Differentiating coronavirus disease 2019 (COVID-19) from influenza and dengue.

The novel coronavirus disease 2019 (COVID-19) presents with non-specific clinical features. This may result in misdiagnosis or delayed diagnosis, and lead to further transmission in the community. We aimed to derive early predictors to differentiate COVID-19 from influenza and dengue. The study comprised 126 patients with COVID-19, 171 with influenza and 180 with dengue, who presented within 5 days of symptom onset. All cases were confirmed by reverse transcriptase polymerase chain reaction tests. We used logistic regression models to identify demographics, clinical characteristics and laboratory markers in classifying COVID-19 versus influenza, and COVID-19 versus dengue. The performance of each model was evaluated using receiver operating characteristic (ROC) curves. Shortness of breath was the strongest predictor in the models for differentiating between COVID-19 and influenza, followed by diarrhoea. Higher lymphocyte count was predictive of COVID-19 versus influenza and versus dengue. In the model for differentiating between COVID-19 and dengue, patients with cough and higher platelet count were at increased odds of COVID-19, while headache, joint pain, skin rash and vomiting/nausea were indicative of dengue. The cross-validated area under the ROC curve for all four models was above 0.85. Clinical features and simple laboratory markers for differentiating COVID-19 from influenza and dengue are identified in this study which can be used by primary care physicians in resource limited settings to determine if further investigations or referrals would be required.

Pan-Sarbecovirus Neutralizing Antibodies in BNT162b2-Immunized SARS-CoV-1 Survivors.

Emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern pose a challenge to the effectiveness of current vaccines. A vaccine that could prevent infection caused by known and future variants of concern as well as infection with pre-emergent sarbecoviruses (i.e., those with potential to cause disease in humans in the future) would be ideal. Here we provide data showing that potent cross-clade pan-sarbecovirus neutralizing antibodies are induced in survivors of severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1) infection who have been immunized with the BNT162b2 messenger RNA (mRNA) vaccine. The antibodies are high-level and broad-spectrum, capable of neutralizing not only known variants of concern but also sarbecoviruses that have been identified in bats and pangolins and that have the potential to cause human infection. These findings show the feasibility of a pan-sarbecovirus vaccine strategy. (Funded by the Singapore National Research Foundation and National Medical Research Council.).

Government trust, perceptions of COVID-19 and behaviour change: cohort surveys, Singapore.

OBJECTIVE: To evaluate how public perceptions and trust in government communications affected the adoption of protective behaviour in Singapore during the coronavirus disease 2019 (COVID-19) pandemic. METHODS: We launched our community-based cohort to assess public perceptions of infectious disease outbreaks in mid-2019. After the first case of COVID-19 was reported in Singapore on 23 January, we launched a series of seven COVID-19 surveys to both existing and regularly enrolled new participants every 2 weeks. As well as sociodemographic properties of the participants, we recorded changing responses to judge awareness of the situation, trust in various information sources and perceived risk. We used multivariable logistic regression models to evaluate associations with perceptions of risk and self-reported adopted frequencies of protective behaviour. FINDINGS: Our cohort of 633 participants provided 2857 unique responses during the seven COVID-19 surveys. Most agreed or strongly agreed that information from official government sources (99.1%; 528/533) and Singapore-based news agencies (97.9%; 522/533) was trustworthy. Trust in government communication was significantly associated with higher perceived threat (odds ratio, OR: 2.2; 95% confidence interval, CI: 1.6-3.0), but inversely associated with perceived risk of infection (OR: 0.6; 95% CI: 0.4-0.8) or risk of death if infected (OR: 0.6; 95% CI: 0.4-0.9). Trust in government communication was also associated with a greater likelihood of adopting protective behaviour. CONCLUSION: Our findings show that trust is a vital commodity when managing an evolving outbreak. Our repeated surveys provided real-time feedback, allowing an improved understanding of the interplay between perceptions, trust and behaviour.

Identifying COVID-19 cases in outpatient settings.

Case identification is an ongoing issue for the COVID-19 epidemic, in particular for outpatient care where physicians must decide which patients to prioritise for further testing. This paper reports tools to classify patients based on symptom profiles based on 236 severe acute respiratory syndrome coronavirus 2 positive cases and 564 controls, accounting for the time course of illness using generalised multivariate logistic regression. Significant symptoms included abdominal pain, cough, diarrhoea, fever, headache, muscle ache, runny nose, sore throat, temperature between 37.5 and 37.9 °C and temperature above 38 °C, but their importance varied by day of illness at assessment. With a high percentile threshold for specificity at 0.95, the baseline model had reasonable sensitivity at 0.67. To further evaluate accuracy of model predictions, leave-one-out cross-validation confirmed high classification accuracy with an area under the receiver operating characteristic curve of 0.92. For the baseline model, sensitivity decreased to 0.56. External validation datasets reported similar result. Our study provides a tool to discern COVID-19 patients from controls using symptoms and day from illness onset with good predictive performance. It could be considered as a framework to complement laboratory testing in order to differentiate COVID-19 from other patients presenting with acute symptoms in outpatient care.

Olfactory taste disorder as a presenting symptom of COVID-19: a large single-center Singapore study.

PURPOSE: To investigate the prevalence and epidemiological risk factors of olfactory and/or taste disorder (OTD), in particular isolated OTD, in patients with laboratory-confirmed COVID-19 infection. METHODS: We conducted a retrospective and cross-sectional study. Patients with laboratory-confirmed COVID-19 infection were recruited from the National Centre for Infectious Diseases (NCID) Singapore between 24 March 2020 and 16 April 2020. The electronic health records of these patients were accessed, and demographic data and symptoms reported (respiratory, self-reported OTD and other symptoms such as headache, myalgia and lethargy) were collected. RESULTS: A total of 1065 patients with laboratory-confirmed COVID-19 were recruited. Overall, the prevalence of OTD was 12.6%. Twelve patients (1.1%) had isolated OTD. The top three symptoms associated with OTD were cough, fever and sore throat. The symptoms of runny nose and blocked nose were experienced by only 29.8 and 19.3% of patients, respectively. Multivariate analysis demonstrated that the female gender, presence of blocked nose and absence of fever were significantly associated with OTD (adjusted relative risks 1.77, 3.31, 0.42, respectively). All these factors were statistically significant. CONCLUSION: Patients with COVID-19 infection can present with OTD, either in isolation or in combination with other general symptoms. Certain demographic profile, such as being female, and symptomatology such as the presence of blocked nose and absence of fever, were more likely to have OTD when infected by COVID-19. Further studies to elucidate the pathophysiology of OTD in these patients will be beneficial.