Spatiotemporal Heterogeneity in the Distribution of Chikungunya and Zika Virus Case Incidences during their 2014 to 2016 Epidemics in Barranquilla, Colombia

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.

A systematic review of the data, methods and environmental covariates used to map Aedes-borne arbovirus transmission risk

BACKGROUND

Aedes (Stegomyia)-borne diseases are an expanding global threat, but gaps in surveillance make comprehensive and comparable risk assessments challenging. Geostatistical models combine data from multiple locations and use links with environmental and socioeconomic factors to make predictive risk maps. Here we systematically review past approaches to map risk for different Aedes-borne arboviruses from local to global scales, identifying differences and similarities in the data types, covariates, and modelling approaches used.

METHODS

We searched on-line databases for predictive risk mapping studies for dengue, Zika, chikungunya, and yellow fever with no geographical or date restrictions. We included studies that needed to parameterise or fit their model to real-world epidemiological data and make predictions to new spatial locations of some measure of population-level risk of viral transmission (e.g. incidence, occurrence, suitability, etc.).

RESULTS

We found a growing number of arbovirus risk mapping studies across all endemic regions and arboviral diseases, with a total of 176 papers published 2002-2022 with the largest increases shortly following major epidemics. Three dominant use cases emerged: (i) global maps to identify limits of transmission, estimate burden and assess impacts of future global change, (ii) regional models used to predict the spread of major epidemics between countries and (iii) national and sub-national models that use local datasets to better understand transmission dynamics to improve outbreak detection and response. Temperature and rainfall were the most popular choice of covariates (included in 50% and 40% of studies respectively) but variables such as human mobility are increasingly being included. Surprisingly, few studies (22%, 31/144) robustly tested combinations of covariates from different domains (e.g. climatic, sociodemographic, ecological, etc.) and only 49% of studies assessed predictive performance via out-of-sample validation procedures.

CONCLUSIONS

Here we show that approaches to map risk for different arboviruses have diversified in response to changing use cases, epidemiology and data availability. We identify key differences in mapping approaches between different arboviral diseases, discuss future research needs and outline specific recommendations for future arbovirus mapping.

Sociodemographic and environmental factors associated with dengue, Zika, and chikungunya among adolescents from two Brazilian capitals

Among the emerging and reemerging arboviral diseases, Zika, dengue and chikungunya deserve special attention due to their wide geographical distribution and clinical severity. The three arboviruses are transmitted by the same vector and can present similar clinical syndromes, bringing challenges to their identification and register. Demographic characteristics and individual and contextual social factors have been associated with the three arboviral diseases. However, little is known about such associations among adolescents, whose relationships with the social environment are different from those of adult populations, implying potentially different places, types, and degrees of exposure to the vector, particularly in the school context. This study aims to identify sociodemographic and environmental risk factors for the occurrence of Zika, dengue, and chikungunya in a cohort of adolescents from the Study of Cardiovascular Risks in Adolescents-ERICA-in the cities of Rio de Janeiro/RJ and Fortaleza/CE, from January 2015 to March 2019. Cases were defined as adolescents with laboratory or clinical-epidemiological diagnosis of Zika, dengue, or chikungunya, notified and registered in the Information System for Notifiable Diseases (SINAN). The cases were identified by linkage between the databases of the ERICA cohort and of SINAN. Multilevel Cox regression was employed to estimate hazard ratios (HR) as measures of association and respective 95% confidence intervals (95%CI). In comparison with adolescents living in lower socioeconomic conditions, the risk of becoming ill due to any of the three studied arboviral diseases was lower among those living in better socioeconomic conditions (HR = 0.43; 95%CI: 0.19-0.99; p = 0.047) and in the adolescents who attended school in the afternoon period (HR = 0.17; 95%CI: 0.06-0.47; p<0.001). When compared to areas whose Building Infestation Index (BII) for Aedes aegypti was considered satisfactory, a BII in the school region classified as "alert" and "risk" was associated with a higher risk of arboviral diseases (HR = 1.62, 95%CI: 0.98-2.70; p = 0.062; HR = 3.72, 95%CI: 1.27-10.9; p = 0.017, respectively). These findings indicate that living in less favored socioeconomic conditions, attending school in the morning, and having a high BII for Ae. aegypti in school's region can contribute to an increased risk of infection by Zika, dengue, or chikungunya in adolescents. The identification of residential or school areas based on those variables can contribute to the implementation of control measures in population groups and priority locations.

Dengue, chikungunya, and Zika virus infections in Latin America and the Caribbean: a systematic review

Objectives

To characterize the distribution profile of dengue, chikungunya, and Zika virus infections in Latin America and the Caribbean and to identify possible factors associated with the risk of dissemination and severity of these arboviruses.

Methods

The protocol of this review was registered on the PROSPERO platform. Searches were carried out in the following databases: Virtual Health Library, MEDLINE/PubMed, and Embase. The search terms were: Zika virus, Zika virus infection, dengue, dengue virus, chikungunya virus, chikungunya fever, epidemiology, observational study, Latin America, and Caribbean region. Studies that addressed the distribution of these arboviruses and the risk factors associated with dengue, Zika virus disease, and chikungunya, published between January 2000 and August 2020 in English, Portuguese, and Spanish, were included.

Results

Of 95 studies included, 70 identified risk factors, clinical manifestations, and outcomes for arbovirus infections and 25 described complications and/or deaths. The highest frequency of confirmed cases was for dengue. Brazil reported most cases of the three arboviruses in the period analyzed. Environmental and socioeconomic factors facilitated the proliferation and adaptation of vectors, and host-related factors were reported to aggravate dengue. Most deaths were due to chikungunya, Zika virus disease caused most neurological alterations, and dengue resulted in greater morbidity leading to more frequent hospitalization.

Conclusions

The review provides a broad view of the three arboviruses and the intrinsic aspects of infections, and highlights the factors that influence the spread of these viruses in the populations studied.

Epidemics of chikungunya, Zika, and COVID-19 reveal bias in case-based mapping

Accurate tracing of epidemic spread over space enables effective control measures. We examined three metrics of infection and disease in a pediatric cohort (N≈3,000) over two chikungunya and one Zika epidemic, and in a household cohort (N=1,793) over one COVID-19 epidemic in Managua, Nicaragua. We compared spatial incidence rates (cases/total population), infection risks (infections/total population), and disease risks (cases/infected population). We used generalized additive and mixed-effects models, Kulldorf's spatial scan statistic, and intracluster correlation coefficients. Across different analyses and all epidemics, incidence rates considerably underestimated infection and disease risks, producing large and spatially non-uniform biases distinct from biases due to incomplete case ascertainment. Infection and disease risks exhibited distinct spatial patterns, and incidence clusters inconsistently identified areas of either risk. While incidence rates are commonly used to infer infection and disease risk in a population, we find that this can induce substantial biases and adversely impact policies to control epidemics.

Spatio-temporal modelling of the first Chikungunya epidemic in an intra-urban setting: The role of socioeconomic status, environment and temperature

Three key elements are the drivers of Aedes-borne disease: mosquito infestation, virus circulating, and susceptible human population. However, information on these aspects is not easily available in low- and middle-income countries. We analysed data on factors that influence one or more of those elements to study the first chikungunya epidemic in Rio de Janeiro city in 2016. Using spatio-temporal models, under the Bayesian framework, we estimated the association of those factors with chikungunya reported cases by neighbourhood and week. To estimate the minimum temperature effect in a non-linear fashion, we used a transfer function considering an instantaneous effect and propagation of a proportion of such effect to future times. The sociodevelopment index and the proportion of green areas (areas with agriculture, swamps and shoals, tree and shrub cover, and woody-grass cover) were included in the model with time-varying coefficients, allowing us to explore how their associations with the number of cases change throughout the epidemic. There were 13627 chikungunya cases in the study period. The sociodevelopment index presented the strongest association, inversely related to the risk of cases. Such association was more pronounced in the first weeks, indicating that socioeconomically vulnerable neighbourhoods were affected first and hardest by the epidemic. The proportion of green areas effect was null for most weeks. The temperature was directly associated with the risk of chikungunya for most neighbourhoods, with different decaying patterns. The temperature effect persisted longer where the epidemic was concentrated. In such locations, interventions should be designed to be continuous and to work in the long term. We observed that the role of the covariates changes over time. Therefore, time-varying coefficients should be widely incorporated when modelling Aedes-borne diseases. Our model contributed to the understanding of the spatio-temporal dynamics of an urban Aedes-borne disease introduction in a tropical metropolitan city.

Spatial connectivity in mosquito-borne disease models: a systematic review of methods and assumptions

Spatial connectivity plays an important role in mosquito-borne disease transmission. Connectivity can arise for many reasons, including shared environments, vector ecology and human movement. This systematic review synthesizes the spatial methods used to model mosquito-borne diseases, their spatial connectivity assumptions and the data used to inform spatial model components. We identified 248 papers eligible for inclusion. Most used statistical models (84.2%), although mechanistic are increasingly used. We identified 17 spatial models which used one of four methods (spatial covariates, local regression, random effects/fields and movement matrices). Over 80% of studies assumed that connectivity was distance-based despite this approach ignoring distant connections and potentially oversimplifying the process of transmission. Studies were more likely to assume connectivity was driven by human movement if the disease was transmitted by an Aedes mosquito. Connectivity arising from human movement was more commonly assumed in studies using a mechanistic model, likely influenced by a lack of statistical models able to account for these connections. Although models have been increasing in complexity, it is important to select the most appropriate, parsimonious model available based on the research question, disease transmission process, the spatial scale and availability of data, and the way spatial connectivity is assumed to occur.

Seroprevalence of Chikungunya virus and living conditions in Feira de Santana, Bahia-Brazil

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.

Acceptability of a Hypothetical Zika Vaccine among Women from Colombia and Spain Exposed to ZIKV: A Qualitative Study

Zika virus (ZIKV) can cause pregnancy loss and congenital Zika syndrome, among other poor health outcomes. The ZIKV epidemic in 2015-2017 disproportionately affected pregnant women in poor-resource settings. We aimed to understand perceptions and attitudes towards a hypothetical ZIKV vaccine, women's willingness to be vaccinated, and potential barriers and facilitators for vaccine acceptance in 1) migrant women living in Spain who travelled to their countries of origin and were diagnosed with ZIKV infection during pregnancy, and their healthcare providers, and 2) women living in Colombia who delivered a child with microcephaly. An exploratory qualitative study based on phenomenology and grounded theory was conducted. Data were collected through in-depth, paired and semi-structured interviews. Overall, women from both sites were willing to receive a hypothetical ZIKV vaccine. However, some expressed concerns of being vaccinated during pregnancy, yet they would accept it if the vaccine was recommended by a healthcare professional they trust. Main fears towards vaccination were related to vaccine safety and potential adverse effects on child's health. Women reported feeling hesitant to participate in a ZIKV vaccine trial. These results may contribute to guiding the effective delivery of future ZIKV vaccines among populations most at risk and particularly vulnerable.

Demographic and clinical characteristics of chikungunya patients from six Colombian cities, 2014-2015

In 2014, the chikungunya virus reached Colombia for the first time, resulting in a nationwide epidemic. The objective of this study was to describe the demographics and clinical characteristics of suspected chikungunya cases. Chikungunya infection was confirmed by enzyme-linked immunosorbent assay and 548 patients where included in the study. Of these patients, 295 were positive for antibodies against chikungunya (53.8%), and 27.6% (151/295) were symptomatic for chikungunya infection, with a symptomatic:asymptomatic ratio of 1.04:1. Factors associated with infection included low income and low socio-economic strata (odds ratio [OR]: 1.8; 95% confidence interval [CI]: 1.0-3.2, p = 0.003 and OR: 2.1; CI: 1.3-3.4, p = 0.002, respectively). Confirmed symptomatic cases were associated with symmetric arthritis (OR: 11.7; CI: 6.0-23.0, p < 0.001) of ankles (OR: 8.5; CI: 3.5-20.9, p < 0.001), hands (OR: 8.5; CI: 3.5-20.9, p < 0.001), feet (OR: 6.5; CI: 2.8-15.3, p < 0.001), and wrists (OR: 17.3; CI: 2.3-130.5, p < 0.001). Our study showed that poverty is associated with chikungunya infection. Public health strategies to prevent and control chikungunya should focus on poorer communities that are more vulnerable to infection. The rate of asymptomatic infections among confirmed cases was 48.8%. However, those with symptoms displayed a characteristic rheumatic clinical picture, which could help differentiate chikungunya infection from other endemic viral diseases.