Risk factors for arbovirus infections in a low-income community of Rio de Janeiro, Brazil, 2015-2016

Dynamics of viral disease outbreaks: A hundred years (1918/19-2019/20) in retrospect - Loses, lessons and emerging issues

Infectious diseases continue to be the leading cause of morbidity and mortality, and a formidable obstacle to the development and well-being of people worldwide. Viruses account for more than half of infectious disease outbreaks that have plagued the world. The past century (1918/19-2019/20) has witnessed some of the worst viral disease outbreaks the world has recorded, with overwhelming impact especially in low- and middle-income countries (LMIC). The frequency of viral disease outbreak appears to be increasing. Generally, although infectious diseases have afflicted the world for centuries and humankind has had opportunities to examine the nature of their emergence and mode of spread, almost every new outbreak poses a formidable challenge to humankind, beating the existing pandemic preparedness systems, if any, and causing significant losses. These underscore inadequacy in our understanding of the dynamics and preparedness against viral disease outbreaks that lead to epidemics and pandemics. Despite these challenges, the past 100 years of increasing frequencies of viral disease outbreaks have engendered significant improvements in response to epidemics and pandemics, and offered lessons to inform preparedness. Hence, the increasing frequency of emergence of viral outbreaks and the challenges these outbreaks pose to humankind, call for the continued search for effective ways to tackle viral disease outbreaks in real time. Through a PRISMA-based approach, this systematic review examines the outbreak of viral diseases in retrospect to decipher the outbreak patterns, losses inflicted on humanity and highlights lessons these offer for meaningful preparation against future viral disease outbreaks and pandemics.

Zika, chikungunya and co-occurrence in Brazil: space-time clusters and associated environmental-socioeconomic factors

Chikungunya and Zika have been neglected as emerging diseases. This study aimed to analyze the space-time patterns of their occurrence and co-occurrence and their associated environmental and socioeconomic factors. Univariate (individually) and multivariate (co-occurrence) scans were analyzed for 608,388 and 162,992 cases of chikungunya and Zika, respectively. These occurred more frequently in the summer and autumn. The clusters with the highest risk were initially located in the northeast, dispersed to the central-west and coastal areas of São Paulo and Rio de Janeiro (2018-2021), and then increased in the northeast (2019-2021). Chikungunya and Zika demonstrated decreasing trends of 13% and 40%, respectively, whereas clusters showed an increasing trend of 85% and 57%, respectively. Clusters with a high co-occurrence risk have been identified in some regions of Brazil. High temperatures are associated with areas at a greater risk of these diseases. Chikungunya was associated with low precipitation levels, more urbanized environments, and places with greater social inequalities, whereas Zika was associated with high precipitation levels and low sewage network coverage. In conclusion, to optimize the surveillance and control of chikungunya and Zika, this study's results revealed high-risk areas with increasing trends and priority months and the role of socioeconomic and environmental factors.

Disease burden of congenital Zika virus syndrome in Brazil and its association with socioeconomic data

Zika virus (ZIKV) infection became a global public health concern, causing an epidemic in Latin America from 2015 to 2016, when a sudden increase in cases of microcephaly and other congenital anomalies was observed. In 2016, the Centers for Disease Control and Prevention and the World Health Organization defined congenital Zika-associated syndrome (CZS) as a set of congenital anomalies seen in children born to mothers with a history of gestational Zika fever, who have microcephaly as the most prevalent clinical sign. In order to describe the magnitude of CZS in Brazil, this study estimated the burden of disease due to CZS in Brazil using the disability-adjusted life years (DALY) indicator and other frequency measures, such as incidence and mortality rate, during the years 2015-2020. The association of these indicators with socioeconomic variables was also evaluated using Spearman's correlation coefficient. Choropleth maps were used to evaluate the spatial distribution of the indicators evaluated and the spatial autocorrelation was verified by the Bivariate Moran Local Index. From 2015 to 2020, 3,591 cases of CZS were confirmed in Brazil, with an incidence of 44.03 cases per 1000 live births, and a specific mortality of 12.35 deaths per 1000 live births. A global loss of 30,027.44 DALYs was estimated from 2015 to 2020. The Northeast region had the highest values for all health indicators assessed. Spatial correlation and autocorrelation analyses showed significant associations between health and socioeconomic indicators, such as per capita income, Gini index, illiteracy rate and basic sanitation. The study allowed us to have access to all reported cases of CZS, showing us the possible situation of the disease in Brazil; therefore, we believe that our results can help in the understanding of future studies.

Spatio-temporal dynamics of three diseases caused by Aedes-borne arboviruses in Mexico

Background

The intensity of transmission of Aedes-borne viruses is heterogeneous, and multiple factors can contribute to variation at small spatial scales. Illuminating drivers of heterogeneity in prevalence over time and space would provide information for public health authorities. The objective of this study is to detect the spatiotemporal clusters and determine the risk factors of three major Aedes-borne diseases, Chikungunya virus (CHIKV), Dengue virus (DENV), and Zika virus (ZIKV) clusters in Mexico.

Methods

We present an integrated analysis of Aedes-borne diseases (ABDs), the local climate, and the socio-demographic profiles of 2469 municipalities in Mexico. We used SaTScan to detect spatial clusters and utilize the Pearson correlation coefficient, Randomized Dependence Coefficient, and SHapley Additive exPlanations to analyze the influence of socio-demographic and climatic factors on the prevalence of ABDs. We also compare six machine learning techniques, including XGBoost, decision tree, Support Vector Machine with Radial Basis Function kernel, K nearest neighbors, random forest, and neural network to predict risk factors of ABDs clusters.

Results

DENV is the most prevalent of the three diseases throughout Mexico, with nearly 60.6% of the municipalities reported having DENV cases. For some spatiotemporal clusters, the influence of socio-economic attributes is larger than the influence of climate attributes for predicting the prevalence of ABDs. XGBoost performs the best in terms of precision-measure for ABDs prevalence.

Conclusions

Both socio-demographic and climatic factors influence ABDs transmission in different regions of Mexico. Future studies should build predictive models supporting early warning systems to anticipate the time and location of ABDs outbreaks and determine the stand-alone influence of individual risk factors and establish causal mechanisms.

Dengue, Chikungunya, and Zika: Spatial and Temporal Distribution in Rio de Janeiro State, 2015–2019

Simultaneous spatial circulation of urban arboviral diseases, such as dengue, chikungunya, and Zika, is a major challenge. In this ecological study of urban arboviruses performed from 2015 to 2019, we analyzed the spatial and temporal dynamics of these arboviruses in all 92 municipalities and nine health regions of Rio de Janeiro state. Annual cumulative incidences are presented for all three arboviruses throughout the study period. Spatial analyses of the three studied arboviruses showed distinct behaviors among municipalities and health regions. Co-circulation of the three arboviruses in the state and a heterogeneous spatiotemporal pattern was observed for each disease and region, with dengue having a higher annual incidence during the five years of the study, as well as two consecutive epidemic years in the state. The increase in transmission in different regions of the state in one year culminated in an epidemic in the state in the following year. A high annual cumulative incidence of chikungunya occurred in municipalities from 2017 to 2019 and of Zika only in 2016. Some municipalities with higher population densities showed higher incidences for some arboviruses and appeared to contribute to the dissemination to cities of lower demographic density and maintenance of these urban arboviruses. Thus, regions recording increased incidences of the three diseases in their territories for long periods should be considered municipal poles, as they initiated and sustained high transmission within their region.

Zika Virus Envelope Protein Domain III Produced in K. phaffii Has the Potential for Diagnostic Applications

Zika virus (ZIKV) represents a global human health threat and it is related to severe diseases such as congenital Zika syndrome (CZS) and Guillain-Barré syndrome (GBS). There is no vaccine available nor specific antiviral treatment, so developing sensitive, specific, and low-cost diagnostic tests is necessary. Thus, the objective of this work was to produce the Zika virus envelope protein domain III (ZIKV-EDIII) in Komagataella phaffii KM71H and evaluate its potential for diagnostic applications. After the K. phaffii had been transformed with the pPICZαA-ZIKV-EDIII vector, an SDS-PAGE and Western Blot were performed to characterize the recombinant protein and an ELISA to evaluate the antigenic potential. The results show that ZIKV-EDIII was produced in the expected size, with a good purity grade and yield of 2.58 mg/L. The receiver operating characteristic (ROC) curve showed 90% sensitivity and 87.5% specificity for IgM, and 93.33% sensitivity and 82.76% specificity for IgG. The ZIKV-EDIII protein was efficiently produced in K. phaffi, and it has the potential for diagnostic applications.

Socioeconomic risk markers of arthropod-borne virus (arbovirus) infections: a systematic literature review and meta-analysis

Introduction

Arthropod-borne viruses (arboviruses) are of notable public health importance worldwide, owing to their potential to cause explosive outbreaks and induce debilitating and potentially life-threatening disease manifestations. This systematic review and meta-analysis aims to assess the relationship between markers of socioeconomic position (SEP) and infection due to arboviruses with mosquito vectors.

Methods

We conducted a systematic search on PubMed, Embase, and LILACS databases to identify studies published between 1980 and 2020 that measured the association of SEP markers with arbovirus infection. We included observational studies without geographic location or age restrictions. We excluded studies from grey literature, reviews and ecological studies. Study findings were extracted and summarised, and pooled estimates were obtained using random-effects meta-analyses.

Results

We identified 36 observational studies using data pertaining to 106 524 study participants in 23 geographic locations that empirically examined the relationship between socioeconomic factors and infections caused by seven arboviruses (dengue, chikungunya, Japanese encephalitis, Rift Valley fever, Sindbis, West Nile and Zika viruses). While results were varied, descriptive synthesis pointed to a higher risk of arbovirus infection associated with markers of lower SEP, including lower education, income poverty, low healthcare coverage, poor housing materials, interrupted water supply, marital status (married, divorced or widowed), non-white ethnicities and migration status. Pooled crude estimates indicated an increased risk of arboviral infection associated with lower education (risk ratio, RR 1.5 95% CI 1.3 to 1.9); I²=83.1%), interruption of water supply (RR 1.2; 95% CI 1.1 to 1.3; I²=0.0%) and having been married (RR 1.5 95% CI 1.1 to 2.1; I²=85.2%).

Conclusion

Evidence from this systematic review suggests that lower SEP increases the risk of acquiring arboviral infection; however, there was large heterogeneity across studies. Further studies are required to delineate the relationship between specific individual, household and community-level SEP indicators and arbovirus infection risks to help inform targeted public health interventions.

PROSPERO registration number

CRD42019158572.

Neighbourhood-level income and Zika virus infection during pregnancy in Recife, Pernambuco, Brazil: an ecological perspective, 2015-2017

Zika virus (ZIKV) infections during pregnancy can lead to adverse neurodevelopmental and clinical outcomes in congenitally infected offspring. As the city of Recife in Pernambuco State, Brazil—the epicentre of the Brazilian microcephaly epidemic—has considerable disparities in living conditions, this study used an ecological approach to investigate the association between income at the neighbourhood level and the risk of ZIKV infections in pregnant individuals between December 2015 and April 2017. The spatial distribution of pregnant individuals with ZIKV infection was plotted on a map of Recife stratified into four categories based on mean monthly income of household heads. Additionally, a Poisson regression model with robust variance was fitted to compare proportions of ZIKV infections among pregnant individuals in relation to the mean monthly income of household heads, based on the 2010 census data, across 94 neighbourhoods in Recife. The results provide evidence that the risk of ZIKV infection to pregnant individuals was higher among those residing in lower-income neighbourhoods: relative to neighbourhoods that had a mean monthly income of ≥5 times minimum wage, neighbourhoods with <1 and 1 to <2 times minimum wage had more than four times the risk (incidence rate ratio, 95% CI 4.08, 1.88 to 8.85 and 4.30, 2.00 to 9.20, respectively). This study provides evidence of a strong association between neighbourhood-level income and ZIKV infection risks in the pregnant population of Recife. In settings prone to arboviral outbreaks, locally targeted interventions to improve living conditions, sanitation, and mosquito control should be a key focus of governmental interventions to reduce risks associated with ZIKV infections during pregnancy.

Autoregressive spatial modeling of possible cases of dengue, chikungunya, and Zika in the capital of Northeastern Brazil

INTRODUCTION:

Dengue, chikungunya, and Zika are a growing global health problem. This study analyzed the spatial distribution of dengue, chikungunya, and Zika cases in São Luís, Maranhão, from 2015 to 2016 and investigated the association between socio-environmental and economic factors and hotspots for mosquito proliferation.

METHODS:

This was a socio-ecological study using data from the National Information System of Notifiable Diseases. The spatial units of analysis were census tracts. The incidence rates of the combined cases of the three diseases were calculated and smoothed using empirical local Bayes estimates. The spatial autocorrelation of the smoothed incidence rate was measured using Local Moran's I and Global Moran's I. Multiple linear regression and spatial autoregressive models were fitted using the log of the smoothed disease incidence rate as the dependent variable and socio-environmental factors, demographics, and mosquito hotspots as independent variables.

RESULTS:

The findings showed a significant spatial autocorrelation of the smoothed incidence rate. The model that best fit the data was the spatial lag model, revealing a positive association between disease incidence and the proportion of households with surrounding garbage accumulation.

CONCLUSIONS:

The distribution of dengue, chikungunya, and Zika cases showed a significant spatial pattern, in which the high-risk areas for the three diseases were explained by the variable "garbage accumulated in the surrounding environment,” demonstrating the need for an intersectoral approach for vector control and prevention that goes beyond health actions.

Dengue, Severity Paradox, and Socioeconomic Distribution Among Afro-Colombians

BACKGROUND

The clinical presentation of dengue ranges from self-limited mild illness to severe forms, including death. African ancestry is often described as protective against dengue severity. However, in the Latin American context, African ancestry has been associated with increased mortality. This "severity paradox" has been hypothesized as resulting from confounding or heterogeneity by socioeconomic status (SES). However, few systematic analyses have been conducted to investigate the presence and nature of the disparity paradox.

METHODS

We fit Bayesian hierarchical spatiotemporal models using individual-level surveillance data from Cali, Colombia (2012-2017), to assess the overall morbidity and severity burden of notified dengue. We fitted overall and ethnic-specific models to assess the presence of heterogeneity by SES across and within ethnic groups (Afro-Colombian vs. non-Afro-Colombians), conducting sensitivity analyses to account for potential underreporting.

RESULTS

Our study included 65,402 dengue cases and 13,732 (21%) hospitalizations. Overall notified dengue incidence rates did not vary across ethnic groups. Severity risk was higher among Afro-Colombians (risk ratio [RR] = 1.16; 95% Credible Interval [95% CrI] = 1.08, 1.24) but after accounting for underreporting by ethnicity this association was nearly null (RR = 1.02; 95% CrI = 0.97, 1.07). Subsidized health insurance and low-SES were associated with increased overall dengue rates and severity.

CONCLUSION

The paradoxically increased severity among Afro-Colombians can be attributed to differential health-seeking behaviors and reporting among Afro-Colombians. Such differential reporting can be understood as a type of intersectionality between SES, insurance scheme, and ethnicity that requires a quantitative assessment in future studies.

Association between socio-environmental factors, coverage by family health teams, and rainfall in the spatial distribution of Zika virus infection in the city of Rio de Janeiro, Brazil, in 2015 and 2016

BACKGROUND

Zika virus (ZIKV) infection caused outbreak in Brazil, in 2015 and 2016. Disorganized urban growth, facilitates the concentration of numerous susceptible and infected individuals. It is useful to understand the mechanisms that can favor the increase in ZIKV incidence, such as areas with wide socioeconomic and environmental diversity. Therefore, the study analyzed the spatial distribution of ZIKV in the city of Rio de Janeiro, Brazil, in 2015 and 2016, and associations between the incidence per 1000 inhabitants and socio-environmental factors.

METHODS

The census tracts were used as the analytical units reported ZIKV cases among the city's inhabitants. Local Empirical Bayesian method was used to control the incidence rates' instability effect. The spatial autocorrelation was verified with Moran's Index and local indicators of spatial association (LISA). Spearman correlation matrix was used to indicate possible collinearity. The Ordinary Least Squares (OLS), Spatial Lag Model (SAR), and Spatial Error Model (CAR) were used to analyze the relationship between ZIKV and socio-environmental factors.

RESULTS

The SAR model exhibited the best parameters: R2 = 0.44, Log-likelihood = - 7482, Akaike Information Criterion (AIC) = 14,980. In this model, mean income between 1 and 2 minimum wages was possible risk factors for Zika occurrence in the localities. Household conditions related to adequate water supply and the existence of public sewage disposal were associated with lower ZIKV cumulative incidence, suggesting possible protective factors against the occurrence of ZIKV in the localities. The presence of the Family Health Strategy in the census tracts was positively associated with the ZIKV cumulative incidence. However, the results show that mean income less than 1 minimum wage were negatively associated with higher ZIKV cumulative incidence.

CONCLUSION

The results demonstrate the importance of socio-environmental variables in the dynamics of ZIKV transmission and the relevance for the development of control strategies.

Distribution and diversity of mosquitoes and Oropouche-like virus infection rates in an Amazonian rural settlement

Mosquito diversity and disease transmission are influenced by landscape modifications, i.e., vectors and pathogens previously found only in forests are now found close to human environments due to anthropic changes. This study determined the diversity and distribution of mosquitoes in forest environments in order to analyze the potential vectors of Amazonian forest arboviruses. Mosquitoes were collected by 1) vertical stratification from forest canopy and ground areas using Hooper Pugedo (HP) light traps and human attraction and 2) horizontal stratification using HP light traps in peridomicile, forest edge, and forest environments near the Rio Pardo rural settlement, Amazonas, Brazil. A total of 3,750 mosquitoes were collected, representing 46 species. 3,139 individuals representing 46 species were sampled by vertical stratification. Both the Shannon-Weaver diversity index (H’) and equitability (J’) were higher in the canopy than on the ground. 611 individuals representing 13 species were sampled by horizontal stratification. H’ decreased in the following order: forest edge > forest > peridomicile, and J’ was greater at the forest edge and smaller in the peridomicile environment. Moreover, H’ was higher for the human attraction collection method than the HP traps. A total of 671 pools were analyzed by RT-qPCR; three species were positive for Oropouche-like viruses (Ochlerotatus serratus, Psorophora cingulata, and Haemagogus tropicalis) and the minimum infection rate was 0.8%. The composition of mosquito species did not differ significantly between anthropic and forest environments in Rio Pardo. Some mosquito species, due to their abundance, dispersion in the three environments, and record of natural infection, were hypothesized to participate in the arbovirus transmission cycle in this Amazonian rural settlement.

Factors associated with Chikungunya infection in a cohort of women aged 15-39 y in Fortaleza, Brazil

BACKGROUND

Outbreaks of Chikungunya virus (CHIKV) occurred in Brazil during 2015-2017. Fortaleza was the city that reported the most cases.

METHODS

The first round of a cohort study was conducted among women aged 15-39 y in Fortaleza, Brazil, in 2018 (Zika in Fortaleza). We collected sera to detect CHIKV IgG and IgM antibodies. Factors for CHIKV infection were identified using a Poisson regression model.

RESULTS

We evaluated 1466 serum samples and 13.8% and 37.2% of women were found positive for CHIKV IgM and IgG antibodies, respectively. Living with more than four others in the same house and having an abandoned house nearby were associated with CHIKV infection. Being currently pregnant was associated with a decreased probability of CHIKV infection, which was also associated with pregnant women reporting using more repellent, both inside and outside the house, than non-pregnant women.

CONCLUSIONS

Crowding in households and abandoned houses nearby can increase potential transmission. Policies providing better living conditions and regulation of abandoned sites and buildings are necessary to control the mosquito population. Programmes providing repellant at low or no cost to pregnant women should be implemented in the neighbourhoods where arbovirus infections are endemic.

Exploring local and global regression models to estimate the spatial variability of Zika and Chikungunya cases in Recife, Brazil

INTRODUCTION

In this study, we aim to compare spatial statistic models to estimate the spatial distribution of Zika and Chikungunya infections in the city of Recife, Brazil. We also aim to establish the relationship between the diseases and the analyzed geographical conditions.

METHODS

The models were defined by combining three categories: type of spatial unit, calculation of the dependent variable format, and estimation methods (Geographical Weighted Regression [GWR] and Ordinary Least Square [OLS]). We identified the most accurate model to estimate the spatial distribution of the diseases. After selecting the model that provided best results, the relationship between the geographical conditions and the incidence of the diseases was analyzed.

RESULTS

It was observed that the matrix of 100 meters (as the spatial unit) showed the highest efficiency to estimate the diseases. The best results were observed in the models that utilized the kernel density estimation (as the calculation of the dependent variable). In all models, the GWR method showed the best results. By considering the OLS coefficient values, it was observed that all geographical conditions are related to the incidence of Zika and Chikungunya, while the GWR coefficient values showed where this relationship was more noticeable.

CONCLUSIONS

The model that utilized the combination of the matrix of 100 meters, kernel density estimation (as the calculation of the dependent variable) and GWR method showed the highest efficiency in estimating the spatial distribution of the diseases. The coefficient values showed that all analyzed geographical conditions are related to the illnesses' incidence.

Entomological Assessment of the Status and Risk of Mosquito-borne Arboviral Transmission in Ghana

Entomological surveillance is one of the tools used in monitoring and controlling vector-borne diseases. However, the use of entomological surveillance for arboviral infection vector control is often dependent on finding infected individuals. Although this method may suffice in highly endemic areas, it is not as effective in controlling the spread of diseases in low endemic and non-endemic areas. In this study, we examined the efficiency of using entomological markers to assess the status and risk of arbovirus infection in Ghana, which is considered a non-endemic country, by combining mosquito surveillance with virus isolation and detection. This study reports the presence of cryptic species of mosquitoes in Ghana, demonstrating the need to combine morphological identification and molecular techniques in mosquito surveillance. Furthermore, although no medically important viruses were detected, the importance of insect-specific viruses in understanding virus evolution and arbovirus transmission is discussed. This study reports the first mutualistic relationship between dengue virus and the double-stranded RNA Aedes aegypti totivirus. Finally, this study discusses the complexity of the virome of Aedes and Culex mosquitoes and its implication for arbovirus transmission.

Joint Estimation of Relative Risk for Dengue and Zika Infections, Colombia, 2015-2016

We jointly estimated relative risk for dengue and Zika virus disease (Zika) in Colombia, establishing the spatial association between them at the department and city levels for October 2015-December 2016. Cases of dengue and Zika were allocated to the 87 municipalities of 1 department and the 293 census sections of 1 city in Colombia. We fitted 8 hierarchical Bayesian Poisson joint models of relative risk for dengue and Zika, including area- and disease-specific random effects accounting for several spatial patterns of disease risk (clustered or uncorrelated heterogeneity) within and between both diseases. Most of the dengue and Zika high-risk municipalities varied in their risk distribution; those for Zika were in the northern part of the department and dengue in the southern to northeastern parts. At city level, spatially clustered patterns of dengue high-risk census sections indicated Zika high-risk areas. This information can be used to inform public health decision making.