparities.

COVID-19 Vaccine Perceptions among Ebola-Affected Communities in North Kivu, Democratic Republic of the Congo, 2021

Populations affected by humanitarian crises and emerging infectious disease outbreaks may have unique concerns and experiences that influence their perceptions toward vaccines. In March 2021, we conducted a survey to examine the perceptions toward COVID-19 vaccines and identify the factors associated with vaccine intention among 631 community members (CMs) and 438 healthcare workers (HCWs) affected by the 2018-2020 Ebola Virus Disease outbreak in North Kivu, Democratic Republic of the Congo. A multivariable logistic regression was used to identify correlates of vaccine intention. Most HCWs (81.7%) and 53.6% of CMs felt at risk of contracting COVID-19; however, vaccine intention was low (27.6% CMs; 39.7% HCWs). In both groups, the perceived risk of contracting COVID-19, general vaccine confidence, and male sex were associated with the intention to get vaccinated, with security concerns preventing vaccine access being negatively associated. Among CMs, getting the Ebola vaccine was associated with the intention to get vaccinated (RR 1.43, 95% CI 1.05-1.94). Among HCWs, concerns about new vaccines' safety and side effects (OR 0.72, 95% CI 0.57-0.91), religion's influence on health decisions (OR 0.45, 95% CI 0.34-0.61), security concerns (OR 0.52, 95% CI 0.37-0.74), and governmental distrust (OR 0.50, 95% CI 0.35-0.70) were negatively associated with vaccine perceptions. Enhanced community engagement and communication that address this population's concerns could help improve vaccine perceptions and vaccination decisions. These findings could facilitate the success of vaccine campaigns in North Kivu and similar settings.

Genomic Surveillance of SARS-CoV-2 Variants in the Dominican Republic and Emergence of a Local Lineage

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an RNA virus that evolves over time, leading to new variants. In the current study, we assessed the genomic epidemiology of SARS-CoV-2 in the Dominican Republic. A total of 1149 SARS-CoV-2 complete genome nucleotide sequences from samples collected between March 2020 and mid-February 2022 in the Dominican Republic were obtained from the Global Initiative on Sharing All Influenza Data (GISAID) database. Phylogenetic relationships and evolution rates were analyzed using the maximum likelihood method and the Bayesian Markov chain Monte Carlo (MCMC) approach. The genotyping details (lineages) were obtained using the Pangolin web application. In addition, the web tools Coronapp, and Genome Detective Viral Tools, among others, were used to monitor epidemiological characteristics. Our results show that the most frequent non-synonymous mutation over the study period was D614G. Of the 1149 samples, 870 (75.74%) were classified into 8 relevant variants according to Pangolin/Scorpio. The first Variants Being Monitored (VBM) were detected in December 2020. Meanwhile, in 2021, the variants of concern Delta and Omicron were identified. The mean mutation rate was estimated to be 1.5523 × 10^-3 (95% HPD: 1.2358 × 10^-3, 1.8635 × 10^-3) nucleotide substitutions per site. We also report the emergence of an autochthonous SARS-CoV-2 lineage, B.1.575.2, that circulated from October 2021 to January 2022, in co-circulation with the variants of concern Delta and Omicron. The impact of B.1.575.2 in the Dominican Republic was minimal, but it then expanded rapidly in Spain. A better understanding of viral evolution and genomic surveillance data will help to inform strategies to mitigate the impact on public health.

Effects of Return-to-Office, Public Schools Reopening, and Vaccination Mandates on COVID-19 Cases Among Municipal Employee Residents of New York City

OBJECTIVE

On September 13, 2021, teleworking ended for New York City municipal employees, and Department of Education employees returned to reopened schools. On October 29, COVID-19 vaccination was mandated. We assessed these mandates' short-term effects on disease transmission.

METHODS

Using difference-in-difference analyses, we calculated COVID-19 incidence rate ratios (IRRs) among residents 18 to 64 years old by employment status before and after policy implementation.

RESULTS

IRRs after (September 23-October 28) versus before (July 5-September 12) the return-to-office mandate were similar between office-based City employees and non-City employees. Among Department of Education employees, the IRR after schools reopened was elevated by 28.4% (95% confidence interval, 17.3%-40.3%). Among City employees, the IRR after (October 29-November 30) versus before (September 23-October 28) the vaccination mandate was lowered by 20.1% (95% confidence interval, 13.7%-26.0%).

CONCLUSIONS

Workforce mandates influenced disease transmission, among other societal effects.

Efficacy and safety of tixagevimab-cilgavimab as pre-exposure prophylaxis for COVID-19: A systematic review and meta-analysis

Some proportions of populations, such as immunocompromised patients and organ transplant recipients might have inadequate immune responses to the vaccine for coronavirus disease 2019 (COVID-19). For these groups of populations, administering monoclonal antibodies might offer some additional protection. This review sought to analyze the effectiveness and safety of tixagevimab-cilgavimab (Evusheld) as pre-exposure prophylaxis against COVID-19. We used specific keywords to comprehensively search for potential studies on PubMed, Scopus, Europe PMC, and ClinicalTrials.gov sources until 3 September 2022. We collected all published articles that analyzed tixagevimab-cilgavimab on the course of COVID-19. Review Manager 5.4 was utilized for statistical analysis. Six studies were included. Our pooled analysis revealed that tixagevimab-cilgavimab prophylaxis may decrease the rate of SARS-CoV-2 infection (OR: 0.24; 95% CI: 0.15-0.40, p < 0.00001, I²  = 75%), lower COVID-19 hospitalization rate (OR: 0.13; 95% CI: 0.07-0.24, p < 0.00001, I²  = 0%), decrease the severity risk (OR: 0.13; 95% CI: 0.07-0.24, p < 0.00001, I²  = 0%), and lower COVID-19 deaths (OR: 0.17; 95% CI: 0.03-0.99, p = 0.05, I²  = 72%). In the included studies, no major adverse events were reported. This study proposes that tixagevimab-cilgavimab was effective and safe for preventing COVID-19. Tixagevimab-cilgavimab may be offered to those who cannot be vaccinated or have inadequate immune response from the COVID-19 vaccine to give additional protection.

Function of the Speech Recognition of the Smartphone to Automatically Operate a Portable Sample Pretreatment Microfluidic System

We proposed a portable sample pretreatment microsystem, which can be automatically operated through speech recognition in a smartphone app. The proposed sample pretreatment microsystem consists of a microfluidic chip, an air router, pressure and vacuum lines with air pump motors, six 3-way solenoid valves, and a microcontroller with a Bluetooth module. The command of a human voice conducted the whole process of DNA extraction from pathogenic bacterial samples. Thus, manual interference during the DNA extraction is eliminated, preventing any potential infection from human touch. The palm-sized sample pretreatment microsystem can be run by a portable battery or a conventional smartphone charger. Genomic DNA ofSalmonella typhimuriumwas purified on a chip in less than 1 min with an extraction efficiency of 70 ± 5%.

The United States public health services failure to control the coronavirus epidemic

The unprecedented COVID-19 epidemic in the United States (US) and worldwide, caused by a new type of coronavirus (SARS-CoV-2), occurred mostly because of higher-than-expected transmission speed and degree of virulence compared with previous respiratory virus outbreaks, especially earlier Coronaviruses with person-to-person transmission (e.g., MERS, SARS). The epidemic's size and duration, however, are mostly a function of failure of public health systems to prevent/control the epidemic. In the US, this failure was due to historical disinvestment in public health services, key players equivocating on decisions, and political interference in public health actions. In this communication, we present a summary of these failures, discuss root causes, and make recommendations for improvement with focus on public health decisions.

Bayesian sequential approach to monitor COVID-19 variants through positivity rate from wastewater

Trends in COVID-19 infection have changed throughout the pandemic due to myriad factors, including changes in transmission driven by social behavior, vaccine development and uptake, mutations in the virus genome, and public health policies. Mass testing was an essential control measure for curtailing the burden of COVID-19 and monitoring the magnitude of the pandemic during its multiple phases. However, as the pandemic progressed, new preventive and surveillance mechanisms emerged. Implementing vaccine programs, wastewater (WW) surveillance, and at-home COVID-19 tests reduced the demand for mass severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing. This paper proposes a sequential Bayesian approach to estimate the COVID-19 positivity rate (PR) using SARS-CoV-2 RNA concentrations measured in WW through an adaptive scheme incorporating changes in virus dynamics. PR estimates are used to compute thresholds for WW data using the CDC thresholds for low, substantial, and high transmission. The effective reproductive number estimates are calculated using PR estimates from the WW data. This approach provides insights into the dynamics of the virus evolution and an analytical framework that combines different data sources to continue monitoring the COVID-19 trends. These results can provide public health guidance to reduce the burden of future outbreaks as new variants continue to emerge. The proposed modeling framework was applied to the City of Davis and the campus of the University of California Davis.

Implementation barriers and facilitators to a COVID-19 intervention in Bangladesh: The benefits of engaging the community for the delivery of the programme

BACKGROUND

BRAC (Bangladesh Rural Advancement Committee), the largest NGO globally, implemented a community-based comprehensive social behavior communication intervention to increase community resilience through prevention, protection, and care for COVID-19. We conducted implementation research to assess fidelity and explore the barriers and facilitators of this intervention implementation.

METHODS

We adopted a concurrent mixed-method triangulation design. We interviewed 666 members of 60 Community Corona Protection Committees (CCPCs) and 80 members of 60 Community Support Teams (CSTs) through multi-stage cluster sampling using a structured questionnaire. The qualitative components relied on 54 key informant interviews with BRAC implementers and government providers.

RESULTS

The knowledge about wearing mask, keeping social distance, washing hands and COVID-19 symptoms were high (on average more than 70%) among CCPC and CST members. While 422 (63.4%) CCPC members reported they 'always' wear a mask while going out, 69 (86.3%) CST members reported the same practice. Only 247 (37.1%) CCPC members distributed masks, and 229 (34.4%) donated soap to the underprivileged population during the last two weeks preceding the survey. The key facilitators included influential community members in the CCPC, greater acceptability of the front-line health workers, free-of-cost materials, and telemedicine services. The important barriers identified were insufficient training, irregular participation of the CCPC members, favouritism of CCPC members in distributing essential COVID-19 preventive materials, disruption in supply and shortage of the COVID-19 preventative materials, improper use of handwashing station, the non-compliant attitude of the community people, challenges to ensure home quarantine, challenges regarding telemedicine with network interruptions, lack of coordination among stakeholders, the short duration of the project.

CONCLUSIONS

Engaging the community in combination with health services through a Government-NGO partnership is a sustainable strategy for implementing the COVID-19 prevention program. Engaging the community should be promoted as an integral component of any public health intervention for sustainability. Engagement structures should incorporate a systems perspective to facilitate the relationships, ensure the quality of the delivery program, and be mindful of the heterogeneity of different community members concerning capacity building. Finally, reaching out to the underprivileged through community engagement is also an effective mechanism to progress through universal health coverage.

The Practice of Post-vaccination COVID-19 Prevention Strategy Among Healthcare Professionals in Felege Hiwot Referral Hospital, Northwest Ethiopia

BACKGROUND

Coronavirus Disease 2019 (COVID-19) is an acute respiratory illness first discovered and identified in China. Countries are taking precautions to prevent COVID-19 in accordance with WHO guidelines.

OBJECTIVE

The objective of this study was to assess the practice of the COVID-19 prevention strategy post-vaccination and associated factors among health care professionals in Felege Hiwot Referral Hospital, Bahir Dar, Northwest Ethiopia, in 2021.

METHODS

An institutional-based cross-sectional study was carried out at Felege Hiwot Referral Hospital, Bahir Dar. Data were entered into Epi-Info software, version 7.1, and exported to SPSS, version 23, for analysis. Descriptive statistics were used to describe the socio-demographic characteristics of the respondents. The crude odds ratio (COR) and the adjusted odds ratio (AOR) with 95% CI were calculated to determine the coefficient of the COVID-19 prevention strategy.

RESULTS

In this study, 68.7% (95% CI: 63.7, 73.8) of health care professionals had good practice of the COVID-19 prevention strategy post-vaccination. Sex (AOR: 1.76; 95% CI: 1.08, 2.89), marital status (AOR: 1.75; 95% CI: 1.09, 2.93), and good attitude toward vaccination (AOR: 3.24; 95% CI: 2.13, 5.48) were significantly associated with the practice of COVID-19 prevention strategies post vaccination.

CONCLUSIONS

The practices of COVID-19 preventive strategies post-vaccination were good among healthcare professionals. Good attitude toward vaccination, sex (male), marital status (married) were factors determining the occurrences of COVID-19 preventive strategies post-vaccination.

Vaccinated Healthcare Workers' Adherence to COVID-19 Prevention Measures and Associated Factors in Northwest Ethiopia: A Facility-Based Cross-Sectional Study

Background

The initial response to coronavirus disease 2019 (COVID-19) was non-pharmaceutical interventions (NPIs). Long-term protection against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection does not appear to be possible by either infection or vaccination. Thus, traditional herd immunity seems impossible. In addition to increasing vaccination rates, NPIs may be needed.

Methods

A facility-based cross-sectional study was conducted among vaccinated healthcare workers. The study took place from July 15 to August 15, 2022. A self-administered questionnaire was used for data collection. In a multivariable logistic regression model, a p-value of less than 0.05 was considered statistically significant.

Results

Four hundred eleven healthcare workers were included in the study. Sixty percent of participants were fully vaccinated. After vaccination, 10.2% of respondents reported infection with SARS-CoV-2. The study showed that 49.4% of participants had a good knowledge of the efficacy and safety of vaccines against SARS-CoV-2. In this study, 36% of individuals adhered well to the COVID-19 prevention strategies. Good knowledge of the efficacy and safety of SARS-CoV-2 vaccines (AOR = 1.69, 95% CI: 1.03-2.78) increased the odds of implementing preventive measures. Healthcare workers who perceived a low and medium risk of SARS-CoV-2 infection after vaccination and who were knowledgeable about SARS-CoV-2 breakthrough infections were less likely to follow preventive measures.

Conclusion

The knowledge of healthcare workers regarding the efficacy and safety of vaccines against SARS-CoV-2 was comparable. However, a large proportion of healthcare workers poorly adhered to prevention practices. Therefore, to reduce the risk of SARS-CoV-2 infection among healthcare professionals, prevention strategies must be continuously evaluated and awareness of the need for preventive measures must be raised even after vaccination.

Understanding coronavirus disease 2019 (COVID-19) vaccine hesitancy: Evidence from the community-driven knowledge site Quora

Objective

The present study aims to examine the threshold of coronavirus disease 2019 (COVID-19) vaccine hesitancy over time and public discourse around COVID-19 vaccination hesitancy.

Methods

We collected 3,952 questions and 66,820 answers regarding COVID-19 vaccination posted on the social question-and-answer website Quora between June 2020 and June 2021 and employed Word2Vec and Sentiment Analysis to analyze the data. To examine changes in the perceptions and hesitancy about the COVID-19 vaccine, we segmented the data into 25 bi-weekly sections.

Results

As positive sentiment about vaccination increased, the number of new vaccinations in the United States also increased until it reached a ceiling point. The vaccine hesitancy phase was identified by the decrease in positive sentiment from its highest peak. Words that occurred only when the positive answer rate peaked (e.g., safe, plan, best, able, help) helped explain factors associated with positive perceptions toward vaccines, and the words that occurred only when the negative answer rate peaked (e.g., early, variant, scientists, mutations, effectiveness) suggested factors associated with vaccine hesitancy. We also identified a period of vaccine resistance, where people who decided not to be vaccinated were unlikely to be vaccinated without further enforcement or incentive.

Conclusions

Findings suggest that vaccine hesitancy occurred because concerns about vaccine safety were high due to a perceived lack of scientific evidence and public trust in healthcare authorities has been seriously undermined. Considering that vaccine-related conspiracy theories and fake news prevailed in the absence of reliable information sources, restoring public trust in healthcare leaders will be critical for future vaccination efforts.

Identification of phytochemicals in Qingfei Paidu decoction for the treatment of coronavirus disease 2019 by targeting the virus-host interactome

Qingfei Paidu decoction (QFPDD) has been clinically proven to be effective in the treatment of coronavirus disease 2019 (COVID-19). However, the bioactive components and therapeutic mechanisms remain unclear. This study aimed to explore the effective components and underlying mechanisms of QFPDD in the treatment of COVID-19 by targeting the virus-host interactome and verifying the antiviral activities of its active components in vitro. Key active components and targets were identified by analysing the topological features of a compound-target-pathway-disease regulatory network of QFPDD for the treatment of COVID-19. The antiviral activity of the active components was determined by a live virus infection assay, and possible mechanisms were analysed by pseudotyped virus infection and molecular docking assays. The inhibitory effects of the components tested on the virus-induced release of IL-6, IL-1β and CXCL-10 were detected by ELISA. Three components of QFPDD, oroxylin A, hesperetin and scutellarin, exhibited potent antiviral activities against live SARS-CoV-2 virus and HCoV-OC43 virus with IC₅₀ values ranging from 18.68 to 63.27 μM. Oroxylin A inhibited the entry of SARS-CoV-2 pseudovirus into target cells and inhibited SARS-CoV-2 S protein-mediated cell-cell fusion by binding with the ACE2 receptor. The active components of QFPDD obviously inhibited the IL-6, IL-1β and CXCL-10 release induced by the SARS-CoV-2 S protein. This study supports the clinical application of QFPDD and provides an effective analysis method for the in-depth study of the mechanisms of traditional Chinese medicine (TCM) in the prevention and treatment of COVID-19.

Causal Modeling of Descriptive Social Norms from Twitter and the Physical World on Expressed Attitudes Change: A Case Study of COVID-19 Vaccination

The high infection rate of SARS-CoV-2 makes it urgent to promote vaccination among the public. Previous studies found that people tend to follow the behaviors desired in descriptive social norms, which exist in both social media (e.g., Twitter) and physical-world communities. However, it remains unclear whether and to what extent the descriptive social norms from the cyber and physical communities affect people's attitude change. This study, focusing on COVID-19 vaccination, developed a Directed Acyclic Graphs model to investigate the causal effects of the descriptive social norms of (i) Twitterverse and (ii) physical-world communities on people's attitude change as well as the temporal scales of the effects. It used a Long Short-Term Memory classifier to extract expressed attitudes and changes from relevant tweets posted by 843 sample users. We found that a people's attitude change toward the vaccination receives a more significant impact from Twitter-based descriptive social norms over the prior week, whereas the norms in the physical-world communities tend to be less influential but still notable with the time gap between 2 weeks and 1 month. The findings revealed the potential of using online social norm approaches to proactively motivate behavioral changes toward a culture of health.

Calibrating COVID-19 community transmission risk levels to reflect infection prevalence

Many organizations, including the US Centers for Disease Control and Prevention, have developed risk indexes to help determine community transmission levels for the ongoing COVID-19 pandemic. These risk indexes are largely based on newly reported cases and percentage of positive SARS-CoV-2 diagnostic nucleic acid amplification tests, which are well-established as biased estimates of COVID-19 transmission. However, transmission risk indexes should accurately and precisely communicate community risks to decision-makers and the public. Therefore, transmission risk indexes would ideally quantify actual, and not just reported, levels of disease prevalence or incidence. Here, we develop a robust data-driven framework for determining and communicating community transmission risk levels using reported cases and test positivity. We use this framework to evaluate the previous CDC community risk level metrics that were proposed as guidelines for determining COVID-19 transmission risk at community level in the US. Using two recently developed data-driven models for COVID-19 transmission in the US to compute community-level prevalence, we show that there is substantial overlap of prevalence between the different community risk levels from the previous CDC guidelines. Using our proposed framework, we redefined the risk levels and their threshold values. We show that these threshold values would have substantially reduced the overlaps of underlying community prevalence between counties/states in different community risk levels between 3/19/2020-9/9/2021. Our study demonstrates how the previous CDC community risk level indexes could have been calibrated to infection prevalence to improve their power to accurately determine levels of COVID-19 transmission in local communities across the US. This method can be used to inform the design of future COVID-19 transmission risk indexes.

Evaluation of self-administered antigen testing in a college setting

BACKGROUND

The objective of our investigation was to better understand barriers to implementation of self-administered antigen screening testing for SARS-CoV-2 at institutions of higher education (IHE).

METHODS

Using the Quidel QuickVue At-Home COVID-19 Test, 1347 IHE students and staff were asked to test twice weekly for seven weeks. We assessed seroconversion using baseline and endline serum specimens. Online surveys assessed acceptability.

RESULTS

Participants reported 9971 self-administered antigen test results. Among participants who were not antibody positive at baseline, the median number of tests reported was eight. Among 324 participants seronegative at baseline, with endline antibody results and ≥ 1 self-administered antigen test results, there were five COVID-19 infections; only one was detected by self-administered antigen test (sensitivity = 20%). Acceptability of self-administered antigen tests was high.

CONCLUSIONS

Twice-weekly serial self-administered antigen testing in a low prevalence period had low utility in this investigation. Issues of testing fatigue will be important to address in future testing strategies.

A longitudinal study of vaccine hesitancy attitudes and social influence as predictors of COVID-19 vaccine uptake in the US

Background

In many countries with high levels of COVID-19 vaccine access, uptake remains a major issue. We examined prospective predictors of COVID-19 vaccine uptake in a United States longitudinal study.

Methods

An online longitudinal study on COVID-19 and well-being assessed vaccine hesitancy attitudes, social norms, and uptake among 444 respondents who had completed both survey waves in March and June 2021.

Results

The mean sample age was 41, with 55% female, 71% white, 13% Black, and 6% Latinx. In March 2021, 14% had received at least one COVID-19 vaccine dose. By June 2021, 64% reported receiving at least one dose. In prospectively assessing predictors of vaccine uptake, we found strong correlations among five different vaccine hesitancy questions. In multivariable logistic regression models, family and friends discouraging vaccination (adjusted odds ratios [aOR] = .26, 95% CI = .07, .98), not knowing whom to believe about vaccine safety (aOR = .51, 95% CI = .27, .95), and concerns that shortcuts were taken with vaccine development (aOR = .43, 95% CI = .23, .81) were all independent predictors of lower vaccine uptake. Political conservatism, gender, education, and income were also independent predictors of reduced uptake. Vaccine hesitancy items were also modeled as a scale, and the scale was found to be strongly predictive of vaccine uptake.

Conclusions

The findings highlight the importance of social norm interventions and suggest general and specific vaccine hesitancy attitudes, especially trust, should be considered in developing vaccine uptake programs.

Evaluation of the United States definitions for COVID-19 community risk levels

The United States CDC defines a county metric of COVID-19 Community Levels to inform public health measures. We find that the COVID-19 Community Levels vary frequently over time, which may not be optimal for decision making. Alternative metric formulations that do not compromise predictive ability are shown to reduce variability.

Perception of Local COVID-19 Transmission and Use of Preventive Behaviors Among Adults with Recent SARS-CoV-2 Infection - Illinois and Michigan, June 1-July 31, 2022

During the early stages of the COVID-19 pandemic, use of preventive behaviors was associated with perceived risk for contracting SARS-CoV-2 infection (1,2). Over time, perceived risk has declined along with waning COVID-19-related media coverage (3,4). The extent to which communities continue to be aware of local COVID-19 transmission levels and are implementing recommended preventive behaviors is unknown. During June 1-July 31, 2022, health departments in DuPage County, Illinois and metropolitan Detroit, Michigan surveyed a combined total of 4,934 adults who had received a positive test result for SARS-CoV-2 during the preceding 3 weeks. The association between awareness of local COVID-19 transmission and use of preventive behaviors and practices was assessed, both in response to perceived local COVID-19 transmission levels and specifically during the 2 weeks preceding SARS-CoV-2 testing. Both areas had experienced sustained high COVID-19 transmission during the study interval as categorized by CDC COVID-19 transmission levels.* Overall, 702 (14%) respondents perceived local COVID-19 transmission levels as high, 987 (20%) as substantial, 1,902 (39%) as moderate, and 581 (12%) as low; 789 (16%) reported they did not know. Adjusting for geographic area, age, gender identity, and combined race and ethnicity, respondents who perceived local COVID-19 transmission levels as high were more likely to report having made behavioral changes because of the level of COVID-19 transmission in their area, including wearing a mask in public, limiting travel, and avoiding crowded places or events. Continued monitoring of public perceptions of local COVID-19 levels and developing a better understanding of their influence on the use of preventive behaviors can guide COVID-19 communication strategies and policy making during and beyond the pandemic.

Circular RNAs as emerging regulators in COVID-19 pathogenesis and progression

Coronavirus disease 2019 (COVID-19), an infectious acute respiratory disease caused by a newly emerging RNA virus, is a still-growing pandemic that has caused more than 6 million deaths globally and has seriously threatened the lives and health of people across the world. Currently, several drugs have been used in the clinical treatment of COVID-19, such as small molecules, neutralizing antibodies, and monoclonal antibodies. In addition, several vaccines have been used to prevent the spread of the pandemic, such as adenovirus vector vaccines, inactivated vaccines, recombinant subunit vaccines, and nucleic acid vaccines. However, the efficacy of vaccines and the onset of adverse reactions vary among individuals. Accumulating evidence has demonstrated that circular RNAs (circRNAs) are crucial regulators of viral infections and antiviral immune responses and are heavily involved in COVID-19 pathologies. During novel coronavirus infection, circRNAs not only directly affect the transcription process and interfere with viral replication but also indirectly regulate biological processes, including virus-host receptor binding and the immune response. Consequently, understanding the expression and function of circRNAs during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection will provide novel insights into the development of circRNA-based methods. In this review, we summarize recent progress on the roles and underlying mechanisms of circRNAs that regulate the inflammatory response, viral replication, immune evasion, and cytokines induced by SARS-CoV-2 infection, and thus highlighting the diagnostic and therapeutic challenges in the treatment of COVID-19 and future research directions.

Acute stress, worry, and impairment in health care and non-health care essential workers during the COVID-19 pandemic

OBJECTIVE

Health care and non-health care essential workers working in face-to-face interactions during the coronavirus disease 2019 (COVID-19) pandemic may be vulnerable to psychosocial distress. Limited empirical research on COVID-19-related psychosocial outcomes has utilized probability-based samples including both health care and non-health care essential workers.

METHOD

We surveyed a sample of 1,821 United States self-identified essential workers, collected using probability-based methods, working in face-to-face interactions during the early phase of the COVID-19 outbreak (March 18, 2020 through April 18, 2020), in three consecutive 10-day cohorts. We assessed acute stress, health-related worries, and functional impairment. Demographics, secondary stressors (lack of childcare or health care, lost wages), and pre-COVID-19 mental and physical health were examined as predictors of psychological outcomes.

RESULTS

Acute stress (β = .08, p = .001), health-related worries (β = .09, p = .001), and functional impairment (β = .05, p = .034) increased over time in the early weeks of the outbreak. Health care essential workers reported lower functional impairment (β = -.06, p = .009) and acute stress (β = -.06, p = .015) compared with non-health care essential workers. Across the sample, prior mental and physical health ailments, inability to obtain health care, lost wages, younger age, female gender, and Hispanic ethnicity were associated with acute stress (βs = -.14 to .15, ps ≤ .001), health-related worries (βs = -.09 to .14, ps ≤ .001), and functional impairment (βs = -.08 to .16, ps ≤ .006). Lack of childcare (β = .09, p < .001) was positively associated with acute stress.

CONCLUSION

Non-health care essential workers may be vulnerable to negative psychosocial outcomes. Targeted training and support may help facilitate coping with the effects of working in-person during the ongoing COVID-19 pandemic. Findings may help inform intervention efforts, critical as COVID-19 becomes endemic and society must learn to live with its evolving variants. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Psychological responses to U.S. statewide restrictions and COVID-19 exposures: A longitudinal study

OBJECTIVE

The COVID-19 pandemic has generated debate as to whether community-level behavioral restrictions are worth the emotional costs of such restrictions. Using a longitudinal design, we juxtaposed the relative impacts of state-level restrictions and case counts with person-level direct and media-based exposures on distress, loneliness, and traumatic stress symptoms (TSS) during the COVID-19 pandemic in the United States.

METHOD

From March 18, 2020 to April 18, 2020 and September 9, 2020 to October 16, 2020, a representative probability sample of U.S. adults (N = 5,594) completed surveys of their psychological responses and personal direct and media-based exposures to the COVID-19 pandemic. Survey data were merged with publicly available data on the stringency of state-level mitigation policies (e.g., school/business closures) during this period and longitudinal case/death counts for each state.

RESULTS

Three multilevel models (outcomes: distress, loneliness, TSS) were constructed. Measurements of dependent variables (Level 1) were nested within respondents (Level 2) who were nested within states (Level 3). State-level mitigation, cases, or deaths were not associated with any dependent variables (all p's > .05). However, person-level exposures, including having contracted COVID-19 oneself (distress b = .22, p < .001; loneliness b = .13, p = .03; TSS b = .18, p = .001), knowing others who were sick (distress b = .04, p < .001; loneliness b = .02, p < .001; TSS b = .05, p < .001) or died (distress b = .10, p = .001; loneliness b = .10, p = .003; TSS b = .16, p < .001), and exposure to pandemic-related media (distress b = .12, p < .001; loneliness b = .09, p < .001; TSS b = .16, p < .001), were positively associated with outcomes.

CONCLUSIONS

Personal exposures to COVID-19 are more strongly associated with psychological outcomes than statewide mitigations levied to stop disease spread. Results may inform public health response planning for future disease outbreaks. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

COVID-19 Case Investigation and Contact Tracing in New York City, June 1, 2020, to October 31, 2021

IMPORTANCE

Contact tracing is a core strategy for preventing the spread of many infectious diseases of public health concern. Better understanding of the outcomes of contact tracing for COVID-19 as well as the operational opportunities and challenges in establishing a program for a jurisdiction as large as New York City (NYC) is important for the evaluation of this strategy.

OBJECTIVE

To describe the establishment, scaling, and maintenance of Trace, NYC's contact tracing program, and share data on outcomes during its first 17 months.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study included people with laboratory test-confirmed and probable COVID-19 and their contacts in NYC between June 1, 2020, and October 31, 2021. Trace launched on June 1, 2020, and had a workforce of 4147 contact tracers, with the majority of the workforce performing their jobs completely remotely. Data were analyzed in March 2022.

MAIN OUTCOMES AND MEASURES

Number and proportion of persons with COVID-19 and contacts on whom investigations were attempted and completed; timeliness of interviews relative to symptom onset or exposure for symptomatic cases and contacts, respectively.

RESULTS

Case investigations were attempted for 941 035 persons. Of those, 840 922 (89.4%) were reached and 711 353 (75.6%) completed an intake interview (women and girls, 358 775 [50.4%]; 60 178 [8.5%] Asian, 110 636 [15.6%] Black, 210 489 [28.3%] Hispanic or Latino, 157 349 [22.1%] White). Interviews were attempted for 1 218 650 contacts. Of those, 904 927 (74.3%) were reached, and 590 333 (48.4%) completed intake (women and girls, 219 261 [37.2%]; 47 403 [8.0%] Asian, 98 916 [16.8%] Black, 177 600 [30.1%] Hispanic or Latino, 116 559 [19.7%] White). Completion rates were consistent over time and resistant to changes related to vaccination as well as isolation and quarantine guidance. Among symptomatic cases, median time from symptom onset to intake completion was 4.7 days; a median 1.4 contacts were identified per case. Median time from contacts' last date of exposure to intake completion was 2.3 days. Among contacts, 30.1% were tested within 14 days of notification. Among cases, 27.8% were known to Trace as contacts. The overall expense for Trace from May 6, 2020, through October 31, 2021, was approximately $600 million.

CONCLUSIONS AND RELEVANCE

Despite the complexity of developing a contact tracing program in a diverse city with a population of over 8 million people, in this case study we were able to identify 1.4 contacts per case and offer resources to safely isolate and quarantine to over 1 million cases and contacts in this study period.

Exploring Public Discussions Regarding COVID-19 Vaccinations on Microblogs in China: Findings from Machine Learning Algorithms

Large-scale, widespread COVID-19 vaccination is the most effective means of cutting off the spread of the novel coronavirus and establishing an immune barrier. Due to the large population base in China, it has been a very difficult task to establish such an immune barrier. Therefore, this study aims to explore the public's discussions related to COVID-19 vaccinations on microblogs and to detect their sentiments toward COVID-19 vaccination so as to improve the vaccination rate in China. This study employed machine learning methods in the field of artificial intelligence to analyze mass data obtained from SinaWeibo. A total of 1,478,875 valid microblog texts were collected between December 2020 and June 2022, the results of which indicated that: (1) overall, negative texts (38.7%) slightly outweighed positive texts (36.1%); "Good" (63%) dominated positive texts, while "disgust" (44.6%) and "fear" (35.8%) dominated negative texts; (2) six overarching themes related to COVID-19 vaccination were identified: public trust in the Chinese government, changes in daily work and study, vaccine economy, international COVID-19 vaccination, the COVID-19 vaccine's R&D, and COVID-19 vaccination for special groups. These themes and sentiments can clarify the public's reactions to COVID-19 vaccination and help Chinese officials' response to vaccine hesitancy. Furthermore, this study seeks to make up for the lack of focus on big data in public health and epidemiology research, and to provide novel insights for future studies.

Pre-Pandemic Cross-Reactive Immunity against SARS-CoV-2 among Central and West African Populations

For more than two years after the emergence of COVID-19 (Coronavirus Disease-2019), significant regional differences in morbidity persist. These differences clearly show lower incidence rates in several regions of the African and Asian continents. The work reported here aimed to test the hypothesis of a pre-pandemic natural immunity acquired by some human populations in central and western Africa, which would, therefore, pose the hypothesis of an original antigenic sin with a virus antigenically close to the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). To identify such pre-existing immunity, sera samples collected before the emergence of COVID-19 were tested to detect the presence of IgG reacting antibodies against SARS-CoV-2 proteins of major significance. Sera samples from French blood donors collected before the pandemic served as a control. The results showed a statistically significant difference of antibodies prevalence between the collected samples in Africa and the control samples collected in France. Given the novelty of our results, our next step consists in highlighting neutralizing antibodies to evaluate their potential for pre-pandemic protective acquired immunity against SARS-CoV-2. In conclusion, our results suggest that, in the investigated African sub-regions, the tested populations could have been potentially and partially pre-exposed, before the COVID-19 pandemic, to the antigens of a yet non-identified Coronaviruses.

Maintenance of Antibody Response in Egyptian Healthcare Workers Vaccinated with ChAdOx1 nCoV-19 Vaccine during Delta and Omicron Variants Pandemic: A Prospective Study

Background: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a constantly evolving virus, resulting in an increased burden on the existing COVID-19 vaccines. Healthcare workers (HCWs) are the first line of defense against the coronavirus disease 2019 (COVID-19) pandemic and have been prioritized among the risk categories receiving the COVID-19 vaccine. This work aimed to investigate the maintenance of antibody response of the Oxford−AstraZeneca vaccine (ChAdOx1/nCoV-19). Methods: Anti-spike immunoglobulin G (IgG) was measured at baseline point (immediately prior to vaccination) and 12- and 24-week (w) points following vaccination. Adverse reactions to the vaccine were reported. Participants were followed up for the incidence of COVID-19 during the 12 w interval between vaccination doses for 24 w after the second dose. Results: A total of 255 HCWs participated in the study. Prior to vaccination, 54.1% experienced COVID-19, 88.2% were seropositive after the first dose, while seropositivity reached 95.7% after the second dose. Following the first and second doses, the anti-spike IgG serum level was significantly higher in subjects with past COVID-19 than in others (p < 0.001 and =0.001, respectively). Conclusions: The Oxford−AstraZeneca vaccine is generally safe and provides a highly effective long-term humoral immune response against the Delta and Omicron variants of SARS-CoV-2.

SARS-COV-2/COVID-19: scenario, epidemiology, adaptive mutations, and environmental factors

The coronavirus pandemic of 2019 has already exerted an enormous impact. For over a year, the worldwide pandemic has ravaged the whole globe, with approximately 250 million verified human infection cases and a mortality rate surpassing 4 million. While the genetic makeup of the related pathogen (SARS-CoV-2) was identified, many unknown facets remain a mystery, comprising the virus's origin and evolutionary trend. There were many rumors that SARS-CoV-2 was human-borne and its evolution was predicted many years ago, but scientific investigation proved them wrong and concluded that bats might be the origin of SARS-CoV-2 and pangolins act as intermediary species to transmit the virus from bats to humans. Airborne droplets were found to be the leading cause of human-to-human transmission of this virus, but later studies showed that contaminated surfaces and other environmental factors are also involved in its transmission. The evolution of different SARS-CoV-2 variants worsens the condition and has become a challenge to overcome this pandemic. The emergence of COVID-19 is still a mystery, and scientists are unable to explain the exact origin of SARS-CoV-2. This review sheds light on the possible origin of SARS-CoV-2, its transmission, and the key factors that worsen the situation.