Zika, dengue and chikungunya population prevalence in Rio de Janeiro city, Brazil, and the importance of seroprevalence studies to estimate the real number of infected individuals

High Burden of Dengue and Chikungunya Virus in Paraguay: Seroprevalence Findings From Blood Donors

The rise of reemerging pathogens such as DENV and CHIKV presents a major public health threat. With half the global population at risk, Paraguay experiences particularly high infection rates. Despite this, data on the seroprevalence of these viruses in this country is lacking. This study aims to assess the seroprevalence of anti-DENV IgG and anti-CHIKV IgG among blood donors in Paraguay. Serum samples from 546 blood donors across seven regional districts and Asunción were collected from March to May 2023. Participants filled out a questionnaire and underwent eligibility screening. Serum samples were tested for anti-DENV IgG and anti-CHIKV IgG antibodies using immunoassays. Data were analyzed using IBM SPSS version 23.0. The median (IQR) age of donors was 34 (26-44), and 47.1% were female. Anti-DENV IgG prevalence was 87.7%, ranging from 73.7% to 100% by location, with an age-related association. Donors aged 18 to 25 had a 79.2% seroprevalence, while those over 46 had the highest at 91.5% (p = 0.010). Anti-CHIKV IgG prevalence was 37.2%, with men showing a seroprevalence nearly 10% higher than women, but no significant age-related differences were observed. Regional variation in CHIKV seroprevalence was not significant. In conclusion, this study suggests a high seroprevalence of both DENV and CHIKV in Paraguayan blood donors. The high DENV seroprevalence reflects the impact of past outbreaks, while the notable CHIKV prevalence underscores the effects of recent outbreaks. Continuous surveillance, improved diagnostics, and effective vector control measures are essential to mitigate these arboviruses' impact in Paraguay.

Modeling the impact of vaccine campaigns on the epidemic transmission dynamics of chikungunya virus outbreaks

A licensed chikungunya vaccine now exists; however, it remains unclear whether it could be deployed during outbreaks to reduce the health burden. We used an epidemic in Paraguay as a case study. We conducted a seroprevalence study and used models to reconstruct epidemic transmission dynamics, providing a framework to assess the theoretical impact of a vaccine had it been available. We estimated that 33.0% (95% confidence interval (CI) 30.1-36.0%) of the population became infected during the outbreak. Of these individuals, 6.3% (95% CI 5.8-6.9%) were detected by the surveillance system, with a mean infection fatality ratio of 0.013% (95% CI 0.012-0.014%). A disease-blocking vaccine with 75% efficacy deployed in 40% of individuals aged ≥12 years over a 3-month period would have prevented 34,200 (95% CI 30,900-38,000) cases, representing 23% of all cases, and 73 (95% CI 66-81) deaths. If the vaccine also leads to infection blocking, 88% of cases would have been averted. These findings suggest that the vaccine is an important new tool to control outbreaks.

Seroprevalence of dengue, Zika, and chikungunya in São Sebastião, Brazil (2020-2021): a population-based survey

BACKGROUND

Urban arboviruses pose a significant global burden, particularly in tropical regions like Brazil. São Sebastião, a lower-middle-class urban area just 26 km from the Brazilian capital, is an endemic area for dengue. However, asymptomatic cases may obscure the actual extent of the disease. In this study, we measured the seroprevalence of dengue, Zika virus, and chikungunya, and compared these findings with surveillance data.

METHODS

A cross-sectional study was conducted involving 1,535 households. ELISA serological tests were performed to detect IgM and IgG antibodies against dengue, Zika virus, and chikungunya. History of previous exposure to arboviruses, data on age, gender, and education level were collected through a questionnaire. Participants who tested positive for IgM and/or IgG were classified as soropositive. Statistical analyses included tests for normality, associations, mean comparisons, and correlations. Positive serological results were compared with cases captured by local epidemiological surveillance.

RESULTS

The study included 1,405 individuals, divided into two groups related to pre-pandemic and pandemic COVID-19 phases. Among participants, 0.7% to 28.8% self-reported history of dengue, Zika, or chikungunya. However, the estimated overall seroprevalence was 64.3% (95% CI: 61.8-66.7) for dengue virus, 51.4% (95% CI: 48.8-53.9) for Zika virus, and 5.4% (95% CI: 4.4-6.7) for chikungunya virus. Multiple arboviruses were noted at 4.0% (95% CI: 3.1-5.1). Advancing age and lower education were associated with higher exposure to arboviruses (p < 0.05). The estimated number of urban arboviral infections was 84 times higher than reported cases.

CONCLUSIONS

The large gap between seroprevalence estimates and cases captured by epidemiological surveillance suggests a silent circulation of arboviruses, highlighting the need for comprehensive serological surveys in endemic regions. Addressing these discrepancies is crucial for effective resource allocation and implementation of public health interventions.

Unraveling the Complexity of Chikungunya Virus Infection Immunological and Genetic Insights in Acute and Chronic Patients

Background: The chikungunya virus (CHIKV), transmitted by infected Aedes mosquitoes, has caused a significant number of infections worldwide. In Brazil, the emergence of the CHIKV-ECSA genotype in 2014 posed a major public health challenge due to its association with more severe symptoms. Objectives/Methods: This study aimed to shed new light on the host immune response by examining the whole-blood transcriptomic profile of both CHIKV-acute and chronically infected individuals from Feira de Santana, Bahia, Brazil, a region heavily affected by CHIKV, Dengue, and Zika virus epidemics. Results: Our data reveal complex symptomatology characterized by arthralgia and post-chikungunya neuropathy in individuals with chronic sequelae, particularly affecting women living in socially vulnerable situations. Analysis of gene modules suggests heightened metabolic processes, represented by an increase in NADH, COX5A, COA3, CYC1, and cap methylation in patients with acute disease. In contrast, individuals with chronic manifestations exhibit a distinct pattern of histone methylation, probably mediated by NCOA3 in the coactivation of different nuclear receptors, KMT2 genes, KDM3B and TET2, and with alterations in the immunological response, majorly led by IL-17RA, IL-6R, and STAT3 Th17 genes. Conclusion: Our results emphasize the complexity of CHIKV disease progression, demonstrating the heterogeneous gene expression and symptomatologic scenario across both acute and chronic phases. Moreover, the identification of specific gene modules associated with viral pathogenesis provides critical insights into the molecular mechanisms underlying these distinct clinical manifestations.

Precision arbovirus serology with a pan-arbovirus peptidome

Arthropod-borne viruses represent a crucial public health threat. Current arboviral serology assays are either labor intensive or incapable of distinguishing closely related viruses, and many zoonotic arboviruses that may transition to humans lack any serologic assays. In this study, we present a programmable phage display platform, ArboScan, that evaluates antibody binding to overlapping peptides that represent the proteomes of 691 human and zoonotic arboviruses. We confirm that ArboScan provides detailed antibody binding information from animal sera, human sera, and an arthropod blood meal. ArboScan identifies distinguishing features of antibody responses based on exposure history in a Colombian cohort of Zika patients. Finally, ArboScan details epitope level information that rapidly identifies candidate epitopes with potential protective significance. ArboScan thus represents a resource for characterizing human and animal arbovirus antibody responses at cohort scale.

A multimodal framework for extraction and fusion of satellite images and public health data

In low- and middle-income countries, the substantial costs associated with traditional data collection pose an obstacle to facilitating decision-making in the field of public health. Satellite imagery offers a potential solution, but the image extraction and analysis can be costly and requires specialized expertise. We introduce SatelliteBench, a scalable framework for satellite image extraction and vector embeddings generation. We also propose a novel multimodal fusion pipeline that utilizes a series of satellite imagery and metadata. The framework was evaluated generating a dataset with a collection of 12,636 images and embeddings accompanied by comprehensive metadata, from 81 municipalities in Colombia between 2016 and 2018. The dataset was then evaluated in 3 tasks: including dengue case prediction, poverty assessment, and access to education. The performance showcases the versatility and practicality of SatelliteBench, offering a reproducible, accessible and open tool to enhance decision-making in public health.

Chikungunya seroprevalence, force of infection, and prevalence of chronic disability after infection in endemic and epidemic settings: a systematic review, meta-analysis, and modelling study

BACKGROUND

Chikungunya is an arboviral disease transmitted by Aedes aegypti and Aedes albopictus mosquitoes with a growing global burden linked to climate change and globalisation. We aimed to estimate chikungunya seroprevalence, force of infection (FOI), and prevalence of related chronic disability and hospital admissions in endemic and epidemic settings.

METHODS

In this systematic review, meta-analysis, and modelling study, we searched PubMed, Ovid, and Web of Science for articles published from database inception until Sept 26, 2022, for prospective and retrospective cross-sectional studies that addressed serological chikungunya virus infection in any geographical region, age group, and population subgroup and for longitudinal prospective and retrospective cohort studies with data on chronic chikungunya or hospital admissions in people with chikungunya. We did a systematic review of studies on chikungunya seroprevalence and fitted catalytic models to each survey to estimate location-specific FOI (ie, the rate at which susceptible individuals acquire chikungunya infection). We performed a meta-analysis to estimate the proportion of symptomatic patients with laboratory-confirmed chikungunya who had chronic chikungunya or were admitted to hospital following infection. We used a random-effects model to assess the relationship between chronic sequelae and follow-up length using linear regression. The systematic review protocol is registered online on PROSPERO, CRD42022363102.

FINDINGS

We identified 60 studies with data on seroprevalence and chronic chikungunya symptoms done across 76 locations in 38 countries, and classified 17 (22%) of 76 locations as endemic settings and 59 (78%) as epidemic settings. The global long-term median annual FOI was 0·007 (95% uncertainty interval [UI] 0·003-0·010) and varied from 0·0001 (0·00004-0·0002) to 0·113 (0·07-0·20). The highest estimated median seroprevalence at age 10 years was in south Asia (8·0% [95% UI 6·5-9·6]), followed by Latin America and the Caribbean (7·8% [4·9-14·6]), whereas median seroprevalence was lowest in the Middle East (1·0% [0·5-1·9]). We estimated that 51% (95% CI 45-58) of people with laboratory-confirmed symptomatic chikungunya had chronic disability after infection and 4% (3-5) were admitted to hospital following infection.

INTERPRETATION

We inferred subnational heterogeneity in long-term average annual FOI and transmission dynamics and identified both endemic and epidemic settings across different countries. Brazil, Ethiopia, Malaysia, and India included both endemic and epidemic settings. Long-term average annual FOI was higher in epidemic settings than endemic settings. However, long-term cumulative incidence of chikungunya can be similar between large outbreaks in epidemic settings with a high FOI and endemic settings with a relatively low FOI.

FUNDING

International Vaccine Institute.

Beyond Borders: Investigating the Mysteries of Cacipacoré, a Lesser-Studied Arbovirus in Brazil

Cacipacoré virus (CPCV) was discovered in 1977 deep in the Amazon rainforest from the blood of a black-faced ant thrush (Formicarius analis). As a member of the family Flaviviridae and genus orthoflavivirus, CPCV's intricate ecological association with vectors and hosts raises profound questions. CPCV's transmission cycle may involve birds, rodents, equids, bovines, marsupials, non-human primates, and bats as potential vertebrate hosts, whereas Culex and Aedes spp. mosquitoes have been implicated as potential vectors of transmission. The virus' isolation across diverse biomes, including urban settings, suggests its adaptability, as well as presents challenges for its accurate diagnosis, and thus its impact on veterinary and human health. With no specific treatment or vaccine, its prevention hinges on traditional arbovirus control measures. Here, we provide an overview of its ecology, transmission cycles, epidemiology, pathogenesis, and prevention, aiming at improving our ability to better understand this neglected arbovirus.

Global Prevalence of Zika and Chikungunya Coinfection: A Systematic Review and Meta-Analysis

Zika virus (ZIKV) and chikungunya virus (CHIKV) are arthropod-borne viruses with significant pathogenicity, posing a substantial health and economic burden on a global scale. Moreover, ZIKV-CHIKV coinfection imposes additional therapeutic challenges as there is no specific treatment for ZIKV or CHIKV infection. While a growing number of studies have documented the ZIKV-CHIKV coinfection, there is currently a lack of conclusive reports on this coinfection. Therefore, we performed a systematic review and meta-analysis to determine the true statistics of ZIKV-CHIKV coinfection in the global human population. Relevant studies were searched for in PubMed, Scopus, and Google Scholar without limitation in terms of language or publication date. A total of 33 studies containing 41,460 participants were included in this meta-analysis. The study protocol was registered with PROSPERO under the registration number CRD42020176409. The pooled prevalence and confidence intervals of ZIKV-CHIKV coinfection were computed using a random-effects model. The study estimated a combined global prevalence rate of 1.0% [95% CI: 0.7-1.2] for the occurrence of ZIKV-CHIKV coinfection. The region of North America (Mexico, Haiti, and Nicaragua) and the country of Haiti demonstrated maximum prevalence rates of 2.8% [95% CI: 1.5-4.1] and 3.5% [95% CI: 0.2-6.8], respectively. Moreover, the prevalence of coinfection was found to be higher in the paediatric group (2.1% [95% CI: 0.0-4.2]) in comparison with the adult group (0.7% [95% CI: 0.2-1.1]). These findings suggest that the occurrence of ZIKV-CHIKV coinfection varies geographically and by age group. The results of this meta-analysis will guide future investigations seeking to understand the underlying reasons for these variations and the causes of coinfection and to develop targeted prevention and control strategies.

Immunity of Canadians and risk of epidemics workshop - Conference report

On November 18-19, 2019, the Immunity of Canadians and Risk of Epidemics (iCARE) Network convened a workshop in Toronto, Ontario, Canada. The objectives of the workshop were to raise the profile of sero-epidemiology in Canada, discuss best practice and methodological innovations, and strategize on the future direction of sero-epidemiology work in Canada. In this conference report, we describe the presentations and discussions from the workshop, and comment on the impact of the COVID-19 pandemic on serosurveillance initiatives, both in Canada and abroad.

Joint spatial modeling of the risks of co-circulating mosquito-borne diseases in Ceará, Brazil

Mosquito-borne diseases such as dengue and chikungunya have been co-circulating in the Americas, causing great damage to the population. In 2021, for instance, almost 1.5 million cases were reported on the continent, being Brazil the responsible for most of them. Even though they are transmitted by the same mosquito, it remains unclear whether there exists a relationship between both diseases. In this paper, we model the geographic distributions of dengue and chikungunya over the years 2016 to 2021 in the Brazilian state of Ceará. We use a Bayesian hierarchical spatial model for the joint analysis of two arboviruses that includes spatial covariates as well as specific and shared spatial effects that take into account the potential autocorrelation between the two diseases. Our findings allow us to identify areas with high risk of one or both diseases. Only 7% of the areas present high relative risk for both diseases, which suggests a competition between viruses. This study advances the understanding of the geographic patterns and the identification of risk factors of dengue and chikungunya being able to help health decision-making.

Solid waste management and Aedes aegypti infestation interconnections: A regression tree application

Public health is at the core of all environmental and anthropic impacts. Urban and territorial planners should include public health concerns in their plans. Basic sanitation infrastructure is essential to maintaining public health and social and economic development. This infrastructure deficiency causes diseases, death and economic losses in developing countries. Framing interconnections among health, sanitation, urbanization and circular economy will assist sustainable development goal achievements. This study aims to identify the relationships between solid waste management indicators in Brazil and the Aedes aegypti mosquito infestation index. Regression trees were employed for modelling due to the complexity and characteristics of the data. The analyses were performed separately from data collected from 3501 municipalities and 42 indicators from the country's five regions. Results show that expenses and personnel indicators were the most critical indicators (in the mid-western, southeastern and southern regions), operational (northeastern (NE) region) and management (northern region). The mean absolute errors ranged from 0.803 (southern region) to 2.507 (NE region). Regional analyses indicate that the municipalities with better SWM results display lower infestation rates in buildings and residences. This research is innovative as it analyses infestation rates rather than dengue prevalence, using a machine learning method, in a multidisciplinary research field that needs further study.

Epidemiological and genomic investigation of chikungunya virus in Rio de Janeiro state, Brazil, between 2015 and 2018

Since 2014, Brazil has experienced an unprecedented epidemic caused by chikungunya virus (CHIKV), with several waves of East-Central-South-African (ECSA) lineage transmission reported across the country. In 2018, Rio de Janeiro state, the third most populous state in Brazil, reported 41% of all chikungunya cases in the country. Here we use evolutionary and epidemiological analysis to estimate the timescale of CHIKV-ECSA-American lineage and its epidemiological patterns in Rio de Janeiro. We show that the CHIKV-ECSA outbreak in Rio de Janeiro derived from two distinct clades introduced from the Northeast region in mid-2015 (clade RJ1, n = 63/67 genomes from Rio de Janeiro) and mid-2017 (clade RJ2, n = 4/67). We detected evidence for positive selection in non-structural proteins linked with viral replication in the RJ1 clade (clade-defining: nsP4-A481D) and the RJ2 clade (nsP1-D531G). Finally, we estimate the CHIKV-ECSA's basic reproduction number (R0) to be between 1.2 to 1.6 and show that its instantaneous reproduction number (Rt) displays a strong seasonal pattern with peaks in transmission coinciding with periods of high Aedes aegypti transmission potential. Our results highlight the need for continued genomic and epidemiological surveillance of CHIKV in Brazil, particularly during periods of high ecological suitability, and show that selective pressures underline the emergence and evolution of the large urban CHIKV-ECSA outbreak in Rio de Janeiro.

Developing brain under renewed attack: viral infection during pregnancy

Living in a globalized world, viral infections such as CHIKV, SARS-COV-2, and ZIKV have become inevitable to also infect the most vulnerable groups in our society. That poses a danger to these populations including pregnant women since the developing brain is sensitive to maternal stressors including viral infections. Upon maternal infection, the viruses can gain access to the fetus via the maternofetal barrier and even to the fetal brain during which factors such as viral receptor expression, time of infection, and the balance between antiviral immune responses and pro-viral mechanisms contribute to mother-to-fetus transmission and fetal infection. Both the direct pro-viral mechanisms and the resulting dysregulated immune response can cause multi-level impairment in the maternofetal and brain barriers and the developing brain itself leading to dysfunction or even loss of several cell populations. Thus, maternal viral infections can disturb brain development and even predispose to neurodevelopmental disorders. In this review, we discuss the potential contribution of maternal viral infections of three relevant relative recent players in the field: Zika, Chikungunya, and Severe Acute Respiratory Syndrome Coronavirus-2, to the impairment of brain development throughout the entire route.

Seroprevalence of Dengue, Chikungunya and Zika at the epicenter of the congenital microcephaly epidemic in Northeast Brazil: A population-based survey

BACKGROUND

The four Dengue viruses (DENV) serotypes were re-introduced in Brazil's Northeast region in a couple of decades, between 1980's and 2010's, where the DENV1 was the first detected serotype and DENV4 the latest. Zika (ZIKV) and Chikungunya (CHIKV) viruses were introduced in Recife around 2014 and led to large outbreaks in 2015 and 2016, respectively. However, the true extent of the ZIKV and CHIKV outbreaks, as well as the risk factors associated with exposure to these viruses remain vague.

METHODS

We conducted a stratified multistage household serosurvey among residents aged between 5 and 65 years in the city of Recife, Northeast Brazil, from August 2018 to February 2019. The city neighborhoods were stratified and divided into high, intermediate, and low socioeconomic strata (SES). Previous ZIKV, DENV and CHIKV infections were detected by IgG-based enzyme linked immunosorbent assays (ELISA). Recent ZIKV and CHIKV infections were assessed through IgG3 and IgM ELISA, respectively. Design-adjusted seroprevalence were estimated by age group, sex, and SES. The ZIKV seroprevalence was adjusted to account for the cross-reactivity with dengue. Individual and household-related risk factors were analyzed through regression models to calculate the force of infection. Odds Ratio (OR) were estimated as measure of effect.

PRINCIPAL FINDINGS

A total of 2,070 residents' samples were collected and analyzed. The force of viral infection for high SES were lower as compared to low and intermediate SES. DENV seroprevalence was 88.7% (CI95%:87.0-90.4), and ranged from 81.2% (CI95%:76.9-85.6) in the high SES to 90.7% (CI95%:88.3-93.2) in the low SES. The overall adjusted ZIKV seroprevalence was 34.6% (CI95%:20.0-50.9), and ranged from 47.4% (CI95%:31.8-61.5) in the low SES to 23.4% (CI95%:12.2-33.8) in the high SES. The overall CHIKV seroprevalence was 35.7% (CI95%:32.6-38.9), and ranged from 38.6% (CI95%:33.6-43.6) in the low SES to 22.3% (CI95%:15.8-28.8) in the high SES. Surprisingly, ZIKV seroprevalence rapidly increased with age in the low and intermediate SES, while exhibited only a small increase with age in high SES. CHIKV seroprevalence according to age was stable in all SES. The prevalence of serological markers of ZIKV and CHIKV recent infections were 1.5% (CI95%:0.1-3.7) and 3.5% (CI95%:2.7-4.2), respectively.

CONCLUSIONS

Our results confirmed continued DENV transmission and intense ZIKV and CHIKV transmission during the 2015/2016 epidemics followed by ongoing low-level transmission. The study also highlights that a significant proportion of the population is still susceptible to be infected by ZIKV and CHIKV. The reasons underlying a ceasing of the ZIKV epidemic in 2017/18 and the impact of antibody decay in susceptibility to future DENV and ZIKV infections may be related to the interplay between disease transmission mechanism and actual exposure in the different SES.

Epidemiology and Economic Burden of Chikungunya: A Systematic Literature Review

Chikungunya (CHIK) is a re-emerging viral infection endemic in tropical and subtropical areas. While the typical clinical presentation is an acute febrile syndrome, long-term articular complications and even death can occur. This review characterizes the global epidemiological and economic burden of chikungunya. The search included studies published from 2007 to 2022 in MEDLINE, Embase, LILACS, and SciELO for a thorough evaluation of the literature. Rayyan software was used for data analysis, and data were summarized descriptively and reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Seventy-six publications were included. Chikungunya is widely distributed in the tropics, including Africa, Asia, South America, and Oceania/the Pacific Islands, and co-circulates with other simultaneous arboviruses such as DENV, ZIKV, and YFV. Chikungunya infection can lead to chronic articular manifestations with a significant impact on the quality of life in the long term. In addition, it generates absenteeism and economic and social losses and can cause fatal infections in vulnerable populations, mainly in high-risk patients with co-morbidities and at the extremes of age. Reported costs associated with CHIKV diseases are substantial and vary by region, age group, and public/private delivery of healthcare services. The chikungunya disease burden includes chronicity, severe infections, increased hospitalization risks, and associated mortality. The disease can impact the economy in several spheres, significantly affecting the health system and national economies. Understanding and measuring the full impact of this re-emerging disease is essential.

Chikungunya seroprevalence in population-based studies: a systematic review and meta-analysis

BACKGROUND

Seroprevalence studies about chikungunya infection are usually conducted after epidemics to estimate the magnitude of the attack. This study aimed to estimate the seroprevalence of CHIKV by WHO region, considering the periods of introduction of the virus in these regions and its potential to lead to epidemics.

METHODS

We systematically reviewed Medline/Pubmed, Embase, Lilacs, Scopus and Web of Science for original articles published up to 2020. Cohort, case-control and cross-sectional studies were eligible for inclusion, based on the results of laboratory diagnosis of previous or previous and recent infection. Those conducted with symptomatic individuals were excluded.

RESULTS

596 articles were identified, 197 full-text were reviewed and 64 were included, resulting in 71 seroprevalences. Most were cross-sectional studies (92%), between 2001 and 2020 (92%), with population of all ages (55%), conducted in Kenya (10.9%), Brazil (9.4%) and French Polynesia (7.8%). The pooled estimates were 24% (95%CI 19-29; I² = 99.7%; p < 0.00), being 21% (95%CI 13-30; I² = 99.5%; p < 0.00) for adults, 7% (95%CI 0-23; I² = 99.7%; p < 0.00) for children and 30% (95%CI 23-38; I² = 99.7%; p < 0.00) for all ages. The higher seroprevalences were found in African, the Americas and South-East Asian Regions.

CONCLUSIONS

The great heterogeneity of seroprevalences points to the persistence of viral circulation. Even where the seroprevalence is high, the population replacement and the absence of vaccines mean that the risk of virus spread and epidemics remains.

REGISTRATION

PROSPERO CRD42020166227.

Development and validation of a clinical rule for the diagnosis of chikungunya fever in a dengue-endemic area

Rio de Janeiro is a dengue-endemic city that experienced Zika and chikungunya epidemics between 2015 and 2019. Differential diagnosis is crucial for indicating adequate treatment and assessing prognosis and risk of death. This study aims to derive and validate a clinical rule for diagnosing chikungunya based on 3,214 suspected cases consecutively treated at primary and secondary health units of the sentinel surveillance system (up to 7 days from onset of symptoms) in Rio de Janeiro, Brazil. Of the total sample, 624 were chikungunya, 88 Zika, 51 dengue, and 2,451 were negative for all these arboviruses according to real-time polymerase chain reaction (RT-qPCR). The derived rule included fever (1 point), exanthema (1 point), myalgia (2 points), arthralgia or arthritis (2 points), and joint edema (2 points), providing an AUC (area under the receiver operator curve) = 0.695 (95% CI: 0.662-0.725). Scores of 4 points or more (validation sample) showed 74.3% sensitivity (69.0% - 79.2%) and 51.5% specificity (48.8% - 54.3%). Adding more symptoms improved the specificity at the expense of a lower sensitivity compared to definitions proposed by government agencies based on fever alone (European Center for Disease Control) or in combination with arthralgia (World Health Organization) or arthritis (Pan American Health Organization, Brazilian Ministry of Health). The proposed clinical rule offers a rapid, low-cost, easy-to-apply strategy to differentiate chikungunya fever from other arbovirus infections during epidemics.

Serological Evidence of Exposure to Saint Louis Encephalitis and West Nile Viruses in Horses of Rio de Janeiro, Brazil

Infections with arboviruses are reported worldwide. Saint Louis encephalitis (SLEV) and West Nile (WNV) viruses are closely related flaviviruses affecting humans and animals. SLEV has been sporadically detected in humans, and corresponding antibodies have been frequently detected in horses throughout Brazil. WNV was first reported in western Brazil over a decade ago, has been associated with neurological disorders in humans and equines and its prevalence is increasing nationwide. Herein, we investigated by molecular and serological methods the presence of SLEV and WNV in equines from Rio de Janeiro. A total of 435 serum samples were collected from healthy horses and tested for specific neutralizing antibodies by plaque reduction neutralization test (PRNT90). Additionally, samples (serum, cerebrospinal fluid, central nervous system tissue) from 72 horses, including horses with neurological disorders resulting in a fatal outcome or horses which had contact with them, were tested by real-time reverse transcription-polymerase chain reaction (RT-qPCR) for both viruses. Adopting the criterion of four-fold antibody titer difference, 165 horses (38%) presented neutralizing antibodies for flaviviruses, 89 (20.4%) for SLEV and five (1.1%) for WNV. No evidence of SLEV and WNV infection was detected by RT-qPCR and, thus, such infection could not be confirmed in the additional samples. Our findings indicate horses of Rio de Janeiro were exposed to SLEV and WNV, contributing to the current knowledge on the distribution of these viruses in Brazil.

A Chikungunya Virus Multiepitope Recombinant Protein Expressed from the Binary System Insect Cell/Recombinant Baculovirus Is Useful for Laboratorial Diagnosis of Chikungunya

Chikungunya virus (CHIKV) is an arbovirus currently distributed worldwide, causing a disease that shares clinical signs and symptoms with other illnesses, such as dengue and Zika and leading to a challenging clinical differential diagnosis. In Brazil, CHIKV emerged in 2014 with the simultaneous introduction of both Asian and East/Central/South African (ECSA) genotypes. Laboratorial diagnosis of CHIKV is mainly performed by molecular and serological assays, with the latter more widely used. Although many commercial kits are available, their costs are still high for many underdeveloped and developing countries where the virus circulates. Here we described the development and evaluation of a multi-epitope recombinant protein-based IgG-ELISA (MULTREC IgG-ELISA) test for the specific detection of anti-CHIKV antibodies in clinical samples, as an alternative approach for laboratorial diagnosis. The MULTREC IgG-ELISA showed 86.36% of sensitivity and 100% of specificity, and no cross-reactivity with other exanthematic diseases was observed. The recombinant protein was expressed from the binary system insect cell/baculovirus using the crystal-forming baculoviral protein polyhedrin as a carrier of the target recombinant protein to facilitate recovery. The crystals were at least 10 times smaller in size and had an amorphous shape when compared to the polyhedrin wild-type crystal. The assay uses a multi-epitope antigen, representing two replicates of 18 amino acid sequences from the E2 region and a sequence of 17 amino acids from the nsP3 region of CHIKV. The recombinant protein was highly expressed, easy to purify and has demonstrated its usefulness in confirming chikungunya exposure, indeed showing a good potential tool for epidemiological surveillance.

Faster indicators of chikungunya incidence using Google searches

Chikungunya, a mosquito-borne disease, is a growing threat in Brazil, where over 640,000 cases have been reported since 2017. However, there are often long delays between diagnoses of chikungunya cases and their entry in the national monitoring system, leaving policymakers without the up-to-date case count statistics they need. In contrast, weekly data on Google searches for chikungunya is available with no delay. Here, we analyse whether Google search data can help improve rapid estimates of chikungunya case counts in Rio de Janeiro, Brazil. We build on a Bayesian approach suitable for data that is subject to long and varied delays, and find that including Google search data reduces both model error and uncertainty. These improvements are largest during epidemics, which are particularly important periods for policymakers. Including Google search data in chikungunya surveillance systems may therefore help policymakers respond to future epidemics more quickly.

To respond quickly to disease outbreaks, policymakers need rapid data on the number of new infections. However, for many diseases, such data is very delayed, due to the administrative work required to record each case in a disease surveillance system. This is a problem for data on chikungunya, a mosquito-borne disease which is a growing threat in Brazil. In Rio de Janeiro, delays in chikungunya cases being recorded average four weeks. These delays are sometimes longer and sometimes shorter. In stark contrast to chikungunya data, data on what people are searching for on Google is available almost immediately. People suffering from chikungunya might search on Google for information about the disease. Here, we investigate whether rapidly available Google data can help generate quick estimates of the number of chikungunya cases in Rio de Janeiro in the previous week. Our model uses a Bayesian methodology to help account for the varying delays in the chikungunya data. We show that including Google search data in the model reduces both the error and uncertainty of the chikungunya case count estimates, in particular during epidemics. Our method could be used to help policymakers to respond more quickly to future chikungunya epidemics.

Chikungunya virus seroprevalence in asymptomatic blood donors during an outbreak in the Federal District of Brazil

INTRODUCTION

Chikungunya virus (CHIKV) is a mosquito-borne alphavirus belonging to the Togaviridae family. The symptomatic infection is characterised by acute febrile disease which generally results in severe arthralgia and myalgia, however, most of the CHIKV infections remain asymptomatic. CHIKV RNA detection in asymptomatic volunteers may be responsible for the transfusion transmission of this infection, especially during outbreaks. There is no information for CHIKV seroprevalence among blood donors from the Federal District of Brazil.

AIM

In early 2019, the Federal District of Brazil experienced a CHIKV outbreak, and this study evaluates the anti-CHIKV IgM and IgG presence in a well characterised cohort of blood donors from this region.

METHODOLOGY

Blood samples were collected from 450 volunteer blood donors during a CHIKV outbreak and tested for the presence of anti-CHIKV IgG and IgM antibodies using ELISA.

RESULTS

The CHIKV seroprevalence was 0.89% (n = 4/450) and anti-CHIKV IgM prevalence was 1.11% (n = 5/450).

CONCLUSION

The obtained results demonstrated that at least some of the blood donors have experienced CHIKV infection which can be related to a hypothetical risk of CHIKV transfusion transmission. More studies are necessary in order to examine the impact of CHIKV on blood transfusion.

Fine-scale heterogeneity in population density predicts wave dynamics in dengue epidemics

The spread of dengue and other arboviruses constitutes an expanding global health threat. The extensive heterogeneity in population distribution and potential complexity of movement in megacities of low and middle-income countries challenges predictive modeling, even as its importance to disease spread is clearer than ever. Using surveillance data at fine resolution from Rio de Janeiro, we document a scale-invariant pattern in the size of successive epidemics following DENV4 emergence. Using surveillance data at fine resolution following the emergence of the DENV4 dengue serotype in Rio de Janeiro, we document a pattern in the size of successive epidemics that is invariant to the scale of spatial aggregation. This pattern emerges from the combined effect of herd immunity and seasonal transmission, and is strongly driven by variation in population density at sub-kilometer scales. It is apparent only when the landscape is stratified by population density and not by spatial proximity as has been common practice. Models that exploit this emergent simplicity should afford improved predictions of the local size of successive epidemic waves.

High prevalence of arthralgia among infants with Chikungunya disease during the 2019 outbreak in northern region of the state of Rio de Janeiro

INTRODUCTION

In a low-income setting with simultaneous presence of Dengue virus, Zika virus, and Chikungunya virus (CHIKV) in the same region, the difficulty of establishing a clinical diagnosis when the molecular test is not a possibility. Thus, it is important to identify signs and symptoms of Chikungunya that can be used to differentiate it from other arboviruses in children.

METHODS

This is a cross-sectional study, which was developed in Rio de Janeiro State, Brazil, with the analysis of pediatric medical records regarding arboviruses. Considering that the population had already been exposed to Dengue and Zika viruses and were experiencing the first notification of the CHIKV. The ethics committee approved this research, and all those legally responsible for the children signed the consent form.

RESULTS

In total, 159 children were seen of which 98 were suspected CHIKV cases, and 51 had their diagnosis confirmed with reagent IgM/IgG for CHIKV. The symptoms that the pediatric population with CHIKV presented most often were fever (90.2%), arthralgia (76.5%), and exanthema (62.7%) in both suspected and confirmed cases of Chikungunya. Thus, CHIKV in those children presents a clinical profile similar to those found in other studies referring to adults. Additionally, only arthralgia and a high aspartate transaminase were related to the positivity of serology for Chikungunya.

CONCLUSIONS

This study describes the signs and symptoms of CHIKV exhibited in the pediatric population with a mild and moderate presentation similar to the findings in the adult during an epidemic experienced in a population vulnerable to CHIKV.

Interacting Epidemics in Amazonian Brazil: Prior Dengue Infection Associated With Increased Coronavirus Disease 2019 (COVID-19) Risk in a Population-Based Cohort Study

BACKGROUND

Immunity after dengue virus (DENV) infection has been suggested to cross-protect from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and mortality.

METHODS

We tested whether serologically proven prior DENV infection diagnosed in September-October 2019, before the coronavirus disease 2019 (COVID-19) pandemic, reduced the risk of SARS-CoV-2 infection and clinically apparent COVID-19 over the next 13 months in a population-based cohort in Amazonian Brazil. Mixed-effects multiple logistic regression analysis was used to identify predictors of infection and disease, adjusting for potential individual and household-level confounders. Virus genomes from 14 local SARS-CoV-2 isolates were obtained using whole-genome sequencing.

RESULTS

Anti-DENV immunoglobulin G (IgG) was found in 37.0% of 1285 cohort participants (95% confidence interval [CI]: 34.3% to 39.7%) in 2019, with 10.4 (95% CI: 6.7-15.5) seroconversion events per 100 person-years during the follow-up. In 2020, 35.2% of the participants (95% CI: 32.6% to 37.8%) had anti-SARS-CoV-2 IgG and 57.1% of the 448 SARS-CoV-2 seropositives (95% CI: 52.4% to 61.8%) reported clinical manifestations at the time of infection. Participants aged >60 years were twice more likely to have symptomatic COVID-19 than children under 5 years. Locally circulating SARS-CoV-2 isolates were assigned to the B.1.1.33 lineage. Contrary to the cross-protection hypothesis, prior DENV infection was associated with twice the risk of clinically apparent COVID-19 upon SARS-CoV-2 infection, with P values between .025 and .039 after adjustment for identified confounders.

CONCLUSIONS

Higher risk of clinically apparent COVID-19 among individuals with prior dengue has important public health implications for communities sequentially exposed to DENV and SARS-CoV-2 epidemics.

National Holidays and Social Mobility Behaviors: Alternatives for Forecasting COVID-19 Deaths in Brazil

In this paper, we investigate the influence of holidays and community mobility on the transmission rate and death count of COVID-19 in Brazil. We identify national holidays and hallmark holidays to assess their effect on disease reports of confirmed cases and deaths. First, we use a one-variate model with the number of infected people as input data to forecast the number of deaths. This simple model is compared with a more robust deep learning multi-variate model that uses mobility and transmission rates (R0, Re) from a SEIRD model as input data. A principal components model of community mobility, generated by the principal component analysis (PCA) method, is added to improve the input features for the multi-variate model. The deep learning model architecture is an LSTM stacked layer combined with a dense layer to regress daily deaths caused by COVID-19. The multi-variate model incremented with engineered input features can enhance the forecast performance by up to 18.99% compared to the standard one-variate data-driven model.