Effects of human behaviour changes during the COVID-19 pandemic on influenza spread in Hong Kong

A behaviour and disease transmission model: incorporating the Health Belief Model for human behaviour into a simple transmission model

The health and economic impacts of infectious diseases such as COVID-19 affect all levels of a community from the individual to the governing bodies. However, the spread of an infectious disease is intricately linked to the behaviour of the people within a community since crowd behaviour affects individual human behaviour, while human behaviour affects infection spread, and infection spread affects human behaviour. Capturing these feedback loops of behaviour and infection is a well-known challenge in infectious disease modelling. Here, we investigate the interface of behavioural science theory and infectious disease modelling to explore behaviour and disease (BaD) transmission models. Specifically, we incorporate a visible protective behaviour into the susceptible-infectious-recovered-susceptible (SIRS) transmission model using the socio-psychological Health Belief Model to motivate behavioural uptake and abandonment. We characterize the mathematical thresholds for BaD emergence in the BaD SIRS model and the feasible steady states. We also explore, under different infectious disease scenarios, the effects of a fully protective behaviour on long-term disease prevalence in a community, and describe how BaD modelling can investigate non-pharmaceutical interventions that target-specific components of the Health Belief Model. This transdisciplinary BaD modelling approach may reduce the health and economic impacts of future epidemics.

A critical review of research methodologies for COVID-19 transmission in indoor built environment

The Coronavirus Disease 2019 (COVID-19) has caused massive losses for the global economy. Scholars have used different methods to study the transmission mode and influencing factors of the virus to find effective methods to provide people with a healthy built environment. However, these studies arrived at different or even contradictory conclusions. This review presents the main research methodologies utilized in this field, summarizes the main investigation methods, and critically discusses their related conclusions. Data statistical analysis, sample collection, simulation models, and replication transmission scenarios are the main research methods. The summarized conclusion for prevention from all reviewed papers are: adequate ventilation and proper location of return air vents, proper use of personal protective equipment, as well as the reasonable and strict enforcement of policies are the main methods for reducing the transmission. Recommendations including standardized databases, causation clarification, rigorous experiment design, improved simulation accuracy and verification are provided.

Association of social vulnerability and influenza vaccination rates for Annual Medicare Enrollees at the county-level in the United States

INTRODUCTION

Influenza is a preventable acute respiratory illness with a high potential to cause serious complications and is associated with high mortality and morbidity in the US. We aimed to determine the specific community-level vulnerabilities for different race/ethnic communities that are most predictive of influenza vaccination rates.

METHODS

We conducted a machine learning analysis (XGBoost) to identify community-level social vulnerability features that are predictive of influenza vaccination rates among Medicare enrollees across counties in the US and by race/ethnicity.

RESULTS

Population density per square mile in a county is the most important feature in predicting influenza vaccination in a county, followed by unemployment rates and the percentage of mobile homes. The gain relative importance of these features are 11.6%, 9.2%, and 9%, respectively. Among whites, population density (17% gain relative importance) was followed by the percentage of mobile homes (9%) and per capita income (8.7%). For Black/African Americans, the most important features were population density (12.8%), percentage of minorities in the county (8.0%), per capita income (6.9%), and percent of over-occupied housing units (6.8%). Finally, for Hispanics, the top features were per capita income (8.4%), percentage of mobile homes (8.0%), percentage of non-institutionalized persons with a disability (7.9%), and population density (7.6%).

CONCLUSIONS

Our study may have implications for the success of large vaccination programs in counties with high social vulnerabilities. Further, our findings suggest that policies and interventions seeking to increase rates of vaccination in race/ethnic minority communities may need to be tailored to address their specific socioeconomic vulnerabilities.

Simulation of travel document purchase measures aimed at preventing the spread of COVID-19 - Case study from Slovakia

The COVID-19 pandemic has had a significant impact on railway services, such as restrictions on transport services, introduction of strict anti-pandemic measures at railway stations, and a ban on free travel. This study simulated passenger flow at the Bratislava railway station before and during the COVID-19 pandemic. This study provides an overview of the number of tickets sold, average waiting time of passengers, and time spent by passengers at ticket windows during peak and off-peak hours. The mass-service theory was used as the operational research method. In addition, the user interface of the AnyLogic simulation programme and practical results of the passenger flow simulations at the Bratislava railway station are discussed. The simulation results showed that passenger movement at the railway station was neither synchronised nor systematic. This concurred with the measures implemented during the pandemic that were considered unacceptable. New methods for selling travel documents at Slovak railway stations were proposed, which contribute to better spatial organisation of the stations, faster customer service at ticket windows, and negating infection risks.

Global variability of influenza activity and virus subtype circulation from 2011 to 2023

BACKGROUND

Although decreased influenza activity has been reported in many countries during the COVID-19 pandemic, it remains unknown how global influenza activity has changed. We described the global variability of influenza activity and virus subtype circulation from 2011 to 2023 to prepare for the potential influenza outbreak with the control of the COVID-19 pandemic.

METHODS

Influenza virological surveillance data between 2011 and 2023 were obtained from the WHO-FluNet database. We first calculated and compared the influenza activity before and during the COVID-19 pandemic. For countries whose influenza activity has recovered, we also described changes in the duration of influenza epidemics. We then determined the proportion of influenza cases caused by the different influenza virus types.

RESULTS

In total, 73 countries with 2.17 million influenza cases were included. In the early stage of the COVID-19 pandemic, decreased influenza activity was observed in all WHO regions. In 2022 and 2023, rebound in influenza activity was observed in all WHO regions, especially in Western Pacific Region. At the same time, a change in the duration of the influenza epidemic was observed in several Southern Hemisphere countries. Moreover, in all WHO regions, few B/Yamagata viruses were detected during the COVID-19 pandemic.

CONCLUSIONS

Lack of exposure to influenza will diminish population immunity and increase the severity of large epidemics on a future global resurgence. Ongoing monitoring of the changes in the duration of the influenza epidemic and circulation subtypes should be the focus of future work.

Local travel behaviour under continuing COVID-19 waves- A proxy for pandemic fatigue?

COVID-19 continues to threaten the world. Relaxing local travel behaviours on preventing the spread of COVID-19, may increase the infection risk in subsequent waves of SARS-CoV-2 transmission. In this study, we analysed changes in the travel behaviour of different population groups (adult, child, student, elderly) during four pandemic waves in Hong Kong before January 2021, by 4-billion second-by-second smartcard records of subway. A significant continuous relaxation in human travel behaviour was observed during the four waves of SARS-CoV-2 transmission. Residents sharply reduced their local travel by 51.9%, 50.1%, 27.6%, and 20.5% from the first to fourth pandemic waves, respectively. The population flow in residential areas, workplaces, schools, shopping areas, amusement areas and border areas, decreased on average by 30.3%, 33.5%, 41.9%, 58.1%, 85.4% and 99.6%, respectively, during the pandemic weeks. We also found that many other cities around the world experienced a similar relaxation trend in local travel behaviour, by comparing traffic congestion data during the pandemic with data from the same period in 2019. The quantitative pandemic fatigue in local travel behaviour could help governments partially predicting personal protective behaviours, and thus to suggest more accurate interventions during subsequent waves, especially for highly infectious virus variants such as Omicron.

Assessing the impact of COVID-19 interventions on influenza-like illness in Beijing and Hong Kong: an observational and modeling study

BACKGROUND

The impact of coronavirus diseases 2019 (COVID-19) related non-pharmaceutical interventions (NPIs) on influenza activity in the presence of other known seasonal driving factors is unclear, especially at the municipal scale. This study aimed to assess the impact of NPIs on outpatient influenza-like illness (ILI) consultations in Beijing and the Hong Kong Special Administrative Region (SAR) of China.

METHODS

We descriptively analyzed the temporal characteristics of the weekly ILI counts, nine NPI indicators, mean temperature, relative humidity, and absolute humidity from 2011 to 2021. Generalized additive models (GAM) using data in 2011-2019 were established to predict the weekly ILI counts under a counterfactual scenario of no COVID-19 interventions in Beijing and the Hong Kong SAR in 2020-2021, respectively. GAM models were further built to evaluate the potential impact of each individual or combined NPIs on weekly ILI counts in the presence of other seasonal driving factors in the above settings in 2020-2021.

RESULTS

The weekly ILI counts in Beijing and the Hong Kong SAR fluctuated across years and months in 2011-2019, with an obvious winter-spring seasonality in Beijing. During the 2020-2021 season, the observed weekly ILI counts in both Beijing and the Hong Kong SAR were much lower than those of the past 9 flu seasons, with a 47.5% [95% confidence interval (CI): 42.3%, 52.2%) and 60.0% (95% CI: 58.6%, 61.1%) reduction, respectively. The observed numbers for these two cities also accounted for only 40.2% (95% CI: 35.4%, 45.3%) and 58.0% (95% CI: 54.1%, 61.5%) of the GAM model estimates in the absence of COVID-19 NPIs, respectively. Our study revealed that, "Cancelling public events" and "Restrictions on internal travel" measures played an important role in the reduction of ILI in Beijing, while the "restrictions on international travel" was statistically most associated with ILI reductions in the Hong Kong SAR.

CONCLUSIONS

Our study suggests that COVID-19 NPIs had been reducing outpatient ILI consultations in the presence of other seasonal driving factors in Beijing and the Hong Kong SAR from 2020 to 2021. In cities with varying local circumstances, some NPIs with appropriate stringency may be tailored to reduce the burden of ILI caused by severe influenza strains or other respiratory infections in future.

Future trajectory of respiratory infections following the COVID-19 pandemic in Hong Kong

The accumulation of susceptible populations for respiratory infectious diseases (RIDs) when COVID-19-targeted non-pharmaceutical interventions (NPIs) were in place might pose a greater risk of future RID outbreaks. We examined the timing and magnitude of RID resurgence after lifting COVID-19-targeted NPIs and assessed the burdens on the health system. We proposed the Threshold-based Control Method (TCM) to identify data-driven solutions to maintain the resilience of the health system by re-introducing NPIs when the number of severe infections reaches a threshold. There will be outbreaks of all RIDs with staggered peak times after lifting COVID-19-targeted NPIs. Such a large-scale resurgence of RID patients will impose a significant risk of overwhelming the health system. With a strict NPI strategy, a TCM-initiated threshold of 600 severe infections can ensure a sufficient supply of hospital beds for all hospitalized severely infected patients. The proposed TCM identifies effective dynamic NPIs, which facilitate future NPI relaxation policymaking.

COVID-19: Data-Driven optimal allocation of ventilator supply under uncertainty and risk

This study presents a new risk-averse multi-stage stochastic epidemics-ventilator-logistics compartmental model to address the resource allocation challenges of mitigating COVID-19. This epidemiological logistics model involves the uncertainty of untested asymptomatic infections and incorporates short-term human migration. Disease transmission is also forecasted through a new formulation of transmission rates that evolve over space and time with respect to various non-pharmaceutical interventions, such as wearing masks, social distancing, and lockdown. The proposed multi-stage stochastic model overviews different scenarios on the number of asymptomatic individuals while optimizing the distribution of resources, such as ventilators, to minimize the total expected number of newly infected and deceased people. The Conditional Value at Risk (CVaR) is also incorporated into the multi-stage mean-risk model to allow for a trade-off between the weighted expected loss due to the outbreak and the expected risks associated with experiencing disastrous pandemic scenarios. We apply our multi-stage mean-risk epidemics-ventilator-logistics model to the case of controlling COVID-19 in highly-impacted counties of New York and New Jersey. We calibrate, validate, and test our model using actual infection, population, and migration data. We also define a new region-based sub-problem and bounds on the problem and then show their computational benefits in terms of the optimality and relaxation gaps. The computational results indicate that short-term migration influences the transmission of the disease significantly. The optimal number of ventilators allocated to each region depends on various factors, including the number of initial infections, disease transmission rates, initial ICU capacity, the population of a geographical location, and the availability of ventilator supply. Our data-driven modeling framework can be adapted to study the disease transmission dynamics and logistics of other similar epidemics and pandemics.

Hong Kong poison information centre: Annual report 2020

Background:

The Hong Kong Poison Information Centre has provided consultation service to healthcare professionals and collected epidemiological data on poisoning in Hong Kong since 2005.

Objective:

To analyse and report the poisoning data of Hong Kong Poison Information Centre in 2020 during the COVID-19 pandemic.

Methods:

A retrospective review of all poisoning cases recorded in the Poison Information and Clinical Management System of Hong Kong Poison Information Centre in 2020.

Results:

A total of 3633 poisoning cases were analysed. Compared to 2019 (pre-COVID era), there was a reduction of ~10% of total poisoning cases recorded (383 cases), with a majority (> 90%) of reduction from poisoning cases with no clinical effect (353 cases). A greater proportion of reduction was observed among the children (0–12 years), patients with general unintentional poisoning, poisoning due to therapeutic error and food poisoning. An increased number of cases was noted from abusive use, adverse herb/proprietary Chinese medicine reaction and poisoning related to household bleaches. Teenage (13–19 years) poisoning seemed to be unaffected by the COVID-19 pandemic and the previously observed increasing trend continued (up to 11.8% of total poisoning cases this year). Despite a total reduction in poisoning cases recorded, the number of deaths increased by 37% from 35 in 2019 to 48 in 2020 (mortality rate 1.5%). A total of seven interesting cases were discussed.

Conclusion:

This 15th annual report provides updated epidemiological information on poisoning patterns in Hong Kong during the COVID-19 pandemic. It also highlighted important changes and possible effects of the COVID-19 pandemic on poisoning in Hong Kong in comparison with our previous reports.

Maternal Stress and Neonatal Nutrition during the COVID-19 Era

Objective

COVID-19 pandemic has put a tremendous amount of stress on people, which can negatively affect nursing. Previous studies showed that perceived stress and cortisol levels in the postpartum period correlate with the LATCH scores, which is a simple tool to assess the pattern of nursing. Likewise, greater prenatal anxiety was associated with a shorter breastfeeding duration. We aimed to evaluate whether pregnant women were under extra stress due to the COVID-19 pandemic and if this stress affected their breastfeeding patterns and anthropometric measures of the neonates.

Methods

Pregnant women giving birth to healthy neonates were included. Coronavirus Anxiety Scale (CAS) and Beck Anxiety Inventory (BAI) were used to assess the anxiety levels of the mothers, and LATCH breastfeeding assessment tool was used to assess the nursing. The results of these scales and anthropometric measures of the neonates were recorded.

Results

Only one mother showed coronavirus-specific anxiety. Therefore, further analysis was done based on the Beck Anxiety (BA) levels of the mothers. CAS and BA scores were positively correlated (p<0.001, r=0.444), indicating that coronavirus-specific anxiety increased with increasing general anxiety. None of the variables changed depending on the anxiety levels of the mothers, except for the % weight gain at day five (p=0.020, r=-0.248). Even though anxiety seemed to show a small effect on weight loss during the first neonatal days, percent weight gain results did not seem to correlate with the anxiety levels in later stages (first month of life). Furthermore, LATCH scores of the infants on day one were positively correlated with BA scores of the mothers (p=0.045, r=0.175).

Conclusion

COVID-19 seemed to have no additional effect on the stress levels of the mothers. The more the mothers have anxiety, the more they may stress about the well-being of their infants, which can improve their nursing pattern.

Interventions to prevent surface transmission of an infectious virus based on real human touch behavior: a case study of the norovirus

OBJECTIVES

Infectious viruses (e.g., SARS-CoV-2, norovirus) can transmit through surfaces. Norovirus has infected millions of individuals annually. Interventions on norovirus transmission in high-risk indoor environment are important.

METHODS

This study focused on a restaurant in Guangzhou, China. More than 41,000 touches by both diners and staff members were collected using video cameras. A surface transmission model was developed and combined with these real human touch behaviors to analyze the effectiveness of different norovirus prevention strategies.

RESULTS

When the virus carrier was a diner, the virus intake fraction of diners in the same table was the highest. Increasing the touch frequency on personal private surfaces would reduce the virus exposure. The virus intake fraction was reduced by 18.4% on average if public surfaces were not touched. Optimization on surface materials could reduce the virus intake fraction by 86.6%. Additionally, disinfecting tablecloths, clothes of diners, and chairs were the three most effective surface disinfection strategies.

CONCLUSION

Controlling human touch behavior (e.g., reducing the self-touches on mucous membranes) is more effective than surface disinfection in controlling norovirus transmission, but surface disinfection cannot be ignored because human behavior is difficult to be controlled.

Analysis of COVID-19 clusters involving vertical transmission in residential buildings in Hong Kong

Multiple clusters of coronavirus disease 2019 (COVID-19) in Hong Kong have involved vertical transmissions in residential buildings, wherein the flats of confirmed cases were often vertically aligned. Data on the buildings and cases associated with 19 such clusters were retrieved and compared with the corresponding data on the entirety of Hong Kong. Vertical transmissions usually occurred in old high-rise buildings with small flat areas and low estate prices during winter. In addition, infection occurred frequently among the elderly and among upstairs neighbours of index cases. Virus-laden aerosols may have been transmitted between flats mostly via shared drainpipes, and the vertical distribution of the confirmed cases in a building varied by its drainage system design. For buildings with their entire drainpipes installed indoors, both the upstairs and downstairs neighbours of the index case flats could be infected. By comparison, buildings with their drainage stacks installed outdoors had lower infection risks and demonstrated a clearer pattern of vertical transmission: most infected cases resided upstairs from the index case flats, indicating that the virus spread could be dominated by the stack effect. This study provides valuable data and analysis for developing epidemic control strategies for residential buildings.

ELECTRONIC SUPPLEMENTARY MATERIAL ESM

The Appendix is available in the online version of this article at 10.1007/s12273-022-0929-5.

Does the length of stay in hospital affect healthcare outcomes of patients without COVID-19 who were admitted during the pandemic? A retrospective monocentric study

Uncertainties remain if changes to hospital care during the coronavirus disease (COVID-19) pandemic had an adverse impact on the care-quality of non-COVID-19 patients. We examined the association of hospital length of stay (LOS) with healthcare quality indicators in patients admitted with general medical conditions (non-COVID-19). In this retrospective monocentric study at a National Health Service hospital (Surrey), data were collected from 1st April 2019 to 31st March 2021, including the pandemic from 1st March 2020. Primary admissions, in-hospital mortality, post-discharge readmission and mortality were compared between the pre-pandemic (reference group) and pandemic period, according to LOS categories. There were 10,173 (47.7% men) from the pre-pandemic and 11,019 (47.5% men) from the pandemic period; mean (SD) age 68.3 year (20.0) and 68.3 year (19.6), respectively. During the pandemic, primary admission rates for acute cardiac conditions, pulmonary embolism, cerebrovascular accident and malignancy were higher, whilst admission rates for respiratory diseases and common age-related infections, and in-hospital mortality rates were lower. Amongst 19,721 survivors, sex distribution and underlying health status did not significantly differ between admissions before the pandemic and during wave-1 and wave-2 of the pandemic. Readmission rates did not differ between pre-pandemic and pandemic groups within the LOS categories of < 7 and 7-14 days, but were lower for the pandemic group who stayed > 14 days. For patients who died within seven days of admission, in-hospital mortality rates were lower in patients admitted during the pandemic. Mortality rates within 30 days of discharge did not differ between pre-pandemic and pandemic groups, irrespective of the initial hospital LOS. Despite higher rates of admission for serious conditions during the pandemic, in-hospital mortality was lower. Discharge time was similar to that for patients admitted before the pandemic, except it was earlier during the pandemic for those who stayed > 14 days, There were no group differences in quality-care outcomes.

Public transit travel choice in the post COVID-19 pandemic era: An application of the extended Theory of Planned behavior

It is widely reported that the COVID-19 pandemic has reduced ridership and brought severe challenges to urban public transit systems in many countries. The impact of the COVID-19 pandemic on individual people's choice of public transit may continue for a while after the peak of the crisis. However, there is insufficient detailed knowledge of how individuals respond in the post-pandemic context and make choices on public transit travel. This paper contributes fresh evidence for this by looking at Beijing as a case. The theoretical framework of the Theory of Planned Behavior is used to model individuals' public transit travel choice-making processes along with three additional constructs representing the impact of the pandemic and the nature of urban mobility behaviors, namely perceived knowledge of COVID-19, the psychological risks of COVID-19, and travel habits. Structural equation modeling is used in model estimation. We point out that there may be potential differences between the effects and meanings of model constructs in the post-pandemic context and in normal daily context. Interestingly, despite the higher psychological risk's negative effects, higher perceived knowledge of COVID-19 has significantly positive effects on people's decision-making processes. A strong pre-pandemic personal habit of traveling by public transit has significant and positive effects on post-pandemic intention and perceived behavioral control. Group comparisons show that "captive" transit users have higher psychological risk of COVID-19 than "choice" transit users, yet their transit use decisions are less influenced by it. Based on the modeling results, more behavioral experiments are needed to further inform efficient policy-making.

Optimization of COVID-19 prevention and control with low building energy consumption

COVID-19 is a global threat. Non-pharmaceutical interventions were commonly adopted for COVID-19 prevention and control. However, during stable periods of the pandemic, energy would be inevitably wasted if all interventions were implemented. The study aims to reduce the building energy consumption when meet the demands of epidemic prevention and control under the stable period of COVID-19. Based on the improved Wells-Riley model considering dynamic quanta generation and pulmonary ventilation rate, we established the infection risk - equivalent fresh air volume - energy consumption model to analyze the infection risk and building energy consumption during different seasons and optimized the urban building energy consumption according to the spatio-temporal population distribution. Shopping centers and restaurants contributed the most in urban energy consumption, and if they are closed during the pandemic, the total infection risk would be reduced by 25%-40% and 15%-25% respectively and the urban energy consumption would be reduced by 30%-40% and 13%-20% respectively. If people wore masks in all public indoor environments (exclude restaurants and KTV), the infection risk could be reduced by 60%-70% and the energy consumption could be reduced by 20%-60%. Gyms pose the highest risk for COVID-19 transmission. If the energy consumption kept the same with the current value, after the optimization, infection risk in winter, summer and the transition season could be reduced by 65%, 53% and 60%, respectively. After the optimization, under the condition of R _t  < 1, the energy consumption in winter, summer, and the transition season could be reduced by 72%, 64%, and 68% respectively.

Social Contacts and Transmission of COVID-19 in British Columbia, Canada

Background

Close-contact rates are thought to be a driving force behind the transmission of many infectious respiratory diseases. Yet, contact rates and their relation to transmission and the impact of control measures, are seldom quantified. We quantify the response of contact rates, reported cases and transmission of COVID-19, to public health contact-restriction orders, and examine the associations among these three variables in the province of British Columbia, Canada.

Methods

We derived time series data for contact rates, daily cases and transmission of COVID-19 from a social contacts survey, reported case counts and by fitting a transmission model to reported cases, respectively. We used segmented regression to investigate impacts of public health orders; Pearson correlation to determine associations between contact rates and transmission; and vector autoregressive modeling to quantify lagged associations between contacts rates, daily cases, and transmission.

Results

Declines in contact rates and transmission occurred concurrently with the announcement of public health orders, whereas declines in cases showed a reporting delay of about 2 weeks. Contact rates were a significant driver of COVID-19 and explained roughly 19 and 20% of the variation in new cases and transmission, respectively. Interestingly, increases in COVID-19 transmission and cases were followed by reduced contact rates: overall, daily cases explained about 10% of the variation in subsequent contact rates.

Conclusion

We showed that close-contact rates were a significant time-series driver of transmission and ultimately of reported cases of COVID-19 in British Columbia, Canada and that they varied in response to public health orders. Our results also suggest possible behavioral feedback, by which increased reported cases lead to reduced subsequent contact rates. Our findings help to explain and validate the commonly assumed, but rarely measured, response of close contact rates to public health guidelines and their impact on the dynamics of infectious diseases.

Optimization of energy efficiency and COVID-19 pandemic control in different indoor environments

The COVID-19 pandemic has led to considerable morbidity and mortality, and consumed enormous resources (e.g. energy) to control and prevent the disease. It is crucial to balance infection risk and energy consumption when reducing the spread of infection. In this study, a quantitative human, behavior-based, infection risk-energy consumption model for different indoor environments was developed. An optimal balance point for each indoor environment can be obtained using the anti-problem method. For this study we selected Wangjing Block, one of the most densely populated places in Beijing, as an example. Under the current ventilation standard (30 m³/h/person), prevention and control of the COVID-19 pandemic would be insufficient because the basic reproduction number (R₀ ) for students, workers and elders are greater than 1. The optimal required fresh air ventilation rates in most indoor environments are near or below 60 m³/h/person, after considering the combined effects of multiple mitigation measures. In residences, sports buildings and restaurants, the demand for fresh air ventilation rate is relatively high. After our global optimization of infection risk control (R₀  ≤ 1), energy consumption can be reduced by 13.7% and 45.1% on weekdays and weekends, respectively, in contrast to a strategy of strict control (R₀  = 1 for each indoor environment).

Human Close Contact Behavior-Based Interventions for COVID-19 Transmission

COVID-19 has threatened human lives. Countries have implemented various interventions such as vaccination, mask-wearing, body temperature screening, and isolation. However, the effectiveness of single and combined interventions has not yet been accurately analyzed. In this study, an improved SEIR model considering both real human indoor close contact behaviors and susceptibility to COVID-19 was established. Taking Hong Kong as an example, a quantitative assessment of the relationship between the efficiency of single and combined interventions and implementation time and intensity was carried out. The results showed that the infection risk (one-hour close contact with an infected person) of COVID-19 of students, workers, and non-workers/non-students was 3.1%, 8.7%, and 13.6%, respectively. Workplace closures were more effective among built environment interventions. If mask-wearing was mandatorily required in schools, workplaces, supermarkets, shopping centers, and public transport, COVID-19 could not be totally restricted. Workers should be prioritized for vaccination, followed by non-workers/non-students and students. Among all interventions, reducing close contact rate and increasing vaccination rate were better interventions. There was no COVID-19 outbreak (basic reproduction number R0 = 1) if the close contact reduction rate was 59.9% or the vaccination rate reached 89.5%. The results may provide scientific support for COVID-19 prevention and control.

Assessing customer financial risk perception and attitude in the hotel industry: Exploring the role of protective measures against COVID-19

The COVID-19 pandemic has lead authorities from many countries to adopt crucial protective measures such as wearing face masks, lockdowns and social distancing. The purpose of the present study was to explore the relationships among the protective measures against virus handled by hotels with financial risk perception, customer attitude, satisfaction and behavioral intention. The study also calculates the mean comparison across the demographic variables of hotel customer satisfaction and behavioral intention. Results reported a significant contribution of the protective measures implemented by Chinese hotels against COVID-19 on financial risk perception, and a customer attitude. It also demonstrates significant and positive interaction with customer satisfaction and behavioral intention. However, financial risk perception and customer attitude did not show effects on satisfaction, while they had effects on behavioral intention. The results suggest that protective measures are an important aspect of encouraging people to visit hotels safely and continually.

Extended short-range airborne transmission of respiratory infections

Debate and scientific inquiries regarding airborne transmission of respiratory infections such as COVID-19 and influenza continue. Health authorities including the WHO and the US CDC have recognized the airborne transmission of COVID-19 in specific settings, although the ventilation requirements remain to be determined. In this work we consider the long-range airborne transmission as an extended short-range airborne route, which reconciles the link between short- and long-range airborne routes. The effective short-range distance is defined as the distance in short range at which long-range route has the same volumetric exposure value as that due to short-range route. Our data show that a decrease in ventilation rate or room volume per person, or an increase in the ratio of the number of infected to susceptible people reduces the effective short-range distance. In a normal breathing scenario with one out of five people infected and a room volume of 12 m³ per person to ensure an effective short-range distance of 1.5 m, a ventilation rate of 10 L/s per person is needed for a duration of 2 h. Our results suggest that effective environmental prevention strategies for respiratory infections require appropriate increases in the ventilation rate while maintaining a sufficiently low occupancy. PRACTICAL IMPLICATIONS: Demonstration of the long-range airborne route as an extended short-range airborne route suggests the significant role played by building ventilation in respiratory infection exposure. The reconciliation of short- and long-range airborne transmission suggests that the commonly observed dominance of close-contact transmission is a probable evidence of short-range airborne transmission, following a separate earlier study that revealed the relative insignificance of large droplet transmission in comparison with the short-range airborne-route. Existing ventilation standards do not account for respiratory infection control, and this study presents a possible approach to account for infection under new ventilation standards.

COVID-19 Vaccination Did Not Change the Personal Protective Behaviors of Healthcare Workers in China

Personal protective behaviors of healthcare workers (HCWs) and dynamic changes in them are known to play a major role in the hospital transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, 1,499 HCWs in Chinese hospitals completed an online survey about their knowledge on SARS-CoV-2 transmission and their personal protective behaviors before and after coronavirus disease 2019 (COVID-19) vaccination. Of all the respondents, 89% were vaccinated at the time of the survey and 96% believed that the vaccine was effective or highly effective. Further, 88% of the vaccinated HCWs expressed that they would get revaccinated if the vaccination failed. Compared with HCWs with a lower education level, those with a higher education level had less fear of being infected with SARS-CoV-2 and reported a lower negative impact of the pandemic on how they treated patients. Physicians and nurses were willing to believe that short-range airborne and long-range fomite are possible transmission routes. HCWs with a higher education level had a better knowledge of COVID-19 but worse personal protective behaviors. The fact that HCWs with a longer work experience had worse personal protective behaviors showed that HCWs gradually relax their personal protective behaviors over time. Moreover, vaccination reduced the negative effects of the COVID-19 pandemic on how the HCWs treated patients. Importantly, the survey revealed that after vaccination, HCWs in China did not relax their personal protective behaviors, and it may bring a low potential risk for following waves of variant virus (e.g., delta).

Public Health Measures During the COVID-19 Pandemic Reduce the Spread of Other Respiratory Infectious Diseases

Background: Public health measures (such as wearing masks, physical distancing, and isolation) have significantly reduced the spread of the coronavirus disease-2019 (COVID-19), but the impact of public health measures on other respiratory infectious diseases is unclear.

Objective: To assess the correlation between public health measures and the incidence of respiratory infectious diseases in China during the COVID-19 pandemic.

Methods: We collected the data from the National Health and Construction Commission in China on the number of patients with six respiratory infectious diseases (measles, tuberculosis, pertussis, scarlet fever, influenza, and mumps) from 2017 to 2020 and assessed the correlation between public health measures and the incidence of respiratory infectious diseases. Finally, we used the data of the six respiratory infectious diseases in 2021 to verify our results.

Results: We found public health measures significantly reduced the incidence of measles (p = 0.002), tuberculosis (p = 0.002), pertussis (p = 0.004), scarlet fever (p = 0.002), influenza (p = 0.034), and mumps (p = 0.002) in 2020, and prevented seasonal peaks. Moreover, the effects of public health measures were most marked during the peak seasons for these infections. Of the six respiratory infectious diseases considered, tuberculosis was least affected by public health measures.

Conclusion: Public health measures were very effective in reducing the incidence of respiratory infectious diseases, especially when the respiratory infectious diseases would normally have been at their peak.

Weakening personal protective behavior by Chinese university students after COVID-19 vaccination

Personal protective behaviors and their dynamic change are known to play a major role in the community spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal pathogen of the coronavirus disease 2019 (COVID-19) pandemic. In this study, a total of 3229 students in Chinese universities completed an online survey about their knowledge on transmission and personal protective behavior before and after COVID-19 vaccination. Of the respondents, 87.6% had been vaccinated. Most students believed that the large droplet (97.0%) and short-range airborne (89.3%) routes were the two most likely SARS-CoV-2 transmission routes, whereas only 24.1% considered long-range airborne transmission to be possible. Students who would be expected to possess better knowledge about virus transmission (e.g., students of medicine) reported better personal protective behaviors. Female students reported relatively better personal hygiene practices than male students, so did the confident students than their diffident peers. Students washed their hands on average of 5.76 times per day during the pandemic. Students at universities in southern regions washed their hands more frequently but paid less attention to indoor ventilation than did their northern counterparts. Interestingly, students who are fear of being infected had the bad personal hygiene. University students wore 22% less masks in public indoor environments after vaccination. Chinese university students weakened their personal protective behavior after vaccination and it may increase the potential risk of infection in the new waves of variant virus (e.g. delta).

Analysis of efficacy of intervention strategies for COVID-19 transmission: A case study of Hong Kong

By the end of February 2021, COVID-19 had spread to over 230 countries, with more than 100 million confirmed cases and 2.5 million deaths. To control infection spread with the least disruption to economic and societal activities, it is crucial to implement the various interventions effectively. In this study, we developed an agent-based SEIR model, using real demographic and geographic data from Hong Kong, to analyse the efficiency of various intervention strategies in preventing infection by the SARS-CoV-2 virus. Close contact route including short-range airborne is considered as the main transmission routes for COVID-19 spread. Contact tracing is not that useful if all other interventions have been fully deployed. The number of infected individuals could be halved if people reduced their close contact rate by 25%. For reducing transmission, students should be prioritized for vaccination rather than retired older people and preschool aged children. Home isolation, and taking the nucleic acid test (NAT) as soon as possible after symptom onset, are much more effective interventions than wearing masks in public places. Temperature screening in public places only disrupted the infection spread by a small amount when other interventions have been fully implemented. Our results may be useful for other highly populated cities, when choosing their intervention strategies to prevent outbreaks of COVID-19 and similar diseases.

Sustainable targeted interventions to mitigate the COVID-19 pandemic: A big data-driven modeling study in Hong Kong

Nonpharmaceutical interventions (NPIs) for contact suppression have been widely used worldwide, which impose harmful burdens on the well-being of populations and the local economy. The evaluation of alternative NPIs is needed to confront the pandemic with less disruption. By harnessing human mobility data, we develop an agent-based model that can evaluate the efficacies of NPIs with individualized mobility simulations. Based on the model, we propose data-driven targeted interventions to mitigate the COVID-19 pandemic in Hong Kong without city-wide NPIs. We develop a data-driven agent-based model for 7.55×10⁶ Hong Kong residents to evaluate the efficacies of various NPIs in the first 80 days of the initial outbreak. The entire territory of Hong Kong has been split into 4905 500×500m² grids. The model can simulate detailed agent interactions based on the demographics data, public facilities and functional buildings, transportation systems, and travel patterns. The general daily human mobility patterns are adopted from Google's Community Mobility Report. The scenario without any NPIs is set as the baseline. By simulating the epidemic progression and human movement at the individual level, we propose model-driven targeted interventions which focus on the surgical testing and quarantine of only a small portion of regions instead of enforcing NPIs in the whole city. The effectiveness of common NPIs and the proposed targeted interventions are evaluated by 100 extensive simulations. The proposed model can inform targeted interventions, which are able to effectively contain the COVID-19 outbreak with much lower disruption of the city. It represents a promising approach to sustainable NPIs to help us revive the economy of the city and the world.

Changes in respiratory virus infection trends during the COVID-19 pandemic in South Korea: the effectiveness of public health measures

BACKGROUND/AIMS

Studies on the effectiveness of public health measures to prevent respiratory virus transmission in real-world settings are lacking. We investigated the effectiveness of universal mask use and adherence to other personal preventive measures on the changing viral respiratory infection patterns during the coronavirus disease 2019 (COVID-19) pandemic.

METHODS

Data were extracted from the South Korean National Respiratory Virus Sentinel Surveillance System. During the COVID-19 pandemic, a cross-sectional survey on adherence to personal preventive measures was conducted. Additionally, the number of subway passengers was analyzed to estimate physical distancing compliance.

RESULTS

During the pandemic, adherence to personal preventive measures significantly increased, particularly indoors and on public transportation. Respiratory virus trends were compared based on laboratory surveillance data of 47,675 patients with acute respiratory infections (2016 to 2020). The 2019 to 2020 influenza epidemic ended within 3 weeks, from the epidemic peak to the epidemic end, quickly ending the inf luenza season; with a 1.8- to 2.5-fold faster decline than in previous seasons. Previously, the overall respiratory virus positivity rate remained high after the influenza seasons had ended (47.7% to 69.9%). During the COVID-19 pandemic, this positive rate, 26.5%, was significantly lower than those in previous years. Hospital-based surveillance showed a decreased number of hospitalized patients with acute viral respiratory illnesses.

CONCLUSION

This study suggests that high compliance to the use of personal preventive measures in public might reduce the incidence of all respiratory virus infections and its hospitalization rates, with no additional quarantine, isolation, or contact screening.

Evidence for lack of transmission by close contact and surface touch in a restaurant outbreak of COVID-19

BACKGROUND

Coronavirus disease 2019 (COVID-19) is primarily a respiratory disease that has become a global pandemic. Close contact plays an important role in infection spread, while fomite may also be a possible transmission route. Research during the COVID-19 pandemic has identified long-range airborne transmission as one of the important transmission routes although lack solid evidence.

METHODS

We examined video data related to a restaurant associated COVID-19 outbreak in Guangzhou. We observed more than 40,000 surface touches and 13,000 episodes of close contacts in the restaurant during the entire lunch duration. These data allowed us to analyse infection risk via both the fomite and close contact routes.

RESULTS

There is no significant correlation between the infection risk via both fomite and close contact routes among those who were not family members of the index case. We can thus rule out virus transmission via fomite contact and interpersonal close contact routes in the Guangzhou restaurant outbreak. The absence of a fomite route agrees with the COVID-19 literature.

CONCLUSIONS

These results provide indirect evidence for the long-range airborne route dominating SARS-CoV-2 transmission in the restaurant. We note that the restaurant was poorly ventilated, allowing for increasing airborne SARS-CoV-2 concentration.

Diverse and nonlinear influences of built environment factors on COVID-19 spread across townships in China at its initial stage

The built environment can contribute to the spread of the novel coronavirus disease (COVID-19) by facilitating human mobility and social contacts between infected and uninfected individuals. However, mobility data capturing detailed interpersonal transmission at a large scale are not available. In this study, we aimed to objectively assess the influence of key built environment factors, which create spaces for activities—“inferred activity” rather than “actually observed activity”—on the spread of COVID-19 across townships in China at its initial stage through a random forest approach. Taking data for 2994 township-level administrative units, the spread is measured by two indicators: the ratio of cumulative infection cases (RCIC), and the coefficient of variation of infection cases (CVIC) that reflects the policy effect in the initial stage of the spread. Accordingly, we selected 19 explanatory variables covering built environment factors (urban facilities, land use, and transportation infrastructure), the level of nighttime activities, and the inter-city population flow (from Hubei Province). We investigated the spatial agglomerations based on an analysis of bivariate local indicators of spatial association between RCIC and CVIC. We found spatial agglomeration (or positive spatial autocorrelations) of RCIC and CVIC in about 20% of all townships under study. The density of convenience shops, supermarkets and shopping malls (DoCSS), and the inter-city population flow (from Hubei Province) are the two most important variables to explain RCIC, while the population flow is the most important factor in measuring policy effects (CVIC). When the DoCSS gets to 21/km², the density of comprehensive hospitals to 0.7/km², the density of road intersections to 72/km², and the density of gyms and sports centers to 2/km², their impacts on RCIC reach their maximum and remain constant with further increases in the density values. Stricter policy measures should be taken at townships with a density of colleges and universities higher than 0.5/km² or a density of comprehensive hospitals higher than 0.25/km² in order to effectively control the spread of COVID-19.