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To identify risk factors for death from pandemic (H1N1) 2009, we obtained data for 157 hospitalized patients with confirmed cases of this disease. Multivariate analysis showed that diabetes and class III obesity were associated with death. These findings helped define priority vaccination groups in Brazil. [ABSTRACT FROM AUTHOR]

The study of the propagation of infectious diseases in urban centers finds a close connection with their population's social characteristics and behavior. This work performs a spatial analysis of dengue cases in urban centers based on the basic reproduction numbers, R 0 , and incidence by planning areas (PAs), as well as their correlations with the Human Development Index (HDI) and the number of trips. We analyzed dengue epidemics in 2002 at two Brazilian urban centers, Belo Horizonte (BH) and Rio de Janeiro (RJ), using PAs as spatial units. Our results reveal heterogeneous spatial scenarios for both cities, with very weak correlations between R 0 and both the number of trips and the HDI; in BH, the values of R 0 show a less spatial heterogeneous pattern than in RJ. For BH, there are moderate correlations between incidence and both the number of trips and the HDI; meanwhile, they weakly correlate for RJ. Finally, the absence of strong correlations between the considered measures indicates that the transmission process should be treated considering the city as a whole., Competing Interests: The authors declare that the research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 The Authors.)

Arbovirus can cause diseases with a broad spectrum from mild to severe and long-lasting symptoms, affecting humans worldwide and therefore considered a public health problem with global and diverse socio-economic impacts. Understanding how they spread within and across different regions is necessary to devise strategies to control and prevent new outbreaks. Complex network approaches have widespread use to get important insights on several phenomena, as the spread of these viruses within a given region. This work uses the motif-synchronization methodology to build time varying complex networks based on data of registered infections caused by Zika, chikungunya, and dengue virus from 2014 to 2020, in 417 cities of the state of Bahia, Brazil. The resulting network sets capture new information on the spread of the diseases that are related to the time delay in the synchronization of the time series among different municipalities. Thus the work adds new and important network-based insights to previous results based on dengue dataset in the period 2001-2016. The most frequent synchronization delay time between time series in different cities, which control the insertion of edges in the networks, ranges 7 to 14 days, a period that is compatible with the time of the individual-mosquito-individual transmission cycle of these diseases. As the used data covers the initial periods of the first Zika and chikungunya outbreaks, our analyses reveal an increasing monotonic dependence between distance among cities and the time delay for synchronization between the corresponding time series. The same behavior was not observed for dengue, first reported in the region back in 1986, either in the previously 2001-2016 based results or in the current work. These results show that, as the number of outbreaks accumulates, different strategies must be adopted to combat the dissemination of arbovirus infections., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Arboviruses are diseases of worldwide importance in the field of communicable diseases. In Brazil, the reemergence of dengue and the emergence of chikungunya and Zika since 2014 have led to epidemic waves of great magnitude and rapid spread. However, their diffusion patterns vary and change over time. This study analyzes the spatial diffusion of the simultaneous circulation of three arboviruses transmitted by the same vector in a large urban space over two epidemic waves in consecutive years. An ecological study of spatial and temporal aggregates on the occurrence of dengue, chikungunya, and Zika, from 2014 to 2019, in Feira de Santana, Bahia State, was carried out using data of cases reported to the national surveillance system. Four different methods were used to analyze the spatial diffusion: Kernel Estimation with sequential maps, cumulative nearest-neighbor ratios (NNI) over time, spatial correlograms and local autocorrelation changes (LISA) over time. From 2014-2019, there were 21,723 confirmed cases of arboviruses. The highest incidences were among women (496.9, 220.2, and 91.0 cases/100,000 women for dengue, chikungunya and Zika respectively). By age group, the highest incidences were from ages 10-19 years old (609.3 dengue cases/100,000), from 60 and more (306.7 chikungunya cases/100,000), and from 0-9 years old (124.1 Zika cases/100,000 inhabitants). The temporal distribution demonstrated two epidemic waves of simultaneous circulation in 2014 and 2015. Kernel maps indicate that arboviruses spread to neighboring areas near the first hotspots, suggesting an expansion diffusion pattern. The NNI, spatial correlograms and LISA changes results suggest expansion patterns for the three arboviruses in all periods. The spatial diffusion pattern of dengue, Zika, and chikungunya in the 2014-2015 epidemics in Feira de Santana was expansion. These findings are useful to guide prevention measures and reduce occurrence in other areas., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Chikungunya is an arbovirus, transmitted by Aedes mosquitoes, which emerged in the Americas in 2013 and spread rapidly to almost every country on this continent. In Brazil, where the first cases were detected in 2014, it currently has reached all regions of this country and more than 900,000 cases were reported. The clinical spectrum of chikungunya ranges from an acute self-limiting form to disabling chronic forms. The purpose of this study was to estimate the seroprevalence of chikungunya infection in a large Brazilian city and investigate the association between viral circulation and living condition., Methodology/principal Findings: We conducted a population-based ecological study in selected Sentinel Areas (SA) through household interviews and a serologic survey in 2016/2017. The sample was of 1,981 individuals randomly selected. The CHIKV seroprevalence was 22.1% (17.1 IgG, 2.3 IgM, and 1.4 IgG and IgM) and varied between SA from 2.0% to 70.5%. The seroprevalence was significantly lower in SA with high living conditions compared to SA with low living condition. There was a positive association between CHIKV seroprevalence and population density (r = 0.2389; p = 0.02033)., Conclusions/significance: The seroprevalence in this city was 2.6 times lower than the 57% observed in a study conducted in the epicentre of the CHIKV epidemic of this same urban centre. So, the herd immunity in this general population, after four years of circulation of this agent is relatively low. It indicates that CHIKV transmission may persist in that city, either in endemic form or in the form of a new epidemic, because the vector infestation is persistent. Besides, the significantly lower seroprevalences in SA of higher Living Condition suggest that beyond the surveillance of the disease, vector control and specific actions of basic sanitation, the reduction of the incidence of this infection also depends on the improvement of the general living conditions of the population., Competing Interests: The authors have declared that no competing interests exist.

The co-circulation of different arboviruses in the same time and space poses a significant threat to public health given their rapid geographic dispersion and serious health, social, and economic impact. Therefore, it is crucial to have high quality of case registration to estimate the real impact of each arboviruses in the population. In this work, a Vector Autoregressive (VAR) model was developed to investigate the interrelationships between discarded and confirmed cases of dengue, chikungunya, and Zika in Brazil. We used data from the Brazilian National Notifiable Diseases Information System (SINAN) from 2010 to 2017. There were three peaks in the series of dengue notification in this period occurring in 2013, 2015 and in 2016. The series of reported cases of both Zika and chikungunya reached their peak in late 2015 and early 2016. The VAR model shows that the Zika series have a significant impact on the dengue series and vice versa, suggesting that several discarded and confirmed cases of dengue could actually have been cases of Zika. The model also suggests that the series of confirmed and discarded chikungunya cases are almost independent of the cases of Zika, however, affecting the series of dengue. In conclusion, co-circulation of arboviruses with similar symptoms could have lead to misdiagnosed diseases in the surveillance system. We argue that the routinely use of mathematical and statistical models in association with traditional symptom-surveillance could help to decrease such errors and to provide early indication of possible future outbreaks. These findings address the challenges regarding notification biases and shed new light on how to handle reported cases based only in clinical-epidemiological criteria when multiples arboviruses co-circulate in the same population., Competing Interests: The authors have declared that no competing interests exist.

Over 200,000 new cases of leprosy are detected each year, of which approximately 7% are associated with grade-2 disabilities (G2Ds). For achieving leprosy elimination, one of the main challenges will be targeting higher risk groups within endemic communities. Nevertheless, the socioeconomic risk markers of leprosy remain poorly understood. To address this gap we systematically reviewed MEDLINE/PubMed, Embase, LILACS and Web of Science for original articles investigating the social determinants of leprosy in countries with > 1000 cases/year in at least five years between 2006 and 2016. Cohort, case-control, cross-sectional, and ecological studies were eligible for inclusion; qualitative studies, case reports, and reviews were excluded. Out of 1,534 non-duplicate records, 96 full-text articles were reviewed, and 39 met inclusion criteria. 17 were included in random-effects meta-analyses for sex, occupation, food shortage, household contact, crowding, and lack of clean (i.e., treated) water. The majority of studies were conducted in Brazil, India, or Bangladesh while none were undertaken in low-income countries. Descriptive synthesis indicated that increased age, poor sanitary and socioeconomic conditions, lower level of education, and food-insecurity are risk markers for leprosy. Additionally, in pooled estimates, leprosy was associated with being male (RR = 1.33, 95% CI = 1.06-1.67), performing manual labor (RR = 2.15, 95% CI = 0.97-4.74), suffering from food shortage in the past (RR = 1.39, 95% CI = 1.05-1.85), being a household contact of a leprosy patient (RR = 3.40, 95% CI = 2.24-5.18), and living in a crowded household (≥5 per household) (RR = 1.38, 95% CI = 1.14-1.67). Lack of clean water did not appear to be a risk marker of leprosy (RR = 0.94, 95% CI = 0.65-1.35). Additionally, ecological studies provided evidence that lower inequality, better human development, increased healthcare coverage, and cash transfer programs are linked with lower leprosy risks. These findings point to a consistent relationship between leprosy and unfavorable economic circumstances and, thereby, underscore the pressing need of leprosy control policies to target socially vulnerable groups in high-burden countries., Competing Interests: The authors have declared that no competing interests exist.