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

The Dynamics of Transmission and Spatial Distribution of Malaria in Riverside Areas of Porto Velho, Rondônia, in the Amazon Region of Brazil

The study area in Rondônia was the site of extensive malaria epidemic outbreaks in the 19th and 20th centuries related to environmental impacts, with large immigration flows. The present work analyzes the transmission dynamics of malaria in these areas to propose measures for avoiding epidemic outbreaks due to the construction of two Hydroelectric Power Plants. A population based baseline demographic census and a malaria prevalence follow up were performed in two river side localities in the suburbs of Porto Velho city and in its rural vicinity. The quantification and nature of malaria parasites in clinical patients and asymptomatic parasite carriers were performed using microscopic and Real Time PCR methodologies. Anopheles densities and their seasonal variation were done by monthly captures for defining HBR (hourly biting rate) values. Main results: (i) malaria among residents show the riverside profile, with population at risk represented by children and young adults; (ii) asymptomatic vivax and falciparum malaria parasite carriers correspond to around 15% of adults living in the area; (iii) vivax malaria relapses were responsible for 30% of clinical cases; (iv) malaria risk for the residents was evaluated as 20–25% for vivax and 5–7% for falciparum malaria; (v) anopheline densities shown outdoors HBR values 5 to 10 fold higher than indoors and reach 10.000 bites/person/year; (vi) very high incidence observed in one of the surveyed localities was explained by a micro epidemic outbreak affecting visitors and temporary residents. Temporary residents living in tents or shacks are accessible to outdoors transmission. Seasonal fishermen were the main group at risk in the study and were responsible for a 2.6 fold increase in the malaria incidence in the locality. This situation illustrates the danger of extensive epidemic outbreaks when thousands of workers and secondary immigrant population will arrive attracted by opportunities opened by the Hydroelectric Power Plants constructions

A review exploring the overarching burden of Zika virus with emphasis on epidemiological case studies from Brazil

This paper explores the main factors for mosquito-borne transmission of the Zika virus by focusing on environmental, anthropogenic, and social risks. A literature review was conducted bringing together related information from this genre of research from peer-reviewed publications. It was observed that environmental conditions, especially precipitation, humidity, and temperature, played a role in the transmission. Furthermore, anthropogenic factors including sanitation, urbanization, and environmental pollution promote the transmission by affecting the mosquito density. In addition, socioeconomic factors such as poverty as well as social inequality and low-quality housing have also an impact since these are social factors that limit access to certain facilities or infrastructure which, in turn, promote transmission when absent (e.g., piped water and screened windows). Finally, the paper presents short-, mid-, and long-term preventative solutions together with future perspectives. This is the first review exploring the effects of anthropogenic aspects on Zika transmission with a special emphasis in Brazil

IFNG +874T/A polymorphism is not associated with American tegumentary leishmaniasis susceptibility but can influence Leishmania induced IFN-γ production

<p>Abstract</p> <p>Background</p> <p>Interferon-gamma is a key cytokine in the protective responses against intracellular pathogens. A single nucleotide polymorphism (SNP) located in the first intron of the human IFN-γ gene can putatively influence the secretion of cytokine with an impact on infection outcome as demonstrated for tuberculosis and other complex diseases. Our aim was to investigate the putative association of IFNG+874T/A SNP with American tegumentary leishmaniasis (ATL) and also the influence of this SNP in the secretion of IFN-γ <it>in vitro</it>.</p> <p>Methods</p> <p>Brazilian ATL patients (78 cutaneous, CL, and 58 mucosal leishmaniasis, ML) and 609 healthy volunteers were evaluated. The genotype of +874 region in the IFN-γ gene was carried out by Amplification Refractory Mutational System (ARMS-PCR). <it>Leishmania</it>-induced IFN-γ production on peripheral blood mononuclear cell (PBMC) culture supernatants was assessed by ELISA.</p> <p>Results</p> <p>There are no differences between +874T/A SNP frequency in cases and controls or in ML versus CL patients. Cutaneous leishmaniasis cases exhibiting AA genotype produced lower levels of IFN-γ than TA/TT genotypes. In mucosal cases, high and low IFN-γ producers were clearly demonstrated but no differences in the cytokine production was observed among the IFNG +874T or A carriers.</p> <p>Conclusion</p> <p>Our results suggest that +874T/A polymorphism was not associated with either susceptibility or severity to leishmaniasis. Despite this, IFNG +874T/A SNP could be involved in the pathogenesis of leishmaniasis by influencing the amount of cytokine released by CL patients, although it could not prevent disease development. On the other hand, it is possible that in ML cases, other potential polymorphic regulatory genes such as TNF-α and IL-10 are also involved thus interfering with IFN-γ secretion.</p

The effectiveness of public health interventions to reduce the health impact of climate change:a systematic review of systematic reviews

Climate change is likely to be one of the most important threats to public health in the coming years. Yet despite the large number of papers considering the health impact of climate change, few have considered what public health interventions may be of most value in reducing the disease burden. We aimed to evaluate the effectiveness of public health interventions to reduce the disease burden of high priority climate sensitive diseases