Trend Dynamics of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Transmission in 16 Cities of Hubei Province, China

Effect of Knowledge/Practice of COVID-19 Prevention Measures on Return-to-Work Concerns; Attitudes About the Efficacy of Traditional Chinese Medicine: Survey on Supermarket Staff in Huanggang, China

Objective: The objective of this study was to investigate how knowledge and practice of coronavirus disease 2019 (COVID-19) prevention measures affected concerns about returning to work among supermarket staff. Attitudes about the ability of traditional Chinese medicine (TCM) to prevent COVID-19 were also assessed.

Methods: A cross-sectional study was conducted in Huanggang, Hubei Province, China from April 23 to 25, 2020. Participants were invited to fill out an electronic questionnaire on their cell phones.

Results: The results showed that from 2,309 valid questionnaires, 61.5% of participants were concerned about resuming work. Major concerns included asymptomatic infection (85.01%) and employees gathering in the workplace (78.96%). Multivariate logistic regression indicated that the female gender, having school-aged children and pregnancy were risk factors for being concerned about resuming work, while good knowledge and practice of preventive measures were protective factors. Knowledge and practice of preventive measures were positively correlated. Among preventive measures, the highest percentage of participants knew about wearing masks and washing hands. Meanwhile, 65.8% of participants expressed confidence in the ability of TCM to prevent COVID-19, where 74 and 51.3% thought there was a need and a strong need, respectively, for preventive TCM-based products. Among them, 71.5% preferred oral granules. Regarding TCM as a COVID-19 preventative, most were interested in information about safety and efficacy.

Conclusion: These findings suggested that promoting knowledge and practices regarding COVID-19 prevention can help alleviate concerns about returning to work. Meanwhile, TCM can feasibly be accepted to diversify COVID-19 prevention methods.

Clinical Trial Registration:http://www.chictr.org.cn/, identifier: ChiCTR2000031955.

A Framework for a Statistical Characterization of Epidemic Cycles: COVID-19 Case Study

Background

Since the beginning of the COVID-19 pandemic, researchers and health authorities have sought to identify the different parameters that drive its local transmission cycles to make better decisions regarding prevention and control measures. Different modeling approaches have been proposed in an attempt to predict the behavior of these local cycles.

Objective

This paper presents a framework to characterize the different variables that drive the local, or epidemic, cycles of the COVID-19 pandemic, in order to provide a set of relatively simple, yet efficient, statistical tools to be used by local health authorities to support decision making.

Methods

Virtually closed cycles were compared to cycles in progress from different locations that present similar patterns in the figures that describe them. With the aim to compare populations of different sizes at different periods of time and locations, the cycles were normalized, allowing an analysis based on the core behavior of the numerical series. A model for the reproduction number was derived from the experimental data, and its performance was presented, including the effect of subnotification (ie, underreporting). A variation of the logistic model was used together with an innovative inventory model to calculate the actual number of infected persons, analyze the incubation period, and determine the actual onset of local epidemic cycles.

Results

The similarities among cycles were demonstrated. A pattern between the cycles studied, which took on a triangular shape, was identified and used to make predictions about the duration of future cycles. Analyses on effective reproduction number (R_t) and subnotification effects for Germany, Italy, and Sweden were presented to show the performance of the framework introduced here. After comparing data from the three countries, it was possible to determine the probable dates of the actual onset of the epidemic cycles for each country, the typical duration of the incubation period for the disease, and the total number of infected persons during each cycle. In general terms, a probable average incubation time of 5 days was found, and the method used here was able to estimate the end of the cycles up to 34 days in advance, while demonstrating that the impact of the subnotification level (ie, error) on the effective reproduction number was <5%.

Conclusions

It was demonstrated that, with relatively simple mathematical tools, it is possible to obtain a reliable understanding of the behavior of COVID-19 local epidemic cycles, by introducing an integrated framework for identifying cycle patterns and calculating the variables that drive it, namely: the R_t, the subnotification effects on estimations, the most probable actual cycles start dates, the total number of infected, and the most likely incubation period for SARS-CoV-2.

Statistical analysis of COVID-19 infection caused by environmental factors: Evidence from Pakistan

Background

Coronavirus disease 2019 (COVID-19) has become a severe public health problem around the globe. Various epidemiological, statistical, and laboratory-based studies have shown that the role of temperature and other environmental factors has important influence in the transmission of coronaviruses. Scientific research is needed to answer the questions about the spread and transmission of the infection, whether people could be avoided from being infected with COVID-19 in next summer.

Aim

We aim to investigate the association of daily average temperature, daily average dew point, daily average humidity, daily average wind speed, and daily average pressure with the infection caused by this novel coronavirus in Pakistan.

Key findings

First, we check the correlation between environmental factors and daily infected cases of COVID-19; among them, temperature and dew point have positive linear relationship with daily infected cases of COVID-19. The thought-provoking findings of the present study suggested that higher temperature and dew point can contribute to a rise in COVID-19 disease in four provinces of Pakistan, possible to genome modifications and viral resistance to harsh environment. Moreover, it is also observed that humidity in Punjab and Sindh, and wind speed in Balochistan and Khyber Pakhtunkhwa have influenced the spreading of daily infected COVID-19 cases.

Significance

Current study will serve as a guideline to develop understanding of environmental factors that influence COVID-19 spread, helping policymakers to prepare and handle a catastrophe resulting from this pandemic.