Overlapping Delta and Omicron Outbreaks During the COVID-19 Pandemic: Dynamic Panel Data Estimates.

BACKGROUND: The Omicron variant of SARS-CoV-2 is more transmissible than prior variants of concern (VOCs). It has caused the largest outbreaks in the pandemic, with increases in mortality and hospitalizations. Early data on the spread of Omicron were captured in countries with relatively low case counts, so it was unclear how the arrival of Omicron would impact the trajectory of the pandemic in countries already experiencing high levels of community transmission of Delta. OBJECTIVE: The objective of this study is to quantify and explain the impact of Omicron on pandemic trajectories and how they differ between countries that were or were not in a Delta outbreak at the time Omicron occurred. METHODS: We used SARS-CoV-2 surveillance and genetic sequence data to classify countries into 2 groups: those that were in a Delta outbreak (defined by at least 10 novel daily transmissions per 100,000 population) when Omicron was first sequenced in the country and those that were not. We used trend analysis, survival curves, and dynamic panel regression models to compare outbreaks in the 2 groups over the period from November 1, 2021, to February 11, 2022. We summarized the outbreaks in terms of their peak rate of SARS-CoV-2 infections and the duration of time the outbreaks took to reach the peak rate. RESULTS: Countries that were already in an outbreak with predominantly Delta lineages when Omicron arrived took longer to reach their peak rate and saw greater than a twofold increase (2.04) in the average apex of the Omicron outbreak compared to countries that were not yet in an outbreak. CONCLUSIONS: These results suggest that high community transmission of Delta at the time of the first detection of Omicron was not protective, but rather preluded larger outbreaks in those countries. Outbreak status may reflect a generally susceptible population, due to overlapping factors, including climate, policy, and individual behavior. In the absence of strong mitigation measures, arrival of a new, more transmissible variant in these countries is therefore more likely to lead to larger outbreaks. Alternately, countries with enhanced surveillance programs and incentives may be more likely to both exist in an outbreak status and detect more cases during an outbreak, resulting in a spurious relationship. Either way, these data argue against herd immunity mitigating future outbreaks with variants that have undergone significant antigenic shifts.

The Interplay Between Policy and COVID-19 Outbreaks in South Asia: Longitudinal Trend Analysis of Surveillance Data.

BACKGROUND: COVID-19 transmission rates in South Asia initially were under control when governments implemented health policies aimed at controlling the pandemic such as quarantines, travel bans, and border, business, and school closures. Governments have since relaxed public health restrictions, which resulted in significant outbreaks, shifting the global epicenter of COVID-19 to India. Ongoing systematic public health surveillance of the COVID-19 pandemic is needed to inform disease prevention policy to re-establish control over the pandemic within South Asia. OBJECTIVE: This study aimed to inform public health leaders about the state of the COVID-19 pandemic, how South Asia displays differences within and among countries and other global regions, and where immediate action is needed to control the outbreaks. METHODS: We extracted COVID-19 data spanning 62 days from public health registries and calculated traditional and enhanced surveillance metrics. We use an empirical difference equation to measure the daily number of cases in South Asia as a function of the prior number of cases, the level of testing, and weekly shifts in variables with a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. RESULTS: Traditional surveillance metrics indicate that South Asian countries have an alarming outbreak, with India leading the region with 310,310 new daily cases in accordance with the 7-day moving average. Enhanced surveillance indicates that while Pakistan and Bangladesh still have a high daily number of new COVID-19 cases (n=4819 and n=3878, respectively), their speed of new infections declined from April 12-25, 2021, from 2.28 to 2.18 and 3.15 to 2.35 daily new infections per 100,000 population, respectively, which suggests that their outbreaks are decreasing and that these countries are headed in the right direction. In contrast, India's speed of new infections per 100,000 population increased by 52% during the same period from 14.79 to 22.49 new cases per day per 100,000 population, which constitutes an increased outbreak. CONCLUSIONS: Relaxation of public health restrictions and the spread of novel variants fueled the second wave of the COVID-19 pandemic in South Asia. Public health surveillance indicates that shifts in policy and the spread of new variants correlate with a drastic expansion in the pandemic, requiring immediate action to mitigate the spread of COVID-19. Surveillance is needed to inform leaders whether policies help control the pandemic.

Has Omicron Changed the Evolution of the Pandemic?

BACKGROUND: Variants of the SARS-CoV-2 virus carry differential risks to public health. The Omicron (B.1.1.529) variant, first identified in Botswana on November 11, 2021, has spread globally faster than any previous variant of concern. Understanding the transmissibility of Omicron is vital in the development of public health policy. OBJECTIVE: The aim of this study is to compare SARS-CoV-2 outbreaks driven by Omicron to those driven by prior variants of concern in terms of both the speed and magnitude of an outbreak. METHODS: We analyzed trends in outbreaks by variant of concern with validated surveillance metrics in several southern African countries. The region offers an ideal setting for a natural experiment given that most outbreaks thus far have been driven primarily by a single variant at a time. With a daily longitudinal data set of new infections, total vaccinations, and cumulative infections in countries in sub-Saharan Africa, we estimated how the emergence of Omicron has altered the trajectory of SARS-CoV-2 outbreaks. We used the Arellano-Bond method to estimate regression coefficients from a dynamic panel model, in which new infections are a function of infections yesterday and last week. We controlled for vaccinations and prior infections in the population. To test whether Omicron has changed the average trajectory of a SARS-CoV-2 outbreak, we included an interaction between an indicator variable for the emergence of Omicron and lagged infections. RESULTS: The observed Omicron outbreaks in this study reach the outbreak threshold within 5-10 days after first detection, whereas other variants of concern have taken at least 14 days and up to as many as 35 days. The Omicron outbreaks also reach peak rates of new cases that are roughly 1.5-2 times those of prior variants of concern. Dynamic panel regression estimates confirm Omicron has created a statistically significant shift in viral spread. CONCLUSIONS: The transmissibility of Omicron is markedly higher than prior variants of concern. At the population level, the Omicron outbreaks occurred more quickly and with larger magnitude, despite substantial increases in vaccinations and prior infections, which should have otherwise reduced susceptibility to new infections. Unless public health policies are substantially altered, Omicron outbreaks in other countries are likely to occur with little warning.

In silico evaluation of the compounds of the ayurvedic drug, AYUSH-64, for the action against the SARS-CoV-2 main protease.

BACKGROUND: Outbreak of Corona Virus Disease in late 2019 (COVID-19) has become a pandemic global Public health emergency. Since there is no approved anti-viral drug or vaccine declared for the disease and investigating existing drugs against the COVID-19. OBJECTIVE: AYUSH-64 is an Ayurvedic formulation, developed and patented by Central Council of Research in Ayurvedic Sciences, India, has been in clinical use as anti-malarial, anti-inflammatory, anti-pyretic drug for few decades. Thus, the present study was undertaken to evaluate AYUSH-64 compounds available in this drug against Severe Acute Respiratory Syndrome-Corona Virus (SARS-CoV-2) Main Protease (Mpro; PDB ID: 6LU7) via in silico techniques. MATERIALS AND METHODS: Different molecular docking software's of Discovery studio and Auto Dock Vina were used for drugs from selected AYUSH-64 compounds against SARS-CoV-2. We also conducted 100 ns period of molecular dynamics simulations with Desmond and further MM/GBSA for the best complex of AYUSH-64 with Mpro of SARS-CoV-2. RESULTS: Among 36 compounds of four ingredients of AYUSH-64 screened, 35 observed to exhibits good binding energies than the published positive co-crystal compound of N3 pepetide. The best affinity and interactions of Akuammicine N-Oxide (from Alstonia scholaris) towards the Mpro with binding energy (AutoDock Vina) of -8.4 kcal/mol and Discovery studio of Libdock score of 147.92 kcal/mol. Further, molecular dynamics simulations with MM-GBSA were also performed for Mpro- Akuammicine N-Oxide docked complex to identify the stability, specific interaction between the enzyme and the ligand. Akuammicine N-Oxide is strongly formed h-bonds with crucial Mpro residues, Cys145, and His164. CONCLUSION: The results provide lead that, the presence of Mpro- Akuammicine N-Oxide with highest Mpro binding energy along with other 34 chemical compounds having similar activity as part of AYUSH-64 make it a suitable candidate for repurposing to management of COVID-19 by further validating through experimental, clinical studies.

Impacts of the COVID-19 pandemic on vegetable production systems and livelihoods: Smallholder farmer experiences in Burkina Faso.

At the onset of COVID-19, researchers quickly recognized the need for research on the consequences of the pandemic for agricultural and food systems, both in terms of immediate impacts on access to inputs and labor, disruptions in transportation and markets, and the longer-term implications on crop productivity, income, and livelihoods. Vegetable production and supply chains are particularly vulnerable due to the perishable nature of the products and labor-intensive production practices. The purpose of this study was to understand the impacts of COVID-19 on vegetable production in Burkina Faso in terms of both the biophysical aspects such as yields and access to inputs and socioeconomic aspects such as access to labor, markets, and social services. A survey was developed to better understand smallholder farmer experiences regarding the impacts of COVID-19 on their vegetable production systems and social well-being. The survey was administered (between August and October 2020) with smallholder farmers (n = 605) in 13 administrative regions covering all agroecological zones of Burkina Faso. The survey results clearly show impacts of COVID-19 on vegetable systems, including a reduction in access to inputs, a reduction in yields, a loss of income, reduced access to local and urban markets, reduced access to transportation, and an increase in post-harvest loss. Market access, distribution, and disruptions were a major shock to the system. Results also showed an increase in women's labor in the household, and for youth, an increase in unemployment, job loss, and concerns of poverty. Finally, food security and social supports were highlighted as major issues for resilience and livelihoods. The results from this survey should be helpful to policymakers and researchers to develop policies and strategies to minimize the negative impacts of this ongoing pandemic on the agri-food systems and support smallholder farmers to overcome stress caused by COVID-19.

Assessing COVID-19 preventive behaviours using the health belief model: A Sri Lankan study.

OBJECTIVE: The novel coronavirus (COVID-19) is turning out to be one of the most severe public health crises in recent history. Promoting preventive behaviour among the public is of paramount importance to effectively contain the disease. Hence, this research attempts to identify factors that affect preventive behaviour against COVID-19. METHODS: The Health Belief Model (HBM), which outlines how perceived susceptibility, severity, benefits, barriers, and health motivation affect individuals' health behaviour, served as the theoretical basis of the study. As the outcome measure of the study was cues to action against COVID-19, a regression analysis was conducted to explore how the aforementioned HBM constructs influence the cues to action. The data were collected using an online survey with a total of 307 respondents. RESULTS: The results revealed that perceived benefits (0.395, p < 0.001), self-efficacy (0.405, p < 0.001), and general health motivation (0.313, p < 0.001) had significant positive impacts on the cues to action taken to prevent COVID-19, whereas perceived barriers (-0.097, p < 0.05) had a significant negative impact. The statistical analysis further revealed that the cues to action taken to prevent COVID-19 were not significantly influenced by perceived susceptibility and perceived severity. CONCLUSION: The study reinstates the usability of the HBM in exploring health behaviour. Importantly, the study findings suggest that by informing the public of the benefits of prevention and general health motivation, and by encouraging self-efficacy and eliminating the barriers to prevention, preventive actions against COVID-19 can be effectively promoted.