Corrigendum: Impact of the COVID-19 pandemic on the diagnosis of tuberculosis in Brazil: Is the WHO end TB strategy at risk?

[This corrects the article DOI: 10.3389/fphar.2022.891711.].

COVID-19 risk areas associated with social vulnerability in northeastern Brazil: an ecological study in 2020.

INTRODUCTION: COVID-19 is a major public health concern in this century. The causative agent SARS-CoV-2, is highly contagious and spreads continuously across territories. Spatial analysis is of enormous importance in the process of understanding the disease and its transmission mechanisms. We aimed to identify the risk areas for COVID-19 and analyze their association with social vulnerability in Maceió, Alagoas. The study was conducted in 2020. METHODOLOGY: This is an ecological study to evaluate the incidence, mortality and case fatality rate of COVID-19 and their relationship with 12 indicators of human development and social vulnerability. Multivariate and spatial statistics were applied. A 95% confidence interval and a 5% confidence level were considered. RESULTS: The spatial scan statistic revealed the existence of six high-risk clusters for the incidence of COVID-19. The regression model showed that social indicators, such as literacy of people, residents of private households, households with more than four residents, and resident brown population, were associated with COVID-19 transmission in Maceió-AL. The disease affected localities whose populations are exposed to a context of intense socioeconomic vulnerability. CONCLUSIONS: Based on the results, it is necessary to adopt measures that take into account the social determinants of health in order to minimize the damage caused by the pandemic.

Spatiotemporal Pattern of COVID-19-Related Mortality during the First Year of the Pandemic in Brazil: A Population-based Study in a Region of High Social Vulnerability.

Currently, the world is facing a severe pandemic caused by the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Although the WHO has recommended preventive measures to limit its spread, Brazil has neglected most of these recommendations, and consequently, our country has the second largest number of deaths from COVID-19 worldwide. In addition, recent studies have shown the relationship between socioeconomic inequalities and the risk of severe COVID-19 infection. Herein, we aimed to assess the spatiotemporal distribution of mortality and lethality rates of COVID-19 in a region of high social vulnerability in Brazil (Northeast region) during the first year of the pandemic. A segmented log-linear regression model was applied to assess temporal trends of mortality and case fatality rate (CFR) and according to the social vulnerability index (SVI). The Local Empirical Bayesian Estimator and Global Moran Index were used for spatial analysis. We conducted a retrospective space-time scan to map clusters at high risk of death from COVID-19. A total of 66,358 COVID-19-related deaths were reported during this period. The mortality rate was 116.2/100,000 inhabitants, and the CFR was 2.3%. Nevertheless, CFR was > 7.5% in 27 municipalities (1.5%). We observed an increasing trend of deaths in this region (AMCP = 18.2; P = 0.001). Also, increasing trends were observed in municipalities with high (N = 859) and very high SVI (N = 587). We identified two significant spatiotemporal clusters of deaths by COVID-19 in this Brazilian region (P = 0.001), and most high-risk municipalities were on the coastal strip of the region. Taken together, our analyses demonstrate that the pandemic has been responsible for several deaths in Northeast Brazil, with clusters at high risk of mortality mainly in municipalities on the coastline and those with high SVI.

Airports, highways and COVID-19: An analysis of spatial dynamics in Brazil.

INTRODUCTION: The high transmissibility and infectivity of the new coronavirus, the high proportion of asymptomatic transmitters and the rapid and continuous spatial displacement of people, by the different mechanisms of locomotion, are elements that can contribute to the dissemination of COVID-19. This study aims to describe the geographical dispersion of COVID-19 in the state of Bahia and the importance of major airports and highways in the dynamics of disease transmission. METHODS: This is an ecological study involving all cases of COVID-19 registered in the state of Bahia between March 6, date of the first registered case and May 16, 2020. After collection, an exploratory spatial analysis was performed, considering the cases accumulated on the last day of each epidemiological week. RESULTS: The first cases of COVID-19 were concentrated in areas served by three important airport complexes in the state, located in Salvador, Ilhéus and Porto Seguro. From week 16-20, there was a more intense expansion of COVID-19 to the interior of the state. A global spatial autocorrelation was observed (I Moran 0.2323; p = 0.01), with the influence of distance: positive correlation at distances less than 205.8 km (I Moran 0.040; p = 0.01) and greater than 800 km (I Moran 0.080; p = 0.01). CONCLUSIONS: Based on the spatial dispersion pattern of COVID-19 in the state of Bahia, airports and highways that cross the state were responsible for the interiorization of the disease.

Clinical manifestations of COVID-19 in the general population: systematic review.

Clinical manifestations of COVID-19 are varied in the general population. This study aimed to systematize the literature regarding clinical manifestations of patients with confirmed COVID-19. A systematic review of the literature was conducted. A total of 8070 scientific productions were found in the databases. Among the studies, 184 met the initial inclusion criteria, with a total of 114,046 patients. After complete reading, 32 studies that did not report clinical manifestations were excluded. The 152 publications finally included a total of 41,409 individuals from at least 23 countries and 26 different clinical manifestations were reported. In percentage terms, 6 symptoms had a general prevalence greater than or equal to 25%, namely, fever (58.66%), cough (54.52%), dyspnea (30.82%), malaise (29.75%), fatigue (28.16%) and sputum/secretion (25.33%). Neurological symptoms (20.82%), dermatological manifestations (20.45%), anorexia (20.26%), myalgia (16.9%), sneezing (14.71%), sore throat (14.41%), rhinitis (14.29%), goosebumps (13.49%), headache (12.17%), chest pain (11.49%) and diarrhea (9.59%) were other common symptoms. Only one study reported dermatological manifestations. The least frequent sign/symptom was hemoptysis (1.65%). In studies with more than 100 patients, the 3 main symptoms were fever (57.93%), cough (54.21%), and dyspnea (30.64%). Dermatological manifestations do not appear among the main symptoms. The identification of all clinical manifestations of COVID-19 is essential for an early diagnosis and the adoption of preventive measures.