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3.
MMWR Morb Mortal Wkly Rep ; 71(13): 489-494, 2022 Apr 01.
Article in English | MEDLINE | ID: covidwho-1771890

ABSTRACT

COVID-19 testing provides information regarding exposure and transmission risks, guides preventative measures (e.g., if and when to start and end isolation and quarantine), identifies opportunities for appropriate treatments, and helps assess disease prevalence (1). At-home rapid COVID-19 antigen tests (at-home tests) are a convenient and accessible alternative to laboratory-based diagnostic nucleic acid amplification tests (NAATs) for SARS-CoV-2, the virus that causes COVID-19 (2-4). With the emergence of the SARS-CoV-2 B.1.617.2 (Delta) and B.1.1.529 (Omicron) variants in 2021, demand for at-home tests increased† (5). At-home tests are commonly used for school- or employer-mandated testing and for confirmation of SARS-CoV-2 infection in a COVID-19-like illness or following exposure (6). Mandated COVID-19 reporting requirements omit at-home tests, and there are no standard processes for test takers or manufacturers to share results with appropriate health officials (2). Therefore, with increased COVID-19 at-home test use, laboratory-based reporting systems might increasingly underreport the actual incidence of infection. Data from a cross-sectional, nonprobability-based online survey (August 23, 2021-March 12, 2022) of U.S. adults aged ≥18 years were used to estimate self-reported at-home test use over time, and by demographic characteristics, geography, symptoms/syndromes, and reasons for testing. From the Delta-predominant period (August 23-December 11, 2021) to the Omicron-predominant period (December 19, 2021-March 12, 2022)§ (7), at-home test use among respondents with self-reported COVID-19-like illness¶ more than tripled from 5.7% to 20.1%. The two most commonly reported reasons for testing among persons who used an at-home test were COVID-19 exposure (39.4%) and COVID-19-like symptoms (28.9%). At-home test use differed by race (e.g., self-identified as White [5.9%] versus self-identified as Black [2.8%]), age (adults aged 30-39 years [6.4%] versus adults aged ≥75 years [3.6%]), household income (>$150,000 [9.5%] versus $50,000-$74,999 [4.7%]), education (postgraduate degree [8.4%] versus high school or less [3.5%]), and geography (New England division [9.6%] versus West South Central division [3.7%]). COVID-19 testing, including at-home tests, along with prevention measures, such as quarantine and isolation when warranted, wearing a well-fitted mask when recommended after a positive test or known exposure, and staying up to date with vaccination,** can help reduce the spread of COVID-19. Further, providing reliable and low-cost or free at-home test kits to underserved populations with otherwise limited access to COVID-19 testing could assist with continued prevention efforts.


Subject(s)
COVID-19 , Adolescent , Adult , Aged , COVID-19/diagnosis , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Testing , Cross-Sectional Studies , Humans , SARS-CoV-2 , United States/epidemiology
4.
Nat Commun ; 13(1): 636, 2022 02 01.
Article in English | MEDLINE | ID: covidwho-1671552

ABSTRACT

Worldwide, racial and ethnic minorities have been disproportionately impacted by COVID-19 with increased risk of infection, its related complications, and death. In the initial phase of population-based vaccination in the United States (U.S.) and United Kingdom (U.K.), vaccine hesitancy may result in differences in uptake. We performed a cohort study among U.S. and U.K. participants who volunteered to take part in the smartphone-based COVID Symptom Study (March 2020-February 2021) and used logistic regression to estimate odds ratios of vaccine hesitancy and uptake. In the U.S. (n = 87,388), compared to white participants, vaccine hesitancy was greater for Black and Hispanic participants and those reporting more than one or other race. In the U.K. (n = 1,254,294), racial and ethnic minority participants showed similar levels of vaccine hesitancy to the U.S. However, associations between participant race and ethnicity and levels of vaccine uptake were observed to be different in the U.S. and the U.K. studies. Among U.S. participants, vaccine uptake was significantly lower among Black participants, which persisted among participants that self-reported being vaccine-willing. In contrast, statistically significant racial and ethnic disparities in vaccine uptake were not observed in the U.K sample. In this study of self-reported vaccine hesitancy and uptake, lower levels of vaccine uptake in Black participants in the U.S. during the initial vaccine rollout may be attributable to both hesitancy and disparities in access.


Subject(s)
COVID-19 Vaccines/administration & dosage , COVID-19/ethnology , COVID-19/prevention & control , SARS-CoV-2/immunology , Vaccination/psychology , Adult , Aged , Aged, 80 and over , /statistics & numerical data , /statistics & numerical data , COVID-19/psychology , Cohort Studies , Female , /statistics & numerical data , Humans , Male , Middle Aged , Minority Groups/psychology , Minority Groups/statistics & numerical data , SARS-CoV-2/genetics , Self Report , United Kingdom/ethnology , United States/epidemiology , /statistics & numerical data , Young Adult
5.
Proc Natl Acad Sci U S A ; 118(51)2021 12 21.
Article in English | MEDLINE | ID: covidwho-1569348

ABSTRACT

Simultaneously tracking the global impact of COVID-19 is challenging because of regional variation in resources and reporting. Leveraging self-reported survey outcomes via an existing international social media network has the potential to provide standardized data streams to support monitoring and decision-making worldwide, in real time, and with limited local resources. The University of Maryland Global COVID-19 Trends and Impact Survey (UMD-CTIS), in partnership with Facebook, has invited daily cross-sectional samples from the social media platform's active users to participate in the survey since its launch on April 23, 2020. We analyzed UMD-CTIS survey data through December 20, 2020, from 31,142,582 responses representing 114 countries/territories weighted for nonresponse and adjusted to basic demographics. We show consistent respondent demographics over time for many countries/territories. Machine Learning models trained on national and pooled global data verified known symptom indicators. COVID-like illness (CLI) signals were correlated with government benchmark data. Importantly, the best benchmarked UMD-CTIS signal uses a single survey item whereby respondents report on CLI in their local community. In regions with strained health infrastructure but active social media users, we show it is possible to define COVID-19 impact trajectories using a remote platform independent of local government resources. This syndromic surveillance public health tool is the largest global health survey to date and, with brief participant engagement, can provide meaningful, timely insights into the global COVID-19 pandemic at a local scale.


Subject(s)
COVID-19/epidemiology , Public Health Surveillance/methods , Social Media , COVID-19/diagnosis , COVID-19 Testing , Cross-Sectional Studies , Epidemiologic Methods , Humans , Internationality , Machine Learning , Pandemics/statistics & numerical data
6.
Gut ; 70(11): 2096-2104, 2021 11.
Article in English | MEDLINE | ID: covidwho-1398714

ABSTRACT

OBJECTIVE: Poor metabolic health and unhealthy lifestyle factors have been associated with risk and severity of COVID-19, but data for diet are lacking. We aimed to investigate the association of diet quality with risk and severity of COVID-19 and its interaction with socioeconomic deprivation. DESIGN: We used data from 592 571 participants of the smartphone-based COVID-19 Symptom Study. Diet information was collected for the prepandemic period using a short food frequency questionnaire, and diet quality was assessed using a healthful Plant-Based Diet Score, which emphasises healthy plant foods such as fruits or vegetables. Multivariable Cox models were fitted to calculate HRs and 95% CIs for COVID-19 risk and severity defined using a validated symptom-based algorithm or hospitalisation with oxygen support, respectively. RESULTS: Over 3 886 274 person-months of follow-up, 31 815 COVID-19 cases were documented. Compared with individuals in the lowest quartile of the diet score, high diet quality was associated with lower risk of COVID-19 (HR 0.91; 95% CI 0.88 to 0.94) and severe COVID-19 (HR 0.59; 95% CI 0.47 to 0.74). The joint association of low diet quality and increased deprivation on COVID-19 risk was higher than the sum of the risk associated with each factor alone (Pinteraction=0.005). The corresponding absolute excess rate per 10 000 person/months for lowest vs highest quartile of diet score was 22.5 (95% CI 18.8 to 26.3) among persons living in areas with low deprivation and 40.8 (95% CI 31.7 to 49.8) among persons living in areas with high deprivation. CONCLUSIONS: A diet characterised by healthy plant-based foods was associated with lower risk and severity of COVID-19. This association may be particularly evident among individuals living in areas with higher socioeconomic deprivation.


Subject(s)
COVID-19/etiology , Diet/adverse effects , Adolescent , Adult , Aged , COVID-19/epidemiology , COVID-19/prevention & control , Diet Surveys , Diet, Healthy , Female , Humans , Male , Middle Aged , Prospective Studies , Risk Factors , Severity of Illness Index , Socioeconomic Factors , Surveys and Questionnaires , Young Adult
7.
Lancet Digit Health ; 3(9): e577-e586, 2021 09.
Article in English | MEDLINE | ID: covidwho-1322425

ABSTRACT

BACKGROUND: Multiple voluntary surveillance platforms were developed across the world in response to the COVID-19 pandemic, providing a real-time understanding of population-based COVID-19 epidemiology. During this time, testing criteria broadened and health-care policies matured. We aimed to test whether there were consistent associations of symptoms with SARS-CoV-2 test status across three surveillance platforms in three countries (two platforms per country), during periods of testing and policy changes. METHODS: For this observational study, we used data of observations from three volunteer COVID-19 digital surveillance platforms (Carnegie Mellon University and University of Maryland Facebook COVID-19 Symptom Survey, ZOE COVID Symptom Study app, and the Corona Israel study) targeting communities in three countries (Israel, the UK, and the USA; two platforms per country). The study population included adult respondents (age 18-100 years at baseline) who were not health-care workers. We did logistic regression of self-reported symptoms on self-reported SARS-CoV-2 test status (positive or negative), adjusted for age and sex, in each of the study cohorts. We compared odds ratios (ORs) across platforms and countries, and we did meta-analyses assuming a random effects model. We also evaluated testing policy changes, COVID-19 incidence, and time scales of duration of symptoms and symptom-to-test time. FINDINGS: Between April 1 and July 31, 2020, 514 459 tests from over 10 million respondents were recorded in the six surveillance platform datasets. Anosmia-ageusia was the strongest, most consistent symptom associated with a positive COVID-19 test (robust aggregated rank one, meta-analysed random effects OR 16·96, 95% CI 13·13-21·92). Fever (rank two, 6·45, 4·25-9·81), shortness of breath (rank three, 4·69, 3·14-7·01), and cough (rank four, 4·29, 3·13-5·88) were also highly associated with test positivity. The association of symptoms with test status varied by duration of illness, timing of the test, and broader test criteria, as well as over time, by country, and by platform. INTERPRETATION: The strong association of anosmia-ageusia with self-reported positive SARS-CoV-2 test was consistently observed, supporting its validity as a reliable COVID-19 signal, regardless of the participatory surveillance platform, country, phase of illness, or testing policy. These findings show that associations between COVID-19 symptoms and test positivity ranked similarly in a wide range of scenarios. Anosmia, fever, and respiratory symptoms consistently had the strongest effect estimates and were the most appropriate empirical signals for symptom-based public health surveillance in areas with insufficient testing or benchmarking capacity. Collaborative syndromic surveillance could enhance real-time epidemiological investigations and public health utility globally. FUNDING: National Institutes of Health, National Institute for Health Research, Alzheimer's Society, Wellcome Trust, and Massachusetts Consortium on Pathogen Readiness.


Subject(s)
Ageusia , Anosmia , COVID-19 , Cough , Dyspnea , Fever , Population Surveillance/methods , Adolescent , Adult , Aged , Aged, 80 and over , Ageusia/epidemiology , Ageusia/etiology , Anosmia/epidemiology , Anosmia/etiology , COVID-19/complications , COVID-19/epidemiology , COVID-19/virology , Cough/epidemiology , Cough/etiology , Digital Technology , Dyspnea/epidemiology , Dyspnea/etiology , Female , Fever/epidemiology , Fever/etiology , Humans , Israel/epidemiology , Male , Middle Aged , Odds Ratio , Pandemics , SARS-CoV-2 , United Kingdom/epidemiology , United States/epidemiology , Young Adult
8.
EClinicalMedicine ; 38: 101029, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1313065

ABSTRACT

BACKGROUND: There is limited prior investigation of the combined influence of personal and community-level socioeconomic factors on racial/ethnic disparities in individual risk of coronavirus disease 2019 (COVID-19). METHODS: We performed a cross-sectional analysis nested within a prospective cohort of 2,102,364 participants from March 29, 2020 in the United States (US) and March 24, 2020 in the United Kingdom (UK) through December 02, 2020 via the COVID Symptom Study smartphone application. We examined the contribution of community-level deprivation using the Neighborhood Deprivation Index (NDI) and the Index of Multiple Deprivation (IMD) to observe racial/ethnic disparities in COVID-19 incidence. ClinicalTrials.gov registration: NCT04331509. FINDINGS: Compared with non-Hispanic White participants, the risk for a positive COVID-19 test was increased in the US for non-Hispanic Black (multivariable-adjusted odds ratio [OR], 1.32; 95% confidence interval [CI], 1.18-1.47) and Hispanic participants (OR, 1.42; 95% CI, 1.33-1.52) and in the UK for Black (OR, 1.17; 95% CI, 1.02-1.34), South Asian (OR, 1.39; 95% CI, 1.30-1.49), and Middle Eastern participants (OR, 1.38; 95% CI, 1.18-1.61). This elevated risk was associated with living in more deprived communities according to the NDI/IMD. After accounting for downstream mediators of COVID-19 risk, community-level deprivation still mediated 16.6% and 7.7% of the excess risk in Black compared to White participants in the US and the UK, respectively. INTERPRETATION: Our results illustrate the critical role of social determinants of health in the disproportionate COVID-19 risk experienced by racial and ethnic minorities.

9.
Nat Commun ; 12(1): 3737, 2021 06 18.
Article in English | MEDLINE | ID: covidwho-1275924

ABSTRACT

Given the continued burden of COVID-19 worldwide, there is a high unmet need for data on the effect of social distancing and face mask use to mitigate the risk of COVID-19. We examined the association of community-level social distancing measures and individual face mask use with risk of predicted COVID-19 in a large prospective U.S. cohort study of 198,077 participants. Individuals living in communities with the greatest social distancing had a 31% lower risk of predicted COVID-19 compared with those living in communities with poor social distancing. Self-reported 'always' use of face mask was associated with a 62% reduced risk of predicted COVID-19 even among individuals living in a community with poor social distancing. These findings provide support for the efficacy of mask-wearing even in settings of poor social distancing in reducing COVID-19 transmission. Despite mass vaccination campaigns in many parts of the world, continued efforts at social distancing and face mask use remain critically important in reducing the spread of COVID-19.


Subject(s)
COVID-19/prevention & control , Masks/statistics & numerical data , Physical Distancing , Adult , Aged , COVID-19/epidemiology , COVID-19/transmission , COVID-19/virology , Disease Transmission, Infectious/prevention & control , Female , Humans , Male , Middle Aged , Prospective Studies , Public Health , SARS-CoV-2/isolation & purification , United States/epidemiology
11.
Sci Rep ; 11(1): 6928, 2021 03 25.
Article in English | MEDLINE | ID: covidwho-1152881

ABSTRACT

We tested whether pregnant and non-pregnant women differ in COVID-19 symptom profile and severity, and we extended previous investigations on hospitalized pregnant women to those who did not require hospitalization. Two female community-based cohorts (18-44 years) provided longitudinal (smartphone application, N = 1,170,315, n = 79 pregnant tested positive) and cross-sectional (web-based survey, N = 1,344,966, n = 134 pregnant tested positive) data, prospectively collected through self-participatory citizen surveillance in UK, Sweden and USA. Pregnant and non-pregnant were compared for frequencies of events, including SARS-CoV-2 testing, symptoms and hospitalization rates. Multivariable regression was used to investigate symptoms severity and comorbidity effects. Pregnant and non-pregnant women positive for SARS-CoV-2 infection were not different in syndromic severity, except for gastrointestinal symptoms. Pregnant were more likely to have received testing, despite reporting fewer symptoms. Pre-existing lung disease was most closely associated with syndromic severity in pregnant hospitalized. Heart and kidney diseases and diabetes increased risk. The most frequent symptoms among non-hospitalized women were anosmia [63% pregnant, 92% non-pregnant] and headache [72%, 62%]. Cardiopulmonary symptoms, including persistent cough [80%] and chest pain [73%], were more frequent among pregnant who were hospitalized. Consistent with observations in non-pregnant populations, lung disease and diabetes were associated with increased risk of more severe SARS-CoV-2 infection during pregnancy.


Subject(s)
COVID-19/complications , Pregnancy Complications, Infectious/physiopathology , Adolescent , Adult , COVID-19/physiopathology , COVID-19/virology , Cohort Studies , Cross-Sectional Studies , Female , Humans , Mobile Applications , Pregnancy , SARS-CoV-2/isolation & purification , Severity of Illness Index , Young Adult
13.
Nat Med ; 27(4): 626-631, 2021 04.
Article in English | MEDLINE | ID: covidwho-1127166

ABSTRACT

Reports of long-lasting coronavirus disease 2019 (COVID-19) symptoms, the so-called 'long COVID', are rising but little is known about prevalence, risk factors or whether it is possible to predict a protracted course early in the disease. We analyzed data from 4,182 incident cases of COVID-19 in which individuals self-reported their symptoms prospectively in the COVID Symptom Study app1. A total of 558 (13.3%) participants reported symptoms lasting ≥28 days, 189 (4.5%) for ≥8 weeks and 95 (2.3%) for ≥12 weeks. Long COVID was characterized by symptoms of fatigue, headache, dyspnea and anosmia and was more likely with increasing age and body mass index and female sex. Experiencing more than five symptoms during the first week of illness was associated with long COVID (odds ratio = 3.53 (2.76-4.50)). A simple model to distinguish between short COVID and long COVID at 7 days (total sample size, n = 2,149) showed an area under the curve of the receiver operating characteristic curve of 76%, with replication in an independent sample of 2,472 individuals who were positive for severe acute respiratory syndrome coronavirus 2. This model could be used to identify individuals at risk of long COVID for trials of prevention or treatment and to plan education and rehabilitation services.


Subject(s)
COVID-19/complications , SARS-CoV-2 , Adult , Age Factors , Aged , Female , Humans , Male , Middle Aged , Prospective Studies , Risk Factors , Time Factors
14.
Lancet Public Health ; 6(1): e21-e29, 2021 01.
Article in English | MEDLINE | ID: covidwho-1072036

ABSTRACT

BACKGROUND: As many countries seek to slow the spread of COVID-19 without reimposing national restrictions, it has become important to track the disease at a local level to identify areas in need of targeted intervention. METHODS: In this prospective, observational study, we did modelling using longitudinal, self-reported data from users of the COVID Symptom Study app in England between March 24, and Sept 29, 2020. Beginning on April 28, in England, the Department of Health and Social Care allocated RT-PCR tests for COVID-19 to app users who logged themselves as healthy at least once in 9 days and then reported any symptom. We calculated incidence of COVID-19 using the invited swab (RT-PCR) tests reported in the app, and we estimated prevalence using a symptom-based method (using logistic regression) and a method based on both symptoms and swab test results. We used incidence rates to estimate the effective reproduction number, R(t), modelling the system as a Poisson process and using Markov Chain Monte-Carlo. We used three datasets to validate our models: the Office for National Statistics (ONS) Community Infection Survey, the Real-time Assessment of Community Transmission (REACT-1) study, and UK Government testing data. We used geographically granular estimates to highlight regions with rapidly increasing case numbers, or hotspots. FINDINGS: From March 24 to Sept 29, 2020, a total of 2 873 726 users living in England signed up to use the app, of whom 2 842 732 (98·9%) provided valid age information and daily assessments. These users provided a total of 120 192 306 daily reports of their symptoms, and recorded the results of 169 682 invited swab tests. On a national level, our estimates of incidence and prevalence showed a similar sensitivity to changes to those reported in the ONS and REACT-1 studies. On Sept 28, 2020, we estimated an incidence of 15 841 (95% CI 14 023-17 885) daily cases, a prevalence of 0·53% (0·45-0·60), and R(t) of 1·17 (1·15-1·19) in England. On a geographically granular level, on Sept 28, 2020, we detected 15 (75%) of the 20 regions with highest incidence according to government test data. INTERPRETATION: Our method could help to detect rapid case increases in regions where government testing provision is lower. Self-reported data from mobile applications can provide an agile resource to inform policy makers during a quickly moving pandemic, serving as a complementary resource to more traditional instruments for disease surveillance. FUNDING: Zoe Global, UK Government Department of Health and Social Care, Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK National Institute for Health Research, UK Medical Research Council and British Heart Foundation, Alzheimer's Society, Chronic Disease Research Foundation.


Subject(s)
COVID-19/epidemiology , Disease Hotspot , Mobile Applications , Public Health Surveillance/methods , Self Report , Adolescent , Adult , Aged , England/epidemiology , Female , Humans , Male , Middle Aged , Prospective Studies , Young Adult
15.
Lancet Digit Health ; 3(3): e148-e157, 2021 03.
Article in English | MEDLINE | ID: covidwho-1065707

ABSTRACT

BACKGROUND: Face masks have become commonplace across the USA because of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic. Although evidence suggests that masks help to curb the spread of the disease, there is little empirical research at the population level. We investigate the association between self-reported mask-wearing, physical distancing, and SARS-CoV-2 transmission in the USA, along with the effect of statewide mandates on mask uptake. METHODS: Serial cross-sectional surveys were administered via a web platform to randomly surveyed US individuals aged 13 years and older, to query self-reports of face mask-wearing. Survey responses were combined with instantaneous reproductive number (Rt) estimates from two publicly available sources, the outcome of interest. Measures of physical distancing, community demographics, and other potential sources of confounding (from publicly available sources) were also assessed. We fitted multivariate logistic regression models to estimate the association between mask-wearing and community transmission control (Rt<1). Additionally, mask-wearing in 12 states was evaluated 2 weeks before and after statewide mandates. FINDINGS: 378 207 individuals responded to the survey between June 3 and July 27, 2020, of which 4186 were excluded for missing data. We observed an increasing trend in reported mask usage across the USA, although uptake varied by geography. A logistic model controlling for physical distancing, population demographics, and other variables found that a 10% increase in self-reported mask-wearing was associated with an increased odds of transmission control (odds ratio 3·53, 95% CI 2·03-6·43). We found that communities with high reported mask-wearing and physical distancing had the highest predicted probability of transmission control. Segmented regression analysis of reported mask-wearing showed no statistically significant change in the slope after mandates were introduced; however, the upward trend in reported mask-wearing was preserved. INTERPRETATION: The widespread reported use of face masks combined with physical distancing increases the odds of SARS-CoV-2 transmission control. Self-reported mask-wearing increased separately from government mask mandates, suggesting that supplemental public health interventions are needed to maximise adoption and help to curb the ongoing epidemic. FUNDING: Flu Lab, Google.org (via the Tides Foundation), National Institutes for Health, National Science Foundation, Morris-Singer Foundation, MOOD, Branco Weiss Fellowship, Ending Pandemics, Centers for Disease Control and Prevention (USA).


Subject(s)
COVID-19/prevention & control , COVID-19/transmission , Masks , Pandemics/prevention & control , Adolescent , Adult , Aged , Communicable Disease Control/methods , Cross-Sectional Studies , Female , Humans , Male , Middle Aged , Physical Distancing , Public Health , SARS-CoV-2 , Surveys and Questionnaires , United States , Young Adult
16.
medRxiv ; 2020 Nov 17.
Article in English | MEDLINE | ID: covidwho-915975

ABSTRACT

BACKGROUND: As many countries seek to slow the spread of COVID-19 without reimposing national restrictions, it has become important to track the disease at a local level to identify areas in need of targeted intervention. METHODS: We performed modelling on longitudinal, self-reported data from users of the COVID Symptom Study app in England between 24 March and 29 September, 2020. Combining a symptom-based predictive model for COVID-19 positivity and RT-PCR tests provided by the Department of Health we were able to estimate disease incidence, prevalence and effective reproduction number. Geographically granular estimates were used to highlight regions with rapidly increasing case numbers, or hotspots. FINDINGS: More than 2.8 million app users in England provided 120 million daily reports of their symptoms, and recorded the results of 170,000 PCR tests. On a national level our estimates of incidence and prevalence showed similar sensitivity to changes as two national community surveys: the ONS and REACT-1 studies. On 28 September 2020 we estimated 15,841 (95% CI 14,023-17,885) daily cases, a prevalence of 0.53% (95% CI 0.45-0.60), and R(t) of 1.17 (95% credible interval 1.15-1.19) in England. On a geographically granular level, on 28 September 2020 we detected 15 of the 20 regions with highest incidence according to Government test data, with indications that our method may be able to detect rapid case increases in regions where Government testing provision is more limited. INTERPRETATION: Self-reported data from mobile applications can provide an agile resource to inform policymakers during a fast-moving pandemic, serving as an independent and complementary resource to more traditional instruments for disease surveillance. FUNDING: Zoe Global Limited, Department of Health, Wellcome Trust, EPSRC, NIHR, MRC, Alzheimer's Society.

17.
medRxiv ; 2020 Oct 14.
Article in English | MEDLINE | ID: covidwho-900748

ABSTRACT

OBJECTIVE: To test whether pregnant and non-pregnant women differ in COVID-19 symptom profile and severity. To extend previous investigations on hospitalized pregnant women to those who did not require hospitalization. DESIGN: Observational study prospectively collecting longitudinal (smartphone application interface) and cross-sectional (web-based survey) data. SETTING: Community-based self-participatory citizen surveillance in the United Kingdom, Sweden and the United States of America. POPULATION: Two female community-based cohorts aged 18-44 years. The discovery cohort was drawn from 1,170,315 UK, Sweden and USA women (79 pregnant tested positive) who self-reported status and symptoms longitudinally via smartphone. The replication cohort included 1,344,966 USA women (134 pregnant tested positive) who provided cross-sectional self-reports. METHODS: Pregnant and non-pregnant were compared for frequencies of symptoms and events, including SARS-CoV-2 testing and hospitalization rates. Multivariable regression was used to investigate symptoms severity and comorbidity effects. RESULTS: Pregnant and non-pregnant women positive for SARS-CoV-2 infection were not different in syndromic severity. Pregnant were more likely to have received testing than non-pregnant, despite reporting fewer symptoms. Pre-existing lung disease was most closely associated with the syndromic severity in pregnant hospitalized women. Heart and kidney diseases and diabetes increased risk. The most frequent symptoms among all non-hospitalized women were anosmia [63% pregnant, 92% non-pregnant] and headache [72%, 62%]. Cardiopulmonary symptoms, including persistent cough [80%] and chest pain [73%], were more frequent among pregnant women who were hospitalized. CONCLUSIONS: Symptom characteristics and severity were comparable among pregnant and non-pregnant women, except for gastrointestinal symptoms. Consistent with observations in non-pregnant populations, lung disease and diabetes were associated with increased risk of more severe SARS-CoV-2 infection during pregnancy.

19.
PLoS One ; 15(10): e0239886, 2020.
Article in English | MEDLINE | ID: covidwho-810229

ABSTRACT

BACKGROUND: Syndromic surveillance through web or phone-based polling has been used to track the course of infectious diseases worldwide. Our study objective was to describe the characteristics, symptoms, and self-reported testing rates of respondents in three different COVID-19 symptom surveys in Canada. METHODS: This was a cross-sectional study using three distinct Canada-wide web-based surveys, and phone polling in Ontario. All three sources contained self-reported information on COVID-19 symptoms and testing. In addition to describing respondent characteristics, we examined symptom frequency and the testing rate among the symptomatic, as well as rates of symptoms and testing across respondent groups. RESULTS: We found that over March- April 2020, 1.6% of respondents experienced a symptom on the day of their survey, 15% of Ontario households had a symptom in the previous week, and 44% of Canada-wide respondents had a symptom in the previous month. Across the three surveys, SARS-CoV-2-testing was reported in 2-9% of symptomatic responses. Women, younger and middle-aged adults (versus older adults) and Indigenous/First nations/Inuit/Métis were more likely to report at least one symptom, and visible minorities were more likely to report the combination of fever with cough or shortness of breath. INTERPRETATION: The low rate of testing among those reporting symptoms suggests significant opportunity to expand testing among community-dwelling residents of Canada. Syndromic surveillance data can supplement public health reports and provide much-needed context to gauge the adequacy of SARS-CoV-2 testing rates.


Subject(s)
Clinical Laboratory Techniques/statistics & numerical data , Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Self Report/statistics & numerical data , Sentinel Surveillance , Adult , Aged , COVID-19 , COVID-19 Testing , Canada/epidemiology , Coronavirus Infections/diagnosis , Cross-Sectional Studies , Female , Humans , Internet , Male , Middle Aged , Pandemics , Pneumonia, Viral/diagnosis , Prevalence , Telephone
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