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Background: India reported first laboratory-confirmed case of coronavirus disease 2019 (COVID-19) on 30 January from Kerala. Media surveillance is useful to capture unstructured information about outbreaks. We established media surveillance and described the characteristics of the COVID-19 cases, clusters, deaths by time, place, and person during January–March 2020 in India. Methods: The media surveillance team of ICMR-National Institute of Epidemiology abstracted data from public domains of India's Central and State health ministries, online news and social media platforms for the period of January 31 to March 26, 2020. We collected data on person (socio-demographics, circumstances of travel/contact, clinical and laboratory), time (date/period of reported exposures; laboratory confirmation and death) and place (location). We drew epidemic curve, described frequencies of cases by age and gender. We described available details for identified clusters. Results: As of March 26, 2020, India reported 694 (Foreigners = 45, 6%) confirmed COVID-19 cases (Attack rate = 0.5 per million population) and 17 deaths (Fatality = 2.5%) from 21 States and 6 Union Territories. The cases were higher among 20–59 years of age (60 of 85) and male gender (65 of 107). Median age at death was 68 years (Range: 38–85 years). We identified 13 clusters with a total of 63 cases and four deaths among the first 200 cases. Conclusion: Surveillance of media sources was useful in characterizing the epidemic in the early phase. Hence, media surveillance should be integrated in the routine surveillance systems to map the events specially in context of new disease outbreaks.

BackgroundIn the ongoing COVID-19 pandemic, an increased incidence of ROCM was noted in India among those infected with COVID. We determined risk factors for rhino-orbito-cerebral mucormycosis (ROCM) post Coronavirus disease 2019 (COVID-19) among those never and ever hospitalized for COVID-19 separately through a multicentric, hospital-based, unmatched case-control study across India.MethodsWe defined cases and controls as those with and without post-COVID ROCM, respectively. We compared their socio-demographics, co-morbidities, steroid use, glycaemic status, and practices. We calculated crude and adjusted odds ratio (AOR) with 95% confidence intervals (CI) through logistic regression. The covariates with a p-value for crude OR of less than 0·20 were considered for the regression model.ResultsAmong hospitalised, we recruited 267 cases and 256 controls and 116 cases and 231 controls among never hospitalised. Risk factors (AOR; 95% CI) for post-COVID ROCM among the hospitalised were age 45-59 years (2·1; 1·4 to 3·1), having diabetes mellitus (4·9; 3·4 to 7·1), elevated plasma glucose (6·4; 2·4 to 17·2), steroid use (3·2; 2 to 5·2) and frequent nasal washing (4·8; 1·4 to 17). Among those never hospitalised, age ≥ 60 years (6·6; 3·3 to 13·3), having diabetes mellitus (6·7; 3·8 to 11·6), elevated plasma glucose (13·7; 2·2 to 84), steroid use (9·8; 5·8 to 16·6), and cloth facemask use (2·6; 1·5 to 4·5) were associated with increased risk of post-COVID ROCM.ConclusionsHyperglycemia, irrespective of having diabetes mellitus and steroid use, was associated with an increased risk of ROCM independent of COVID-19 hospitalisation. Rational steroid usage and glucose monitoring may reduce the risk of post-COVID.

Objectives: To identify risk factors associated with Coronavirus disease 2019 (COVID-19) in a Tertiary care cancer hospital-based cluster and recommend control measures. Methods: We conducted tracing and confirmation among hospital and community contacts. We telephonically interviewed and abstracted information from hospital records and registers. We described the cluster by time, place and person. We conducted unmatched case-control study to compare risk factors and computed Odds Ratio (OR) and 95% confidence interval. Results: We confirmed COVID-19 in 21 of 1478 tested (1.4%). Secondary attack (%) of COVID-19 among 824 contacts was higher among in-patients of block A (18), household contacts (3.4), housekeeping staff (3.3) and nurses (1.7). The cluster started on April 22 with two successive peaks five days apart and lasted until May 8. Being male, patients aged >33 years [OR = 30·7; 95% CI = 3·6 to 264], having hypertension [OR = 4·3; 95% CI = 1·1 to 16·7] or diabetes [OR = 3·8; 95% CI = 1·0 to 14·1] were associated with COVID-19. Mask compliance was poor (20%) among hospital workers. Discussion: We recommended screening of all patients for diabetes and hypertension and isolation/testing of anyone with influenza-like illness for preventing COVID-19 clusters in hospital settings.