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

Epidemiology, clinical characteristics and risk factors of coronavirus disease 2019 (COVID-19) in Casablanca

This is an analytical cross-sectional study of coronavirus disease 2019 (COVID-19) based on data collected between 1 November 2020 and 31 March 2021 in Casablanca focusing on the disease's epidemiological status and risk factors. A total of 4569 samples were collected and analysed by reverse-transcription polymerase chain reaction (RT-PCR); 967 patients were positive, representing a prevalence of 21.2 % for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The mean age was 47.5±18 years, and infection was more common in young adults (<60 years). However, all age groups were at risk of COVID-19, and in terms of disease severity, the elderly were at greater risk because of potential underlying health problems. Among the clinical signs reported in this study, loss of taste and/or smell, fever, cough and fatigue were highly significant predictors of a positive COVID-19 test result (P<0.001). An assessment of the reported symptoms revealed that 27 % of COVID-19-positive patients (n=261) experienced loss of taste and/or smell, whereas only 2 % (n=72) of COVID-19-negative patients did (P<0.001). This result was consistent between univariate (OR=18.125) and multivariate (adjusted OR=10.484) logistic regression analyses, indicating that loss of taste and/or smell is associated with a more than 10-fold higher multivariate adjusted probability of a positive COVID-19 test (adjusted OR=10.48; P<0.001). Binary logistic regression model analysis based on clinical signs revealed that loss of taste and/or smell had a performance index of 0.846 with a P<0.001, confirming the diagnostic utility of this symptom for the prediction of COVID-19-positive status. In conclusion, symptom evaluation and a RT-PCR [taking into account cycle threshold (C t) values of the PCR proxy] test remain the most useful screening tools for diagnosing COVID-19. However, loss of taste/smell, fatigue, fever and cough remain the strongest independent predictors of a positive COVID-19 result.

A Digital First Healthcare Approach to Managing Pandemics: A Scoping Review of Pandemic Self-Triage Tools

BACKGROUND

During the COVID-19 pandemic, many patient-facing digital self-triage tools were designed and deployed to alleviate demand for pandemic virus triage in hospitals and doctors' offices by providing a way for people to self-assess health status and get advice on whether to seek care. These tools, provided via websites, apps, or patient portals allow people to answer questions, e.g., about symptoms and contact history, and receive guidance to appropriate care, which might be self-care.

OBJECTIVE

The purpose of this scoping review was to explore the state of literature on digital self-triage tools that direct or advise care for adults during a pandemic, and to explore what has been learned about intended purpose, use, and quality of guidance, tool usability, impact on providers, and ability to forecast health outcomes or care demand.

METHODS

A literature search was conducted in July 2021 using MEDLINE, Embase, Scopus, PsycINFO, CINAHL and Cochrane databases. Using Covidence, 1227 titles and abstracts were screened by two researchers, with 83 reviewed via full text screening. 22 articles met inclusion criteria: they allowed adults to self-assess for pandemic virus and directed to care. Using Microsoft Excel, we extracted and charted the following data: authors, publication year and country, country the tool was used in, whether the tool was integrated into a healthcare system, research question/purpose, direction of care provided, and key findings.

RESULTS

All but two studies reported on tools developed since early 2020 during the COVID-19 pandemic. Studies reported on tools were developed in 17 countries. Direction of care advice included directing to an ER, seek urgent care, contact/see a doctor, be tested, or to stay at home/self-isolate. Only two studies evaluated tool usability. One used 52 use-cases to evaluate quality of advice by tools in four countries, finding advice varied, e.g., tools in the US and UK often advising staying home when clinical assessment was warranted, while tools in Japan and Singapore advised seeking care. No study demonstrated that the tools reduce demand on the health care system, although at least one suggests data can predict demand for care and data allows monitoring public health.

CONCLUSIONS

While self-triage tools developed and used around the world have similarities in directing to care (ER, physician, self-care), they also differ in important ways. Some collect data to predict healthcare demand. Some are for use when concerned about health status; others are intended to be used repeatedly by users to monitor public health. Quality of triage may vary. The high use of such tools during the COVID-19 pandemic suggests research is needed to assess and ensure quality of advice given by self-triage tools, and to assess intended or unintended consequences on public health and health care systems.

CLINICALTRIAL

Self-care for coronavirus disease through electronic health technologies: A scoping review

Background and Aims

Considering the rapid spread and transmission of COVID-19 and its high mortality rate, self-care practices are of special importance during this pandemic to prevent and control the spread of the virus. In this regard, electronic health systems can play a major role in improving self-care practices related to coronavirus disease. This study aimed to review the electronic health technologies used in each of the constituent elements of the self-care (self-care maintenance, self-care monitoring, and self-care management) during the COVID-19 pandemic.

Methods

This scoping review was conducted based on Arksey and O'Malley's framework. In this study, the specific keywords related to "electronic health," "self-care," and "COVID-19" were searched on PubMed, Web of Science, Scopus, and Google.

Results

Of the 47 articles reviewed, most articles (27 articles) were about self-care monitoring and aimed to monitor the vital signs of patients. The results showed that the use of electronic health tools mainly focuses on training in the control and prevention of coronavirus disease during this pandemic, in the field of self-care maintenance, and medication management, communication, and consultation with healthcare providers, in the field of self-care management. Moreover, the most commonly used electronic health technologies were mobile web applications, smart vital signs monitoring devices, and social networks, respectively.

Conclusion

The study findings suggested that the use of electronic health technologies, such as mobile web applications and social networks, can effectively improve self-care practices for coronavirus disease. In addition, such technologies can be applied by health policymakers and disease control and prevention centers to better manage the COVID-19 pandemic.

Early Detection of Neurodevelopmental Disorders of Toddlers and Postnatal Depression by Mobile Health App: Observational Cross-sectional Study

Background

Delays in the diagnosis of neurodevelopmental disorders (NDDs) in toddlers and postnatal depression (PND) in mothers are major public health issues. In both cases, early intervention is crucial.

Objective

We aimed to assess if a mobile app named Malo can reduce delay in the recognition of NDD and PND.

Methods

We performed an observational, cross-sectional, data-based study in a population of young parents with a minimum of 1 child under 3 years of age at the time of inclusion and using Malo on a regular basis. We included the first 4000 users matching the criteria and agreeing to participate between November 11, 2021, and January 14, 2022. Parents received monthly questionnaires via the app, assessing skills on sociability, hearing, vision, motricity, language of their infants, and possible autism spectrum disorder. Mothers were also requested to answer regular questionnaires regarding PND, from 4-28 weeks after childbirth. When any patient-reported outcomes matched predefined criteria, an in-app notification was sent to the user, recommending the booking of an appointment with their family physician or pediatrician. The main outcomes were the median age of the infant at the time of notification for possible NDD and the median time of PND notifications after childbirth. One secondary outcome was the relevance of the NDD notification for a consultation as assessed by the physicians.

Results

Among 4242 children assessed by 5309 questionnaires, 613 (14.5%) had at least 1 disorder requiring a consultation. The median age of notification for possible autism spectrum, vision, audition, socialization, language, or motor disorders was 11, 9, 17, 12, 22, and 4 months, respectively. The sensitivity of the alert notifications of suspected NDDs as assessed by the physicians was 100%, and the specificity was 73.5%. Among 907 mothers who completed a PND questionnaire, highly probable PND was detected in 151 (16.6%) mothers, and the median time of detection was 8-12 weeks.

Conclusions

The algorithm-based alert suggesting NDD was highly sensitive with good specificity as assessed by real-life practitioners. The app was also efficient in the early detection of PND. Our results suggest that the regular use of this multidomain familial smartphone app would permit the early detection of NDD and PND.

Trial Registration

ClinicalTrials.gov NCT04958174; https://clinicaltrials.gov/ct2/show/NCT04958174

Assessing a new pre-screening score for the simplified evaluation of the clinical quality and relevance of e-health applications. (Preprint)

Background

In 2020, more than 250 eHealth solutions were added to app stores each day, or 90,000 in the year; however, the vast majority of these solutions have not undergone clinical validation, their quality is unknown, and the user does not know if they are effective and safe. We sought to develop a simple prescreening scoring method that would assess the quality and clinical relevance of each app. We designed this tool with 3 health care stakeholder groups in mind: eHealth solution designers seeking to evaluate a potential competitor or their own tool, investors considering a fundraising candidate, and a hospital clinician or IT department wishing to evaluate a current or potential eHealth solution.

Objective

We built and tested a novel prescreening scoring tool (the Medical Digital Solution scoring tool). The tool, which consists of 26 questions that enable the quick assessment and comparison of the clinical relevance and quality of eHealth apps, was tested on 68 eHealth solutions.

Methods

The Medical Digital Solution scoring tool is based on the 2021 evaluation criteria of the French National Health Authority, the 2022 European Society of Medical Oncology recommendations, and other provided scores. We built the scoring tool with patient association and eHealth experts and submitted it to eHealth app creators, who evaluated their apps via the web-based form in January 2022. After completing the evaluation criteria, their apps obtained an overall score and 4 categories of subscores. These criteria evaluated the type of solution and domain, the solution’s targeted population size, the level of clinical assessment, and information about the provider.

Results

In total, 68 eHealth solutions were evaluated with the scoring tool. Oncology apps (22%, 20/90) and general health solutions (23%, 21/90) were the most represented. Of the 68 apps, 32 (47%) were involved in remote monitoring by health professionals. Regarding clinical outcomes, 5% (9/169) of the apps assessed overall survival. Randomized studies had been conducted for 21% (23/110) of the apps to assess their benefit. Of the 68 providers, 38 (56%) declared the objective of obtaining reimbursement, and 7 (18%) out of the 38 solutions seeking reimbursement were assessed as having a high probability of reimbursement. The median global score was 11.2 (range 4.7-17.4) out of 20 and the distribution of the scores followed a normal distribution pattern (Shapiro-Wilk test: P=.33).

Conclusions

This multidomain prescreening scoring tool is simple, fast, and can be deployed on a large scale to initiate an assessment of the clinical relevance and quality of a clinical eHealth app. This simple tool can help a decision-maker determine which aspects of the app require further analysis and improvement.

App-based COVID-19 syndromic surveillance and prediction of hospital admissions in COVID Symptom Study Sweden

The app-based COVID Symptom Study was launched in Sweden in April 2020 to contribute to real-time COVID-19 surveillance. We enrolled 143,531 study participants (≥18 years) who contributed 10.6 million daily symptom reports between April 29, 2020 and February 10, 2021. Here, we include data from 19,161 self-reported PCR tests to create a symptom-based model to estimate the individual probability of symptomatic COVID-19, with an AUC of 0.78 (95% CI 0.74–0.83) in an external dataset. These individual probabilities are employed to estimate daily regional COVID-19 prevalence, which are in turn used together with current hospital data to predict next week COVID-19 hospital admissions. We show that this hospital prediction model demonstrates a lower median absolute percentage error (MdAPE: 25.9%) across the five most populated regions in Sweden during the first pandemic wave than a model based on case notifications (MdAPE: 30.3%). During the second wave, the error rates are similar. When we apply the same model to an English dataset, not including local COVID-19 test data, we observe MdAPEs of 22.3% and 19.0% during the first and second pandemic waves, respectively, highlighting the transferability of the prediction model.

The app-based COVID Symptom Study was launched in Sweden in April 2020 to contribute to real-time COVID-19 surveillance using daily symptom reports from study participants. Here, the authors show how syndromic surveillance can be used to estimate regional COVID-19 prevalence and to predict later COVID-19 hospital admissions.

Nowcasting (Short-Term Forecasting) of COVID-19 Hospitalizations Using Syndromic Healthcare Data, Sweden, 2020

We report on local nowcasting (short-term forecasting) of coronavirus disease (COVID-19) hospitalizations based on syndromic (symptom) data recorded in regular healthcare routines in Östergötland County (population ≈465,000), Sweden, early in the pandemic, when broad laboratory testing was unavailable. Daily nowcasts were supplied to the local healthcare management based on analyses of the time lag between telenursing calls with the chief complaints (cough by adult or fever by adult) and COVID-19 hospitalization. The complaint cough by adult showed satisfactory performance (Pearson correlation coefficient r>0.80; mean absolute percentage error <20%) in nowcasting the incidence of daily COVID-19 hospitalizations 14 days in advance until the incidence decreased to <1.5/100,000 population, whereas the corresponding performance for fever by adult was unsatisfactory. Our results support local nowcasting of hospitalizations on the basis of symptom data recorded in routine healthcare during the initial stage of a pandemic.

Towards a COVID-19 symptom triad: The importance of symptom constellations in the SARS-CoV-2 pandemic

Pandemic scenarios like SARS-Cov-2 require rapid information aggregation. In the age of eHealth and data-driven medicine, publicly available symptom tracking tools offer efficient and scalable means of collecting and analyzing large amounts of data. As a result, information gains can be communicated to front-line providers. We have developed such an application in less than a month and reached more than 500 thousand users within 48 hours. The dataset contains information on basic epidemiological parameters, symptoms, risk factors and details on previous exposure to a COVID-19 patient. Exploratory Data Analysis revealed different symptoms reported by users with confirmed contacts vs. no confirmed contacts. The symptom combination of anosmia, cough and fatigue was the most important feature to differentiate the groups, while single symptoms such as anosmia, cough or fatigue alone were not sufficient. A linear regression model from the literature using the same symptom combination as features was applied on all data. Predictions matched the regional distribution of confirmed cases closely across Germany, while also indicating that the number of cases in northern federal states might be higher than officially reported. In conclusion, we report that symptom combinations anosmia, fatigue and cough are most likely to indicate an acute SARS-CoV-2 infection.

Manifestations and mechanisms of central nervous system damage caused by SARS-CoV-2

The global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its threat to humans have drawn worldwide attention. The acute and long-term effects of SARS-CoV-2 on the nervous system pose major public health challenges. Patients with SARS-CoV-2 present diverse symptoms of the central nervous system. Exploring the mechanism of coronavirus damage to the nervous system is essential for reducing the long-term neurological complications of COVID-19. Despite rapid progress in characterizing SARS-CoV-2, the long-term effects of COVID-19 on the brain remain unclear. The possible mechanisms of SARS-CoV-2 injury to the central nervous system include: 1) direct injury of nerve cells, 2) activation of the immune system and inflammatory cytokines caused by systemic infection, 3) a high affinity of the SARS-CoV-2 spike glycoprotein for the angiotensin-converting enzyme ACE2, 4) cerebrovascular disease caused by hypoxia and coagulation dysfunction, and 5) a systemic inflammatory response that promotes cognitive impairment and neurodegenerative diseases. Although we do not fully understand the mechanism by which SARS-CoV-2 causes nerve injury, we hope to provide a framework by reviewing the clinical manifestations, complications, and possible mechanisms of neurological damage caused by SARS-CoV-2. With hope, this will facilitate the early identification, diagnosis, and treatment of possible neurological sequelae, which could contribute toward improving patient prognosis and preventing transmission.

Olfactory Training and Visual Stimulation Assisted by a Web Application for Patients With Persistent Olfactory Dysfunction After SARS-CoV-2 Infection: Observational Study

Background

Persistent olfactory dysfunction is a significant complication of SARS-CoV-2 infection. Olfactory training involving aromatic oils has been recommended to improve olfactory recovery, but quantitative data are missing.

Objective

We aimed to quantify the benefit of olfactory training and visual stimulation assisted by a dedicated web application for patients who experienced olfactory dysfunction for ≥1 month.

Methods

We performed an observational, real-life, data-based study on a cohort of patients who experienced at least 1 month of persistent olfactory dysfunction between January 30 and March 26, 2021. An analysis was performed after a mean olfactory training time of 4 weeks, and at least 500 patients were assessable for primary outcome assessment. Participants exposed themselves twice daily to odors from 4 high-concentration oils and visual stimulation assisted by a dedicated web application. Improvement was defined as a 2-point increase on a 10-point, self-assessed olfactory visual analogue scale.

Results

In total, 548 patients were assessable for primary outcome assessment. The mean baseline, self-assessed olfactory score was 1.9 (SD 1.7), and this increased to 4.6 (SD 2.8) after a mean olfactory training time of 27.7 days (SD 17.2). Olfactory training was associated with at least a 2-point increase in 64.2% (352/548) of patients. The rate of patients’ olfactory improvement was higher for patients who trained for more than 28 days than that rate for patients who trained for less than 28 days (73.3% vs 59%; P=.002). The time to olfactory improvement was 8 days faster for patients with hyposmia compared to the time to improvement for patients with anosmia (P<.001). This benefit was observed regardless of the duration of the olfactory dysfunction.

Conclusions

Olfactory training and visual stimulation assisted by a dedicated web application was associated with significant improvement in olfaction, especially after 28 days of olfactory training.

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.

Analysis of COVID-19 Transmission Sources in France by Self-Assessment Before and After the Partial Lockdown: Observational Study

Background

We developed a questionnaire on a web application for analyzing COVID-19 contamination circumstances in France during the second wave of the pandemic.

Objective

This study aims to analyze the impact on contamination characteristics before and after the second partial lockdown in France to adapt public health restrictions to further prevent pandemic surges.

Methods

Between December 15 and 24, 2020, after a national media campaign, users of the sourcecovid.fr web application were asked questions about their own or a close relative’s COVID-19 contamination after August 15, 2020, in France. The data of the contamination’s circumstances were assessed and compared before and after the second partial lockdown, which occurred on October 25, 2020, during the second wave of the pandemic and was ongoing on December 24, 2020.

Results

As of December 24, 2020, 441,000 connections on the web application were observed. A total of 2218 questionnaires were assessable for analysis. About 61.8% (n=1309) of the participants were sure of their contamination origin, and 38.2% (n=809) thought they knew it. The median age of users was 43.0 (IQR 32-56) years, and 50.7% (n=1073) were male. The median incubation time of the assessed cohort was 4.0 (IQR 3-5) days. Private areas (family’s or friend’s house) were the main source of contamination (1048/2090, 50.2%), followed by work colleagues (579/2090, 27.7%). The main time of day for the contamination was the evening (339/961, 35.3%) before the lockdown and was reduced to 18.2% (86/473) after the lockdown (P<.001). The person who transmitted the virus to the user before and after the lockdown was significantly different (P<.001): a friend (382/1317, 29% vs 109/773, 14.1%), a close relative (304/1317, 23.1% vs 253/773, 32.7%), or a work colleague (315/1317, 23.9% vs 264/773, 34.2%). The main location where the virus was transmitted to the users before and after the lockdown was significantly different too (P<.001): home (278/1305, 21.3% vs 194/760, 25.5%), work (293/1305, 22.5% vs 225/760, 29.6%), collective places (430/1305, 33% vs 114/760, 15%), and care centers (58/1305, 4.4% vs 74/760, 9.7%).

Conclusions

Modalities of transmissions significantly changed before and after the second lockdown in France. The main sources of contamination remained the private areas and with work colleagues. Work became the main location of contamination after the lockdown, whereas contaminations in collective places were strongly reduced.

Trial Registration

ClinicalTrials.gov NCT04670003; https://clinicaltrials.gov/ct2/show/NCT04670003

ConVid - Behavior Survey by the Internet during the COVID-19 pandemic in Brazil: conception and application methodology

The ConVid - Behavior Survey was conducted in Brazil from April 24 to May 24, 2020, aiming to investigate changes in lifestyles and health conditions during the COVID-19 pandemic. In this article, we present the conception and methodology of the research. We used a cross-sectional study using an Internet questionnaire, with questions validated in previous health surveys. The sampling method "virtual snowball" was used, as well as post-stratification procedures. The results related to chronic non-communicable diseases and pre-pandemic lifestyles were compared with estimates from the 2013 Brazilian National Health Survey and 2019 Surveillance of Risk and Protective Factors for Chronic Diseases by Telephone Survey. The total sample was 45,161 people. After data weighing, the sample distributions of demographic variables were similar to population variables. Only people with a low schooling level were underrepresented. The comparison with the previous results showed similarity in most estimates: recommended consumption of fruits and vegetables (22.1%), recommended physical activity (35.2%), tobacco smoking habit (12.3%), frequent and abusive alcohol consumption (6.7%), obesity (21.2%), self-reported prevalence of hypertension (18.6%), diabetes (7.1%), and heart disease (4.4%). The online survey made it possible to know the population's health conditions during the pandemic. The similarity of the indicators with those obtained in traditional research allowed the validation of the mean estimates. Studies are needed to investigate how the endogenous effects of virtual social networks can be considered when estimating variance.

Symptoms and symptom clusters associated with SARS-CoV-2 infection in community-based populations: Results from a statewide epidemiological study

Background

Prior studies examining symptoms of COVID-19 are primarily descriptive and measured among hospitalized individuals. Understanding symptoms of SARS-CoV-2 infection in pre-clinical, community-based populations may improve clinical screening, particularly during flu season. We sought to identify key symptoms and symptom combinations in a community-based population using robust methods.

Methods

We pooled community-based cohorts of individuals aged 12 and older screened for SARS-CoV-2 infection in April and June 2020 for a statewide prevalence study. Main outcome was SARS-CoV-2 positivity. We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for individual symptoms as well as symptom combinations. We further employed multivariable logistic regression and exploratory factor analysis (EFA) to examine symptoms and combinations associated with SARS-CoV-2 infection.

Results

Among 8214 individuals screened, 368 individuals (4.5%) were RT-PCR positive for SARS-CoV-2. Although two-thirds of symptoms were highly specific (>90.0%), most symptoms individually possessed a PPV <50.0%. The individual symptoms most greatly associated with SARS-CoV-2 positivity were fever (OR = 5.34, p<0.001), anosmia (OR = 4.08, p<0.001), ageusia (OR = 2.38, p = 0.006), and cough (OR = 2.86, p<0.001). Results from EFA identified two primary symptom clusters most associated with SARS-CoV-2 infection: (1) ageusia, anosmia, and fever; and (2) shortness of breath, cough, and chest pain. Moreover, being non-white (13.6% vs. 2.3%, p<0.001), Hispanic (27.9% vs. 2.5%, p<0.001), or living in an Urban area (5.4% vs. 3.8%, p<0.001) was associated with infection.

Conclusions

Symptoms can help distinguish SARS-CoV-2 infection from other respiratory viruses, especially in community or urgent care settings where rapid testing may be limited. Symptoms should further be structured in clinical documentation to support identification of new cases and mitigation of disease spread by public health. These symptoms, derived from asymptomatic as well as mildly infected individuals, can also inform vaccine and therapeutic clinical trials.

A Self-Assessment Web-Based App to Assess Trends of the COVID-19 Pandemic in France: Observational Study

Background

We developed a self-assessment and participatory web-based triage app to assess the trends of the COVID-19 pandemic in France in March 2020.

Objective

We compared daily large-scale RT–PCR test results to monitor recent reports of anosmia through a web-based app to assess the dynamics of emergency department visits, hospitalizations, and intensive care unit (ICU) admissions among individuals with COVID-19 in France.

Methods

Between March 21 and November 18, 2020, users of the maladiecoronavirus.fr self-triage app were asked questions about COVID-19 symptoms. Data on daily hospitalizations, large-scale positive results on RT–PCR tests, emergency department visits, and ICU admission of individuals with COVID-19 were compared to data on daily reports of anosmia on the app.

Results

As of November 18, 2020, recent anosmia was reported 575,214 times from among approximately 13,000,000 responses. Daily anosmia reports during peak engagement with the app on September 16, 2020, were spatially correlated with the peak in daily COVID-19–related hospitalizations in November 2020 (Spearman rank correlation coefficient [ρ]=0.77; P<.001). This peak in daily anosmia reports was observed primarily among young adults (age range 18-40 years), being observed 49 days before the peak of hospitalizations that corresponded to the first wave of infections among the young population, followed by a peak in hospitalizations among older individuals (aged ≥50 years) in November 2020. The reduction in the daily reports of anosmia associated with the peaks in the number of cases preceded the reduction in daily hospitalizations by 10 and 9 days during the first and the second waves of infection, respectively, although the reduction in the positivity rates on RT–PCR tests preceded the reduction in daily hospitalizations by only 2 days during the second wave of infections.

Conclusions

Data on daily reports of anosmia collected through a nationwide, web-based self-assessment app can be a relevant tool to anticipate surges in outbreaks, hospitalizations, and ICU admission during the COVID-19 pandemic.

Trial Registration

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

Anosmia and dysgeusia in SARS-CoV-2 infection: incidence and effects on COVID-19 severity and mortality, and the possible pathobiology mechanisms - a systematic review and meta-analysis

Background: The present study aimed to determine the global prevalence of anosmia and dysgeusia in coronavirus disease 2019 (COVID-19) patients and to assess their association with severity and mortality of COVID-19. Moreover, this study aimed to discuss the possible pathobiological mechanisms of anosmia and dysgeusia in COVID-19. Methods: Available articles from PubMed, Scopus, Web of Science, and preprint databases (MedRxiv, BioRxiv, and Researchsquare) were searched on November 10th, 2020. Data on the characteristics of the study (anosmia, dysgeusia, and COVID-19) were extracted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. Newcastle-Ottawa scale was used to assess research quality. Moreover, the pooled prevalence of anosmia and dysgeusia were calculated, and the association between anosmia and dysgeusia in presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was assessed using the Z test. Results: Out of 32,142 COVID-19 patients from 107 studies, anosmia was reported in 12,038 patients with a prevalence of 38.2% (95% CI: 36.5%, 47.2%); whereas, dysgeusia was reported in 11,337 patients out of 30,901 COVID-19 patients from 101 studies, with prevalence of 36.6% (95% CI: 35.2%, 45.2%), worldwide. Furthermore, the prevalence of anosmia was 10.2-fold higher (OR: 10.21; 95% CI: 6.53, 15.96, p < 0.001) and that of dysgeusia was 8.6-fold higher (OR: 8.61; 95% CI: 5.26, 14.11, p < 0.001) in COVID-19 patients compared to those with other respiratory infections or COVID-19 like illness. To date, no study has assessed the association of anosmia and dysgeusia with severity and mortality of COVID-19. Conclusion: Anosmia and dysgeusia are prevalent in COVID-19 patients compared to those with the other non-COVID-19 respiratory infections. Several possible mechanisms have been hypothesized; however, future studies are warranted to elucidate the definitive mechanisms of anosmia and dysgeusia in COVID-19. Protocol registration: PROSPERO CRD42020223204.

Implementation of a Self-Triage Web Application for Suspected COVID-19 and Its Impact on Emergency Call Centers: Observational Study

Background

We developed a self-triage web application for COVID-19 symptoms, which was launched in France in March 2020, when French health authorities recommended all patients with suspected COVID-19 call an emergency phone number.

Objective

Our objective was to determine if a self-triage tool could reduce the burden on emergency call centers and help predict increasing burden on hospitals.

Methods

Users were asked questions about their underlying conditions, sociodemographic status, postal code, and main COVID-19 symptoms. Participants were advised to call an emergency call center if they reported dyspnea or complete loss of appetite for over 24 hours. Data on COVID-19–related calls were collected from 6 emergency call centers and data on COVID-19 hospitalizations were collected from Santé Publique France and the French Ministry of Health. We examined the change in the number of emergency calls before and after the launch of the web application.

Results

From March 17 to April 2, 2020, 735,419 questionnaires were registered in the study area. Of these, 121,370 (16.5%) led to a recommendation to call an emergency center. The peak number of overall questionnaires and of questionnaires leading to a recommendation to call an emergency center were observed on March 22, 2020. In the 17 days preceding the launch of the web application, emergency call centers in the study area registered 66,925 COVID-19–related calls and local hospitals admitted 639 patients for COVID-19; the ratio of emergency calls to hospitalizations for COVID-19 was 104.7 to 1. In the 17 days following the launch of the web application, there were 82,347 emergency calls and 6009 new hospitalizations for COVID-19, a ratio of 13.7 calls to 1 hospitalization (chi-square test: P<.001).

Conclusions

The self-triage web application launch was followed by a nearly 10-fold increase in COVID-19–related hospitalizations with only a 23% increase in emergency calls. The peak of questionnaire completions preceded the peak of COVID-19–related hospitalizations by 5 days. Although the design of this study does not allow us to conclude that the self-triage tool alone contributed to the alleviation of calls to the emergency call centers, it does suggest that it played a role, and may be used for predicting increasing burden on hospitals.

Trial Registration

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

Symptoms and symptom clusters associated with SARS-CoV-2 infection in community-based populations: Results from a statewide epidemiological study

Background:

Prior studies examining symptoms of COVID-19 are primarily descriptive and measured among hospitalized individuals. Understanding symptoms of SARS-CoV-2 infection in pre-clinical, community-based populations may improve clinical screening, particularly during flu season. We sought to identify key symptoms and symptom combinations in a community-based population using robust methods.

Methods:

We pooled community-based cohorts of individuals aged 12 and older screened for SARS-CoV-2 infection in April and June 2020 for a statewide seroprevalence study. Main outcome was SARS-CoV-2 positivity. We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for individual symptoms as well as symptom combinations. We further employed multivariable logistic regression and exploratory factor analysis (EFA) to examine symptoms and combinations associated with SARS-CoV-2 infection.

Results:

Among 8214 individuals screened, 368 individuals (4.5%) were RT-PCR positive for SARS-CoV-2. Although two-thirds of symptoms were highly specific (>90.0%), most symptoms individually possessed a PPV <50.0%. The individual symptoms most greatly associated with SARS-CoV-2 positivity were fever (OR=5.34, p<0.001), anosmia (OR=4.08, p<0.001), ageusia (OR=2.38, p=0.006), and cough (OR=2.86, p<0.001). Results from EFA identified two primary symptom clusters most associated with SARS-CoV-2 infection: (1) ageusia, anosmia, and fever; and (2) shortness of breath, cough, and chest pain. Moreover, being non-white (13.6% vs. 2.3%, p<0.001), Hispanic (27.9% vs. 2.5%, p<0.001), or living in an Urban area (5.4% vs. 3.8%, p<0.001) was associated with infection.

Conclusions:

Symptoms can help distinguish SARS-CoV-2 infection from other respiratory viruses, especially in community or urgent care settings where rapid testing may be limited. Symptoms should further be structured in clinical documentation to support identification of new cases and mitigation of disease spread by public health. These symptoms, derived from asymptomatic as well as mildly infected individuals, can also inform vaccine and therapeutic clinical trials.

Syndromic Surveillance Insights from a Symptom Assessment App Before and During COVID-19 Measures in Germany and the United Kingdom: Results From Repeated Cross-Sectional Analyses

Background

Unprecedented lockdown measures have been introduced in countries worldwide to mitigate the spread and consequences of COVID-19. Although attention has been focused on the effects of these measures on epidemiological indicators relating directly to the infection, there is increased recognition of their broader health implications. However, assessing these implications in real time is a challenge, due to the limitations of existing syndromic surveillance data and tools.

Objective

The aim of this study is to explore the added value of mobile phone app–based symptom assessment tools as real-time health insight providers to inform public health policy makers.

Methods

A comparative and descriptive analysis of the proportion of all self-reported symptoms entered by users during an assessment within the Ada app in Germany and the United Kingdom was conducted between two periods, namely before and after the implementation of “Phase One” COVID-19 measures. Additional analyses were performed to explore the association between symptom trends and seasonality, and symptom trends and weather. Differences in the proportion of unique symptoms between the periods were analyzed using a Pearson chi-square test and reported as log2 fold changes.

Results

Overall, 48,300-54,900 symptomatic users reported 140,500-170,400 symptoms during the Baseline and Measures periods in Germany. Overall, 34,200-37,400 symptomatic users in the United Kingdom reported 112,100-131,900 symptoms during the Baseline and Measures periods. The majority of symptomatic users were female (Germany: 68,600/103,200, 66.52%; United Kingdom: 51,200/71,600, 72.74%). The majority were aged 10-29 years (Germany: 68,500/100,000, 68.45%; United Kingdom: 50,900/68,800, 73.91%), and about one-quarter were aged 30-59 years (Germany: 26,200/100,000, 26.15%; United Kingdom: 14,900/68,800, 21.65%). Overall, 103 symptoms were reported either more or less frequently (with statistically significant differences) during the Measures period as compared to the Baseline period, and 34 of these were reported in both countries. The following mental health symptoms (log2 fold change, P value) were reported less often during the Measures period: inability to manage constant stress and demands at work (–1.07, P<.001), memory difficulty (–0.56, P<.001), depressed mood (–0.42, P<.001), and impaired concentration (–0.46, P<.001). Diminished sense of taste (2.26, P<.001) and hyposmia (2.20, P<.001) were reported more frequently during the Measures period. None of the 34 symptoms were found to be different between the same dates in 2019. In total, 14 of the 34 symptoms had statistically significant associations with weather variables.

Conclusions

Symptom assessment apps have an important role to play in facilitating improved understanding of the implications of public health policies such as COVID-19 lockdown measures. Not only do they provide the means to complement and cross-validate hypotheses based on data collected through more traditional channels, they can also generate novel insights through a real-time syndromic surveillance system.

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.