Population Health Surveillance Research Articles

Examining associations between mental health and Chronic Non-Communicable Diseases (C-NCDs) among older adults in Wakiso, Uganda.

Globally, the prevalence of chronic non-communicable diseases (C-NCDs) and occurrence of multi-morbidity specifically, has been increasing and will continue to rise as life expectancy increases. The burden of mental health disorders has also been rising globally. In sub-Saharan Africa (SSA), literature on these health issues, which are interrelated, is scarce. This study assesses the prevalence of C-NCDs, and depressive and anxiety symptomology and examines the relationship between these issues among a sample of older adults in Uganda. Between 2021-2022, 604 consenting adults aged 35 years and older were surveyed on a broad range of health issues for the ongoing AMBSO Population Health Surveillance (APHS) cohort study in Wakiso district. Descriptive analyses were performed to characterize the burden of C-NCDs (e.g. diabetes, hypertension), depression (PHQ-9 using a cutoff of <5 scores for minimal/no and 5+ for mild to severe symptomology) and anxiety (GAD-7 using a cutoff of 5+ scores for mild to severe symptomology). Bivariate analysis and multivariable logistic regression models were built using STATA software version 16.0 to examine associations between mental health disorders and having at least one C-NCD. Our exposures of interest were depressive and anxiety symptoms and our outcomes of interest was presence of C-NCDs. Majority of participants were females (63.6%), median age was 46 (IQR: 39-54). Any C-NCDs prevalence was 18.7%, while 18.9% and 11.4%, had screening scores indicative of depressive and anxiety symptomology, respectively. Three percent (3.2%) had PHQ-9 scores indicative of moderate to severe depressive symptomology. In models adjusted for sociodemographic characteristics, there was 12% increased odds of suffering from C-NCDs for every unit increase in PHQ-9 score (AOR = 1.12, 95% CI: 1.10-1.20). Participants with any anxiety symptoms had 2.1 greater odds of suffering from C-NCD compared to those who did not have anxiety symptoms (AOR = 2.10, 95% CI: 1.21-3.70). C-NCDs were prevalent in older adults, particularly among those experiencing mental health symptoms. Screening for C-NCDs and mental health disorders should be integrated into routine health care for older adults in the country. Early screening and identification of these health issues through primary health care could significantly reduce the public health burden attributable to mental health disorders and the incidence of multi-morbidity in Uganda.

Polygenic and socioeconomic contributions to nicotine use and cardiometabolic health in early mid-life.

Early mid-life is marked by accumulating risks for cardiometabolic illness linked to health-risk behaviors like nicotine use. Identifying polygenic indices (PGI) has enriched scientific understanding of the cumulative genetic contributions to behavioral and cardiometabolic health, though few studies have assessed these associations alongside socioeconomic (SES) and lifestyle factors. Drawing on data from 2,337 individuals from the United States participating in the National Longitudinal Study of Adolescent to Adult Health, the current study assesses the fraction of variance in five related outcomes - use of conventional and electronic cigarettes, body mass index (BMI), waist circumference, and glycosylated hemoglobin (A1c) - explained by PGI, SES, and lifestyle. Regression models on African ancestry (AA) and European ancestry (EA) subsamples reveal that the fraction of variance explained by PGI ranges across outcomes. While adjusting for sex and age, PGI explained 3.5%, 2.2%, and 0% in the AA subsample of variability in BMI, waist circumference, and A1c, respectively (in the EA subsample these figures were 7.7%, 9.4%, and 1.3%). The proportion of variance explained by PGI in nicotine-use outcomes is also variable. Results further indicate that PGI and SES are generally complementary, accounting for more variance in the outcomes when modeled together versus separately. PGI are gaining attention in population health surveillance, but polygenic variability might not align clearly with health differences in populations or surpass SES as a fundamental cause of health disparities. We discuss future steps in integrating PGI and SES to refine population health prediction rules. Study findings point to the complementary relationship of polygenic indices (PGI) and socioeconomic indicators in explaining population variance in nicotine outcomes and cardiometabolic wellness. Population health surveillance and prediction rules would benefit from the combination of information from both polygenic and socioeconomic risks. Additionally, the risk for electronic cigarette use among users of conventional cigarettes may have a genetic component tied to the cumulative genetic propensity for heavy smoking. Further research on PGI for vaping is needed.

Women's access to family planning and experiences of reproductive coercion during the COVID-19 lockdown in two districts of Uganda

BackgroundIn March 2020, Uganda enforced country-wide restrictions to control the spread of SARS-CoV-2, categorizing some health services, including family planning (FP), as non-essential. Globally, similar COVID-19 restrictions have been associated with increased vulnerability to reproductive coercion (RC) among women, due to changes in FP service availability and restricted access by partners. This study aims to investigate these dynamics in Uganda, specifically examining the impact of the COVID-19 lockdown on women's access to FP, their experiences of RC, and the relationship between RC and intimate partner violence (IPV). MethodsWe conducted a cross-sectional analysis of data from 960 women participating in the AMBSO Population Health Surveillance Study (APHS) between August 2020 and March 2021 across Wakiso (N = 164) and Hoima (N = 796) districts in Uganda. Our analysis focused on women who were sexually active in the past month, using bivariate analyses to explore the associations between RC and recent experiences of sexual, physical, and verbal IPV. FindingsThe most commonly reported FP methods were injectables (36.8 %) and implants (16 %). Despite the COVID-19 lockdown, less than one percent of participants reported an inability to access their preferred FP method. Notably, 3 % of the women experienced RC in the past 12 months. There was a significant association between RC and sexual IPV (p < 0.0001), as well as physical IPV (p < 0.0001). Instances of verbal IPV were observed to have tripled during the lockdown period. InterpretationAn increase in verbal IPV was found among women during the COVID-19 lockdown. Additionally, a notable association emerged between other forms of IPV and an increased risk of RC. Despite the lockdown, access to FP remained high, which could be attributed to the prevalent use of long-acting FP methods.

Identification of Hypertension in Electronic Health Records Through Computable Phenotype Development and Validation for Use in Public Health Surveillance: Retrospective Study.

Electronic health record (EHR) systems are widely used in the United States to document care delivery and outcomes. Health information exchange (HIE) networks, which integrate EHR data from the various health care providers treating patients, are increasingly used to analyze population-level data. Existing methods for population health surveillance of essential hypertension by public health authorities may be complemented using EHR data from HIE networks to characterize disease burden at the community level. We aimed to derive and validate computable phenotypes (CPs) to estimate hypertension prevalence for population-based surveillance using an HIE network. Using existing data available from an HIE network, we developed 6 candidate CPs for essential (primary) hypertension in an adult population from a medium-sized Midwestern metropolitan area in the United States. A total of 2 independent clinician reviewers validated the phenotypes through a manual chart review of 150 randomly selected patient records. We assessed the precision of CPs by calculating sensitivity, specificity, positive predictive value (PPV), F1-score, and validity of chart reviews using prevalence-adjusted bias-adjusted κ. We further used the most balanced CP to estimate the prevalence of hypertension in the population. Among a cohort of 548,232 adults, 6 CPs produced PPVs ranging from 71% (95% CI 64.3%-76.9%) to 95.7% (95% CI 84.9%-98.9%). The F1-score ranged from 0.40 to 0.91. The prevalence-adjusted bias-adjusted κ revealed a high percentage agreement of 0.88 for hypertension. Similarly, interrater agreement for individual phenotype determination demonstrated substantial agreement (range 0.70-0.88) for all 6 phenotypes examined. A phenotype based solely on diagnostic codes possessed reasonable performance (F1-score=0.63; PPV=95.1%) but was imbalanced with low sensitivity (47.6%). The most balanced phenotype (F1-score=0.91; PPV=83.5%) included diagnosis, blood pressure measurements, and medications and identified 210,764 (38.4%) individuals with hypertension during the study period (2014-2015). We identified several high-performing phenotypes to identify essential hypertension prevalence for local public health surveillance using EHR data. Given the increasing availability of EHR systems in the United States and other nations, leveraging EHR data has the potential to enhance surveillance of chronic disease in health systems and communities. Yet given variability in performance, public health authorities will need to decide whether to seek optimal balance or declare a preference for algorithms that lean toward sensitivity or specificity to estimate population prevalence of disease.

Prevalence and predictors of use of long-term and short-acting reversible contraceptives among women of reproductive age in Wakiso and Hoima districts, Uganda: A cross-sectional study

Modern contraceptive use has increased globally, but unmet needs persist in low- and middle-income countries. This study in Uganda aimed to examine the prevalence and factors influencing the use of short-acting reversible contraceptives (SARC) like pills and long-term methods such as intrauterine devices. Limited evidence exists on the use of SARC and long-term methods in Uganda. Data from the Africa Medical and Behavioural Sciences Organization (AMBSO) Population Health Surveillance (APHS) in Hoima and Wakiso districts were analysed. Among the 1642 women aged 15–49 years, the prevalence of modern contraceptive use was 30% for SARC, and 18% for long-term method. Women with formal education were three times more likely to use long-term methods than those without formal education, relative risk ratios (RRR), 3.1–3.4, (95%CI 1.2–8.2). Joint decision-making for contraceptive use increased SARC usage, RRR 1.4 (95%CI 1.1–1.8). Urbanization played a role, with women in more urbanized Wakiso district less likely to use any modern contraception, RRR 0.6–0.7 (95%CI 0.5–0.9) compared to those living in the less urbanized Hoima. About half of the women in the study used modern contraceptives and the use of SARC was almost twice that of long-term methods. Increased access to contraception education for all women of reproductive age could significantly improve the use of long-term methods which offer more reliable protection against unintended pregnancies. The findings shed light on the need to strengthen both general and sexuality education to girls and women and to tailor contraception access for all in need, for mobile semi-urban as well as rural women. Well-informed strategies that engage young men and male partners in informed decision-making for contraceptive use could enhance progress.

A new multiplexed magnetic capture-Droplet digital PCR tool for monitoring wildlife population health and pathogen surveillance.

Anthropogenic stressors are exacerbating the emergence and spread of pathogens worldwide. In regions like the Arctic, where ecosystems are particularly susceptible, marked changes are predicted in regional diversity, intensity, and patterns of infectious diseases. To understand such rapidly changing host-pathogen dynamics and mitigate the impacts of novel pathogens, we need sensitive disease surveillance tools. We developed and validated a novel multiplexed, magnetic capture, and ddPCR tool for the surveillance of multiple pathogens in polar bears, a sentinel species that is considered susceptible to climate change and other stressors with a pan-Arctic distribution. Through sequence-specific magnetic capture, we concentrated five target template sequences from three zoonotic bacteria (Erysipelothrix rhusiopathiae, Francisella tularensis, and Mycobacterium tuberculosis complex) and two parasitic (Toxoplasma gondii and Trichinella spp.) pathogens from large quantities (<100 g) of host tissue. We then designed and validated two multiplexed probe-based ddPCR assays for the amplification and detection of the low-concentration target DNA. Validations used 48 polar bear tissues (muscle and liver). We detected 14, 1, 3, 4, and 22 tissue positives for E. rhusiopathiae, F. tularensis, M. tuberculosis complex, T. gondii, and Trichinella spp., respectively. These multiplexed assays offer a rapid, specific tool for quantifying and monitoring the changing geographical and host distributions of pathogens relevant to human and animal health.

Consumers' Trust in Different Sources of Information Related to Food Hazards and Their Judgment of Government Performance-A Cross-Sectional Study in Brazil.

Trust in institutions is fundamental for the stability and proper functioning of democracies, particularly in matters of high public sensitivity, such as food safety. This study aimed to assess trust levels in different sources of information and respondents' evaluation of the performance of government agencies responsible for controlling food-related hazards. Individuals interviewed in three environments (hospitals/clinics, supermarkets, universities, N = 1000) answered a face-to-face questionnaire in the Federal District of Brazil, and another population (health surveillance employees at the municipal, state and federal levels; N = 1017) answered the questionnaire online. About 60% of the population interviewed considered government performance to be low/very low. Scientists/universities, medical doctors (MD)/health professionals, and nongovernmental organizations (NGOs) were judged to be the most reliable sources of information on food hazards, while the food industry, supermarkets and social media inspired the lowest trust. Individuals from the hospitals/clinics group had significantly higher trust in MD/health professionals, media and websites than the two other Federal District groups. In general, income and education were the most predictive factors for the results, being negatively associated with assessment of government performance and trust in most information sources. In the Federal District, there was a negative association between trust levels in the government and worry about pesticides and genetically modified food, but a positive association between trust in NGOs and worry on these hazards. The results point to the need for the implementation of more effective communication strategies by institutions in which the population has low trust levels, such as government and food companies.

Utilization of Electronic Health Records for Chronic Disease Surveillance: A Systematic Literature Review.

This study reviews the current utilization of electronic health records (EHRs) for chronic disease surveillance, discusses approaches that are used in obtaining EHR-derived disease prevalence estimates, and identifies health indicators that have been studied using EHR-based surveillance methods. PubMed was searched for relevant keywords: (electronic health records [Title/Abstract] AND surveillance [Title/Abstract]) OR (electronic medical records [Title/Abstract] AND surveillance [Title/Abstract]). Articles were assessed based on detailed inclusion and exclusion criteria and organized by common themes, as per the PRISMA review protocol. The study period was limited to 2015-2021 due to the wider adoption of EHR in the U.S. only since 2015. The review included only US studies and only those that focused on chronic disease surveillance. 17 studies were included in the review. The most common approaches the review identified focused on validating EHR-derived estimates against those from traditional national surveys. The most studied conditions were diabetes, obesity, and hypertension. The majority of reviewed studies demonstrated comparable prevalence estimates with traditional population health surveillance surveys. The most common approach for the estimation of chronic disease conditions was to use small-area estimation by geographic patterns, neighborhoods, or census tracts. The use of EHR-based surveillance systems for public health purposes is feasible, and the population health estimates appear comparable to those obtained through traditional surveillance surveys. The application of EHRs for public health surveillance appears promising and could offer a real-time alternative to traditional surveillance methods. A timely assessment of population health at local and regional levels would ensure a more targeted allocation of public health and healthcare resources as well as more effective intervention and prevention initiatives.

Data collection systems for active safety surveillance of vaccines during pregnancy in low- and middle-income countries: developing and piloting an assessment tool (VPASS)

BackgroundThere is an urgent need for active safety surveillance to monitor vaccine exposure during pregnancy in low- and middle-income countries (LMICs). Existing maternal, newborn, and child health (MNCH) data collection systems could serve as platforms for post-marketing active surveillance of maternal immunization safety. To identify sites using existing systems, a thorough assessment should be conducted. Therefore, this study had the objectives to first develop an assessment tool and then to pilot this tool in sites using MNCH data collection systems through virtual informant interviews.MethodsWe conducted a rapid review of the literature to identify frameworks on population health or post-marketing drug surveillance. Four frameworks that met the eligibility criteria were identified and served to develop an assessment tool capable of evaluating sites that could support active monitoring of vaccine safety during pregnancy. We conducted semi-structured interviews in six geographical sites using MNCH data collection systems (DHIS2, INDEPTH, and GNMNHR) to pilot domains included in the assessment tool.ResultsWe developed and piloted the “VPASS (Vaccines during Pregnancy – sites supporting Active Safety Surveillance) assessment tool” through interviews with nine stakeholders, including central-level systems key informants and site-level managers from DHIS2 and GNMNHR; DHIS2 in Kampala (Uganda) and Kigali (Rwanda); GNMNHR from Belagavi (India) and Lusaka (Zambia); and INDEPTH from Nanoro (Burkina Faso) and Manhica (Mozambique). The tool includes different domains such as the system’s purpose, the scale of implementation, data capture and confidentiality, type of data collected, the capability of integration with other platforms, data management policies and data quality monitoring. Similarities among sites were found regarding some domains, such as data confidentiality, data management policies, and data quality monitoring. Four of the six sites met some domains to be eligible as potential sites for active surveillance of vaccinations during pregnancy, such as a routine collection of MNCH individual data and the capability of electronically integrating individual MNCH outcomes with information related to vaccine exposure during pregnancy. Those sites were: Rwanda (DHIS2), Manhica (IN-DEPTH), Lusaka (GNMNHR), and Belagavi (GNMNHR).ConclusionThis study's findings should inform the successful implementation of active safety surveillance of vaccines during pregnancy by identifying and using active individual MNCH data collection systems in LMICs.

Examining the use of decision trees in population health surveillance research: an application to youth mental health survey data in the COMPASS study.

In population health surveillance research, survey data are commonly analyzed using regression methods; however, these methods have limited ability to examine complex relationships. In contrast, decision tree models are ideally suited for segmenting populations and examining complex interactions among factors, and their use within health research is growing. This article provides a methodological overview of decision trees and their application to youth mental health survey data. The performance of two popular decision tree techniques, the classification and regression tree (CART) and conditional inference tree (CTREE) techniques, is compared to traditional linear and logistic regression models through an application to youth mental health outcomes in the COMPASS study. Data were collected from 74 501 students across 136 schools in Canada. Anxiety, depression and psychosocial well-being outcomes were measured along with 23 sociodemographic and health behaviour predictors. Model performance was assessed using measures of prediction accuracy, parsimony and relative variable importance. Decision tree and regression models consistently identified the same sets of most important predictors for each outcome, indicating a general level of agreement between methods. Tree models had lower prediction accuracy but were more parsimonious and placed greater relative importance on key differentiating factors. Decision trees provide a means of identifying high-risk subgroups to whom prevention and intervention efforts can be targeted, making them a useful tool to address research questions that cannot be answered by traditional regression methods.

Lock the Doors: The Myocarditis Disaster and a call for the broad examination of the CDC and FDA

“Lock the doors.” uttered by LeRoy Cain, the flight director of STS-107, meant the complete loss of Space Shuttle Columbia. Locking the doors initiated the protocol to preserve data and logs for the impending investigation. Some hard lessons were learned from the Space Shuttle Challenger disaster 17 years earlier, one of which was that the National Aeronautics and Space Administration (NASA) should not be put in a position to investigate itself. The interagency Columbia Accident Investigation Board (CAIB) was formed to learn what we could from the fate of Columbia. Had NASA been the investigating agency, given the culture, it is possible the concluding cause would have been a random event such as bird strike after takeoff or micrometeoroid in orbit. “We are convinced that the management practices overseeing the Space Shuttle Program were as much a cause of the accident as the foam that struck the left wing.”[1] Those management practices point to lock-stepping, where dissenting opinions are discouraged or suppressed. NASA’s opinion was that foam is safe. When Bob Page, chair of NASA’s Intercenter Photo Working Group, saw foam strike the wing he raised an alarm that the heat shield may be compromised. He and two members of the Debris Assessment Team made a total of three requests to the Department of Defense (DoD) to obtain high-resolution images of Columbia’s left wing. A request that, by all accounts, the DoD was willing and able to fulfill. Those requests were subsequently canceled by the shuttle program managers. The CAIB report went on to say, “[t]he Board was also influenced by discussions with members of Congress, who suggested that this nation needed a broad examination of NASAʼs Human Space Flight Program, rather than just an investigation into what physical fault caused Columbia to break up during re-entry.” There are two vitally important lessons we have learned from NASA. The first is that a government agency should not be able to investigate itself. The second is that lock-stepping is lethal. The most advanced population health surveillance in the United States couldn’t find a single healthy child who died of COVID-19. Zero is a powerful number. Zero is also the number of vaccines that impart superior immunity over that of natural immunity. If we could choose one feature that the emergent 5th endemic cold virus could have, it would unequivocally be a minimal effect on children – safeguarding our future and allowing the progression of natural immunity. There is nothing mild about pediatric myocarditis. Even with the best medical management, 1/3rd of all patients never completely recovers, and will live with dilated cardiomyopathy. If untreated, 80% of children will develop chronic heart disease. These children are subject to a high risk of sudden death and may require an urgent heart transplant[2].

COGNITIVE DECLINE PUBLIC HEALTH SURVEILLANCE: EXPERT-GUIDED COLLABORATION FOR BRFSS MODULE REVISION

Abstract The Behavioral Risk Factor Surveillance System (BRFSS) Cognitive Decline Module collects population level data on subjective cognitive decline (SCD) — self-reported difficulties in thinking or memory — which can be one of the earliest warning signs of dementia. Originally devised in 2009, the module undergoes periodic revision to ensure it remains current, the data collected are actionable, and to encourage uptake of the module by state health agencies. In 2021, the Alzheimer’s Association and the Centers for Disease Control and Prevention’s Alzheimer’s Disease Program formed an expert workgroup to examine the ongoing value and relevance of the module and propose any improvements. Workgroup members included researchers, chronic disease directors, epidemiologists, survey methodologists, policy analysts, and BRFSS coordinators. Using a consensus-building process, the workgroup utilized pre-meeting worksheets to identify areas of agreement and disagreement which informed key debates during subsequent meetings. Among many factors, the workgroup assessed the existing module for accuracy and utility. Discussion centered on aligning language and concepts contained within the module’s questions with current scientific research on SCD and how to accurately and adequately assess the associated burden SCD imposes. People living with cognitive impairment were consulted during the revision process to ensure phrasing reflected their lived experience. The result was a consensus set of suggested revisions to the Cognitive Decline Module, submitted to CDC for review and approval. The robust process, involving a variety of stakeholders and perspectives, can serve as an efficient and effective model for ensuring the longevity and usefulness of population health surveillance.

The Memphis Pandemic Health Informatics System (MEMPHI-SYS)-Creating a Metropolitan COVID-19 Data Registry Linked Directly to Community Testing to Enhance Population Health Surveillance.

The current coronavirus disease (COVID-19) pandemic has placed unprecedented strain on underfunded public health resources in the Southeastern United States. The Memphis, TN, metropolitan region has lacked infrastructure for health data exchange.This manuscript describes a multidisciplinary initiative to create a community-focused COVID-19 data registry, the Memphis Pandemic Health Informatics System (MEMPHI-SYS). MEMPHI-SYS leverages test result data updated directly from community-based testing sites, as well as a full complement of public health data sets and knowledge-based informatics. It has been guided by relationships with community stakeholders and is managed alongside the largest publicly funded community-based COVID-19 testing response in the Mid-South. MEMPHI-SYS has supported interactive Web-based analytic resources and informs federally funded COVID-19 outreach directed toward neighborhoods most in need of pandemic support.MEMPHI-SYS provides an instructive case study of how to collaboratively establish the technical scaffolding and human relationships necessary for data-driven, health equity-focused pandemic surveillance, and policy interventions.

Real-world data for precision public health of noncommunicable diseases: a scoping review

BackgroundGlobal public health action to address noncommunicable diseases (NCDs) requires new approaches. NCDs are primarily prevented and managed in the community where there is little investment in digital health systems and analytics; this has created a data chasm and relatively silent burden of disease. The nascent but rapidly emerging area of precision public health offers exciting new opportunities to transform our approach to NCD prevention. Precision public health uses routinely collected real-world data on determinants of health (social, environmental, behavioural, biomedical and commercial) to inform precision decision-making, interventions and policy based on social position, equity and disease risk, and continuously monitors outcomes – the right intervention for the right population at the right time. This scoping review aims to identify global exemplars of precision public health and the data sources and methods of their aggregation/application to NCD prevention.MethodsThe Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR) was followed. Six databases were systematically searched for articles published until February 2021. Articles were included if they described digital aggregation of real-world data and ‘traditional’ data for applied community, population or public health management of NCDs. Real-world data was defined as routinely collected (1) Clinical, Medication and Family History (2) Claims/Billing (3) Mobile Health (4) Environmental (5) Social media (6) Molecular profiling (7) Patient-centred (e.g., personal health record). Results were analysed descriptively and mapped according to the three horizons framework for digital health transformation.ResultsSix studies were included. Studies developed population health surveillance methods and tools using diverse real-world data (e.g., electronic health records and health insurance providers) and traditional data (e.g., Census and administrative databases) for precision surveillance of 28 NCDs. Population health analytics were applied consistently with descriptive, geospatial and temporal functions. Evidence of using surveillance tools to create precision public health models of care or improve policy and practice decisions was unclear.ConclusionsApplications of real-world data and designed data to address NCDs are emerging with greater precision. Digital transformation of the public health sector must be accelerated to create an efficient and sustainable predict-prevent healthcare system.

The Burden of Disease in Germany at the National and Regional Level.

.Summary measures such as disability-adjusted life years (DALY) are becoming increasingly important for the standardized assessment of the burden of disease due to death and disability. The BURDEN 2020 pilot project was designed as an independent burden-of-disease study for Germany, which was based on nationwide data, but which also yielded regional estimates. DALY is defined as the sum of years of life lost due to death (YLL) and years lived with disability (YLD). YLL is the difference between the age at death due to disease and the remaining life expectancy at this age, while YLD quantifies the number of years individuals have spent with health impairments. Data are derived mainly from causes of death statistics, population health surveys, and claims data from health insurers. In 2017, there were approximately 12 million DALY in Germany, or 14 584 DALY per 100 000 inhabitants. Conditions which caused the greatest number of DALY were coronary heart disease (2321 DALY), low back pain (1735 DALY), and lung cancer (1197 DALY). Headache and dementia accounted for a greater disease burden in women than in men, while lung cancer and alcohol use disorders accounted for a greater disease burden in men than in women. Pain disorders and alcohol use disorders were the leading causes of DALY among young adults of both sexes. The disease burden rose with age for some diseases, including cardiovascular diseases, dementia, and diabetes mellitus. For some diseases and conditions, the disease burden varied by geographical region. The results indicate a need for age- and sex-specific prevention and for differing interventions according to geographic region. Burden of disease studies yield comprehensive population health surveillance data and are a useful aid to decision-making in health policy.

Burden of disease assessment for Germany and its regions – results from the BURDEN 2020 study

Abstract Background Epidemiological measures such as incidence, prevalence, or deaths are essential for monitoring population health. However, evaluating them in isolation cannot adequately compare and assess the relative importance of different diseases. Assessments of the burden of disease (BoD) are therefore of growing importance in supporting health policy decisions. Using disability-adjusted life years (DALY) as a summary measure of population health, BoD integrates morbidity and mortality in a transparent approach. Methods Within BoD methodology, deviations in the health of the population from an ‘ideal’ health status is quantified in the unit of life years. DALY are the sum of years of life lost due to death (YLL) and years lived with disability (YLD). While YLL describe the gap between age at death and statistical life expectancy, the indicator YLD quantifies years lived with a disability or disease. Calculations were based on different primary and secondary data sources for Germany, especially cause-of-death statistics, epidemiological survey data, and statutory health insurance data. Results In Germany, there were about 12 million DALY in 2017, the equivalent of 14,584 DALY per 100,000 population. Coronary heart disease contributes the most to the overall burden of disease, followed by lower back pain and lung cancer. In women, headache disorders and dementias account for more DALY as compared to men. Men have a higher burden of disease from lung cancer or alcohol use disorders. Pain disorders and alcohol use disorders lead the DALY rankings for both sexes in younger adulthood. The burden due to cardiovascular disease, COPD, and diabetes mellitus increases with age and also varies by region. Conclusions The results suggest age- and gender-specific prevention as well as regional health care needs. BoD studies therefore provide comprehensive data for population health surveillance and can support health policy decisions. Key messages • The importance of specific diseases as measured by DALY differs greatly by age and gender, highlighting the need for targeted prevention measures. • Regional patterns emerge for cardiovascular disease, COPD, and depressive disorders, among others, which may indicate health care needs.

Health surveillance representative of koala (Phascolarctos cinereus) distribution in Victoria, Australia.

Health surveillance of wildlife populations is essential for conservation and reduction of the impacts of disease. Population declines and areas of overabundance of koalas (Phascolarctos cinereus) can disrupt the overall survival of the species as well as its habitat. This retrospective study was conducted to describe population distributions, identify areas which need increased surveillance and improve koala health surveillance methodology by Wildlife Health Victoria: Surveillance (WHV:S) at the Veterinary School of The University of Melbourne. Twelve years of Victorian koala observation data from the Atlas of Living Australia combined with surveillance data from WHV:S were used to create choropleth maps, using Quantum Geographic Information Systems of populations and surveillance events, visually representing hot spots. This data was further used to calculate health surveillance efforts between 2008 to the beginning of 2020. Analysis ranked postcodes throughout Victoria from low surveillance efforts to high, using standardised surveillance ratio's 95% confidence interval upper limits which were mapped using a colour gradient. This identified postcodes which need increased surveillance effort, corresponding to areas with high koala observations and low surveillance submissions. This analysis can guide surveillance for postcodes with koalas that were under-represented and inform improved methodology of future surveillance by WHV:S. The specific advice for improvements to WHV:S includes utilisation of citizen science and syndromic surveillance, website improvement, increasing community awareness and more. The limitations of this study were discussed.

Developing Population Health Surveillance Using mHealth in Low-Resource Settings: Qualitative Assessment and Pilot Evaluation.

BackgroundPopulation surveillance data are essential for understanding population needs and evaluating health programs. Governmental and nongovernmental organizations in western Myanmar did not previous have means for conducting robust, electronic population health surveillance.ObjectiveThis study involved developing mobile health (mHealth)–based population health surveillance in a rural, low-resource setting with minimal cellular infrastructure in western Myanmar. This was an early formative study in which our goal was to establish the initial feasibility of conducting mHealth population health surveillance, optimizing procedures, and building capacity for future work.MethodsWe used an iterative design process to develop mHealth-based population health surveillance focused on general demographics (eg, total census, age category, sex, births, and deaths). Interviews were conducted with international consultants (nurse midwives) and local clinicians (nurses and physicians) in Myanmar. Our analytic approach was informed by the Systems Engineering Initiative for Patient Safety work systems model to capture the multilevel user needs for developing health interventions, which was used to create a prototype data collection tool. The prototype was then pilot-tested in 33 villages to establish an initial proof of concept.ResultsWe conducted 7 interviews with 5 participants who provided feedback regarding the domains of the work system, including environmental, organizational, sociocultural, technological, informational, and task- and people-based considerations, for adapting an mHealth tool. Environmental considerations included managing limited electricity and internet service. Organizational needs involved developing agreements to work within existing government infrastructure as well as leveraging the communal nature of societies to describe the importance of surveillance data collection and gain buy-in. Linguistic diversity and lack of experience with technology were both cited as people- and technology-based aspects to inform prototype design. The use of mobile tools was also viewed as a means to improve the quality of the data collected and as a feasible option for working in settings with limited internet access. Following the prototype design based on the findings of initial interviews, the mHealth tool was piloted in 33 villages, allowing our team to collect census data from 11,945 people for an initial proof of concept. We also detected areas of potentially missing data, which will need to be further investigated and mitigated in future studies.ConclusionsPrevious studies have not focused heavily on the early stages of developing population health surveillance capacity in low- and middle-income countries. Findings related to key design considerations using a work systems lens may be informative to others developing technology-based solutions in extremely low-resource settings. Future work will involve collecting additional health-related data and further evaluating the quality of the data collected. Our team established an initial proof of concept for using an mHealth tool to collect census-related information in a low-resource, extremely rural, and low-literacy environment.

Effectiveness of using e-government platform "Absher" as a tool for noncommunicable diseases survey in Saudi Arabia 2019-2020: A cross-sectional study.

BackgroundE-government platforms provide an opportunity to use a novel data source for population health surveillance (also known as e-health). Absher is a Saudi e-government platform with 23 million authenticated users, including residents and citizens in Saudi Arabia. All Absher users were invited to participate in a web-based survey to estimate the prevalence of noncommunicable diseases and their risk factors in Saudi Arabia.ObjectiveTo assess the potential of using an e-government platform (Absher) to administer web-based health surveys.MethodsA cross-sectional, web-based health survey was administered to Absher users between April 2019 and March 2020. The survey instrument included eight items and took <5 min to complete. The respondents' data were compared to Saudi Arabia's 2016 census. Descriptive summary statistics of the prevalence of major noncommuncable diseases are presented and compared to population-based prevalence data from Saudi Arabia's World Health Survey (WHS) 2019. All analysis was conducted using Stata 13.0.ResultsOverall, the Absher health survey had a 24.6% response rate, with most respondents being male (84%), Saudi (67%), and between 30 and 44 years of age (49%). Overall, the prevalence of noncommunicable diseases and risk factors among respondents was high for overweight (35%) and obesity (30%) and low for asthma (6%). The prevalence of diabetes, dyslipidemia, and hypertension was between 15 and 17% on average, and 26.5% were smokers. In comparison to population-based World Health Survey estimates, the Absher survey overestimated obesity, diabetes, dyslipidemia, hypertension, and smoking rates, and underestimated overweight, whereas asthma prevalence was similar for Absher and the WHS.ConclusionsWith improvements in the study design, the use of e-government platforms can provide a useful and potentially low-cost data source for public health research.

Vision Care Utilization and Insurance Coverage Prior to and Following Medicaid Expansion in Ohio

Background: Increased access and utilization of vision care services has the potential to reduce preventable vision loss. The state of Ohio has been uniquely proactive when collecting vision-oriented data through population health surveys, including the Behavioral Risk Factor Surveillance System (BRFSS). These data can be used to better understand vision care utilization patterns and access to insurance. Methods: Responses to 3 items administered in the Ohio BRFSS that assess vision care utilization and insurance coverage were compared between 2 different administration periods, 2005-2011 and 2018-2019, using chi-square tests. Comparable data from 2 items assessing eye care utilization were available in 2005-2011 and 2019. Comparable data for insurance coverage were available in 2005-2011 and in 2018-2019. Responses were further stratified by population characteristics, including age, gender, household income, and education level. Results: The percentages of those reporting eye exams in the previous year were not significantly different between 2005-2011 and 2019 (chi-square, p = 0.06). In Ohio, the primary reason for not seeing a vision care provider in the past 12 months was “No reason to go” in 2005-2011 and in 2019. The second most common reason for not seeing a vision care provider in the past 12 months was “Cost/insurance,” which decreased between 2005-2011 and 2019 (chi-square, p &lt;0.001). Insurance coverage for eye care increased between 2005-2011 and 2018-2019 (chi-square, p &lt;0.001). Important differences were found within the demographic stratification. Conclusion: Population health surveillance data provide useful insight into vision care utilization and insurance coverage. Despite the increase in insurance coverage, eye care provider utilization remains relatively stable.