Background Protective effects of Bacillus Calmette–Guérin (BCG) vaccination and clofazimine and dapsone treatment against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have been reported. Patients at risk for leprosy represent an interesting model for assessing the effects of these therapies on the occurrence and severity of coronavirus disease 2019 (COVID-19). We assessed the influence of leprosy-related variables in the occurrence and severity of COVID-19. Methodology/Principal findings We performed a 14-month prospective real-world cohort study in which the main risk factor was 2 previous vaccinations with BCG and the main outcome was COVID-19 detection by reverse transcription polymerase chain reaction (RT-PCR). A Cox proportional hazards model was used. Among the 406 included patients, 113 were diagnosed with leprosy. During follow-up, 69 (16.99%) patients contracted COVID-19. Survival analysis showed that leprosy was associated with COVID-19 (p<0.001), but multivariate analysis showed that only COVID-19-positive household contacts (hazard ratio (HR) = 8.04; 95% CI = 4.93–13.11) and diabetes mellitus (HR = 2.06; 95% CI = 1.04–4.06) were significant risk factors for COVID-19. Conclusions/Significance Leprosy patients are vulnerable to COVID-19 because they have more frequent contact with SARS-CoV-2-infected patients, possibly due to social and economic limitations. Our model showed that the use of corticosteroids, thalidomide, pentoxifylline, clofazimine, or dapsone or BCG vaccination did not affect the occurrence or severity of COVID-19.

Introduction: As highly specific molecular biology-based techniques may not be sensitive enough for the diagnosis of American tegumentary leishmaniasis (ATL), clinicians frequently rely on immunological tests before treatment initiation. Hence, the correct combination of diagnostic tests is imperative for ATL diagnosis. We aimed to evaluate the accuracy of the Montenegro (Leishmanin) skin test (MST) in polymerase chain reaction (PCR)-negative patients to accurately detect ATL. Methods: Patients with a clinical picture compatible with ATL were divided into ATL (confirmed by lesion smear, culture indirect immunofluorescence, and/or histopathology) and no-ATL (diseases that can mimic leishmaniasis) groups. Conventional PCR for the minicircle kDNA of Leishmania was performed, and the MST was carried out for PCR-negative patients. Results: Ninety-nine patients were included in this study, including 79 diagnosed with ATL (6 with mucocutaneous leishmaniasis) and 20 without ATL (no-ATL group). The MST showed a high sensitivity of 90.0% (95% confidence interval [CI] = 69.90-97.21) in PCR-negative patients that was 10% higher than the sensitivity reported in PCR-positive population (79.66%; 95% CI = 67.73-87.96). Conclusions: One of the most important reasons for PCR negativity among patients with active ATL is the presence of a strong cellular immunological response, especially in chronic and mucocutaneous leishmaniasis. This reinforces the considerable utility of the tests that detect cellular responses against Leishmania antigens such as the MST in PCR-negative patients when the performance in screening situations is questionable.

This work proposes a methodology applied to repositories modeled using star schemas, such as data marts, to discover relevant time series relations. This paper applies a set of measures related to association, correlation, and causality to create connections among data. In this context, the research proposes a new causality function based on peaks and values that relate coherently time series. To evaluate the approach, the authors use a set of experiments exploring time series about a particular neglected disease that affects several Brazilian cities called American Tegumentary Leishmaniasis and time series about the climate of some cities in Brazil. The authors populate data marts with these data, and the proposed methodology has generated a set of relations linking the notifications of this disease to the variation of temperature and pluviometry.