A standardised differential privacy framework for epidemiological modeling with mobile phone data.

During the COVID-19 pandemic, the use of mobile phone data for monitoring human mobility patterns has become increasingly common, both to study the impact of travel restrictions on population movement and epidemiological modeling. Despite the importance of these data, the use of location information to guide public policy can raise issues of privacy and ethical use. Studies have shown that simple aggregation does not protect the privacy of an individual, and there are no universal standards for aggregation that guarantee anonymity. Newer methods, such as differential privacy, can provide statistically verifiable protection against identifiability but have been largely untested as inputs for compartment models used in infectious disease epidemiology. Our study examines the application of differential privacy as an anonymisation tool in epidemiological models, studying the impact of adding quantifiable statistical noise to mobile phone-based location data on the bias of ten common epidemiological metrics. We find that many epidemiological metrics are preserved and remain close to their non-private values when the true noise state is less than 20, in a count transition matrix, which corresponds to a privacy-less parameter ϵ = 0.05 per release. We show that differential privacy offers a robust approach to preserving individual privacy in mobility data while providing useful population-level insights for public health. Importantly, we have built a modular software pipeline to facilitate the replication and expansion of our framework.

A theory of change for community-initiated mental health care in the United States.

Mental health service delivery needs radical reimagination in the United States where unmet needs for care remain large and most metrics on the burden of mental health problems have worsened, despite significant numbers of mental health professionals, spending on service provision and research. The COVID-19 pandemic has exacerbated the need for mental health care. One path to a radical reimagination is "Community Initiated Care (CIC)" which equips and empowers communities to address by providing brief psychosocial interventions by people in community settings. We co-developed a theory of change (ToC) for CIC with 24 stakeholders including representatives from community-based, advocacy, philanthropic and faith-based organizations to understand how CIC could be developed and adapted for specific contexts. We present a ToC which describes ways in which the CIC initiative can promote and strengthen mental health in communities in the United States with respect to community organization and leadership; community care and inclusion and normalizing mental health. We propose 10 strategies as part of CIC and propose a way forward for implementation and evaluation. This CIC model is a local, tailored approach which can expand the role of community members to strengthen our response to mental health needs in the United States.

The Vinyasa Tool for mHealth Solutions: Supporting Human-Centered Design in Nascent Digital Health Ecosystems.

BACKGROUND: mHealth (mobile health) systems have been deployed widely in low- and middle-income countries (LMICs) for health system strengthening, requiring considerable resource allocation. However, most solutions have not achieved scale or sustainability. Poor usability and failure to address perceived needs are among the principal reasons mHealth systems fail to achieve acceptance and adoption by health care workers. A human-centered design approach to improving mHealth system use requires an exploration of users' perceptions of mHealth systems, including the environmental, user-related, and technological aspects of a system. At present, there is a dearth of contextually intelligent tools available to mHealth developers that can guide such exploration before full-scale development and deployment. OBJECTIVE: To develop a tool to aid optimization of mHealth solutions in LMICs to facilitate human-centered design and, consequently, successful adoption. METHODS: We collated findings and themes from key qualitative studies on mHealth deployment in LMICs. We then used the Informatics Stack framework by Lehmann to label, sort, and collate findings and themes into a list of questions that explore the environment, users, artifacts, information governance, and interoperability of mHealth systems deployed in LMICs. RESULTS: We developed the Vinyasa Tool to aid qualitative research about the need and usability of mHealth solutions in LMICs. The tool is a guide for focus group discussions and key informant interviews with community-based health care workers and primary care medical personnel who use or are expected to use proposed mHealth solutions. The tool consists of 71 questions organized in 11 sections that unpack and explore multiple aspects of mHealth systems from the perspectives of their users. These include the wider world and organization in which an mHealth solution is deployed; the roles, functions, workflow, and adoption behavior of a system's users; the security, privacy, and interoperability afforded by a system; and the artifacts of an information system-the data, information, knowledge, algorithms, and technology that constitute the system. The tool can be deployed in whole or in part, depending on the context of the study. CONCLUSIONS: The Vinyasa Tool is the first such comprehensive qualitative research instrument incorporating questions contextualized to the LMIC setting. We expect it to find wide application among mHealth developers, health system administrators, and researchers developing and deploying mHealth tools for use by patients, providers, and administrators. The tool is expected to guide users toward human-centered design with the goal of improving relevance, usability, and, therefore, adoption.

Geographically skewed recruitment and COVID-19 seroprevalence estimates: a cross-sectional serosurveillance study and mathematical modelling analysis.

OBJECTIVES: Convenience sampling is an imperfect but important tool for seroprevalence studies. For COVID-19, local geographic variation in cases or vaccination can confound studies that rely on the geographically skewed recruitment inherent to convenience sampling. The objectives of this study were: (1) quantifying how geographically skewed recruitment influences SARS-CoV-2 seroprevalence estimates obtained via convenience sampling and (2) developing new methods that employ Global Positioning System (GPS)-derived foot traffic data to measure and minimise bias and uncertainty due to geographically skewed recruitment. DESIGN: We used data from a local convenience-sampled seroprevalence study to map the geographic distribution of study participants' reported home locations and compared this to the geographic distribution of reported COVID-19 cases across the study catchment area. Using a numerical simulation, we quantified bias and uncertainty in SARS-CoV-2 seroprevalence estimates obtained using different geographically skewed recruitment scenarios. We employed GPS-derived foot traffic data to estimate the geographic distribution of participants for different recruitment locations and used this data to identify recruitment locations that minimise bias and uncertainty in resulting seroprevalence estimates. RESULTS: The geographic distribution of participants in convenience-sampled seroprevalence surveys can be strongly skewed towards individuals living near the study recruitment location. Uncertainty in seroprevalence estimates increased when neighbourhoods with higher disease burden or larger populations were undersampled. Failure to account for undersampling or oversampling across neighbourhoods also resulted in biased seroprevalence estimates. GPS-derived foot traffic data correlated with the geographic distribution of serosurveillance study participants. CONCLUSIONS: Local geographic variation in seropositivity is an important concern in SARS-CoV-2 serosurveillance studies that rely on geographically skewed recruitment strategies. Using GPS-derived foot traffic data to select recruitment sites and recording participants' home locations can improve study design and interpretation.

Wildfire Threat to Inpatient Health Care Facilities in California, 2022.

Objectives. To assess wildfire risks to California inpatient health care facilities in 2022. Methods. Locations of inpatient facilities and associated inpatient bed capacities were mapped in relation to California Department of Forestry and Fire Protection fire threat zones (FTZs), which combine expected fire frequency with potential fire behavior. We computed the distances of each facility to the nearest high, very high, and extreme FTZs. Results. Half (107 290 beds) of California's total inpatient capacity is within 0.87 miles of a high FTZ and 95% (203 665 beds) is within 3.7 miles of a high FTZ. Half of the total inpatient capacity is within 3.3 miles of a very high FTZ and 15.5 miles of an extreme FTZ. Conclusions. Wildfires threaten a large number of inpatient health care facilities in California. In many counties, all health care facilities may be at risk. Public Health Implications. Wildfires in California are rapid-onset disasters with short preimpact phases. Policies should address facility-level preparedness including smoke mitigation, sheltering measures, evacuation procedures, and resource allocation. Regional evacuation needs, including access to emergency medical services and patient transportation, must also be considered. (Am J Public Health. 2023;113(5):555-558. https://doi.org/10.2105/AJPH.2023.307236).

Technology, Training, and Task Shifting at the World's Largest Mass Gathering in 2025: An Opportunity for Antibiotic Stewardship in India.

The role of antibiotic overuse in intensifying selection pressures and contributing to the emergence of antimicrobial resistance is well established. The Kumbh Mela, a religious festival that occurs in 4 Indian cities of spiritual significance, is the world's largest mass gathering, attracting over 80 million pilgrims in 2013. Digital syndromic surveillance from the 2013 and 2015 Melas demonstrated a consistent pattern of antibiotic overuse, with an antibiotic prescribing rate of up to 31% for all patient encounters. As preparations for the 2025 Kumbh Mela begin, task shifting, point-of-care diagnostic and digital tools, robust clinician training, and community awareness can promote the restrained and evidence-based use of antibiotics, minimizing the potential for the emergence of antimicrobial resistance at the world's largest mass gathering.

Scaling up community-delivered mental health support and care: A landscape analysis.

Introduction: The mental health crisis has caused widespread suffering and has been further exacerbated by the COVID-19 pandemic. Marginalized groups are especially affected, with many concerns rooted in social determinants of mental health. To stem this tide of suffering, consideration of approaches outside the traditional biomedical model will be necessary. Drawing from task-sharing models of mental health care that have been pioneered in low-resource settings, community-initiated care (CIC) represents a potentially promising collection of approaches. This landscape analysis seeks to identify examples of CIC that have been implemented outside of the research context, with the aim of identifying barriers and facilitators of scale up. Methods: A narrative review approach was used for this landscape analysis in which the PubMed database was searched and further supplemented with Google Scholar. Promising programs were then discussed over multiple rounds of meetings with the research team, consisting of collaborators with varied experiences in mental health. Using the selection criteria and feedback derived from group meetings, a final list of programs was identified and summarized according to common characteristics and features. Results: The initial PubMed search yielded 16 results, supplemented by review of the first 100 entries in Google Scholar. Through 5 follow-up meetings among team members, consensus was reached on a final list of 9 programs, which were grouped into three categories based on similar themes and topics: (1) approaches for the delivery of psychosocial interventions; (2) public health and integrative approaches to mental health; and (3) approaches for addressing youth mental health. Key facilitators to scale up included the importance of sustainable financing and human resources, addressing social determinants and stigma, engaging diverse stakeholders, leveraging existing health infrastructure, using sustainable training models, ensuring cultural relevance and appropriateness, and leveraging digital technologies. Discussion: This landscape analysis, though not an exhaustive summary of the literature, describes promising examples of efforts to scale up CIC outside of the research context. Going forward, it will be necessary to mobilize stakeholders at the community, health system, and government levels to effectively promote CIC.

Health Emergency and Disaster Risk Management Workforce Development Strategies: Delphi Consensus Study.

INTRODUCTION: Health workforce development is essential for achieving the goals of an effective health system, as well as establishing national Health Emergency and Disaster Risk Management (Health EDRM). STUDY OBJECTIVE: The objective of this Delphi consensus study was to identify strategic recommendations for strengthening the workforce for Health EDRM in low- and middle-income countries (LMIC) and high-income countries (HIC). METHODS: A total of 31 international experts were asked to rate the level of importance (one being strongly unimportant to seven being strongly important) for 46 statements that contain recommendations for strengthening the workforce for Health EDRM. The experts were divided into a LMIC group and an HIC group. There were three rounds of rating, and statements that did not reach consensus (SD ≥ 1.0) proceeded to the next round for further ranking. RESULTS: In total, 44 statements from the LMIC group and 34 statements from the HIC group attained consensus and achieved high mean scores for importance (higher than five out of seven). The components of the World Health Organization (WHO) Health EDRM Framework with the highest number of recommendations were "Human Resources" (n = 15), "Planning and Coordination" (n = 7), and "Community Capacities for Health EDRM" (n = 6) in the LMIC group. "Policies, Strategies, and Legislation" (n = 7) and "Human Resources" (n = 7) were the components with the most recommendations for the HIC group. CONCLUSION: The expert panel provided a comprehensive list of important and actionable strategic recommendations on workforce development for Health EDRM.

Where are People Dying in Disasters, and Where is it Being Studied? A Mapping Review of Scientific Articles on Tropical Cyclone Mortality in English and Chinese.

BACKGROUND: Tropical cyclones are a recurrent, lethal hazard. Climate change, demographic, and development trends contribute to increasing hazards and vulnerability. This mapping review of articles on tropical cyclone mortality assesses geographic publication patterns, research gaps, and priorities for investigation to inform evidence-based risk reduction. METHODS: A mapping review of published scientific articles on tropical cyclone-related mortality indexed in PubMed and EMBASE (English) and SINOMED and CNKI (Chinese), focusing on research approach, location, and storm information, was conducted. Results were compared with data on historical tropical cyclone disasters. FINDINGS: A total of 150 articles were included, 116 in English and 34 in Chinese. Nine cyclones accounted for 61% of specific event analyses. The United States (US) reported 0.76% of fatalities but was studied in 51% of articles, 96% in English and four percent in Chinese. Asian nations reported 90.4% of fatalities but were studied in 39% of articles, 50% in English and 50% in Chinese. Within the US, New York, New Jersey, and Pennsylvania experienced 4.59% of US tropical cyclones but were studied in 24% of US articles. Of the 12 articles where data were collected beyond six months from impact, 11 focused on storms in the US. Climate change was mentioned in eight percent of article abstracts. INTERPRETATION: Regions that have historically experienced high mortality from tropical cyclones have not been studied as extensively as some regions with lower mortality impacts. Long-term mortality and the implications of climate change have not been extensively studied nor discussed in most settings. Research in highly impacted settings should be prioritized.

Applying Human-Centered Design Principles to Digital Syndromic Surveillance at a Mass Gathering in India: Viewpoint.

In the wake of the COVID-19 pandemic, digital health tools have been deployed by governments around the world to advance clinical and population health objectives. Few interventions have been successful or have achieved sustainability or scale. In India, government agencies are proposing sweeping changes to India's digital health architecture. Underpinning these initiatives is the assumption that mobile health solutions will find near universal acceptance and uptake, though the observed reticence of clinicians to use electronic health records suggests otherwise. In this practice article, we describe our experience with implementing a digital surveillance tool at a large mass gathering, attended by nearly 30 million people. Deployed with limited resources and in a dynamic chaotic setting, the adherence to human-centered design principles resulted in near universal adoption and high end-user satisfaction. Through this use case, we share generalizable lessons in the importance of contextual relevance, stakeholder participation, customizability, and rapid iteration, while designing digital health tools for individuals or populations.

All-cause excess mortality across 90 municipalities in Gujarat, India, during the COVID-19 pandemic (March 2020-April 2021).

Official COVID-19 mortality statistics are strongly influenced by local diagnostic capacity, strength of the healthcare and vital registration systems, and death certification criteria and capacity, often resulting in significant undercounting of COVID-19 attributable deaths. Excess mortality, which is defined as the increase in observed death counts compared to a baseline expectation, provides an alternate measure of the mortality shock-both direct and indirect-of the COVID-19 pandemic. Here, we use data from civil death registers from a convenience sample of 90 (of 162) municipalities across the state of Gujarat, India, to estimate the impact of the COVID-19 pandemic on all-cause mortality. Using a model fit to weekly data from January 2019 to February 2020, we estimated excess mortality over the course of the pandemic from March 2020 to April 2021. During this period, the official government data reported 10,098 deaths attributable to COVID-19 for the entire state of Gujarat. We estimated 21,300 [95% CI: 20, 700, 22, 000] excess deaths across these 90 municipalities in this period, representing a 44% [95% CI: 43%, 45%] increase over the expected baseline. The sharpest increase in deaths in our sample was observed in late April 2021, with an estimated 678% [95% CI: 649%, 707%] increase in mortality from expected counts. The 40 to 65 age group experienced the highest increase in mortality relative to the other age groups. We found substantial increases in mortality for males and females. Our excess mortality estimate for these 90 municipalities, representing approximately at least 8% of the population, based on the 2011 census, exceeds the official COVID-19 death count for the entire state of Gujarat, even before the delta wave of the pandemic in India peaked in May 2021. Prior studies have concluded that true pandemic-related mortality in India greatly exceeds official counts. This study, using data directly from the first point of official death registration data recording, provides incontrovertible evidence of the high excess mortality in Gujarat from March 2020 to April 2021.

Who's at Risk in a Changing Climate? Mapping Electricity-Dependent Patient Populations in a Coastal City.

BACKGROUND: Climate change is causing increasingly frequent extreme weather events. This pilot study demonstrates a GIS-based approach for assessing risk to electricity-dependent patients of a coastal academic medical center during future hurricanes.  Methods: A single-center retrospective chart review was conducted and the spatial distribution of patients with prescriptions for nebulized medications was mapped. Census blocks at risk of flooding in future hurricanes were identified; summary statistics describing proportion of patients at risk are reported.  Results: Out of a local population of 2,101 patients with prescriptions for nebulized medications in the preceding year, 521 (24.8%) were found to live in a hurricane flood zone.  Conclusions: Healthcare systems can assess risk to climate-vulnerable patient populations using publicly available data in combination with hospital medical records. The approach described here could be applied to a variety of environmental hazards and can inform institutional and individual disaster preparedness efforts.

Climate Change and Health in New England: A Review of Training and Policy Initiatives at Health Education Institutions and Professional Societies.

BACKGROUND: There has been increasing interest in climate change among healthcare professionals, but it is unclear to what extent resources on this topic are available to students and clinicians in New England. METHODS: Structured review of publicly available information regarding climate change and health activity at schools of medicine, public health, and physician assistant studies and in state medical and physician assistant societies in New England. RESULTS: Of 39 programs reviewed, 18 (46%) had at least one climate-related initiative. Six universities accounted for 87% of climate change and health initiatives in the region. Three out of 12 state professional associations had committees or position statements addressing climate change. CONCLUSION: There is substantial activity related to climate change and health in New England, but it is concentrated in a small number of locations. Opportunities exist to improve access to education on this topic and increase involvement of health professional associations.

Driving digital transformation of comprehensive primary health services at scale in India: an enterprise architecture framework.

In its commitment towards Sustainable Development Goals, India envisages comprehensive primary health services as a key pillar in achieving universal health coverage. Embedded in siloed vertical programmes, their lack of interoperability and standardisation limits sustainability and hence their benefits have not been realised yet. We propose an enterprise architecture framework that overcomes these challenges and outline a robust futuristic digital health infrastructure for delivery of efficient and effective comprehensive primary healthcare. Core principles of an enterprise platform architecture covering four platform levers to facilitate seamless service delivery, monitor programmatic performance and facilitate research in the context of primary healthcare are listed. A federated architecture supports the custom needs of states and health programmes through standardisation and decentralisation techniques. Interoperability design principles enable integration between disparate information technology systems to ensure continuum of care across referral pathways. A responsive data architecture meets high volume and quality requirements of data accessibility in compliance with regulatory requirements. Security and privacy by design underscore the importance of building trust through role-based access, strong user authentication mechanisms, robust data management practices and consent. The proposed framework will empower programme managers with a ready reference toolkit for designing, implementing and evaluating primary care platforms for large-scale deployment. In the context of health and wellness centres, building a responsive, resilient and reliable enterprise architecture would be a fundamental path towards strengthening health systems leveraging digital health interventions. An enterprise architecture for primary care is the foundational building block for an efficient national digital health ecosystem. As citizens take ownership of their health, futuristic digital infrastructure at the primary care level will determine the health-seeking behaviour and utilisation trajectory of the nation.

Rebooting consent in the digital age: a governance framework for health data exchange.

In August 2020, India announced its vision for the National Digital Health Mission (NDHM), a federated national digital health exchange where digitised data generated by healthcare providers will be exported via application programme interfaces to the patient's electronic personal health record. The NDHM architecture is initially expected to be a claims platform for the national health insurance programme 'Ayushman Bharat' that serves 500 million people. Such large-scale digitisation and mobility of health data will have significant ramifications on care delivery, population health planning, as well as on the rights and privacy of individuals. Traditional mechanisms that seek to protect individual autonomy through patient consent will be inadequate in a digitised ecosystem where processed data can travel near instantaneously across various nodes in the system and be combined, aggregated, or even re-identified.In this paper we explore the limitations of 'informed' consent that is sought either when data are collected or when they are ported across the system. We examine the merits and limitations of proposed alternatives like the fiduciary framework that imposes accountability on those that use the data; privacy by design principles that rely on technological safeguards against abuse; or regulations. Our recommendations combine complementary approaches in light of the evolving jurisprudence in India and provide a generalisable framework for health data exchange that balances individual rights with advances in data science.