Surveillance system integration: reporting the results of a global multicountry survey.

OBJECTIVES: Currently, there is no comprehensive picture of the global surveillance landscape. This survey examines the current state of surveillance systems, levels of integration, barriers and opportunities for the integration of surveillance systems at the country level, and the role of national public health institutes (NPHIs). STUDY DESIGN: This was a cross-sectional survey of NPHIs. METHODS: A web-based survey questionnaire was disseminated to 110 NPHIs in 95 countries between July and August 2022. Data were descriptively analysed, stratified by World Health Organization region, World Bank Income Group, and self-reported Integrated Disease Surveillance (IDS) maturity status. RESULTS: Sixty-five NPHIs responded. Systems exist to monitor notifiable diseases and vaccination coverage, but less so for private, pharmaceutical, and food safety sectors. While Ministries of Health usually lead surveillance, in many countries, NPHIs are also involved. Most countries report having partially developed IDS. Surveillance data are frequently inaccessible to the lead public health agency and seldomly integrated into a national public health surveillance system. Common challenges to establishing IDS include information technology system issues, financial constraints, data sharing and ownership limitations, workforce capacity gaps, and data availability. CONCLUSIONS: Public health surveillance systems across the globe, although built on similar principles, are at different levels of maturity but face similar developmental challenges. Leadership, ownership and governance, supporting legal mandates and regulations, as well as adherence to mandates, and enforcement of regulations are critical components of effective surveillance. In many countries, NPHIs play a significant role in integrated disease surveillance.

The state of integrated disease surveillance globally: synthesis report of a mixed methods study.

OBJECTIVES: Disease surveillance is an essential public health function needed to prevent, detect, monitor and respond to health threats. Integrated disease surveillance (IDS) enhances its utility and has been advocated for decades by the World Health Organization. This study sought to examine the state of IDS implementation worldwide. STUDY DESIGN: The study used a concurrent mixed methods approach consisting of a systematic scoping review of the literature on IDS, a survey of International Association of National Public Health Institutes (IANPHI) members and qualitative deep dive case studies in seven countries. METHODS: This report collates, analyses and synthesises the findings from the three components. The scoping review consisted of a review of summarised evidence on IDS. Eight reviews and five primary studies were included. The cross-sectional survey was conducted of 110 IANPHI members representing ninety-five countries. Qualitative case studies were conducted in Malawi, Mozambique, Uganda, Pakistan, Canada, Sweden, and England, which involved thirty-four focus group discussions and forty-eight key informant interviews. RESULTS: In the different countries, IDS is conceptualised differently and there are differing levels of maturity of IDS functions. Although the role of National Public Health Institutes has not been well defined in the IDS, they play a significant role in IDS in many countries. Fragmentation between sectors and resourcing (human and financial) issues were common. Good governance measures such as appropriate legislative and regulatory frameworks and roles and responsibilities for IDS were often unclear. The COVID-19 pandemic has strengthened some surveillance systems, often through leveraging existing respiratory surveillance systems. In some instances, improvements were seen only for COVID-19 related data but these changes were not sustained. Evaluation of IDS was also reported to be weak. CONCLUSIONS: Integration should be driven by a clear purpose and contextualised. Political commitment, clear governance, and resourcing are needed. Technology and the establishment of technical communities of practice may help. However, the complexity and cost of integration should not be under-estimated, and further economic and impact evaluations of IDS are needed.

Designing Electronic Data Capture Systems for Sustainability in Low-Resource Settings: Viewpoint With Lessons Learned From Ethiopia and Myanmar.

Electronic data capture (EDC) is a crucial component in the design, evaluation, and sustainment of population health interventions. Low-resource settings, however, present unique challenges for developing a robust EDC system due to limited financial capital, differences in technological infrastructure, and insufficient involvement of those who understand the local context. Current literature focuses on the evaluation of health interventions using EDC but does not provide an in-depth description of the systems used or how they are developed. In this viewpoint, we present case descriptions from 2 low- and middle-income countries: Ethiopia and Myanmar. We address a gap in evidence by describing each EDC system in detail and discussing the pros and cons of different approaches. We then present common lessons learned from the 2 case descriptions as recommendations for considerations in developing and implementing EDC in low-resource settings, using a sociotechnical framework for studying health information technology in complex adaptive health care systems. Our recommendations highlight the importance of selecting hardware compatible with local infrastructure, using flexible software systems that facilitate communication across different languages and levels of literacy, and conducting iterative, participatory design with individuals with deep knowledge of local clinical and cultural norms.

The state of integrated disease surveillance in seven countries: a synthesis report.

OBJECTIVES: Integrated disease surveillance (IDS) offers the potential for better use of surveillance data to guide responses to public health threats. However, the extent of IDS implementation worldwide is unknown. This study sought to understand how IDS is operationalized, identify implementation challenges and barriers, and identify opportunities for development. STUDY DESIGN: Synthesis of qualitative studies undertaken in seven countries. METHODS: Thirty-four focus group discussions and 48 key informant interviews were undertaken in Pakistan, Mozambique, Malawi, Uganda, Sweden, Canada, and England, with data collection led by the respective national public health institutes. Data were thematically analysed using a conceptual framework that covered governance, system and structure, core functions, finance and resourcing requirements. Emerging themes were then synthesised across countries for comparisons. RESULTS: None of the countries studied had fully integrated surveillance systems. Surveillance was often fragmented, and the conceptualization of integration varied. Barriers and facilitators identified included: 1) the need for clarity of purpose to guide integration activities; 2) challenges arising from unclear or shared ownership; 3) incompatibility of existing IT systems and surveillance infrastructure; 4) workforce and skills requirements; 5) legal environment to facilitate data sharing between agencies; and 6) resourcing to drive integration. In countries dependent on external funding, the focus on single diseases limited integration and created parallel systems. CONCLUSIONS: A plurality of surveillance systems exists globally with varying levels of maturity. While development of an international framework and standards are urgently needed to guide integration efforts, these must be tailored to country contexts and guided by their overarching purpose.

Trends in 2-1-1 Calls During Public Health Emergencies, Overall and By Gender: Hurricane Irma and COVID-19 in Broward County, Florida.

Trends in 2-1-1 calls reflect evolving community needs during public health emergencies (PHEs). The study examined how changes in 2-1-1 call volume after 2 PHEs (Hurricane Irma and the coronavirus disease 2019 [COVID-19] pandemic declaration) in Broward County, Florida, varied by PHE type and whether variations differed by gender and over time. Examining 2-1-1 calls during June to December 2016, June to December 2017, and March 2019 to April 2021, this study measured changes in call volume post-PHEs using interrupted time series analysis. Hurricane Irma and the COVID-19 pandemic were associated with increases in call volume (+81 calls/d and +84 calls/d, respectively). Stratified by gender, these PHEs were associated with larger absolute increases for women (+66 and +57 calls/d vs +15 and +27 calls/d for men) but larger percent increases above their baseline for men (+143% and +174% vs +119% and +138% for women). Calls by women remained elevated longer after Hurricane Irma (5 wk vs 1 wk), but the opposite pattern was observed after the pandemic declaration (8 vs 21 wk). PHEs reduce gender differences in help-seeking around health-related social needs. Findings demonstrate the utility of 2-1-1 call data for monitoring and responding to evolving community needs in the PHE context.

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

BACKGROUND: Population 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. OBJECTIVE: This 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. METHODS: We 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. RESULTS: We 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. CONCLUSIONS: Previous 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.

Gendering Neighbourhood Marginalization Metrics in Mental Health Services Research: A Cross-Sectional Exploration of a Rural and Small Urban Population.

Background: Little is known about the extent to which socioenvironmental characteristics may influence mental health outcomes in smaller population centres or differently among women and men. This study used a gender-based analysis approach to explore individual- and neighbourhood-level sex differences in mental health service use in a context of uniquely smaller urban and rural settlements. Methods: This cross-sectional analysis leveraged multiple person-based administrative health datasets linked with geospatial datasets among the population aged 1 and over in the province of New Brunswick, Canada. We used multinomial logistic regression to examine associations between neighbourhood characteristics with risk of service contacts for mood and anxiety disorders in 2015/2016, characterizing the areal measures among all residents (gender neutral) and by males and females separately (gender specific), and controlling for age group. Results: Among the province's 707,575 eligible residents, 10.7% (females: 14.0%; males: 7.3%) used mental health services in the year of observation. In models adjusted for gender-neutral neighbourhood characteristics, service contacts were significantly more likely among persons residing in the most materially deprived areas compared with the least (OR = 1.09 [95% CI: 1.05-1.12]); when stratified by individuals' sex, the risk pattern held for females (OR = 1.13 [95% CI: 1.09-1.17]) but not males (OR = 1.00 [95% CI: 0.96-1.05]). Residence in the most female-specific materially deprived neighbourhoods was independently associated with higher risk of mental health service use among individual females (OR = 1.08 [95% CI: 1.02-1.14]) but not among males (OR = 1.02 [95% CI: 0.95-1.10]). Conclusion: These findings emphasize that research needs to better integrate sex and gender in contextual measures aiming to inform community interventions and neighbourhood designs, notably in small urban and rural settings, to reduce socioeconomic inequalities in the burden of mental disorders.

Self-Reported Speeding Among New York City Adult Drivers, 2015-2016.

Motor vehicle crashes are a leading cause of injury related deaths. Urban areas accommodate multiple road users and pedestrians account for a larger share of traffic fatalities. Speed reduction has been one component of New York City's multidisciplinary approach to reduce traffic fatalities-Vision Zero. Data from the New York City (NYC) Community Health Survey 2015-2016 were used to document population-based estimates of self-reported speeding (defined as driving ten miles per hour or more over the posted speed limit in the past 30 days) among NYC adult drivers collected soon after the adoption of Vision Zero in 2014. Self-reported speeding is common, with nearly two-thirds (63%) of adult drivers indicating they ever sped and 13% often speeding. In adjusted multivariable models, often speeding was more common among younger drivers vs. older drivers (adjusted prevalence ratio: 2.77; 95%CI 1.93-3.98), males vs. females (adjusted prevalence ratio: 1.59; 95%CI 1.35-1.87), wealthier drivers vs. poorer drivers (adjusted prevalence ratio: 1.37; 95%CI 1.10-1.70) and those reporting worse perceived social cohesion vs. better perceived social cohesion (adjusted prevalence ratio 1.51; 95%CI 1.09-2.10). Population-based health surveys facilitate exploration of a range of potential influences on health behaviors.

Prevalence estimation by joint use of big data and health survey: a demonstration study using electronic health records in New York city.

BACKGROUND: Electronic Health Records (EHR) has been increasingly used as a tool to monitor population health. However, subject-level errors in the records can yield biased estimates of health indicators. There is an urgent need for methods to estimate the prevalence of health indicators using large and real-time EHR while correcting the potential bias. METHODS: We demonstrate joint analyses of EHR and a smaller gold-standard health survey. We first adopted Mosteller's method that pools two estimators, among which one is potentially biased. It only requires knowing the prevalence estimates from two data sources and their standard errors. Then, we adopted the method of Schenker et al., which uses multiple imputations of subject-level health outcomes that are missing for the subjects in EHR. This procedure requires information to link some subjects between two sources and modeling the mechanism of misclassification in EHR as well as modeling inclusion probabilities to both sources. RESULTS: In a simulation study, both estimators yielded negligible bias even when EHR was biased. They performed as well as health survey estimator when EHR bias was large and better than health survey estimator when EHR bias was moderate. It may be challenging to model the misclassification mechanism in real data for the subject-level imputation estimator. We illustrated the methods analyzing six health indicators from 2013 to 14 NYC HANES and the 2013 NYC Macroscope, and a study that linked some subjects in both data sources. CONCLUSIONS: When a small gold-standard health survey exists, it can serve as a safeguard against potential bias in EHR through the joint analysis of the two sources.

Cervical cancer screening in the Canadian armed forces: An estimation of screening participation rates using the CF-HERO surveillance system.

BACKGROUND: Military women are faced with unique circumstances, including frequent relocation and occupational factors that may influence their participation in routine cervical cancer screening. No data on programmatic participation in cervical cancer screening in Canadian Armed Forces women has been synthesized to date. OBJECTIVE: To estimate cervical cancer screening rates in Canadian military women using clinical and administrative data sources. METHODS: Actively serving Regular Force females who were >25 years of age between January 1st 2015 and December 31st 2017 were included in the study. Scanned documents containing Papanicolaou (Pap) test results were extracted from electronic health records and further linked to demographic data sources. Screening coverage rates were calculated over the three-year study period, and results were stratified by both military command and rank. RESULTS: The study period yielded over 23,000 person-years of data. The average screening rate over this period was 77.7 %, and was highest in the 45-60 year age group. Variations in rates were observed by rank and command, with higher screening rates observed in Officers and Royal Canadian Navy staff. Overall, screening rates showed a declining trend for all groups across the study period. CONCLUSIONS: Cervical cancer screening rates amongst CAF members are currently below recommended guidelines and appear to be declining. These trends mirror those observed more widely in the general Canadian population, and may be a consequence of recent changes to guidelines for both cervical cancer and human papillomavirus (HPV) screening.

Geo-Distinctive Comorbidity Networks of Pediatric Asthma.

Most pediatric asthma cases occur in complex interdependencies, exhibiting complex manifestation of multiple symptoms. Studying asthma comorbidities can help to better understand the etiology pathway of the disease. Albeit such relations of co-expressed symptoms and their interactions have been highlighted recently, empirical investigation has not been rigorously applied to pediatric asthma cases. In this study, we use computational network modeling and analysis to reveal the links and associations between commonly co-observed diseases/conditions with asthma among children in Memphis, Tennessee. We present a novel method for geo-parsed comorbidity network analysis to show the distinctive patterns of comorbidity networks in urban and suburban areas in Memphis.

PopHR: a knowledge-based platform to support integration, analysis, and visualization of population health data.

Population health decision makers must consider complex relationships between multiple concepts measured with differential accuracy from heterogeneous data sources. Population health information systems are currently limited in their ability to integrate data and present a coherent portrait of population health. Consequentially, these systems can provide only basic support for decision makers. The Population Health Record (PopHR) is a semantic web application that automates the integration and extraction of massive amounts of heterogeneous data from multiple distributed sources (e.g., administrative data, clinical records, and survey responses) to support the measurement and monitoring of population health and health system performance for a defined population. The design of the PopHR draws on the theories of the determinants of health and evidence-based public health to harmonize and explicitly link information about a population with evidence about the epidemiology and control of chronic diseases. Organizing information in this manner and linking it explicitly to evidence is expected to improve decision making related to the planning, implementation, and evaluation of population health and health system interventions. In this paper, we describe the PopHR platform and discuss the architecture, design, key modules, and its implementation and use.

Should we enhance the commonly used deprivation index for a regional context?

BACKGROUND/OBJECTIVES: Versions of deprivation indices have been increasingly used to monitor patterns and magnitudes of inequality in health. For policy-makers, it is of interest to assess whether they need to construct regionally tailored indices, or whether the existing indices perform sufficiently in detecting inequalities in their respective jurisdiction. Few studies have explored the benefits of constructing a more tailored index for a regional context. METHODS: The study examined, in linear regression models, the proportion of variance (adjusted R2) explained in age-standardized cardiovascular disease (CVD) incidence rate ratios by an index emulating a now-widely-used multiple deprivation index created in Quebec (INSPQI), and a newly created index for Nova Scotia with additional census variables. The magnitudes of inequality were compared by the differences between mean incidences of most and least deprived groups. RESULTS: The newly created deprivation index did not explain as well as the INSPQI-like index the community-level variability in CVD incidences. The gap in mean CVD incidences between the most and least deprived groups was somewhat narrower with the new index, indicating that the new index is not necessarily more sensitive to the inequality attributed to community social disadvantages. CONCLUSIONS: Complicating the indices may not necessarily be of benefit when used for surveillance of population health inequalities. For public health practitioners and decision makers who need to make quick decisions in provisions of services and programs, a generic, well-established deprivation index such as INSPQI can serve well in a regional context.