Seroprevalence of SARS-CoV-2 IgG antibodies in a healthcare setting during the first pandemic wave in Senegal

Ahouidi, Ambroise D.; Anderson, Mark; Diédhiou, Cyrille K.; Dia, Aminata; Mbow, Moustapha; Dia, Yacine Amet; Mboup, Aminata; Gaye, Abdou Magib; Manga, N.M.; Cloherty, Gavin; Mboup, Souleymane

doi:10.1016/j.ijregi.2021.12.008

Cited by 2 publications

(4 citation statements)

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“…conducted a study between June and October 2020. They found that the overall positivity rate was 20.4% and significant geographical differences in seropositivity with a higher seroprevalence in Dakar, around 40% [38]. Then, Talla et al found an adjusted national prevalence of anti-SARS-CoV-2 IgG/IgM in Senegal estimated to be 28.4% between October 24 and November 26, 2020 [39].…”

Section: Discussionmentioning

confidence: 99%

“…The very IgG high seroprevalence could be due to increased exposure to the SARS-CoV-2 virus and the anti-COVID vaccination policy implemented by the authorities. They found that the overall positivity rate was 20.4% and significant geographical differences in seropositivity with a higher seroprevalence in Dakar, around 40% [38].…”

Section: Risk Factors Associated With Sars-covmentioning

confidence: 99%

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Serological Survey in a university community after the fourth wave of COVID-19 in Senegal

Thiam,

Diouara,

Ndiaye

et al. 2024

Preprint

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Cross-sectional survey was conducted to assess the true extent of COVID-19 exposure among students and staff of Polytechnic High School (PHS). Random cluster sampling was carried out between May 19 and August 18, 2022, after the fourth wave of COVID-19 transmission. IgM and IgG SARS-CoV-2 antibodies were screened using WANTAI SARS-CoV-2 ELISA assays. Seroprevalence and descriptive statistics were calculated. Moreover, the associations between seropositivity and different factors (age, gender, preventive, etc.) were determined using logistic regression. A total of 637 participants were recruited, including 563 students, followed by 52 TAS officers, and 22 professors. The median age among was 21 years [18 - 63]. 62.0% of the participants were female, and 36.89% were male, with a male-to-female ratio = 0.59. The overall IgG and IgM seroprevalence were 92% and 6.91% respectively. We found a higher IgM seroprevalence in men than women (9.4% vs. 5.6%) and a lower IgM seroprevalence in (18-25) age group compared to (55-65) years. Low compliance with preventive measures was found with a significant IgM seroprevalence depending on non-respect of social distancing (p = 0.008). IgM seropositivity was associated with Body Mass Indice (BMI) categorized (O.R. 0.238, p = 0.043), ethnic group (O.R. 0.723, p = 0.046) and marital status (O.R. 2.399, p = 0.021). Moreover, IgG seropositivity was associated with vaccination status (O.R. 4.741, p < 0.001). Our study revealed that the majority of students and staff have already been exposed to SARS-CoV-2, which confirms the circulation of SARS-CoV-2 in PHS at the time of the survey. Our results underline the importance of seroepidemiological surveys to estimate the real impact of the COVID-19 pandemic in a community and to monitor disparities in antibody response in the population.

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Section: Discussionmentioning

confidence: 99%

Section: Risk Factors Associated With Sars-covmentioning

confidence: 99%

Serological Survey in a university community after the fourth wave of COVID-19 in Senegal

Thiam,

Diouara,

Ndiaye

et al. 2024

Preprint

View full text Add to dashboard Cite

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“…As early as April 2020, the Africa Centers for Disease Control and Prevention called attention to the lack of SARS-CoV-2 diagnostics in the region (10). Indeed, serological surveys from multiple countries revealed infection burdens much higher than those predicted based on case-based surveillance, an indication of underdiagnosis of COVID-19 cases by diagnostic systems (11)(12)(13). Testing is an integral part of the COVID-19 responses of sub-Saharan African countries (14), and the lack of adequate testing capacity can impede public health efforts.…”

Section: Introductionmentioning

confidence: 99%

“…As early as April 2020, the Africa Centers for Disease Control and Prevention called attention to the lack of SARS-CoV-2 diagnostics in the region (3). Indeed, serological surveys from multiple countries revealed infection burdens much higher than those predicted from case-based surveillance, an indication of underdiagnosis of SARS-CoV-2 cases by diagnostic systems (4–6). Testing is an integral part of the COVID-19 responses of sub-Saharan African countries (7), and the lack of adequate testing capacity is an impediment to public health efforts.…”

Section: Introductionmentioning

confidence: 99%

Leveraging social network topology could improve the efficiency of SARS-CoV-2 epidemic control strategies in resource-limited contexts

Evans

Ramiadantsoa

Garchitorena

et al. 2022

Preprint

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BackgroundSuperspreading infections play an important role in the SARS-CoV-2 pandemic. Superspreading is caused primarily by heterogeneity in social contact rates, and therefore represents an opportunity for targeting surveillance and control via consideration of social network topologies, particularly in resource-limited settings. Yet, it remains unclear how to implement such surveillance and control, espeically when network data is unavailable.MethodsWe evaluated the efficiency of a testing strategy that targeted potential superspreading individuals based on their degree centrality on a social network compared to a random testing strategy in the context of low testing capacity. We simulated SARS-CoV-2 dynamics on two contact networks from rural Madagascar and measured the epidemic duration, infection burden, and tests needed to end the epidemics. In addition, we examined the robustness of this approach when individuals’ true degree centralities were unknown and were instead estimated via readily-available socio-demographic variables.FindingsTargeted testing of potential superspreaders reduced the infection burden by 40-63% at low testing capacities, while requiring between 45-78% fewer tests compared to random testing. Further, targeted testing remained more efficient when the true network topology was unknown and prioritization was based on socio-demographic characteristics.InterpretationIncorporating social network topology into epidemic control strategies is an effective public health strategy for health systems suffering from low testing capacity and can be implemented via socio-demographic proxies when social networks are unknown.FundingThis research was funded by the Agence Nationale de la Recherche, a NIH-SSF-NIFA Ecology and Evolution of Infectious Disease Award (No. 1R01-TW011493-01), and a Duke University Provost’s Collaboratory grant.

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Seroprevalence of SARS-CoV-2 IgG antibodies in a healthcare setting during the first pandemic wave in Senegal

Cited by 2 publications

References 1 publication

Serological Survey in a university community after the fourth wave of COVID-19 in Senegal

Serological Survey in a university community after the fourth wave of COVID-19 in Senegal

Leveraging social network topology could improve the efficiency of SARS-CoV-2 epidemic control strategies in resource-limited contexts

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