Prevalence of SARS-CoV-2 infection among urban cleaning and solid waste management workers during transmission of the Omicron variant in Brazil.

This study estimated the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in urban cleaning and solid waste management workers during the transmission of the Omicron variant in one of the poorest regions of Brazil (the state of Sergipe). Nasopharyngeal swabs were collected from 494 workers, and the presence of SARS-CoV-2 RNA was tested by quantitative reverse-transcriptase polymerase chain reaction. Data on socio-demographic characteristics, comorbidities, vaccination status, mask use, and use of public transport to commute to the workplace were collected. The prevalence with a 95% confidence interval (CI) was calculated from the proportion of SARS-CoV-2 positive cases among the total number of individuals tested. The prevalence ratio (PR) with a 95% CI was the measure of association used to evaluate the relationship between SARS-CoV-2 infection and the exposure variables. The prevalence of SARS-CoV-2 infection was 22.5% (95% CI, 19.0 to 26.4). Individuals under the age of 40 had a higher prevalence of infection (PR, 1.53; 95% CI, 1.03 to 2.30) as well as those who did not believe in the protective effect of vaccines (PR, 1.78; 95% CI, 1.05 to 2.89). Our results indicate the need for better guidance on preventive measures against coronavirus disease 2019 among urban cleaning and solid waste management workers.

The increase in SARS-CoV-2 lineages during 2020-2022 in a state in the Brazilian Northeast is associated with a number of cases.

SARS-CoV-2 has caused a high number of deaths in several countries. In Brazil, there were 37 million confirmed cases of COVID-19 and 700,000 deaths caused by the disease. The population size and heterogeneity of the Brazilian population should be considered in epidemiological surveillance due to the varied tropism of the virus. As such, municipalities and states must be factored in for their unique specificities, such as socioeconomic conditions and population distribution. Here, we investigate the spatiotemporal dispersion of emerging SARS-CoV-2 lineages and their dynamics in each microregion from Sergipe state, northeastern Brazil, in the first 3 years of the pandemic. We analyzed 586 genomes sequenced between March 2020 and November 2022 extracted from the GISAID database. Phylogenetic analyses were carried out for each data set to reconstruct evolutionary history. Finally, the existence of a correlation between the number of lineages and infection cases by SARS-CoV-2 was evaluated. Aracaju, the largest city in northeastern Brazil, had the highest number of samples sequenced. This represented 54.6% (320) of the genomes, and consequently, the largest number of lineages identified. Studies also analyzed the relationship between mean lineage distributions and mean monthly infections, daily cases, daily deaths, and hospitalizations of vaccinated and unvaccinated patients. For this, a correlation matrix was created. Results revealed that the increase in the average number of SARS-CoV-2 variants was related to the average number of SARS-CoV-2 cases in both unvaccinated and vaccinated individuals. Thus, our data indicate that it is necessary to maintain epidemiological surveillance, especially in capital cities, since they have a high rate of circulation of resident and non-resident inhabitants, which contributes to the dynamics of the virus.

Magnitude of visceral leishmaniasis and HIV coinfection and association with social determinants of health in the Northeast region of Brazil: a retrospective, spatiotemporal model (2010-2018).

The Northeast region of Brazil (NRB) includes the states with the highest prevalence of visceral leishmaniasis (VL), as well as those with significant increases in HIV cases. This study aims to analyze the spatiotemporal patterns of VL-HIV coinfection and its association with the social determinants of health (SDH) in the NRB. Time trend analysis and Bayesian spatial statistical inferences, Moran's autocorrelation, and retrospective space-time scanning were performed. Spatial regression modelling was used to build an explanatory model for the occurrence of VL-HIV coinfection within NRB. A total of 1550 cases of VL-HIV coinfection were confirmed. We observed a higher prevalence among males (1232; 83%), individuals aged from 20 to 59 years (850; 54.8%), non-white skin color (1,422; 91.7%), and with low education (550; 35.48%). NRB showed an increasing and significant trend in the detection rate of coinfection (APC, 5.3; 95% CI, 1.4 to 9.4). The states of Maranhão and Piauí comprised the high-risk cluster. The SDH that most correlated with the occurrence of coinfection were poor housing, low income, and low education. VL-HIV is dispersed in the NRB but chiefly affects states with greater social vulnerability. Taken together, these findings reinforce the necessity to implement surveillance strategies that will contribute to the reduction of cases in these populations.