Surveillance of COVID-19 in the General Population Using an Online Questionnaire: Report From 18,161 Respondents in China

Relationship between depression and burnout among nurses in Intensive Care units at the late stage of COVID-19: a network analysis

BACKGROUND

Mental health problems are critical and common in medical staff working in Intensive Care Units (ICU) even at the late stage of COVID-19, particularly for nurses. There is little research to explore the inner relationships between common syndromes, such as depression and burnout. Network analysis (NA) was a novel approach to quantified the correlations between mental variables from the perspective of mathematics. This study was to investigate the interactions between burnout and depression symptoms through NA among ICU nurses.

METHOD

A cross-sectional study with a total of 616 Chinese nurses in ICU were carried out by convenience sampling from December 19, 2022 to January19, 2023 via online survey. Burnout symptoms were measured by Maslach Burnout Inventory-General Survey (MBI-GS) (Chinese version), and depressive symptoms were assessed by the 9-item Patient Health Questionnaire (PHQ-9). NA was applied to build interactions between burnout and depression symptoms. We identified central and bridge symptoms by R package qgraph in the network model. R package bootnet was used to examined the stability of network structure.

RESULTS

The prevalence of burnout and depressive symptoms were 48.2% and 64.1%, respectively. Within depression-burnout network, PHQ4(Fatigue)-MBI2(Used up) and PHQ4(Fatigue)-MBI5(Breakdown) showed stronger associations. MBI2(Used up) had the strongest expected influence central symptoms, followed by MBI4(Stressed) and MBI7 (Less enthusiastic). For bridge symptoms. PHQ4(Fatigue), MBI5(Breakdown) and MBI2(Used up) weighed highest. Both correlation stability coefficients of central and bridge symptoms in the network structure were 0.68, showing a high excellent level of stability.

CONCLUSION

The symptom of PHQ4(Fatigue) was the bridge to connect the emotion exhaustion and depression. Targeting this symptom will be effective to detect mental disorders and relieve mental syndromes of ICU nurses at the late stage of COVID-19 pandemic.

Impact of the COVID-19 Pandemic on People Living With Rare Diseases and Their Families: Results of a National Survey

BACKGROUND

With more than 103 million cases and 1.1 million deaths, the COVID-19 pandemic has had devastating consequences for the health system and the well-being of the entire US population. The Rare Diseases Clinical Research Network funded by the National Institutes of Health was strategically positioned to study the impact of the pandemic on the large, vulnerable population of people living with rare diseases (RDs).

OBJECTIVE

This study was designed to describe the characteristics of COVID-19 in the RD population, determine whether patient subgroups experienced increased occurrence or severity of infection and whether the pandemic changed RD symptoms and treatment, and understand the broader impact on respondents and their families.

METHODS

US residents who had an RD and were <90 years old completed a web-based survey investigating self-reported COVID-19 infection, pandemic-related changes in RD symptoms and medications, access to care, and psychological impact on self and family. We estimated the incidence of self-reported COVID-19 and compared it with that in the US population; evaluated the frequency of COVID-19 symptoms according to self-reported infection; assessed infection duration, complications and need for hospitalization; assessed the influence of the COVID-19 pandemic on RD symptoms and treatment, and whether the pandemic influenced access to care, special food and nutrition, or demand for professional psychological assistance.

RESULTS

Between May 2, 2020, and December 15, 2020, in total, 3413 individuals completed the survey. Most were female (2212/3413, 64.81%), White (3038/3413, 89.01%), and aged ≥25 years (2646/3413, 77.53%). Overall, 80.6% (2751/3413) did not acquire COVID-19, 2.08% (71/3413) acquired it, and 16.58% (566/3413) did not know. Self-reported cases represented an annual incidence rate of 2.2% (95% CI 1.7%-2.8%). COVID-19 cases were more than twice the expected (71 vs 30.3; P<.001). COVID-19 was associated with specific symptoms (loss of taste: odds ratio [OR] 38.9, 95% CI 22.4-67.6, loss of smell: OR 30.6, 95% CI 17.7-53.1) and multiple symptoms (>9 symptoms vs none: OR 82.5, 95% CI 29-234 and 5-9: OR 44.8, 95% CI 18.7-107). Median symptom duration was 16 (IQR 9-30) days. Hospitalization (7/71, 10%) and ventilator support (4/71, 6%) were uncommon. Respondents who acquired COVID-19 reported increased occurrence and severity of RD symptoms and use or dosage of select medications; those who did not acquire COVID-19 reported decreased occurrence and severity of RD symptoms and use of medications; those who did not know had an intermediate pattern. The pandemic made it difficult to access care, receive treatment, get hospitalized, and caused mood changes for respondents and their families.

CONCLUSIONS

Self-reported COVID-19 was more frequent than expected and was associated with increased prevalence and severity of RD symptoms and greater use of medications. The pandemic negatively affected access to care and caused mood changes in the respondents and family members. Continued surveillance is necessary.

Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review

BACKGROUND

Public health surveillance plays a vital role in informing public health decision-making. The onset of the COVID-19 pandemic in early 2020 caused a widespread shift in public health priorities. Global efforts focused on COVID-19 monitoring and contact tracing. Existing public health programs were interrupted due to physical distancing measures and reallocation of resources. The onset of the COVID-19 pandemic intersected with advancements in technologies that have the potential to support public health surveillance efforts.

OBJECTIVE

This scoping review aims to explore emergent public health surveillance methods during the early COVID-19 pandemic to characterize the impact of the pandemic on surveillance methods.

METHODS

A scoping search was conducted in multiple databases and by scanning key government and public health organization websites from March 2020 to January 2022. Published papers and gray literature that described the application of new or revised approaches to public health surveillance were included. Papers that discussed the implications of novel public health surveillance approaches from ethical, legal, security, and equity perspectives were also included. The surveillance subject, method, location, and setting were extracted from each paper to identify trends in surveillance practices. Two public health epidemiologists were invited to provide their perspectives as peer reviewers.

RESULTS

Of the 14,238 unique papers, a total of 241 papers describing novel surveillance methods and changes to surveillance methods are included. Eighty papers were review papers and 161 were single studies. Overall, the literature heavily featured papers detailing surveillance of COVID-19 transmission (n=187). Surveillance of other infectious diseases was also described, including other pathogens (n=12). Other public health topics included vaccines (n=9), mental health (n=11), substance use (n=4), healthy nutrition (n=1), maternal and child health (n=3), antimicrobial resistance (n=2), and misinformation (n=6). The literature was dominated by applications of digital surveillance, for example, by using big data through mobility tracking and infodemiology (n=163). Wastewater surveillance was also heavily represented (n=48). Other papers described adaptations to programs or methods that existed prior to the COVID-19 pandemic (n=9). The scoping search also found 109 papers that discuss the ethical, legal, security, and equity implications of emerging surveillance methods. The peer reviewer public health epidemiologists noted that additional changes likely exist, beyond what has been reported and available for evidence syntheses.

CONCLUSIONS

The COVID-19 pandemic accelerated advancements in surveillance and the adoption of new technologies, especially for digital and wastewater surveillance methods. Given the investments in these systems, further applications for public health surveillance are likely. The literature for surveillance methods was dominated by surveillance of infectious diseases, particularly COVID-19. A substantial amount of literature on the ethical, legal, security, and equity implications of these emerging surveillance methods also points to a need for cautious consideration of potential harm.

Prevalence and network structure of post-traumatic stress symptoms and their association with suicidality among Chinese mental health professionals immediately following the end of China's Dynamic Zero-COVID Policy: a national survey

Studies on post-traumatic stress symptoms (PTSS) among mental health professionals (MHPs) are limited, particularly since restrictions due to coronavirus disease (COVID-19) have been lifted such as the recent termination of China's Dynamic Zero-COVID Policy. The current study filled this gap by exploring the prevalence, correlates, and network structure of PTSS as well as its association with suicidality from a network analysis perspective. A cross-sectional, national survey was conducted using a convenience sampling method on MHPs between January 22 and February 10, 2023. PTSS were assessed using the Post-Traumatic Stress Disorder Checklist-Civilian version, while suicidality was assessed using standardized questions related to ideation, plans, and attempts. Univariate and multivariate analyses examined correlates of PTSS. Network analysis explored the structure of PTSS and suicidality. The centrality index of "Expected influence" was used to identify the most central symptoms in the network, reflecting the relative importance of each node in the network. The "flow" function was adopted to identify specific symptoms that were directly associated with suicidality. A total of 10,647 MHPs were included. The overall rates of PTSS and suicidality were 6.7% (n = 715; 95% CI = 6.2-7.2%) and 7.7% (n = 821; 95% CI = 7.2-8.2%), respectively. Being married (OR = 1.523; P < 0.001), quarantine experience (OR = 1.288; P < 0.001), suicidality (OR = 3.750; P < 0.001) and more severe depressive symptoms (OR = 1.229; P < 0.001) were correlates of more PTSS. Additionally, higher economic status (e.g., good vs. poor: OR = 0.324; P = 0.001) and health status (e.g., good vs. poor: OR = 0.456; P < 0.001) were correlates of reduced PTSS. PCL6 ("Avoiding thoughts"; EI = 1.189), PCL7 ("Avoiding reminders"; EI = 1.157), and PCL11 ("Feeling emotionally numb"; EI = 1.074) had the highest centrality, while PCL12 ("Negative belief"), PCL 16 ("Hypervigilance") and PCL 14 ("Irritability") had the strongest direct, positive associations with suicidality. A high prevalence of lingering PTSS was found among MHPs immediately after China's "Dynamic Zero-COVID Policy" was terminated. Avoidance and hyper-arousal symptoms should be monitored among at-risk MHPs after the COVID-19 pandemic and serve as potential targets for the prevention and treatment of PTSS in this population.

Prevalence of COVID-19 fear and its association with quality of life and network structure among Chinese mental health professionals after ending China's dynamic zero-COVID policy: a national survey

Background

China recorded a massive COVID-19 pandemic wave after ending its Dynamic Zero-COVID Policy on January 8, 2023. As a result, mental health professionals (MHPs) experienced negative mental health consequences, including an increased level of fear related to COVID-19. This study aimed to explore the prevalence and correlates of COVID-19 fear among MHPs following the end of the Policy, and its association with quality of life (QoL) from a network analysis perspective.

Methods

A cross-sectional national study was conducted across China. The correlates of COVID-19 fear were examined using both univariate and multivariate analyses. An analysis of covariance (ANCOVA) was conducted to determine the relationship between fear of COVID-19 and QoL. Central symptoms were identified using network analysis through the "Expected Influence" of the network model while specific symptoms directly correlated with QoL were identified through the "flow function."

Results

A total of 10,647 Chinese MHPs were included. The overall prevalence of COVID-19 fear (FCV-19S total score ≥ 16) was 60.8% (95% CI = 59.9-61.8%). The binary logistic regression analysis found that MHPs with fear of COVID-19 were more likely to be married (OR = 1.198; p < 0.001) and having COVID-19 infection (OR = 1.235; p = 0.005) and quarantine experience (OR = 1.189; p < 0.001). Having better economic status (good vs. poor: OR = 0.479; p < 0.001; fair vs. poor: OR = 0.646; p < 0.001) and health status (good vs. poor: OR = 0.410; p < 0.001; fair vs. poor: OR = 0.617; p < 0.001) were significantly associated with a lower risk of COVID-19 fear. The ANCOVA showed that MHPs with fear of COVID-19 had lower QoL [F = 228.0, p < 0.001]. "Palpitation when thinking about COVID-19" was the most central symptom in the COVID-19 fear network model, while "Uncomfortable thinking about COVID-19" had the strongest negative association with QoL (average edge weight = -0.048).

Conclusion

This study found a high prevalence of COVID-19 fear among Chinese MHPs following the end of China's Dynamic Zero-COVID Policy. Developing effective prevention and intervention measures that target the central symptoms as well as symptoms correlated with QoL in our network structure would be important to address COVID-19 fear and improve QoL.

An interactive national digital surveillance system to fight against COVID-19 in Bangladesh

Background

COVID-19 has affected many people globally, including in Bangladesh. Due to a lack of preparedness and resources, Bangladesh has experienced a catastrophic health crisis, and the devastation caused by this deadly virus has not yet been halted. Hence, precise and rapid diagnostics and infection tracing are essential for managing the condition and limiting its spread. The conventional screening procedure, such as reverse transcription polymerase chain reaction (RT-PCR), is not available in most rural areas and is time-consuming. Therefore, a data-driven intelligent surveillance system can be advantageous for rapid COVID-19 screening and risk estimation.

Objectives

This study describes the design, development, implementation, and characteristics of a nationwide web-based surveillance system for educating, screening, and tracking COVID-19 at the community level in Bangladesh.

Methods

The system consists of a mobile phone application and a cloud server. The data is collected by community health professionals via home visits or telephone calls and analyzed using rule-based artificial intelligence (AI). Depending on the results of the screening procedure, a further decision is made regarding the patient. This digital surveillance system in Bangladesh provides a platform to support government and non-government organizations, including health workers and healthcare facilities, in identifying patients at risk of COVID-19. It refers people to the nearest government healthcare facility, collecting and testing samples, tracking and tracing positive cases, following up with patients, and documenting patient outcomes.

Results

This study began in April 2020, and the results are provided in this paper till December 2022. The system has successfully completed 1,980,323 screenings. Our rule-based AI model categorized them into five separate risk groups based on the acquired patient information. According to the data, around 51% of the overall screened populations are safe, 35% are low risk, 9% are high risk, 4% are mid risk, and the remaining 1% is very high risk. The dashboard integrates all collected data from around the nation onto a single platform.

Conclusion

This screening can help the symptomatic patient take immediate action, such as isolation or hospitalization, depending on the severity. This surveillance system can also be utilized for risk mapping, planning, and allocating health resources to more vulnerable areas to reduce the virus's severity.

Inter-relationships of depressive and anxiety symptoms with suicidality among adolescents: A network perspective

BACKGROUND

Persons with suicidality including suicidal ideation (SI), suicide plans (SP) and/or suicide attempts (SA) are at higher risk for future suicide than those without suicidality. To reduce the risk of future suicide, it is important to understand symptoms of emotional distress that have the strongest links with SI, SP and SA. This network analysis examined item-level relations of depressive and anxiety symptoms with suicidality among adolescents during the COVID-19 pandemic.

METHODS

Adolescents between 12 and 20 years of age were assessed with the Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder Scale (GAD-7), and individual binary reponse (no/yes) items assessing SI, SP, and SA during the pandemic. The structure of depressive symptoms, anxiety symptoms and suicidality was characterized using "Expected Influence" and "Bridge Expected Influence" as centrality indices in the symptom network. Network stability was tested using a case-dropping bootstrap procedure. Node-specific predictive betweenness was computed to examine short paths of anhedonia, other depressive symptoms and anxiety symptoms with suicidality. A Network Comparison Test (NCT) was conducted to examine whether network characteristics differed based on gender.

RESULTS

Prevalence rates of depressive symptoms, anxiety symptoms, and suicidality were 44.60 % (95% confidence interval (CI) = 41.53-47.67 %), 31.12 % (95%CI = 28.26-33.98 %), and 16.95 % (95%CI = 14.63-19.26 %), respectively, in the study sample. The network analysis identified GAD3 ("Worry too much") as the most central symptom, followed by GAD6 ("Irritability") and PHQ6 ("Guilt") in the sample. Additionally, PHQ6 ("Guilt"), GAD6 ("Irritability"), and PHQ2 ("Sad mood") were bridge nodes linking depressive and anxiety symptoms with suicidality. A flow network indicated that the connection between S ("Suicidality") and PHQ6 ("Guilt") reflected the strongest connection, followed by connections of S ("Suicidality") with GAD2 ("Uncontrollable worrying"), and S ("Suicidality") with PHQ2 ("Sad mood"). Finally, PHQ2 ("Sad mood") was the main bridge node linking anhedonia with other depressive and anxiety symptoms and suicidality in the sample.

CONCLUSIONS

Findings highlight the potential importance of reducing specific depressive and anxiety symptoms as possible means of reducing suicidality among adolescents during the pandemic. Central symptoms and key bridge symptoms identified in this study should be targeted in suicide prevention for at-risk adolescents.

Network analysis of depression, anxiety, insomnia and quality of life among Macau residents during the COVID-19 pandemic

BACKGROUND

Although the Coronavirus Disease 2019 (COVID-19) has greatly impacted individuals' mental health and quality of life, network analysis studies of associations between symptoms of common syndromes during the pandemic are lacking, particularly among Macau residents. This study investigated the network structure of insomnia, anxiety, and depression and explored their associations with quality of life in this population.

METHOD

This online survey was conducted in Macau between August 18 and November 9, 2020. Insomnia, anxiety, depressive symptoms, and quality of life were assessed with the Insomnia Severity Index, Generalized Anxiety Disorder Scale, Patient Health Questionnaire, and World Health Organization Quality of Life-brief version, respectively. Analyses were performed to identify central symptoms and bridge symptoms of this network and their links to quality of life.

RESULTS

975 participants enrolled in this survey. The prevalence of depressive, anxiety and insomnia symptoms were 38.5% (95% confidence interval (CI): 35.5%-41.5%), 28.8% (95%CI: 26.0%-31.7%), and 27.6% (95% CI: 24.8%-30.4%), respectively. "Sleep maintenance" had the highest expected influence centrality, followed by "Trouble relaxing", "Interference with daytime functioning", "Irritability", and "Fatigue". Five bridge symptoms were identified: "Sleep problems", "Restlessness", "Irritability", "Severity of sleep onset", and "Motor activity". The insomnia symptom, "Sleep dissatisfaction", had the strongest direct relation to quality of life.

CONCLUSION

Insomnia symptoms played a critical role in the distress symptom network regarding node and bridge centrality as well as associations with quality of life among Macau residents. Close attention to these symptoms may be critical to reducing risk and preventing exacerbations in common forms of distress in this population.

Evaluating the feasibility and acceptability of an exercise and behaviour change intervention in socioeconomically deprived patients with peripheral arterial disease: The textpad study protocol

This pilot randomised controlled trial aims to assess the feasibility and acceptability of a 12-week home-based telehealth exercise and behavioural intervention delivered in socioeconomically deprived patients with peripheral artery disease (PAD). The study will also determine the preliminary effectiveness of the intervention for improving clinical and health outcomes. Sixty patients with PAD who meet the inclusion criteria will be recruited from outpatient clinic at the Freeman Hospital, United Kingdom. The intervention group will undergo telehealth behaviour intervention performed 3 times per week over 3 months. This program will comprise a home-based exercise (twice a week) and an individual lifestyle program (once per week). The control group will receive general health recommendations and advice to perform unsupervised walking training. The primary outcome will be feasibility and acceptability outcomes. The secondary outcomes will be objective and subjective function capacity, quality of life, dietary quality, physical activity levels, sleep pattern, alcohol and tobacco use, mental wellbeing, and patients’ activation. This pilot study will provide preliminary evidence of the feasibility, acceptability and effectiveness of home-based telehealth exercise and behavioural intervention delivered in socioeconomically deprived patients with PAD. In addition, the variance of the key health outcomes of this pilot study will be used to inform the sample size calculation for a future fully powered, multicentre randomized clinical trial.

Identification of central symptoms in Internet addictions and depression among adolescents in Macau: A network analysis

BACKGROUND

Internet addiction (IA) and depression are common among adolescents and often are co-occurring. This study examined the network structures of IA and depressive symptoms (depression hereafter) in adolescents.

METHODS

A total of 1,009 adolescents were recruited. IA and depression were measured using the Internet Addiction Test (IAT) and the 9 items-Patient Health Questionnaire (PHQ-9), respectively. A network analysis was conducted to identify central symptoms and bridge symptoms using centrality indices. Network stability was evaluated using the case-dropping procedure. The Network Comparison Test (NCT) was conducted to examine whether network characteristics differed by gender.

RESULTS

Network analysis revealed that nodes IAT-15 ("Preoccupation with the Internet"), IAT-2 ("Neglect chores to spend more time online"), PHQ-6 ("Guilty"), and IAT-16 ("Request an extension for longer time spent online") were the most central symptoms within the model of coexisting IA and depression. The most important bridge symptom was node IAT-11 ("Anticipation for future online activities"), followed by IAT-12 ("Fear that life is boring and empty without the Internet") and IAT-19 ("Spend more time online over going out with others"). Gender did not significantly influence the network structure. The IA and depression network model showed a high degree of stability.

CONCLUSION

The central symptoms along with key bridge symptoms identified could be potentially targeted when treating and preventing IA and depression among adolescents.

Network analysis of depressive and anxiety symptoms in adolescents during the later stage of the COVID-19 pandemic

Network analysis is an effective approach for examining complex relationships between psychiatric symptoms. This study was designed to examine item-level relationships between depressive and anxiety symptoms using network analysis in an adolescent sample and identified the most central symptoms within the depressive-anxiety symptoms network model. Depressive and anxiety symptoms were assessed using the Patient Health Questionire-9 (PHQ-9) and Generalized Anxiety Disorder Screener (GAD-7), respectively. The structure of depressive and anxiety symptoms was characterized using "Strength" and "Bridge Strength" as centrality indices in the symptom network. Network stability was tested using a case-dropping bootstrap procedure. Finally, a Network Comparison Test (NCT) was conducted to examine whether network characteristics differed on the basis of gender, school grade and residence. Network analysis revealed that nodes PHQ2 ("Sad mood"), GAD6 ("Irritability"), GAD3 ("Worry too much"), and PHQ6 ("Guilty") were central symptoms in the network model of adolescents. Additionally, bridge symptoms linking anxiety and depressive symptoms in this sample were nodes PHQ6 ("Guilty"), PHQ2 ("Sad mood"), and PHQ9 ("Suicide ideation"). Gender, school grade and residence did not significantly affect the network structure. Central symptoms (e.g., Sad mood, Irritability, Worry too much, and Guilty) and key bridge symptoms (e.g., Guilty, Sad mood, and Suicide ideation) in the depressive and anxiety symptoms network may be useful as potential targets for intervention among adolescents who are at risk for or suffer from depressive and anxiety symptoms.

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.

How to identify the most suitable questionnaires and rating scales for your clinical practice or research?

BACKGROUND

Selection of the most suitable instrument for a health outcome or exposure assessment is challenging, as there are many different instruments and their versions, most with unknown validity.

AIMS

To develop guidelines facilitating the search for the most suitable instrument.

MATERIALS AND METHODS

Based on our experience, we formalised a five-step process. The first step is the search for systematic reviews of available instruments validity in COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN), International prospective register of systematic reviews (PROSPERO), or conventional (eg, Medline and Web of Science) databases. If there is no systematic review, the clinician should look for original validation studies and assess them critically. We presented two alternatives of this assessment: qualitative using COSMIN and quantitative using our methodological framework. The latter helps to decide upon the instrument validity completeness and interpret the statistical results from original studies objectively. This process was then transformed into guidelines, which were tested by three external clinicians to select the most appropriate instrument to measure depression, occupational stress and daily fatigue.

RESULTS

The guidelines were proved to facilitate the instrument search and selection, practical and time-saving.

DISCUSSION

The guidelines assessment highlighted that clinicians should check whether the instrument that they are looking for was developed for screening or diagnosing purposes, whether it can be self-administered or not, and for which setting it was validated (academic vs clinical).

CONCLUSION

These guidelines facilitate the objective choice of the most suitable instrument in clinical practice by making the search simple, systematic and time-effective.

Exploring the Clinical Utility of Gustatory Dysfunction (GD) as a Triage Symptom Prior to Reverse Transcription Polymerase Chain Reaction (RT-PCR) in the Diagnosis of COVID-19: A Meta-Analysis and Systematic Review

BACKGROUND

The diagnosis of COVID-19 is made using reverse transcription polymerase chain reaction (RT-PCR) but its sensitivity varies from 20 to 100%. The presence of gustatory dysfunction (GD) in a patient with upper respiratory tract symptoms might increase the clinical suspicion of COVID-19.

AIMS

To perform a systematic review and meta-analysis to determine the pooled sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-) and diagnostic odds ratio (DOR) of using GD as a triage symptom prior to RT-PCR.

METHODS

PubMed and Embase were searched up to 20 June 2021. Studies published in English were included if they compared the frequency of GD in COVID-19 adult patients (proven by RT-PCR) to COVID-19 negative controls in case control or cross-sectional studies. The Newcastle-Ottawa scale was used to assess the methodological quality of the included studies.

RESULTS

21,272 COVID-19 patients and 52,298 COVID-19 negative patients were included across 44 studies from 21 countries. All studies were of moderate to high risk of bias. Patients with GD were more likely to test positive for COVID-19: DOR 6.39 (4.86-8.40), LR+ 3.84 (3.04-4.84), LR- 0.67 (0.64-0.70), pooled sensitivity 0.37 (0.29-0.47) and pooled specificity 0.92 (0.89-0.94). While history/questionnaire-based assessments were predictive of RT-PCR positivity (DOR 6.62 (4.95-8.85)), gustatory testing was not (DOR 3.53 (0.98-12.7)). There was significant heterogeneity among the 44 studies (I2 = 92%, p < 0.01).

CONCLUSIONS

GD is useful as a symptom to determine if a patient should undergo further testing, especially in resource-poor regions where COVID-19 testing is scarce. Patients with GD may be advised to quarantine while repeated testing is performed if the initial RT-PCR is negative.

FUNDING

None.

Digital SARS-CoV-2 Detection Among Hospital Employees: Participatory Surveillance Study

Background

The implementation of novel techniques as a complement to traditional disease surveillance systems represents an additional opportunity for rapid analysis.

Objective

The objective of this work is to describe a web-based participatory surveillance strategy among health care workers (HCWs) in two Swiss hospitals during the first wave of COVID-19.

Methods

A prospective cohort of HCWs was recruited in March 2020 at the Cantonal Hospital of St. Gallen and the Eastern Switzerland Children’s Hospital. For data analysis, we used a combination of the following techniques: locally estimated scatterplot smoothing (LOESS) regression, Spearman correlation, anomaly detection, and random forest.

Results

From March 23 to August 23, 2020, a total of 127,684 SMS text messages were sent, generating 90,414 valid reports among 1004 participants, achieving a weekly average of 4.5 (SD 1.9) reports per user. The symptom showing the strongest correlation with a positive polymerase chain reaction test result was loss of taste. Symptoms like red eyes or a runny nose were negatively associated with a positive test. The area under the receiver operating characteristic curve showed favorable performance of the classification tree, with an accuracy of 88% for the training data and 89% for the test data. Nevertheless, while the prediction matrix showed good specificity (80.0%), sensitivity was low (10.6%).

Conclusions

Loss of taste was the symptom that was most aligned with COVID-19 activity at the population level. At the individual level—using machine learning–based random forest classification—reporting loss of taste and limb/muscle pain as well as the absence of runny nose and red eyes were the best predictors of COVID-19.

Syndromic surveillance to detect disease outbreaks using time between emergency department presentations

OBJECTIVE

Early warning of disease outbreaks is paramount for health jurisdictions. The objective of the present study was to develop syndromic surveillance monitoring plans from routinely collected ED data with application to detecting disease outbreaks.

METHODS

The study involved secondary data analysis of ED presentations to major public hospitals in Queensland and South Australia spanning 2017-2020. Monitoring plans were developed for all major Queensland and South Australian public hospitals using an adaptation of Exponentially Weighted Moving Averages - a process control method used in detecting anomalies in industrial production processes. The methods rely on setting a threshold (control limit) relating to the time between an event of interest (e.g. flu outbreak) using ED presentations as a signal to monitor. An outbreak is flagged as this time gets significantly smaller, and each event offers a decision point on whether an outbreak has occurred. The models incorporate differing levels of temporal memory to cover outbreaks of different sizes.

RESULTS

The novel approach to real-time outbreak detection indicates outbreaks for individual hospitals coinciding with the first wave of the COVID-19 outbreak in Queensland and South Australia as well as the large 2017 and 2019 influenza seasons.

CONCLUSION

Outbreak detection models demonstrate the ability to quickly flag an outbreak based on clinician-assigned ED diagnoses. An implemented syndromic surveillance approach can pick up geographic outbreaks quickly so they can be contained. Such capability can help with surveillance related to the current COVID-19 pandemic and potential future pandemics.

Data Empowerment of Decision-Makers in an Era of a Pandemic: Intersection of "Classic" and Artificial Intelligence in the Service of Medicine

BACKGROUND

The COVID-19 outbreak required prompt action by health authorities around the world in response to a novel threat. With enormous amounts of information originating in sources with uncertain degree of validation and accuracy, it is essential to provide executive-level decision-makers with the most actionable, pertinent, and updated data analysis to enable them to adapt their strategy swiftly and competently.

OBJECTIVE

We report here the origination of a COVID-19 dedicated response in the Israel Defense Forces with the assembly of an operational Data Center for the Campaign against Coronavirus.

METHODS

Spearheaded by directors with clinical, operational, and data analytics orientation, a multidisciplinary team utilized existing and newly developed platforms to collect and analyze large amounts of information on an individual level in the context of SARS-CoV-2 contraction and infection.

RESULTS

Nearly 300,000 responses to daily questionnaires were recorded and were merged with other data sets to form a unified data lake. By using basic as well as advanced analytic tools ranging from simple aggregation and display of trends to data science application, we provided commanders and clinicians with access to trusted, accurate, and personalized information and tools that were designed to foster operational changes and mitigate the propagation of the pandemic. The developed tools aided in the in the identification of high-risk individuals for severe disease and resulted in a 30% decline in their attendance to their units. Moreover, the queue for laboratory examination for COVID-19 was optimized using a predictive model and resulted in a high true-positive rate of 20%, which is more than twice as high as the baseline rate (2.28%, 95% CI 1.63%-3.19%).

CONCLUSIONS

In times of ambiguity and uncertainty, along with an unprecedented flux of information, health organizations may find multidisciplinary teams working to provide intelligence from diverse and rich data a key factor in providing executives relevant and actionable support for decision-making.

Attitudes Toward COVID-19 Vaccines in Chinese Adolescents

Background: As COVID-19 vaccination programs are being implemented widely, it is important to examine the attitudes of adolescents toward the COVID-19 vaccine and its uptake. The aim of this study was to examine the acceptance of and attitudes toward COVID-19 vaccines, and their associated factors among adolescents in China.

Methods: This was a cross-sectional, observational study conducted between November 27, 2020 and March 12, 2021 using snowball sampling method. Basic sociodemographic characteristics, health-related information, severity of depressive and anxiety symptoms, and attitudes and behavior toward COVID-19 vaccines were assessed.

Results: Overall, 1,057 adolescents participated in this study, yielding a response rate of 89.3%. There were 799 (75.59%) [95% Confidence Interval (CI) 73.00–78.18%] adolescents who would accept future COVID-19 vaccination. Binary logistic regression analysis revealed that adolescents who previously heard about COVID-19 vaccines (P = 0.001, odds ratio (OR) = 1.90, 95%CI:1.32–2.74), who thought that COVID-19 vaccines could protect them from COVID-19 infection (P = 0.002, OR = 2.93, 95%CI: 1.49–5.70), and those who encouraged their family members and friends to get vaccinated (P < 0.001, OR = 12.19, 95%CI: 6.78–21.92) and who believed that vaccines are safe (P = 0.012, OR = 3.94, 95%CI: 1.36–11.44) were more likely to accept future COVID-19 vaccination. In addition, younger adolescents (P = 0.003, OR = 0.93, 95%CI: 0.89–0.98) were more likely to accept future COVID-19 vaccines than older adolescents.

Conclusions: In conclusion, Chinese adolescents appeared to have positive attitudes toward COVID-19 vaccines. It is important to increase public confidence and knowledge regarding the efficacy and safety of COVID-19 vaccines to maximize the success of vaccination programs.

The role of ethics in science: a systematic literature review from the first wave of COVID-19

This paper proposes a systematic literature review on ethics and CoviD-19, aiming to understand the impact and the perception of the pandemic during the first wave (January-June 2020) and the consequences one year later. PubMed was systematically searched up May 2020 to identify studies that took into consideration various ethical issues that have been arising from the Covid-19 outbreak. The eligibility of the papers was determined by two authors, who screened the results mediated by a third author. In order to facilitate the screening, the titles were divided into five sub-thematic macro-areas, namely allocation, policy, specialist, clinical trials, and technology and, when possible, per geographical area. Specifically, a posteriori, we decided to focus on the papers referring to policies and technology, as they highlighted ethical issues that are not overused and worthy of particular attention. Thus, 38 studies out of 233 met our inclusion criteria and were fully analysed. Accordingly, this review touches on themes such as fairness, equity, transparency of information, the duty of care, racial disparities, the marginalisation of the poor, and privacy and ethical concerns. Overall, it was found that despite the increased awareness of interdisciplinarity and the essential reference to ethics, many scientific articles use it with little competence, considering it only a "humanitarian" enrichment. In fact, as we understand, reflecting a year after the outbreak of the pandemic, although Covid-19 is leading scientists to increasingly recognise the importance of ethical issues, there is still a lot of confusion that could be helped by establishing international guidelines to act as a moral compass in times of crisis.

Capturing COVID-19-Like Symptoms at Scale Using Banner Ads on an Online News Platform: Pilot Survey Study

Background

Identifying new COVID-19 cases is challenging. Not every suspected case undergoes testing, because testing kits and other equipment are limited in many parts of the world. Yet populations increasingly use the internet to manage both home and work life during the pandemic, giving researchers mediated connections to millions of people sheltering in place.

Objective

The goal of this study was to assess the feasibility of using an online news platform to recruit volunteers willing to report COVID-19like symptoms and behaviors.

Methods

An online epidemiologic survey captured COVID-19related symptoms and behaviors from individuals recruited through banner ads offered through Microsoft News. Respondents indicated whether they were experiencing symptoms, whether they received COVID-19 testing, and whether they traveled outside of their local area.

Results

A total of 87,322 respondents completed the survey across a 3-week span at the end of April 2020, with 54.3% of the responses from the United States and 32.0% from Japan. Of the total respondents, 19,631 (22.3%) reported at least one symptom associated with COVID-19. Nearly two-fifths of these respondents (39.1%) reported more than one COVID-19like symptom. Individuals who reported being tested for COVID-19 were significantly more likely to report symptoms (47.7% vs 21.5%; P<.001). Symptom reporting rates positively correlated with per capita COVID-19 testing rates (R²=0.26; P<.001). Respondents were geographically diverse, with all states and most ZIP Codes represented. More than half of the respondents from both countries were older than 50 years of age.

Conclusions

News platforms can be used to quickly recruit study participants, enabling collection of infectious disease symptoms at scale and with populations that are older than those found through social media platforms. Such platforms could enable epidemiologists and researchers to quickly assess trends in emerging infections potentially before at-risk populations present to clinics and hospitals for testing and/or treatment.

Participatory COVID-19 Surveillance Tool in Rural Appalachia : Real-Time Disease Monitoring and Regional Response

INTRODUCTION

Few US studies have examined the usefulness of participatory surveillance during the coronavirus disease 2019 (COVID-19) pandemic for enhancing local health response efforts, particularly in rural settings. We report on the development and implementation of an internet-based COVID-19 participatory surveillance tool in rural Appalachia.

METHODS

A regional collaboration among public health partners culminated in the design and implementation of the COVID-19 Self-Checker, a local online symptom tracker. The tool collected data on participant demographic characteristics and health history. County residents were then invited to take part in an automated daily electronic follow-up to monitor symptom progression, assess barriers to care and testing, and collect data on COVID-19 test results and symptom resolution.

RESULTS

Nearly 6500 county residents visited and 1755 residents completed the COVID-19 Self-Checker from April 30 through June 9, 2020. Of the 579 residents who reported severe or mild COVID-19 symptoms, COVID-19 symptoms were primarily reported among women (n = 408, 70.5%), adults with preexisting health conditions (n = 246, 70.5%), adults aged 18-44 (n = 301, 52.0%), and users who reported not having a health care provider (n = 131, 22.6%). Initial findings showed underrepresentation of some racial/ethnic and non-English-speaking groups.

PRACTICAL IMPLICATIONS

This low-cost internet-based platform provided a flexible means to collect participatory surveillance data on local changes in COVID-19 symptoms and adapt to guidance. Data from this tool can be used to monitor the efficacy of public health response measures at the local level in rural Appalachia.

Physical activity, screen exposure and sleep among students during the pandemic of COVID-19

This study aimed to determine the levels of health-related behaviours (physical activity, screen exposure and sleep status) among Chinese students from primary, secondary and high schools during the pandemic of COVID-19, as well as their changes compared with their status before the pandemic. A cross-sectional online survey of 10,933 students was conducted among 10 schools in Guangzhou, China, between 8th and 15th March, 2020. After getting the informed consent from student's caregivers, an online questionnaire was designed and used to obtain time spending on health-related behaviours during the pandemic of COVID-19, as well as the changes compared with 3 months before the pandemic, which was completed by students themselves or their caregivers. Students were stratified by regions (urban, suburban, exurban), gender (boys and girls), and grades (lower grades of primary school, higher grades of primary schools, secondary schools and high schools). Data were expressed as number and percentages and Chi-square test was used to analyse difference between groups. Overall, the response rate of questionnaire was 95.3% (10,416/10,933). The median age of included students was 13.0 (10.0, 16.0) years and 50.1% (n = 5,219) were boys. 41.4%, 53.6% and 53.7% of total students reported less than 15 min per day in light, moderate and vigorous activities and 58.7% (n = 6,113) reported decreased participation in physical activity compared with the time before pandemic. Over 5 h of screen time spending on online study was reported by 44.6% (n = 4,649) of respondents, particular among high school students (81.0%). 76.9% of students reported increased screen time compared with the time before pandemic. Inadequate sleep was identified among 38.5% of students and the proportion was highest in high school students (56.9%). Our study indicated that, during the COVID-19 pandemic, the school closure exerted tremendous negative effects on school-aged children's health habits, including less physical activity, longer screen exposure and irregular sleeping pattern.

Hamster and ferret experimental infection with intranasal low dose of a single strain of SARS-CoV-2

Understanding the pathogenesis of the SARS-CoV-2 infection is key to developing preventive and therapeutic strategies against COVID-19, in the case of severe illness but also when the disease is mild. The use of appropriate experimental animal models remains central in the in vivo exploration of the physiopathology of infection and antiviral strategies. This study describes SARS-CoV-2 intranasal infection in ferrets and hamsters with low doses of low-passage SARS-CoV-2 clinical French isolate UCN19, describing infection levels, excretion, immune responses and pathological patterns in both animal species. Individual infection with 103 p.f.u. SARS-CoV-2 induced a more severe disease in hamsters than in ferrets. Viral RNA was detected in the lungs of hamsters but not of ferrets and in the brain (olfactory bulb and/or medulla oblongata) of both species. Overall, the clinical disease remained mild, with serological responses detected from 7 days and 10 days post-inoculation in hamsters and ferrets respectively. The virus became undetectable and pathology resolved within 14 days. The kinetics and levels of infection can be used in ferrets and hamsters as experimental models for understanding the pathogenicity of SARS-CoV-2, and testing the protective effect of drugs.

The Global Infectious Diseases Epidemic Information Monitoring System: Development and Usability Study of an Effective Tool for Travel Health Management in China

BACKGROUND

Obtaining comprehensive epidemic information for specific global infectious diseases is crucial to travel health. However, different infectious disease information websites may have different purposes, which may lead to misunderstanding by travelers and travel health staff when making accurate epidemic control and management decisions.

OBJECTIVE

The objective of this study was to develop a Global Infectious Diseases Epidemic Information Monitoring System (GIDEIMS) in order to provide comprehensive and timely global epidemic information.

METHODS

Distributed web crawler and cloud agent acceleration technologies were used to automatically collect epidemic information about more than 200 infectious diseases from 26 established epidemic websites and Baidu News. Natural language processing and in-depth learning technologies have been utilized to intelligently process epidemic information collected in 28 languages. Currently, the GIDEIMS presents world epidemic information using a geographical map, including date, disease name, reported cases in different countries, and the epidemic situation in China. In order to make a practical assessment of the GIDEIMS, we compared infectious disease data collected from the GIDEIMS and other websites on July 16, 2019.

RESULTS

Compared with the Global Incident Map and Outbreak News Today, the GIDEIMS provided more comprehensive information on human infectious diseases. The GIDEIMS is currently used in the Health Quarantine Department of Shenzhen Customs District (Shenzhen, China) and was recommended to the Health Quarantine Administrative Department of the General Administration of Customs (China) and travel health-related departments.

CONCLUSIONS

The GIDEIMS is one of the most intelligent tools that contributes to safeguarding the health of travelers, controlling infectious disease epidemics, and effectively managing public health in China.

The same storm but not the same boat: Effects of COVID-19 stay-at-home order on mental health in individuals with overweight

OBJECTIVE

To describe the effects of stay-at-home orders and social distancing during the coronavirus disease (COVID-19) outbreak on mental health and to compare these outcomes between individuals with normal weight and overweight.

METHODS

This cross-sectional study included 1857 Brazilian adults, who were invited through social media to answer an online questionnaire from 5 May 2020 to 17 May 2020. The instrument included questions related to health behaviour, mental health (anxiety, depression, self-esteem, sadness and stress) and overall health. Overweight was defined as body mass index (BMI) ≥ 25 Kg/m² . Multiple logistic regression was conducted to identify whether overweight is associated with mental health variables.

RESULTS

Women reported increased anxiety (36.5% vs 22.2%, P < .01), depression (16.2% vs 8.8%, P < .01), low self-esteem (19.8% vs 10.6%, P < .01), sadness (17.7% vs 10.2%, P < .01), and stress (29.5% vs 19.3%, P < .01) relative to men. Women with overweight are more likely to report higher feeling of anxiety (OR 1.62, CI 95% 1.22-2.14), depression (OR 1.79, CI 95% 1.25-2.55), low self-esteem (OR 1.82, CI95% 1.28-2.58) and sadness (OR 1.51, CI 95% 1.08-2.10), adjusted for age, social isolation days, educational level, chronic diseases, smoke, alcohol intake and physical activity.

CONCLUSION

Women, specially those with overweight are more vulnerable to the deleterious effects of stay-at-home orders on mental health during the COVID-19 pandemic.

The prevalence of depressive and anxiety symptoms and their associations with quality of life among clinically stable older patients with psychiatric disorders during the COVID-19 pandemic

The impact of the COVID-19 pandemic on clinically stable older patients with psychiatric disorders is unclear. This study examined the prevalence of depressive and anxiety symptoms, and their associations with quality of life (QOL) in clinically stable older patients with psychiatric disorders during the COVID-19 pandemic. This was a multicenter, cross-sectional study. Depressive and anxiety symptoms, insomnia, pain, and QOL were assessed with standardized instruments. A total of 1063 patients were included. The prevalence of depressive and anxiety symptoms, and combined depressive and anxiety symptoms were 62.3% (95%CI = 59.4-65.2%), 52.4% (95%CI = 49.3-55.4%), and 45.9% (95%CI = 42.9-48.9%), respectively. Patients with depressive and anxiety symptoms had significantly lower QOL than those without (P < 0.01). Binary logistic regression analyses revealed that having depressive symptoms was positively associated with more severe insomnia (OR = 1.29, P < 0.01) and pain (OR = 1.14, P < 0.01), and was negatively associated with other psychiatric diagnoses (except for major depressive disorder, schizophrenia, and organic mental disorder; OR = 0.50, P < 0.01), while having anxiety symptoms was positively associated with severe physical diseases (OR = 1.57, P = 0.02), poor adherence to treatment (OR = 1.50, P < 0.01), and more severe insomnia (OR = 1.15, P < 0.01) and pain (OR = 1.11, P < 0.01). Having combined depression and anxiety symptoms was positively associated with poor adherence to treatment (OR = 1.42, P = 0.02) and more severe insomnia (OR = 1.19, P < 0.01) and pain (OR = 1.15, P < 0.01), and was negatively associated with the diagnosis of schizophrenia (OR = 0.50, P = 0.04) and others (OR = 0.53, P < 0.01). Depressive and anxiety symptoms were common in clinically stable older patients with psychiatric disorders during the COVID-19 pandemic. Considering the negative impact of these symptoms on QOL, regular screening and appropriate treatment are recommended for this population.

Fatigue and Its Association With Quality of Life Among Carers of Patients Attending Psychiatric Emergency Services During the COVID-19 Pandemic

Aims: Carers of psychiatric patients often suffered from mental and physical burden during the coronavirus disease 2019 (COVID-19) pandemic due to the lack of mental health services. This study investigated the pattern of fatigue and its association with quality of life (QOL) among the carers of patients attending psychiatric emergency services during the COVID-19 pandemic. Methods: In this cross-sectional study, carers of patients attending psychiatric emergency services during the COVID-19 pandemic were consecutively included. Fatigue, insomnia symptoms, depressive symptoms, and QOL were assessed with standardized instruments. Results: A total of 496 participants were included. The prevalence of fatigue was 44.0% (95% CI = 39.6-48.4%). Multivariate logistic regression analysis revealed that fatigue was positively associated with higher education level (OR = 1.92, P < 0.01) and more severe depressive (OR = 1.18, P < 0.01) and insomnia symptoms (OR = 1.11, P < 0.01). ANCOVA analysis revealed that the QOL was significantly lower in carers with fatigue compared with those without (P = 0.03). Conclusions: Fatigue was common among carers of patients attending psychiatric emergency services during the COVID-19 pandemic. Considering the adverse impact of fatigue on QOL and other health outcomes, routine screening and appropriate intervention for fatigue are warranted for this subpopulation.

Prioritizing COVID-19 tests based on participatory surveillance and spatial scanning

OBJECTIVES

This study aimed to identify, describe and analyze priority areas for COVID-19 testing combining participatory surveillance and traditional surveillance.

DESIGN

It was carried out a descriptive transversal study in the city of Caruaru, Pernambuco state, Brazil, within the period of 20/02/2020 to 05/05/2020. Data included all official reports for influenza-like illness notified by the municipality health department and the self-reports collected through the participatory surveillance platform Brasil Sem Corona.

METHODS

We used linear regression and loess regression to verify a correlation between Participatory Surveillance (PS) and Traditional Surveillance (TS). Also a spatial scanning approach was deployed in order to identify risk clusters for COVID-19.

RESULTS

In Caruaru, the PS had 861 active users, presenting an average of 1.2 reports per user per week. The platform Brasil Sem Corona started on March 20th and since then, has been officially used by the Caruaru health authority to improve the quality of information from the traditional surveillance system. Regarding the respiratory syndrome cases from TS, 1588 individuals were positive for this clinical outcome. The spatial scanning analysis detected 18 clusters and 6 of them presented statistical significance (p-value < 0.1). Clusters 3 and 4 presented an overlapping area that was chosen by the local authority to deploy the COVID-19 serology, where 50 individuals were tested. From there, 32 % (n = 16) presented reagent results for antibodies related to COVID-19.

CONCLUSION

Participatory surveillance is an effective epidemiological method to complement the traditional surveillance system in response to the COVID-19 pandemic by adding real-time spatial data to detect priority areas for COVID-19 testing.

Impact of the COVID-19 Pandemic on Consumers' Access to Essential Medicines in Nigeria

COVID-19 is a global pandemic which has seriously impacted the economy of nations. Access to essential medicines is of utmost importance. This study examined the impacts of the COVID-19 pandemic on the ease of access to essential medicines by end users. A cross-sectional survey using electronic questionnaires was conducted on study participants across the 36 states of Nigeria. They were assessed on sociodemographics, health characteristics, and challenges in accessing essential medicines during the COVID-19 pandemic. Data obtained were analyzed using the Statistical Package for the Social Sciences (SPSS version 20, IBM, Armonk, NY) with overall impact of the pandemic operationalized as < 60.0% or ≥ 60.0% access to essential medicines by respondents as maximal and minimal impact, respectively. The results showed that 35.2% of the respondents managing chronic illnesses had difficulties accessing essential medicines during the COVID-19 lockdown, with 84.0% experiencing deteriorating chronic health conditions in the light of difficulty in accessing their medicines. The proportion of respondents who sourced for orthodox medicines before COVID-19 lockdown (98.4%) was significantly (P < 0.05) higher than that of those who sourced for the same during the lockdown (89.0%). Increase in cost of medicines was observed by 77.7% of participants, with 73.9% of respondents living with chronic illness affirming that their income was negatively affected by the pandemic. The COVID-19 pandemic had minimal impact on consumers’ ability to access essential medicines. However, important challenges identified were poor availability of means of transportation, reduced income, and high cost of medicines, as well as fear of contracting the virus.

Epidemiological Parameters of COVID-19: Case Series Study

Background

The estimates of several key epidemiological parameters of the COVID-19 pandemic are often based on small sample sizes or are inaccurate for various reasons.

Objective

The aim of this study is to obtain more robust estimates of the incubation period, serial interval, frequency of presymptomatic transmission, and basic reproduction number (R₀) of COVID-19 based on a large case series.

Methods

We systematically retrieved and screened 20,658 reports of laboratory-confirmed COVID-19 cases released by the health authorities of China, Japan, and Singapore. In addition, 9942 publications were retrieved from PubMed and China National Knowledge Infrastructure (CNKI) through April 8, 2020. To be eligible, a report had to contain individual data that allowed for accurate estimation of at least one parameter. Widely used models such as gamma distributions were fitted to the data sets and the results with the best-fitting values were presented.

Results

In total, 1591 cases were included for the final analysis. The mean incubation period (n=687) and mean serial interval (n=1015 pairs) were estimated to be 7.04 (SD 4.27) days and 6.49 (SD 4.90) days, respectively. In 40 cases (5.82%), the incubation period was longer than 14 days. In 32 infector-infectee pairs (3.15%), infectees’ symptom onsets occurred before those of infectors. Presymptomatic transmission occurred in 129 of 296 infector-infectee pairs (43.58%). R₀ was estimated to be 1.85 (95% CI 1.37-2.60).

Conclusions

This study provides robust estimates of several epidemiological parameters of COVID-19. The findings support the current practice of 14-day quarantine of persons with potential exposure, but also suggest the need for additional measures. Presymptomatic transmission together with the asymptomatic transmission reported by previous studies highlight the importance of adequate testing, strict quarantine, and social distancing.

Self-Reported Symptoms of SARS-CoV-2 Infection in a Nonhospitalized Population in Italy: Cross-Sectional Study of the EPICOVID19 Web-Based Survey

BACKGROUND

Understanding the occurrence of symptoms resembling those of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a large nonhospitalized population at the peak of the epidemic in Italy is of paramount importance; however, data are currently scarce.

OBJECTIVE

The aims of this study were to evaluate the association of self-reported symptoms with SARS-CoV-2 nasopharyngeal swab (NPS) test results in nonhospitalized individuals and to estimate the occurrence of symptoms associated with coronavirus disease (COVID-19) in a larger nontested population.

METHODS

EPICOVID19 is a self-administered cross-sectional voluntary web-based survey of adults throughout Italy who completed an anonymous questionnaire in the period of April 13 to 21, 2020. The associations between symptoms potentially related to SARS-CoV-2 infection and NPS results were calculated as adjusted odds ratios (aORs) with 95% CIs by multiple logistic regression analysis controlling for age, sex, education, smoking habits, and number of comorbidities. Thereafter, for each symptom and for combinations of the symptoms, we calculated the sensitivity, specificity, accuracy, and areas under the curve (AUCs) in a receiver operating characteristic (ROC) analysis to estimate the occurrence of COVID-19-like infection in the nontested population.

RESULTS

A total of 171,310 people responded to the survey, of whom 102,543 (59.9%) were women; mean age 47.4 years. Out of the 4785 respondents with known NPS test results, 4392 were not hospitalized. Among the 4392 nonhospitalized respondents, those with positive NPS tests (856, 19.5%) most frequently reported myalgia (527, 61.6%), olfactory and taste disorders (507, 59.2%), cough (466, 54.4%), and fever (444, 51.9%), whereas 7.7% were asymptomatic. Multiple regression analysis showed that olfactory and taste disorders (aOR 10.3, 95% CI 8.4-12.7), fever (aOR 2.5, 95% CI 2.0-3.1), myalgia (aOR 1.5, 95% CI 1.2-1.8), and cough (aOR 1.3, 95% CI 1.0-1.6) were associated with NPS positivity. Having two to four of these symptoms increased the aOR from 7.4 (95% CI 5.6-9.7) to 35.5 (95% CI 24.6-52.2). The combination of the four symptoms showed an AUC of 0.810 (95% CI 0.795-0.825) in classifying positive NPS test results and then was applied to the nonhospitalized and nontested sample (n=165,782). We found that 7739 to 20,103 of these 165,782 respondents (4.4% to 12.1%) had experienced symptoms suggestive of COVID-19 infection.

CONCLUSIONS

Our results suggest that self-reported symptoms are reliable indicators of SARS-CoV-2 infection in a pandemic context. A nonnegligible number of symptomatic respondents (up to 12.1%) were undiagnosed and potentially contributed to the spread of the infection.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04471701; https://clinicaltrials.gov/ct2/show/NCT04471701.

[Coronavirus disease 2019 (COVID-19) and headaches]

Over the course of the new coronavirus infectious disease (coronavirus disease 2019; COVID-19) pandemic, our social situation has been changing dramatically, in addition to the substantial efforts made for the early and appropriate management of COVID-19 and preventing this infection spreading. Recently, neurological symptoms associated with COVID-19 have been shown to be not uncommon, with headaches receiving attention as one of the main neurological symptoms. The frequency of headaches associated with COVID-19 ranged from 5.6% to 70.3%, based on 21 clinical studies and 8 meta-analyses. However, headaches were observed in 11.1% to 81.0% of non-COVID-19 individuals, including healthcare workers caring for COVID-19 patients. Although detailed descriptions of headaches were rarely provided in the literature obtained, in this article, I wil discuss the frequency and characteristics of headaches, and the pathophysiology of headaches as it relateds to COVID-19.

Epidemiological Observations on the Association Between Anosmia and COVID-19 Infection: Analysis of Data From a Self-Assessment Web Application

BACKGROUND

We developed a self-assessment and participatory surveillance web application for coronavirus disease (COVID-19), which was launched in France in March 2020.

OBJECTIVE

Our objective was to determine if self-reported symptoms could help monitor the dynamics of the COVID-19 outbreak in France.

METHODS

Users were asked questions about underlying conditions, sociodemographic status, zip code, and COVID-19 symptoms. Depending on the symptoms reported and the presence of coexisting disorders, users were told to either stay at home, contact a general practitioner (GP), or call an emergency phone number. Data regarding COVID-19-related hospitalizations were retrieved from the Ministry of Health.

RESULTS

As of March 29, 2020, the application was opened 4,126,789 times; 3,799,535 electronic questionnaires were filled out; and 2,477,174 users had at least one symptom. In total, 34.8% (n=1,322,361) reported no symptoms. The remaining users were directed to self-monitoring (n=858,878, 22.6%), GP visit or teleconsultation (n=1,033,922, 27.2%), or an emergency phone call (n=584,374, 15.4%). Emergency warning signs were reported by 39.1% of participants with anosmia, a loss of the sense of smell (n=127,586) versus 22.7% of participants without anosmia (n=1,597,289). Anosmia and fever and/or cough were correlated with hospitalizations for COVID-19 (Spearman correlation coefficients=0.87 and 0.82, respectively; P<.001 for both).

CONCLUSIONS

This study suggests that anosmia may be strongly associated with COVID-19 and its severity. Despite a lack of medical assessment and virological confirmation, self-checking application data could be a relevant tool to monitor outbreak trends.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04331171; https://clinicaltrials.gov/ct2/show/NCT04331171.

No Place Like Home: Cross-National Data Analysis of the Efficacy of Social Distancing During the COVID-19 Pandemic

Background

In the absence of a cure in the time of a pandemic, social distancing measures seem to be the most effective intervention to slow the spread of disease. Various simulation-based studies have been conducted to investigate the effectiveness of these measures. While those studies unanimously confirm the mitigating effect of social distancing on disease spread, the reported effectiveness varies from 10% to more than 90% reduction in the number of infections. This level of uncertainty is mostly due to the complex dynamics of epidemics and their time-variant parameters. However, real transactional data can reduce uncertainty and provide a less noisy picture of the effectiveness of social distancing.

Objective

The aim of this paper was to integrate multiple transactional data sets (GPS mobility data from Google and Apple as well as disease statistics from the European Centre for Disease Prevention and Control) to study the role of social distancing policies in 26 countries and analyze the transmission rate of the coronavirus disease (COVID-19) pandemic over the course of 5 weeks.

Methods

Relying on the susceptible-infected-recovered (SIR) model and official COVID-19 reports, we first calculated the weekly transmission rate (β) of COVID-19 in 26 countries for 5 consecutive weeks. Then, we integrated these data with the Google and Apple mobility data sets for the same time frame and used a machine learning approach to investigate the relationship between the mobility factors and β values.

Results

Gradient boosted trees regression analysis showed that changes in mobility patterns resulting from social distancing policies explain approximately 47% of the variation in the disease transmission rates.

Conclusions

Consistent with simulation-based studies, real cross-national transactional data confirms the effectiveness of social distancing interventions in slowing the spread of COVID-19. In addition to providing less noisy and more generalizable support for the idea of social distancing, we provide specific insights for public health policy makers regarding locations that should be given higher priority for enforcing social distancing measures.