Seroprevalence of Coronavirus Disease 2019 (COVID-19) Antibodies in a Vulnerable Neighbourhood, Buenos Aries Argentina

SARS-CoV-2 Clinical Trial

Official title:

Seroprevalence of Antibodies to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2) in a Vulnerable Neighbourhood, Buenos Aries Argentina

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT04472078
• Other study ID #: 1831
• Status: Completed
• Start date: June 10, 2020
• Est. completion date: December 11, 2020

Study information

• Verified date: December 2020
• Source: Hospital Italiano de Buenos Aires
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational [Patient Registry]

Clinical Trial Summary

Background The study aimed to establish the seroprevalence of SARS-COV-2 in an Argentinian slum three months after the first case was reported.

Methods Between June 10th and July 1st, a cross-sectional design was carried out on people over 14 years old, selected from a probabilistic sample of households. Finger prick puncture ELISA test

Description:

A community-level seroprevalence survey was conducted in a cross-sectional design during a Participatory Action Research (PAR).

Starter PAR team: researcher who developed the Elisa Test, virologist that perform the analysis of the test and physician that served as volunteer field epidemiologist at the surveillance system (DetectAr Barrio 31) offered technical cooperation to test people experiencing homelessness.

PAR-First step: A sample for convenience of homeless people was tested during 3 days in a popular dining room managed by a non-governmental organization. Samples were collected by a DetectAr nurse and a volunteer epidemiologist.

PAR-Second step: feasibility was determined by the DetectAr coordinators of the Community Health Division of the Ministry of Health and the 12 health community workers (HCWs) when two volunteer epidemiologists from a University Institute explained the field organization (sample technique, data collection and database entry) for obtaining a probabilistic sample of residents. The PAR process was a cornerstone for reaching the sample size.

PAR-Third step: A cross-sectional study for seroprevalence survey was carried out.

Sample size and sample method Sample size was calculated for a seroprevalence of 5% according to evidence. A two-stage random sampling method was applied. First level: sector of the slum, Second level: geographical areas determined by the Department of Statistic and Census. Thirty houses were selected at this level. People over 14 years old were tested at the front door of their houses.

Serological test An enzyme linked immunosorbent assay [ELISA] developed in Argentina, by a laboratory in Buenos Aires, Argentina, was used. Performance characteristics are a high specificity (>95%) and a high sensibility (>95%) for SARS-COV-2 IgG. The test detects antibodies against two viral antigens, trimeric spike and the receptor binding domain (RBD) of the spike. Viral proteins were expressed in human cells. This kit has obtained regulatory approval by Argentina's national drug regulatory agency (ANMAT, National Administration for Drugs, Food and Medical Devices)[. Blood samples were collected in a capillary tube from a finger prick, taken at the front door of each house. All HCWs were trained and epidemiological data was entered in a database. Samples were processed and analyzed at the virology laboratory in a pediatric hospital of Buenos Aires.

Statistical analysis To obtain the weighted prevalence, sample dataset was expanded to that of the last census by 3 factors: at neighborhood level, at household level and at individual level. The calculation of expansion factors at the household level is the inverse of the joint probability of selecting the last sampling unit (a household). The expansion factors at the household level imply three types of adjustments. The first one is related with non-response (given that some households did not want to answer the survey); the second one corresponds to the projection of sample to the entire population, and the third one to calibration techniques with a final adjustment by groups of age and gender, using external information from population census. Therefore, calibration variables were people 14 year-old or more, grouped by sex and by intervals of age: 14-30; 31-45; 46-59; 60 and more.

Prevalence of IgG antibodies were adjusted using sampling weights and post-stratification to allow for differences in non-response rates based on age group, sex, and census-tract income.

As household members share exposure to COVID-19, thus the outcome (prevalence of COVID-19 IgG) should show some correlation within the household. To test clustering effect, a random effects logistic regression model (multilevel model) was applied as it includes the variation between clusters explicitly in the likelihood and therefore takes account of intracluster correlation.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 873
• Est. completion date: December 11, 2020
• Est. primary completion date: June 26, 2020
• Accepts healthy volunteers: No
• Gender: All
• Age group: 14 Years and older

Eligibility

Inclusion Criteria:

• All subjects of 14 years or more who accept to be test

Exclusion Criteria:

• none

Related Conditions & MeSH terms

• Coronavirus Infections
• SARS-CoV-2

Intervention

Diagnostic Test:
• Serological Assay or IgG for SARS-CoV-2
Serological Assay for detection of IgG for SARS-CoV-2

Locations

Country	Name	City	State
Argentina	Hospital de Niños Ricardo Gutierrez	Buenos Aires	Caba

Sponsors (3)

Lead Sponsor	Collaborator
Hospital Italiano de Buenos Aires	Hospital de Niños R. Gutierrez de Buenos Aires, Salud Comunitaria Ministerio de Salud GCBA

Country where clinical trial is conducted

Argentina, 

References & Publications (9)

Aarts E, Verhage M, Veenvliet JV, Dolan CV, van der Sluis S. A solution to dependency: using multilevel analysis to accommodate nested data. Nat Neurosci. 2014 Apr;17(4):491-6. doi: 10.1038/nn.3648. Epub 2014 Mar 26. — View Citation

Buckley RM. Targeting the World's Slums as Fat Tails in the Distribution of COVID-19 Cases. J Urban Health. 2020 Jun;97(3):358-364. doi: 10.1007/s11524-020-00450-w. — View Citation

Corburn J, Vlahov D, Mberu B, Riley L, Caiaffa WT, Rashid SF, Ko A, Patel S, Jukur S, Martínez-Herrera E, Jayasinghe S, Agarwal S, Nguendo-Yongsi B, Weru J, Ouma S, Edmundo K, Oni T, Ayad H. Slum Health: Arresting COVID-19 and Improving Well-Being in Urban Informal Settlements. J Urban Health. 2020 Jun;97(3):348-357. doi: 10.1007/s11524-020-00438-6. — View Citation

Galbraith S, Daniel JA, Vissel B. A study of clustered data and approaches to its analysis. J Neurosci. 2010 Aug 11;30(32):10601-8. doi: 10.1523/JNEUROSCI.0362-10.2010. — View Citation

Moen EL, Fricano-Kugler CJ, Luikart BW, O'Malley AJ. Analyzing Clustered Data: Why and How to Account for Multiple Observations Nested within a Study Participant? PLoS One. 2016 Jan 14;11(1):e0146721. doi: 10.1371/journal.pone.0146721. eCollection 2016. — View Citation

Pereira RJ, Nascimento GNLD, Gratão LHA, Pimenta RS. The risk of COVID-19 transmission in favelas and slums in Brazil. Public Health. 2020 Jun;183:42-43. doi: 10.1016/j.puhe.2020.04.042. Epub 2020 May 8. — View Citation

Sood N, Simon P, Ebner P, Eichner D, Reynolds J, Bendavid E, Bhattacharya J. Seroprevalence of SARS-CoV-2-Specific Antibodies Among Adults in Los Angeles County, California, on April 10-11, 2020. JAMA. 2020 Jun 16;323(23):2425-2427. doi: 10.1001/jama.2020.8279. — View Citation

Theel ES, Slev P, Wheeler S, Couturier MR, Wong SJ, Kadkhoda K. The Role of Antibody Testing for SARS-CoV-2: Is There One? J Clin Microbiol. 2020 Jul 23;58(8). pii: e00797-20. doi: 10.1128/JCM.00797-20. Print 2020 Jul 23. Review. — View Citation

Zhang CH, Schwartz GG. Spatial Disparities in Coronavirus Incidence and Mortality in the United States: An Ecological Analysis as of May 2020. J Rural Health. 2020 Jun;36(3):433-445. doi: 10.1111/jrh.12476. Epub 2020 Jun 16. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	to establish the seroprevalence of SARS-CoV-2	Prevalence of positive IgG for SARS-CoV-2	up to 20 weeks

External Links

•   "Herd Immunity": A Rough Guide
•   Community-level Seroprevalence Surveys
•   COVID-19 reagents
•   Household and population census: villas 31 and 31 bis, City of Buenos Aires 2009
•   Participatory action research in health systems
•   Prevalence of SARS-CoV-2 in Spain (ENE-COVID): a nationwide, population-based seroepidemiological study.
•   Seroprevalence of anti-SARS-CoV-2 IgG antibodies in Geneva, Switzerland (SEROCoV-POP): a population-based study.
•   Seroprevalence of SARS-CoV-2 in Hong Kong and in residents evacuated from Hubei province, China: a multicohort study.
•   Studies on the processes of social and urban integration in three Buenos Aires slums
•   Systemic Facilitation of Collective Processes: Supporting Creativity and Participative Processes in Groups, Communities and Networks
•   The Color of Coronavirus: COVID-19 Deaths by Race and Ethnicity in the U.S.