Prenatal influenza exposure and cardiovascular events in adulthood

Objectives: This study examined the association between prenatal exposure to pandemic influenza and cardiovascular events in adulthood. Design: Using Danish surveillance data to identify months when influenza activity was highest during three previous pandemics (1918, 1957, and 1968), persons were defined as exposed/unexposed based on whether they were in utero during peak months of one of the pandemics. Episodes of acute myocardial infarction (MI) and stroke were identified in the Danish National Registry of Patients covering all Danish hospitals since 1977. Setting/Sample Information from Danish national registries on all persons with a Civil Personal Registry number and birthdates in 1915 through 1922, 1954 through 1960, and 1966 through 1972 was collected. Main outcome measures Crude incidence rate ratios (IRRs) were calculated per pandemic. Generalized linear models were fit to estimate IRRs adjusted for sex. Results: For acute MI, sex-adjusted IRRs for persons in utero during peaks of the 1918, 1957, and 1968 pandemics, compared with those born afterward, were 1·02 (95% confidence interval (CI): 0·99, 1·05), 0·96 (95% CI: 0·87, 1·05), and 1·18 (95% CI: 0·96, 1·45), respectively. For stroke, the corresponding IRRs were 0·99 (95% CI: 0·97, 1·02), 0·99 (95% CI: 0·92, 1·05), and 0·85 (95% CI: 0·77, 0·94), respectively. Conclusions: There was generally no evidence of an association between prenatal influenza exposure and acute MI or stroke in adulthood. However, survivor bias and left truncation of outcomes for the 1918 pandemic are possible, and the current young ages of persons included in the analyses for the 1957 and 1968 pandemics may warrant later re-evaluation

Diagnosed prevalence of Alzheimer’s disease and related dementias in Medicare Advantage plans

IntroductionOne- third of Medicare beneficiaries are enrolled in Medicare Advantage (MA). Yet, little is known about MA beneficiaries diagnosed with Alzheimer’s disease (AD) and AD- related dementias (AD/ADRD).MethodsWe calculated the prevalence of AD/ADRD diagnoses in 2014 and 2016 in three MA plans. We determined the demographic characteristics of beneficiaries diagnosed with AD/ADRD, and whether they disenrolled from the MA plan for any reason within 364 days from the index date.ResultsIn 2014 and 2016, the overall prevalence of AD/ADRD diagnoses was 5.6% and 6.5%, respectively. In 2016, AD/ADRD beneficiaries were on average 82.4 (SD = 7.4) years of age, 61.8% female, and had multiple comorbidities. By 364 days post- index date, 32% of beneficiaries with AD/ADRD had disenrolled from their plan. The demographic characteristics of 2014 beneficiaries with diagnosed AD/ADRD were similar to their 2016 counterparts.DiscussionThe prevalence of AD/ADRD diagnosis in MA is lower than rates reported in Medicare fee- for- service.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156169/2/dad212048.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156169/1/dad212048_am.pd

In utero exposure to the 1918 pandemic influenza in Denmark and risk of dementia

Background: Substantial but inconclusive evidence suggests in utero exposure to influenza infection may be linked with Alzheimer′s disease. Objectives: We examined whether individuals exposed in utero to the 1918 influenza pandemic are at increased risk of dementia. Patients/Methods In this cohort study, surveillance data were used to identify months when influenza activity was at its peak during the pandemic. Using birth dates, exposed and unexposed individuals were identified based on whether they were in utero during ≥1 of the peak months. The outcome, any type of dementia, was identified in population‐based medical registries. Time and age at risk were restricted so exposed and unexposed had equal time at risk; diagnoses for dementia were assessed between ages 62 and 92, with a maximum of 30 years at risk. Poisson regression was used to estimate sex‐adjusted incidence rate ratios (IRRs). Results: We identified 106 479 exposed and 177 918 unexposed persons. Using the cumulative risk function, there were similar proportions of exposed and unexposed with a dementia diagnosis at 11.9% and 11.7%, respectively. Across all ages, the IRR for the association between in utero influenza exposure and any dementia was 1.01 (95% CI 0.99‐1.04); for Alzheimer's disease, it was 0.97 (0.93‐1.01). When stratified by age and sex, and when dementia type was examined, estimates of association were also null or close to null. Conclusions: Our study suggests there is likely not an association between in utero exposure to the 1918 influenza pandemic and dementia among those 62 and older

Precision Public Health for Non-communicable Diseases: An Emerging Strategic Roadmap and Multinational Use Cases

Non-communicable diseases (NCDs) remain the largest global public health threat. The emerging field of precision public health (PPH) offers a transformative opportunity to capitalize on digital health data to create an agile, responsive and data-driven public health system to actively prevent NCDs. Using learnings from digital health, our aim is to propose a vision toward PPH for NCDs across three horizons of digital health transformation: Horizon 1—digital public health workflows; Horizon 2—population health data and analytics; Horizon 3—precision public health. This perspective provides a high-level strategic roadmap for public health practitioners and policymakers, health system stakeholders and researchers to achieving PPH for NCDs. Two multinational use cases are presented to contextualize our roadmap in pragmatic action: ESP and RiskScape (USA), a mature PPH platform for multiple NCDs, and PopHQ (Australia), a proof-of-concept population health informatics tool to monitor and prevent obesity. Our intent is to provide a strategic foundation to guide new health policy, investment and research in the rapidly emerging but nascent area of PPH to reduce the public health burden of NCDs

Validation of Claims-Based Algorithm for Lyme Disease, Massachusetts, USA

Compared with notifiable disease surveillance, claims-based algorithms estimate higher Lyme disease incidence, but their accuracy is unknown. We applied a previously developed Lyme disease algorithm (diagnosis code plus antimicrobial drug prescription dispensing within 30 days) to an administrative claims database in Massachusetts, USA, to identify a Lyme disease cohort during July 2000–June 2019. Clinicians reviewed and adjudicated medical charts from a cohort subset by using national surveillance case definitions. We calculated positive predictive values (PPVs). We identified 12,229 Lyme disease episodes in the claims database and reviewed and adjudicated 128 medical charts. The algorithmʼs PPV for confirmed, probable, or suspected cases was 93.8% (95% CI 88.1%–97.3%); the PPV was 66.4% (95% CI 57.5%–74.5%) for confirmed and probable cases only. In a high incidence setting, a claims-based algorithm identified cases with a high PPV, suggesting it can be used to assess Lyme disease burden and supplement traditional surveillance data