Selected article for: "non response rate and sample size"

Author: Kshatri, Jaya Singh; Bhattacharya, Dr. Debdutta; Kanungo, Srikanta; Giri, Sidhartha; Palo, Subrata Kumar; Parai, Debaprasad; Turuk, Jyotirmayee; Mansingh, Asit; Choudhury, Hariram; Dash, Girish Chandra; Mishra, Niranjan; Satapathy, Durga Madhab; Sahoo, Sanjaya Kumar; Pati, Sanghamitra; team, - RMRC Odisha Serosurvey
Title: Findings from serological surveys (in August 2020) to assess the exposure of adult population to SARS Cov-2 infection in three cities of Odisha, India
  • Cord-id: r90wyczk
  • Document date: 2020_1_1
  • ID: r90wyczk
    Snippet: BackgroundThere is always an uncertainty of epidemiological, serological infectivity and virulence of the emerging novel coronavirus. Antibody test can be used for assessing whether immunity has developed in the infected person after 5-7 days of illness and understand cumulative exposure levels to the infection, make inferences on the actual burden of infection, its geographical spread, effect on specific demographic/risk groups, gaps in testing and infection fatality rates. ObjectiveTo estimate
    Document: BackgroundThere is always an uncertainty of epidemiological, serological infectivity and virulence of the emerging novel coronavirus. Antibody test can be used for assessing whether immunity has developed in the infected person after 5-7 days of illness and understand cumulative exposure levels to the infection, make inferences on the actual burden of infection, its geographical spread, effect on specific demographic/risk groups, gaps in testing and infection fatality rates. ObjectiveTo estimate and compare the sero-prevalence, hidden prevalence and determine the demographic risk factors associated with SARS-CoV-2 infection among adults in three largest cities of Odisha, India. MethodologyThis was a population based cross sectional serological survey carried out in August 2020 in the three largest cities of the state of Odisha. Sample size per city was estimated to be 1500 and participants were enrolled from the community using multi-stage random sampling from 25 clusters from each city. Data was collected using ODK based tools by household visits and 3-4 ml of blood samples were collected after informed consent. Samples were transported to testing lab where Serum was separated and tested for anti-SARS CoV-2 antibodies using automated CLIA platform. Statistical analysis was done using R-software packages. ResultsA total of 4146 participants from the 3 cities of Bhubaneswar (BBS), Berhampur (BAM) and Rourkela (RKL) participated. A total of 5635 households were approached and the average non response rate in the community was 17.4%. The gender weighted seroprevalence across the three cities was 20.78% (95% CI: 19.56%-22.05%). Seroprevalence was highest in BAM at 31.14% (95% CI: 28.69-33.66%) followed by 24.59% (95% CI: 22.39-26.88%) in RKL and 5.24% (95% CI: 4.10-6.58%) in BBS. While females reported a higher seroprevalence (22.8%) as compared to males (18.8%), there was no significant difference in seroprevalence across age groups. A majority of the seropositive participants were asymptomatic (93.87%). Among those who reported symptoms, the most common symptom was fever (68.89%) followed by cough (46.06%) and myalgia (32.67%). The case to infection ratio on the date of serosurvey was 1: 6.6 in BBS, 1:61 in BAM and 1:29.8 in RKL. ConclusionThe study found a high seroprevalence against COVID-19 in urban Odisha as well as high numbers of asymptomatic infections.

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