Association of collaborative care intervention features with depression and metabolic outcomes in the INDEPENDENT study: A mixed methods study.

AIMS: The INtegrating DEPrEssioN and Diabetes treatmENT (INDEPENDENT) trial tested a collaborative care model including electronic clinical decision support (CDS) for treating diabetes and depression in India. We aimed to assess which features of this clinically and cost-effective intervention were associated with improvements in diabetes and depression measures. METHODS: Post-hoc analysis of the INDEPENDENT trial data (189 intervention participants) was conducted to determine each intervention feature's effect: 1. Collaborative case reviews between expert psychiatrists and the care team; 2. Patient care-coordinator contacts; and 3. Clinicians' CDS prompt modifications. Primary outcome was baseline-to-12-months improvements in diabetes control, blood pressure, cholesterol, and depression. Implementer interviews revealed barriers and facilitators of intervention success. Joint displays integrated mixed methods' results. RESULTS: High baseline HbA1c≥ 74.9 mmol/mol (9%) was associated with 5.72 fewer care-coordinator contacts than those with better baseline HbA1c (76.8 mmol/mol, 9.18%, p < 0.001). Prompt modification proportions varied from 38.3% (diabetes) to 1.3% (LDL). Interviews found that providers' and participants' visit frequencies were preference dependent. Qualitative data elucidated patient-level factors that influenced number of clinical contacts and prompt modifications explaining their lack of association with clinical outcomes. CONCLUSION: Our mixed methods approach underlines the importance of the complementarity of different intervention features. Qualitative findings further illuminate reasons for variations in fidelity from the core model.

Projected health and economic impacts of sugar-sweetened beverage taxation in Germany: A cross-validation modelling study.

BACKGROUND: Taxes on sugar-sweetened beverages (SSBs) have been implemented globally to reduce the burden of cardiometabolic diseases by disincentivizing consumption through increased prices (e.g., 1 peso/litre tax in Mexico) or incentivizing industry reformulation to reduce SSB sugar content (e.g., tiered structure of the United Kingdom [UK] Soft Drinks Industry Levy [SDIL]). In Germany, where no tax on SSBs is enacted, the health and economic impact of SSB taxation using the experience from internationally implemented tax designs has not been evaluated. The objective of this study was to estimate the health and economic impact of national SSBs taxation scenarios in Germany. METHODS AND FINDINGS: In this modelling study, we evaluated a 20% ad valorem SSB tax with/without taxation of fruit juice (based on implemented SSB taxes and recommendations) and a tiered tax (based on the UK SDIL) in the German adult population aged 30 to 90 years from 2023 to 2043. We developed a microsimulation model (IMPACTNCD Germany) that captures the demographics, risk factor profile and epidemiology of type 2 diabetes, coronary heart disease (CHD) and stroke in the German population using the best available evidence and national data. For each scenario, we estimated changes in sugar consumption and associated weight change. Resulting cases of cardiometabolic disease prevented/postponed and related quality-adjusted life years (QALYs) and economic impacts from healthcare (medical costs) and societal (medical, patient time, and productivity costs) perspectives were estimated using national cost and health utility data. Additionally, we assessed structural uncertainty regarding direct, body mass index (BMI)-independent cardiometabolic effects of SSBs and cross-validated results with an independently developed cohort model (PRIMEtime). We found that SSB taxation could reduce sugar intake in the German adult population by 1 g/day (95%-uncertainty interval [0.05, 1.65]) for a 20% ad valorem tax on SSBs leading to reduced consumption through increased prices (pass-through of 82%) and 2.34 g/day (95%-UI [2.32, 2.36]) for a tiered tax on SSBs leading to 30% reduction in SSB sugar content via reformulation. Through reductions in obesity, type 2 diabetes, and cardiovascular disease (CVD), 106,000 (95%-UI [57,200, 153,200]) QALYs could be gained with a 20% ad valorem tax and 192,300 (95%-UI [130,100, 254,200]) QALYs with a tiered tax. Respectively, €9.6 billion (95%-UI [4.7, 15.3]) and €16.0 billion (95%-UI [8.1, 25.5]) costs could be saved from a societal perspective over 20 years. Impacts of the 20% ad valorem tax were larger when additionally taxing fruit juice (252,400 QALYs gained, 95%-UI [176,700, 325,800]; €11.8 billion costs saved, 95%-UI [€6.7, €17.9]), but impacts of all scenarios were reduced when excluding direct health effects of SSBs. Cross-validation with PRIMEtime showed similar results. Limitations include remaining uncertainties in the economic and epidemiological evidence and a lack of product-level data. CONCLUSIONS: In this study, we found that SSB taxation in Germany could help to reduce the national burden of noncommunicable diseases and save a substantial amount of societal costs. A tiered tax designed to incentivize reformulation of SSBs towards less sugar might have a larger population-level health and economic impact than an ad valorem tax that incentivizes consumer behaviour change only through increased prices.

Forecasting the mortality burden of coronary heart disease and stroke in Germany: National trends and regional inequalities.

BACKGROUND: The decline of cardiovascular disease (CVD) mortality has slowed in many countries, including Germany. We examined the implications of this trend for future coronary heart disease (CHD) and stroke mortality in Germany considering persistent mortality inequalities between former East and West Germany. METHODS: We retrieved demographic and mortality data from 1991 to 2019 from the German Federal Statistical Office. Using a Bayesian age-period-cohort framework, we projected CHD and stroke mortality from 2019 to 2035, stratified by sex and German region. We decomposed annual changes in deaths into three components (mortality rates, population age structure and population size) and assessed regional inequalities with age-sex-standardized mortality ratios. RESULTS: We confirmed that declines of CVD mortality rates in Germany will likely stagnate. From 2019 to 2035, we projected fewer annual CHD deaths (114,600 to 103,500 [95%-credible interval: 81,700; 134,000]) and an increase in stroke deaths (51,300 to 53,700 [41,400; 72,000]). Decomposing past and projected mortality, we showed that population ageing was and is offset by declining mortality rates. This likely reverses after 2030 leading to increased CVD deaths thereafter. Inequalities between East and West declined substantially since 1991 and are projected to stabilize for CHD but narrow for stroke. CONCLUSIONS: CVD deaths in Germany likely keep declining until 2030, but may increase thereafter due to population ageing if the reduction in mortality rates slows further. East-West mortality inequalities for CHD remain stable but may converge for stroke. Underlying risk factor trends need to be monitored and addressed by public health policy.

Health and economic impact of improved glucose, blood pressure and lipid control among German adults with type 2 diabetes: a modelling study.

AIMS/HYPOTHESIS: The aim of this study was to estimate the long-term health and economic consequences of improved risk factor control in German adults with type 2 diabetes. METHODS: We used the UK Prospective Diabetes Study Outcomes Model 2 to project the patient-level health outcomes and healthcare costs of people with type 2 diabetes in Germany over 5, 10 and 30 years. We parameterised the model using the best available data on population characteristics, healthcare costs and health-related quality of life from German studies. The modelled scenarios were: (1) a permanent reduction of HbA1c by 5.5 mmol/mol (0.5%), of systolic BP (SBP) by 10 mmHg, or of LDL-cholesterol by 0.26 mmol/l in all patients, and (2) achievement of guideline care recommendations for HbA1c (≤53 mmol/mol [7%]), SBP (≤140 mmHg) or LDL-cholesterol (≤2.6 mmol/l) in patients who do not meet the recommendations. We calculated nationwide estimates using age- and sex-specific quality-adjusted life year (QALY) and cost estimates, type 2 diabetes prevalence and population size. RESULTS: Over 10 years, a permanent reduction of HbA1c by 5.5 mmol/mol (0.5%), SBP by 10 mmHg or LDL-cholesterol by 0.26 mmol/l led to per-person savings in healthcare expenditures of €121, €238 and €34, and 0.01, 0.02 and 0.015 QALYs gained, respectively. Achieving guideline care recommendations for HbA1c, SBP or LDL-cholesterol could reduce healthcare expenditure by €451, €507 and €327 and gained 0.03, 0.05 and 0.06 additional QALYs in individuals who did not meet the recommendations. Nationally, achieving guideline care recommendations for HbA1c, SBP and LDL-cholesterol could reduce healthcare costs by over €1.9 billion. CONCLUSIONS/INTERPRETATION: Sustained improvements in HbA1c, SBP and LDL-cholesterol control among diabetes patients in Germany can lead to substantial health benefits and reduce healthcare expenditures.

Interim Evaluation of Germany's Sugar Reduction Strategy for Soft Drinks: Commitments versus Actual Trends in Sugar Content and Sugar Sales from Soft Drinks.

INTRODUCTION: A high intake of sugar, in particular from sugar-sweetened soft drinks, increases the risk for obesity, type 2 diabetes mellitus, and dental caries. Germany has pursued a national strategy for sugar reduction in soft drinks based on voluntary commitments by industry since 2015, but its effects are unclear. METHODS: We use aggregated annual sales data from Euromonitor International to assess trends in mean sales-weighted sugar content of soft drinks and per capita sugar sales from soft drinks in Germany from 2015 to 2021. We compare these trends to the reduction path set by Germany's national sugar reduction strategy and to data for the United Kingdom, which adopted a soft drinks tax in 2017 and which we selected as best practice comparison country based on pre-defined criteria. RESULTS: Between 2015 and 2021, the mean sales-weighted sugar content of soft drinks sold in Germany decreased by 2% from 5.3 to 5.2 g/100 mL, falling short of an interim 9% reduction target and a 29% reduction observed in the United Kingdom over the same period. Sugar sales from soft drinks in Germany decreased from 22.4 to 21.6 g/capita/day (-4%) between 2015 and 2021 but remain high from a public health perspective. CONCLUSIONS: Reductions observed under Germany's sugar reduction strategy fall short of stated targets and trends observed internationally under best practice conditions. Additional policy measures may be needed to support sugar reduction in soft drinks in Germany.

Long-term Effects of a Collaborative Care Model on Metabolic Outcomes and Depressive Symptoms: 36-Month Outcomes from the INDEPENDENT Intervention.

BACKGROUND: Collaborative care (CC) is a multicomponent team-based approach to providing mental health care with systematic integration into outpatient medical settings. The 12-month INDEPENDENT CC intervention improved joint disease control measures in patients with both depression and diabetes at 12 and 24 months following randomization. OBJECTIVE: This study investigated the durability of intervention effects on patient outcomes at 36 months following randomization. PARTICIPANTS: Adult patients with poorly controlled T2D and depression in India randomized to CC or usual care. DESIGN: Post hoc analyses of between-group differences in patient outcomes at 36 months post-randomization (N = 331) and maintenance of outcomes from 12 to 36 months (N = 314). MAIN MEASURES: We evaluated combined risk factor improvement since baseline, defined as ≥ 50.0% reduction in Symptom Checklist Depression Scale (SCL-20) scores along with reduction of at least 0.5 percentage point hemoglobin A1C, 5 mmHg systolic blood pressure, or 10 mg/dL low-density lipoprotein cholesterol. Improvements in single risk factors were also examined. KEY RESULTS: There were no between-group differences in improvements since baseline in multiple or single risk factors at 36 months. Patients in the CC group with improved outcomes at 12 months were more likely to maintain a ≥ 50.0% reduction since baseline in SCL-20 scores (CC [54.9%] vs. UC [40.9%]; RR: 1.27 [95% CI: 1.04, 1.56]) and 0.5 percentage point reduction since baseline in hemoglobin A1C (CC [31.9%] vs. UC [19.5%]; RR: 1.64 [95% CI: 1.11, 2.41]) at 36 months. CONCLUSIONS: While improvements since baseline in patient outcomes did not differ between the collaborative care and usual care groups at 36 months, patients who received CC were more likely to maintain improvements in depressive symptoms and glucose levels at 36 months if they had achieved these improvements at the end of active intervention. TRIAL REGISTRATION NUMBER: NCT02022111.

Cost-Effectiveness of a Collaborative Care Model Among Patients With Type 2 Diabetes and Depression in India.

OBJECTIVE: To assess the cost-effectiveness of collaborative versus usual care in adults with poorly controlled type 2 diabetes and depression in India. RESEARCH DESIGN AND METHODS: We performed a within-trial cost-effectiveness analysis of a 24-month parallel, open-label, pragmatic randomized clinical trial at four urban clinics in India from multipayer and societal perspectives. The trial randomly assigned 404 patients with poorly controlled type 2 diabetes (HbA1c ≥8.0%, systolic blood pressure ≥140 mmHg, or LDL cholesterol ≥130 mg/dL) and depressive symptoms (9-item Patient Health Questionnaire score ≥10) to collaborative care (support from nonphysician care coordinators, electronic registers, and specialist-supported case review) for 12 months, followed by 12 months of usual care or 24 months of usual care. We calculated incremental cost-effectiveness ratios (ICERs) in Indian rupees (INR) and international dollars (Int'l-$) and the probability of cost-effectiveness using quality-adjusted life-years (QALYs) and depression-free days (DFDs). RESULTS: From a multipayer perspective, collaborative care costed an additional INR309,558 (Int'l-$15,344) per QALY and an additional INR290.2 (Int'l-$14.4) per DFD gained compared with usual care. The probability of cost-effectiveness was 56.4% using a willingness to pay of INR336,000 (Int'l-$16,654) per QALY (approximately three times per-capita gross domestic product). The willingness to pay per DFD to achieve a probability of cost-effectiveness >95% was INR401.6 (Int'l-$19.9). From a societal perspective, cost-effectiveness was marginally lower. In sensitivity analyses, integrating collaborative care in clinical workflows reduced incremental costs by ∼47% (ICER 162,689 per QALY, cost-effectiveness probability 89.4%), but cost-effectiveness decreased when adjusting for baseline values. CONCLUSIONS: Collaborative care for patients with type 2 diabetes and depression in urban India can be cost-effective, especially when integrated in clinical workflows. Long-term cost-effectiveness might be more favorable. Scalability across lower- and middle-income country settings depends on heterogeneous contextual factors.

Estimating the impact of nutrition and physical activity policies with quasi-experimental methods and simulation modelling: an integrative review of methods, challenges and synergies.

BACKGROUND: The promotion of healthy lifestyles has high priority on the global public health agenda. Evidence on the real-world (cost-)effectiveness of policies addressing nutrition and physical activity is needed. To estimate short-term policy impacts, quasi-experimental methods using observational data are useful, while simulation models can estimate long-term impacts. We review the methods, challenges and potential synergies of both approaches for the evaluation of nutrition and physical activity policies. METHODS: We performed an integrative review applying purposive literature sampling techniques to synthesize original articles, systematic reviews and lessons learned from public international workshops conducted within the European Union Policy Evaluation Network. RESULTS: We highlight data requirements for policy evaluations, discuss the distinct assumptions of instrumental variable, difference-in-difference, and regression discontinuity designs and describe the necessary robustness and falsification analyses to test them. Further, we summarize the specific assumptions of comparative risk assessment and Markov state-transition simulation models, including their extension to microsimulation. We describe the advantages and limitations of these modelling approaches and discuss future directions, such as the adequate consideration of heterogeneous policy responses. Finally, we highlight how quasi-experimental and simulation modelling methods can be integrated into an evidence cycle for policy evaluation. CONCLUSIONS: Assumptions of quasi-experimental and simulation modelling methods in policy evaluations should be credible, rigorously tested and transparently communicated. Both approaches can be applied synergistically within a coherent framework to compare policy implementation scenarios and improve the estimation of nutrition and physical activity policy impacts, including their distribution across population sub-groups.

Costs and cost-effectiveness of HIV early infant diagnosis in low- and middle-income countries: a scoping review.

BACKGROUND: Continuing progress in the global pediatric human immunodeficiency virus (HIV) response depends on timely identification and care of infants with HIV. As countries scale-out improvements to HIV early infant diagnosis (EID), economic evaluations are needed to inform program design and implementation. This scoping review aimed to summarize the available evidence and discuss practical implications of cost and cost-effectiveness analyses of HIV EID. METHODS: We systematically searched bibliographic databases (Embase, MEDLINE and EconLit) and grey literature for economic analyses of HIV EID in low- and middle-income countries published between January 2008 and June 2021. We extracted data on unit costs, cost savings, and incremental cost-effectiveness ratios as well as outcomes related to health and the HIV EID care process and summarized results in narrative and tabular formats. We converted unit costs to 2021 USD for easier comparison of costs across studies. RESULTS: After title and abstract screening of 1278 records and full-text review of 99 records, we included 29 studies: 17 cost analyses and 12 model-based cost-effectiveness analyses. Unit costs were 21.46-51.80 USD for point-of-care EID tests and 16.21-42.73 USD for laboratory-based EID tests. All cost-effectiveness analyses stated at least one of the interventions evaluated to be cost-effective. Most studies reported costs of EID testing strategies; however, few studies assessed the same intervention or reported costs in the same way, making comparison of costs across studies challenging. Limited data availability of context-appropriate costs and outcomes of children with HIV as well as structural heterogeneity of cost-effectiveness modelling studies limits generalizability of economic analyses of HIV EID. CONCLUSIONS: The available cost and cost-effectiveness evidence for EID of HIV, while not directly comparable across studies, covers a broad range of interventions and suggests most interventions designed to improve EID are cost-effective or cost-saving. Further studies capturing costs and benefits of EID services as they are delivered in real-world settings are needed.

The effect of differential privacy on Medicaid participation among racial and ethnic minority groups.

OBJECTIVE: To investigate how county and state-level estimates of Medicaid enrollment among the total, non-Hispanic White, non-Hispanic Black or African American, and Hispanic or Latino/a population are affected by Differential Privacy (DP), where statistical noise is added to the public decennial US census data to protect individual privacy. DATA SOURCES: We obtained population counts from the final version of the US Census Bureau Differential Privacy Demonstration Products from 2010 and combined them with Medicaid enrollment data. STUDY DESIGN: We compared 2010 county and state-level population counts released under the traditional disclosure avoidance techniques and the ones produced with the proposed DP procedures. DATA COLLECTION/EXTRACTION METHODS: Not applicable. PRINCIPAL FINDINGS: We find the DP method introduces errors up to 10% into counts and proportions of Medicaid participation rate accuracy at the county level, especially for small subpopulations and racial and ethnic minority groups. The effect of DP on Medicaid participation rate accuracy is only small and negligible at the state level. CONCLUSIONS: The implementation of DP in the 2020 census can affect the analyses of health disparities and health care access and use among different subpopulations in the United States. The planned implementation of DP in other census-related surveys such as the American Community Survey can misrepresent Medicaid participation rates for small racial and ethnic minority groups. This can affect Medicaid funding decisions.

Effect of a collaborative care model on anxiety symptoms among patients with depression and diabetes in India: The INDEPENDENT randomized clinical trial.

OBJECTIVE: We assessed the impact of a collaborative care intervention on anxiety symptoms among participants in India with comorbid depression, poorly controlled diabetes, and moderate to severe anxiety symptoms. METHOD: We analyzed data from a randomized controlled trial conducted at four diabetes clinics in India. Participants received either collaborative care or usual care. We included only participants who scored ⩾10 on the Generalized Anxiety Disorder-7 (GAD-7) at baseline. We estimated the effect of the intervention on clinically significant reduction in anxiety symptoms; we considered several potential baseline moderators and mediation by anti-depressant use. RESULTS: One hundred and seventy-two participants scored 10 or above on the GAD-7 at baseline. Collaborative care participants were more likely than control participants to achieve a clinically significant reduction in anxiety symptoms at 6 and 12 months (65.7% vs. 41.4% at 12 months, p = 0.002); these differences were not sustained at 18 or 24 months. There was little evidence of moderation by participant characteristics at baseline, and effects were not mediated by anti-depressant use. CONCLUSIONS: Collaborative care for the treatment of depression and type 2 diabetes can lead to clinically significant reductions in anxiety symptoms among patients with anxiety. Effects were notable during the active intervention period but not over the year post-intervention.

Simulation Modeling for the Economic Evaluation of Population-Based Dietary Policies: A Systematic Scoping Review.

Simulation modeling can be useful to estimate the long-term health and economic impacts of population-based dietary policies. We conducted a systematic scoping review following the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) guideline to map and critically appraise economic evaluations of population-based dietary policies using simulation models. We searched Medline, Embase, and EconLit for studies published in English after 2005. Modeling studies were mapped based on model type, dietary policy, and nutritional target, and modeled risk factor-outcome pathways were analyzed. We included 56 studies comprising 136 model applications evaluating dietary policies in 21 countries. The policies most often assessed were reformulation (34/136), taxation (27/136), and labeling (20/136); the most common targets were salt/sodium (60/136), sugar-sweetened beverages (31/136), and fruit and vegetables (15/136). Model types included Markov-type (35/56), microsimulation (11/56), and comparative risk assessment (7/56) models. Overall, the key diet-related risk factors and health outcomes were modeled, but only 1 study included overall diet quality as a risk factor. Information about validation was only reported in 19 of 56 studies and few studies (14/56) analyzed the equity impacts of policies. Commonly included cost components were health sector (52/56) and public sector implementation costs (35/56), as opposed to private sector (18/56), lost productivity (11/56), and informal care costs (3/56). Most dietary policies (103/136) were evaluated as cost-saving independent of the applied costing perspective. An analysis of the main limitations reported by authors revealed that model validity, uncertainty of dietary effect estimates, and long-term intervention assumptions necessitate a careful interpretation of results. In conclusion, simulation modeling is widely applied in the economic evaluation of population-based dietary policies but rarely takes dietary complexity and the equity dimensions of policies into account. To increase relevance for policymakers and support diet-related disease prevention, economic effects beyond the health sector should be considered, and transparent conduct and reporting of model validation should be improved.

International travel-related control measures to contain the COVID-19 pandemic: a rapid review.

BACKGROUND: In late 2019, the first cases of coronavirus disease 2019 (COVID-19) were reported in Wuhan, China, followed by a worldwide spread. Numerous countries have implemented control measures related to international travel, including border closures, travel restrictions, screening at borders, and quarantine of travellers. OBJECTIVES: To assess the effectiveness of international travel-related control measures during the COVID-19 pandemic on infectious disease transmission and screening-related outcomes. SEARCH METHODS: We searched MEDLINE, Embase and COVID-19-specific databases, including the Cochrane COVID-19 Study Register and the WHO Global Database on COVID-19 Research to 13 November 2020. SELECTION CRITERIA: We considered experimental, quasi-experimental, observational and modelling studies assessing the effects of travel-related control measures affecting human travel across international borders during the COVID-19 pandemic. In the original review, we also considered evidence on severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). In this version we decided to focus on COVID-19 evidence only. Primary outcome categories were (i) cases avoided, (ii) cases detected, and (iii) a shift in epidemic development. Secondary outcomes were other infectious disease transmission outcomes, healthcare utilisation, resource requirements and adverse effects if identified in studies assessing at least one primary outcome. DATA COLLECTION AND ANALYSIS: Two review authors independently screened titles and abstracts and subsequently full texts. For studies included in the analysis, one review author extracted data and appraised the study. At least one additional review author checked for correctness of data. To assess the risk of bias and quality of included studies, we used the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for observational studies concerned with screening, and a bespoke tool for modelling studies. We synthesised findings narratively. One review author assessed the certainty of evidence with GRADE, and several review authors discussed these GRADE judgements. MAIN RESULTS: Overall, we included 62 unique studies in the analysis; 49 were modelling studies and 13 were observational studies. Studies covered a variety of settings and levels of community transmission. Most studies compared travel-related control measures against a counterfactual scenario in which the measure was not implemented. However, some modelling studies described additional comparator scenarios, such as different levels of stringency of the measures (including relaxation of restrictions), or a combination of measures. Concerns with the quality of modelling studies related to potentially inappropriate assumptions about the structure and input parameters, and an inadequate assessment of model uncertainty. Concerns with risk of bias in observational studies related to the selection of travellers and the reference test, and unclear reporting of certain methodological aspects. Below we outline the results for each intervention category by illustrating the findings from selected outcomes. Travel restrictions reducing or stopping cross-border travel (31 modelling studies) The studies assessed cases avoided and shift in epidemic development. We found very low-certainty evidence for a reduction in COVID-19 cases in the community (13 studies) and cases exported or imported (9 studies). Most studies reported positive effects, with effect sizes varying widely; only a few studies showed no effect. There was very low-certainty evidence that cross-border travel controls can slow the spread of COVID-19. Most studies predicted positive effects, however, results from individual studies varied from a delay of less than one day to a delay of 85 days; very few studies predicted no effect of the measure. Screening at borders (13 modelling studies; 13 observational studies) Screening measures covered symptom/exposure-based screening or test-based screening (commonly specifying polymerase chain reaction (PCR) testing), or both, before departure or upon or within a few days of arrival. Studies assessed cases avoided, shift in epidemic development and cases detected. Studies generally predicted or observed some benefit from screening at borders, however these varied widely. For symptom/exposure-based screening, one modelling study reported that global implementation of screening measures would reduce the number of cases exported per day from another country by 82% (95% confidence interval (CI) 72% to 95%) (moderate-certainty evidence). Four modelling studies predicted delays in epidemic development, although there was wide variation in the results between the studies (very low-certainty evidence). Four modelling studies predicted that the proportion of cases detected would range from 1% to 53% (very low-certainty evidence). Nine observational studies observed the detected proportion to range from 0% to 100% (very low-certainty evidence), although all but one study observed this proportion to be less than 54%. For test-based screening, one modelling study provided very low-certainty evidence for the number of cases avoided. It reported that testing travellers reduced imported or exported cases as well as secondary cases. Five observational studies observed that the proportion of cases detected varied from 58% to 90% (very low-certainty evidence). Quarantine (12 modelling studies) The studies assessed cases avoided, shift in epidemic development and cases detected. All studies suggested some benefit of quarantine, however the magnitude of the effect ranged from small to large across the different outcomes (very low- to low-certainty evidence). Three modelling studies predicted that the reduction in the number of cases in the community ranged from 450 to over 64,000 fewer cases (very low-certainty evidence). The variation in effect was possibly related to the duration of quarantine and compliance. Quarantine and screening at borders (7 modelling studies; 4 observational studies) The studies assessed shift in epidemic development and cases detected. Most studies predicted positive effects for the combined measures with varying magnitudes (very low- to low-certainty evidence). Four observational studies observed that the proportion of cases detected for quarantine and screening at borders ranged from 68% to 92% (low-certainty evidence). The variation may depend on how the measures were combined, including the length of the quarantine period and days when the test was conducted in quarantine. AUTHORS' CONCLUSIONS: With much of the evidence derived from modelling studies, notably for travel restrictions reducing or stopping cross-border travel and quarantine of travellers, there is a lack of 'real-world' evidence. The certainty of the evidence for most travel-related control measures and outcomes is very low and the true effects are likely to be substantially different from those reported here. Broadly, travel restrictions may limit the spread of disease across national borders. Symptom/exposure-based screening measures at borders on their own are likely not effective; PCR testing at borders as a screening measure likely detects more cases than symptom/exposure-based screening at borders, although if performed only upon arrival this will likely also miss a meaningful proportion of cases. Quarantine, based on a sufficiently long quarantine period and high compliance is likely to largely avoid further transmission from travellers. Combining quarantine with PCR testing at borders will likely improve effectiveness. Many studies suggest that effects depend on factors, such as levels of community transmission, travel volumes and duration, other public health measures in place, and the exact specification and timing of the measure. Future research should be better reported, employ a range of designs beyond modelling and assess potential benefits and harms of the travel-related control measures from a societal perspective.

Toward targeted prevention: risk factors for prediabetes defined by impaired fasting glucose, impaired glucose tolerance and increased HbA1c in the population-based KORA study from Germany.

AIMS: To identify socioeconomic, behavioral and clinical factors that are associated with prediabetes according to different prediabetes definition criteria. METHODS: Analyses use pooled data of the population-based Cooperative Health Research in the Region of Augsburg (KORA) studies (n = 5312 observations aged ≥ 38 years without diabetes). Prediabetes was defined through either impaired fasting glucose (IFG), impaired glucose tolerance (IGT) or elevated HbA1c according to thresholds of the American Diabetes Association. Explanatory variables were regressed on prediabetes using generalized estimating equations. RESULTS: Mean age was 58.4 years; 50% had prediabetes (33% had IFG, 16% IGT, and 26% elevated HbA1c, 10% fulfilled all three criteria). Age, obesity, hypertension, low education, unemployment, statutory health insurance, urban residence and physical inactivity were associated with prediabetes. Male sex was a stronger risk factor for IFG (OR = 2.5; 95%-CI: 2.2-2.9) than for IGT or elevated HbA1c, and being unemployed was a stronger risk factor for IGT (OR = 3.2 95%-CI: 2.6-4.0) than for IFG or elevated HbA1c. CONCLUSIONS: The overlap of people with IFG, IGT and elevated HbA1c is small, and some factors are associated with only one criterion. Knowledge on sociodemographic and socioeconomic risk factors can be used to effectively target interventions to people at high risk for type 2 diabetes.

Effect of a Collaborative Care Model on Depressive Symptoms and Glycated Hemoglobin, Blood Pressure, and Serum Cholesterol Among Patients With Depression and Diabetes in India: The INDEPENDENT Randomized Clinical Trial.

Importance: Mental health comorbidities are increasing worldwide and worsen outcomes for people with diabetes, especially when care is fragmented. Objective: To assess whether collaborative care vs usual care lowers depressive symptoms and improves cardiometabolic indices among adults with diabetes and depression. Design, Setting, and Participants: Parallel, open-label, pragmatic randomized clinical trial conducted at 4 socioeconomically diverse clinics in India that recruited patients with type 2 diabetes; a Patient Health Questionnaire-9 score of at least 10 (range, 0-27); and hemoglobin A1c (HbA1c) of at least 8%, systolic blood pressure (SBP) of at least 140 mm Hg, or low-density lipoprotein (LDL) cholesterol of at least 130 mg/dL. The first patient was enrolled on March 9, 2015, and the last was enrolled on May 31, 2016; the final follow-up visit was July 14, 2018. Interventions: Patients randomized to the intervention group (n = 196) received 12 months of self-management support from nonphysician care coordinators, decision support electronic health records facilitating physician treatment adjustments, and specialist case reviews; they were followed up for an additional 12 months without intervention. Patients in the control group (n = 208) received usual care over 24 months. Main Outcomes and Measures: The primary outcome was the between-group difference in the percentage of patients at 24 months who had at least a 50% reduction in Symptom Checklist Depression Scale (SCL-20) scores (range, 0-4; higher scores indicate worse symptoms) and a reduction of at least 0.5 percentage points in HbA1c, 5 mm Hg in SBP, or 10 mg/dL in LDL cholesterol. Prespecified secondary outcomes were percentage of patients at 12 and 24 months who met treatment targets (HbA1c <7.0%, SBP <130 mm Hg, LDL cholesterol <100 mg/dL [<70 mg/dL if prior cardiovascular disease]) or had improvements in individual outcomes (≥50% reduction in SCL-20 score, ≥0.5-percentage point reduction in HbA1c, ≥5-mm Hg reduction in SBP, ≥10-mg/dL reduction in LDL cholesterol); percentage of patients who met all HbA1c, SBP, and LDL cholesterol targets; and mean reductions in SCL-20 score, Patient Health Questionnaire-9 score, HbA1c, SBP, and LDL cholesterol. Results: Among 404 patients randomized (mean [SD] age, 53 [8.6] years; 165 [40.8%] men), 378 (93.5%) completed the trial. A significantly greater percentage of patients in the intervention group vs the usual care group met the primary outcome (71.6% vs 57.4%; risk difference, 16.9% [95% CI, 8.5%-25.2%]). Of 16 prespecified secondary outcomes, there were no statistically significant between-group differences in improvements in 10 outcomes at 12 months and in 13 outcomes at 24 months. Serious adverse events in the intervention and usual care groups included cardiovascular events or hospitalizations (4 [2.0%] vs 7 [3.4%]), stroke (0 vs 3 [1.4%]), death (2 [1.0%] vs 7 [3.4%]), and severe hypoglycemia (8 [4.1%] vs 0). Conclusions and Relevance: Among patients with diabetes and depression in India, a 12-month collaborative care intervention, compared with usual care, resulted in statistically significant improvements in a composite measure of depressive symptoms and cardiometabolic indices at 24 months. Further research is needed to understand the generalizability of the findings to other low- and middle-income health care settings. Trial Registration: ClinicalTrials.gov Identifier: NCT02022111.

Associations between self-management behavior and sociodemographic and disease-related characteristics in elderly people with type 2 diabetes - New results from the population-based KORA studies in Germany.

AIMS: Self-management behavior (SMB) is an important aspect in the management of diabetes. This study aimed to identify sociodemographic and disease-related factors associated with good SMB in people with type 2 diabetes (T2D). METHODS: We used data from 479 people with T2D aged 65 or older from the population-based KORA (Cooperative Health Research in the Area of Augsburg) Health Survey 2016 in Southern Germany. We estimated Poisson and logistic regression models testing the cross-sectional relationship between individual or disease-related characteristics and an established SMB sum index comprising six SMB dimensions stratified according to insulin treatment status. RESULTS: Mean age in the sample was 75 and mean diabetes duration was 13 years. The overall level of SMB was low. Higher SMB index scores were associated with higher age, treatment with insulin, participation in a diabetes education program, and, for people with insulin treatment, with a BMI below 30 kg/m2. Single item analyses generally supported these findings. CONCLUSIONS: SMB in people with T2D needs to be improved with efficient interventions. Targeting obese individuals and those at an early stage of the disease with low-barrier, regular education or self-management programs may be a preferred strategy.

Travel-related control measures to contain the COVID-19 pandemic: a rapid review.

BACKGROUND: In late 2019, first cases of coronavirus disease 2019, or COVID-19, caused by the novel coronavirus SARS-CoV-2, were reported in Wuhan, China. Subsequently COVID-19 spread rapidly around the world. To contain the ensuing pandemic, numerous countries have implemented control measures related to international travel, including border closures, partial travel restrictions, entry or exit screening, and quarantine of travellers. OBJECTIVES: To assess the effectiveness of travel-related control measures during the COVID-19 pandemic on infectious disease and screening-related outcomes. SEARCH METHODS: We searched MEDLINE, Embase and COVID-19-specific databases, including the WHO Global Database on COVID-19 Research, the Cochrane COVID-19 Study Register, and the CDC COVID-19 Research Database on 26 June 2020. We also conducted backward-citation searches with existing reviews. SELECTION CRITERIA: We considered experimental, quasi-experimental, observational and modelling studies assessing the effects of travel-related control measures affecting human travel across national borders during the COVID-19 pandemic. We also included studies concerned with severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) as indirect evidence. Primary outcomes were cases avoided, cases detected and a shift in epidemic development due to the measures. Secondary outcomes were other infectious disease transmission outcomes, healthcare utilisation, resource requirements and adverse effects if identified in studies assessing at least one primary outcome. DATA COLLECTION AND ANALYSIS: One review author screened titles and abstracts; all excluded abstracts were screened in duplicate. Two review authors independently screened full texts. One review author extracted data, assessed risk of bias and appraised study quality. At least one additional review author checked for correctness of all data reported in the 'Risk of bias' assessment, quality appraisal and data synthesis. For assessing the risk of bias and quality of included studies, we used the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for observational studies concerned with screening, ROBINS-I for observational ecological studies and a bespoke tool for modelling studies. We synthesised findings narratively. One review author assessed certainty of evidence with GRADE, and the review author team discussed ratings. MAIN RESULTS: We included 40 records reporting on 36 unique studies. We found 17 modelling studies, 7 observational screening studies and one observational ecological study on COVID-19, four modelling and six observational studies on SARS, and one modelling study on SARS and MERS, covering a variety of settings and epidemic stages. Most studies compared travel-related control measures against a counterfactual scenario in which the intervention measure was not implemented. However, some modelling studies described additional comparator scenarios, such as different levels of travel restrictions, or a combination of measures. There were concerns with the quality of many modelling studies and the risk of bias of observational studies. Many modelling studies used potentially inappropriate assumptions about the structure and input parameters of models, and failed to adequately assess uncertainty. Concerns with observational screening studies commonly related to the reference test and the flow of the screening process. Studies on COVID-19 Travel restrictions reducing cross-border travel Eleven studies employed models to simulate a reduction in travel volume; one observational ecological study assessed travel restrictions in response to the COVID-19 pandemic. Very low-certainty evidence from modelling studies suggests that when implemented at the beginning of the outbreak, cross-border travel restrictions may lead to a reduction in the number of new cases of between 26% to 90% (4 studies), the number of deaths (1 study), the time to outbreak of between 2 and 26 days (2 studies), the risk of outbreak of between 1% to 37% (2 studies), and the effective reproduction number (1 modelling and 1 observational ecological study). Low-certainty evidence from modelling studies suggests a reduction in the number of imported or exported cases of between 70% to 81% (5 studies), and in the growth acceleration of epidemic progression (1 study). Screening at borders with or without quarantine Evidence from three modelling studies of entry and exit symptom screening without quarantine suggests delays in the time to outbreak of between 1 to 183 days (very low-certainty evidence) and a detection rate of infected travellers of between 10% to 53% (low-certainty evidence). Six observational studies of entry and exit screening were conducted in specific settings such as evacuation flights and cruise ship outbreaks. Screening approaches varied but followed a similar structure, involving symptom screening of all individuals at departure or upon arrival, followed by quarantine, and different procedures for observation and PCR testing over a period of at least 14 days. The proportion of cases detected ranged from 0% to 91% (depending on the screening approach), and the positive predictive value ranged from 0% to 100% (very low-certainty evidence). The outcomes, however, should be interpreted in relation to both the screening approach used and the prevalence of infection among the travellers screened; for example, symptom-based screening alone generally performed worse than a combination of symptom-based and PCR screening with subsequent observation during quarantine. Quarantine of travellers Evidence from one modelling study simulating a 14-day quarantine suggests a reduction in the number of cases seeded by imported cases; larger reductions were seen with increasing levels of quarantine compliance ranging from 277 to 19 cases with rates of compliance modelled between 70% to 100% (very low-certainty evidence). AUTHORS' CONCLUSIONS: With much of the evidence deriving from modelling studies, notably for travel restrictions reducing cross-border travel and quarantine of travellers, there is a lack of 'real-life' evidence for many of these measures. The certainty of the evidence for most travel-related control measures is very low and the true effects may be substantially different from those reported here. Nevertheless, some travel-related control measures during the COVID-19 pandemic may have a positive impact on infectious disease outcomes. Broadly, travel restrictions may limit the spread of disease across national borders. Entry and exit symptom screening measures on their own are not likely to be effective in detecting a meaningful proportion of cases to prevent seeding new cases within the protected region; combined with subsequent quarantine, observation and PCR testing, the effectiveness is likely to improve. There was insufficient evidence to draw firm conclusions about the effectiveness of travel-related quarantine on its own. Some of the included studies suggest that effects are likely to depend on factors such as the stage of the epidemic, the interconnectedness of countries, local measures undertaken to contain community transmission, and the extent of implementation and adherence.

The impact of diabetes on labour market participation: a systematic review of results and methods.

BACKGROUND: Diabetes mellitus is a major chronic disease, which is connected to direct and indirect costs and productivity losses. However, its effects on labour market participation are not straightforward to identify, nor are they consistently included in cost-of-illness studies. First, this study aims to synthesise existing evidence regarding the impact of diabetes on labour market outcomes that imply a complete absence of work. Second, the analysis takes a particular look at relevant methodological choices and the resulting quality of the studies included. METHODS: We conducted a systematic literature research (PubMed, Embase, PsychINFO), by applying a standard screening, selection and results extraction process, which considered all types of studies including cross-sectional and longitudinal approaches. Risk-of-bias and quality within the studies were assessed and results were compared. We dedicated special attention to the modelling of potential reverse causality between diabetes and labour market outcomes and the consideration of comorbidities and complications. RESULTS: Overall, 30 studies satisfied our inclusion criteria. We identified four main labour participation outcomes: absence of employment, unemployment, early retirement, and disability pension. The studies reviewed show a negative impact of diabetes on the labour market participation outcomes considered. However, only a few studies controlled for endogeneity, differentiated between type 1 and type 2 diabetes or modelled the impact of comorbidities. We report how modelling choices affect the directions and interpretations of the effects. CONCLUSIONS: The available evidence mainly suggests a negative impact of diabetes on several outcomes indicating labour market participation. The methodological limitations identified can guide future research with respect to both outcomes and methods. This study provides therefore an empirical contribution to the discussion on how to model the economic impact of diabetes.