The aim of this observational study was to develop, with the intended users, an epidemic surveillance and response system that will be effective, sensitive, coordinated and appropriate. The STREESCO project aims to * Implement active epidemiological surveillance of suspected cases in Benin at strategic sites in accordance with the World Health Organization (WHO) protocol, in support of the national strategy for responding to the CoVID-19 virus. * To strengthen this national strategy by developing a clinico-epidemiological surveillance system in remote areas of Benin (health centre approach) and Burkina Faso (population survey approach). * To gain a better understanding of the dynamics of the epidemic and its parameters in Africa thanks to a modern biostatistical and geo-epidemiological analysis of the data collected as part of this project.
Within the framework of the health systems set up by the Benin health authorities, the project aims to develop, with the intended users, an epidemic surveillance and response system that will be effective, sensitive, coordinated and adapted to a context where resources are limited. Following the start of data collection on 01 March 2021, new reforms to the response strategy against CoVID-19 in Benin have led the investigators to opt for a new strategy in order to meet the objectives of the study. The epidemiological surveillance system will be adapted to the reforms, and data collected and processed prospectively on the dynamics of the epidemic will be collected in CoVID-19 screening centres and in public and private health centres. This is the scientific data needed to issue an early warning signal and enable the healthcare system to respond appropriately. The information system will be based on (i) epidemiological surveys in the field, (ii) virological, serological and antigenic tests, (iii) indicators that will enable action to be monitored, adaptation to the epidemic to be assessed and the response capacity of health structures to be controlled. Analysis (biostatistics, geo-epidemiology) of the data collected will provide useful knowledge for a better understanding of the dynamics of the epidemic. Finally, the project will encourage collaboration between African and European researchers and strengthen the capacity of African institutions to set up an epidemic surveillance system.
Study Type
OBSERVATIONAL
Enrollment
7,000
Institut de Recherche Clinique du Bénin
Abomey-Calavi, Atlantique Department, Benin
Proportion of subjects infected with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) by strategic sites (suspected cases, contact cases)
Total number of subjects with a positive COVID-19 test divided by the total number of volunteers tested in the study.
Time frame: 9 months
Average number of contact cases per person infected with SARS-CoV-2 across all the study sites was as follows
Identify the number of contact cases per subject testing positive for SARS-CoV-2 infection at each of the strategic sites.
Time frame: 9 months
Factors associated with SARS-CoV-2 infection in volunteers screened at 03 strategic sites
Multivariate logistic regression model on sociodemographic, anthropometric, clinical and environmental characteristics of volunteer subjects screened for SARS-CoV-2 infection
Time frame: 9 months
Clusters of cases in the area of each strategic site (radius, period, relative risk)
Analysis of the spatial distribution of positive cases of SARS-CoV-2 infection on each of the strategic sites
Time frame: 9 months
Intra-district incidence rate on the 03 strategic sites
Number of positive cases for SARS-CoV-2 infection divided by the total number of the population multiplied by 1000.
Time frame: 9 months
Environmental factors associated with incidence rates and hotspots
Binomial mixed generalized additive model (GAMM)
Time frame: 9 months
Basic reproduction number for each strategic site and overall
Bayesian approach to quantify transmissibility over time during the epidemic at each site and overall.
Time frame: 9 months
Proportion of health workers infected with SARS-CoV-2 by strategic sites
Total number of health workers with a positive COVID-19 test divided by the total number of health workers tested in the study.
Time frame: 9 months
Factors associated with SARS-CoV-2 infection in health workers at 03 strategic sites
Multivariate logistic regression model on sociodemographic, anthropometric, clinical and environmental characteristics, prevention and control measures among health workers for SARS-CoV-2 infection.
Time frame: 9 months
Seroprevalence of SARS-CoV-2 infection among pregnant women in the 3rd trimester in maternity wards of strategic study sites
Number of pregnant women with a positive Rapid Diagnostic Test (RDT) divided by the total number of pregnant women tested during the study.
Time frame: 3 months
Factors associated with SARS-CoV-2 sero-infection in pregnant women in the 3rd trimester at 03 strategic sites
Multivariate logistic regression model on sociodemographic, anthropometric, clinical, linked to the course of pregnancy and vaccination status characteristics in pregnant women in the 3rd trimester at 03 strategic sites
Time frame: 3 months
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