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Strong associations and moderate predictive value of early symptoms for SARS-CoV-2 test positivity among healthcare workers, the Netherlands, March 2020.

ABSTRACT: Healthcare workers (n?=?803) with mild symptoms were tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (n?=?90 positive) and asked to complete a symptom questionnaire. Anosmia, muscle ache, ocular pain, general malaise, headache, extreme tiredness and fever were associated with positivity. A predictive model based on these symptoms showed moderate discriminative value (sensitivity: 91.2%; specificity: 55.6%). While our models would not justify presumptive SARS-CoV-2 diagnosis without molecular confirmation, it can contribute to targeted screening strategies.

SUBMITTER: Tostmann A

PROVIDER: S-EPMC7189649 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Strong associations and moderate predictive value of early symptoms for SARS-CoV-2 test positivity among healthcare workers, the Netherlands, March 2020.

Tostmann Alma A Bradley John J Bousema Teun T Yiek Wing-Kee WK Holwerda Minke M Bleeker-Rovers Chantal C Ten Oever Jaap J Meijer Corianne C Rahamat-Langendoen Janette J Hopman Joost J van der Geest-Blankert Nannet N Wertheim Heiman H

Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin 20200401 16

Healthcare workers (n = 803) with mild symptoms were tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (n = 90 positive) and asked to complete a symptom questionnaire. Anosmia, muscle ache, ocular pain, general malaise, headache, extreme tiredness and fever were associated with positivity. A predictive model based on these symptoms showed moderate discriminative value (sensitivity: 91.2%; specificity: 55.6%). While our models would not justify presumptive SARS-CoV-2 diagnos ...[more]

PMID: 32347200

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Project description:BackgroundDespite increased testing efforts and the deployment of vaccines, COVID-19 cases and death toll continue to rise at record rates. Health systems routinely collect clinical and non-clinical information in electronic health records (EHR), yet little is known about how the minimal or intermediate spectra of EHR data can be leveraged to characterize patient SARS-CoV-2 pretest probability in support of interventional strategies.Methods and findingsWe modeled patient pretest probability for SARS-CoV-2 test positivity and determined which features were contributing to the prediction and relative to patients triaged in inpatient, outpatient, and telehealth/drive-up visit-types. Data from the University of Washington (UW) Medicine Health System, which excluded UW Medicine care providers, included patients predominately residing in the Seattle Puget Sound area, were used to develop a gradient-boosting decision tree (GBDT) model. Patients were included if they had at least one visit prior to initial SARS-CoV-2 RT-PCR testing between January 01, 2020 through August 7, 2020. Model performance assessments used area-under-the-receiver-operating-characteristic (AUROC) and area-under-the-precision-recall (AUPR) curves. Feature performance assessments used SHapley Additive exPlanations (SHAP) values. The generalized pretest probability model using all available features achieved high overall discriminative performance (AUROC, 0.82). Performance among inpatients (AUROC, 0.86) was higher than telehealth/drive-up testing (AUROC, 0.81) or outpatient testing (AUROC, 0.76). The two-week test positivity rate in patient ZIP code was the most informative feature towards test positivity across visit-types. Geographic and sociodemographic factors were more important predictors of SARS-CoV-2 positivity than individual clinical characteristics.ConclusionsRecent geographic and sociodemographic factors, routinely collected in EHR though not routinely considered in clinical care, are the strongest predictors of initial SARS-CoV-2 test result. These findings were consistent across visit types, informing our understanding of individual SARS-CoV-2 risk factors with implications for deployment of testing, outreach, and population-level prevention efforts.

Project description:ObjectivesThis study aims to characterise the physical and psychological well-being of maternal and newborn healthcare workers (MNHCWs) during the COVID-19 pandemic.DesignObservational repeated cross-sectional study.SettingAn online questionnaire was distributed to MNHCWs around the globe in three separate rounds from March 2020 to March 2021.ParticipantsTotal samples of N=1357 (round 1) and N=420 (round 3) primarily consisted of doctors, midwives and nurses in maternal and newborn specialties. Samples represented all WHO regions, with 33% (round 1) and 42% (round 3) from low- or middle-income countries (LMICs).Primary and secondary outcome measuresResponses from rounds 1 (March-June 2020) and 3 (December 2020-March 2021) were analysed to measure self-reported levels of relative stress and workplace protection from COVID-19, while associated factors were determined through multivariable ordinal logistic regression.ResultsIn round 1, 90% of MNHCWs reported increased stress levels and 45% reported insufficient personal protective equipment (PPE) access. Nurses and physicians were less likely to report increased stress than midwives at the pandemic onset. Factors associated with increased stress included being female, being from an LMIC and insufficient PPE. In round 3, 75% reported similar or increased stress while 10% reported insufficient PPE. In both rounds, over 50% of MNHCWs felt relatively or completely unprotected from COVID-19 in the workplace. Those from LMICs were more likely to report feeling unprotected, while receiving organisational information that valued safety was associated with better feelings of protection in the workplace.ConclusionsAmong our international sample of MNHCWs, we observed high rates of self-reported stress increase at the start of the pandemic with persistence or increase up to a year later. High rates of feeling unprotected persisted even as PPE became more available. These results may inform interventions needed to support and protect MNHCWs during this and future pandemics.

Project description:Background COVID-19 is currently a global health threat. Healthcare workers are on the front-line of the COVID-19 outbreak response and therefore at heightened risk of infection. There is a dearth of evidence from Sub-Saharan Africa about healthcare worker experiences in managing COVID-19. We have reported on healthcare worker responses, experiences, and perspectives on epidemic response strategies at Queen Elizabeth Central Hospital, Malawi's largest referral hospital. Methods We conducted 39 face-to-face in-depth interviews with a purposively selected sample of healthcare workers during the first wave of COVID-19 in Malawi (March 2020 to October 2020). The study included healthcare workers who provided direct and indirect patient care. Results During the early phase of the first wave (March to May 2020), healthcare workers expressed concerns with inadequate working space, unconducive infrastructure, delayed and rushed training on the management of COVID-19, and lack of incentives. Additionally, the hospital had staff shortages and limited essential resources such as piped oxygen and personal protective equipment. This increased healthcare worker fears of contracting COVID-19 and they were less willing to volunteer at COVID-19 isolation units. Resource constraints and limited preparedness compromised the care pathway particularly with increased numbers of COVID-19 patients. By the peak of the first wave (June to August 2020) many of these issues had been resolved. The hospital provided refresher training courses, personal protective equipment became available, incentives were offered to healthcare workers working in COVID-19 units and piped oxygen was installed. Staff morale was boosted, and more staff were willing to work at the COVID-19 isolation centres. Conclusion Experiences of healthcare workers during the first wave of COVID-19 are critical for improving care in future COVID-19 waves. Response strategies in resource-constrained areas should prioritise timely training of staff, creation of adequate isolation areas, provision of adequate medical supplies and strengthening leadership.

Project description:BackgroundThe Dutch province of Limburg borders the German district of Heinsberg, which had a large cluster of COVID-19 cases linked to local carnival activities before any cases were reported in the Netherlands. However, Heinsberg was not included as an area reporting local or community transmission per the national case definition at the time. In early March, two residents from a long-term care facility (LTCF) in Sittard, a Dutch town located in close vicinity to the district of Heinsberg, tested positive for COVID-19. In this study we aimed to determine whether cross-border introduction of the virus took place by analysing the LTCF outbreak in Sittard, both epidemiologically and microbiologically.MethodsSurveys and semi-structured oral interviews were conducted with all present LTCF residents by health care workers during regular points of care for information on new or unusual signs and symptoms of disease. Both throat and nasopharyngeal swabs were taken from residents suspect of COVID-19, based on regional criteria, for the detection of SARS-CoV-2 by Real-time Polymerase Chain Reaction. Additionally, whole genome sequencing was performed using a SARS-CoV-2 specific amplicon-based Nanopore sequencing approach. Moreover, twelve random residents were sampled for possible asymptomatic infections.ResultsOut of 99 residents, 46 got tested for COVID-19. Out of the 46 tested residents, nineteen (41%) tested positive for COVID-19, including 3 asymptomatic residents. CT-values for asymptomatic residents seemed higher compared to symptomatic residents. Eleven samples were sequenced, along with three random samples from COVID-19 patients hospitalized in the regional hospital at the time of the LTCF outbreak. All samples were linked to COVID-19 cases from the cross-border region of Heinsberg, Germany.ConclusionsSequencing combined with epidemiological data was able to virtually prove cross-border transmission at the start of the Dutch COVID-19 epidemic. Our results highlight the need for cross-border collaboration and adjustment of national policy to emerging region-specific needs along borders in order to establish coordinated implementation of infection control measures to limit the spread of COVID-19.

Dataset Information

Strong associations and moderate predictive value of early symptoms for SARS-CoV-2 test positivity among healthcare workers, the Netherlands, March 2020.

Publications

Strong associations and moderate predictive value of early symptoms for SARS-CoV-2 test positivity among healthcare workers, the Netherlands, March 2020.

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