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Heterogeneous patterns of COVID-19 transmission in an Urban set up – sero-epidemiological survey data from Ujjain, Madhya Pradesh (a central Indian city)

In the wake of rising number of SARS-CoV-2 cases, the Government of India had placed mass-quarantine measures, termed as “lockdown” measures from end-March 2020. The subsequent phase-wise relaxation from July 2020 led to a surge in the number of cases. This necessitated an understanding of the true...

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Detalles Bibliográficos
Autores principales: Joshi, Ankur, Shankar, Prem, Chatterjee, Anirban, Singh, Jitendra, Pakhare, Abhijit, Yadav, Kriti, Shrivas, Arti, Maurya, Anand Kumar, Nagi, Raunaq Singh, Biswas, Debasis, Kokane, Arun M., Singh, Sarman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8182372/
https://www.ncbi.nlm.nih.gov/pubmed/34136600
http://dx.doi.org/10.1016/j.dib.2021.107169
Descripción
Sumario:In the wake of rising number of SARS-CoV-2 cases, the Government of India had placed mass-quarantine measures, termed as “lockdown” measures from end-March 2020. The subsequent phase-wise relaxation from July 2020 led to a surge in the number of cases. This necessitated an understanding of the true burden of SARS-CoV-2 in the community. Consequently, a sero-epidemiological survey was carried out in the central Indian city of Ujjain, Madhya Pradesh. This article details the processes of data acquisition, compilation, handling, and information derivation from the survey. Information on socio-demographic and serological variables were collected from 4,883 participants using a multi-stage stratified random sampling method. Appropriate weightage was calculated for each participant as sampling fraction derived from Primary Sampling Unit (PSU), Secondary Sampling Unit (SSU) and Tertiary Sampling Unit (TSU). The weightage was then applied to the data to adjust the findings at population level. The comprehensive and robust methodology employed here may act as a model for similar future endeavours. At the same time, the dataset can also be relevant for researchers in fields such as data science, epidemiology, virology and earth modelling.