An assessment of self-reported COVID-19 related symptoms of 227,898 users of a social networking service in Japan: Has the regional risk changed after the declaration of the state of emergency?

Impact of COVID-19 pandemic on the dynamic of patients with oral and maxillofacial trauma: interrupted time-series analysis

Oral and maxillofacial trauma is influenced by various factors, including regional characteristics and social background. Due to the coronavirus disease 2019 (COVID-19) pandemic, a state of emergency was declared in Japan in March 2020. In this study, we aimed to examine the dynamics of patients with oral and maxillofacial trauma over a 12-years period using interrupted time-series (ITS) analysis. Patients were examined at the Shimane University Hospital, Maxillofacial Trauma Center from April 2012 to April 2023. In addition to general patient characteristics, data regarding the type of trauma and its treatment were obtained from 1203 patients (770 men and 433 women). Group comparisons showed significant differences in age, trauma status, method of treatment, referral source, route, and injury occasion. ITS analysis indicated significant changes in combined nasal fractures, non-invasive reduction, and sports injuries (P < 0.05), suggesting COVID-19 significantly impacted oral and maxillofacial trauma dynamics. A pandemic of an infectious disease may decrease the number of minor trauma cases but increase the number of injuries from outdoor activities, resulting in no overall change in the dynamics of the number of trauma patients. Medical systems for oral and maxillofacial trauma should be in place at all times, independent of infectious disease pandemics.

Syndromic surveillance of population-level COVID-19 burden with cough monitoring in a hospital emergency waiting room

Syndromic surveillance is an effective tool for enabling the timely detection of infectious disease outbreaks and facilitating the implementation of effective mitigation strategies by public health authorities. While various information sources are currently utilized to collect syndromic signal data for analysis, the aggregated measurement of cough, an important symptom for many illnesses, is not widely employed as a syndromic signal. With recent advancements in ubiquitous sensing technologies, it becomes feasible to continuously measure population-level cough incidence in a contactless, unobtrusive, and automated manner. In this work, we demonstrate the utility of monitoring aggregated cough count as a syndromic indicator to estimate COVID-19 cases. In our study, we deployed a sensor-based platform (Syndromic Logger) in the emergency room of a large hospital. The platform captured syndromic signals from audio, thermal imaging, and radar, while the ground truth data were collected from the hospital's electronic health record. Our analysis revealed a significant correlation between the aggregated cough count and positive COVID-19 cases in the hospital (Pearson correlation of 0.40, p-value < 0.001). Notably, this correlation was higher than that observed with the number of individuals presenting with fever (ρ = 0.22, p = 0.04), a widely used syndromic signal and screening tool for such diseases. Furthermore, we demonstrate how the data obtained from our Syndromic Logger platform could be leveraged to estimate various COVID-19-related statistics using multiple modeling approaches. Aggregated cough counts and other data, such as people density collected from our platform, can be utilized to predict COVID-19 patient visits related metrics in a hospital waiting room, and SHAP and Gini feature importance-based metrics showed cough count as the important feature for these prediction models. Furthermore, we have shown that predictions based on cough counting outperform models based on fever detection (e.g., temperatures over 39°C), which require more intrusive engagement with the population. Our findings highlight that incorporating cough-counting based signals into syndromic surveillance systems can significantly enhance overall resilience against future public health challenges, such as emerging disease outbreaks or pandemics.

Engaging a national-scale cohort of smart thermometer users in participatory surveillance

Participatory surveillance systems crowdsource individual reports to rapidly assess population health phenomena. The value of these systems increases when more people join and persistently contribute. We examine the level of and factors associated with engagement in participatory surveillance among a retrospective, national-scale cohort of individuals using smartphone-connected thermometers with a companion app that allows them to report demographic and symptom information. Between January 1, 2020 and October 29, 2022, 1,325,845 participants took 20,617,435 temperature readings, yielding 3,529,377 episodes of consecutive readings. There were 1,735,805 (49.2%) episodes with self-reported symptoms (including reports of no symptoms). Compared to before the pandemic, participants were more likely to report their symptoms during pandemic waves, especially after the winter wave began (September 13, 2020) (OR across pandemic periods range from 3.0 to 4.0). Further, symptoms were more likely to be reported during febrile episodes (OR = 2.6, 95% CI = 2.6-2.6), and for new participants, during their first episode (OR = 2.4, 95% CI = 2.4-2.5). Compared with participants aged 50-65 years old, participants over 65 years were less likely to report their symptoms (OR = 0.3, 95% CI = 0.3-0.3). Participants in a household with both adults and children (OR = 1.6 [1.6-1.7]) were more likely to report symptoms. We find that the use of smart thermometers with companion apps facilitates the collection of data on a large, national scale, and provides real time insight into transmissible disease phenomena. Nearly half of individuals using these devices are willing to report their symptoms after taking their temperature, although participation varies among individuals and over pandemic stages.

Passive Monitoring of Crowd-Level Cough Counts in Waiting Areas produces Reliable Syndromic Indicator for Total COVID-19 Burden in a Hospital Emergency Clinic

Syndromic surveillance is an effective tool for enabling the timely detection of infectious disease outbreaks and facilitating the implementation of effective mitigation strategies by public health authorities. While various information sources are currently utilized to collect syndromic signal data for analysis, the aggregated measurement of cough, an important symptom for many illnesses, is not widely employed as a syndromic signal. With recent advancements in ubiquitous sensing technologies, it becomes feasible to continuously measure population-level cough incidence in a contactless, unobtrusive, and automated manner. In this work, we demonstrate the utility of monitoring aggregated cough count as a syndromic indicator to estimate COVID-19 cases. In our study, we deployed a sensor-based platform (Syndromic Logger) in the emergency room of a large hospital. The platform captured syndromic signals from audio, thermal imaging, and radar, while the ground truth data were collected from the hospital's electronic health record. Our analysis revealed a significant correlation between the aggregated cough count and positive COVID-19 cases in the hospital (Pearson correlation of 0.40, p-value < 0.001). Notably, this correlation was higher than that observed with the number of individuals presenting with fever (ρ = 0.22, p = 0.04), a widely used syndromic signal and screening tool for such diseases. Furthermore, we demonstrate how the data obtained from our Syndromic Logger platform could be leveraged to estimate various COVID-19-related statistics using multiple modeling approaches. Our findings highlight the efficacy of aggregated cough count as a valuable syndromic indicator associated with the occurrence of COVID-19 cases. Incorporating this signal into syndromic surveillance systems for such diseases can significantly enhance overall resilience against future public health challenges, such as emerging disease outbreaks or pandemics.

Smart Thermometer-Based Participatory Surveillance to Discern the Role of Children in Household Viral Transmission During the COVID-19 Pandemic

Importance

Children's role in spreading virus during the COVID-19 pandemic is yet to be elucidated, and measuring household transmission traditionally requires contact tracing.

Objective

To discern children's role in household viral transmission during the pandemic when enveloped viruses were at historic lows and the predominance of viral illnesses were attributed to COVID-19.

Design, Setting, and Participants

This cohort study of a voluntary US cohort tracked data from participatory surveillance using commercially available thermometers with a companion smartphone app from October 2019 to October 2022. Eligible participants were individuals with temperature measurements in households with multiple members between October 2019 and October 2022 who opted into data sharing.

Main Outcomes and Measures

Proportion of household transmissions with a pediatric index case and changes in transmissions during school breaks were assessed using app and thermometer data.

Results

A total of 862 577 individuals from 320 073 households with multiple participants (462 000 female [53.6%] and 463 368 adults [53.7%]) were included. The number of febrile episodes forecast new COVID-19 cases. Within-household transmission was inferred in 54 506 (15.4%) febrile episodes and increased from the fourth pandemic period, March to July 2021 (3263 of 32 294 [10.1%]) to the Omicron BA.1/BA.2 wave (16 516 of 94 316 [17.5%]; P < .001). Among 38 787 transmissions in 166 170 households with adults and children, a median (IQR) 70.4% (61.4%-77.6%) had a pediatric index case; proportions fluctuated weekly from 36.9% to 84.6%. A pediatric index case was 0.6 to 0.8 times less frequent during typical school breaks. The winter break decrease was from 68.4% (95% CI, 57.1%-77.8%) to 41.7% (95% CI, 34.3%-49.5%) at the end of 2020 (P < .001). At the beginning of 2022, it dropped from 80.3% (95% CI, 75.1%-84.6%) to 54.5% (95% CI, 51.3%-57.7%) (P < .001). During summer breaks, rates dropped from 81.4% (95% CI, 74.0%-87.1%) to 62.5% (95% CI, 56.3%-68.3%) by August 2021 (P = .02) and from 83.8% (95% CI, 79.2%-87.5) to 62.8% (95% CI, 57.1%-68.1%) by July 2022 (P < .001). These patterns persisted over 2 school years.

Conclusions and Relevance

In this cohort study using participatory surveillance to measure within-household transmission at a national scale, we discerned an important role for children in the spread of viral infection within households during the COVID-19 pandemic, heightened when schools were in session, supporting a role for school attendance in COVID-19 spread.

Designing Digital COVID-19 Screening: Insights and Deliberations

Due to the global COVID-19 pandemic, public health control and screening measures have been introduced at healthcare facilities, including those housing our most vulnerable populations. These warning measures situated at hospital entrances are presently labour-intensive, requiring additional staff to conduct manual temperature checks and risk-assessment questionnaires of every individual entering the premises. To make this process more efficient, we present eGate, a digital COVID-19 health-screening smart Internet of Things system deployed at multiple entry points around a children's hospital. This paper reports on design insights based on the experiences of concierge screening staff stationed alongside the eGate system. Our work contributes towards social-technical deliberations on how to improve design and deploy of digital health-screening systems in hospitals. It specifically outlines a series of design recommendations for future health screening interventions, key considerations relevant to digital screening control systems and their implementation, and the plausible effects on the staff who work alongside them.

Seroprevalence of SARS-CoV2 Infections in Health Care Personnel in a Long-Term Care Institution After the First Wave of the Pandemic: A Cross-Sectional Study

BACKGROUND

At the time of our study, occupational health evidence specific for long-term care employees was mostly lacking. The purpose of this study was to determine the proportion of positive cases in employees after the first COVID-19 wave in May 2020. We also determined the prevalence of asymptomatic cases.

METHOD

The study population included all health care workers (HCW) employed at one mid-size long-term hospital in Spain (May 2020). A cross-sectional study design included an interviewer-administered self-reported questionnaire (including sociodemographic questions, risk factors for COVID-19 complications such as hypertension or diabetes, and previous polymerase chain reaction [PCR] results) and antibody determination (Biozek rapid test). Data were analyzed using Student's t, Fisher, and chi-square tests. Two multivariate logistic models were created to evaluate exposure factors and symptoms separately on the outcome of having had COVID-19.

FINDINGS

Of the 97% of workers who participated (580/596), 300 (51.7%) suffered symptoms of COVID-19, 161 (27.8%) of the rapid antibody tests were positive for IgM and/or IgG, 160 (27.6%) workers had at least one risk factor, and 32 (19.0%) of the 168 SARS-CoV-2-positive cases were asymptomatic. The proportion of negative or unavailable PCRs, with positive antibody, was 11.7% (56/477). Casual contact without protection (odds ratio [OR]: 1.9, 95% confidence interval [CI]: 1.1-3.4), doctor occupation (OR 3.3, 95% CI: 1.1-10.2), and nursing assistant occupation (OR 2.5, 95% CI: 1.2-5.8) were independently associated with SARS-CoV-2 infection.

CONCLUSION

Physicians and nursing assistants in a long-term care setting were at a higher risk of SARS-COV-2 infection over other occupations in the first wave of the pandemic, especially when in contact with patients without protection. Almost one-fifth of the workers with a positive PCR test for SARS-COV-2 were asymptomatic and seroprevalence (27.8%) was well below the approximated herd immunity cutoff (60-70%). Essential workers in long-term care must be monitored frequently by Employee Health Service and should be required to wear personal protective equipment including a fit-tested N-95 while in close contact with patients and coworkers.

Covid-19 vaccination reported side effects and hesitancy among the Syrian population: a cross-sectional study

INTRODUCTION

Studying post-vaccination side effects and identifying the reasons behind low vaccine uptake are pivotal for overcoming the pandemic.

METHODS

This cross-sectional study was distributed through social media platforms and face-to-face interviews. Data from vaccinated and unvaccinated participants were collected and analyzed using the chi-square test, multivariable logistic regression to detect factors associated with side effects and severe side effects.

RESULTS

Of the 3509 participants included, 1672(47.6%) were vaccinated. The most common reason for not taking the vaccine was concerns about the vaccine's side effects 815(44.4). The majority of symptoms were mild 788(47.1%), followed by moderate 374(22.3%), and severe 144(8.6%). The most common symptoms were tiredness 1028(61.5%), pain at the injection site 933(55.8%), and low-grade fever 684(40.9%). Multivariable logistic regression analysis revealed that <40 years (vs. ≥40; OR: 2.113, p-value = 0.008), females (vs. males; OR: 2.245, p-value< .001), did not receive influenza shot last year (vs. did receive Influenza shot last year OR: 1.697, p-value = 0.041), AstraZeneca (vs. other vaccine brands; OR: 2.799, p-value< .001), co-morbidities (vs. no co-morbidities; OR: 1.993, p-value = 0.008), and diabetes mellitus (vs. no diabetes mellitus; OR: 2.788, p-value = 0.007) were associated with severe post-vaccine side effects. Serious side effects reported were blood clots 5(0.3%), thrombocytopenia 2(0.1%), anaphylaxis 1(0.1%), seizures 1(0.1%), and cardiac infarction 1(0.1%).

CONCLUSION

Our study revealed that most side effects reported were mild in severity and self-limiting. Increasing the public's awareness of the nature of the vaccine's side effects would reduce the misinformation and improve the public's trust in vaccines. Larger studies to evaluate rare and serious adverse events and long-term side effects are needed, so people can have sufficient information and understanding before making an informed consent which is essential for vaccination.

Demographic and professional risk factors of SARS-CoV-2 infections among physicians in low- and middle-income settings: Findings from a representative survey in two Brazilian states

Health workers (HWs) are a key resource for health systems worldwide, and have been affected heavily by the COVID-19 pandemic. Evidence is consolidating on incidence and drivers of infections, predominantly in high-income settings. It is however unclear what the risk factors may be for specific health professions, particularly in low- and middle-income countries (LMICs). We conducted a cross-sectional survey in a representative sample of 1,183 medical doctors registered with Brazil's Federal Council of Medicine in one developed (São Paulo) and one disadvantaged state (Maranhão). Between February-June 2021, we administered a telephone questionnaire to collect data on physicians' demographics, deployment to services, vaccination status, and self-reported COVID-19 infections. We performed descriptive, univariate, and multilevel clustered analysis to explore the association between physicians' infection rates, and their sociodemographic and employment characteristics. A generalized linear mixed model with a binomial distribution was used to estimate the adjusted odds ratio. We found that 35.8% of physicians in our sample declared having been infected with SARS-CoV-2 virus during the first year of the pandemic. The infection rate in Maranhão (49.2%) [95% CI 45.0-53.4] was almost twice that in São Paulo (24.1%) [95% CI 20.8-27.5]. Being a physician in Maranhão [95% CI 2.08-3.57], younger than 50 years [95% CI 1.41-2.89] and having worked in a COVID-19 ward [95% CI 1.28-2.27], were positively associated with the probability of infection. Conversely, working with diagnostic services [95% CI 0.53-0.96], in administrative functions [95% CI 0.42-0.80], or in teaching and research [95% CI 0.48-0.91] were negatively associated. Based on our data from Brazil, COVID-19 infections in LMICs may be more likely in health systems with lower physician-to-patient ratios, and younger doctors working in COVID-19 wards may be infected more frequently. Such findings may be used to identify policies to mitigate COVID-19 effects on HWs in LMICs.

SARS-CoV-2 suppression and early closure of bars and restaurants: a longitudinal natural experiment

Despite severe economic damage, full-service restaurants and bars have been closed in hopes of suppressing the spread of SARS-CoV-2 worldwide. This paper explores whether the early closure of restaurants and bars in February 2021 reduced symptoms of SARS-CoV-2 in Japan. Using a large-scale nationally representative longitudinal survey, we found that the early closure of restaurants and bars decreased the utilization rate among young persons (OR 0.688; CI95 0.515-0.918) and those who visited these places before the pandemic (OR 0.754; CI95 0.594-0.957). However, symptoms of SARS-CoV-2 did not decrease in these active and high-risk subpopulations. Among the more inactive and low-risk subpopulations, such as elderly persons, no discernible impacts are observed in both the utilization of restaurants and bars and the symptoms of SARS-CoV-2. These results suggest that the early closure of restaurants and bars without any other concurrent measures does not contribute to the suppression of SARS-CoV-2.

Longitudinal analysis of built environment and aerosol contamination associated with isolated COVID-19 positive individuals

The indoor environment is the primary location for the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), largely driven by respiratory particle accumulation in the air and increased connectivity between the individuals occupying indoor spaces. In this study, we aimed to track a cohort of subjects as they occupied a COVID-19 isolation dormitory to better understand the impact of subject and environmental viral load over time, symptoms, and room ventilation on the detectable viral load within a single room. We find that subject samples demonstrate a decrease in overall viral load over time, symptoms significantly impact environmental viral load, and we provide the first real-world evidence for decreased aerosol SARS-CoV-2 load with increasing ventilation, both from mechanical and window sources. These results may guide environmental viral surveillance strategies and be used to better control the spread of SARS-CoV-2 within built environments and better protect those caring for individuals with COVID-19.

Project and Prototype of Mobile Application for Monitoring the Global COVID-19 Epidemiological Situation

The purpose of this research is to analyze currently available solutions that help to monitor the global epidemiological situation, including travel restrictions, as well as proposing a new solution dedicated to users who want to keep updated with the current restrictions and COVID-19-related statistics. The analysis of existing tools is prepared from the perspective of practical usability for the end user. This paper consists of an overview of the tools and techniques of data visualization and demonstrates how to integrate them with practical business usage in a mobile application.

Covidseeker: A Geospatial Temporal Surveillance Tool

Introduction: Geospatial temporal data derived from smartphones traditionally used for purposes of navigation may offer valuable information for public health surveillance and locational hot spotting. Our objective was to develop a web-based application, called Covidseeker, that captures continuous fine-grained geospatial temporal data from smartphones and leverages these data to study transmission patterns of COVID-19. Methods: This report describes the development of Covidseeker and the process by which it utilizes geospatial temporal data from smartphones and processes it into a usable format to study geospatial temporal patterns of COVID-19. We provide an overview of the design process, the principles, the software architecture, and the dashboard of the Covidseeker application and consider key challenges and strategic uses of capturing geospatial temporal data and the potential for future applications in outbreak surveillance. Results: A resource such as Covidseeker can support situational awareness by providing information about the location and timing of transmission of diseases such as COVID-19. Geospatial temporal data housed in smartphones hold tremendous potential to capture more depth about where and when transmission occurs and the patterns of human mobility that lead to increases in risk of COVID-19. Conclusion: An enormous and highly rich source of geospatial temporal information about human mobility can be used to provide highly localized discrete information that is difficult to capture by traditional sources. The architecture of Covidseeker can be applied to help track COVID-19 and should be integrated with traditional disease surveillance practices.

Comparison of longitudinal trends in self-reported symptoms and COVID-19 case activity in Ontario, Canada

BACKGROUND

Limitations in laboratory diagnostic capacity impact population surveillance of COVID-19. It is currently unknown whether participatory surveillance tools for COVID-19 correspond to government-reported case trends longitudinally and if it can be used as an adjunct to laboratory testing. The primary objective of this study was to determine whether self-reported COVID-19-like illness reflected laboratory-confirmed COVID-19 case trends in Ontario Canada.

METHODS

We retrospectively analyzed longitudinal self-reported symptoms data collected using an online tool-Outbreaks Near Me (ONM)-from April 20th, 2020, to March 7th, 2021 in Ontario, Canada. We measured the correlation between COVID-like illness among respondents and the weekly number of PCR-confirmed COVID-19 cases and provincial test positivity. We explored contemporaneous changes in other respiratory viruses, as well as the demographic characteristics of respondents to provide context for our findings.

RESULTS

Between 3,849-11,185 individuals responded to the symptom survey each week. No correlations were seen been self-reported CLI and either cases or test positivity. Strong positive correlations were seen between CLI and both cases and test positivity before a previously documented rise in rhinovirus/enterovirus in fall 2020. Compared to participatory surveillance respondents, a higher proportion of COVID-19 cases in Ontario consistently came from low-income, racialized and immigrant areas of the province- these groups were less well represented among survey respondents.

INTERPRETATION

Although digital surveillance systems are low-cost tools that have been useful to signal the onset of viral outbreaks, in this longitudinal comparison of self-reported COVID-like illness to Ontario COVID-19 case data we did not find this to be the case. Seasonal respiratory virus transmission and population coverage may explain this discrepancy.

Exploring the Spatiotemporal Evolution and Sustainable Driving Factors of Information Flow Network: A Public Search Attention Perspective

The promotion of information flow reinforces the interactive cooperation and evolutionary process among cities. In the information age, public online search is a typical behavior of Internet society, which is the key to information flow generation and agglomeration. In this study, we attempt to explore the evolutionary characteristics of intercity networks driven by public online social behavior in the information age and construct an information flow network (IFN) from the perspective of public search attention. We also explore the evolution of the IFN in terms of the whole network, node hierarchy, and subgroup aggregation. Meanwhile, we also discuss the impact of the sustainable driving factors on the IFN. Finally, an empirical study was conducted in Guanzhong Plain Urban Agglomeration (GPUA). Our results show that: (1) the information flow in GPUA fluctuating upward in the early study period and gradually decreasing in the later study period. However, the agglomeration degree of information flow in the urban agglomeration continues to increase. (2) The hierarchical structure of urban nodes in GPUA presents a trend of “high in the middle and low on both sides”, and the formation of subgroups is closely related to geographic location. (3) The driving factors all impacting the IFN include public ecology, resource investment, information infrastructure, and economic foundation. This study provides theoretical and practical support for exploring the intercity network and promotes the sustainable urban development.

A review of GIS methodologies to analyze the dynamics of COVID-19 in the second half of 2020

COVID-19 has infected over 163 million people and has resulted in over 3.9 million deaths. Regarding the tools and strategies to research the ongoing pandemic, spatial analysis has been increasingly utilized to study the impacts of COVID-19. This article provides a review of 221 scientific articles that used spatial science to study the pandemic published from June 2020 to December 2020. The main objectives are: to identify the tools and techniques used by the authors; to review the subjects addressed and their disciplines; and to classify the studies based on their applications. This contribution will facilitate comparisons with the body of work published during the first half of 2020, revealing the evolution of the COVID-19 phenomenon through the lens of spatial analysis. Our results show that there was an increase in the use of both spatial statistical tools (e.g., geographically weighted regression, Bayesian models, spatial regression) applied to socioeconomic variables and analysis at finer spatial and temporal scales. We found an increase in remote sensing approaches, which are now widely applied in studies around the world. Lockdowns and associated changes in human mobility have been extensively examined using spatiotemporal techniques. Another dominant topic studied has been the relationship between pollution and COVID-19 dynamics, which enhance the impact of human activities on the pandemic's evolution. This represents a shift from the first half of 2020, when the research focused on climatic and weather factors. Overall, we have seen a vast increase in spatial tools and techniques to study COVID-19 transmission and the associated risk factors.

Assessing the capacity of symptom scores to predict COVID-19 positivity in Nigeria: a national derivation and validation cohort study

OBJECTIVES

This study aimed to develop and validate a symptom prediction tool for COVID-19 test positivity in Nigeria.

DESIGN

Predictive modelling study.

SETTING

All Nigeria States and the Federal Capital Territory.

PARTICIPANTS

A cohort of 43 221 individuals within the national COVID-19 surveillance dataset from 27 February to 27 August 2020. Complete dataset was randomly split into two equal halves: derivation and validation datasets. Using the derivation dataset (n=21 477), backward multivariable logistic regression approach was used to identify symptoms positively associated with COVID-19 positivity (by real-time PCR) in children (≤17 years), adults (18-64 years) and elderly (≥65 years) patients separately.

OUTCOME MEASURES

Weighted statistical and clinical scores based on beta regression coefficients and clinicians' judgements, respectively. Using the validation dataset (n=21 744), area under the receiver operating characteristic curve (AUROC) values were used to assess the predictive capacity of individual symptoms, unweighted score and the two weighted scores.

RESULTS

Overall, 27.6% of children (4415/15 988), 34.6% of adults (9154/26 441) and 40.0% of elderly (317/792) that had been tested were positive for COVID-19. Best individual symptom predictor of COVID-19 positivity was loss of smell in children (AUROC 0.56, 95% CI 0.55 to 0.56), either fever or cough in adults (AUROC 0.57, 95% CI 0.56 to 0.58) and difficulty in breathing in the elderly (AUROC 0.53, 95% CI 0.48 to 0.58) patients. In children, adults and the elderly patients, all scoring approaches showed similar predictive performance.

CONCLUSIONS

The predictive capacity of various symptom scores for COVID-19 positivity was poor overall. However, the findings could serve as an advocacy tool for more investments in resources for capacity strengthening of molecular testing for COVID-19 in Nigeria.

Decreased human respiratory syncytial virus activity during the COVID-19 pandemic in Japan: an ecological time-series analysis

BACKGROUND

Non-pharmaceutical interventions (NPIs), such as sanitary measures and travel restrictions, aimed at controlling the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), may affect the transmission dynamics of human respiratory syncytial virus (HRSV). We aimed to quantify the contribution of the sales of hand hygiene products and the number of international and domestic airline passenger arrivals on HRSV epidemic in Japan.

METHODS

The monthly number of HRSV cases per sentinel site (HRSV activity) in 2020 was compared with the average of the corresponding period in the previous 6 years (from January 2014 to December 2020) using a monthly paired t-test. A generalized linear gamma regression model was used to regress the time-series of the monthly HRSV activity against NPI indicators, including sale of hand hygiene products and the number of domestic and international airline passengers, while controlling for meteorological conditions (monthly average temperature and relative humidity) and seasonal variations between years (2014-2020).

RESULTS

The average number of monthly HRSV case notifications in 2020 decreased by approximately 85% (p < 0.001) compared to those in the preceding 6 years (2014-2019). For every average ¥1 billion (approximately £680,000/$9,000,000) spent on hand hygiene products during the current month and 1 month before there was a 0.29% (p = 0.003) decrease in HRSV infections. An increase of average 1000 domestic and international airline passenger arrivals during the previous 1-2 months was associated with a 3.8 × 10^- 4% (p < 0.001) and 1.2 × 10^- 3% (p < 0.001) increase in the monthly number of HRSV infections, respectively.

CONCLUSIONS

This study suggests that there is an association between the decrease in the monthly number of HRSV cases and improved hygiene and sanitary measures and travel restrictions for COVID-19 in Japan, indicating that these public health interventions can contribute to the suppression of HRSV activity. These findings may help in public health policy and decision making.

Development and assessment of a hospital admissions-based syndromic surveillance system for COVID-19 in Ontario, Canada: ACES Pandemic Tracker

BACKGROUND

The COVID-19 pandemic has continued to pose a major global public health risk. The importance of public health surveillance systems to monitor the spread and impact of COVID-19 has been well demonstrated. The purpose of this study was to describe the development and effectiveness of a real-time public health syndromic surveillance system (ACES Pandemic Tracker) as an early warning system and to provide situational awareness in response to the COVID-19 pandemic in Ontario, Canada.

METHODS

We used hospital admissions data from the Acute Care Enhanced Surveillance (ACES) system to collect data on pre-defined groupings of symptoms (syndromes of interest; SOI) that may be related to COVID-19 from 131 hospitals across Ontario. To evaluate which SOI for suspected COVID-19 admissions were best correlated with laboratory confirmed admissions, laboratory confirmed COVID-19 hospital admissions data were collected from the Ontario Ministry of Health. Correlations and time-series lag analysis between suspected and confirmed COVID-19 hospital admissions were calculated. Data used for analyses covered the period between March 1, 2020 and September 21, 2020.

RESULTS

Between March 1, 2020 and September 21, 2020, ACES Pandemic Tracker identified 22,075 suspected COVID-19 hospital admissions (150 per 100,000 population) in Ontario. After correlation analysis, we found laboratory-confirmed hospital admissions for COVID-19 were strongly and significantly correlated with suspected COVID-19 hospital admissions when SOI were included (Spearman's rho = 0.617) and suspected COVID-19 admissions when SOI were excluded (Spearman's rho = 0.867). Weak to moderate significant correlations were found among individual SOI. Laboratory confirmed COVID-19 hospital admissions lagged in reporting by 3 days compared with suspected COVID-19 admissions when SOI were excluded.

CONCLUSIONS

Our results demonstrate the utility of a hospital admissions syndromic surveillance system to monitor and identify potential surges in severe COVID-19 infection within the community in a timely manner and provide situational awareness to inform preventive and preparatory health interventions.

Association between participation in the government subsidy programme for domestic travel and symptoms indicative of COVID-19 infection in Japan: cross-sectional study

OBJECTIVE

To investigate the association between participation in government subsidies for domestic travel (subsidise up to 50% of all travel expenses) introduced nationally in Japan on 22 July 2020 and the incidence of symptoms indicative of COVID-19 infections.

DESIGN

Cross-sectional analysis of nationally representative survey data.

SETTING

Internet survey conducted between 25 August and 30 September 2020 in Japan. Sampling weights were used to calculate national estimates.

PARTICIPANTS

25 482 survey respondents (50.3% (12 809) women; mean (SD) age, 48.8 (17.4) years).

MAIN OUTCOME MEASURES

Incidence rate of five symptoms indicative of the COVID-19 infection (high fever, sore throat, cough, headache, and smell and taste disorder) within the past month of the survey, after adjustment for characteristics of individuals and prefecture fixed effects (effectively comparing individuals living in the same prefecture).

RESULTS

At the time of the survey, 3289 (12.9%) participated in the subsidy programme. After adjusting for potential confounders, we found that participants in the subsidy programme exhibited higher incidence of high fever (adjusted rate, 4.7% for participants vs 3.7% for non-participants; adjusted OR (aOR) 1.83; 95% CI 1.34 to 2.48; p<0.001), sore throat (19.8% vs 11.3%; aOR 2.09; 95% CI 1.37 to 3.19; p=0.002), cough (19.0% vs 11.3%; aOR 1.96; 95% CI 1.26 to 3.01; p=0.008), headache (29.2% vs 25.5%; aOR 1.24; 95% CI 1.08 to 1.44; p=0.006) and smell and taste disorder (2.6% vs 1.8%; aOR 1.98; 95% CI 1.15 to 3.40; p=0.01) compared with non-participants. These findings remained qualitatively unaffected by additional adjustment for the use of 17 preventative measures (eg, social distancing, wearing masks and handwashing) and fear against the COVID-19 infection.

CONCLUSIONS

The participation of the government subsidy programme for domestic travel was associated with a higher probability of exhibiting symptoms indicative of the COVID-19 infection.

COVID-19 and Heat Illness in Tokyo, Japan: Implications for the Summer Olympic and Paralympic Games in 2021

The 2020 summer Olympic and Paralympic Games in Tokyo were postponed to July-September 2021 due to the coronavirus disease 2019 (COVID-19) pandemic. While COVID-19 has emerged as a monumental health threat for mass gathering events, heat illness must be acknowledged as a potentially large health threat for maintaining health services. We examined the number of COVID-19 admissions and the Tokyo rule for emergency medical care, in Tokyo, from March to September 2020, and investigated the weekly number of emergency transportations due to heat illness and weekly averages of the daily maximum Wet Bulb Globe Temperature (WBGT) in Tokyo in the summer (2016-2020). The peak of emergency transportations due to heat illness overlapped the resurgence of COVID-19 in 2020, and an increase of heat illness patients and WBGT has been observed. Respect for robust science is critical for the decision-making process of mass gathering events during the pandemic, and science-based countermeasures and implementations for COVID-19 will be warranted. Without urgent reconsiderations and sufficient countermeasures, the double burden of COVID-19 and heat-related illnesses in Tokyo will overwhelm the healthcare provision system, and maintaining essential health services will be challenging during the 2021 summer Olympic and Paralympic Games.

Association between Participation in Government Subsidy Program for Domestic Travel and Symptoms Indicative of COVID-19 Infection

Importance

As countermeasures against the economic downturn caused by the coronavirus 2019 (COVID-19) pandemic, many countries have introduced or considering financial incentives for people to engage in economic activities such as travel and use restaurants. Japan has implemented a large-scale, nationwide government-funded program that subsidizes up to 50% of all travel expenses since July 2020 with the aim of reviving the travel industry. However, it remains unknown as to how such provision of government subsidies for travel impacted the COVID-19 pandemic.

Objective

To investigate the association between participation in government subsidies for domestic travel in Japan and the incidence of COVID-19 infections.

Design Setting and Participants

Using the data from a large internet survey conducted between August 25 and September 30, 2020, in Japan, we examined whether individuals who used subsidies experienced a higher likelihood of symptoms indicative of the COVID-19 infection.

Exposure

Participation in the government subsidy program for domestic travel.

Main Outcomes and Measures

Five symptoms indicative of the COVID-19 infection (high fever, sore throat, cough, headache, and smell and taste disorder) within the past one month of the survey.

Results

Of the 25,482 respondents (50.3% [12,809] women; mean [SD] age, 48.4 [17.4] years), 3,289 (12.9%) participated in the subsidy program at the time of survey. After adjusting for potential confounders, we found that participants in the subsidy program exhibited higher incidence of high fever (adjusted rate, 4.8% for participants vs. 3.7% for non-participants; adjusted odds ratio [aOR], 1.90; 95%CI, 1.42-2.54; p<0.001), sore throat (19.8% vs. 11.3%; aOR, 2.09; 95%CI, 1.37-3.20; p=0.002), cough (19.1% vs. 11.2%; aOR 1.96; 95%CI, 1.27-3.02; p=0.007), headache (29.1% vs. 25.5%; aOR, 1.24; 95%CI, 1.07-1.43; p=0.007), and smell and taste disorder (2.6% vs. 1.8%; aOR 1.98; 95%CI; 1.15-3.40; p=0.01) compared with non-participants.

Conclusion and Relevance

The participants of government subsidies for domestic travel experienced a higher incidence of symptoms indicative of the COVID-19 infection.

Lessons Learned from Japan's Response to the First Wave of COVID-19: A Content Analysis

While the epidemiological impact of the coronavirus disease 2019 (COVID-19) pandemic has been relatively moderate in East-Asian countries, the pandemic has significantly impacted on citizens' lives and livelihoods, and Japan is no exception. In the early phase of the COVID-19 pandemic, Japan managed unprecedented quarantines and realized the difficulty of controlling COVID-19, finally recording a relatively high number of deaths per million in the Western Pacific region. However, scant research has highlighted the distinctive features of Japan's reaction and the challenges encountered. To clarify these points and examine Japan's first response to COVID-19, we performed a content analysis. Minutes of expert meetings were analyzed from multiple viewpoints, including epidemiology, health systems, border control, and health communication. The obscure evolution of the testing strategy, the usefulness of retrospective contact tracing, the rapid scientific risk assessment, a sluggish expansion of health system capacity and response in border control, and misunderstanding between risk communication and crisis communication are made evident by our analysis. Examining previous responses and gathering lessons learned in each country will improve global responses to COVID-19 and strengthen regional health security. Therefore, while investing in public health and ensuring transparency, Japan needs to clarify the previous decision-making process of each countermeasure towards COVID-19.

Trend change of the transmission route of COVID-19-related symptoms in Japan

OBJECTIVES

The Japanese prime minister declared a state of emergency on April 7 2020 to combat the outbreak of coronavirus disease 2019 (COVID-19). This declaration was unique in the sense that it was essentially driven by the voluntary restraint of the residents. We examined the change of the infection route by investigating contact experiences with COVID-19-positive cases.

STUDY DESIGN

This study is a population-level questionnaire-based study using a social networking service (SNS).

METHODS

To assess the impact of the declaration, this study used population-level questionnaire data collected from an SNS with 121,375 respondents (between March 27 and May 5) to assess the change in transmission routes over the study period, which was measured by investigating the association between COVID-19-related symptoms and (self-reported) contact with COVID-19-infected individuals.

RESULTS

The results of this study show that the declaration prevented infections in the workplace, but increased domestic infections as people stayed at home. However, after April 24, workplace infections started to increase again, driven by the increase in community-acquired infections.

CONCLUSIONS

While careful interpretation is necessary because our data are self-reported from voluntary SNS users, these findings indicate the impact of the declaration on the change in transmission routes of COVID-19 over time in Japan.