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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 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.

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. Graphical Abstract

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

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.

The global health crisis of antibacterial resistance (ABR) poses a particular threat in low-resource settings like East Africa. Interventions for ABR typically target antibiotic use, overlooking the wider set of factors which drive vulnerability and behaviours. In this cross-sectional study, we investigated the joint contribution of behavioural, environmental, socioeconomic, and demographic factors associated with higher risk of multi-drug resistant urinary tract infections (MDR UTIs) in Kenya, Tanzania, and Uganda. We sampled outpatients with UTI symptoms in healthcare facilities and linked their microbiology data with patient, household and community level data. Using bivariate statistics and Bayesian profile regression on a sample of 1610 individuals, we show that individuals with higher risk of MDR UTIs were more likely to have compound and interrelated social and environmental disadvantages: they were on average older, with lower education, had more chronic illness, lived in resource-deprived households, more likely to have contact with animals, and human or animal waste. This suggests that interventions to tackle ABR need to take account of intersectional socio-environmental disadvantage as a priority. Antibiotic resistance is biologically driven by antibiotic use but other social, environmental, demographic, economic and behavioural factors also contribute. Here, the authors conduct a cross-sectional study to identify risk factors jointly associated with multidrug resistant urinary tract infection in East Africa.

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.

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.

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.

Season is a major determinant of infectious disease rates, including arboviruses spread by mosquitoes, such as dengue, chikungunya, and Zika. Seasonal patterns of disease are driven by a combination of climatic or environmental factors, such as temperature or rainfall, and human behavioral time trends, such as school year schedules, holidays, and weekday-weekend patterns. These factors affect both disease rates and healthcare-seeking behavior. Seasonality of dengue fever has been studied in the context of climatic factors, but short- and long-term time trends are less well-understood. With 2009-2016 medical record data from patients diagnosed with dengue fever at two hospitals in rural Ecuador, we used Poisson generalized linear modeling to determine short- and long-term seasonal patterns of dengue fever, as well as the effect of day of the week and public holidays. In a subset analysis, we determined the impact of school schedules on school-aged children. With a separate model, we examined the effect of climate on diagnosis patterns. In the first model, the most important predictors of dengue fever were annual sinusoidal fluctuations in disease, long-term trends (as represented by a spline for the full study duration), day of the week, and hospital. Seasonal trends showed single peaks in case diagnoses, during mid-March. Compared to the average of all days, cases were more likely to be diagnosed on Tuesdays (risk ratio (RR): 1.26, 95% confidence interval (CI) 1.05-1.51) and Thursdays (RR: 1.25, 95% CI 1.02-1.53), and less likely to be diagnosed on Saturdays (RR: 0.81, 95% CI 0.65-1.01) and Sundays (RR: 0.74, 95% CI 0.58-0.95). Public holidays were not significant predictors of dengue fever diagnoses, except for an increase in diagnoses on the day after Christmas (RR: 2.77, 95% CI 1.46-5.24). School schedules did not impact dengue diagnoses in school-aged children. In the climate model, important climate variables included the monthly total precipitation, an interaction between total precipitation and monthly absolute minimum temperature, an interaction between total precipitation and monthly precipitation days, and a three-way interaction between minimum temperature, total precipitation, and precipitation days. This is the first report of long-term dengue fever seasonality in Ecuador, one of few reports from rural patients, and one of very few studies utilizing daily disease reports. These results can inform local disease prevention efforts, public health planning, as well as global and regional models of dengue fever trends.