The interplay between COVID-19 restrictions and vaccination

Forecasting the spread of COVID-19 based on policy, vaccination, and Omicron data

The COVID-19 pandemic caused by the novel SARS-COV-2 virus poses a great risk to the world. During the COVID-19 pandemic, observing and forecasting several important indicators of the epidemic (like new confirmed cases, new cases in intensive care unit, and new deaths for each day) helped prepare the appropriate response (e.g., creating additional intensive care unit beds, and implementing strict interventions). Various predictive models and predictor variables have been used to forecast these indicators. However, the impact of prediction models and predictor variables on forecasting performance has not been systematically well analyzed. Here, we compared the forecasting performance using a linear mixed model in terms of prediction models (mathematical, statistical, and AI/machine learning models) and predictor variables (vaccination rate, stringency index, and Omicron variant rate) for seven selected countries with the highest vaccination rates. We decided on our best models based on the Bayesian Information Criterion (BIC) and analyzed the significance of each predictor. Simple models were preferred. The selection of the best prediction models and the use of Omicron variant rate were considered essential in improving prediction accuracies. For the test data period before Omicron variant emergence, the selection of the best models was the most significant factor in improving prediction accuracy. For the test period after Omicron emergence, Omicron variant rate use was considered essential in deciding forecasting accuracy. For prediction models, ARIMA, lightGBM, and TSGLM generally performed well in both test periods. Linear mixed models with country as a random effect has proven that the choice of prediction models and the use of Omicron data was significant in determining forecasting accuracies for the highly vaccinated countries. Relatively simple models, fit with either prediction model or Omicron data, produced best results in enhancing forecasting accuracies with test data.

Event Study Design for Modeling Early Relaxation in Turkish Public with COVID-19 Vaccine

OBJECTIVE

Vaccination is crucial to fighting the coronavirus disease (COVID-19) pandemic. A large body of literature investigates the effect of the initiation of the COVID-19 vaccination in case numbers in Turkey, including the resistance and willingness to taking the vaccine. The effect of early relaxation in the Turkish public with the initiation of vaccination on new daily cases is unknown.

METHODS

This study performs an event study analysis to explore the pre-relaxation effect of vaccination on the Turkish public by using daily data of new cases, stringency index, and residential mobility. Two events are comparatively defined as the vaccination of the health personnel (Event 1) and the citizens age 65 and over (Event 2). The initial dates of these events are January 13 and February 12, 2021, respectively. The length of the estimation window is determined as 14 days for the 2 events. To represent only the early stages of the vaccination, the study period ends on April 12, 2021. Thus, whereas the event window of Event 1 includes 90 observations, Event 2 covers 60 observations.

RESULTS

While average values of residential mobility, stringency index, and daily numbers of cases are 15.36, 71.03, and 11 978.93 in the estimation window for Event 1, these averages are 8.89, 70.88, and 17 303.20 in the event window. For Event 2, the same average values are 9.14, 69.38, and 7 664.93 in the estimation window and 8.25, 71.12, and 22 319.10 in the event window. When 14-day abnormal growth rates of the daily number of cases for Event 1 and Event 2 are compared, it is observed that Event 1 has negative growth rates initially and reaches a 7.59% growth at most. On the other hand, Event 2 starts with a 1.11% growth rate, and having a steady increase, it reaches a 23.70% growth in the last 14 days of the study period.

CONCLUSION

The preliminary result shows that, despite taking more strict governmental measures, while residential mobility decreases, the daily number of COVID-19 cases increases in the early stages of vaccination compared to short pre-periods of it. This indicates that the initiation of vaccination leads to early behavioral relaxation in public. Moreover, the effect of Event 2 on the case numbers is more significant and immediate, compared to that of Event 1, which may be linked to the characteristic of the Turkish culture being more sensitive to the older adult population.

Efficacy of homemade face masks against human coughs: Insights on penetration, atomization, and aerosolization of cough droplets

Ever since the emergence of the ongoing COVID-19 pandemic, the usage of makeshift facemasks is generally advised by policymakers as a possible substitute for commercially available surgical or N95 face masks. Although such endorsements could be economical and easily accessible in various low per-capita countries, the experimental evidence on the effectiveness of such recommendations is still lacking. In this regard, we carried out a detailed experimental investigation to study the fate of a large-sized surrogate cough droplet impingement at different velocities (corresponding to mild to severe coughs) on various locally procured cloth fabrics. Observation shows that larger ejected droplets (droplets that would normally settle as fomites in general) during a coughing event have enough momentum to penetrate single-layer cloth masks; the penetrated volume atomize into smaller daughter droplets that fall within aerosol range, thereby increasing infection potential. Theoretically, two essential criteria based on the balances of viscous dissipation-kinetic energy and surface tension-kinetic energy effects have been suggested for the droplet penetration through mask layers. Furthermore, a new parameter called η (the number density of pores for a fabric) is developed to characterize the volume penetration potential and subsequent daughter droplet size. Finally, the effect of mask washing frequency is analyzed. The outcomes from the current study can be used as a guide in selecting cloth fabrics for stitching multi-layered.