Logistics Workers Are a Key Factor for SARS-CoV-2 Spread in Brazilian Small Towns: Case-Control Study.

BACKGROUND: Data on how SARS-CoV-2 enters and spreads in a population are essential for guiding public policies. OBJECTIVE: This study seeks to understand the transmission dynamics of SARS-CoV-2 in small Brazilian towns during the early phase of the epidemic and to identify core groups that can serve as the initial source of infection as well as factors associated with a higher risk of COVID-19. METHODS: Two population-based seroprevalence studies, one household survey, and a case-control study were conducted in two small towns in southeastern Brazil between May and June 2020. In the population-based studies, 400 people were evaluated in each town; there were 40 homes in the household survey, and 95 cases and 393 controls in the case-control study. SARS-CoV-2 serology testing was performed on participants, and a questionnaire was applied. Prevalence, household secondary infection rate, and factors associated with infection were assessed. Odds ratios (ORs) were calculated by logistic regression. Logistics worker was defined as an individual with an occupation focused on the transportation of people or goods and whose job involves traveling outside the town of residence at least once a week. RESULTS: Higher seroprevalence of SARS-CoV-2 was observed in the town with a greater proportion of logistics workers. The secondary household infection rate was 49.1% (55/112), and it was observed that in most households (28/40, 70%) the index case was a logistics worker. The case-control study revealed that being a logistics worker (OR 18.0, 95% CI 8.4-38.7) or living with one (OR 6.9, 95% CI 3.3-14.5) increases the risk of infection. In addition, having close contact with a confirmed case (OR 13.4, 95% CI 6.6-27.3) and living with more than four people (OR 2.7, 95% CI 1.1-7.1) were also risk factors. CONCLUSIONS: Our study shows a strong association between logistics workers and the risk of SARS-CoV-2 infection and highlights the key role of these workers in the viral spread in small towns. These findings indicate the need to focus on this population to determine COVID-19 prevention and control strategies, including vaccination and sentinel genomic surveillance.

Immunoprophylaxis using polypeptide chimera vaccines plus adjuvant system promote Th1 response controlling the spleen parasitism in hamster model of visceral leishmaniasis.

In recent years, several advances have been observed in vaccinology especially for neglected tropical diseases (NTDs). One of the tools employed is epitope prediction by immunoinformatic approaches that reduce the time and cost to develop a vaccine. In this scenario, immunoinformatics is being more often used to develop vaccines for NTDs, in particular visceral leishmaniasis (VL) which is proven not to have an effective vaccine yet. Based on that, in a previous study, two predicted T-cell multi-epitope chimera vaccines were experimentally validated in BALB/c mice to evaluate the immunogenicity, central and effector memory and protection against VL. Considering the results obtained in the mouse model, we assessed the immune response of these chimeras inMesocricetus auratushamster, which displays, experimentally, similar pathological status to human and dog VL disease. Our findings indicate that both chimeras lead to a dominant Th1 response profile, inducing a strong cellular response by increasing the production of IFN-γ and TNF-α cytokines associated with a decrease in IL-10. Also, the chimeras reduced the spleen parasite load and the weight a correlation between protector immunological mechanisms and consistent reduction of the parasitic load was observed. Our results demonstrate that both chimeras were immunogenic and corroborate with findings in the mouse model. Therefore, we reinforce the use of the hamster as a pre-clinical model in vaccination trials for canine and human VL and the importance of immunoinformatic to identify epitopes to design vaccines for this important neglected disease.

Successive Pandemic Waves with Different Virulent Strains and the Effects of Vaccination for SARS-CoV-2.

One hundred years after the flu pandemic of 1918, the world faces an outbreak of a new severe acute respiratory syndrome, caused by a novel coronavirus. With a high transmissibility, the pandemic has spread worldwide, creating a scenario of devastation in many countries. By the middle of 2021, about 3% of the world population had been infected and more than 4 million people had died. Different from the H1N1 pandemic, which had a deadly wave and ceased, the new disease is maintained by successive waves, mainly produced by new virus variants and the small number of vaccinated people. In the present work, we create a version of the SIR model using the spatial localization of persons, their movements, and considering social isolation probabilities. We discuss the effects of virus variants, and the role of vaccination rate in the pandemic dynamics. We show that, unless a global vaccination is implemented, we will have continuous waves of infections.

Severe airport sanitarian control could slow down the spreading of COVID-19 pandemics in Brazil.

BACKGROUND: We investigated a likely scenario of COVID-19 spreading in Brazil through the complex airport network of the country, for the 90 days after the first national occurrence of the disease. After the confirmation of the first imported cases, the lack of a proper airport entrance control resulted in the infection spreading in a manner directly proportional to the amount of flights reaching each city, following the first occurrence of the virus coming from abroad. METHODOLOGY: We developed a Susceptible-Infected-Recovered model divided in a metapopulation structure, where cities with airports were demes connected by the number of flights. Subsequently, we further explored the role of the Manaus airport for a rapid entrance of the pandemic into indigenous territories situated in remote places of the Amazon region. RESULTS: The expansion of the SARS-CoV-2 virus between cities was fast, directly proportional to the city closeness centrality within the Brazilian air transportation network. There was a clear pattern in the expansion of the pandemic, with a stiff exponential expansion of cases for all the cities. The more a city showed closeness centrality, the greater was its vulnerability to SARS-CoV-2. CONCLUSIONS: We discussed the weak pandemic control performance of Brazil in comparison with other tropical, developing countries, namely India and Nigeria. Finally, we proposed measures for containing virus spreading taking into consideration the scenario of high poverty.