SARS-CoV-2-Specific IgG and IgA response in maternal blood and breastmilk of vaccinated naïve and convalescent lactating participants.

Background: Recent studies have shown the presence of SARS-CoV-2-specific antibodies in the milk of breastfeeding mothers vaccinated with mRNA and convalescent. However, limited information is available in lactating women receiving other vaccine platforms used in developing countries, such as the inactivated SARS-CoV-2 vaccine BBIBP-CorV (Sinopharm) and the non-replicating adenovirus vaccines Sputnik V (Gamaleya Institute) and ChAdOx1-S (Oxford AstraZeneca). Methods: Here, we evaluated anti-SARS-CoV-2 IgG and IgA levels in both serum and milk samples using a longitudinal and a cross-sectional cohort of 208 breastfeeding vaccinated women from Argentina with or without previous SARS-CoV-2 infection. Results: The analysis showed that IgA levels remain constant in serum and milk of breastfeeding mothers between the first and second doses of vector-based vaccines (Sputnik V and ChAdOx1-S). After the second dose, anti-spike IgA was found positive in 100% of the serum samples and in 66% of breastmilk samples. In addition, no significant differences in milk IgA levels were observed in participants receiving BBIBP-CorV, Sputnik V or ChAdOx1-S. IgG levels in milk increased after the second dose of vector-based vaccines. Paired longitudinal samples taken at 45 and 120 days after the second dose showed a decrease in milk IgG levels over time. Study of IgA levels in serum and milk of vaccinated naïve of infection and vaccinated-convalescent breastfeeding participants showed significantly higher levels in vaccinated-convalescent than in participants without previous infection. Conclusion: This study is relevant to understand the protection against SARS-CoV-2 by passive immunity in newborns and children who are not yet eligible to receive vaccination.

[Evaluation of interventions during the COVID-19 pandemic: development of a model based on subpopulations with different contact rates]. / Evaluación de intervenciones durante la pandemia COVID-19: desarrollo de un modelo basado en subpoblaciones con distintas tasas de contacto.

Although multiple attempts have been made to mathematically model the current epidemic of SARS-CoV-2, the causative agent of coronavirus disease 2019 (COVID-19), few models have been conceived as accessible interactive tools for users from various backgrounds. The goal of this study was to develop a model that took into account the heterogeneity in contact rates within the population and to implement it in an accessible application allowing to estimate the impact of possible interventions based on available information. An extended version of the Susceptible-Exposed-Infected-Resistant (SEIR) model, named SEIR-HL, was developed, assuming a population divided into two subpopulations, with different contact rates. Additionally, a formula for the calculation of the basic reproduction number (R0) for a population divided into n subpopulations was proposed, where the contact rates for each subpopulation can be distinguished according to contact type or context. The predictions made by SEIR-HL were compared to those of SEIR, showing that the heterogeneity in contact rates can dramatically affect the dynamics of simulations, even when run from the same initial conditions and with the same parameters. SEIR-HL was used to predict the effect on the epidemic evolution of the displacement of individuals from high-contact positions to low-contact positions. Lastly, by way of example, SEIR-HL was applied to the analysis of the SARS-CoV-2 epidemic in Argentina and an example of the application of the R0 formula was also developed. Both the SEIR-HL model and an R0 calculator were computerized and made available to the community.