Covid-19 Dynamic Monitoring and Real-Time Spatio-Temporal Forecasting

Background: Periodically, humanity is often faced with new and emerging viruses that can be a significant global threat. It has already been over a century post—the Spanish Flu pandemic, and we are witnessing a new type of coronavirus, the SARS-CoV-2, which is responsible for Covid-19. It emerged from the city of Wuhan (China) in December 2019, and within a few months, the virus propagated itself globally now resulting more than 50 million cases with over 1 million deaths. The high infection rates coupled with dynamic population movement demands for tools, especially within a Brazilian context, that will support health managers to develop policies for controlling and combating the new virus. / Methods: In this work, we propose a tool for real-time spatio-temporal analysis using a machine learning approach. The COVID-SGIS system brings together routinely collected health data on Covid-19 distributed across public health systems in Brazil, as well as taking to under consideration the geographic and time-dependent features of Covid-19 so as to make spatio-temporal predictions. The data are sub-divided by federative unit and municipality. In our case study, we made spatio-temporal predictions of the distribution of cases and deaths in Brazil and in each federative unit. Four regression methods were investigated: linear regression, support vector machines (polynomial kernels and RBF), multilayer perceptrons, and random forests. We use the percentage RMSE and the correlation coefficient as quality metrics. / Results: For qualitative evaluation, we made spatio-temporal predictions for the period from 25 to 27 May 2020. Considering qualitatively and quantitatively the case of the State of Pernambuco and Brazil as a whole, linear regression presented the best prediction results (thematic maps with good data distribution, correlation coefficient >0.99 and RMSE (%) <4% for Pernambuco and around 5% for Brazil) with low training time: [0.00; 0.04 ms], CI 95%. / Conclusion: Spatio-temporal analysis provided a broader assessment of those in the regions where the accumulated confirmed cases of Covid-19 were concentrated. It was possible to differentiate in the thematic maps the regions with the highest concentration of cases from the regions with low concentration and regions in the transition range. This approach is fundamental to support health managers and epidemiologists to elaborate policies and plans to control the Covid-19 pandemics

COVID-SGIS: A Smart Tool for Dynamic Monitoring and Temporal Forecasting of Covid-19

Background: The global burden of the new coronavirus SARS-CoV-2 is increasing at an unprecedented rate. The current spread of Covid-19 in Brazil is problematic causing a huge public health burden to its population and national health-care service. To evaluate strategies for alleviating such problems, it is necessary to forecast the number of cases and deaths in order to aid the stakeholders in the process of making decisions against the disease. We propose a novel system for real-time forecast of the cumulative cases of Covid-19 in Brazil. / Methods: We developed the novel COVID-SGIS application for the real-time surveillance, forecast and spatial visualization of Covid-19 for Brazil. This system captures routinely reported Covid-19 information from 27 federative units from the Brazil.io database. It utilizes all Covid-19 confirmed case data that have been notified through the National Notification System, from March to May 2020. Time series ARIMA models were integrated for the forecast of cumulative number of Covid-19 cases and deaths. These include 6-days forecasts as graphical outputs for each federative unit in Brazil, separately, with its corresponding 95% CI for statistical significance. In addition, a worst and best scenarios are presented. / Results: The following federative units (out of 27) were flagged by our ARIMA models showing statistically significant increasing temporal patterns of Covid-19 cases during the specified day-to-day period: Bahia, Maranhão, Piauí, Rio Grande do Norte, Amapá, Rondônia, where their day-to-day forecasts were within the 95% CI limits. Equally, the same findings were observed for Espírito Santo, Minas Gerais, Paraná, and Santa Catarina. The overall percentage error between the forecasted values and the actual values varied between 2.56 and 6.50%. For the days when the forecasts fell outside the forecast interval, the percentage errors in relation to the worst case scenario were below 5%. / Conclusion: The proposed method for dynamic forecasting may be used to guide social policies and plan direct interventions in a cost-effective, concise, and robust manner. This novel tools can play an important role for guiding the course of action against the Covid-19 pandemic for Brazil and country neighbors in South America

Expanding the knowledge about Leishmania species in wild mammals and dogs in the Brazilian savannah

Background: Wild, synanthropic and domestic mammals act as hosts and/or reservoirs of several Leishmania spp. Studies on possible reservoirs of Leishmania in different areas are fundamental to understand host-parasite interactions and develop strategies for the surveillance and control of leishmaniasis. In the present study, we evaluated the Leishmania spp. occurrence in mammals in two conservation units and their surroundings in Brasília, Federal District (FD), Brazil. Methods: Small mammals were captured in Brasília National Park (BNP) and Contagem Biological Reserve (CBR) and dogs were sampled in residential areas in their vicinity. Skin and blood samples were evaluated by PCR using different molecular markers (D7 24Sα rRNA and rDNA ITS1). Leishmania species were identified by sequencing of PCR products. Dog blood samples were subjected to the rapid immunochromatographic test (DPP) for detection of anti-Leishmania infantum antibodies. Results: 179 wild mammals were studied and 20.1% had Leishmania DNA successfully detected in at least one sample. Six mammal species were considered infected: Clyomys laticeps, Necromys lasiurus, Nectomys rattus, Rhipidomys macrurus, Didelphis albiventris and Gracilinanus agilis. No significant difference, comparing the proportion of individuals with Leishmania spp., was observed between the sampled areas and wild mammal species. Most of the positive samples were collected from the rodent N. lasiurus, infected by L. amazonensis or L. braziliensis. Moreover, infections by Trypanosoma spp. were detected in N. lasiurus and G. agilis. All 19 dog samples were positive by DPP; however, only three (15.8%) were confirmed by PCR assays. DNA sequences of ITS1 dog amplicons showed 100% identity with L. infantum sequence. Conclusions: The results suggest the participation of six species of wild mammals in the enzootic transmission of Leishmania spp. in FD. This is the first report of L. amazonensis in N. lasiurus

Effects of preoperative feeding with a whey protein plus carbohydrate drink on the acute phase response and insulin resistance. A randomized trial

<p>Abstract</p> <p>Background</p> <p>Prolonged preoperative fasting increases insulin resistance and current evidence recommends carbohydrate (CHO) drinks 2 hours before surgery. Our hypothesis is that the addition of whey protein to a CHO-based drink not only reduces the inflammatory response but also diminish insulin resistance.</p> <p>Methods</p> <p>Seventeen patients scheduled to cholecystectomy or inguinal herniorraphy were randomized and given 474 ml and 237 ml of water (CO group) or a drink containing CHO and milk whey protein (CHO-P group) respectively, 6 and 3 hours before operation. Blood samples were collected before surgery and 24 hours afterwards for biochemical assays. The endpoints of the study were the insulin resistance (IR), the prognostic inflammatory and nutritional index (PINI) and the C-reactive protein (CRP)/albumin ratio. A 5% level for significance was established.</p> <p>Results</p> <p>There were no anesthetic or postoperative complications. The post-operative IR was lower in the CHO-P group when compared with the CO group (2.75 ± 0.72 vs 5.74 ± 1.16; p = 0.03). There was no difference between the two groups in relation to the PINI. The CHO-P group showed a decrease in the both CRP elevation and CRP/albumin ratio (p < 0.05). The proportion of patients who showed CRP/albumin ratio considered normal was significantly greater (p < 0.05) in the CHO-P group (87.5%) than in the CO group (33.3%).</p> <p>Conclusions</p> <p>Shortening the pre-operative fasting using CHO and whey protein is safe and reduces insulin resistance and postoperative acute phase response in elective moderate operations.</p> <p>Trial registration</p> <p>ClinicalTrail.gov <a href="http://www.clinicaltrials.gov/ct2/show/NCT01354249">NCT01354249</a></p