Simulation-based evaluation of school reopening strategies during COVID-19: A case study of Sao Paulo, Brazil.
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ABSTRACT:
SUBMITTER: Cruz EHM
PROVIDER: S-EPMC8134889 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:As COVID-19-related health indicators improve after restrictive measures were set in place in different parts of the world, governments are expected to guide how to ease interventions while minimizing the risk of resurgent outbreaks. Whereas epidemiologists track the progress of the disease using daily indicators to understand the pandemic better, economic activity indicators are usually available at a lower frequency and with considerable time lags. We propose and implement a timely trade-based regional economic activity indicator (EAI) that uses high-frequency traffic data to monitor daily sectoral economic activity in different sectors for the Brazilian State of São Paulo, a highly impacted region, overcoming the challenge of real-time assessment of the economy amid the COVID-19 outbreak. We then use this novel set of information combined with hospitalization rates to provide a first assessment of the São Paulo Plan, the COVID-19 exit strategy designed to gradually lifting interventions introduced to control the outbreak in the State. Available data show that, in its first 60 days, the phased strategy pursued in São Paulo has been effective in gradually reactivating economic activity while maintaining the adequate responsiveness of the healthcare system.Supplementary informationThe online version contains supplementary material available at 10.1007/s00168-021-01085-8.
| S-EPMC8610368 | biostudies-literature
Project description:Two hundred days after the first confirmed case of COVID-19 in Brazil, the epidemic has rapidly spread in metropolitan areas and advanced throughout the countryside. We followed the temporal epidemic pattern at São Paulo State, the most populous of the country, the first to have a confirmed case of COVID-19, and the one with the most significant number of cases until now. We analysed the number of new cases per day in each regional health department and calculated the effective reproduction number (Rt) over time. Social distance measures, along with improvement in testing and isolating positive cases, general population mask-wearing and standard health security protocols for essential and non-essential activities, were adopted and impacted on slowing down epidemic velocity but were insufficient to stop transmission.
| S-EPMC7750657 | biostudies-literature
Project description:With COVID-19 surging across the world, understanding the effectiveness of intervention strategies on transmission dynamics is of primary global health importance. Here, we develop and analyze an epidemiological compartmental model using multi-objective genetic algorithm design optimization to compare scenarios related to strategy type, the extent of social distancing, time window, and personal protection levels on the transmission dynamics of COVID-19 in São Paulo, Brazil. The results indicate that the optimal strategy for São Paulo is to reduce social distancing over time with a stepping-down reduction in the magnitude of social distancing every 80-days. Our results also indicate that the ability to reduce social distancing depends on a 5-10% increase in the current percentage of people strictly following protective guidelines, highlighting the importance of protective behavior in controlling the pandemic. Our framework can be extended to model transmission dynamics for other countries, regions, states, cities, and organizations.
| S-EPMC7814036 | biostudies-literature
Project description:BackgroundHeterogeneity in COVID-19 morbidity and mortality is often associated with a country's health-services structure and social inequality. This study aimed to characterize social inequalities in COVID-19 mortality in São Paulo, the most populous city in Brazil and Latin America.MethodsWe conducted a population-based study, including COVID-19 deaths among São Paulo residents from March to September 2020. Age-standardized mortality rates and unadjusted rate ratios (RRs) [with corresponding 95% confidence intervals (CIs)] were estimated by race, sex, age group, district of residence, household crowding, educational attainment, income level and percentage of households in subnormal areas in each district. Time trends in mortality were assessed using the Joinpoint model.ResultsMales presented an 84% increase in COVID-19 mortality compared with females (RR = 1.84, 95% CI 1.79-1.90). Higher mortality rates were observed for Blacks (RR = 1.77, 95% CI 1.67-1.88) and mixed (RR = 1.42, 95% CI 1.37-1.47) compared with Whites, whereas lower mortality was noted for Asians (RR = 0.63, 95% CI 0.58-0.68). A positive gradient was found for all socio-economic indicators, i.e. increases in disparities denoted by less education, more household crowding, lower income and a higher concentration of subnormal areas were associated with higher mortality rates. A decrease in mortality over time was observed in all racial groups, but it started earlier among Whites and Asians.ConclusionOur results reveal striking social inequalities in COVID-19 mortality in São Paulo, exposing structural inequities in Brazilian society that were not addressed by the governmental response to COVID-19. Without an equitable response, COVID-19 will further exacerbate current social inequalities in São Paulo.
| S-EPMC7989375 | biostudies-literature
Project description:Seeking to understand the socio-spatial behaviour of the COVID-19 virus in the most impacted area in Brazil, five spatial regression models were analysed to assess the disease distribution in the affected territory. Results obtained using the Spearman correlation test provided evidence for the correlation between COVID-19 death incidence and social aspects such as population density, average people per household, and informal urban settlements. More importantly, all analysed models using four selected explanatory variables have proven to represent at least 85 per cent of reported deaths at the district level. Overall, our results have demonstrated that the geographically weighted regression (GWR) model best explains the spatial distribution of COVID-19 in the city of São Paulo, highlighting the spatial aspects of the data. Spatial analysis has shown the spread of COVID-19 in areas with highly vulnerable populations. Our findings corroborate reports from the recent literature, pointing out the need for special attention in peripheral areas and informal settlements.
| S-EPMC7557234 | biostudies-literature
Project description:The state of São Paulo, Brazil, where more than 94.000 dentists are currently registered, has become the epicenter of COVID-19 in Latin America. The aim of this cross-sectional study was to evaluate the impact of COVID-19 pandemic on dentists in this state. A semi-structured questionnaire was sent via e-mail to 93.280 dentists with active registration in the Dental Council of São Paulo (CROSP). The impact of COVID-19 pandemic was assessed through questions related to demographic, socioeconomic, dental practice characteristics and personal protective equipment (PPE) use. Ordinal logistic regression analysis was performed to investigate the association between all the variables (p<0.05). Over 8 days, 2113 responses were received. Only 26.52% of the sample reported a low-income reduction (from 0-10%), while the majority of dentists reported a more negative financial impact, 35.6% with a reduction of more than 50% of their monthly income. Dentists who worked in the private sector and at the capital had a greater financial impact when compared to those of the public sector and countryside of the state (p<0.05). Furthermore, about 83% reported not having received any specific training to control the transmission of coronavirus in the health area. This study provides evidence of the negative impact of the COVID-19 pandemic on the routine of dentists in the state of São Paulo, Brazil. Hopefully, this study will help dental and other health care professionals to better understand the consequences of disease in dental settings and strengthen preparedness throughout the dental health care system.
| S-EPMC8389449 | biostudies-literature
Project description:Soils and groundwater contamination modifies the physical-chemical conditions of the environment, altering natural biogeochemical processes of the ground. As a result, several mineral transformations occur, in which iron plays a decisive role. The presence of iron enables the study of magnetic properties, improving the understanding of the geophysical signatures of highly dynamic environments (e.g., biogeochemical hotspots and contamination plumes). In this work, we seek to identify creosote biodegradation related to the precipitation of magnetic minerals on sediments at a contaminated site in São Paulo, Brazil. Several rock magnetism analyses were carried out to provide the magnetic mineralogy of the samples in terms of their composition, size, and abundance. We conducted high-temperature thermomagnetic curves, frequency-dependent magnetic susceptibility, anesthetic remanent magnetization (ARM) and isothermal remanent magnetization (IRM) data, superparamagnetic concentration and dipole moment (SPCDM), and scanning electron microscopy (SEM) analyses. The magnetic signatures of the contaminated samples suggest an increase of superparamagnetic grains in the water table fluctuation zone if compared to the magnetic signatures of the uncontaminated samples. Thermomagnetic curves of contaminated samples showed a lower heterogeneity of the magnetic mineral phases than the uncontaminated ones. This work contributes to the advancement of the understanding of how natural biogeochemical processes are impacted by human actions, such as soil contamination, and even by climate change, which should affect soil redox conditions in periods of drought and flooding.
| S-EPMC9759522 | biostudies-literature
Project description:BACKGROUND: Over the last century the incidence of cutaneous melanoma has increased worldwide, a trend that has also been observed in Brazil. The identified risk factors for melanoma include the pattern of sun exposure, family history, and certain phenotypic features. In addition, the incidence of melanoma might be influenced by ethnicity. Like many countries, Brazil has high immigration rates and consequently a heterogeneous population. However, Brazil is unique among such countries in that the ethnic heterogeneity of its population is primarily attributable to admixture. This study aimed to evaluate the contribution of European ethnicity to the risk of cutaneous melanoma in Brazil. METHODOLOGY/PRINCIPAL FINDINGS: We carried out a hospital-based case-control study in the metropolitan area of Sao Paulo, Brazil. We evaluated 424 hospitalized patients (202 melanoma patients and 222 control patients) regarding phenotypic features, sun exposure, and number of grandparents born in Europe. Through multivariate logistic regression analysis, we found the following variables to be independently associated with melanoma: grandparents born in Europe-Spain (OR = 3.01, 95% CI: 1.03-8.77), Italy (OR = 3.47, 95% CI: 1.41-8.57), a Germanic/Slavic country (OR = 3.06, 95% CI: 1.05-8.93), or ≥ 2 European countries (OR = 2.82, 95% CI: 1.06-7.47); eye color-light brown (OR = 1.99, 95% CI: 1.14-3.84) and green/blue (OR = 4.62; 95% CI 2.22-9.58); pigmented lesion removal (OR = 3.78; 95% CI: 2.21-6.49); no lifetime sunscreen use (OR = 3.08; 95% CI: 1.03-9.22); and lifetime severe sunburn (OR = 1.81; 95% CI: 1.03-3.19). CONCLUSIONS: Our results indicate that European ancestry is a risk factor for cutaneous melanoma. Such risk appears to be related not only to skin type, eye color, and tanning capacity but also to others specific characteristics of European populations introduced in the New World by European immigrants.
| S-EPMC3338653 | biostudies-other
Project description:To estimate the prevalence of one month psychotropic drug use in São Paulo, Brazil, and to assess the gap treatment between the presence of mental disorders and psychotropic drug users.A probabilistic sample of non-institutionalized individuals from the general population of São Paulo (n = 2336; turnout: 84.5%) who were 15 years or older were interviewed by a trained research staff, applying the Composite International Diagnostic Interview 2.1 (CIDI WHO) (depression, anxiety-phobia, OCD\PTSD, alcoholism sections), and an inventory investigating psychotropic drug use during the 12-month and one-month periods immediately preceding the interview. Logistic models were fitted to investigate associations between psychotropic drug use as well as socio-demographic and clinical variables.The one month prevalence of psychotropic drug use in São Paulo was 5.89%, the most commonly used drugs were antidepressants (3.15%) and tranquilizers (2.67%). A higher consumption of psychotropic drugs (overall, antidepressants and tranquilizers) was observed among women (OR:2.42), older individuals (OR:1.04), individuals with higher levels of formal education (1.06), and individuals with a family (OR:2.29) or personal history of mental illness (OR:3.27). The main psychotropic drug prescribers were psychiatrists (41%), followed by general practitioners (30%); 60% of psychotropic drugs were obtained through a government-run dispensing program. Most individuals who obtained a positive diagnosis on the CIDI 2.1 during the previous month were not using psychotropic medication (85%). Among individuals with a diagnosis of moderate to severe depression, 67.5% were not on any pharmacological treatment.There is a change in the type of psychotropic more often used in São Paulo, from benzodiazepines to antidepressants, this event is observed in different cultures. The prevalence of use is similar to other developing countries. Most of the patients presenting a psychiatric illness in the month prior to testing were not receiving any sort of psychiatric medication. This may be explained by a failure to identify cases in primary care, which could be improved (and access to treatment could be facilitated) if professionals received more specialized training in managing cases with mental health problems.
| S-EPMC4529275 | biostudies-other
Project description:The new coronavirus disease (COVID-19) is a challenge for clinical decision-making and the effective allocation of healthcare resources. An accurate prognostic assessment is necessary to improve survival of patients, especially in developing countries. This study proposes to predict the risk of developing critical conditions in COVID-19 patients by training multipurpose algorithms. We followed a total of 1040 patients with a positive RT-PCR diagnosis for COVID-19 from a large hospital from São Paulo, Brazil, from March to June 2020, of which 288 (28%) presented a severe prognosis, i.e. Intensive Care Unit (ICU) admission, use of mechanical ventilation or death. We used routinely-collected laboratory, clinical and demographic data to train five machine learning algorithms (artificial neural networks, extra trees, random forests, catboost, and extreme gradient boosting). We used a random sample of 70% of patients to train the algorithms and 30% were left for performance assessment, simulating new unseen data. In order to assess if the algorithms could capture general severe prognostic patterns, each model was trained by combining two out of three outcomes to predict the other. All algorithms presented very high predictive performance (average AUROC of 0.92, sensitivity of 0.92, and specificity of 0.82). The three most important variables for the multipurpose algorithms were ratio of lymphocyte per C-reactive protein, C-reactive protein and Braden Scale. The results highlight the possibility that machine learning algorithms are able to predict unspecific negative COVID-19 outcomes from routinely-collected data.
| S-EPMC7870665 | biostudies-literature