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
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
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
Unlike other wireless technologies, the deployment of 802.11 networks is not limited to operators: access points can easily be installed by end-users for domestic use. This singular type of deployment is the reason why 802.11 networks are omnipresent in our urban landscapes. Indeed, in metropolitan areas, laptops frequently detect tens of 802.11 access points from the same location. In this work, we describe both simple and more complex data about access points obtained in two Paris districts during an extensive experiment from August to October 2007. We introduce a lightweight scanning platform that runs on common smartphones. Using the obtained data, we examine various parameters: (1) SSID, (2) manufacturers, (3) security modes, (4) density, (5) data rates, and (6) channels utilization. For example, we show that in the two districts that we mapped as few as 7% of the Wi-Fi networks are not secured. Similarly, we provide a practical evidence that 90% of detected access points where installed along with DSL Internet access.
BACKGROUND Delay in diagnosis of neurodevelopment disorders (NDD) of toddlers and postnatal depression (PND) is a major public health issue. In both cases, early intervention is crucial. OBJECTIVE We aimed to assess if a digital product 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 one child under 3 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 application, assessing skills on sociability, hearing, vision, motricity and language of their infants and possible autism spectrum disorder. Mothers were also requested to answer regular questionnaires regarding PND, from 4 to 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 of possible NDD and the median time of PND notifications after childbirth. One secondary outcome was the relevance of the consultation after NDD notification as assessed by the physicians. RESULTS Among 4242 children assessable by 5309 questionnaires, 14.5% had at least one 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 neurodevelopmental disorders as assessed by physician was 100% and specificity was 73.5%. Among 907 mothers who completed a postnatal depression questionnaire, highly probable postnatal depression was detected in 16.6% of mothers and 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 early detection of PND. Our results suggests that regular use of this multidomain familial smartphone application would permit early detection of NDD and PND. CLINICALTRIAL ClinicalTrials.gov Identifier: NCT04958174
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