High prevalence of Zika virus infection in populations of Aedes aegypti from South-western Ecuador.

We performed an arboviral survey in mosquitoes from four endemic Ecuadorian cities (Huaquillas, Machala, Portovelo and Zaruma) during the epidemic period 2016-2018. Collections were performed during the pre-rainy season (2016), peak transmission season (2017) and post-rainy season (2018). Ae. aegypti mosquitoes were pooled by date, location and sex. Pools were screened by RT-PCR for the presence of ZIKV RNA, and infection rates (IRs) per 1,000 specimens were calculated. A total of 2,592 pools (comprising 6,197 mosquitoes) were screened. Our results reveal high IRs in all cities and periods sampled. Overall IRs among female mosquitoes were highest in Machala (89.2), followed by Portovelo (66.4), Zaruma (47.4) and Huaquillas (41.9). Among male mosquitoes, overall IRs were highest in Machala (35.6), followed by Portovelo (33.1), Huaquillas (31.9) and Zaruma (27.9), suggesting that alternative transmission routes (vertical/venereal) can play important roles for ZIKV maintenance in the vector population of these areas. Additionally, we propose that the stabilization of ZIKV vertical transmission in the vector population could help explain the presence of high IRs in field-caught mosquitoes during inter-epidemic periods.

Correction: Recommended reporting items for epidemic forecasting and prediction research: The EPIFORGE 2020 guidelines.

[This corrects the article DOI: 10.1371/journal.pmed.1003793.].

Allergies, body mass, and hospitalization due to arbovirus infection: A prospective surveillance study in Machala, Ecuador.

Dengue, chikungunya, and Zika are arboviruses that cause 390 million infections annually. Risk factors for hospitalization are poorly understood. Communities affected by these diseases have an escalating prevalence of allergies and obesity, which are linked to immune dysfunction. We assessed the association of allergies or body mass with hospitalization for an arbovirus infection. From 2014 to 2017, we recruited participants with a clinical diagnosis of arbovirus infection. Arbovirus infections were laboratory-confirmed and allergies were self-reported. Mid-upper arm circumference (MUAC), weight, and height were measured. We used two logistic regression models to assess the relationships between hospitalization and allergies and between hospitalization and body mass (MUAC for participants <20 years old and body mass index (BMI) for adults ≥20 years old). Models were stratified by age group and adjusted for confounders. For allergies, 41 of 265 were hospitalized. There was no association between allergies and hospitalization. For body mass, 34 of 251 were hospitalized. There was a 43% decrease in hospitalization odds for each additional centimetre MUAC among children (aOR 0.566, 95% CI 0.252-1.019) and a 12% decrease in hospitalization odds for each additional BMI unit among adults (aOR 0.877, 95% CI 0.752-0.998). Our work encourages the exploration of the underlying mechanisms.

Trends in mosquito species distribution modeling: insights for vector surveillance and disease control.

Species distribution modeling (SDM) has become an increasingly common approach to explore questions about ecology, geography, outbreak risk, and global change as they relate to infectious disease vectors. Here, we conducted a systematic review of the scientific literature, screening 563 abstracts and identifying 204 studies that used SDMs to produce distribution estimates for mosquito species. While the number of studies employing SDM methods has increased markedly over the past decade, the overwhelming majority used a single method (maximum entropy modeling; MaxEnt) and focused on human infectious disease vectors or their close relatives. The majority of regional models were developed for areas in Africa and Asia, while more localized modeling efforts were most common for North America and Europe. Findings from this study highlight gaps in taxonomic, geographic, and methodological foci of current SDM literature for mosquitoes that can guide future efforts to study the geography of mosquito-borne disease risk.

Editorial: Infectious Disease Epidemiology and Transmission Dynamics.

Infectious diseases, such as COVID-19 [...].

Chronic kidney disease in Ecuador: An epidemiological and health system analysis of an emerging public health crisis.

The absence of a chronic kidney disease (CKD) registry in Ecuador makes it difficult to assess the burden of disease, but there is an anticipated increase in the incidence of CKD along with increasing diabetes, hypertension and population age. From 2012, augmented funding for renal replacement therapy expanded dialysis clinics and patient coverage. We conducted 73 in-depth sociological interviews with healthcare providers in eight provinces and collected quantitative epidemiological data on patients with CKD diagnoses from six national-level databases between 2015 and 2018. Datasets show a total of 17,484 dialysis patients in 2018, or 567 patients per million population (pmp), with an annual cost exceeding 11% of Ecuador's public health budget. Each year, there were 139-162 pmp new dialysis patients, while doctors reported waiting lists. The number of patients on peritoneal dialysis was static; those on hemodialysis increased over time. Only 13 of 24 provinces were found to have dialysis services, and nephrologists were clustered in major cities, which limits access, delays medical attention, and adds a travel burden on patients. Prevention and screening programs are scarce, while hospitalization is an important reality for CKD patients. CKD is an emerging public health crisis that has increased dramatically over the last decade in Ecuador and is expected to continue, making coverage for all patients impossible and the current structure, unsustainable. A patient registry would help health policymakers and administrators estimate the demand and progression of patients with consideration for comorbidities, disease stage, requirements and costs, mortality and follow-up. This should be used to help identify where to focus prevention and improved treatment efforts. Organized monitoring of CKD patients would benefit from improvements in patient referral. Community-based education and prevention programs, the strengthening of primary healthcare capacity (including basic routine tests) and improved nephrology services are also urgently needed.

Household and climate factors influence Aedes aegypti presence in the arid city of Huaquillas, Ecuador.

Arboviruses transmitted by Aedes aegypti (e.g., dengue, chikungunya, Zika) are of major public health concern on the arid coastal border of Ecuador and Peru. This high transit border is a critical disease surveillance site due to human movement-associated risk of transmission. Local level studies are thus integral to capturing the dynamics and distribution of vector populations and social-ecological drivers of risk, to inform targeted public health interventions. Our study examines factors associated with household-level Ae. aegypti presence in Huaquillas, Ecuador, while accounting for spatial and temporal effects. From January to May of 2017, adult mosquitoes were collected from a cohort of households (n = 63) in clusters (n = 10), across the city of Huaquillas, using aspirator backpacks. Household surveys describing housing conditions, demographics, economics, travel, disease prevention, and city services were conducted by local enumerators. This study was conducted during the normal arbovirus transmission season (January-May), but during an exceptionally dry year. Household level Ae. aegypti presence peaked in February, and counts were highest in weeks with high temperatures and a week after increased rainfall. Univariate analyses with proportional odds logistic regression were used to explore household social-ecological variables and female Ae. aegypti presence. We found that homes were more likely to have Ae. aegypti when households had interruptions in piped water service. Ae. aegypti presence was less likely in households with septic systems. Based on our findings, infrastructure access and seasonal climate are important considerations for vector control in this city, and even in dry years, the arid environment of Huaquillas supports Ae. aegypti breeding habitat.

Recommended reporting items for epidemic forecasting and prediction research: The EPIFORGE 2020 guidelines.

BACKGROUND: The importance of infectious disease epidemic forecasting and prediction research is underscored by decades of communicable disease outbreaks, including COVID-19. Unlike other fields of medical research, such as clinical trials and systematic reviews, no reporting guidelines exist for reporting epidemic forecasting and prediction research despite their utility. We therefore developed the EPIFORGE checklist, a guideline for standardized reporting of epidemic forecasting research. METHODS AND FINDINGS: We developed this checklist using a best-practice process for development of reporting guidelines, involving a Delphi process and broad consultation with an international panel of infectious disease modelers and model end users. The objectives of these guidelines are to improve the consistency, reproducibility, comparability, and quality of epidemic forecasting reporting. The guidelines are not designed to advise scientists on how to perform epidemic forecasting and prediction research, but rather to serve as a standard for reporting critical methodological details of such studies. CONCLUSIONS: These guidelines have been submitted to the EQUATOR network, in addition to hosting by other dedicated webpages to facilitate feedback and journal endorsement.

Social Stressors, Arboviral Infection, and Immune Dysregulation in the Coastal Lowland Region of Ecuador: A Mixed Methods Approach in Ecological Perspective.

Aedes aegypti, the mosquito that transmits arboviral diseases such as dengue (DENV), chikungunya (CHIKV), and Zika viruses (ZIKV), is present in tropical and subtropical regions of the world. Individuals at risk of mosquito-borne disease (MBD) in the urban tropics face daily challenges linked to their socio-environment conditions, such as poor infrastructure, poverty, crowding, and limited access to adequate healthcare. These daily demands induce chronic stress events and dysregulated immune responses. We sought to investigate the role of socio-ecologic risk factors in distress symptoms and their impact on biological responses to MBD in Machala, Ecuador. Between 2017 and 2019, individuals (≥ 18 years) with suspected arbovirus illness (DENV, ZIKV, and CHIKV) from sentinel clinics were enrolled (index cases, N = 28). Cluster investigations of the index case households and people from four houses within a 200-m radius of index home (associate cases, N = 144) were conducted (total N = 172). Hair samples were collected to measure hair cortisol concentration (HCC) as a stress biomarker. Blood samples were collected to measure serum cytokines concentrations of IL-10, IL-8, TNF-α, and TGF-ß. Univariate analyses were used to determine the association of socio-health metrics related to perceived stress scores (PSS), HCC, and immune responses. We found that housing conditions influence PSS and HCC levels in individuals at risk of MBD. Inflammatory cytokine distribution was associated with the restorative phase of immune responses in individuals with low-moderate HCC. These data suggest that cortisol may dampen pro-inflammatory responses and influence activation of the restorative phase of immune responses to arboviral infections.

Assessing critical gaps in COVID-19 testing capacity: the case of delayed results in Ecuador.

BACKGROUND: Testing is crucial for COVID-19 response and management, however, WHO's preparedness index omits estimations of actual testing capabilities, which influence the ability to contain, mitigate and clinically manage infectious diseases. With one of the highest excess death rates globally, Ecuador had a comparatively low number of confirmed COVID-19 cases, which may have been influenced by limited availability of data for decision-making due to low laboratory capacity. METHODS: We examine de-identified data on 55,063 individuals with suspected COVID-19 between February 27 and April 30, 2020 included in the RT-PCR testing database collected by the Ministry of Health. Processing times and rates per province, and the number of pending tests, were tallied cumulatively. We assessed the relationship between sample shipping, laboratory capacity and case completion using a negative binomial generalized linear model. RESULTS: The national average time for case completion was 3 days; 12.1% of samples took ≥10 days to complete; the national average daily backlog was 29.1 tests per 100,000 people. Only 8 out of 24 provinces had authorized COVID-19 processing laboratories but not all processed samples. There was an association between samples coming from outside the processing laboratory province, the number of other samples present at the laboratory during processing, and the amount of time needed to process a sample. Samples from another province took 1.29 times as long to process, on average. The percentage of pending results on April 30 was 67.1%. CONCLUSION: A centralized RT-PCR testing system contributes to critical delays in processing, which may mask a case burden higher than reported, impeding timely awareness, and adequate clinical care and vaccination strategies and subsequent monitoring. Although Ecuador adapted or authorized existing facilities to address limitations in laboratory capacity for COVID-19, this study highlights the need to estimate and augment laboratory capabilities for improved decision making and policies on diagnostic guidelines and availability. Support is needed to procure the necessary human and physical resources at all phases of diagnostic testing, including transportation of samples and supplies, and information management. Strengthening emergency preparedness enables a clear understanding of COVID-19 disparities within and across the country.

Climate predicts geographic and temporal variation in mosquito-borne disease dynamics on two continents.

Climate drives population dynamics through multiple mechanisms, which can lead to seemingly context-dependent effects of climate on natural populations. For climate-sensitive diseases, such as dengue, chikungunya, and Zika, climate appears to have opposing effects in different contexts. Here we show that a model, parameterized with laboratory measured climate-driven mosquito physiology, captures three key epidemic characteristics across ecologically and culturally distinct settings in Ecuador and Kenya: the number, timing, and duration of outbreaks. The model generates a range of disease dynamics consistent with observed Aedes aegypti abundances and laboratory-confirmed arboviral incidence with variable accuracy (28-85% for vectors, 44-88% for incidence). The model predicted vector dynamics better in sites with a smaller proportion of young children in the population, lower mean temperature, and homes with piped water and made of cement. Models with limited calibration that robustly capture climate-virus relationships can help guide intervention efforts and climate change disease projections.

Time to reality check the promises of machine learning-powered precision medicine.

Machine learning methods, combined with large electronic health databases, could enable a personalised approach to medicine through improved diagnosis and prediction of individual responses to therapies. If successful, this strategy would represent a revolution in clinical research and practice. However, although the vision of individually tailored medicine is alluring, there is a need to distinguish genuine potential from hype. We argue that the goal of personalised medical care faces serious challenges, many of which cannot be addressed through algorithmic complexity, and call for collaboration between traditional methodologists and experts in medical machine learning to avoid extensive research waste.

Identification and evaluation of epidemic prediction and forecasting reporting guidelines: A systematic review and a call for action.

INTRODUCTION: High quality epidemic forecasting and prediction are critical to support response to local, regional and global infectious disease threats. Other fields of biomedical research use consensus reporting guidelines to ensure standardization and quality of research practice among researchers, and to provide a framework for end-users to interpret the validity of study results. The purpose of this study was to determine whether guidelines exist specifically for epidemic forecast and prediction publications. METHODS: We undertook a formal systematic review to identify and evaluate any published infectious disease epidemic forecasting and prediction reporting guidelines. This review leveraged a team of 18 investigators from US Government and academic sectors. RESULTS: A literature database search through May 26, 2019, identified 1467 publications (MEDLINE n = 584, EMBASE n = 883), and a grey-literature review identified a further 407 publications, yielding a total 1777 unique publications. A paired-reviewer system screened in 25 potentially eligible publications, of which two were ultimately deemed eligible. A qualitative review of these two published reporting guidelines indicated that neither were specific for epidemic forecasting and prediction, although they described reporting items which may be relevant to epidemic forecasting and prediction studies. CONCLUSIONS: This systematic review confirms that no specific guidelines have been published to standardize the reporting of epidemic forecasting and prediction studies. These findings underscore the need to develop such reporting guidelines in order to improve the transparency, quality and implementation of epidemic forecasting and prediction research in operational public health.

A decade of arbovirus emergence in the temperate southern cone of South America: dengue, Aedes aegypti and climate dynamics in Córdoba, Argentina.

BACKGROUND: Argentina is located at the southern temperate range of arboviral transmission by the mosquito Aedes aegypti and has experienced a rapid increase in disease transmission in recent years. Here we present findings from an entomological surveillance study that began in Córdoba, Argentina, following the emergence of dengue in 2009. METHODS: From 2009 to 2017, larval surveys were conducted monthly, from November to May, in 600 randomly selected households distributed across the city. From 2009 to 2013, ovitraps (n = 177) were sampled weekly to monitor the oviposition activity of Ae. aegypti. We explored seasonal and interannual dynamics of entomological variables and dengue transmission. Cross correlation analysis was used to identify significant lag periods. RESULTS: Aedes aegypti were detected over the entire study period, and abundance peaked during the summer months (January to March). We identified a considerable increase in the proportion of homes with juvenile Ae. aegypti over the study period (from 5.7% of homes in 2009-10 to 15.4% of homes in 2016-17). Aedes aegypti eggs per ovitrap and larval abundance were positively associated with temperature in the same month. Autochthonous dengue transmission peaked in April, following a peak in imported dengue cases in March; autochthonous dengue was not positively associated with vector or climate variables. CONCLUSIONS: This longitudinal study provides insights into the complex dynamics of arbovirus transmission and vector populations in a temperate region of arbovirus emergence. Our findings suggest that Córdoba is well suited for arbovirus disease transmission, given the stable and abundant vector populations. Further studies are needed to better understand the role of regional human movement.

Medically Attended Outpatient Coronavirus Infections in Ecuadorean Children During the 20 Months Preceding Countrywide Lockdown Related to the SARS-CoV-2 Pandemic of 2020.

BACKGROUND: Human coronaviruses (HCoVs) cause respiratory tract infections during childhood manifesting as common colds, bronchiolitis, croup and pneumonia. In temperate geographies, HCoV activity peaks between December and March. The epidemiology and manifestations of HCoV infections have not been previously reported from Ecuador. METHODS: Children <5 years who presented with ≥2 symptoms consistent with an acute respiratory tract infection were eligible for enrollment. After obtaining informed consent, demographic data and details regarding the acute illness were recorded. Secretions collected with a nasopharyngeal swab underwent diagnostic testing using multiplex polymerase chain reaction. RESULTS: A total of 850 subjects were enrolled. A total of 677 (80%) tested positive for at least 1 pathogen, including 49 (7.2%) who tested positive for ≥1 HCoV type. HCoV-NL63 was the most frequent type detected (39%), followed by HCoV-OC43 (27%), 229E (22%) and HKU1 (12%). Nearly all subjects who tested positive for HCoV had nasal congestion or secretions (47/49; 96%). The most frequent syndromic diagnosis was common cold (41%), followed by bronchiolitis (27%). We found no association between the infecting HCoV type and subject's syndromic diagnosis (P > 0.05) or anatomic location of infection (upper vs. lower respiratory tract; P > 0.05). The 2018-2019 peak HCoV activity occurred from October to November; the 2019-2020 peak occurred from January to February. CONCLUSIONS: HCoVs were detected in ~7% of outpatient Ecuadorean children <5 years of age with symptoms of acute respiratory tract infection. The most frequently detected HCoV types, and the period of peak HCoV activity differed for the 2018-2019 and 2019-2020 seasons.

Key Findings and Comparisons From Analogous Case-Cluster Studies for Dengue Virus Infection Conducted in Machala, Ecuador, and Kamphaeng Phet, Thailand.

Dengue viruses (DENV) pose a significant and increasing threat to human health across broad regions of the globe. Currently, prevention, control, and treatment strategies are limited. Promising interventions are on the horizon, including multiple vaccine candidates under development and a renewed and innovative focus on controlling the vector, Aedes aegypti. However, significant gaps persist in our understanding of the similarities and differences in DENV epidemiology across regions of potential implementation and evaluation. In this manuscript, we highlight and compare findings from two analogous cluster-based studies for DENV transmission and pathogenesis conducted in Thailand and Ecuador to identify key features and questions for further pursuit. Despite a remarkably similar incidence of DENV infection among enrolled neighborhood contacts at the two sites, we note a higher occurrence of secondary infection and severe illness in Thailand compared to Ecuador. A higher force of infection in Thailand, defined as the incidence of infection among susceptible individuals, is suggested by the higher number of captured Aedes mosquitoes per household, the increasing proportion of asymptomatic infections with advancing age, and the high proportion of infections identified as secondary-type infections by serology. These observations should be confirmed in long-term, parallel prospective cohort studies conducted across regions, which would advantageously permit characterization of baseline immune status (susceptibility) and contemporaneous assessment of risks and risk factors for dengue illness.

The origins of dengue and chikungunya viruses in Ecuador following increased migration from Venezuela and Colombia.

BACKGROUND: In recent years, Ecuador and other South American countries have experienced an increase in arboviral diseases. A rise in dengue infections was followed by introductions of chikungunya and Zika, two viruses never before seen in many of these areas. Furthermore, the latest socioeconomic and political instability in Venezuela and the mass migration of its population into the neighboring countries has given rise to concerns of infectious disease spillover and escalation of arboviral spread in the region. RESULTS: We performed phylogeographic analyses of dengue (DENV) and chikungunya (CHIKV) virus genomes sampled from a surveillance site in Ecuador in 2014-2015, along with genomes from the surrounding countries. Our results revealed at least two introductions of DENV, in 2011 and late 2013, that initially originated from Venezuela and/or Colombia. The introductions were subsequent to increases in the influx of Venezuelan and Colombian citizens into Ecuador, which in 2013 were 343% and 214% higher than in 2009, respectively. However, we show that Venezuela has historically been an important source of DENV dispersal in this region, even before the massive exodus of its population, suggesting already established paths of viral distribution. Like DENV, CHIKV was introduced into Ecuador at multiple time points in 2013-2014, but unlike DENV, these introductions were associated with the Caribbean. Our findings indicated no direct CHIKV connection between Ecuador, Colombia, and Venezuela as of 2015, suggesting that CHIKV was, at this point, not following the paths of DENV spread. CONCLUSION: Our results reveal that Ecuador is vulnerable to arbovirus import from many geographic locations, emphasizing the need of continued surveillance and more diversified prevention strategies. Importantly, increase in human movement along established paths of viral dissemination, combined with regional outbreaks and epidemics, may facilitate viral spread and lead to novel virus introductions. Thus, strengthening infectious disease surveillance and control along migration routes and improving access to healthcare for the vulnerable populations is of utmost importance.

Ingested insecticide to control Aedes aegypti: developing a novel dried attractive toxic sugar bait device for intra-domiciliary control.

BACKGROUND: Illnesses transmitted by Aedes aegypti (Linnaeus, 1762) such as dengue, chikungunya and Zika comprise a considerable global burden; mosquito control is the primary public health tool to reduce disease transmission. Current interventions are inadequate and insecticide resistance threatens the effectiveness of these options. Dried attractive bait stations (DABS) are a novel mechanism to deliver insecticide to Ae. aegypti. The DABS are a high-contrast 28 inch2 surface coated with dried sugar-boric acid solution. Aedes aegypti are attracted to DABS by visual cues only, and the dried sugar solution elicits an ingestion response from Ae. aegypti landing on the surface. The study presents the development of the DABS and tests of their impact on Ae. aegypti mortality in the laboratory and a series of semi-field trials. METHODS: We conducted multiple series of laboratory and semi-field trials to assess the survivability of Ae. aegypti mosquitoes exposed to the DABS. In the laboratory experiments, we assessed the lethality, the killing mechanism, and the shelf life of the device through controlled experiments. In the semi-field trials, we released laboratory-reared female Ae. aegypti into experimental houses typical of peri-urban tropical communities in South America in three trial series with six replicates each. Laboratory experiments were conducted in Quito, Ecuador, and semi-field experiments were conducted in Machala, Ecuador, an area with abundant wild populations of Ae. aegypti and endemic arboviral transmission. RESULTS: In the laboratory, complete lethality was observed after 48 hours regardless of physiological status of the mosquito. The killing mechanism was determined to be through ingestion, as the boric acid disrupted the gut of the mosquito. In experimental houses, total mosquito mortality was greater in the treatment house for all series of experiments (P < 0.0001). CONCLUSIONS: The DABS devices were effective at killing female Ae. aegypti under a variety of laboratory and semi-field conditions. DABS are a promising intervention for interdomiciliary control of Ae. aegypti and arboviral disease prevention.

Severity Index for Suspected Arbovirus (SISA): Machine learning for accurate prediction of hospitalization in subjects suspected of arboviral infection.

BACKGROUND: Dengue, chikungunya, and Zika are arboviruses of major global health concern. Decisions regarding the clinical management of suspected arboviral infection are challenging in resource-limited settings, particularly when deciding on patient hospitalization. The objective of this study was to determine if hospitalization of individuals with suspected arboviral infections could be predicted using subject intake data. METHODOLOGY/PRINCIPAL FINDINGS: Two prediction models were developed using data from a surveillance study in Machala, a city in southern coastal Ecuador with a high burden of arboviral infections. Data were obtained from subjects who presented at sentinel medical centers with suspected arboviral infection (November 2013 to September 2017). The first prediction model-called the Severity Index for Suspected Arbovirus (SISA)-used only demographic and symptom data. The second prediction model-called the Severity Index for Suspected Arbovirus with Laboratory (SISAL)-incorporated laboratory data. These models were selected by comparing the prediction ability of seven machine learning algorithms; the area under the receiver operating characteristic curve from the prediction of a test dataset was used to select the final algorithm for each model. After eliminating those with missing data, the SISA dataset had 534 subjects, and the SISAL dataset had 98 subjects. For SISA, the best prediction algorithm was the generalized boosting model, with an AUC of 0.91. For SISAL, the best prediction algorithm was the elastic net with an AUC of 0.94. A sensitivity analysis revealed that SISA and SISAL are not directly comparable to one another. CONCLUSIONS/SIGNIFICANCE: Both SISA and SISAL were able to predict arbovirus hospitalization with a high degree of accuracy in our dataset. These algorithms will need to be tested and validated on new data from future patients. Machine learning is a powerful prediction tool and provides an excellent option for new management tools and clinical assessment of arboviral infection.