COVID-19: District level vulnerability assessment in India.

OBJECTIVES: COVID-19 Pandemic has brought a threatening challenge to the world and as well as for Indian society and economy. In India, it has become a public health disaster and its' intensity increasing continuously. For the disaster risk reduction, and capacity building against the COVID-19 pandemic understanding of the relationship between socio-environmental conditions with the pandemic is very necessary. The objective of the present work is to construct a socio-environmental vulnerability index of the potential risk of community spread of COVID-19 using socio-economic and environmental variables. METHODOLOGY: In this, cross-sectional study principal component analyses have been used to drive SoEVI. 4 uncorrelated sub-index has been extracted from 16 sub-indicators which reflects 59% of the variance. Aggregation of 4 Sub-Index has been done to obtain the final vulnerability Index. RESULTS: Results show that there is spatial variability in vulnerability based on environmental and socio-economic conditions. Districts of north and central India found more vulnerable then south India. Statistical significance has been tested using regression analysis, positive relation has been found between vulnerability index and confirmed and active cases. CONCLUSION: The vulnerability index has highlighted environmentaly and socioeconomicallybackward districts. These areas will suffer more critical problems against COVID-19 pandemic for their socio-environmental problem.

Comparison of SARS-CoV-2 diagnosis by rapid antigen detection kit with RT-qPCR in a tertiary care setup in North Eastern India.

PURPOSE: Real time reverse transcriptase polymerase chain reaction (RT-qPCR) is still considered a gold standard for the diagnosis of COVID-19. However, due to several limitations, use of RT-qPCR is limited in a resource poor setting like North East India. Rapid antigen detection testing kit has revolutionized the diagnosis and management of COVID-19 in India. However, conflicting reports exist regarding the efficacy of the kits for diagnosis of COVID-19. This study aims to highlight the performance of Standard Q COVID-19® Antigen detection kit (SD Biosensor) compared with RT-qPCR in the setup of North East India. METHODS: Nasopharyngeal and oropharyngeal swab samples were collected from consenting patients attending the flu clinic in the period from 1st July to December 31, 2020. Samples were transferred to Viral Research and Diagnostic Laboratory (VRDL) for RT-qPCR test. Antigen detection from the patient samples were undertaken using Standard Q ® COVID-19 antigen detection kit (SD Biosensor, Republic of Korea). Data were then analyzed for comparison between RT-qPCR and antigen kit results. RESULTS: During the study period, 189 samples were collected, out of which 119 were positive by RT-qPCR. Out of 119 positive samples, calculated sensitivity and specificity of the rapid antigen kit was 63% and 100% respectively. Sensitivity and diagnostic accuracy increases in symptomatic patients as compared to asymptomatic patients. Cohen's Kappa coefficient showed a moderate association (0.6) between the kit and RT-qPCR test. The kit performed optimally at a CT value of ≤32.5 for N gene with a predicted sensitivity of 77.3% and specificity of 93.3%. CONCLUSION: The study shows an overall acceptable sensitivity and specificity of the testing kit, with a better performance in symptomatic patients. The association of the kit result is moderate with the results obtained in RT-qPCR. In this study, the rapid antigen test kit performed optimally at N gene qRT PCR cut off value of ≤32.5.

SEIRD model to study the asymptomatic growth during COVID-19 pandemic in India.

According to the current perception, symptomatic, presymptomatic and asymptomatic infectious persons can infect the healthy population susceptible to the SARS-CoV-2. More importantly, various reports indicate that the number of asymptomatic cases can be several-fold higher than the reported symptomatic cases. In this article, we take the reported cases in India and various states within the country till September 1, as the specimen to understand the progression of the COVID-19. Employing a modified SEIRD model, we predict the spread of COVID-19 by the symptomatic as well as asymptomatic infectious population. Considering reported infection primarily due to symptomatic, we compare the model predicted results with the available data to estimate the dynamics of the asymptomatically infected population. Our data indicate that in the absence of the asymptomatic infectious population, the number of symptomatic cases would have been much less. Therefore, the current progress of the symptomatic infection can be reduced by quarantining the asymptomatically infectious population via extensive or random testing. This study is motivated strictly toward academic pursuit; this theoretical investigation is not meant for influencing policy decisions or public health practices.

COVID-19: District level vulnerability assessment in India

Objectives: COVID-19 Pandemic has brought a threatening challenge to the world and as well as for Indian society and economy. In India, it has become a public health disaster and its' intensity increasing continuously. For the disaster risk reduction, and capacity building against the COVID-19 pandemic understanding of the relationship between socio-environmental conditions with the pandemic is very necessary. The objective of the present work is to construct a socio-environmental vulnerability index of the potential risk of community spread of COVID-19 using socio-economic and environmental variables. Methodology: In this, cross-sectional study principal component analyses have been used to drive SoEVI. 4 uncorrelated sub-index has been extracted from 16 sub-indicators which reflects 59% of the variance. Aggregation of 4 Sub-Index has been done to obtain the final vulnerability Index. Results: Results show that there is spatial variability in vulnerability based on environmental and socio-economic conditions. Districts of north and central India found more vulnerable then south India. Statistical significance has been tested using regression analysis, positive relation has been found between vulnerability index and confirmed and active cases. Conclusion: The vulnerability index has highlighted environmentaly and socioeconomicallybackward districts. These areas will suffer more critical problems against COVID-19 pandemic for their socio-environmental problem.