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Osorio, J.

Publications and source records attributed to Osorio, J..

4 recordsLinked to original sources

Seasonal patterns of dengue fever in rural Ecuador: 2009-2016

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, day of the week, and hospital. Seasonal trends showed single peaks in case diagnoses, during April. Compared to an average day, 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 (RR: 2.14, 95% CI 1.26--3.64), an interaction between total precipitation and monthly absolute minimum temperature (RR: 0.93, 95% CI 0.88--0.98), an interaction between total precipitation and monthly precipitation days (RR: 0.90, 95% CI 0.82--0.99), and a three-way interaction between minimum temperature, total precipitation, and precipitation days (RR: 1.01, 95% CI 1.00--1.02). 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.\n\nAuthor summaryDengue fever exhibits a seasonal pattern in many parts of the world, much of which has been attributed to climate and weather. However, additional factors may contribute to dengue seasonality. With 2009-- 2016 medical record data from rural Ecuador, we studied the short-and long-term seasonal patterns of dengue fever, as well as the effect of school schedules and public holidays. We also examined the effect of climate on dengue. We found that dengue diagnoses peak once per year during April, but that diagnoses are also affected by day of the week. Dengue was also impacted by regional climate and complex interactions between local weather variables. 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. This is the first report on the impacts of school schedules, holidays, and weekday-weekend patterns on dengue diagnoses. These results suggest a potential impact of human behaviors on dengue exposure risk. More broadly, these results can inform local disease prevention efforts and public health planning, as well as global and regional models of dengue fever trends.

epidemiology

Zika viruses of both African and Asian lineages cause fetal harm in a vertical transmission model

Congenital Zika virus (ZIKV) infection was first linked to birth defects during the American outbreak 1-3. It has been proposed that mutations unique to the Asian/American-genotype explain, at least in part, the ability of Asian/American ZIKV to cause congenital Zika syndrome (CZS) 4,5. Recent studies identified mutations in ZIKV infecting humans that arose coincident with the outbreak in French Polynesia and were stably maintained during subsequent spread to the Americas 5. Here we show that African ZIKV can infect and harm fetuses and that the S139N mutation that has been associated with the American outbreak is not essential for fetal harm. Our findings, in a vertical transmission mouse model, suggest that ZIKV will remain a threat to pregnant women for the foreseeable future, including in Africa, southeast Asia, and the Americas. Additional research is needed to better understand the risks associated with ZIKV infection during pregnancy, both in areas where the virus is newly endemic and where it has been circulating for decades.

microbiology

Infection via mosquito bite alters Zika virus replication kinetics in rhesus macaques

For more than three decades it has been recognized that small amounts of vector saliva can significantly alter the infectivity of vector-borne pathogens and subsequent in vivo dynamics. Mouse and nonhuman primate models now serve as useful platforms to study Zika virus (ZIKV) pathogenesis, candidate therapies, and vaccines, but they rely on needle inoculation of virus: the effects of mosquito-borne infection on disease outcome have not been explored in these models. To model vector-borne transmission of ZIKV in nonhuman primates, we infected Aedes aegypti mosquitoes with ZIKV and allowed them to feed on four ZIKV-naive rhesus macaques. We compared ZIKV replication kinetics and tissue distribution between animals that were subcutaneously inoculated with 104 plaque-forming units of ZIKV and those that were exposed via mosquito bite. Here, we show that infection via mosquito bite delays ZIKV replication to peak viral loads in rhesus macaques. Importantly, in mosquito-infected animals ZIKV tissue distribution was limited to hemolymphatic tissues, female reproductive tract tissues, kidney, and liver, potentially emulating key features of human ZIKV infections, most of which are characterized by mild or asymptomatic disease. This newly developed system will be valuable for studying ZIKV disease because it more closely mimics human infection by mosquito bite than needle-based inoculations.

microbiology

Investigating The Functional Consequence Of White Matter Damage: An Automatic Pipeline To Create Longitudinal Disconnection Tractograms

Neurosurgical resection is one of the few opportunities researchers have to image the human brain both prior to and following focal damage. One of the challenges associated with studying brains undergoing surgical resection is that they often do not fit the brain templates most image-processing methodologies are based on, so manual intervention is required to reconcile the pathology and the most extreme cases must be excluded. Manual intervention requires significant time investment and introduces reproducibility concerns. We propose an automatic longitudinal pipeline based on High Angular Resolution Diffusion Imaging acquisitions to facilitate a Pathway Lesion Symptom Mapping analysis relating focal white matter injury to functional deficits. This two-part approach includes (i) automatic segmentation of focal white matter injury from anisotropic power differences, and (ii) modeling disconnection using tractography on the single-subject level, which specifically identifies the disconnections associated with focal white matter damage. The advantages of this approach stem from (1) objective and automatic lesion segmentation and tractogram generation, (2) objective and precise segmentation of affected tissue likely to be associated with damage to long-range white matter pathways (defined by anisotropic power), (3) good performance even in the cases of anatomical distortions by use of nonlinear tensor-based registration in the patient space, which aligns images using white matter contrast. Mapping a system as variable and complex as the human brain requires sample sizes much larger than the current technology can support. This pipeline can be used to execute large-scale, sufficiently powered analyses by meeting the need for an automatic approach to objectively quantify white matter disconnection.\n\nAbbreviations\n\nFundingThis work was supported by the National Institutes of Health [5R01NS066654-05]; KJ was supported by the Department of Defense (DoD) [National Defense Science & Engineering Graduate Fellowship (NDSEG) Program].

bioengineering