Contact tracing of COVID-19 in Karnataka, India: Superspreading and determinants of infectiousness and symptomatic infection.

BACKGROUND: India has experienced the second largest outbreak of COVID-19 globally, yet there is a paucity of studies analysing contact tracing data in the region which can optimise public health interventions (PHI's). METHODS: We analysed contact tracing data from Karnataka, India between 9 March and 21 July 2020. We estimated metrics of transmission including the reproduction number (R), overdispersion (k), secondary attack rate (SAR), and serial interval. R and k were jointly estimated using a Bayesian Markov Chain Monte Carlo approach. We studied determinants of risk of further transmission and risk of being symptomatic using Poisson regression models. FINDINGS: Up to 21 July 2020, we found 111 index cases that crossed the super-spreading threshold of ≥8 secondary cases. Among 956 confirmed traced cases, 8.7% of index cases had 14.4% of contacts but caused 80% of all secondary cases. Among 16715 contacts, overall SAR was 3.6% [95% CI, 3.4-3.9] and symptomatic cases were more infectious than asymptomatic cases (SAR 7.7% vs 2.0%; aRR 3.63 [3.04-4.34]). As compared to infectors aged 19-44 years, children were less infectious (aRR 0.21 [0.07-0.66] for 0-5 years and 0.47 [0.32-0.68] for 6-18 years). Infectors who were confirmed ≥4 days after symptom onset were associated with higher infectiousness (aRR 3.01 [2.11-4.31]). As compared to asymptomatic cases, symptomatic cases were 8.16 [3.29-20.24] times more likely to cause symptomatic infection in their secondary cases. Serial interval had a mean of 5.4 [4.4-6.4] days, and case fatality rate was 2.5% [2.4-2.7] which increased with age. CONCLUSION: We found significant heterogeneity in the individual-level transmissibility of SARS-CoV-2 which could not be explained by the degree of heterogeneity in the underlying number of contacts. To strengthen contact tracing in over-dispersed outbreaks, testing and tracing delays should be minimised and retrospective contact tracing should be implemented. Targeted measures to reduce potential superspreading events should be implemented. Interventions aimed at children might have a relatively small impact on reducing transmission owing to their low symptomaticity and infectivity. We propose that symptomatic cases could cause a snowballing effect on clinical severity and infectiousness across transmission generations; further studies are needed to confirm this finding.

Microbiological and Radiological Perspective of Fungal Rhinosinusitis during the Covid-19 Pandemic: A Prospective Observational Study in A Tertiary Care Centre in Northern India

Radiological investigations are essential for the diagnosis and classification of fungal rhinosinusitis;however, radiological findings might occasionally be misleading. Computed tomography (CT) scan and magnetic resonance imaging (MRI) complement each other, facilitating clinicians to arrive at a diagnosis. Hence, even with the best radiological modalities, correlation between clinical and microbiological findings is crucial for the accurate diagnosis of fungal rhinosinusitis. In addition, the role of traditional methods such as KOH microscopy and culture should be accurately evaluated. To this end, we aimed to diagnose rhinosinusitis with a fungal etiology based on radiological findings and subsequently correlate these findings with those of microbiological techniques, namely culture and KOH microscopy. A total of 57 clinically suspected fungal rhinosinusitis cases were included in the study. Radiological investigations were performed using either CT or MRI. Tissues samples were processed and analyzed using KOH microscopy and culture. The results of the study suggest that using a single method for the diagnosis of fungal rhinosinusitis is inadequate. Rather, the diagnosis should be based on radiological as well as microbiological findings, especially for cases that are clinically ambiguous. [ FROM AUTHOR] Copyright of Journal of Pure & Applied Microbiology is the property of Dr. M. N. Khan and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Development and validation of a questionnaire to assess knowledge, attitude, practices, and concerns regarding COVID-19 vaccination among the general population.

BACKGROUND AND AIMS: There seems to be hesitation in the general population in accepting COVID 19 vaccine because of associated myths and/or misinformation. This study is dedicated to develop and validate a tool to interpret vaccine acceptance and/or hesitancy by assessing the knowledge, attitude, practices, and concerns regarding the COVID vaccine. MATERIAL AND METHODS: Mixed methods study design was used. In phase 1, the questionnaire was developed through literature review, focus group discussion, expert evaluation, and pre-testing. In phase 2, the validity of the questionnaire was obtained by conducting a cross-sectional survey on 201 participants. The construct validity was established via principal component analysis. Cronbach's alpha value was used to assess the reliability of the questionnaire. RESULTS: The 39-item questionnaire to assess the knowledge, attitude, practices, and concerns regarding the COVID-19 vaccine was developed. The Cronbach's alpha value of the questionnaire was 0.86 suggesting a good internal consistency. CONCLUSION: The developed tool is valid to assess the knowledge, attitude, practices and concerns regarding the COVID-19 vaccine acceptance and/or hesitancy. It has the potential utility for healthcare workers and government authorities to further build vaccine literacy.

Impact of COVID-19 on lifestyle-related behaviours- a cross-sectional audit of responses from nine hundred and ninety-five participants from India.

BACKGROUND AND AIMS: The impact of measures taken to contain COVID-19 on lifestyle-related behaviour is undefined in Indian population. The current study was undertaken to assess the impact of COVID-19 on lifestyle-related behaviours: eating, physical activity and sleep behaviour. METHODS: The study is a cross-sectional web-based survey. A validated questionnaire to assess the changes in lifestyle-related behaviour was administered on adults across India using a Google online survey platform. RESULTS: A total of 995 responses (58.5% male, mean age 33.3 years) were collected. An improvement in healthy meal consumption pattern and a restriction of unhealthy food items was observed, especially in the younger population (age <30 years). A reduction in physical activity coupled with an increase in daily screen time was found especially among men and in upper-socio-economic strata. Quarantine induced stress and anxiety showed an increase by a unit in nearly one-fourth of the participants. CONCLUSIONS: COVID-19 marginally improved the eating behaviour, yet one-third of participants gained weight as physical activity declined significantly coupled with an increase in screen and sitting time. Mental health was also adversely affected. A detailed understanding of these factors can help to develop interventions to mitigate the negative lifestyle behaviours that have manifested during COVID-19.

Transmission dynamics of the COVID-19 epidemic in India and modeling optimal lockdown exit strategies.

India imposed one of the world's strictest population-wide lockdowns on March 25, 2020 for COVID-19. We estimated epidemiological parameters, evaluated the effect of control measures on the epidemic in India, and explored strategies to exit lockdown. We obtained patient-level data to estimate the delay from onset to confirmation and the asymptomatic proportion. We estimated the basic and time-varying reproduction number (R0 and Rt) after adjusting for imported cases and delay to confirmation using incidence data from March 4 to April 25, 2020. Using a SEIR-QDPA model, we simulated lockdown relaxation scenarios and increased testing to evaluate lockdown exit strategies. R0 for India was estimated to be 2·08, and the Rt decreased from 1·67 on March 30 to 1·16 on April 22. We observed that the delay from the date of lockdown relaxation to the start of the second wave increases as lockdown is extended farther after the first wave peak-this delay is longer if lockdown is relaxed gradually. Aggressive measures such as lockdowns may be inherently enough to suppress an outbreak; however, other measures need to be scaled up as lockdowns are relaxed. Lower levels of social distancing when coupled with a testing ramp-up could achieve similar outbreak control as an aggressive social distancing regime where testing was not increased.