BACKGROUND: Ethiopia reported the first case of COVID-19 on 13(th) March, 2020 with community transmission ensuing by mid-May. A national, population-based serosurvey against anti-SARS-CoV-2 IgG was conducted to measure the prevalence of prior COVID-19 infections and better approximate the burden across major towns in Ethiopia. METHODS: We conducted a cross-sectional, population-based serosurvey from June 24 to July 8, 2020 in 14 major urban areas. Two-stage cluster sampling was used to randomly select enumeration areas and households. All persons aged ≥15 years were enrolled. Serum samples were tested by Abbott™ ARCHITECT™ assay for SARS-CoV-2 IgG antibodies. National COVID-19 surveillance data on the median date of the serosurvey is analyzed for comparison. FINDINGS: Adjusted seroprevalence was 3.5% (95% CI: 3.2%-3.8%) after controlling for age, sex and test kit performance. Males (3.7%) and females (3.3%) were nearly equally infected, while middle-aged adults '40-65 years' had the highest (4.0%) prevalence. Gambella (7.5%), Dire Dawa (6.2%) and Jigjiga (6.1%) were the most affected towns. About 6.7% and 8.0% of seropositives had symptoms and chronic underlying illness, respectively. A surveillance system had identified 4,416 RT-PCR confirmed cases in Addis Ababa. INTERPRETATION: This serosurvey shows that a majority of urban Ethiopians remain uninfected with SARS-CoV-2. Most anti-SARS-CoV-2 IgG positive cases were asymptomatic with no underlying illness, keeping case detection to a minimum.

INTRODUCTION: Chad is a country within the Lake Chad sub region, currently at risk for poliovirus infection. The Lake Chad Task Team on polio eradication in this sub region made significant efforts to reduce the risk of polio transmission in Chad by tacking immunization teams in the Island Settlement using a Geographic Information System (GIS) technology. This article demonstrates the application of GIS technology to track vaccination teams to monitor immunization coverage in the Island settlements, reduce the number of missed settlements, to provide evidence for vaccination implementation and accountability and improve team performance. METHODS: In each district where tracking was conducted, global positioning system-enabled Android phones were given to each team on a daily basis and were used to record team tracks. These tracks were uploaded to a dashboard to show the level of coverage and identify areas missed by the teams. RESULTS: In 2018, tracking covered 30 immunization days, in six rounds. Approximately average of 1173 Island settlements were tracked and covered in each of the six rounds. A total of 806,999 persons aged 0-10 years were immunized, out of which 4273 were zero dose cases at the point of their immunization. Tracking activities were conducted. There was an improvement in the geographic coverage of settlements and an overall reduction in the number of missed settlements. CONCLUSIONS: The tracking of vaccination teams and Island settlements ensured useful information for planning and implementation of polio campaigns and enabled supervisors to evaluate performance of vaccination teams.

BACKGROUND: Dengue Fever (DF) is a viral disease primarily transmitted by Aedes (Ae.) aegypti mosquitoes. Outbreaks in Eastern Ethiopia were reported during 2014-2016. In May 2017, we investigated the first suspected DF outbreak from Kabridahar Town, Somali region (Eastern Ethiopia) to describe its magnitude, assess risk factors, and implement control measures. METHODS: Suspected DF cases were defined as acute febrile illness plus ≥2 symptoms (headache, fever, retro-orbital pain, myalgia, arthralgia, rash, or hemorrhage) in Kabridahar District residents. All reported cases were identified through medical record review and active searches. Severe dengue was defined as DF with severe organ impairment, severe hemorrhage, or severe plasma leakage. We conducted a neighborhood-matched case-control study using a subset of suspected cases and conveniently-selected asymptomatic community controls and interviewed participants to collect demographic and risk factor data. We tested sera by RT-PCR to detect dengue virus (DENV) and identify serotypes. Entomologists conducted mosquito surveys at community households to identify species and estimate larval density using the house index (HI), container index (CI) and Breteau index (BI), with BI≥20 indicating high density. RESULTS: We identified 101 total cases from May 12-31, 2017, including five with severe dengue (one death). The attack rate (AR) was 17/10,000. Of 21 tested samples, 15 (72%) were DENV serotype 2 (DENV 2). In the case-control study with 50 cases and 100 controls, a lack of formal education (AOR [Adjusted Odds Ratio] = 4.2, 95% CI [Confidence Interval] 1.6-11.2) and open water containers near the home (AOR = 3.0, 95% CI 1.2-7.5) were risk factors, while long-lasting insecticide treated-net (LLITN) usage (AOR = 0.21, 95% CI 0.05-0.79) was protective. HI and BI were 66/136 (49%) and 147 per 100 homes (147%) respectively, with 151/167 (90%) adult mosquitoes identified as Ae. aegypti. CONCLUSION: The epidemiologic, entomologic, and laboratory investigation confirmed a DF outbreak. Mosquito indices were far above safe thresholds, indicating inadequate vector control. We recommended improved vector surveillance and control programs, including best practices in preserving water and disposal of open containers to reduce Aedes mosquito density.

OBJECTIVE: This study was conducted to identify factors contributing to health satisfaction outcomes among emerging adults (ages 18-25) with diabetes. METHOD: SEARCH for Diabetes in Youth study participants whose diabetes was prevalent in 2001 and were ≥18 years of age when they completed a 2008-2009 follow-up survey (n = 340) were included. We developed a health resilience model (HRM) to identify potentially modifiable factors (anticipatory guidance, social support, physical activity, quality of life) associated with health outcomes (satisfaction with health care, overall personal health, self-report of hemoglobin A1c [HbA1c]). Proportional odds logistic regression models were used to examine relationships between modifiable factors and health outcomes while adjusting for predetermined characteristics; linear regression models were used for reported HbA1c. Comparison of participants who reported HbA1c versus nonreporters was conducted. RESULTS: A majority (70%) of participants rated satisfaction with health care ≥7 out of 10, and most (71%) rated overall health as good, very good, or excellent. Satisfaction with health care was independent of change in provider between the ages of 17 and 24. After controlling for predetermined characteristics, we found that the odds of increased satisfaction with health care and overall personal health were 1.3 and 1.2 greater, respectively, when participants discussed additional diabetes-related anticipatory guidance topics with a provider and 1.3 and 2.1, respectively, for each 10-unit change in quality of life score. Relationship between HbA1c level and modifiable factors was not significant; however, participants reporting HbA1c had higher ratings of health care and overall health versus nonreporters. CONCLUSIONS: HRM describes relationships between modifiable factors and patient-reported outcomes of satisfaction with health care and overall personal health among a cohort of ethnically and racially diverse emerging adults with longstanding diabetes, over half of whom experienced a change in provider. HRM may discern candidate areas for intervention, such as effective anticipatory guidance that can impact satisfaction with health care and overall health, to promote positive health outcomes.

OBJECTIVE: To describe the prevalence of access and process barriers to health care and to examine their relationship to sociodemographic and disease factors in a large and diverse cohort of US youth with type 1 diabetes. STUDY DESIGN: A cross-sectional analysis of 780 youth who participated in the SEARCH for Diabetes in Youth Study and were diagnosed with type 1 diabetes in 2002-2005. Experience of barriers to care was collected from parent report on questionnaires. Analyses included multivariate regression models to predict the presence of specific barriers to care. RESULTS: Overall, 81.7% of participants reported at least one barrier; the 3 most common were costs (47.5%), communication (43.0%), and getting needed information (48.4%). Problems with access to care, not having a regular provider, and receiving contextual care (care that takes into account personal and family context) were associated with poorer glycated hemoglobin levels. Adjusted multivariate models indicated that barriers related to access (regular provider, cost) were most likely for youth with low family income and those without public health insurance. Barriers associated with the processes of quality care (contextual care, communication) were more likely for Hispanic youth and those whose parents had less education. CONCLUSIONS: This study indicates that a large proportion of youth with type 1 diabetes experience substantial barriers to care. Barriers to access and those associated with processes of quality care differed by sociodemographic characteristics. Future investigators should expand knowledge of the systemic processes that lead to disparate outcomes for some youth with diabetes and assess potential solutions.

OBJECTIVE: Youth with type 1 diabetes mellitus are at risk for poor glycemic control as they age into adulthood. The aim of this study was to describe sociodemographic and clinical correlates of poor glycemic control associated with the transfer of care from pediatric to adult diabetes providers among a cohort of youth with type 1 diabetes diagnosed in adolescence. METHODS: Analyses included 185 adolescent participants with recently diagnosed type 1 diabetes in the SEARCH for Diabetes in Youth Study with pediatric care at baseline who were age ≥18 years at follow-up. Demographic and clinical factors were measured by survey and laboratory results. Survival analysis was used to estimate the age of transition. Logistic regression analysis assessed the association of demographic and clinical factors with the transition of care and poor glycemic control at follow-up. RESULTS: Fifty-seven percent of participants had transitioned to adult diabetes care providers by the follow-up visit. The estimated median age of transition of care was 20.1 years (95% confidence interval 19.8-20.4). Older age, lower baseline glycosylated hemoglobin, and less parental education were independently associated with increased odds of transition. The odds of poor glycemic control at follow-up were 2.5 times higher for participants who transitioned to adult care compared with those who remained in pediatric care. CONCLUSIONS: Transferring from pediatric to adult care, experienced by more than half the sample, was associated with an increased risk of poor glycemic control at follow-up. These findings suggest that young adults need additional support when moving to adult care.

Migration status and the accompanying diversity in culture, foods and family norms, may be an important consideration for practitioners providing individualized care to treat and prevent complications among youth with diabetes. Approximately 20 % of youth in the US have ≥1 foreign-born parent. However, the proportion and characteristics of youth with diabetes and ≥1 foreign-born parent have yet to be described. Study participants (n = 3,086) were from SEARCH for Diabetes in Youth, a prospective multi-center study in the US. Primary outcomes of interest included HbA1c, body mass index and barriers to care. Multivariable analyses were carried out using logistic regression and analysis of covariance. Approximately 17 % of participants with type 1 diabetes (T1D) and 22 % with type 2 diabetes (T2D) had ≥1 foreign-born parent. Youth with T1D and ≥1 foreign-born parent were less likely to have poor glycemic control [adjusted odds ratio (OR) (95 % confidence interval): 0.70 (0.53, 0.94)]. Among youth with T2D, those with ≥1 foreign-born parent had lower odds of obesity [adjusted OR (95 % CI): 0.35 (0.17, 0.70)]. This is the first study to estimate the proportion and characteristics of youth with diabetes exposed to migration in the US. Research into potential mechanisms underlying the observed protective effects is warranted.

OBJECTIVES: To evaluate the reliability and cluster structure of the Pediatric Quality of Life Inventory Type 1 Diabetes Module 3.0 (PedsQL-T1DM) and associated subscales and to explore the associations between PedsQL-T1DM total score and demographic and clinical characteristics and clinical indicators among a large racially/ethnically diverse cohort of youth with type 1 diabetes. STUDY DESIGN: Principal components analysis was conducted on responses from the PedsQL-T1DM child self-report forms completed by SEARCH for Diabetes in Youth study participants aged ≥5 years. Multivariate linear regression models were fit to examine the associations among PedsQL-T1DM total score, demographic and clinical characteristics, and clinical indicators. RESULTS: The sample comprised 2602 youth with a mean age of 13.6 +/- 4.1 years and a mean T1DM duration of 62.1 +/- 47.0 months. Principal components analysis did not support the 5 existing PedsQL-T1DM subscales. In multivariate analyses, the PedsQL-T1DM total score was negatively and significantly associated with younger age (5-7 years), female sex, receiving insulin by injection (vs pump), having parents without a college degree, Medicaid/Medicare insurance, and having a comorbid medical condition. Youth with poor glycemic control based on their age-specific hemoglobin A1c target values and those with depressive symptoms had significantly lower PedsQL-T1DM scores than their counterparts with good control and no or limited depressive symptoms. CONCLUSION: This study has identified sociodemographic and clinical characteristics of youth with T1DM more likely to experience poor diabetes-specific quality of life. The association of lower PedsQL-T1DM scores with depressive symptoms and poor glycemic control is especially concerning and may be the focus of future interventions and studies.

AIMS: To identify demographic, family and clinical characteristics associated with provider recommended frequency of blood glucose monitoring (BGM), actual frequency of BGM, and concordance between these categories in youth with type 1 diabetes (T1D) as reported by child's caregiver. METHODS: Caregivers of 390 children 10-17 years were interviewed about their children's providers' recommendations for frequency of BGM and their child's frequency of performance of BGM. RESULTS: The majority (92%) of caregivers reported being told that their child should BGM ≥4 times per day and 78% reported their child checked that frequently. Caregivers of children who were younger, non-Hispanic White, from two-parent households, higher income households, and on insulin pumps were more likely to report being told by their provider to perform BGM ≥6 times per day and more likely to report that their child performed BGM ≥6 times per day. Younger children and those with private health insurance were more likely to adhere to reported recommendations. Children whose caregivers reported that their child met/exceeded their provider recommendations had lower A1c values than those who did not. CONCLUSIONS: These findings may help clinicians identify subgroups of youth at-risk for poor diabetes management and provide further education in order to improve outcomes.

OBJECTIVE: To estimate the prevalence of asthma among youth with types 1 and 2 diabetes and examine associations between asthma and glycemic control. METHODS: This was a cross-sectional analysis of data from the SEARCH for Diabetes in Youth study, which included youth diagnosed with type 1 (n = 1683) and type 2 (n = 311) diabetes from 2002 through 2005. Asthma status and medications were ascertained from medical records and self-administered questionnaires, and glycemic control was assessed from hemoglobin A1c measured at the study visit. RESULTS: Prevalence of asthma among all youth with diabetes was 10.9% (95% confidence interval [CI]: 9.6%-12.3%). The prevalence was 10.0% (95% CI: 8.6%-11.4%) among youth with type 1 and 16.1% (95% CI: 12.0%-20.2%) among youth with type 2 diabetes and differed according to race/ethnicity. Among youth with type 1 diabetes, those with asthma had higher mean A1c levels than those without asthma, after adjustment for age, gender, race/ethnicity, and BMI (7.77% vs 7.49%; P = .034). Youth with asthma were more likely to have poor glycemic control, particularly those with type 1 diabetes whose asthma was not treated with pharmacotherapy, although this association was attenuated by adjustment for race/ethnicity. CONCLUSIONS: Prevalence of asthma may be elevated among youth with diabetes relative to the general US population. Among youth with type 1 diabetes, asthma is associated with poor glycemic control, especially if asthma is untreated. Specific asthma medications may decrease systemic inflammation, which underlies the complex relationship between pulmonary function, BMI, and glycemic control among youth with diabetes.

OBJECTIVE: To describe demographic and clinical characteristics associated with self-reported receipt of tests and measurements recommended by the American Diabetes Association (ADA) for children and youths with diabetes. METHODS: The study included 1514 SEARCH for Diabetes in Youth study participants who completed a survey about diabetes care received. Quality-of-care measures were based on ADA guidelines for eye examinations and glycohemoglobin (hemoglobin A1c [HbA1c]), lipid level, microalbuminuria, and blood pressure measurements, and a composite variable of these 5 indicators was created. Multivariate logistic regression models were used to assess the association of selected demographic and clinical characteristics with the reported receipt of all recommended tests and measurements according to age and diabetes type subgroups. RESULTS: Overall, 95% of the participants reported having their blood pressure checked at all or most visits, 88% had lipid levels measured, 83% had kidney function tested, 68% underwent HbA1c testing, and 66% underwent an eye examination, in accordance with ADA recommendations. Participants aged 18 years or older, particularly those with type 2 diabetes, tended to have fewer tests of all kinds performed. Age and family income emerged as important correlates of overall quality of care in multivariate models; older age and lower income were associated with not meeting guidelines. CONCLUSIONS: Although there was relatively good adherence to ADA-recommended guidelines for most indicators, efforts are needed to improve rates of HbA1c testing and eye examinations, particularly among older youths.